Comparative evaluation of profits realized by Florida pharmacies through medicaid prescription dispensing and private-pa...

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Title:
Comparative evaluation of profits realized by Florida pharmacies through medicaid prescription dispensing and private-pay prescription dispensing
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Das, Sujit, 1945-
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Fees, Pharmaceutical -- Florida   ( mesh )
Medicaid   ( mesh )
Insurance, Pharmaceutical Services -- Florida   ( mesh )
Arzneimittelmarkt / Gesundheitsökonomik / USA
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Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 1986.
Bibliography:
Includes bibliographical references (leaves 154-157).
Statement of Responsibility:
by Sujit Das.
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Typescript.
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Vita.

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A COMPARATIVE EVALUATION OF PROFITS REALIZED BY
FLORIDA PHARMACIES THROUGH MEDICAID PRESCRIPTION DISPENSING
AND PRIVATE-PAY PRESCRIPTION DISPENSING






BY






SUJIT DAS


A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN
PARTIAL FULFILLMENT OF THE REQUIREMENTS
FOR THE DEGREE OF DOCTOR OF PHILOSOPHY


UNIVERSITY OF FLORIDA


1986



























To my wife, Blossom,

my father, and

to the memory of my mother.














ACKNOWLEDGMENTS


I sincerely appreciate the guidance, help, and encouragement I

have received from Dr. William C. McCormick during my graduate studies

at the University of Florida. His knowledge and expertise in pharmacy

administration were invaluable in shaping my professional skills. I

am especially grateful for his skillful direction of this research.

To Dr. Richard A. Angorn, mentor and friend, I express my sincere

thanks. I wish to especially acknowledge his sincere advice during

periods when I needed them most.

My sincere thanks and gratitude are extended to Dr. Carole L.

Kimberlin, whose expertise in research methodology has shaped my

research skills.

I am grateful to Dr. Wes Hutchinson, for his invaluable

contribution in designing this research.

I wish to thank Dr. Howard J. Eng for his friendly advice and

help.

Thanks are due to Dr. Donna Berardo, for her friendship and

advice.

I appreciate the efforts of Cindy Zimmerman, for assistance in

preparing this document.

Special thanks are due to Mr. Jerry Wells for having allowed me

to use the state Medicaid data base to perform this study.









Last, but not least, I wish to place on record the invaluable

encouragement I received at all stages of my graduate studies from my

loving wife, Blossom. I appreciate her patience and her faith in me.














TABLE OF CONTENTS


Page
ACKNOWLEDGMENTS ...................................................i i i

ABSTRACT ......................................................... vii i

CHAPTERS

I THE PROBLEM ............................................... 1

Introduction ............................ ...... ............ 1
Statement of the Problem ................................. 2
Significance of the Problem ...............................3
Potential Contributions of the Study ......................4

II REVIEW OF LITERATURE ..................................... ..6

Comparative Studies ........................................ 6
New York Study .......................................6
Iowa Study ........................................... 8
Ohio Study ........................................... 8
Michigan Study ..................................... 9
Indiana Study .......................................10
Texas Study ......................................... 11
American Pharmaceutical Association Studies ......... 12
An Alternative Approach to Evaluate Cost Shifting ........ 15
The Indiana Study ...................................15
The National Study ..................................18
The Effect of Federal Maximum Allowable Cost Program .....20
The Prescription--Its Pricing Components .................21
Variables Affecting Dispensing Costs .....................23
Prescription Volume .................................23
Type of Pharmacy .................................... 24
Type of Ownership ...................................24
Geographic Location .................................25
Pharmacy Location ...................................25
Age of the Pharmacy .................................25
Medicaid Prescription Volume ........................ 26
Total Third Party Prescriptions Dispensed ...........26
Prescriptions Dispensed per Pharmacist ..............26
Manager's Salary .................................... 27
Costs of Goods Sold per Prescription ................ 27
Services Offered ....................................27
Predicting Dispensing Cost--A Regression Model ......28









Summary of Literature Review .............................30
Theoretical Framework ....................................30

III METHODOLOGY .............................................. 33

Research Design .......................................... 33
Research Variables .... ......... ... ...... ....................34
Dependent Variables .................................36
Independent Variables ............................... 36
Pharmacy Characteristics ............................38
Accounting Models ....................................... 39
Prescription Department Profit ......................41
Total Pharmacy Profit ............................... 41
Front-End Profits ................................... 42
Research Hypotheses ......................................43
Data Source .............................................. 45
Procedure ................................................ 47
Prescription Audit ....................................... 48
Methodological Assumptions ...............................49
Limitations .............................................. 49
Summary .................................................. 50

IV RESULTS ........................... ......... .............. 52

Description of Sample Pharmacies ......................... 53
Florida Pharmacy Survey Findings ....................53
Results From Data Analysis ..........................54
Descriptive Statistics of Other Independent
Variables ......................................... 64
Descriptive Statistics of Dependent Variables ....... 69
Research Hypotheses ............... ...................... 78
Usual and Customary Versus Medicaid Reimbursement
Rate .............................................. 78
Price Comparisons for Specific Drug Categories ......82
Net Profit Comparisons ..............................85
Effect of Pharmacy Characteristics on Dependent
Variables .............................................. 87

V SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS ................97

Summary .................................................. 97
Conclusions and Recommendations .......................... 98
Medicaid Prescription Volume ........................ 98
Differences Between Private-Pay and Medicaid
Prescriptions ..................................... 98
Differences Between Private-Pay and Medicaid
Prescriptions by Pharmacy Type ....................99
Price Comparisons for Specific Drug Categories ......99
Net Profit Comparisons .............................100
Other Comments ................... .......... ........ 101
Future Research Questions ..........................102









APPENDICES

A COST OF DISPENSING PROCEDURE ............................104

B LIST OF DRUGS INCLUDED IN PRESCRIPTION AUDIT ............107

C THE MAIL SURVEY QUESTIONNAIRE OF THE FLORIDA PHARMACY
SURVEY 1985 .............................................110

D MEAN DRUG PRICES PER UNIT FOR ALL PHARMACIES COMBINED
AND BY PHARMACY TYPE .................................... 114

E PAIRED 't' TEST FOR INDIVIDUAL DRUG CATEGORIES
FOR ALL PHARMACIES COMBINED AND BY PHARMACY TYPE ........123

F CORRELATION MATRIX OF ALL RELEVANT INDEPENDENT
VARIABLES FOR ALL PHARMACIES COMBINED AND BY
TYPE OF PHARMACY ........................................ 131

REFERENCES ..... ............................................. ....... 154

BIOGRAPHICAL SKETCH ............................................. .. 158














Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

A COMPARATIVE EVALUATION OF PROFITS REALIZED BY
FLORIDA PHARMACIES THROUGH MEDICAID PRESCRIPTION DISPENSING
AND PRIVATE-PAY PRESCRIPTION DISPENSING

BY

SUJIT DAS

August, 1986


Chairman: William C. McCormick
Major Department: Pharmacy


A study was performed to examine the operating profits realized

from Medicaid prescriptions with those from private-pay prescriptions

in a sample of Florida pharmacies. It also compared the net profit

percentages from prescription and nonprescription activities. It was

a retrospective study utilizing secondary data from the Florida

Department of Health and Rehabilitative Services.

The sample consisted of 369 pharmacies, of which 252 were chains

and 117 were independents. A mail questionnaire survey was used for

data collection.

Independent pharmacies were found to dispense a higher proportion

of Medicaid prescriptions when compared to chains. Overall, the

profits realized from private-pay prescriptions were found to be

higher than those from Medicaid prescriptions. When comparing the per

unit prices for fast-moving drugs, it was found that the price


viii









reimbursed by Medicaid was higher than that charged to private-paying

patients. However, when the per unit prices were broken down by

pharmacy type, for independent pharmacies the Medicaid reimbursement

amount was lower than the price charged to private-paying patients.

It was found that the "front-end" net profit percent was higher than

the prescription department net profit percent.














CHAPTER I
THE PROBLEM



Introduction

With the enactment of Title XIX of the Social Security Act

(Medicaid) in 1965, the federal government entered the arena of

outpatient drug coverage. In 1967, the federal government announced

that the only acceptable form of reimbursement would be a fixed

professional fee (Gagnon, 1980). Subsequently, in 1975 a new Medicaid

regulation, Part 19, was implemented which dealt with reimbursement

for drugs. This regulation required state agencies to conduct

periodic surveys to determine costs of dispensing drugs. The

Department of Health, Education, and Welfare (now Health and Human

Services) also advised, "in determining fees, states should review

data obtained through these surveys as well as other information to

assure that established fees are equitable" (Gagnon, 1980, p. 35). In

the state of Florida such a survey was last conducted in 1984 in order

to assess Medicaid reimbursement rates for prescription drugs.

Studies have shown that Medicaid reimbursements for prescription

drugs have been lower than the prices normally charged for private-pay

patients. Moreover, Medicaid reimbursements in most states are fixed

amounts; this ignores the type of pharmacy (e.g., independents or

chains) providing the services and the differences in operating

costs. Thus it has been claimed that Medicaid reimbursements for









prescription drugs are inequitable when compared to private-pay

prescriptions (Brody, 1980; Gosselin & Carter, 1978; Seicker, 1981,

1983).

The inadequate returns from Medicaid prescriptions have forced

pharmacists to shift costs to private-pay patients (Gosselin & Carter,

1978). Pharmacists in general have been voicing their opinions

concerning the program and demanding fair and equitable returns. Some

have refused to participate in the program; others have subsidized the

program by increasing their charges for private-pay (or usual and

customary) prescriptions, and still others have suffered economic

losses (McCormick & Morse, 1980).

This study was designed to evaluate the profitability

attributable to participation in the Florida Medicaid Drug Program,

and compare this with profitability realized from dispensing private-

pay prescriptions.



Statement of the Problem

This study was designed primarily to assess the extent to which

Medicaid reimbursements cover actual operating costs and to what

extent profits are realized from participation in the Medicaid Drug

Program. A second objective was to evaluate the profit realized

through private-pay prescription dispensing. A third objective was to

compare differences in the net operating profits realized through

Medicaid dispensing and private-pay dispensing.









Through the performance of the above mentioned objectives,

preliminary conclusions could be drawn as to whether any cost-shifting

was taking place in the State of Florida.

Another objective of this study was to go a step further and look

at individual drug categories. This entails comparing the usual and

customary prices charged on a per unit basis (e.g., per

tablet/capsule/milliliter) with the allowable Medicaid reimbursement

amount for each of the selected drug categories.

The final objective of this study was to compare the

profitability of the prescription department with the remainder or the

"front-end" of the pharmacy. Finally the study will report the

differences in dispensing costs based on different pharmacy

characteristics.



Significance of the Problem

The importance of this study rests with the fact that this is the

first large scale study to be performed in the state of Florida to

evaluate the differences between usual and customary prescription

prices versus Medicaid reimbursement rates. Pharmacy literature

abounds with studies which have shown that Medicaid and other third

party programs do not reimburse amounts similar to what is charged to

private-pay customers. Medicaid drug programs are state administered,

and there are variations in the amount of reimbursements paid from one

state to another. Therefore, the results of this study are necessary

in order to indicate the significance of the problem in the state of

Florida.












Potential Contributions of the Study

The study will make a contribution towards the continuing process

of determining reasonable and justifiable amounts of reimbursements

for Medicaid prescriptions. It will be an improvement over the 1984

Florida Department of Health and Rehabilitative Services survey of

Florida pharmacies in that the actual costs of dispensing will be

compared with the reimbursements received and the effect this has on

profitability.

In view of the continued growth rate of Medicaid prescriptions as

a proportion of total prescriptions filled, Florida pharmacists will

be able to objectively assess the economic and financial effects of

filling Medicaid prescriptions. Moreover, they will have a much

stronger argument in convincing the authorities to reimburse fair and

equitable returns on their investments.

The study will also indicate whether Medicaid participation has

resulted in cost-shifting, and thereby increased costs for private-pay

patients. This has implications in answering questions of whether

private-pay patients are subsidizing Medicaid programs through higher

costs associated with prescription drugs.

This study will examine how prices differ on a few specific fast-

moving drug categories.

The results of this study will also indicate to practitioners and

providers whether a variable fee reimbursement policy should be

implemented in the state of Florida.










Furthermore, this study will indicate whether pharmacists are

justified in their complaints that 'Iedicaid reimbursements are

inequitable and unreasonable.

Another aspect of the study will indicate to Florida pharmacists

the differences between profitability levels between the prescription

department and the front-end of the pharmacy.

Finally, this study will show how dispensing costs vary depending

on the type and volume of prescriptions handled by Florida

pharmacies. This would serve as a useful tool for long-term strategic

planning by pharmacy managers and further the knowledge base of the

profession of pharmacy.














CHAPTER II
REVIEW OF LITERATURE


This review of related literature is divided into two broad

areas--studies involving comparison of third party versus usual and

customary prescription prices, and cost of dispensing studies which

examine the effects of different pharmacy characteristics on operating

expenses. This chapter will first describe relevant studies on

prescription price comparisons on a state by state basis, followed by

the effect of various pharmacy characteristics on dispensing costs.

Finally, a theoretical model involving the prescription drug

environment and the relationships of different variables will be

described.



Comparative Studies

New York Study

One of the first studies to be conducted on Medicaid

reimbursements for prescription drugs was by Professor Rinaldo DeNuzzo

of the Albany College of Pharmacy in 1976. This survey of Medicaid

reimbursements for prescription drugs in New York State indicated that

Medicaid was underpaying $0.14 per prescription when compared to

private-pay prescriptions, and to remain in business the pharmacies

were forced to add $0.02 to each private-paying prescription. The

failure of Medicaid to reimburse costs resulted in indirect increases










in private-pay prescriptions (Gosselin & Carter, 1978). Gosselin and

Carter (1978) have applied the DeNuzzo study to 1976 New York Medicaid

expenditures and have shown that Medicaid underpaid by at least $2.9

million in 1976, of which $2.5 million was passed on to private-pay

patients, and the pharmacies still absorbed a loss of at least

$442,000. Their assessment indicated that Medicaid rates for New York

did not keep up with inflation, resulting in a fee of $2.60 in July

1978. This fell below an inflation adjusted fee of $2.76, which

should have been effective in 1975 (Gosselin & Carter, 1978). A

similar study conducted in Illinois showed that for fees to be

equitable, reimbursements should vary based on the type of store and

services offered (Gosselin & Carter, 1978).

Extrapolating the New York figures, Gosselin and Carter (1978)

estimated an underpayment of $26.2 million on a nationwide basis, of

which $22.2 million had been passed onto private-pay patients and $4

million absorbed by pharmacies as losses. As a result of such

activities, the authors indicated that net profit per store had

started declining in 1965 when Medicaid was first instituted, whereas

it had been slowly increasing from 1960 to 1965. The authors argued

that Medicaid reimbursements should be based on usual and customary

charges, rather than fixed fees which are far below private-pay

prescriptions. They also stated that one of the effects of Medicaid

reimbursements was a decrease in the number of retail pharmacies in

New York City from 6,000 in 1965 to 4,300 in 1975.









Iowa Study

In a study conducted in Scott County, Iowa, in 1979, County

Pharmaceutical Association members were able to convince a private

third party payor to increase its professional fee component from

$2.15 to $2.50 per prescription. This was based on surveys of all

pharmacies in the county, whereby average prescription fees charged

were found to be $3.01 (Naber, 1979).

Ohio Study

A dispensing fee determination study of independent pharmacies

located in central Ohio was performed by Pathak (1982) in 1980.

Operating cost data were collected from 39 independent pharmacies by

trained data collectors. The average dispensing fee which included a

minimal profit of 4.3% was found to be $3.70, and the average

prescription price was $7.79. During this period, the Medicaid

dispensing fee paid by the State of Ohio was $2.60. Therefore, the

author concluded that every Medicaid prescription filled by an

independent pharmacy there was a net $1.10 ($3.70-$2.60) per

prescription loss to that pharmacy. Extrapolating the results of this

study, Pathak (1982) estimated the losses incurred by all independent

pharmacies located in central Ohio from Medicaid participation to be

$438,738 in 1980. He further concluded that private-pay customers

were providing a subsidy of $0.41 per prescription to all third party

programs including Medicaid. This results in approximately 5.3%

higher prices paid by private-pay patients because of inadequate

reimbursement for cost of filling a prescription to independent

pharmacies by third party prescription programs.









Extending the results of this study to all independent pharmacies

in Ohio, Pathak (1982) concluded an average annual loss of $8,133 per

pharmacy due to third party participation.

The major drawback of this study is the small sample size and the

extent to which the results have been extrapolated. Furthermore, this

study only looks at the dispensing cost component and ignores the

prescription ingredient cost.

Michigan Study

In 1981, a study was performed by McKercher and Hawkins .(1982) on

behalf of the Michigan Pharmacists Association to compare usual and

customary and third party prescription prices. The population

consisted of all community pharmacies licensed in the state of

Michigan. A 25% random sample was selected to receive mail survey

questionnaires. The final sample consisted of 109 usable responses.

Forty-two of these pharmacies were audited in order to verify

prescription prices as reported in the survey instrument.

The final analysis was performed on 20% of the prescription

sample numbering 1,399 which were all dispensed on 7/1/81 by 86

pharmacies. This sample consisted of prescriptions dispensed by both

chains and independent pharmacies.

The research analysis consisted of comparing the actual usual and

customary prices charged by these pharmacies with the actual prices

which would have been paid by Medicaid and Michigan Blue Cross Blue

Shield (MBCBS) drug program. The results show that on the average

Medicaid and MBCBS pay $1.12 and $0.47, respectively, less per

prescription when compared to cash-paying prescriptions. Furthermore,










this study provided evidence suggesting that private-pay customers pay

subsidies of $0.28 per prescription due to MBCBS program and $0.80 per

prescription due to the Medicaid program. The researchers also showed

that cash-paying consumers were paying $0.21 more than the average

profit on each prescription. On extrapolation, the researchers

concluded that for the whole state of Michigan, the documented $3.17

average gross profit per prescription was sustained by a $6.3 million

cost shift to private-paying customers. They also stated that $21.78

million was absorbed by Michigan pharmacies which represented the

difference between adequate gross profits and actual gross profit.

Indiana Study

A study of Indiana pharmacies was performed by Jacobs (1983)

during May 1981 to evaluate the effect of the Medicaid drug program.

Data on 200 non-MAC (maximum allowable cost as determined by the

government) prescriptions were collected from each of 80 pharmacies

located throughout Indiana by undergraduate pharmacy students who had

been trained as data collectors. A total of 16,000 prescriptions was

used in this study. The research consisted of comparing the usual and

customary prices charged for these prescriptions and comparing them

with probable Medicaid reimbursements for the same prescriptions.

The results of this study indicate that, depending upon the

pricing policy used by the pharmacy, the average reimbursement

reduction due to the Indiana Medicaid drug program varied from $0.32

to $0.83 for all pharmacies. This reduction ranged from $0.42 to

$0.98 and $0.24 to $0.68 for independent and chain pharmacies,

respectively. The average retail prescription price for all









pharmacies was $7.56; and $7.29 and $7.84 respectively for chains and

independents.

Texas Study

Under contract with the Texas Department of Human Services,

Kreling and Kirk (1985) conducted a study of Texas pharmacies to

evaluate different marketplace characteristics of usual and customary

prescriptions. On the basis of Jacobs's (1981) study which showed

that prescription volume had the greatest impact on cost of

dispensing, the authors selected pharmacies by a stratified random

sampling technique based on the number of Medicaid claims submitted by

Texas pharmacies during 1982. Pharmacies with less than 2,400

Medicaid claims were excluded. Data on 200 usual and customary

prescriptions per pharmacy, dispensed prior to January 6, 1984, were

collected from a sample of 92 pharmacies. After elimination of any

over-the-counter products and those prescriptions with a negative

gross margin of less than -$1.00, a total of 17,623 prescriptions was

used for analysis. Prescription prices ranged from $8.80 to $17.54,

with an overall mean of $12.14. The gross margin ranged from $3.21 to

$8.23, with an overall mean of $5.38.

In the next phase of study, information regarding the cost of

dispensing was obtained directly from the Texas Department of Human

Resources. Cost of dispensing data was available for 78 out of the 92

sample pharmacies. The cost of dispensing for the 78 pharmacies

ranged from $1.46 to $5.68 with an overall mean of $3.37, a standard

deviation of $1.08 and a median of $3.25.









The average net profit per prescription was found to be $2.03

(difference between average gross margin of $5.40 and average cost of

dispensing of $3.37). The average profits per prescription ranged

from a loss of $0.74 to a profit of $4.50, with a standard deviation

of $1.12. The researchers found that the average prescription price

differences between pharmacies were due to the differences in average

prescription sizes rather than prescription volume or location of the

pharmacies. Overall the average prescription price per dose was very

stable between pharmacy classifications and ranged between $0.292 and

$0.311.

Finally, the study confirmed that differences existed in costs of

dispensing based on prescription volume and location (urban and

rural).

The major drawback of this study was the small sample size of 78

pharmacies. Therefore, the extent to which the findings can be

generalized is limited.

American Pharmaceutical Association Studies

The major study conducted on a national basis to evaluate direct

administrative costs associated with all third party prescriptions was

undertaken jointly by the American Pharmaceutical Association (APhA)

and the National Association of Chain Drug Stores in 1978. A pretest

was performed on 14 pharmacies to develop the measuring instrument

(Health Information Designs, Inc., 1979a). The actual study was

conducted in 39 Standard Metropolitan Statistical Areas throughout the

country, each having a population of over one million. A total of 96

pharmacies was included in the final report. The study was performed









by trained surveyors and was a time and motion observational study.

The results indicated a handling expense of $0.67 per prescription

with a standard deviation of $0.02 (Health Information Designs, Inc.,

1979b).

Included in the national sample were 20 pharmacies from Florida,

located in Tampa, of which 13 were chains and 7 were independents.

The study indicated a higher percentage (16%) of third party

prescriptions was handled by independents than by chains (9%). The

results indicated a mean expense of $0.70 per prescription, and the

range was from $0.32 to $1.14 (McCormick & Morse, 1980). One of the

major drawbacks of this study was its lack of generalizability to

include pharmacies in smaller towns.

At the recommendation of APhA Task Force on Third Party Programs,

the APhA's Pharmacy Management Institute (PMI) conducted a study in

three cities to examine professional income from different third party

payment plans. This study was performed in 1981, and eight pharmacies

in each city were randomly chosen for the study. Specifically, the

survey looked at the aggregate amount of reimbursement received from

Medicaid and from a selected third party, and compared these with fees

recovered from private-pay patients. Data were collected using 10

hypothetical and 10 actual prescriptions. The hypothetical

prescription drugs were chosen from a list of the top 200 most

frequently prescribed drugs. Results indicated that Medicaid

reimbursements were equal to self-pay professional income in 17% of

the cases for the hypothetical prescriptions, and in 25% of the actual

prescriptions. Under the private third party plan for actual










prescriptions, reimbursements were greater in 21% of cases, equal in

1%, and less in 79% of the cases. For the hypothetical prescriptions,

the compensation was greater in 37% of the cases and less in 63% of

the cases. Thus Seicker (1981) concluded that Medicaid and private

third party reimbursement income fell substantially short of that

actually earned as professional income from private-pay patients. The

major drawback of this study was that it could not be generalized for

the entire nation, since only three cities in three different states

were selected for the study.

A 2-year prospective study was conducted by the PMI from July

1980 to December 1982, in a large community pharmacy in the

Northeast. The study collected information on all Medicaid

prescriptions dispensed during this period and compared the amounts

billed, the actual amount received from Medicaid, and the prevailing

charges for similar prescriptions. The study indicated an increasing

gap between what was billed and the prevailing charges. This

difference had increased from $0.20-$0.25 in July 1980, to $0.88 and

$0.41, respectively, for amounts billed to Medicaid and received from

Medicaid in December 1982. The results also show an increase in the

total monthly amounts billed to Medicaid from $3,000 during the summer

of 1980 to $4,000 by the end of 1982, although the total number of

prescriptions handled was fairly stable during this period. This

increase was attributed to increased ingredient costs, since the

Medicaid fee had not changed during the study period. Overall,

results indicated that the pharmacy was dispensing Medicaid

prescriptions at $1.50 less than those for private-pay prescriptions,









when lost income and minimum added costs for processing were

considered (Seicker, 1983).



An Alternative Approach to Evaluate Cost Shifting

All the studies which have been discussed so far are primarily

based on the cost incurred by pharmacies to dispense prescriptions.

Most of these studies have compared the costs incurred with the amount

charged (for usual and customary) or the price reimbursed (for

Medicaid and other third parties).

An approach for looking at cost-shifting is the "all-payor" rate

system as described by Ginsburg and Sloan (1984). Under this system

all payors, regardless of the source of payment, would pay the same

rate for the same service. This approach was proposed by the authors

to look at cost-shifting in hospitals, resulting from a variety of

rate structures set by various government agencies and private third

party insurers. The methodology involves comparing the all-payor rate

for a specific service with the amount reimbursed by any given third

party carrier. If the third party reimburses an amount lower than the

all-payor rate, then the difference would be the inadequate

reimbursement amount resulting from that specific insurance plan.

The Indiana Study

Schondelmeyer and Stone (1985) utilizing the above concept have

proposed a conceptual and methodological approach for examining the

effects of third party prescription programs on community pharmacies.









The researchers proposed the concept of Single Rate Prescription

Price (SRPP) which formed the cornerstone of their study. The SRPP

for a particular prescription was defined as the price that must be

charged, if all customers were to pay the same price for that

prescription. The SRPP was calculated for any given prescription

using the following equation:


n
SRPP = [ ) (TPRR. x PTP. )] + (PPC x PPP )
P i=1 ip ip p p


where

PPC = private-pay charge for a given prescription

TPRR = third party reimbursement for the same prescription

PPP = percent of private pay prescription in a given pharmacy

PTP = percent of each third party prescription in a given
pharmacy

p = a particular prescription

i = a specific third party program

n = total number of third party programs at a given pharmacy.


Thus the SRPP for any given prescription was defined as the

weighted average of all different prices (third parties and usual and

customary).

Two other concepts defined in the study were inadequacy of a

given third party's reimbursement rate (IATPRR) and the cost shift

subsidy paid by private-pay customers (CSS). These were calculated

for a specific prescription as follows:










IATPRR = SRPP TPRR


CSS = PPC SRPP

Utilizing the above described concepts, Schondelmeyer and Stone

(1985) performed a survey of Indiana community pharmacies.

Approximately one-third of the 1,500 community pharmacists licensed in

Indiana were randomly selected to form the study sample. Survey

questionnaires were mailed to 499 pharmacies on January 9, 1984. A

usable response rate of 44% (221 of 499) was achieved. The overall

objective of this study was to assess the extent and impact of third

party-induced cost shifting on Indiana community pharmacies.

Data were collected for 10 prescription products--eight drugs

randomly selected from the top 200 most frequently prescribed drugs

and two from the top 25 generic drugs. Also demographic data and

information on the reasons for participating in third party programs

were collected.

The results of the study indicated that there were six major

third party providers in Indiana who together accounted for 30.2% of

all prescriptions. Medicaid was the largest provider accounting for

11.6% of all prescriptions. Comparing private-pay with third parties,

the study revealed that Medicaid reimbursed pharmacies at rates

significantly (p< 0.05) lower than private-pay for all 10 study

drugs, whereas for private third party carriers, lower reimbursement

rates were received for only six to eight of the products. Comparing

the SRPP for all 10 products revealed that private-pay prices were

significantly higher than the SRPP for 7 of the 10 drugs, Medicaid









reimbursement rate was lower than the SRPP for all 10 drugs, and for

other third parties it varied from five to eight products being

reimbursed at levels below the SRPP.

Results from cost shift subsidy (CSS) calculations indicated

that, for 8 of the 10 prescription products, the private-pay customers

were subsidizing third party customers. The mean CSS ranged from

-$0.08 to $1.38 with a weighted mean of $0.52. The largest CSS was

due to Medicaid (mean $1.42), followed by the Indiana Blue Cross Blue

Shield drug program (mean $1.34). The amount of CSS varied directly

with the percent of third party prescriptions dispensed by pharmacies.

Among the reasons attributed to participation in third party

programs, the most important one was the desire to serve the needs of

regular customers. Pharmacies with high third party volumes rated the

statement concerning lack of any other alternatives (to participation

in third party plans) significantly more important than other

pharmacies.

This study utilized a unique conceptual approach in order to

evaluate cost-shifting in Indiana pharmacies. The major weakness of

this study was its reliance on self-reported data without performing a

sample in-store audit check. The major criticism of the conceptual

methodology is that the SRPP ignores the costs incurred by the

pharmacies to dispense a prescription.

The National Study

The above described study was followed by a similar study

performed on a national sample by Stone and Schondelmeyer (1986). A

stratified random sample of 2,134 community pharmacies was selected










from a total of 58,700 pharmacies licensed in the United States. A 6-

page questionnaire was mailed on September 28, 1984. A usable

response rate of 27.1% (529 pharmacies) was achieved, which consisted

of 111 chain pharmacies with the remainder being independent community

pharmacies. The number of chains responding was deemed not

representative of the total population; hence they were not included

in the major analyses.

Data were collected for the same 10 prescription drug items as in

the Indiana study. The findings of this study are listed below:

1. Third parties paid 33.9% of all prescriptions filled in

independent pharmacies.

2. Six third party providers accounted for 96% of all third

party prescriptions in independent pharmacies.

3. Medicaid was the largest provider, accounting for 18.4% of

all prescriptions in independent pharmacies.

4. Independents, on the average, filled one-third more Medicaid

prescriptions than chain pharmacies.

5. Third party reimbursement rates were significantly lower than

private-pay rates for more than three-fourths of all

prescriptions.

6. Third party reimbursement rates were lower than SRPP for over

60% of all prescriptions.

7. An average CSS of $0.48 was paid by private-pay customers in

independent pharmacies.

8. CSS paid by private-pay customers was significantly higher

($0.31) in independent pharmacies when compared to chains.










9. Medicaid was the major cause for CSS, followed by Blue Cross

Blue Shield and PCS plans.

10. The amount of CSS was directly related to the percent of

third party prescriptions filled by a pharmacy.

The findings of this national study were found to be similar to

the Indiana study. The major drawback of this study was the total

reliance on self-reported survey data.



The Effect of Federal Maximum Allowable Cost Program

In 1973, the Federal Maximum Allowable Cost (MAC) program was

initiated for multi-source drug entities. The MAC program was adopted

in many states as a reimbursement device for the cost of ingredients

under Medicaid plans. In 1981, National Wholesale Druggists'

Association and Smith Kline & French Laboratories co-sponsored a study

conducted in five states to assess the impact of MAC on independent

community pharmacies (Torielli, Gagnon, & Lingle, 1982). The study

indicated that pharmacies with high volume Medicaid prescriptions (10%

or more) had only a slightly greater incentive to stock drugs at or

below MAC prices. On the average, only 54% of such pharmacies stocked

products at or below the MAC prices. Apparently, other costs, such as

inventory holding costs, weighed more heavily in the decision to stock

such drugs than did the losses from Medicaid prescriptions. Fifty-

eight percent of all responding pharmacies indicated that they filled

Medicaid prescriptions with drugs priced above the MAC limit and that

they absorbed the losses. Nine percent indicated that they refused to










fill Medicaid prescriptions when they did not have below MAC-priced

products in stock (Torielli et al., 1982).

In quantifying losses from dispensing above MAC-priced drugs,

Torielli et al. (1982) showed that, oo an average, losses of $3.56 per

prescription were incurred. Forty-seven percent of respondents stated

that they increased their prices for private-pay patients to

compensate for Medicaid losses.



The Prescription--Its Pricing Components

A prescription can be defined as "an order for medication to be

dispensed to an ultimate user" (Nielsen, 1986, p. 81). The pricing of

a prescription is comprised of three components: cost of ingredients,

cost of dispensing, and net profit (Herman & Zabloski, 1978; Pathak,

1983). This relationship is depicted in Figure 2-1. As can be seen

from the figure, the term "Dispensing Fee," which represents the Gross

Margin component, includes both the cost of dispensing and the net

profit components. For the purposes of arriving at the retail price

to be charged to the public, the two commonly used prescription

pricing methods are the percentage markup and the professional fee.


The percentage markup method can base its percentage of
markup as a percent of either the cost of medication
(markup-on-cost) or the retail price of the prescription
(markup-on-retail).1 The result is a variable fee with a
direct relationship to both the cost of medication and
prescription retail price. The professional fee
[dispensing fee] pricing method involves adding a constant
amount to the cost of medication to establish the retail
price of the prescription. (Jacobs, 1983, p. 2)


1 Even though this term is technically inaccurate, it is commonly
used in retail drug trade.















Fluctuating Market
Cost of the
Prescription Ingredient


Operating Cost
+ of Dispensing
a Prescription



Dispensing Cost
of that
Prescription


+ Profit


Usual
= and
Customary


I

Mark-up or a
Dispensing Fee
Adjusted Frequently
Based on Operating
Cost Charges


Fixed Preestablished
Cost of the
Ingredient Based
on Past Market Data
Based on Arbitrary
Cut-Off Points


Average Fixed
+ Dispensing Fee
Based on
Infrequent Survey


Usual
< and
Customary


Medicaid
= Prescription
Price


Figure 2-1.


Components of a Usual and Customary Prescription Price
and a Medicaid Prescription Price.










On the contrary, for Medicaid pricing purposes there are only two

relevant components for drug reimbursements: cost of the ingredients

and the dispensing fee. Both of these components are controlled by

the "lowest of" clause. The cost of ingredients is controlled by the

MAC/EAC (Estimated Acquisition Cost as determined by the government)

limitations, and the dispensing fee is usually controlled by a fixed

fee for the entire state (Pathak, 1983). The Medicaid pricing

equation is depicted in Figure 2-1.

Irrespective of the method of pricing (for usual and customary

prescriptions) or reimbursement (Medicaid programs), the cost of

dispensing (or dispensing fee) is influenced by a number of different

pharmacy characteristics. The effect of these factors and the

direction of these relationships will be explored in the next section.



Variables Affecting Dispensing Costs

The following variables have been found by different researchers

to influence cost of dispensing (Cady, 1975; Carroll & Gagnon, 1980;

Cotton & Rucker, 1972; Kotzan & Braucher, 1970; Kreling & Kirk, 1985;

Norwood & Gagnon, 1975; Reeder, 1985; Reeder, Fincher, Nelson, &

Sadik, 1980). These variables and their effects on dispensing costs

are described below.

Prescription Volume

Prescription volume is the total number of prescriptions (new and

refills) which a pharmacy dispenses during the course of a year. It

has been shown by various researchers (Anderson, 1976; Berki &

Hornbrook, 1971; Hammel & Holberg, 1976; Institute for Community










Pharmacy Research, 1977; Kreling & Kirk, 1985; Norwood, 1976; Reeder

et al., 1980) that an inverse relationship exists between prescription

volume and costs associated with dispensing. Thus the higher the

prescription volume, the lower will be the costs incurred to

dispense. This relationship is based on the principle of economies of

scale whereby costs decrease with increases in output, until the point

where laws of diminishing returns start taking effect. Reeder (1985)

found that this relationship holds true for up to 80,000 prescriptions

dispensed per year in a study of 54 pharmacies in South Carolina.

Type of Pharmacy

In studies involving community pharmacies, it is the norm to

classify them according to the type of pharmacy. Broadly, two such

categories are prevalent in the literature--independents and chains.

Independents are usually those operating four or fewer pharmacies and

chains are usually those operating five or more pharmacies. Studies

have shown that, in general, independent pharmacies incur higher

dispensing costs than chains (Herman & Zabloski, 1978; Kotzan &

Braucher, 1970; Norwood & Gagnon, 1975).

Type of Ownership

This is another method of classifying pharmacies based on who

owns them. Theoretically three different ownership entities are

feasible--sole proprietorships, partnerships, and corporations.

A review of literature suggests that corporations function most

efficiently among the three categories. Therefore, operating profits

are highest for corporations when compared to the other two categories

of ownership.










Geographic Location

Pharmacies have been classified in relation to their geographic

location. Many classifications abound in the literature depending on

the type of study. The one most relevant for the purposes of this

study is to classify location as either urban or rural. Urban

locations are defined for this study as those zip codes located within

Standard Metropolitan Statistical Areas (SMSA), and rural locations

include those zip codes located within non-SMSA locations. Studies

have shown that dispensing costs are higher in urban locations when

compared to rural ones (Holberg, 1975; Reeder et al., 1980; Ross,

1977).

Pharmacy Location

This variable refers to the actual setting where the pharmacy is

located. The most commonly used categories are downtown, residential,

shopping center, and medical office building (Herman & Zabloski,

1978). Research indicates that costs associated with medical office

building pharmacies (sometimes referred to as professional pharmacies)

are the highest (Elm & Hammerness, 1976; Herman & Zabloski, 1978).

Age of the Pharmacy

It has been shown by Carroll and Gagnon (1980) that net profit

per prescription was found to be related to the number of years a

pharmacy has been in existence. Years of existence is said to have an

indirect effect on costs, which in turn causes profits to vary. Thus,

the longer a pharmacy is in existence, the lower are its costs to

operate, which should result in higher net profits.










Medicaid Prescription Volume

This variable is used by some researchers to categorize

pharmacies based on either the total Medicaid prescriptions dispensed

during a year, or as a percent of all prescriptions. On one hand, the

true relationship between costs associated with increasing volumes of

Medicaid dispensing is debatable. Holberg (1975) associates higher

dispensing costs in pharmacies that account for 10% or more Medicaid

prescription sales. On the other hand, Anderson (1976) and Reeder

(1985) found negative correlations between dispensing costs and

Medicaid prescription volume. Kreling and Kirk (1985) in their Texas

study found no relationship between dispensing costs and Medicaid

volume. The general consensus among practitioners as presented in the

literature seems to indicate that Medicaid participation is associated

with higher dispensing costs.

Total Third Party Prescriptions Dispensed

This is another variable which has often been associated with

cost of dispensing studies. The variable is described in terms of the

proportion of third party prescriptions dispensed as a function of

total prescriptions. Holberg (1975) has found higher dispensing costs

in pharmacies whose third party sales contributed 10% or more of total

prescription sales.

Prescriptions Dispensed per Pharmacist

This variable is defined as the number of prescriptions a

pharmacist dispenses during the course of a normal 8-hour working

day. It has a direct effect on efficiency and, therefore, is found to

have a very high negative correlation with costs. Reeder et al.










(1980) in a study of 515 pharmacies in South Carolina reported a

correlation coefficient of -0.705 between dispensing costs and the

number of prescriptions dispensed per pharmacist.

Manager's Salary

The salary of the store manager has been shown to have some

effect on dispensing costs. Reeder et al. (1980) found this variable

to be positively correlated with dispensing costs.

Costs of Goods Sold per Prescription

The cost of the drug ingredients) component of the prescription

is found to have a direct effect on dispensing costs (Reeder et al.,

1980). The reason for this relationship is attributed to indirect

effects. Reeder et al. (1980) state that cost of goods sold may be a

surrogate for volume and efficiency. This means that the higher the

prescription volume and the more efficient a pharmacy is operating,

the lower will be its cost of goods sold per prescription. This is

due to larger quantities being purchased more efficiently through the

availability of quantity discounts and the avoidance of interest

expenses on purchase payments.

Services Offered

This variable serves as a catch-all wherein pharmacies offering

counseling, patient profiles, delivery, charge accounts, emergency

services, advertisements, computer usage, etc. could be included. It

has been reported that pharmacies offering these services incur higher

expenditures resulting in higher dispensing costs (Anderson, 1976;

Herman & Zabloski, 1978; Holberg, 1975).










Predicting Dispensing Cost--A Regression Model

All of the above variables have been found by different

researchers to have an effect on the cost of dispensing. However, it

should be noted that these variables may not be independently

responsible for variations in dispensing costs. It is highly likely

that a large amount of interaction between these variables accounts

for their effect on dispensing costs. Researchers have performed

stepwise regressions in order to isolate the most significant ones and

have reported multiple regression models. There are significant

differences between such models. The possible reason could be that

the extent of influence of these variables on dispensing costs varies

from state to state or even by locations within a state.

One such regression model to predict cost of dispensing as

reported by Reeder et al. (1980) is as follows:


DC = -0.00003X1 + 0.26891X2 = O.00001X3 + 0.09226X4

+ 0.00001X5 + 2.26881


Multiple R2 = 0.813 F = 67.18 (1,172)

where

X1 = Prescriptions dispensed per pharmacist

X2 = Cost of goods sold per prescription

X3 = Total number of prescriptions dispensed

X4 = Population size of pharmacy location

X5 = Manager's salary

DC = Dispensing cost per prescription.











In 1968 the Department of Health and Human Services Task Force on

Prescription Drugs proposed seven tenets for an ideal reimbursement

system. The more important of these were (a) dispensers should be

rewarded according to their economic costs based on an efficient use

of resources; and (b) part of the costs of drugs should not be shifted

from beneficiaries to nonbeneficiaries (Gagnon, 1980). However, all

of the above cited studies indicate that the opposite phenomenon is

occurring.

Finally, some states, namely Nebraska, Kansas, Texas, Louisiana,

and North Carolina, have been cited as having well administered

Medicaid pharmacy programs. These five states utilize a variable fee

reimbursement schedule, depending on the type of pharmacy. In

general, the fees for prescription services are at least seen as

adequate by dispensers (Brody, 1980).

The fixed fee method of reimbursement has become the dominant

form of prescription reimbursements to pharmacies under government

programs (Gagnon, 1980; Rucker, 1971). The state of Florida utilizes

a fixed fee schedule for payment of professional fees and the Average

Wholesale Prices (AWP) as reimbursement for the cost of ingredients.

The average amount per claim is about $8.03, the current dispensing

fee is $3.33, and the total drug payout in 1982 was $49 million

(Glasser, 1982). The total budget deficit in 1981 for Medicaid

prescription drugs was $5.2 million ("State Medicaid," 1981).










Summary of Literature Review

A review of related literature has revealed that there are

substantial differences between Medicaid reimbursement levels and

private-pay prescription incomes. Studies have shown that incentives

for cost-shifting were created in order for pharmacies to recover lost

income incurred through Medicaid program participation. It is also

suggested that part of the lost income is being absorbed by the

pharmacies. The MAC study by Torielli et al. (1982) has shown that a

majority of the pharmacies are not recovering the cost of ingredients

through Medicaid reimbursements. Only one study has looked into the

actual direct administrative costs incurred to dispense and process

all third party prescriptions.

In summary, most of the studies have compared Medicaid and other

third party reimbursements with private-pay prescriptions. Judgments

based on these studies have labeled Medicaid drug reimbursements as

inequitable when compared with usual and customary charges.



Theoretical Framework

The theoretical framework consists of depicting the prescription

drug environment and showing the effects of different pharmacy related

variables on operating costs. The framework is shown in Figure 2-2.

The prescription drug environment was adapted from Paul and

McEvilla (1980). The environment consists of various actors who

influence the drug delivery system, including third party programs.

Specifically, the diagram has been adapted to depict the Florida

Medicaid drug program which is under the auspices of the Florida
























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0
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0
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Department of Health and Rehabilitative Services (DHRS). In the

figure, the plan's sponsor is shown as the DHRS, which currently

reimburses pharmacies for the cost of ingredients using the MAC or EAC

and a fixed dispensing fee of $3.33. All the actors, such as the

physician, manufacturers, plan sponsor, government regulators, etc.,

affect the relationship between the pharmacist and the patient and

vice versa.

Superimposed on the prescription drug environment are the

variables which directly affect the operating costs (or cost of

dispensing) of a pharmacy, and indirectly the patient (by way of

retail price paid) or the plan sponsor (who bases its dispensing fee

on surveys to evaluate operating expenses). The direction of the

effect of these variables on dispensing costs is indicated after the

variable name. As an example, the prescription volume has a negative

effect on dispensing costs, i.e., the higher the prescription volume

the lower will be the operating costs.

The theoretical model shown in Figure 2-2 forms the basis of this

study; the purpose of which is to evaluate the differences between the

usual and customary prices charged and the probable reimbursement

price the Florida Medicaid drug program would pay for the same

prescriptions. Another objective is to look at how the different

variables affecting the dispensing costs affect the price differences

and other research variables.














CHAPTER III
METHODOLOGY

This chapter describes the research design of the study. After

identifying the research variables, the various accounting equations

are described. Next the specific research hypotheses for each of the

independent variables and their relationship to dependent variables

are stated. This is followed by a description of the data source and

the procedures used. Finally, methodological assumptions and the

limitations of this study are described followed by a brief summary of

this chapter.



Research Design

This study was designed to evaluate and compare the operating

profits (losses) realized through Medicaid drug dispensing and

private-pay dispensing. The study also attempted to see if there was

any cost shifting occurring as a result of Medicaid participation by

pharmacies in the State of Florida. Another facet of the study was to

evaluate whether the allowable dispensing fee component of the State

of Florida's Department of Health and Rehabilitative Services (DHRS)

is adequate to cover the operating expenses incurred in dispensing a

prescription in Florida pharmacies.

A further extension of this study looks at the price

differentials for a number of specific drug categories. This will

result in realistically looking at which drug categories result in










profits or losses due to Medicaid participation when compared to the

usual and customary price charged by the sample pharmacies.

The final aspect of this study was to compare the profits

realized from prescription sales with those from nonprescription

sales.

This was a retrospective descriptive cross-sectional study

utilizing secondary data. The secondary data were collected by the

accounting firm of Myers and Stauffer under contract with the Florida

DHRS. The data were collected in late 1984 for the purpose of

assessing the cost of dispensing incurred by Florida pharmacies.



Research Variables

The different variables utilized in this study are listed below,

followed by a description of the variables. The dependent variables

are

1. the price charged for usual and customary prescriptions,

2. the amount Florida Medicaid would reimburse, and

3. net profit as a percent of sales.

The independent variables of interest were

1. all cost items--(a) overhead costs,

(b) labor costs, and

(c) cost of goods sold; and

2. type and quantity of drugs dispensed in the usual and

customary price segment of the survey.

Other independent variables or different pharmacy characteristics

for the purposes of this study were









1. type of pharmacy--independents and chains;

2. total prescriptions dispensed during the year 1984--five

categories, which are

(a) < 10,000

(b) 10,001 to 20,000

(c) 20,001 to 30,000

(d) 30,001 to 40,000

(e) > 40,001;
3. total number of Medicaid prescriptions dispensed during 1984--

three categories as follows:

(a) 1 to 500

(b) 501 to 1,000

(c) 1,001 or above;

4. percent Medicaid as a proportion of total prescription

volume--four categories as follows:

(a) 0.01% to 5%

(b) 5.01% to 10%

(c) 10.01% to 20%

(d) 20.01% and above;

5. services offered--

(a) Computers

(b) Delivery

(c) Advertisement;

6. type of ownership--

(a) Sole proprietor (or individual)










(b) Partnership

(c) Corporation.

The variables listed above are operationally defined herewith.

Dependent Variables

1. Usual and customary prescription price--This was the actual

price charged by the pharmacies to their private-paying customers. It

was self-reported by the pharmacies in the usual and customary survey

of the first 30 new prescriptions filled from a specific date. For

the purposes of this study a mean price was calculated for the

prescriptions included in the study.

2. Medicaid reimbursement rate--This was the amount Florida DHRS

would reimburse for the prescriptions in the usual and customary

prescription survey. This amount is comprised of two components--the

price of the drug ingredient and the flat dispensing fee of $3.33 (in

1984).

3. Net profit percent--This is the amount of profit earned by

the pharmacies expressed as a percent of sales. The net profit

figures are exclusive of taxes. There are three different net profit

percent figures for any given pharmacy. These are net profit percent

(NP%) for the prescription department, NP% for nonprescription sales

(or "front-end" of the store), and NP% for the total store

(prescription department plus "front-end" sales). All these data were

calculated from self-reported operating figures of the pharmacies.

Independent Variables

1. Pharmacy Cost Items--These are all items expended by the

pharmacies over a period of 1 year in order to operate the pharmacy.










There are three components--overhead, labor, and cost of goods sold.

All these costs pertain only to the prescription department, and many

of the line items are obtained by allocation. The sum of the labor

and overhead costs when divided by the total prescriptions dispensed

gives the dispensing cost per prescription for each pharmacy. The

method utilized to allocate various cost items and the procedure to

derive the dispensing costs are explained in Appendix A.

2. Drugs included in the study--These are the prescription drugs

from the usual and customary survey which are included for data

analysis purposes. Prescriptions containing drug items excluding MAC

drugs were included in the data analysis. The reason for this was to

make sure Medicaid reimbursed for the actual drug item dispensed, and

not another brand or a generic form of the brand actually dispensed.

This would ensure validity of the comparisons between Medicaid and

usual and customary prescription prices.

On the other hand, drugs included for comparing price differences

between different drug items were different. These were drugs which

were among the top 200 most frequently prescribed drugs during 1984.

The actual drugs included broadly fall into two categories--single

source and multi-source drugs. Among the single source, 10 drug items

were selected which ranked within the top 100 drugs for 1984 ("Top 200

Drugs," 1985). The rankings ranged from number 1 to 88. For the

multi-source drugs, seven products were selected and they ranked from

1 to 21. All of the top 10 drugs for new prescriptions for 1984 were

included in the total of 17 fast-moving drugs (26 line items

comprising different strengths/forms of the same active ingredient)









selected for this part of the study. A list of these drugs can be

found in Appendix B.

Pharmacy Characteristics

1. Type of pharmacy--This variable relates to the type of

operation of the pharmacy. Two basic types are prevalent in the

literature--independents and chains. The independents are those

operating from one to four pharmacies, and chains are ones having five

or more pharmacies. This form of classification is most prevalent in

literature and it was also used in the survey performed by Myers and

Stauffer (1985) on behalf of Florida DHRS.

2. Prescription volume--This is the total number of all types of

prescriptions dispensed by a pharmacy during 1984. The total volume

is broken into five categories similar to the ones used in the Myers

and Stauffer (1985) survey. These five categories were less than or

equal to 10,000; 10,001-20,000; 20,001-30,000; 30,001-40,000; and

40,001 or more prescriptions dispensed during 1984.

3. Medicaid volume--The total number of Medicaid prescriptions

dispensed by a pharmacy during 1984 encompasses this variable. The

actual numbers of Medicaid prescriptions for each pharmacy were

obtained from the records of Florida DHRS. Medicaid volume was

categorized into three categories. These categories were arbitrarily

selected as a result of reviewing the Medicaid volume figures of the

participating pharmacies. The three categories were less than or

equal to 500, 501 to 1,000, and 1,001 or more Medicaid prescriptions

dispensed during 1984.










4. Medicaid percent--This variable was defined as the number of

Medicaid prescriptions dispensed during 1984 as a proportion of total

prescriptions dispensed during 1984. The ratio was expressed as a

percent. After reviewing the data, four categories were arbitrarily

decided upon. These were 0.01 to 5%, 5.01 to 10%, 10.01 to 20%, and

20.01% or more.

5. Services offered--These were the various services offered by

the pharmacies. Only three different ones were included since they

were all that were available from the secondary data sources of Myers

and Stauffer (1985). The three services were computers, delivery, and

advertisement. The data were coded as to whether these services were

or were not offered by the sample pharmacies.

6. Ownership type--This entails the actual type of legal

ownership of the pharmacy. Three different types of ownership are

feasible: sole proprietorships, partnerships, and corporations.

These three categories were used in the survey and for this study.



Accounting Models

A number of variables required for the study were calculated from

the raw cost figures found in the secondary data source. All of these

variables were derived through standard accounting equations.

However, a new variable was created called Single Rate Prescription

Cost (SRPC), in order to perform some of the data analysis. The SRPC

was defined for the purposes of this research as the overall average

costs incurred to dispense any given prescription by a specific

pharmacy. It consists of two components: the cost of drug









ingredients) and the cost of dispensing. The accounting model to

derive the SRPC is as follows:


SRPC = TRXCGS + RXLABOR + RXOVHED
SRPC = TOTRX


where

TRXCGS = Total cost of goods sold for the prescription
department for 1984.

RXLABOR = Total labor costs incurred by the prescription
department during 1984,

RXOVHED = Total overhead expenses incurred by the prescription
department during 1984, and

TOTRX = Total number of prescriptions dispensed during 1984.


Thus, on the average any given prescription would cost a pharmacy

the amount calculated as the SRPC for that pharmacy.

Usual and customary mean price (UCMP) and Medicaid reimbursement

rate (MRR) were calculated using the following equations:


UCMP= UCPC for X prescriptions
X

MRR = MCGS for X prescriptions + $3.33
X

where

UCPC = Usual and customary price charged for the prescriptions
in the survey,

MCGS = Medicaid cost of goods reimbursement payable for the
prescriptions in the survey, and
X = Number of prescriptions from the usual and customary
survey included in this study.











The profit (losses) from usual and customary and Medicaid

prescriptions for the pharmacies can be calculated using the following

accounting equation:


UCP = UCMP SRPC

MP = MRR SRPC


where


UCP = Average profit from a usual and customary prescription,
and

MP = Average profit from dispensing a Medicaid prescription.


The net profits for the pharmacies were calculated using the

following equations:


Prescription Department Profit


TRXSA = TRXCGS + RXLABOR + RXOVHED + RXPROFIT

or

RXPROFIT = TRXSA (RXCGS + RXLABOR + RXOVHED)


where


TRXSA = Total 1984 prescription sales, and

RXPROFIT = Total 1984 prescription department profit.


Total Pharmacy Profit


SALES = TCGS + TLABOR + TOVHED + PROFIT

or
PROFIT = SALES (TCGS + TLABOR + TOVHED)










where

TPROFIT = Total 1984 profit for the whole pharmacy,

TCGS = Total cost of goods sold for the whole pharmacy,

TLABOR = Total labor costs for the whole pharmacy,

TOVHED = Total overhead costs for the whole pharmacy, and

TSALES = Total sales for the whole pharmacy during 1984.


Front-End Profits

FEPROFIT = PROFIT RXPROFIT


where

FEPROFIT = Total front-end profit for the pharmacy during 1984.


Using the above equations the net profit as a percent of sales

was calculated as follows:


NPPRX = RXPROFIT/TRXSA

NPPFE = FEPROFIT/(TSALES TRXSA)

NPPTP = TPROFIT/TSALES


where

NPPRX = Net profit percent for prescription department,

NPPFE = Net profit percent for front-end of pharmacy, and

NPPTP = Net profit percent for total pharmacy.


All of the above accounting equations were utilized in order to

derive the relevant variables for testing the research hypotheses

stated in the next section.











Research Hypotheses
The research hypotheses which were tested by this study are

stated herewith.

1. The average price charged for usual and customary

prescriptions will be significantly higher than the price reimbursed

for similar prescriptions by Florida Medicaid. The magnitude of this

price differential will vary based on the differences in pharmacy

characteristics.

The statistical form of this hypothesis is as follows:


HO: UCMP = MRR

HA: UCMP > MRR

One-tail "t" tests will be performed at a significance level (p)

of 0.01.

2. The average per prescription profits from usual and customary

prescriptions will be greater than that for Medicaid prescriptions.

The magnitude of this differential will vary based on differences in

pharmacy characteristics. This hypothesis stated in accounting

equation form is


UCP MP = 0

or UCP = MP

Substituting for UCP and MP, the above equation can be expressed










UCMP SRPC = MRR SRPC

The above equation can be reduced to


UCMP = MRR

The statistical form of the hypothesis will be as follows:


HO: UCMP = MRR

HA: UCMP > MRR

One-tail "t" tests will be performed at p = 0.01.

3. The price charged for different drug items on a per unit

basis will be lower for usual and customary prices when compared to

Medicaid reimbursement price. This is contrary to the other

hypothesis. The reason for the direction of this hypothesis can be

attributed with certainty to the fact that market competitive forces

will drive down the prices charged to private-paying customers. This

is because the drugs selected for the purposes of this hypothesis are

among the top selling drugs of 1984.

The magnitude of the price differential will vary depending on

the drug item and pharmacy characteristics. The statistical form of

this hypothesis is as follows:


HO: MRR/unit = UCMP/unit


HA: MRR/unit > UCMP/unit










where
MRR/unit = the Medicaid reimbursement rate per unit of the
drug item, i.e., per capsule/tablet/milliliter,

UCMP/unit = usual and customary price charged on a per unit
basis.

One-tail "t" tests will be performed at p = 0.01.

4. The majority of pharmacies were making a higher net profit

percent (before taxes) from their prescription department operations

when compared to the operations of the rest of the pharmacy. The

magnitude of this difference will vary based on pharmacy

characteristics.

The statistical form of this hypothesis can be expressed as

follows:


HO: NPPRX = NPPFE

HA: NPPRX > NPPFE


One-tail "t" tests will be performed at p = 0.01.



Data Source
Secondary data from the 1985 cost of dispensing study performed

by Myers and Stauffer (1985) under contract with the Florida

Department of Health and Rehabilitative Services were utilized. This

was a mail questionnaire survey of pharmacies who were registered with

the Florida DHRS during 1984. The survey questionnaire was mailed to

2,213 eligible community pharmacies on December 1, 1984, and 369

usable surveys were received by the extended deadline of March 6,

1986. The overall response rate was 17%, and the researchers stated


~










that this figure was sufficient to provide estimates at the 95%

confidence interval with a sample precision of 2%.

The survey questionnaire, Appendix C, obtained detailed cost

figures in order to assess the cost of dispensing for the sample

pharmacies. The researchers randomly performed in-store audits of 43

community pharmacies in order to verify the self-reported cost figures

in the survey questionnaire. They did not find any significant trend

in overstating or understating costs.

Of the 369 responding pharmacies, 252 representing three chain

organizations comprised 25% of the total chain pharmacy population in

Florida.

The other 117 pharmacies represent 10% of the total independent

pharmacy population.

In addition to the cost data auditing and analysis, a survey of

usual and customary prescriptions dispensed by the sample pharmacies

was performed. This survey consisted of listing the first 30 new

prescriptions, dispensed from the opening of business on one of two

dates--April 16, 1984, or October 16, 1984. The pharmacists were

asked to exclude all third party prescriptions, including Medicaid,

compounded prescriptions, and prescriptions for over-the-counter

products. The information requested was the prescription number, the

name and the strength of the drug, the quantity dispensed, the

National Drug Code (NDC) number, and the actual selling price of the

prescription.

The usual and customary survey contained approximately 11,000

prescriptions. Prescriptions with quantity discrepancies were










discarded. Moreover, all prescriptions with a gross margin of less

than -$2.75 were excluded in order to eliminate any erroneous data.

This was done by the researchers based on their prior experience and

knowledge from performing similar surveys.



Procedure

The secondary data source consisting of the cost of dispensing

survey and the usual and customary prescription survey for Florida

pharmacies was obtained from the pharmacy consultant of Florida DHRS,

Mr. Jerry Wells, R.Ph. He handed over the hard-printed copy of the

data to the researcher on May 28, 1985. Unfortunately, the Department

would not provide the data tapes, in interests of maintaining strict

confidentiality as to the identity of the participating pharmacies.

This was an issue of concern to the Department as well as to Myers and

Stauffer, the firm that performed the study.

On receiving the data, they were carefully scrutinized to

determine what types of data were available from these files. The

next step consisted of making a list of the variables which could be

retrieved from the output. Once this was finalized, the researcher

proceeded to transcribe the relevant variables from the output onto

data coding sheets. This was an enormous task that entailed a high

probability of errors in transcription. Therefore, once all the

variables had been transcribed on data coding sheets, they were

compared with the original output with the help of volunteers. Once

this was over, the next step was to enter all these data into the

computer. This was performed by the researcher over a period of










time. Once all data were in the computer, a print-out was obtained.

This was then compared and checked against the data on the coding

sheets. All mistakes were corrected and the data in the computer were

then ready for analysis.



Prescription Audit
This part of the procedure deals with screening all the usual and

customary prescriptions (7,699) and selecting all prescriptions

(2,029) dispensed for the 17 drugs (comprising 26 line items). These

drugs are listed in Appendix B. The audited prescriptions containing

the pharmacy identification number, the name and quantity of drug

dispensed, the usual and customary price charged, and the probable

Medicaid amount which would have been reimbursed, were all transcribed

on data coding sheets. The NDC number of each audited prescription

was verified with the Drug Topics Redbook (1984), in order to identify

the strength of the drug. This was done because in the survey only

the drug name was stated and not the strength, e.g., 5 mg tablets,

500 mg capsules, etc. This procedure was very time-consuming and a

volunteer was enlisted to assist in this task. Once all the

prescriptions had been transcribed, they were entered into the

computer. After this task was completed, a print-out was obtained and

checked against the original. All transcribing errors were then

rectified.

The next step was to program the computer to obtain the price per

unit (i.e., per tablet/capsule/milliliter). This was done by dividing










the transcribed prices by the quantity of drug dispensed. After this,

the data were ready for statistical analysis.



Methodological Assumptions

A basic assumption made in this study was to accept the various

cost allocation procedures and the method adopted to derive the

dispensing costs by Myers and Stauffer (1985) in their Florida

dispensing cost survey. This was done for two reasons: the Florida

DHRS utilizes this method to derive the dispensing fee to be paid for

Medicaid prescriptions and, secondly, Myers and Stauffer (1985) by

virtue of performing a number of dispensing cost studies have

standardized the procedure to derive the dispensing cost figures. It

was also determined after a detailed review of other cost of

dispensing studies that the method followed by Myers and Stauffer

(1985) was realistic and justifiable. Therefore under all of the

above mentioned circumstances, the researcher felt justified to accept

the dispensing costs as found in the survey.



Limitations
A possible limitation of the study would be the number of usual

and customary prescriptions surveyed. This figure was a maximum of

30, based on which this study compares the Medicaid reimbursement with

private-pay prices. The small number of prescriptions could be a

limitation in generalizing the results of this study.

The small number of responding pharmacies, particularly for

independents (10% response rate), is a limitation in the extent to










which this study can be projected for the whole of Florida. However,

the study provides a realistic estimate of the profits (or losses)

from Medicaid when compared to private-pay prescriptions for those

pharmacies that participated in the survey.

In terms of the individual drug category comparisons, the 17

fast-moving drugs included in the study were not dispensed by all the

pharmacies in the survey. Therefore, for this portion of the study,

the sample size in terms of the number of pharmacies included is lower

than the rest of the study. This then further limits the degree of

generalizability of this study.

Finally, this study is limited in terms of the availability of

data. This limitation was two-fold: first, the research had to

conform to studies which could be performed from the type of data

collected in the survey; and, second, certain data, primarily pharmacy

characteristics such as location of pharmacy, years of existence,

percent of total third party prescriptions, etc., were not revealed by

the surveyors to the researcher. This limited evaluation of the

effect of various pharmacy characteristics on the dependent variables.



Summary
This chapter dealt with the research design. All the independent
and dependent variables were listed and operationally defined. Next

the various accounting equations used for this research were

described. After this, the four main research hypotheses and their

statistical forms were expressed. The source of the secondary data

and their descriptions were stated followed by the research






51


procedure. The next chapter will deal with the statistical results of

this research followed by a discussion and interpretation of the

resul ts.















CHAPTER IV
RESULTS

This chapter will deal with the results of statistical analysis

of the data in relation to the objectives of this study. All

statistical analyses were performed using the SAS (1985) computer

package. The first part of this chapter consists of descriptive

statistics of the sample pharmacies and the variables pertaining to

the research. This is followed by statistics related to each of the

research hypotheses. The Lilly Digest (1985) and the NACDS--Lilly

Digest (1985) are two data sources which provide figures for

independent and chain pharmacies, respectively, on a national basis.

A number of comparisons of the operations of Florida pharmacies as

found in this study will be made with national averages. The method

of data collection to obtain national statistics by the Lilly Digest

(1985) and the NACDS--Lilly Digest (1985) is comparable to the Florida

pharmacy survey. They all used voluntary samples, and the data were

collected through mail questionnaire surveys. The Lilly Digest (1985)

had a sample size of 1,341 independent pharmacies and the NACDS--Lilly

Digest (1985) had 1,282 chain pharmacies, in both cases distributed

throughout the nation. The interpretations (conclusions and

recommendations) are presented in the next chapter.










Description of Sample Pharmacies

Florida Pharmacy Survey Findings

The Myers and Stauffer (1985) study of Florida pharmacies, under

contract with Florida Department of Health and Rehabilitative Services

(DHRS), mailed out a 4-page survey instrument requesting data on

expenditures for the year 1984 and also a list of the first 30

private-pay prescriptions dispensed during a specified period. The

population consisted of 2,213 pharmacies listed with DHRS, of which

1,012 were operated by 22 chain organizations; the rest were

independents. Chains were defined in this study as those

organizations which operated five or more pharmacies. The first

mailing was completed by December 1, 1984; there were two follow-

ups. By the extended deadline of March 11, 1985, a total of 369

usable surveys was received which constituted a response rate of

17%. Of these, 252 pharmacies representing three chain organizations

and constituting 25% of the total chain population participated in the

survey. The remainder of the 117 participating pharmacies represented

10% of the total independent population.

The respondents, when broken down by type of ownership, consisted

of 18 pharmacies owned by sole proprietors, five pharmacies owned by

partnerships, and the balance of 346 owned by corporations.

From the respondents, 43 stores were randomly selected for in-

store audits. There was no significant trend found in overstating or

understating costs reported in the survey.

For the usual and customary part of the survey, 356 pharmacies

participated. However, not all these pharmacies participated in the










cost survey, nor did all of those participating in the cost survey

participate in the usual and customary survey. The usual and

customary survey produced a total of 11,000 prescriptions which were

actually dispensed to private-paying customers.

On a per prescription basis, the mean labor cost was $2.76, the

overhead cost was $1.08, and the total cost per prescription was $3.83

(Myers & Stauffer, 1985, Table 6). When broken down by type of

pharmacy, the total cost per prescription was $4.13 for independents

and $3.69 for chains (Myers & Stauffer, 1985, Table 9). The average

prescription price from the usual and customary survey was $11.91

(excluding prescriptions for MAC drugs) as found by Myers and Stauffer

(1985, Table 1).

Results From Data Analysis

Table 4-1 shows the number of pharmacies in the different

categories of prescription volume, Medicaid volume, and Medicaid

percent. The largest number of pharmacies (129 or 35%) dispensed over

40,000 prescriptions in 1984. The table indicates that 147, 62, and

121 pharmacies dispensed 500 or less, 501-1,000, and over 1,000

Medicaid prescriptions respectively during 1984. Thus, the largest

number of pharmacies, comprising 44.5% of the total, dispensed 500 or

less Medicaid prescriptions. The largest number of pharmacies (243 or

73.6%) dispensed 5% or fewer Medicaid prescriptions.

Tables 4-2 through 4-4 show the prescription volume, Medicaid

volume, and Medicaid percentage categories broken down by type of

pharmacy (independents and chains). Table 4-2 shows that the majority

of both types of pharmacies (104 independents and 136 chains)













Frequency Table of Prescriptions Dispensed.


Number of Pharmacies


Prescription Volume


< 10,000
To,001 -
20,001 -
30,001 -
> 40,000

Total


20,000
30,000
40,000


Medicaid Volume

< 500
701 1,000
> 1,000


Total


Medicaid Percent


< 5%
5.01 10%
10.01 20%
> 20%

Total


* Myers and Stauffer (1985) provided Medicaid
pharmacies out of 369 surveyed.


volume data for only 330


Percent


2.7
15.4
24.7
22.2
35.0

100.0


147
62
121

330*


44.5
18.8
36.7

100.0


243
50
26
11

330*


73.6
15.2
7.9
3.3

100.0


Table 4-1.















Table of Prescription Volume by Pharmacy Type.


Prescription Volume
Pharmacy 10,001- 20,001- 30,001-
Type < 10,000 20,000 30,000 40,000 >40,000 Total

Independents

Frequency 8 38 40 18 13 117
Percent 2.17 10.33 10.87 4.89 3.53 31.79


Chains

Frequency 2 19 51 64 115 251
Percent 0.54 5.16 13.86 17.39 31.25 68.20


Total

Frequency 10 57 91 82 128 368
Percent 2.71 15.49 24.73 22.28 34.78 99.99*


* The pharmacy type of a pharmacy was missing.


Table 4-2.














Table 4-3. Table of Medicaid Volume by Pharmacy Type.


Medicaid Volume
Pharmacy Type < 500 501-1,000 > 1,000 Total


Independents

Frequency 24 16 65 105
Percent 7.29 4.86 19.76 31.91

Chains

Frequency 123 46 55 224
Percent 37.39 13.98 16.72 68.09

Total

Frequency 147 62 120 329
Percent 44.68 18.84 36.48 100.00














Table 4-4. Table of Medicaid Percent by Pharmacy Type.


Medicaid Percent
Pharmacy Type < 5% 5.01-10% 10.01-20% > 20% Total


Independents

Frequency 38 32 24 11 105
Percent 11.55 9.73 7.29 3.34 31.91


Chains

Frequency 205 17 2 0 224
Percent 62.31 5.17 0.61 0.00 68.09


Total

Frequency 243 49 26 11 329
Percent 73.86 14.90 7.90 3.34 100.00










dispensed 40,000 or fewer prescriptions. Table 4-3 shows that the

majority of chains (123) dispensed less than 500 Medicaid

prescriptions, whereas the opposite was true for independents, i.e.,

65 independents dispensed over 1,000 Medicaid prescriptions (the

highest category). Table 4-4 confirms this, indicating that 205

chains (or 91.5% of the total chains) dispensed 5% or fewer Medicaid

prescriptions. For independents, a sum of 70 (38+32) pharmacies (or

66% of the total independents) dispensed 10% or fewer Medicaid

prescriptions. Only 11 pharmacies, all of which were independents,

dispensed over 20% of their total prescriptions to Medicaid

recipients.

Tables 4-5 is a two-way table of pharmacy types classified by

computer utilization, delivery services, and advertising. The table

indicates that only a total of 26 pharmacies (24 independents and 2

chains) out of 368 pharmacies have computers. The table shows that

only 54 (all independents) had delivery services. A total of 127

pharmacies (115 independents and 12 chains) indicated that they

advertise. Fifty-one chains failed to indicate whether they offered

any of these three services.

Table 4-6 is a two-way table of ownership type by pharmacy

type. The table indicates that all 251 chains are owned by

corporations. Of the 117 independents, 18 are owned by individuals, 5

by partnerships, and balance of 94 have corporate ownership.

Table 4-7 is a two-way table of ownership type and pharmacy type

broken down by volume of prescriptions dispensed. The table shows

that the majority of corporations (219), individually operated















Table 4-5. Table of Pharmacy Type by Services.


Pharmacy Type

Independents Chains Total

Computers

Missing 0 51 51
No 93 198 291
Yes 24 2 26


Delivery

Missing 0 51 51
No 63 200 263
Yes 54 0 54


Advertising

Missing 1 51 52
No 1 188 189
Yes 115 12 127















Ownership Type by Pharmacy Type.


Pharmacy Type
Ownership Type Independents Chains Total


Individual

Frequency 18 0 18
Column Percent 15.39 0.00


Partnerships

Frequency 5 0
Column Percent 4.27 0.00


Corporations

Frequency 94 251 345
Column Percent 80.34 100.00


Total

Frequency 117 251 368
Percent 100.00 100.00


- -


Table 4-6.















Prescription Volume by Ownership Type.


Ownership Type
Prescription Volume Individual Partnership Corporation Total


< 10,000


Frequency
Column Percent

10,001-20,000

Frequency
Column Percent

20,001-30,000

Frequency
Column Percent

30,001-40,000

Frequency
Column Percent

> 40,000

Frequency
Column Percent


Total

Frequency
Percent


5
27.78


4
22.22


8
44.44


0
0.00


1
5.56


18
100.00


0
0.00


3
50.00


0
0.00


1
16.67


2
33.33


6
100.00


5
1.45


50
14.49


83
24.06


81
23.48


126
36.52


345
100.00


Table 4-7.










pharmacies (17), and partnership operations (4) dispensed 40,000 or

fewer prescriptions.

From the descriptive statistics stated above, it is apparent that

some of the pharmacy characteristics do not have sufficient numbers to

test some of the various research hypotheses. This was because of the

small number of pharmacies possessing these characteristics.

Specifically, these variables are computer utilization (26), delivery

services (54--all of which were independents), advertising (127), and

pharmacy ownership (only 18 individuals and 6 partnerships). An

interesting observation relating to advertising was that only 12 chain

pharmacies stated that they had advertising programs. However, in

reality this is not true, since most chains in Florida advertise

heavily. This is because the researcher has observed that a number of

chain pharmacies, including the largest chain in Florida, advertise

quite frequently. Some even advertise on a weekly basis. Therefore,

it was apparent that due to some reason, most chains did not indicate

that they had advertising programs. One possibility could be that

advertising expenses are allocated on a regional basis rather than on

a per pharmacy basis.

In view of the small number of pharmacies possessing the above

mentioned characteristics, the effect of these on the various

dependent variables will not be examined. This is because meaningful

inferences cannot be drawn from the analysis.










Descriptive Statistics of Other Independent Variables

Total prescription volume

Table 4-8 shows the total prescription volume dispensed by type

of pharmacy. Chains dispensed 78% and independents dispensed 22% of

the total prescription volume of 1,344,7437. The mean prescription

volume was 24,843 for independents, and 41,787 for chain pharmacies.

One interesting feature was that the highest number of prescriptions

(113,810) was dispensed by an independent pharmacy. When compared to

national averages, the Florida independents and chains had lower

prescription volumes. The national means were 28,776 for independents

(The Lilly Digest, 1985) and 45,495 for chains (NACDS--Lilly Digest,

1985).

Total Medicaid volume

Table 4-9 is a two-way table of Medicaid prescriptions dispensed

by type of pharmacy. Independents dispensed 55% (216,415) Medicaid

prescriptions as opposed to 45% (180,100) prescriptions dispensed by

chains. A total of 396,516 Medicaid prescriptions was dispensed by

329 pharmacies. As was expected, the highest volume (8,000) was

dispensed by an independent pharmacy. The mean volume dispensed was

2,061 for independents and 804 for chains; the overall mean was 1,205

prescriptions per pharmacy.

Medicaid percent

It can be seen from Table 4-9 that the mean Medicaid prescription

percentage for independents was 9%; for chains it was 2%; and overall,

it was 4%. The largest percentage (40%) of Medicaid prescriptions was

dispensed by an independent pharmacy. These figures are much lower















Table 4-8. Total Prescription Volume Dispensed by Pharmacy Type.


Total Prescription Volume Dispensed
Pharmacy Number of Standard
Type Pharmacies Mean Deviation Minimum Maximum Sum


Inde-
pendents 117 24843 15321.72 1515 113810 2906570

Chains 251 41787 19055.68 6911 106057 10488401


Total 368 36443 19586.74 1515 113810 13447437
















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when compared to national statistics. The overall Medicaid percentage

nationally was 14.8% (The Lilly Digest, 1985) as compared to 4% for

Florida. These figures broken down by type of pharmacy in the

nationwide sample were 17.6% and 8.7% for independents and chains

respectively (The Lilly Digest, 1985), and 9% and 2%, respectively,

for Florida.

The Medicaid volume data provided by Myers and Stauffer (1985)

was truncated due to confidentiality reasons. They did not provide

the data for those pharmacies dispensing the top 10% Medicaid

prescriptions during 1984. This could be the most probable reason for

the large discrepancy in Medicaid percent dispensed when comparing

with national averages.

Dispensing cost per prescription

Table 4-10 gives the frequency of dispensing cost by type of

pharmacy. The table shows that the mean dispensing cost incurred by

independents was $4.13 and $3.70 for chains; the overall mean was

$3.83. The extreme figures for the minimum ($2.02) and maximum

($7.06) dispensing costs both belong to chains. The standard

deviation was $0.87 for both independents and chains; it was $0.88

overall. It is noteworthy to observe that the means for both types of

pharmacies were higher than the $3.33 dispensing fee paid by OHRS for

Medicaid prescriptions.

Dispensing cost when broken down by pharmacy type showed that 99

(84.6%) independents and 154 (61.4%) chains had a cost per

prescription of greater than $3.33. The dispensing cost for 13















Table 4-10. Dispensing Cost Per Prescription Dispensed by Pharmacy
Type.


Pharmacy
Type


Independents

Chains


Total


Number of
Pharmacies


117

251


368


Mear
$


4.13

3.70


3.83


Dispensing Cost

Standard
Deviation
$


0.87

0.87


0.88


Per Prescription


Minimum Maximum
$ $


2.26 6.79

2.02 7.06


2.02 7.06


I










independents and 95 chains was lower than the Medicaid fee of $3.33.

Two of the chains had a dispensing cost of $3.33.

Number of prescriptions included in the study

The total number of prescriptions included in the study from the

usual and customary survey is given in Table 4-11. The total of 7,699

prescriptions consisted of non-MAC drug items. The mean number of

prescriptions was 22 for independents and 21 for chains. The overall

mean was 21 prescriptions per pharmacy. These numbers relate to the

number of prescriptions used to compare usual and customary prices

with Medicaid reimbursement rates. Independents constituted a total

of 2,540 (32.99%) prescriptions, and chains had a total of 4,751

(61.71%) prescriptions.

The number of prescriptions audited for the specific drug price

comparisons was 2,029. This translates to 26.35% (2,029/7,699) of the

total prescriptions audited for the specific drug price comparisons.

Descriptive Statistics of Dependent Variables

Usual and customary mean price (UCMP)

Table 4-12 is a frequency of UCMP by type of pharmacy. The mean

price per prescription actually charged was $14.09 for independent

pharmacies, $12.59 for chains, and the overall mean was $13.10. The

minimum mean prescription price of $8.25 was charged by a chain, and

the highest average price charged was $33.94 by an independent

pharmacy. The range for UCMP for both independents ($25.59) and

chains ($11.14) was quite large.













Table 4-11. Number of Prescriptions Included in the Study by Pharmacy
Type.


Prescriptions Included in Study
Pharmacy Number of Standard
Type Pharmacies Mean Deviation Minimum Maximum Sum Percent


Missing 19 21.47 5.72 1 28 408 5.30

Inde-
pendents 114 22.28 3.02 15 29 2540 32.99

Chains 223 21.30 2.52 15 28 4751 61.71


Total 356 21.62 2.94 1 29 7699 100.00


Note: There were 19 pharmacies responding to the usual and customary
prescription survey whose pharmacy type affiliation was
missing.













Table 4-12. Usual and Customary Mean Price of Prescriptions by
Pharmacy Type.


Usual and Customary
Mean Price for Prescriptions

Standard
Pharmacy Number of Mean Deviation Minimum Maximum
Type Pharmacies $ $ $ $


Missing 19 13.03 2.84 8.98 18.84

Independents 114 14.09 3.30 8.35 33.94

Chains 223 12.59 1.96 8.25 19.39


Total 356 13.10 2.60 8.25 33.94










Medicaid reimbursement rate (MRR)

The last of the independent variables is tabulated in Table 4-13

according to pharmacy type. The mean amount which would have been

reimbursed by DHRS was $12.93 for independents and $12.65 for chains;

the overall mean was $12.75. The minimum reimbursable amount was

$5.60 for a chain and $8.02 for an independent. The maximum Medicaid

reimbursement rate was $32.78 for an independent and $19.72 for a

chain. The standard deviations of $3.03 for independents and $2.13

for chains were quite small when compared to the range of $24.76 and

$14.12, respectively. This indicates the presence of outlyers.

Total profits

Table 4-14 shows the total profit for the entire pharmacy

operation by type of pharmacy. Independents made a mean profit of

$2548.91, chains made a mean profit of $119,443.68 per pharmacy, and

the overall average profit was $76,767.82. An independent suffered

the greatest loss ($298,987.00) and a chain earned the highest profit

($640,599.00). Independents contributed only 1.2% of the total

profits of all the sample pharmacies, whereas the chains accounted for

98.8% of the profits. The reported total profits nationally were

$17,375 for independents (The Lilly Digest, 1985) and $106,404 for

chains (NACDS--Lilly Digest, 1985).

Prescription department profit

Table 4-15 shows the prescription department profits by type of

pharmacy. The mean profit for independents was $2,881.86, for chains

$12,794.91, and the overall mean profit was $9,833.93. The maximum

profit of $130,540.00 was reported by an independent pharmacy, as was










Table 4-13. Medicaid Reimbursement Rate for Prescriptions Dispensed
by Pharmacy Type.


Medicaid Reimbursement Rate
for Prescriptions

Standard
Pharmacy Number of Mean Deviation Minimum Maximum
Type Pharmacies $ $ $ $


Missing 2 13.15 1.36 12.19 14.11

Independents 114 12.93 3.03 8.02 32.78

Chains 223 12.65 2.13 5.60 19.72


Total 339 12.75 2.46 5.60 32.78


Table 4-14. Table of Total Profit Made by Pharmacy Type.


Total Profit Made

Standard
Pharmacy Number of Mean Deviation Minimum Maximum
Type Pharmacies $ $ $ $

Independents 115 2548.91 39316.66 -298987.00 104038.00

Chains 200 119443.68 122403.08 -168573.00 640599.00


Total 315 76767.82 115078.69 -298987.00 640599.00














Table 4-15. Table of Prescription Department Profits by Pharmacy
Type.


Pharmacy
Type


Prescriptions Department Profits

Standard
Number of Mean Deviation Minimum Maximum Sum
Pharmacies $ $ $ $ $


Inde-
pendents 117 2881.86 30428.40 -116236.00 130540.00 337178.00

Chains 251 12794.91 35503.58 -50153.00 108881.00 3211522.00


Total 368 9833.93 34342.69 -116236.00 130540.00 3548700.00










the maximum loss of $116,236.00. Independents accounted for 9.32% of

the total profits, whereas chains accounted for 88.74%.

Front-end profits

Table 4-16 is a table of front-end profits by pharmacy type. The

independents on the average suffered a loss of $286.57, while chains

made a mean profit of $101,064.81; the overall mean was $64,063.52.

Thus independents, on the average, suffered losses from their front-

end operations.

Net profit percentages

Table 4-17 through 4-19 are tables of net profit percentages

(NP%) for the total pharmacy, prescription department, and the front-

end, respectively.

The NP% for the total pharmacy operation was negative for

independents, 5% for chains, and on overall mean of 3% for all

pharmacies. The figures for independents are very low when compared

to the national figure of 3.1% for the year 1984 (The Lilly Digest,

1985). On the other hand, the Florida chains had a higher net profit

percent compared to the national average of 4.7% (NACDS--Lilly Digest,

1985).

The prescription department NP% is shown in Table 4-18. The

independents on the average (1%) fared better than chains (0%) in

operating their prescription departments. The highest loss percentage

was reported by a chain (43%) and the highest profit percentage by an

independent (46%).












Table 4-16. Table of Front-End Profits by Pharmacy Type.


Front-End Profits

Standard
Pharmacy Number of Mean Deviation Minimum Maximum Sum
Type Pharmacies $ $ $ $ $


Inde-
pendents 115 -286.57 45932.55 -225012.00 220274.00 -32955.00

Chains 200 101064.81 105785.61 -167683.00 531718.00 20212963.00


Total 315 64063.62 101141.29 -225012.00 531718.00 20180008.00


Table 4-17. Total Pharmacy Net Pr


Pharmacy
Type


Independents

Chains


Total


Number of
Pharmacies


115

200


315


'ofit Percent by Pharmacy Type.


Total Pharmacy Net Profit

Standard
Mean Deviation Minimum Maximum
% % % %


-0 8 -40 14

5 6 -14 15


3 7 -40 15











Table 4-18. Prescription Department Net Profit Percent by Pharmacy
Type.


Pharmacy
Type


Independents

Chains


Total


Number of
Pharmacies


117

251


368


Prescription Department Net Profit

Standard
Mean Deviation Minimum Maximum
% % % %


1 10 -30 46

-0 9 -43 13


-0 10 -43 46


Table 4-19. Front-End Net Profit Percent by Pharmacy Type.


Front-End Net Profit Percent

Standard
Pharmacy Number of Mean Deviation Minimum Maximum
Type Pharmacies % % % %


Independents 114 -3 41 -21 147

Chains 200 7 8 -23 66


Total 314 3 26 -21 147










Table 4-19 shows the NP% for the front-end pharmacy operations.

The independents, on the average, show a loss of 3%, whereas the

chains show an average profit of 7%; the overall mean profit was 3%.

Difference between usual and customary and
Medicaid prices (UCMP-MRR)

This variable is the difference between the usual and customary

price charged and the Medicaid reimbursement rate which would have

been paid for the same prescription. The variable is abbreviated as

OIFF 1. Table 4-20 shows the means of DIFF 1 by type of pharmacy.

The mean for independents is $1.17, -$0.06 for chains, and $0.35 for

all pharmacies combined. These figures mean that the UCMP was higher

than MRR for independents and all pharmacies taken together, but not

for chains alone. An overall standard deviation of $1.34 indicates a

high variation of the value of DIFF 1 between different pharmacies.

The above section completes all the descriptive statistics for

the sample pharmacies and the dependent and independent variables used

in this research. The following sections will provide the statistical

results related to the different research questions which this study

is attempting to answer.



Research Hypotheses
Usual and Customary Versus Medicaid Reimbursement Rate

The first two research hypotheses relate to the differences

between the usual and customary prices charged (UCM4P) and the probable

Medicaid reimbursement rate (MRR) which would have been paid by

DHRS. Specifically, the first hypothesis looks at whether or not the















Table 4-20.


Table of Usual and Customary Price (UCMP) Minus Medicaid
Reimbursement Rate (MRR) by Pharmacy Type.


Standard
Pharmacy Number of Mean Deviation Minimum Maximum
Type Pharmacies $ $ $ $


Independents 114 1.17 1.36 -1.42 7.12

Chains 223 -0.06 1.12 -2.85 4.48


Total 337 0.35 1.34 -2.85 7.12


--










UCMP was greater than MRR. The second hypothesis asks whether or not

profits realized from usual and customary prescriptions (UCP) are

greater than profits from Medicaid participation (MCP). However, as

shown in Chapter III, after derivation of the second hypothesis the

final equation is similar to the first hypothesis. Thus, the

statistical form of these two hypotheses are


HO: UCMP = MRR


HA: UCMP > MRR


Tables 4-21 and 4-22 are computer outputs of "t" test performed

to test the above hypotheses. In the first table, the "t" test is for

all pharmacies together, whereas the second table shows "t" tests by

type of pharmacies. From Table 4-21, it can be seen that the null

hypothesis can be rejected in favor of the alternate hypothesis at a

significance level (2) of 0.01. Thus, for all pharmacies combined,

the null hypothesis is rejected. Therefore, the data support the

hypothesis that profits realized from usual and customary are higher

than those realized from Medicaid.

From Table 4-22 it can be seen that for independent pharmacies,

the null hypothesis is rejected at a p value of 0.01. Therefore, the

data support the hypothesis that profits realized from usual and

customary prescriptions are higher than those realized from Medicaid

prescriptions for independent Florida pharmacies.












Table 4-21. Paired t Test for UCMP and MRR for all Pharmacies.


Standard Standard Error
Mean Deviation of Mean
Variable T PR>:T: N $ $ $


DIFF 1 4.88 0.0001 339 0.35 1.34 0.07


Note: DIFF I = UCMP MRR.













Table 4-22. Paired t Test for UCMP and MRR by Pharmacy Type.


Standard Standard Error
Pharmacy Mean Deviation of Mean
Type T PR>:T: N $ $ $


Inde-
pendents 9.14 0.0001 114 1.17 1.36 0.13

Chains -0.74 0.4595 223 -0.06 1.12 0.08










On the contrary, the "t" test indicates that the null hypothesis

cannot be rejected at p=O.01 for chain pharmacies. Therefore, for

chains, the data show that there is no difference between profits

realized from usual and customary prescriptions and profits realized

from Medicaid prescriptions.

Price Comparisons for Specific Drug Categories

This hypothesis pertains to price comparisons on a per unit basis

for 17 specific drugs, consisting of 26 line items. This is in

contrast to the first two hypotheses whose price and profit

comparisons were performed on a per prescription basis. A single

prescription normally would contain several units of the drug. The

mean drug prices along with their standard deviation, maximum and

minimum values, and other statistical data can be found in Appendix

D. The first part gives the mean for individual drug categories for

all pharmacies combined, followed by the means broken down by pharmacy

type. The mean price for all pharmacies varied from a low of $0.05

for 1 milliliter of Amoxil Suspension (125 mg/5 ml) to a high of $1.36

for each capsule of Keflex (500 mg).

The research question which was answered in this hypothesis was

whether the unit price reimbursed by Medicaid was greater than that of

private-pay prescriptions for the 17 of the 200 fast-moving drug

items. Tables 4-23 and 4-24 provide the paired "t" test results which

answer this question. The first table performs the test for all

pharmacies together, and the second table performs the same test by

type of pharmacy. In both tables, the variable DIFF is equal to the

difference between the unit Medicaid reimbursement price and the unit











Table 4-23. Paired t Test for Hypothesis for all Drugs Combined.


Standard Std Error
Number of Mean Deviation of Mean
Variable Prescriptions $ $ $ T PR>:T:


DIFF 2029 0.03 0.14 0.003 5.85 0.0001


Note: DIFF = MRR/unit UCMP/unit.













Table 4-24. Paired t Test by Pharmacy Type for all Drugs Combined.


Standard Std Error
Pharmacy Number of Mean Deviation of Mean
Type Prescriptions $ $ $ T PR>:T:

Inde-
pendents 646 -0.02 0.08 0.003 -5.53 0.0001

Chains 1272 0.04 0.17 0.005 8.10 0.0001










usual and customary price, i.e.,


DIFF = MRR/unit UCMP/unit.

The "t" test for all pharmacies was significant at p=0.01 as

found in Table 4-23. Therefore, the data reject the null hypothesis

that the unit Medicaid price was equal to the unit private-pay

price. The research hypothesis that Medicaid reimbursement rate per

unit of drug item is greater than those charged to private-paying

patients was accepted.

A similar finding was observed for all drugs together when broken

down by pharmacy type--independents and chains. This can be found in

Table 4-24. As can be seen from this table, of the total 2,029

audited prescriptions, 646 came from independents, 1,272 from chain

pharmacies, and the balance of 111 were from pharmacies whose

affiliation was unknown. One observation to note is that the mean

DIFF for independents was a negative amount (-$0.0165). This is

indicative of the finding that unit price for private-pay was greater

than unit Medicaid price for independent pharmacies. The research

hypothesis that Medicaid reimbursement rate per unit of drug item is

greater than those charged to private-paying patients was accepted for

chains.

Statistical tests were also performed on individual drugs for all

pharmacies together and also by pharmacy type. The computer print-out

of these data can be found in Appendix E. The "t" test for all

pharmacies combined was significant at p=O.01 for 12 drug items out of

a total of 26 line items. Therefore the research hypothesis that the










per unit Medicaid price was higher than the usual and customary price

was accepted for these 12 line items. On the other hand, for the

balance of 14 line items, there was insufficient evidence to indicate

that Medicaid unit price was different from usual and customary unit

price. There was insufficient evidence to indicate any differences

between single-source products (Darvocet-N 100, Keflex, Tagamet,

Valium, and Zantac) and multi-source products (all the other drugs).

With respect to individual drugs for independent pharmacies, the

"t" tests were significant at _=0.01 for only 4 out of 26 drugs.

Tnerefore, for these four drugs (Bactrim DS, Keflex 250 mg, Rufen, and

Septra DS) the null hypothesis is rejected. Thus the research

hypothesis that unit Medicaid price is greater than unit usual and

customary price is accepted for these four drugs.

Looking at individual drug items for chains, the evidence

indicates a significant "t" test at V=0.01 for 16 of the 26 line

items. Thus for the majority of the drugs, the research hypothesis

that unit Medicaid price is greater than usual and customary price is

accepted.

Net Profit Comparisons

The last research hypothesis asks the question whether the net

profit percent before taxes (NP%) for the prescription department

operations is greater than that of the front-end operations.

Statistical "t" tests were performed for all pharmacies combined and

also by type of pharmacy. The results can be found in Tables 4-25 and

4-26. The variable OIFF is the difference between prescription

department NP% (RXNPPCT) and the front-end NP% (FENPPCT). The mean












Table 4-25. Paired t Test for Net Profit Percent for all Pharmacies.


Standard Standard Error
Number of Mean Deviation of Mean
Variable Pharmacies % % % T PR>:T:


DIFF 315 -2.4 3.0 1.7 -1.41 0.1607


Note: DIFF = RXNPPCT FENPPCT.















Table 4-26. Paired t Test for Net Profit Percent by Pharmacy Type.


Standard Standard Error
Pharmacy Number of Mean Deviation of Mean
Type Pharmacies % % % T PR>:T:


Inde-
pendents 114 3.1 4.7 4.4 0.70 0.4834

Chains 200 -5.5 1.0 0.7 -7.71 0.0001










DIFF was -2.4%. The paired "t" test at p=0.01 was not significant.

Therefore the research hypothesis that prescription department NP% is

greater than front-end NP% cannot be accepted.

Table 4-26 shows the same "t" test performed separately for

independent and chain pharmacies. The results indicate that at

V=0.01, the data fail to reject the null hypothesis for
independents. The p_ value was significant for chains. Therefore, the

null hypothesis is rejected for chains. Thus the research hypothesis

that prescription department NP% is different from front-end NP% can

only be accepted for chains.

This concludes the results of all the research hypotheses for

this study. Results of further analyses will be presented in the

remainder of this chapter. They pertain to an examination of the

effect of pharmacy characteristics on the dependent variables.



Effect of Pharmacy Characteristics on Dependent Variables

A priori, the intention was to produce a regression equation in

order to explain the dependent variable DIFF_1 (i.e., difference

between the mean price charged to private-pay customers and the mean

Medicaid reimbursement rate). In order to identify the relevant

variables to be included in a regression model, a correlation matrix

of all relevant variables was produced. This was done in order to

check for high correlations between independent variables in order to

avoid multicollinearity problems. The correlation matrix for all

pharmacies combined can be found in Appendix F. The results indicated

significant correlation at =0O.05 among most of the independent










variables. Thus, it was deemed infeasible to utilize the majority of

the independent variables in a regression model due to presence of

multicollinearity. The only insignificant correlation between

continuous independent variables was between total prescription volume

and Medicaid volume (correlation of 0.04 at a p value of 0.43). A

stepwise regression was performed with DIFF 1 (UCMP-MRR) as the

dependent variable and two independent variables (total prescription

volume and Medicaid volume), plus some categorical independent

variables (pharmacy type, delivery, advertising, and computers) from

the survey. The results indicated that only pharmacy type was the

most significant variable with an R2 of 0.17. Two other variables

came into the model, namely delivery and advertising. However, the

increment in R2 due to these two variables was only 0.029, i.e., an R2

of 0.20 was obtained. Also, as stated earlier, there were not enough

pharmacies in all the cells of delivery or advertising and, hence,

these variables were unacceptable.

After discussion with the statistical consultant (M. Conlin,

personal communication, 1986), it was decided to perform a Proc GLM

procedure with the following model:


DIFF_1 = B0 + 81 ST + 82 MEOVOL + 83 ST*MEDVOL + e .


The reasoning behind this was that Medicaid volume and pharmacy

type were the two most important independent variables. The presence

of an interaction term was very likely, since Medicaid volume was

found to be associated with the type of pharmacy. Also, the

correlation coefficient between DIFF 1 and MEDVOL and DIFF 1 and ST










was -0.43 and 0.18, respectively. These values were highly

significant.

The results of this regression model can be found in Table

4-27. The model has an R2 of 0.218, the F test is significant at

p<0.0001. The hypothesis that 83 (the interaction parameter) is

significantly different from zero is supported, since an F of -2.77 is

highly significant (p>0.0059). Therefore, it is useful to include the

interaction term. The regression model is thus as follows:


DIFF 1 = -0.24 + 1.60 ST + 0.0002 MEDVOL 0.0003 ST*MEDVOL .


This model explains 21.8% of the variation in the value of DIFF-1.

As a result of the multicollinearity problem, the researcher was

advised about investigating the possibility of performing factor

analysis. On consultation with a statistician (T. Sincich, personal

communication, 1986), the researcher was apprised that factor analysis

would only identify similar groups of independent variables, and

nothing further of value could be gained from this procedure in order

to explain the dependent variable (DIFF 1). Therefore, factor

analysis in no way would help to identify the effect of independent

variables on the dependent variable. Thus, the possibility of

performing factor analysis was abandoned.

Finally, due to all the above problems, it was decided to look at

the values of the dependent variables at different levels of some of

the more important independent variables. Tables 4-28 through 4-30

are three-way tables showing the mean values of DIFF 1 (UCMP-MRR) for



















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