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 Executive summary
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 Study approach and methods
 Bivariate analyses
 Multivariate analyses
 Reference
 AHCA disease hierarchy and disease...
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Title: Utilization analysis of the Minority Physician Network and Provider Service Network programs
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Table of Contents
    Title Page
        Page 1
    Table of Contents
        Page 2
    Executive summary
        Page 3
    Background on Florida's medicaid pilot programs
        Page 4
        Page 5
    Study approach and methods
        Page 6
        Page 7
        Page 8
        Page 9
        Page 10
        Page 11
        Page 12
    Bivariate analyses
        Page 13
        Page 14
        Page 15
        Page 16
        Page 17
        Page 18
        Page 19
    Multivariate analyses
        Page 20
        Page 21
        Page 22
        Page 23
        Page 24
        Page 25
        Page 26
        Page 27
        Page 28
        Page 29
        Page 30
        Page 31
    Reference
        Page 32
    AHCA disease hierarchy and disease definitions
        Page 33
        Page 34
        Page 35
        Page 36
        Page 37
        Page 38
        Page 39
        Page 40
    Tables
        Page 41
        Page 42
        Page 43
        Page 44
        Page 45
        Page 46
        Page 47
        Page 48
        Page 49
        Page 50
        Page 51
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        Page 53
        Page 54
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Full Text



Utilization Analysis of the Minority Physician Network
and Provider Service Network Programs

Contract M0508, Deliverable 8:3




Prepared by
Christy H. Lemak, PhD
Allyson G. Hall, PhD
Praveen Saxena
Jianyi Zhang
Monica Albertie
Lorna P. Chorba
Florida Center for Medicaid & the Uninsured
University of Florida

Christopher Johnson, PhD
School of Rural Public Health
Texas A&M University





Florida Center for Medicaid & the Uninsured
College of Public Health and Health Professions
University of Florida
352-273-5059

Sponsored by
The Agency for Health Care Administration


Florida Center for MedFcald and the Uni sured
,-. .a1S.BC I ,December 2005








Table of Contents


E executive Sum m ary ...................................................................... ................................ 3

Background on Florida's Medicaid Pilot Programs.......................... ...................4

Part I: Study Approach and Methods........................... ................................. 6

D ata ............................................................. .. ................................ 6
M ea su re s .............. .... .................................................................................... ... .. ..
U utilization T ypes................................................. .............................................. 9

Part II: Bivariate A nalyses........................................................................................... 13

Bivariate A nalyses R results ...................... .... ......... ..................... ...................13pa

Bivariate Analyses Conclusions................ ....................... ................... 19

Part III: Multivariate Analyses .......................................................................................20

A n alytic M eth ods ...................................................................... ... ......................... 20
Interpreting R results .............................................. ................................................. 21
M ultivariate R results ...................... .. .. ......... .. .......................... ...................22

M ultivariate C conclusions .......................................................... ................... 30

References ........................ .............. .. ..... ...... ............ ......32

Appendix I: AHCA Disease Hierarchy and Disease Definitions ..............................................33

A p p en d ix II: L ist of T ab les ................................................................................ .....................4 1








Executive Summary


This study examines medical utilization in two of Florida's pilot programs that were designed to
explore alternatives to traditional Medicaid HMO and primary care case management (PCCM) models:
the provider service network (PSN) demonstration (South Florida Community Care Network) and the
minority physician network (MPN) pilot (Florida NetPass and PhyTrust).

We examine claims data to determine whether new models that typically use local medical
management programs, sophisticated information systems, and physician financial incentive programs
achieve different utilization than that of MediPass. Because programs were implemented in different
parts of the state at different times, we include utilization data for April 2003 March 2004 for Palm
Beach, Broward, and Dade Counties and June 2003 March 2004 for Medicaid Areas 5 and 6.

The study includes four types of medical utilization: emergency room, inpatient, pharmacy, and office
visits. Each type is measured in multiple ways: emergency room (all visits and those for "urgent"
conditions), inpatient admissions (all admissions and those for "ambulatory care sensitive" conditions)
and inpatient days, pharmacy claims (all and those for generic drugs), and office visits (defined in three
different ways).

We used bivariate analyses to analyze beneficiary demographic information and utilization by plan
type and county. Next, we performed negative binomial multivariate regressions for each utilization
type and county. In these models, we controlled for eligibility type (TANF, SSI, Other), age and
gender, and, as a proxy for risk adjustment, three types of chronic disease (asthma, diabetes,
hypertension).

In most cases, the pilot programs exhibit lower levels of utilization than MediPass. Specifically,
compared to MediPass, both Florida NetPass and PhyTrust had lower utilization for emergency room
visits, pharmacy, and ambulatory care sensitive conditions, and higher levels of utilization for office
visits. For the most part, PhyTrust members experienced fewer inpatient admissions and inpatient days
than MediPass patients. Compared to MediPass, the PSN had lower utilization for pharmacy and
office visits, but higher emergency room and inpatient utilization.

It is important to note, however, that we did not examine the specific managed care mechanisms used
by each plan (e.g., when financial incentive plans became operational, what specific areas were
included in medical management, how often information was shared with physicians, etc.). The three
organizations studied here-PhyTrust, Florida NetPass, and the South Florida Community Care
Network-have different contracts with the Florida Agency for Health Care Administration (AHCA or
the Agency), different management models, different "shared savings" methodologies, and many other
differences. Examining how specific aspects of each model affect specific types of utilization are
beyond the scope of this study.

We also found that the models did not exhibit uniform effects in all parts of the state. The most
consistent findings were in the larger counties of Miami-Dade, Broward, and Palm Beach.

In conclusion, we believe that this study coupled with the cost analysis done earlier begins to build a
body of evidence that suggests that these alternative models of care may be changing utilization
patterns for Medicaid beneficiaries.








Background on Florida's Medicaid Pilot Programs


As Medicaid expenditures continue to escalate, states are looking for new, cost-effective ways to
finance and deliver services. Often, pilot or demonstration projects are used to try new models in a
limited way before expanding these models statewide. In Florida, several pilot programs are underway
to explore alternatives to traditional Medicaid HMO and primary care case management (PCCM)
models.

Some of Florida's innovative programs involve networks of providers who manage care for a group of
Medicaid beneficiaries. A key question of the pilot phase is whether providing local medical
management services improves access to and quality of Medicaid services, and, at the same time,
decreases costs.

The PSN demonstration began in 2000 when the Agency contracted with the South Florida
Community Care Network (SFCCN). SFCCN includes the Public Health Trust (Jackson Health
System), Memorial Health System, and the North Broward Hospital District. In 2001, AHCA initiated
the MPN program, contracting with two physician-owned organizations in which the majority of
physicians are members of racial and ethnic minority groups: Florida NetPASS and PhyTrust. Each
pilot program consists of a network of primary care physicians (PCPs) and manages an enrollment of
MediPass beneficiaries.

The State had several goals as it established these programs. For example, the legislation language
regarding the MPN program (GAA FY 2001-2002), specified
The development of improved approaches to managing access and utilization,
The establishment of physician-owned and -operated managed care organizations with
Medicaid experience,
The establishment of at least one pilot that is a predominately minority physician network, and
The utilization of a shared savings payment methodology that is budget neutral.

Researchers at the University of Florida have conducted comprehensive evaluations of these programs.
Findings for the PSN evaluations are available through the Agency's web site at
http://ahca.myflorida.com/Medicaid/Research/Projects/psn/reports.shtml, while details of the MPN program
can be accessed at http://ahca.mvflorida.com/Medicaid/Research/contracts/m0424/m0424.shtml.

In general, the evaluations studied the "cost savings" question in three ways. First, the actual medical
expenditures in the networks were compared to Florida's PCCM program (MediPass) using standard
regression modeling approaches. Second, an analysis of the shared savings achieved by the networks
was conducted using the payment methodology defined in their contracts with the State (essentially
comparing expenditures to a standard upper payment limit and accounting for administrative fees
paid). Third, the time and effort to administer these programs by the State were estimated.

Overall, the evaluations found some cost-savings associated with the network programs relative to
MediPass. The savings were attributed to the enhanced utilization management and sophisticated
information technologies employed by the network organizations. In general, providers were very
satisfied with the programs.

The previous evaluations did not, however, comprehensively examine medical utilization and,
specifically, whether and how the local management of Medicaid providers might affect patterns of
utilization (and ultimately costs). In this research, we conduct a comprehensive analysis of utilization








in each pilot program and MediPass. Ideally, this study would include all components of Florida
Medicaid. However, because the Agency does not collect utilization data from Medicaid HMOs, we
were unable to include data on Medicaid HMO utilization in this study.

This study was motivated by the key findings from prior evaluations of Florida's demonstration
programs. For example, in our final evaluation report on the MPN pilots, we noted that the most
important aspects of the MPN Program include the following:
The private and "local" aspects of the MPNs offer opportunities to monitor and support
providers in ways the current MediPass program has not achieved.
The MPNs appear to make MediPass work better by providing providers with timely and
important beneficiary information.
The MPNs manage their PCP networks locally and offer improved communication with the
Agency.
MPN physicians are extremely satisfied with the program relative to their experience with
MediPass and Medicaid HMOs.

We also reported that the MPNs use an information approach to managing care and working with the
PCPs in their networks. They distribute periodic performance reports to their physicians. Each has
invested in computer systems to track and analyze beneficiary and provider data. The organizations
use sophisticated, proprietary information systems and highly qualified staff to work with the data
provided by the Agency monthly. The information system tools and managed care experience of these
organizations are a key strength of the MPN and PSN models.

In addition, the MPNs were authorized to institute physician incentive plans that were in compliance
with federal regulations regarding physician incentives utilized by Medicaid managed care
organizations. For the first time in Florida, Medicaid physicians could receive financial rewards for
achieving specific access, quality, and utilization targets.

In this research, we examine claims data to determine whether local medical management
programs, sophisticated information systems, and physician financial incentive programs matter.
That is, are there differences in utilization for the pilot programs relative to MediPass?

Results of these analyses will inform important policy decisions and implementation activities for
AHCA. The PSN and MPNs remain operational today. Further, the Florida legislature recently voted
to give the Agency authority to develop a waiver to develop reforms to the Medicaid program. A key
element of the reform proposal is the formation of delivery networks that will have greater flexibility
in the design of benefit packages. It is anticipated that these delivery networks will look like the PSN
model. Understanding the performance of the State's previous experiments in these areas is essential
to making appropriate policy decisions about the structure of Florida's Medicaid program in the future.








Part I: Study Approach and Methods


Our overall approach is to compare utilization in the MPNs (PhyTrust and Florida NetPass), PSN
(SFCCN), and MediPass. In bivariate analyses, we present data on demographic characteristics and
utilization by county and eligibility type. In multivariate analyses, we control for important member
characteristics to see differences in utilization by plan type.

It is important to note that we do not examine specific contractual obligations of each pilot (e.g., what
types of patients are eligible for the specific program); the unique managed care mechanisms in place
in the pilots (e.g., financial incentive plans for physicians, provider selection issues, reporting
practices), or any other specific elements of each pilot.

Instead, we seek to answer the overall research question: Do the MPN and PSNprograms
achieve different levels of medical utilization for Medicaid patients?

Methods

Data

We worked with AHCA staff to obtain the following data needed for the analyses: pharmacy claims,
emergency department claims, inpatient hospital claims, physician office visit claims, and member-
months files. A member-month is defined as the total number of days of enrollment, divided by 30
days, which is rounded to the nearest month (e.g. 30.2 rounded to 30).

Following is a summation of the data used for the analyses:

Table 1: Summation of Data Used for the Analyses


Total Users 455.125
Total Member Months 3,267,179
Total ER Visits (#) 178,850
Total Pharmacy Claims (#) 4,554,706
Total Office Visits (#) 1.270.014








For this study, we included one full year of Medicaid paid claims data for Palm Beach, Broward, and
Dade Counties (where programs were established during that time) and ten months of data for Areas 5
and 6 (where the MPNs were beginning to become operational in 2003). The following table (Table 2)
summarizes the programs and claims dates covered in this research. The dates refer to dates of service.

Table 2: Geographies and Time Periods Used in the Study

S Programs in Operation
Geographic Area Progra i Operatin Time Period Studied
(Approx. Start Date)

Areas 5 and 6 (All Counties) MediPass, NetPass (May 2003) June 2003 March 2004
PhyTrust (May 2003)
MediPass, NetPass (Nov. 2001),
Broward County, Miami-Dade County PhyTrust (Nov. 200April 2003 March 2004
PSN (Dade: March 2000,
Broward: April 2000)

Palm Beach County MediPass, NetPass (Nov. 2001) April 2003 March 2004


We used the member-months data and a database of recipient ID by month to identify paid claims for
each MPN organization, the PSN, and MediPass (excluding the others). We did not exclude any
eligibility categories. We maintained separate databases for each type of utilization: inpatient
hospital, emergency room, office visits, and pharmacy. Each claim is therefore identified with a
particular plan, date, and county.

For member-months, we used beginning and ending eligibility dates. For utilization, we used the first
claim date. Dollar amounts refer to claim paid amounts.

Measures

Member Characteristics:

Members. We present information on total Medicaid members, total users (those with a claim above
the PCP monthly case management fee), and total member-months. A member-month is defined as the
total number of days of enrollment, divided by 30 days, which is rounded to the nearest month (e.g.
30.2 rounded to 30). In addition, results are presented as per 1,000 member months for ease of
interpretation.

Geographic Area. We included Florida counties where the MPNs and PSN were operating (see Table
2 above). Claims identified with a particular plan in a geography where that plan did not operate were
excluded from the analyses (for example, a PSN claim from Area 5 would be excluded from the
analysis).








Age and Gender. We present information for eight age-gender combinations or "bands" that were
defined by AHCA staff. In the multivariate models, the referent category is the final category (age
greater than 54, both genders). The age/gender bands are shown in Table 3.

Table 3: Age/Gender Bands


Less than 1 Both genders
1 5 years Both genders
6 13 years Bolh genders
14 -20 years Female
14 -20 years Male
21 54 years Female
21 54 years Male
Greater than 54 Both genders

Race/Ethnicity. The following categories were used to describe member race/ethnicity: Hispanic,
Black, White, and Other Race. In the multivariate models, the referent category is White.

Eligibility Category. We include three eligibility types: Temporary Assistance for Needy Families
(TANF), Supplemental Social Security Income (SSI), and Other Eligibility Category (including, for
example, SOBRA children, foster children or subsidized adoptions, SSI with Medicare). In the
multivariate models, TANF is the referent group.

Chronic Disease State. As a proxy for risk adjustment, we include an indicator of members having
one or more chronic disease states. The Agency analyzed the claims for the first (June 2003) and last
month (March 2004) of our study to determine which members were identified as having one or more
of eight chronic illnesses. For each of the illnesses listed below, each member was identified as having
the illness (Yes), not having the illness (No), or unknown with respect to the illness (Unknown). That
is, "unknown" includes beneficiaries who were (1) not specifically identified by the Agency as having
the disease or not having the disease or (2) not in any Medicaid program during the months analyzed
by the Agency for this purpose. AHCA's disease hierarchy and definitions for these diseases are
presented in Appendix I:

HIV/AIDS
SHemophilia
Sickle Cell
End Stage Renal Disease (ESRD)
Congestive Heart Failure (CHF)
Diabetes Mellitus
Asthma
SHypertension

We created indicator variables that show whether a person was identified as having the disease at the
beginning and/or end of the study period (e.g., if Yes once or twice, this indicator equals Yes). As
shown in Table 4, the number and percent of members who are definitively known to have these
diseases range from 0.0% (hemophilia in PSN) to 6.4% (hypertension in PSN). In our multivariate
analyses, we include the three disease states with consistently larger member populations (diabetes,








asthma, and hypertension), comparing those who are known to have the disease at one point or the
other to those who do not have the disease or are unknown with respect to the disease.

Table 4: Members by Disease State and Plan Type




Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
HIV/AIDS No 364,497 65.70 56,493 83.77 71,135 76.6 28,402 63.68
Yes 4,681 0.84 332 0.49 644 0.69 168 0.38
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
HEMOPHILIA No 369,086 66.53 56,807 84.24 71,771 77.28 28,570 64.05
Yes 92 0.02 18 0.03 8 0.01 0 0
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
SICKLE CELL No 367,418 66.23 56,577 83.89 71,456 76.94 28,279 63.40
Yes 1,760 0.32 248 0.37 323 0.35 291 0.65
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
ESRD No 367,381 66.22 56,554 83.86 71,385 76.87 28,512 63.92
Yes 1,797 0.32 271 0.40 394 0.42 58 0.13
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
CHF No 365,260 65.84 56,382 83.61 71,219 76.69 28,493 63.88
Yes 3,918 0.71 443 0.66 560 0.60 77 0.17
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
DIABETES No 357,643 64.46 55,630 82.49 70,224 75.62 28,353 63.57
iYes 11,535 2.08 1,195 1.77 1,555 1.67 217 0.49
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
ASTHMA No 344,091 62.02 54,927 81.45 67,759 72.96 27,203 60.99
Yes 25,087 4.52 1,898 2.81 4,020 4.33 1,367 3.06
Unknown 185,610 33.46 10,613 15.74 21,088 22.71 16,034 35.95
HYPERTENSION No 348,436 62.81 54,290 80.50 68,779 74.06 25,698 57.61
Yes 20,742 3.74 2,535 3.76 3,000 3.23 2,872 6.44

Utilization Types

Emergency Room Utilization. We included measures of the total number of emergency room visits
and the number of emergency room visits for urgent conditions. We used an AHCA-provided list of
over 6,000 diagnoses that identify "Urgent" ER visits. Due to data limitations at the Agency, ER data
can only be presented for November 1, 2001 to September 29, 2003, which could limit the validity of
results for some areas.

Pharmacy Utilization. We measured pharmacy utilization in two ways: total number of pharmacy
claims and number of generic pharmacy claims. We used an indicator in the AHCA data to identify
Generic Products (the GPI).








Inpatient Hospital Utilization. We analyzed the total number of inpatient admissions and the total
number of inpatient days.

In addition to these inpatient utilization measures, we also identified inpatient claims with
"Ambulatory Care Sensitive" (ACS) conditions. Research shows that some inpatient admissions may
be identified as related to inadequate access to ambulatory care services.

We identify ACS admissions in three ways. First, we used the standard algorithm developed by John
Billings at NYU (Billings 2003, Billings and Cantor 2001, Billings et al. 1996, Bindman et al. 1995).
We call this method the "standard" ACS definition.

Second, we used a method previously used by Florida Agency for Health Care Administration
("AHCA"). Finally, we created a way to indicate if the inpatient claim was identified as an ACS
admission using either method ("Either"). The following table (Table 5) lists the conditions and
definition codes used to identify ACS admissions using each method.

Table 5: Definitions "Ambulatory Care Sensitive" Admissions


AHCA Definition Codes


Standard Definition
Codes


Standard Definition Notes


540.0, 540.1

493


Cellulitis


Congestive Heart
Failure

Diabetes

Gangrene
Hypokalemia


Immunizable
Conditions

Malignant
Hypertension


681,682


428, 402.01, 402.11,
402.91

250.1, 250.2, 250.3, 251

785.4


681,682, 683, 686


428, 402.01,402.11,
402.91, 518.4

250.1, 250.2, 250.3,
250.8, 250.9, 250.0
NA


Exclude cases with a surgical procedure
[01-86.99], except incision of skin and
subcutaneous tissue [86.0] where it is the
only listed surgical procedure
Exclude cases with the following surgical
procedures: 36.01, 36.02, 36.05, 36.1,
37.5, or 37.7


276.8


032,033, 037,072, 045,
055

401.0, 402.0, 403.0,
404.0, 405.0, 437.2


033,037, 045,
320.0, 390, 391
401.0, 401.9,
402.00, 402.10,
402.90


320.2 age 1-5 only

Exclude cases with the following
procedures: 36.01, 36.02, 36.05, 36.1,
37.5, or 37.7


Condition


Ruptured
Appendix
Asthma









Table 5: Definitions "Ambulatory Care Sensitive" Admissions- continued


Condition


Pneumonia

Pyelonephritis


Condition


Perforated Ulcer


Congenital syphilis
Grand mal status
and other epileptic
convulsions
Severe ENT
infections

Tuberculosis

Chronic
obstructive
pulmonary disease

Angina

Skin grafts with
cellulites
Hypoglycemia
Gastroenteritis
Kidney/urinary
infection
Dehydration -
volume depletion
Iron deficiency
anemia
Nutritional
deficiencies
Failure to thrive
Pelvic
inflammatory
disease

Dental Conditions


AHCA Definition Codes


481,482,483,485,486

590.0, 590.1, 590.8

AHCA Definition Codes

531.0, 531.2, 531.4,
531.6, 532.0, 532.2,
532.4, 532.6, 533.0,
533.1, 533.2, 533.4,
533.5, 533.6


Standard Definition
Codes

481,482.2. 482.3.
482.9, 483, 485, 486

NA
Standard Definition
Codes


Standard Definition Notes

Exclude cases with secondary diagnosis
of sickle cell (282.6) and patients < 2
months


Standard Definition Notes


Secondary diagnosis for newborns only


382, 462, 463, 465,
472.1
011 (Pulmonary),
012-018 (Other TB)

491,492, 494, 496,
466.0

411.1, 411.8, 413

DRG 263, DRG 264


Exclude otitis media cases [382] with
myringotomy with insertion of tube [20.01]



Acute bronchitis [466.0] only with
secondary diagnosis of 491, 492, 494, 496

Exclude cases with a surgical procedure
[01-86.99]

Exclude admissions from SNF/ICF


251.2

558.9


590, 599.0, 599.9


276.5


280.1, 280.8, 280.9

260,261,262,
268.0, 268.1
783.4


Examine principal and secondary
diagnoses separately
Age 0 5 only, and examine principal and
secondary diagnoses separately
Examine principal and secondary
diagnoses separately
Age < 1 only
Women only denominator- exclude
cases with a surgical procedure of
hysterectomy [68.3-68.8]


521,522,523,525,
528








Office Visit Utilization. Three different methodologies were used to identify claims for medical
office visits, as described in Table 6 below.

Table 6: Office Visit Definitions


Method Definition

Procedure Codes 99201-99215, regardless of
I Procedure Codes Only location


For place of service 11 (physician office) or 72 (rural
II Expanded Procedure
S e and Pace o health clinic), Procedures Codes 99201-99215 +
Codes and Place of
Service 99385-7, 99396, or 99397 (Adult Health Services) +
99391-99394 (Child Health Check Up)


Procedures Codes 99201-99215 + 99385-7, 99396,
or 99397 (Adult Health Services) + 99391-99394
III -xand Pro ure (Child Health Check Up), excluding places of services
I xpane ocee 12 (home), 21 (inpatient hospital), 22 (outpatient
Certain PEaclsug hospital), 23 (ER), 31-33 (SNF, NH), 34 (Special
Certain Places of
Treatment Facility), 41 (Ambulance), 55 (Resident
Service
Treatment Center), 62 (Comprehensive Outpatient
Rehab), 65 (Independent Kidney Center), and 81
(Independent Lab)








Part II: Bivariate Analyses


In the bivariate analyses, we analyzed beneficiary demographic information and utilization by plan
type and county. In each utilization table, we used the following indicators.

Emergency Room Utilization. We present data on the number of Emergency Room visits per 1000
members and the total amount paid for ER visits per 1000 members. We also used an AHCA-provided
list of over 6,000 diagnoses that identify "Urgent" ER visits. Presented in each table is the percent of
all emergency room visits that were "urgent." Due to data limitations at the Agency, ER data is
presented for November 1, 2001 to September 29, 2003, which could limit the validity of results for
some areas.

Pharmacy Utilization. We present data on number of pharmacy claims per 1000 members. We also
used an indicator in the data to identify Generic Products (GPI). We present the percentage of all
pharmacy claims that were generic.

Inpatient Hospital Utilization. We present the total number of inpatient admissions per 1000
members and the total number of inpatient hospital days per 1000 members. We identified inpatient
claims with "Ambulatory Care Sensitive" conditions using "standard" and "AHCA" definitions, as
well as an indicator that reflects an ACS admission for either method. Tables include a measure for
each of these per 1000 members.

Bivariate Analyses Results

Table 7 (below) displays overall beneficiary demographic information for all members in all combined
areas included in the analysis. This data reflects beneficiaries who were eligible at any point during
the study time period.








Table 7: Beneficiary Demographics (All Study Areas for MediPass, MPN, and
PSN) June 2003 March 2004


June 2003 March 2004
Total Percent
Female 244,025 54%
Male 211,100 46%
Total 455,125
Age < 1 both genders 20,562 5%
Age 1 5 both genders 118,628 26%
Age 6 13 both genders 121,489 27%
Age 14 20 female 34,912 8%
Age 14- 20 male 34,060 7%
Age 21 54 female 60,756 13%
Age 21 54 male 29,828 7%
Age > 54 both genders 34,890 8%
Total 455,125
White 100,821 22%
Black 121,876 27%
American Indian 156 0%
Oriental 2,409 1%
Hispanic 168,316 37%
Other 61,547 14%
Total 455,125
SSI 83,569 18%
TANF 159,137 35%
Other 212,419 47%
Total 455,125


Table 8, shows beneficiary demographic information by county, and reflects some variation in these
characteristics by county. This data reflects beneficiaries who were eligible at any point during the
study time period. For example, the percentage of Hispanic members (in this study) is 57% for
Miami-Dade County (Area 11) and 9% in Pasco County (Area 5). The percentage of members with
SSI eligibility is 22% in Pasco County (Area 5) and 6% in Hardee County (Area 6). There is less
variation in the age and age/gender distribution across the geographic areas included in the analyses.







Table 8: Beneficiary Demographics by County (All Study Areas)

June 2003 March 2004 (Areas 5, 6)
April 2003 March 2004 (other areas)
6AreaSi 5 5 6 66 6 9 10 11

Area 1 11 I

County o4%I 3% % 54%
O y-- -.o 5Ai 54% 535
54% i 52% 5 o - o 47% %i 47% 46%
M a le _ _ _ __-- i | i j--- ---
Female 48% 47% 46% 45% 46% 47% 46%


Age both genders % 4% 5% % 6% 4% 6% 5% 5% 4%
Age 5 both genders 28% 4% 24% 25%9 310. 30% 24%
Age 1-13 both genders 2% 2% 29% 25% 28 26% 29% 29 25%

Age 14-0 fale % 8% 7% 8% 9% ......................... 8% ...
Age 6-13 both genders 27% 30 3% 8% 8% o
Age 14-20 male 8%i 8%% % % 7% 8% 7
o 8Yo 71%o 15%
Age 21-54female 18% 11 9% 13% 16 1 7% / 5% 15
I 6% 5% 6. 7% 7%,0 7
Age 21-54 male 8% 7 1 4% 56 % % 5 1
6% 5%, 2% 4% 7%: 4%4i %
Ae > 54 both enders


BlAmerican Indian 0k0 000 00 0o 000 00o 00. 00,0 0% 0%
American Indianl 1 0% 0 0% 0I 0d. 1% 0%
HOriental 0 120 480 2600 290, 2209 190. 2800 21% 57%
Hispac 7% 12 o 8%/ 8% 120 14% 16%

ST M 22%9 l6 644 16% 52 18 ,78 4 % 120 20
TAN i "~-~6 52% 3



White 65% 3 446% % 22%
Otheria I ndia 1203 %,89


TOtal Other Members 5,609 20, 4,842 2,76716,778 2,604 7,868 22,963 42,73 96,116
Total OtherMember 5s








Utilization by County


Table 9 compares utilization by county. There are observed differences in utilization by county, as
described here.

Emergency Room Utilization. In aggregate, urgent emergency room visits accounted for 56% of all
emergency room visits in the counties studied here, with a low of 50% in Miami-Dade County and a
high of 69% in Polk County. Pasco County had the highest ratio of ER visits per 1000 members
(549.8); Hillsborough County had the lowest ratio (395.8).

Pharmacy Utilization. The ratio of pharmacy claims/1000 members ranges from a low of 5,709 in
Hardee County to a high of 14,638 in Miami-Dade County. There is very little variation in the
percentage of pharmacy claims that were for generic drugs (42% in Miami-Dade and in Broward, 47%
in Pasco County).

Inpatient Utilization. There is variation across the counties included in this analysis for the number
of inpatient admissions and patient days per 1000 members, from a low of 46.0 admits/1000 and 153
days/1000 in Hardee County to a high of 124.8 admits/1000 and 677.2 days/1000 in Miami-Dade
County. For Ambulatory Care Sensitive (ACS) admissions, we also see variation across the state. For
the Standard ACS definition, the highest rate/1000 is seen in Highlands County (29.2) and the lowest is
in Hardee County (15.5). Using the definition of ACS developed by AHCA, Miami-Dade County has
the highest rate/1000 (14.2) and Pinellas has the lowest rate (7.9).









Table 9: Utilization Indicators by County (All Study Areas)


June 2003 March 2004 (Areas 5, 6)
April 2003 March 2004 (Other areas)


Area 5 5 6 6 6 6 6 9 10 11

I 3 j I I
0 II I | I

< -j 0 -J CO <
County TOTAL 0- I I I 0 0
Total Users 453,494 14,640 39,063 7,266 5,951 46,835 7,504 20,613 42,083 78,253 198,168

Total Member Months 3,267,179 105,591 269,543 50,544 41,773 320,860 51,750 133,979 364,025 638,333 1,735,446

Total ER Visits 178,850 8,144 16,077 3,380 2,800 18,690 3,299 9,502 20,160 34,148 83,085

Total Urgent ER Claims 100,439 5,047 9,670 2,207 1,795 12,278 2,083 6,569 11,380 18,483 41,519

% Urgent ER (Urgent/ER) 56% 62% 60% 65% 64% 66% 63% 69% 56% 54% 50%

ER Visits/1000 Members 393 549.8 407.7 454.9 467.2 395.8 433.6 456.3 461.3 419.4 406.1

Total Pharmacy Claims 4,554,706 168,153 320,539 42,420 47,921 420,265 54,614 139,122 383,017 624,274 2,995,037

Pharmacy/1000 Members 10,007.60 11,352.50 8,128.50 5,708.50 7,996.20 8,900.90 7,178.50 6,681.50 8,765.10 7,667.40 14,637.70
Total Generic Pharmacy
Total Generic Pharmacy 1,966,397 79,250 144,967 18,106 20,817 192,211 25,302 63,756 165,793 263,637 1,264,471
Claims
% Generic Pharmacy Claims 43% 47% 45% 43% 43% 46% 46% 46% 43% 42% 42%

Total Inpatient Admits 42,920 1,456 3,239 342 486 3,379 548 1,292 4,672 8,203 25,526
Total Inpatient Admits/1000 94.3 98.3 82.1 46 81.1 71.6 72 62 106.9 100.8 124.8
Members
Total Inpatient Days 218,624 6,763 14,725 1,137 1,717 16,742 2,544 4,987 22,173 41,824 138,562
Total Inpatient Days/1000 480.4 456.6 373.4 153 286.5 354.6 334.4 239.5 507.4 513.7 677.2
Members









Table 9: Utilization Indicators by County (All Study Areas) Continued


Area 5 5 6 6 6 6 6 9 10 11

< I II wu
0 I w I- I <
o 9 1 C O I
< z < (. i < 0 i l a<
County TOTAL a. 0 I I a |
Total ACS Admits (Standard) 9,096 266 631 115 1751 832 120 371 1,028 1,618 5,203
Total ACS Admits/1000
otal AS Adm 20 18 16 15.5 29.2 17.6 15.8 17.8 23.5 19.9 25.4
(Standard)
Total ACS Admits (AHCA) 5,159 138 313 69 81 465 82 219 606 968 2,902
Total ACS Admits/1000
11.3 9.3 7.9 9.3 13.5 9.8 10.8 10.5 13.9 11.9 14.2
(AHCA)
Total ACS Admits (Either) 9,602 284 668 123 186 882 128 389 1,108 1,696 5,474
Total ACS Admits/1000
iTotal ACS Adits21.1 19.2 16.9 16.6 31 187 168 187 25.4 20.8 26.8
(Either)
Total Office Visits
Totl O e Vss 1,116,905 36,660 78,448 15,796 16,381 89,728 10,929 34,263 93,740 143,998 596,962
(only CPT codes)
Total Office Visits/ 1000
T ce isits2,454.10 2,475.00 1,989.30 2,125.70 2,733.40 1,900.40 1,436.50 1,645.50 2,145.20 1,768.60 2,917.50
Members
Total Office Visits
1,082,132 36,332 77,971 15,725 16,271 85,844 10,871 33,989 93,334 137,727 574,068
(CPT + 00, 11, 71, 72)
Total Office Visits/ 1000 285
T ce isits2,377.70 2,452.90 1,977.30 2,116.10 2,715.00 1,818.10 1,428.90 1,632.40 2,135.90 1,691.60 2,805.70
Members
Total Office Visits
(extended CP1,270,014 40,945 89,925 17,492 18,285 103,412 12,467 38,947 107,082 170,164 671,295
(extended CPTs)
Total Office Visits/ 1000 3,280.80
Total Office Visits1000 2,790.50 2,764.30 2,280.40 2,353.90 3,051.10 2,190.20 1,638.70 1,870.50 2,450.50 2,090.00 3,280.80
Members









Tables 24 43 (in Appendix II) compare utilization by plan type and county for TANF or SSI
members. It is important to note that that these analyses do not control for any member
characteristics except eligibility type (and county). These bivariate results, however, begin to
provide evidence of utilization differences for the MPNs, PSN, and MediPass.

For example, across almost all counties and for both TANF and SSI members, MediPass,
PhyTrust, NetPass, and the PSN had similar percentages of urgent ER visits (around 60%). In
both Broward and Miami-Dade counties, however, the percentage of urgent ER visits was much
lower for SSI members (33-44%), with the lowest percentage for SSI members in the PSN
(33%). Similarly, in most counties and eligibility groups, MediPass had a higher rate of ER use
per 1000 members compared to PhyTrust and NetPass. In Broward and Miami-Dade counties,
however, the PSN's rate of ER use was higher than any other plan type.

Compared to MediPass, both pilots and the PSN had a lower number of pharmacy claims/1000
members for all counties and eligibility categories. In addition, MediPass had a lower percentage
of generic pharmacy claims compared to all the pilot programs for all counties and eligibility
categories.

MediPass, PhyTrust, NetPass and the PSN had very similar inpatient admissions /1000 members
for all counties and eligibility categories. SSI members experienced almost triple the numbers of
inpatient admits/1000 members compared to TANF across all counties and programs. In
comparison the number of inpatient days/1000 members was higher, with MediPass having
generally more inpatient days/1000 members compared to all the pilot programs. Again SSI had
a higher number of ACS admits/1000 members than TANF across all counties and programs.
Compared to MediPass, both pilots and the PSN had a lower number of office visits/1000
members across all counties and eligibility types.

Bivariate Analyses Conclusions

In general, this analysis indicates that there are differences in these utilization indicators when
comparing the MPN, PSN, and MediPass programs. There are also observed differences in
utilization across the counties included in this study.

These bivariate analyses are, however, simply descriptive. They do not control for the
underlying characteristics of the Medicaid population in each county that may account for
observed differences in utilization. In order to be more precise in our comparisons, we must use
a multivariate approach to control for important factors that may influence utilization (e.g., age,
gender, chronic illness).









Part III: Multivariate Analyses


Analytic Methods

The evaluation team performed an analysis of the 2003 2004 utilizations using negative
binomial regression for each utilization type and county.

Poisson or the negative binomial regression models are two count model regression techniques
that have been used within the literature to explain the utilization of health services in various
settings (Cameron & Trivedi, 1998; Winkelmann, 2000). The choice of model depends on the
number of zeros that a dependent variable has, because too many zeros for counts leads to the
over-dispersion of the Poisson model. The negative binomial model accounts for situations
where variance of the dependent variable exceeds the mean, when the incidence rate is not the same
for all observations. Specifically, the negative binomial approach controls for the high number of
zeros and overdispersion. It also allows for the incidence rate to vary for individual observations.
The presence of a large number of zeros in the count data on the utilization of health service exhibits
overdispersion in the model and, thus, we used a negative binomial regression. In this study, the
percentage of members with no utilization is very high for most types of utilization, from a low
of 63% for pharmacy claims to a high of 99% no utilization (value of 0) for most other types of
utilization (inpatient admissions, etc.).

The negative binomial distribution assumes that variables follow a gamma distribution. It is
assumed that the dependent variable Y, such as the number of Emergency Room visits, has a
negative binomial distribution given the independent variables (such as plan type and control
variables),

P(Y=yi) = e- Yi / yi!, yi= 0, 1, 2, ......

where the log of the mean [ is assumed to be a linear function of the independent variables. That
is,

ln(|i) = I xipj,
J

where xi corresponds to the vector of explanatory variable, 3j corresponds to the vector of
coefficient of explanatory variable, which implies that t is the exponential function of
independent variables,

[t = exp(S xipj).


The unconditional likelihood for an observation in a negative binomial regression model is
F(m + yi)
f(yi) = p"'(1- p)
F(yi + 1)r(m)









where p = 1/(1+ acp), a is the shape parameter, which accounts for the level of overdispersion in the
data, and m = 1/c. The coefficients (j) and the shape parameter (a) are estimated using
maximum likelihood estimation.

Interpreting Results

The results of the binomial regression model are expressed in terms of an incidence risk ratio
(IRR). The IRR compares the incidence rate of two variables. The IRR in our models will be
the ratio of the rate of utilization of the variable of interest to the rate of utilization of the
comparison variable. For example, if we intend to compare the emergency room utilization for
Hispanics with that of Whites, then the IRR for the Variable "Hispanic" will be the ratio of the
expected rate of emergency room visits of the Hispanics to that of the Whites (the referent
group). Thus, the IRR predicts the probability of Hispanics having higher utilization compared
to Whites.

Specifically, in this example, an IRR of 1.20 for Hispanics means that Hispanics experience a
20% higher incidence of ER visits relative to Whites. If the IRR for Blacks is 0.85, that means
that Blacks experience a 15% lower incidence of ER visits compared to Whites.

Further, the significance of the association of any variable is determined by the 95% confidence
interval (CI) of the estimated IRR. Inclusion of 1 within the CI interval means that the variable
is not significantly associated with the dependent variable. In all summary tables, only
significant IRRs are displayed for plan type variables (that is, Florida NetPass, PhyTrust, and
PSN).









Multivariate Results


We ran separate models for each type of utilization by county (and an additional model that
included all geographic areas in aggregate). We include the overall summary (Table 10) and
county summaries in Tables 11 14 and 44 53 (in Appendix II). Full binomial regression
model results are available upon request.

We summarize the results with respect to Florida NetPass, PhyTrust, and the PSN in Tables 10 -
14 (below). These tables include plan type IRRs for those differences that are statistically
significant.

Table 10: Summary of Utilization by Plan Type

Summary of Utilization Differences
All Study Areas (Aggregate), Only Significant Differences Shown

Compared to MediPass (IRR)

FNP PT PSN

Total Emergency Room Visits (#) 0.94 0.96 1.23
Urgent Emergency Room Visits (#) 0.90
Total Pharmacy Claims (#) 0.94 0.83 0.74
Generic Pharmacy Claims (#) 0.95 0.86 0.74
Total Inpatient Admissions (#) 0.88 1.08
Total Inpatient Days (#) 0.86
Total Inpatient ACS Admissions (Standard) 0.88 0.83 1.09
Total Inpatient ACS Admissions (AHCA Def) 0.88 0.77 1.24
Total Inpatient ACS Admissions (Either Def) 0.90 0.84 1.10
Total Office Visits (I) 1.34 1.58 0.45
Total Office Visits (II) 1.34 1.58 0.19
Total Office Visits (111) 1.35 1.59 0.46

As shown in Table 10 (above), members of the MPNs typically demonstrate lower levels of
utilization. Compared to MediPass, both Florida NetPass and PhyTrust had lower utilization for
emergency room visits, pharmacy, and ambulatory care sensitive conditions, and higher levels of
utilization for office visits. The PSN had lower utilization for pharmacy and office visits, but
higher emergency room and inpatient utilization. PhyTrust members experienced fewer inpatient
admissions and inpatient days than MediPass patients.









Table 11: Emergency Room Utilization by Plan Type and County

Compared to MediPass (IRR)
FNP PT PSN
Total Emergency Room Visits (#)
Total Aggregate, All Areas Below 0.94 0.96 1.23
Area 5: Pasco 0.90 N/A
Area 5: Pinellas 1.10 0.90 N/A
Area 6: Hardee N/A
Area 6: Highlands 1.50 N/A
Area 6: Hillsborough 1.09 1.04 N/A
Area 6: Manatee N/A
Area 6: Polk 0.92 N/A
Area 9: Palm Beach 0.96 N/A N/A
Area 10: Broward 0.96 1.20
Area 11: Miami-Dade 0.93 0.96 1.37
Urgent Emergency Room Visits (#)


Total Aggregate, All Areas Below
Area 5: Pasco
Area 5: Pinellas
Area 6: Hardee
Area 6: Highlands
Area 6: Hillsborough
Area 6: Manatee
Area 6: Polk
Area 9: Palm Beach
Area 10: Broward
Area 11: Miami-Dade


S 0.90

J 1 0.91 N/A
S 1.11 0.90 N/A
S 0.83 0.88 N/A
J 1.57 N/A
S 1.11 1.11 N/A
SI N/A
SI N/A
J N/A N/A
J 1.19
S0.94 1.20


There are mixed results by plan type and county for Emergency Room and Urgent Emergency
Room utilization (Table 11 above). In some counties, Florida NetPass and PhyTrust had
significantly higher (or lower) ER utilization. The PSN had significantly higher ER utilization in
both Broward and Miami-Dade County.









Table 12: Pharmacy Utilization by Plan Type and County

Compared to MediPass (IRR)
FNP PT PSN

Total Pharmacy Claims (#)
Total Aggregate, All Areas Below 0.94 0.83 0.74
Area 5: Pasco 0.79 0.91 N/A
Area 5: Pinellas 0.84 0.93 N/A
Area 6: Hardee 0.68 0.88 N/A
Area 6: Highlands 0.88 1 IN/A
Area 6: Hillsborough 0.83 0.93 N/A
Area 6: Manatee 1.20 0.82 N/A
Area 6: Polk 0.84 0.92 N/A
Area 9: Palm Beach 0.89 N/A N/A
Area 10: Broward 0.88 0.84 0.78
Area 11: Miami-Dade 0.92 0.78 0.69
Generic Pharmacy Claims (#)
Total Aggregate, All Areas Below 0.95 0.86 0.74
Area 5: Pasco 0.88 0.95 N/A
Area 5: Pinellas 0.96 N/A
Area 6: Hardee 0.86 0.93 N/A
Area 6: Highlands N/A
Area 6: Hillsborough 0.87 0.97 N/A
Area 6: Manatee 0.91 N/A
Area 6: Polk 0.94 0.87 N/A
Area 9: Palm Beach 0.94 N/A N/A
Area 10: Broward 0.86 0.86 0.83
Area 11: Miami-Dade 0.92 0.82 0.69

All of the pilot programs experienced lower pharmacy and generic pharmacy utilization than
MediPass in almost every county where they operate (Table 12). There were a few exceptions;
for example, in Manatee County, Florida NetPass had a higher total pharmacy utilization than
MediPass (IRR=1.2). Otherwise, the pilots appear to be successful in reducing the number of
pharmacy claims when compared to MediPass.









Table 13: Inpatient Utilization by Plan Type and County

Compared to MediPass (IRR)

FNP PT PSN

Total Inpatient Admissions (#)

Total Aggregate, All Areas Below 0.88 1.08

Area 5: Pasco 1.40 N/A

Area 5: Pinellas 1.49 N/A

Area 6: Hardee 0.78 N/A

Area 6: Highlands N/A

Area 6: Hillsborough 0.82 N/A

Area 6: Manatee N/A

Area 6: Polk 0.75 N/A

Area 9: Palm Beach 0.89 N/A N/A

Area 10: Broward 0.87 0.91

Area 11: Miami-Dade 0.91 0.89

Total Inpatient Days (#)

Total Aggregate, All Areas Below 0.86

Area 5: Pasco 1.60 1.33 N/A

Area 5: Pinellas 1.29 N/A

Area 6: Hardee 0.70 N/A

Area 6: Highlands N/A

Area 6: Hillsborough 0.78 N/A

Area 6: Manatee N/A

Area 6: Polk 0.83 N/A

Area 9: Palm Beach 0.84 N/A N/A

Area 10: Broward 0.86 0.83 0.89

Area 11: Miami-Dade 0.99









Table 13: Inpatient Utilization by Plan Type and County Continued

Compared to MediPass (IRR)

FNP PT PSN

Total Ambulatory Care Sensitive Condition (Standard) Admissions (#)

Total Aggregate, All Areas Below 0.88 0.83 1.09

Area 5: Pasco 0.64 N/A

Area 5: Pinellas N/A

Area 6: Hardee N/A

Area 6: Highlands N/A

Area 6: Hillsborough N/A

Area 6: Manatee N/A

Area 6: Polk N/A

Area 9: Palm Beach 0.76 N/A N/A

Area 10: Broward 0.83 0.77

Area 11: Miami-Dade 0.86 0.83

Total Ambulatory Care Sensitive Condition (AHCA Defined) Admissions (#)

Total Aggregate, All Areas Below 0.88 0.77 1.24

Area 5: Pasco 0.30 N/A

Area 5: Pinellas N/A

Area 6: Hardee N/A

Area 6: Highlands N/A

Area 6: Hillsborough N/A

Area 6: Manatee N/A

Area 6: Polk N/A

Area 9: Palm Beach 0.67 N/A N/A

Area 10: Broward 0.71 0.75

Area 11: Miami-Dade 0.76 1.28










Table 13: Inpatient Utilization by Plan Type and County Continued

Compared to MediPass (IRR)

FNP PT PSN

Total Ambulatory Care Sensitive Condition (Either Def.) Admissions (#)

Total Aggregate, All Areas Below 0.90 0.84 1.10

Area 5: Pasco 0.47 0.64 N/A

Area 5: Pinellas N/A

Area 6: Hardee N/A

Area 6: Highlands N/A

Area 6: Hillsborough N/A

Area 6: Manatee N/A

Area 6: Polk N/A

Area 9: Palm Beach 0.79 N/A N/A

Area 10: Broward 0.79

Area 11: Miami-Dade 0.87 0.84 1.10



As shown in Table 13 (above), the MPNs and PSN demonstrated lower inpatient utilization
(admissions, days) in most counties-with a few exceptions. Both pilot programs had more
inpatient days than MediPass in Pasco County. Florida NetPass had more inpatient admissions
and days than MediPass in Pasco and Pinellas Counties.

Table 13 also shows that both MPNs had fewer standard definition Ambulatory Care Sensitive
admissions than MediPass in Pasco (PhyTrust), Palm Beach (Florida NetPass), and Broward and
Miami-Dade Counties (PhyTrust and Florida NetPass). For the AHCA definition of ACS
admissions, the PSN had more ambulatory care sensitive admissions than MediPass did in
Miami-Dade County.









Table 14: Office Visit Utilization by Plan Type and County

Compared to MediPass (IRR)

FNP PT PSN

Total Office Visits, Version I

Total-Aggregate, All Areas Below 1.34 1.58 0.45

Area 5: Pasco 2.78 3.11 N/A

Area 5: Pinellas 2.38 2.51 N/A

Area 6: Hardee 2.38 2.87 N/A

Area 6: Highlands 2.45 N/A

Area 6: Hillsborough 2.51 2.59 N/A

Area 6: Manatee 3.29 3.22 N/A

Area 6: Polk 2.78 2.62 N/A

Area 9: Palm Beach 1.23 N/A N/A

Area 10: Broward 1.20 1.09 0.55

Area 11: Miami-Dade 1.19 1.12 0.37

Total Office Visits, Version II

Total Aggregate, All Areas Below 1.34 1.58 0.19

Area 5: Pasco 2.74 3.11 N/A

Area 5: Pinellas 2.36 2.52 N/A

Area 6: Hardee 2.39 2.86 N/A

Area 6: Highlands 2.46 N/A

Area 6: Hillsborough 2.54 2.68 N/A

Area 6: Manatee 3.29 3.20 N/A

Area 6: Polk 2.77 2.62 N/A

Area 9: Palm Beach 1.24 N/A N/A

Area 10: Broward 1.20 1.09 0.32

Area 11: Miami-Dade 1.18 1.12 0.12










Table 14: Office Visit Utilization by Plan Type and County Continued

Compared to MediPass (IRR)

FNP PT PSN

Total Office Visits, Version III

Total Aggregate, All Areas Below 1.35 1.59 0.46

Area 5: Pasco 2.90 3.09 N/A

Area 5: Pinellas 2.40 2.58 N/A

Area 6: Hardee 2.41 2.84 N/A

Area 6: Highlands 2.44 N/A

Area 6: Hillsborough 2.58 2.60 N/A

Area 6: Manatee 3.26 3.38 N/A

Area 6: Polk 2.84 2.72 N/A

Area 9: Palm Beach 1.25 N/A N/A

Area 10: Broward 1.22 1.07 0.57

Area 11: Miami-Dade 1.19 1.13 0.37



There are very consistent patterns of office visit utilization by plan type (Table 14 above). In
every county and using all three definitions of "office visits," Florida NetPass and PhyTrust had
higher levels of office visit utilization and the PSN had lower office visit utilization than
MediPass.

The county summaries (Tables 44 53 in Appendix II) display significant utilization differences
by county and plan type. These data indicate that the MPNs are most consistently effective in
achieving lower ER, inpatient, and pharmacy use and higher office visit use (relative to
MediPass) in the Florida counties of Hardee, Polk, Palm Beach, Broward, and Miami-Dade. Full
model result tables are available by request.

The PSN was successful in achieving lower pharmacy and inpatient use in Broward County. The
increased ACS admissions were observed only in Miami-Dade County. The PSN experienced
higher emergency room visits, urgent emergency room visits, and lower office visits (relative to
MediPass) in both counties where it operates (Broward and Miami-Dade).



Multivariate Conclusions:










We found some evidence that the provider network model, with its local management of
provider networks, increased communication with primary care physicians. We also found some
evidence that financial incentive programs, does result in different utilization patterns for
Florida's pilot programs.

In most cases, the pilot programs exhibit lower levels of utilization than MediPass, after
controlling for age/sex, race/ethnicity, county, eligibility type, geographic area (county), and
three chronic disease states (asthma, diabetes, and hypertension).

Overall utilization patterns suggest that the MPNs have higher levels of office visit utilization
and lower levels of pharmacy, inpatient, and emergency room use. This would be a strong
indication of more appropriate use of medical services and would provide more information on
why the programs achieved "cost savings" relative to MediPass (in terms of expenditures).
The PSN, however, had much lower levels of office visit utilization and pharmacy use, but
higher levels of inpatient and ER use in many areas. This may also lead to lower medical
expenditures relative to MediPass. The higher levels of ER utilization are of interest and deserve
further exploration. One possible reason could be the strong links between the PSN and the
county hospitals which could encourage increased reliance on these institutions. Another
possibility could be that the patients who are served by the PSN have a past history of seeking
care from the emergency rooms. Despite PSN enrollment, patients still view the emergency
room as a source of usual medical care. Finally, patients served by the PSN could have higher
levels of disease acuity and thus are heavy users of hospital care.

It is important to note that we did not examine the specific managed care mechanisms used by
each plan (e.g., when financial incentive plans became operational, what specific areas were
included in medical management, how often information was shared with physicians, etc.). The
three organizations studied here-PhyTrust, Florida NetPass, and the South Florida Community
Care Network PSN-have different contracts with the Agency, different management models,
different "shared savings" methodologies, and many other differences. Examining how specific
aspects of each model affect specific types of utilization is beyond the scope of this study.

We also found that the models did not exhibit uniform effects in all parts of the state. The most
consistent findings were in the larger counties of Miami-Dade, Broward, and Palm Beach.

Limitations

There are some limitations of the research conducted here. First, it may be too soon to see
effects of MPN activities in Areas 5 and 6, since the programs were implemented in these areas
later than in other parts of the state.

Second, we have analyzed only utilization in aggregate measures. We do not include specific
types of utilization that may reflect differences in quality or continuity of care. We were also
unable to consider important aspects of utilization that relate to access and continuity of care,
such as primary versus specialty care visits, "episode of care" visits (e.g., before and after an
inpatient stay), the ACS admissions for specific conditions, and others.









The analysis relies on claims data, which has problems and benefits. We assume the issues
related to claims data would be consistent across all plan types and counties and would therefore
not bias our results.

During the time frame used in this study, the State was implementing several Medicaid programs
and initiatives. We do not specifically control or account for other Medicaid programs that may
have had an impact on the utilization patterns observed here.

Finally, as a proxy for risk adjustment, we used a measure that indicated whether or not the
recipient had one or more chronic disease states. Since so few of these patients were identified
using the Agency's algorithm, it may be that these measures were not adequately capturing
differences in the degree of illness among Medicaid recipients. Due to data limitations, we did
not include any measure of severity in these analyses.

Conclusion

Despite these limitations, we believe that this study, coupled with the cost analyses done earlier,
begins to build a body of evidence that suggests that these alternative models of care may be
improving the quality of care for MediPass beneficiaries.

An analysis over a longer time frame, that perhaps incorporates an examination of specific
aspects of each alternative delivery model, will provide more definitive conclusions.









REFERENCES


Billings J. "Using Administrative Data to Monitor Access, Identify Disparities, and Assess
Performance of the Safety Net" in Billings J, Weinick R. Eds. A Tool Kit for Monitoring the
Local Safety Net. Agency for Health Care Research and Quality. July 2003.

Billings J, Cantor J. Access to health care services in Health Care Delivery in the United States,
Seventh Edition Kovner A, Jonas, S Eds. New York: Springer Publishing Company, 2001.

Billings J, Anderson G, Newman L. Recent findings on preventable hospitalizations. Health
Affairs (Fall, 1996): 239-249.

Bindman A, Grumbach K, Osmond D, Komaromy M, Vranizan K, Lurie N, and Billings J.
Preventable hospitalizations and access to health care. Journal of American Medical Association
274, no. 4 (1995): 305-311.

Cameron C. and Trivedi C. Regression Analysis of Count Data, Econometric Society
Monograph No.30, Cambridge University Press, 1998.

Winkelmann, R. Seemingly Unrelated Negative Binomial Regression, Oxford Bulletin of
Economics and Statistics, 62, (2000), 553-560.









Appendix I


AHCA Disease Hierarchy and Disease Definitions


Disease Definitions

For all of the disease states, claims with dates of service in the past 18 months are used to
identify beneficiaries meeting the criteria for having a disease.

1) HIV/AIDS
2) Hemophilia
3) End Stage Renal Disease (ESRD)
4) Congestive Heart Failure (CHF)
5) Diabetes
6) Asthma
7) Hypertension










HIV/AIDS

All eligible recipients, with any of the following in their claims:


1) One or more of the following ICD-9 codes: 042.x, 043.x, and/or 136.3;
2) ICD-9 code 279.10 coupled with corroborating evidence of ICD-9 codes indicating
HIV/AIDS supporting diagnoses (Tables I and II below); or
3) Any occurrences of procedure code W9999, Project AIDS Care Waiver Services.


Table 15: HIV/AIDS Supporting Diagnoses-List 1
Diagnosis Code Description
003.1 Salmonella septicemia
007.2 Coccidiosis
007.4 Cryptosporidiosis
031.x Other specified mycobacterial diseases
046.3 Progressive multifocal leukoencephalopathy
078.5 Cytomegalic inclusion disease
112.5 Candidiasis
114.x Coccidioidomycosis
115.xx Histoplasmosis
(exclude:
115.00 Infection by Histoplasma capsulatum without mention of
manifestation
115.05 Infection by Histoplasma capsulatum with pneumonia
115.10 Infection by Histoplasma duboisii without mention of
manifestation
115.15 Infection by Histoplasma duboisii with pneumonia
115.90 Histoplasmosis, unspecified, other)
117.5 Cryptococcosis
130.x Toxoplasmosis
136.x INF/Parasite DIS NEC/NOS
176.x Kaposi's sarcoma
200.20 Burkitt's Tumor unspecified
200.21 Burkitt's Tumor head
200.22 Burkitt's Tumor thorax
200.23 Burkitt's Tumor abdomen
200.24 Burkitt's Tumor axilla
200.25 Burkitt's Tumor inguinal
200.26 Burkitt's Tumor pelvic
200.27 Burkitt's Tumor spleen
200.28 Burkitt's Tumor multiple
321.0 Crytococcal meningitis
484.1 Pneumonia in cytomegalic inclusion disease









Table 16: HIV/AIDS Supporting Diagnoses-List 2


Diagnosis Code Description
010.x Tuberculosis
011 .x Tuberculosis
012.x Tuberculosis
013.x Tuberculosis
014.x Tuberculosis
015.x Tuberculosis
016.x Tuberculosis
017.x Tuberculosis
018.x Tuberculosis
053.x Herpes zoster
054.x Herpes simplex
173.x Other malignant neoplasm of skin
180.x Malignant neoplasm cervix uteri
200.00 Reticulosarocoma unspecified
200.01 Reticulosarocoma head
200.02 Reticulosarocoma thorax
200.03 Reticulosarocoma abdomen
200.04 Reticulosarocoma axilla
200.05 Reticulosarocoma inguin
200.06 Reticulosarocoma pelvic
200.07 Reticulosarocoma spleen
200.08 Reticulosarocoma multiple
200.8x Other named lymphoma variants


Hemophilia

All eligible beneficiaries with the following identified in their claims:

1) Any occurrences of ICD-9 codes 286.0, 286.1, and 286.2;
2) Any occurrences of drug therapeutic class code 201216 (MOE, MOF); or
3) Any occurrences ofHCPCS drug codes J7190, J7194, and J7196.


ESRD
All eligible recipients that have at least one of the following diagnosis codes (Table 17) or at
least one of the following procedure codes or generic drug codes in their claims:









Table 17: Diagnosis Codes for End Stage Renal Disease (ESRD)

Diagnosis Code Description
403.01 Hypertensive renal disease, malignant with renal failure
403.11 Hypertensive renal disease, benign with renal failure
403.91 Hypertensive renal disease, unspecified with renal failure
404.03 Hypertensive heart and renal disease, malignant with ESRD and renal failure
404.13 Hypertensive heart and renal disease, benign with ESRD and renal failure
404.93 Hypertensive heart and renal disease, unspecified with ESRD and renal
failure
585 Chronic renal failure
586 Renal failure, unspecified


Procedure Codes:

90918, 90919, 90920, 90921, 90922, 90923, 90924, 90925, 90935, 90937, 90945, 90947, Q9920
to Q9940, J0635, J1760, J1770, J1780, 50340, 50360, 50370, 50380, 50365

Drug Generic Codes: 04420, 93141, 25110, 25111, and 25112



Congestive Heart Failure:

All eligible recipients with at least one of the codes listed in Table 18 in their claims.

Table 18: Diagnosis Codes for Congestive Heart Failure

Diagnosis Code Description
398.91 Rheumatic heart failure (congestive)
402.01 Malignant hypertensive heart disease with congestive heart failure
402.11 Benign hypertensive heart disease with congestive heart disease
402.91 Unspecified hypertensive heart disease with congestive heart failure
404.01 Hypertensive heart and renal disease with congestive heart failure
404.11 Hypertensive heart and renal disease with congestive heart failure, benign
404.91 Hypertensive heart and renal disease with congestive heart failure,
malignant
428.0 Congestive Heart Failure
428.1 Congestive Heart Failure, left heart failure
428.9 Heart Failure, unspecified









Diabetes

All eligible recipients with the following in their claims:

1) If ICD-9 code 648.8 occurs in any claims:
a) Five (5) or more occurrences1 of claims with ICD-9 codes 250.xx2; or
b) More than one (1) occurrence of claims with ICD-9 codes 250.xx plus more than one (1)
occurrence of claims with drug therapeutic class codes:

682008 Insulins C4G
682020 Sulfonylurease, or C4K, C4N
682092 Misc. (Glucagons, Metformin, Rosglitazim). C4L, C4M

2) If ICD-9 code 648.8 does not occur in any claims:
(a) More than two (2) occurrences of claims with drug therapeutic class codes: C4G, C4K,
C4N, C4L, or C4M;
(b) More than two (2) occurrences of claims with ICD-9 codes 250.xx; or
(c) At least one (1) occurrence of drug therapeutic class codes C4G, C4K, C4N, C4L, or
C4M plus at least one (1) occurrence of ICD-9 codes 250.xx.



Asthma

All eligible recipients that have the following in their claims:

1) Any diagnosis code from Table 19, 20 or 21 AND two (2) or more fills of any NDC
code(s) from Table 22 EXCEPT Claritin; or

2) 8-11 refills of any NDC code(s) from Table 22 EXCEPT Claritin. At least two fills of
any of these medications in combination (but not alone) would be indicative of asthma.
At least three fills of any of these medications alone would be indicative of asthma.
Note, however, that Claritin in particular is often misprescribed for asthma.

Table 19: Diagnosis Code Usually Correlated with Asthma (may be miscoded)

ICD9 Code Description
493 Asthma










Table 20: Diagnosis Codes Somewhat Correlated with Asthma (ifmore than one
event coded similarly)

ICD9 Code Description
466 Acute bronchitis or bronchiolitis
472 Chronic pharyngitis and nasopharyngitis
473 Chronic sinusitis
474 Chronic disease of the tonsils and adenoids
476 Chronic laryngitis
477 Allergic rhinitis
490 Bronchitis, not specified as acute or chronic
518.81 Acute respiratory failure, no other codes
518.82 Other pulmonary insufficiency, not elsewhere classified


Table 21: Diagnosis Codes Possibly Suggestive of Asthma (ifmore than one event
coded similarly, especially in conjunction i i/th NDC codes)

ICD9 Code Description
460 Acute nasopharyngitis
461 Acute sinusitis
462 Acute pharyngitis
464 Acute laryngitis and tracheitis
465 Acute URI of multiple or unspecified sites










Table 22: NDC Codes Indicative of Asthma (multiple codes alone or in conjunction
i ith ICD9 codes above).
Drug Brand name NDC codes
Flunisolide Aerobid (two 0456-0672-99
preparations)
Metaproterenol sulfate Alupent 0597-0070-17, 0597-0070-18, 0597-0071-75, 0597-0071-30, 0597-0078-62, 0597-
0069-62, 0597-0073-16, 0597-0074-01, 0597-0072-01
Triamcinolone Azmacort 0075-0060-37
acetonide
Beclomethesone Beclovent (four 0173-0469-00, 0173-0312-88, 0173-0312-98, 0085-0736-04
dipropionate preparations)
Terbutaline sulfate Breathaire 0028-5557-88, 0028-5557-87
Loratidine Claritin* 00085-0612-02, 00085-0612-01, 00085-1128-02, 00085-0458-01, 00085-0458-02,
00085-0458-03, 00085-0458-04, 00085-0458-06, 00085-0640-01, 00085-0640-02,
00085-1233-01, 00085-1233-02, 00085-0635-01, 00085-0635-04, 00085-0635-05
Cromolyn sodium Intal 0585-0675-01, 0585-0675-02, 0585-0673-02, 0585-0673-03
(Intal)
Pirbuterol acetate Maxair Autohaler 0089-0817-10, 0089-0815-21, (Maxair inhaler), 0089-0790-21
Albuterol Proventil, Ventolin 0085-0614-02, 0085-0614-03 (inhalation solution):
0085-0208-02, (Repetabs, tablets): 0085-0431-02, 0085-0252-02
Salmeterol xinafoate Serevent 0173-0464-00, 0173-0465-00, 0173-0467-00
Theophylline Theodur 50474-100-01, 50474-100-60, 50474-200-01, 50474-200-50, 50474-200-01, 50474-
anhydrous 300-50, 50474-300-60, 50474-400-01, 50474-400-50, 50474-400-60.
Nedocromil sodium Tilade 0585-0685-02, 0585-0685-04
Zileuton Zyflo 0074-8036-22
*Generic loratidine includes: 59569460900, 52959045210, 54868264600, 55045206403,
55175277900, 55175277902, 55175277904, 55175277905, 55289042104, 55289042105,
55289042110, 55289042115, 60346094114, 60346094100, 60346094106, and 60346094107









Hypertension

All recipient claims that may have at least one of the diagnosis codes listed in Table 23.

Table 23: Diagnosis Codes for Hypertension

Diagnosis Code Description
401.0 Essential hypertension, malignant
401.1 Essential hypertension, benign
401.9 Essential hypertension, unspecified
402.00 Hypertensive heart disease, malignant, without congestive heart failure
402.10 Hypertensive heart disease, benign, without congestive heart failure
402.90 Hypertensive heart disease, unspecified, without congestive heart failure
403.00 Hypertensive renal disease, malignant, without mention of renal failure
403.10 Hypertensive renal disease, benign, without mention of renal failure
403.90 Hypertensive renal disease, unspecified, without mention of renal failure
404.00 Hypertensive heart and renal disease, malignant, without mention of
congestive heart failure or renal failure
404.10 Hypertensive heart and renal disease, benign, without mention of congestive
heart failure or renal failure
404.90 Hypertensive heart and renal disease, unspecified, without mention of
congestive heart failure or renal failure










Appendix II
List of Tables


Part Table Number Title
I Study Approach and Methods
1 Summation of Data Used for the Analyses
2 Geographies and Time Period Used in the Study
3 Age/Gender Bands
4 Members by Disease State and Plan Type
5 Definitions -"Ambulatory Case Sensitive" Admissions
6 Office Visit Definitions
II Bivariate Results
7 Beneficiary Demographics (All Study Areas) June 2003-March 2004
8 Beneficiary Demographics by County (All Study Areas)
9 Utilization Indicators by County (All Study Areas)
24 Utilization by Plan Type; Area 5 Pasco County, TANF Only
25 Utilization by Plan Type; Area 5 Pasco County, SSI Only
26 Utilization by Plan Type; Area 5 Pinellas County, TANF Only
27 Utilization by Plan Type; Area 5 Pinellas County, SSI Only
28 Utilization by Plan Type; Area 6 Hardee County, TANF Only
29 Utilization by Plan Type; Area 6 Hardee County, SSI Only
30 Utilization by Plan Type; Area 6 Highlands County, TANF Only
31 Utilization by Plan Type; Area 6 Highlands County, SSI Only
32 Utilization by Plan Type; Area 6 Hillsborough County, TANF Only
33 Utilization by Plan Type; Area 6 Hillsborough County, SSI Only
34 Utilization by Plan Type; Area 6 Manatee County, TANF Only
35 Utilization by Plan Type; Area 6 Manatee County, SSI Only
36 Utilization by Plan Type; Area 6 Polk County, TANF Only
37 Utilization by Plan Type; Area 6 Polk County, SSI Only
38 Utilization by Plan Type; Area 9 Palm Beach County, TANF Only
39 Utilization by Plan Type; Area 9 Palm Beach County, SSI Only
40 Utilization by Plan Type; Area 10 Broward County, TANF Only
41 Utilization by Plan Type; Area 10 Broward County, SSI Only
42 Utilization by Plan Type; Area 11 Miami-Dade County, TANF Only
43 Utilization by Plan Type; Area 11 Miami-Dade County, SSI Only
III Multivariate Results
10 Summary of Utilization by Plan Type
11 Emergency Room Utilization by Plan Type and County
12 Pharmacy Utilization by Plan Type and County
13 Inpatient Utilization by Plan Type and County
14 Office Visit Utilization by Plan Type and County
44 Summary of Utilization by Plan Type-Pasco County
45 Summary of Utilization by Plan Type-Pinellas County
46 Summary of Utilization by Plan Type-Hardee County
47 Summary of Utilization by Plan Type-Highlands County
48 Summary of Utilization by Plan Type-Hillsborough County
49 Summary of Utilization by Plan Type-Manatee County
50 Summary of Utilization by Plan Type-Polk County
51 Summary of Utilization by Plan Type-Palm Beach County










Part Table Number Title
52 Summary of Utilization by Plan Type-Broward County Summary
53 Summary of Utilization by Plan Type-Miami-Dade County
Appendix I
15 HIV/AIDS Supporting Diagnoses-List 1
16 HIV/AIDS Supporting Diagnoses-List 2
17 Diagnosis Codes for End Stage Renal Disease ESRD)
18 Diagnosis Codes for Congestive Heart Failure
19 Diagnosis Code Usually Correlated with Asthma
20 Diagnosis Codes Somewhat Correlated with Asthma
21 Diagnosis Codes Possibly Suggestive of Asthma
22 NDC Codes Indicative of Asthma
23 Diagnosis Codes for Hypertension








Table 24: Utilization by Plan Type; Area 5 Pasco County, TANF Only

Area 5 Pasco County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 6,832 5,170 1,505 648
Total Users 6,739 5,087 1,489 640
Total Member Months 40,691 30,305 7,857 2,529
Total ER Visits 2,853 2,139 488 226
Total Urgent ER Claims 1,831 1,386 310 135
% Urgent ER (Urgent/ER) 64% 65% 64% 60%
ER Visits/1000 Members 417.6 413.7 324.3 348.8
Total Pharmacy Claims 34,771 27,026 5,604 2,141
Pharmacy/1000 Members 5,089.4 5,227.5 3,723.6 3,304.0
Total Generic Pharmacy Claims 16,511 12,530 2,761 1,220
% Generic Pharmacy Claims 47% 46% 49% 57%
Total Inpatient Admits 314 211 63 40
Total Inpatient Admits/1000 Members 46.0 40.8 41.9 61.7
Total Inpatient Days 944 642 168 134
Total Inpatient Days/1000 Members 138.2 124.2 111.6 206.8
Total ACS Admits (Standard) 57 40 12 5
Total ACS Admits/1000 Members (Standard) 8.3 7.7 8.0 7.7
Total ACS Admits (AHCA) 31 27 2 2
Total ACS Admits/1000 Members (AHCA) 4.5 5.2 1.3 3.1
Total ACS Admits (Either) 62 45 12 5
Total ACS Admits/1000 Members (Either) 9.1 8.7 8.0 7.7
Total Office Visits (only CPT codes) 11,859 9,035 2,169 655
Total Office Visits/1000 Members 1,735.8 1,747.6 1,441.2 1,010.8
Total Office Visits
(CPTcodesandO ,71,7) 11,824 9,017 2,164 643
(CPT codes and 00, 11, 71, 72) ........... .. ....
Total Office Visits/1000 Members 1,730.7 1,744.1 1,437.9 992.3
Total Office Visits (extended CPT codes) 13,415 10,154 2,471 790
Total Office Visits/1000 Members 1,963.6 1,964.0 1,641.9 1,219.1








Table 25: Utilization by Plan Type; Area 5 Pasco County, SSI Only

Area 5 Pasco County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 3,326 2,903 444 176
Total Users 3,299 2,874 443 174
Total Member Months 27,385 23,579 2,949 857
Total ER Visits 3,047 2,632 311 104
Total Urgent ER Claims 1,729 1,480 187 62
% Urgent ER (Urgent/ER) 57% 56% 60% 60%
ER Visits/1000 Members 916.1 906.6 700.5 590.9
Total Pharmacy Claims 103,941 93,600 7,564 2,777
Pharmacy/1000 Members 31,251.1 32,242.5 17,036.0 15,778.4
Total Generic Pharmacy Claims 49,656 44,591 3,661 1,404
% Generic Pharmacy Claims 48% 48% 48% 51%
Total Inpatient Admits 950 829 80 41
Total Inpatient Admits/1000 Members 285.6 285.6 180.2 233.0
Total Inpatient Days 5,121 4,416 476 229
Total Inpatient Days/1000 Members 1,539.7 1,521.2 1,072.1 1,301.1
Total ACS Admits (Standard) 159 154 4 1
Total ACS Admits/1000 Members (Standard) 47.8 53.0 9.0 5.7
Total ACS Admits (AHCA) 81 77 3 1
Total ACS Admits/1000 Members (AHCA) 24.4 26.5 6.8 5.7
Total ACS Admits (Either) 168 161 6 1
Total ACS Admits/1000 Members (Either) 50.5 55.5 13.5 5.7
Total Office Visits (only CPT codes) 13,891 12,368 1,122 401
Total Office Visits/1000 Members 4,176.5 4,260.4 2,527.0 2,278.4
Total Office Visits
13,688 12,182 1,117 389
(CPT codes and 00, 11, 71, 72) 13688 12182 1117 389
Total Office Visits/1000 Members 4,115.5 4,196.3 2,515.8 2,210.2
Total Office Visits (extended CPT codes) 15,031 13,343 1,244 444
Total Office Visits/1000 Members 4,519.2 4,596.3 2,801.8 2,522.7









Table 26: Utilization by Plan Type; Area 5 Pinellas County, TANF Only

Area 5 Pinellas County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 14,316 11,289 2,518 1,273
Total Users 14,076 11,092 1,296 584
Total Member Months 92,166 73,381 13,815 4,970
Total ER Visits 5,456 4,265 784 407
Total Urgent ER Claims 3,407 2,668 487 252
% Urgent ER (Urgent/ER) 62% 63% 62% 62%
ER Visits/1000 Members 381.1 377.8 311.4 319.7

Total Pharmacy Claims 61,703 49,283 9,109 3,311
Pharmacy/1000 Members 4,310.1 4,365.6 3,617.6 2,600.9
Total Generic Pharmacy Claims 27,310 21,271 4,228 1,811
% Generic Pharmacy Claims 44% 43% 46% 55%

Total Inpatient Admits 692 516 120 56
Total Inpatient Admits/1000 Members 48.3 45.7 47.7 44.0
Total Inpatient Days 2,212 1,673 357 182
Total Inpatient Days/1000 Members 154.5 148.2 141.8 143.0
Total ACS Admits (Standard) 127 92 25 10
Total ACS Admits/1000 Members (Standard) 8.9 8.1 9.9 7.9
Total ACS Admits (AHCA) 64 51 9 4
Total ACS Admits/1000 Members (AHCA) 4.5 4.5 3.6 3.1
Total ACS Admits (Either) 130 95 25 10
Total ACS Admits/1000 Members (Either) 9.1 8.4 9.9 7.9

Total Office Visits (only CPT codes) 21,803 17,578 3,291 934
Total Office Visits/1000 Members 1,523.0 1,557.1 1,307.0 733.7
Total Office Visits
21,732 17,513 3,291 928
(CPT codes and 00, 11, 71, 72) ......... ...... 3 1 928
Total Office Visits/1000 Members 1,518.0 1,551.3 1,307.0 729.0
Total Office Visits (extended CPT codes) 25,391 20,423 3,825 1,143
Total Office Visits/1000 Members 1,773.6 1,809.1 1,519.1 897.9








Table 27: Utilization by Plan Type; Area 5 Pinellas County, SSI Only

Area 5 Pinellas County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 6,505 5,524 866 459
Total Users 6,482 5,502 864 457
Total Member Months 54,359 45,792 6,197 2,370

Total ER Visits 5,655 4,762 548 345
Total Urgent ER Claims 2,876 2,434 270 172
% Urgent ER (Urgent/ER) 51% 51% 49% 50%
ER Visits/1000 Members 869.3 862.1 632.8 751.6

Total Pharmacy Claims 193,849 167,774 17,613 8,462
Pharmacy/1000 Members 29,800.0 30,371.8 20,338.3 18,435.7
Total Generic Pharmacy Claims 90,604 78,594 7,808 4,202
% Generic Pharmacy Claims 47% 47% 44% 50%

Total Inpatient Admits 2,055 1,685 196 174
Total Inpatient Admits/1000 Members 315.9 305.0 226.3 379.1
Total Inpatient Days 10,800 8,742 1,131 927
Total Inpatient Days/1000 Members 1,660.3 1,582.5 1,306.0 2,019.6
Total ACS Admits (Standard) 356 304 32 20
Total ACS Admits/1000 Members (Standard) 54.7 55.0 37.0 43.6
Total ACS Admits (AHCA) 178 153 16 9
Total ACS Admits/1000 Members (AHCA) 27.4 27.7 18.5 19.6
Total ACS Admits (Either) 381 324 36 21
Total ACS Admits/1000 Members (Either) 58.6 58.7 41.6 45.8

Total Office Visits (only CPT codes) 25,083 21,904 1,908 1,271
Total Office Visits/1000 Members 3,856.0 3,965.2 2,203.2 2,769.1
Total Office Visits
Total Office Visits 24,852 21,708 1,885 1,259
(CPT codes and 00, 11, 71, 72) 24,852 21,70
Total Office Visits/1000 Members 3,820.4 3,929.8 2,176.7 2,742.9
Total Office Visits (extended CPT codes) 27,887 23,926 2,556 1,405
Total Office Visits/1000 Members 4,287.0 4,331.3 2,951.5 3,061.0









Table 28: Utilization by Plan Type; Area 6 Hardee County, TANF Only

Area 6 Hardee County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 2,592 1,700 837 412
Total Users 2,550 1,658 831 410
Total Member Months 15,124 8,483 4,790 1,851

Total ER Visits 1,165 682 331 152
Total Urgent ER Claims 730 429 200 101
% Urgent ER (Urgent/ER) 63% 63% 60% 66%
ER Visits/1000 Members 449.5 401.2 395.5 368.9

Total Pharmacy Claims 10,176 6,573 2,715 888
Pharmacy/1000 Members 3,925.9 3,866.5 3,243.7 2,155.3
Total Generic Pharmacy Claims 4,556 2,778 1,287 491
% Generic Pharmacy Claims 45% 42% 47% 55%

Total Inpatient Admits 95 51 32 12
Total Inpatient Admits/1000 Members 36.7 30.0 38.2 29.1
Total Inpatient Days 229 133 67 29
Total Inpatient Days/1000 Members 88.3 78.2 80.0 70.4
Total ACS Admits (Standard) 18 12 4 2
Total ACS Admits/1000 Members (Standard) 6.9 7.1 4.8 4.9
Total ACS Admits (AHCA) 10 5 4 1
Total ACS Admits/1000 Members (AHCA) 3.9 2.9 4.8 2.4
Total ACS Admits (Either) 21 13 6 2
Total ACS Admits/1000 Members (Either) 8.1 7.6 7.2 4.9

Total Office Visits (only CPT codes) 5,168 3,257 1,415 496
Total Office Visits/1000 Members 1,993.8 1,915.9 1,690.6 1,203.9
Total Office Visits
5,158 3,252 1,411 495
(CPT codes and 00, 11, 71, 72) 5,158 3,252 11
Total Office Visits/1000 Members 1,990.0 1,912.9 1,685.8 1,201.5
Total Office Visits (extended CPT codes) 5,718 3614 1,525 579
Total Office Visits/1000 Members 2,206.0 2,125.9 1,822.0 1,405.3








Table 29: Utilization by Plan Type; Area 6 Hardee County, SSI Only

Area 6 Hardee County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 492 338 186 46
Total Users 488 333 186 46
Total Member Months 4,216 2,459 1,486 271

Total ER Visits 536 362 144 30
Total Urgent ER Claims 334 226 92 16
% Urgent ER (Urgent/ER) 62% 62% 64% 53%
ER Visits/1000 Members 1,089.4 1,071.0 774.2 652.2

Total Pharmacy Claims 13,782 10,403 2,888 491
Pharmacy/1000 Members 28,012.2 30,778.1 15,526.9 10,673.9
Total Generic Pharmacy Claims 5,706 4,181 1,269 256
% Generic Pharmacy Claims 41% 40% 44% 52%

Total Inpatient Admits 124 89 31 4
Total Inpatient Admits/1000 Members 252.0 263.3 166.7 87.0
Total Inpatient Days 586 429 134 23
Total Inpatient Days/1000 Members 1,191.1 1,269.2 720.4 500.0
Total ACS Admits (Standard) 37 27 8 2
Total ACS Admits/1000 Members (Standard) 75.2 79.9 43.0 43.5
Total ACS Admits (AHCA) 22 17 4 1
Total ACS Admits/1000 Members (AHCA) 44.7 50.3 21.5 21.7
Total ACS Admits (Either) 37 27 8 2
Total ACS Admits/1000 Members (Either) 75.2 79.9 43.0 43.5

Total Office Visits (only CPT codes) 2,221 1,517 571 133
Total Office Visits/1000 Members 4,514.2 4,488.2 3,069.9 2,891.3
Total Office Visits
(CPT codes and 00, 11, 71, 72) 2,187 1,46 59
Total Office Visits/1000 Members 4,445.1 4,426.0 3,005.4 2,869.6
Total Office Visits (extended CPT codes) 2,390 1,619 624 147
Total Office Visits/1000 Members 4,857.7 4,789.9 3,354.8 3,195.7










Table 30: Utilization by Plan Type; Area 6 Highlands County, TANF Only

Area 6 Highlands County June 2003 March 2004
TANF Only MediPass
Total (excluding PhyTrust NetPass*
NetPass and
PhyTrust)
Total Members 2,605 2,487 41 339
Total Users 2,572 2,453 40 336
Total Member Months 15,132 13,559 177 1,396
Total ER Visits 1,014 906 13 95
Total Urgent ER Claims 653 591 8 54
% Urgent ER (Urgent/ER) 64% 65% 62% 57%
ER Visits/1000 Members 389.3 364.3 317.1 280.2
Total Pharmacy Claims 11,596 10,433 124 1,039
Pharmacy/1000 Members 4,451.4 4,195.0 3,024.4 3,064.9
Total Generic Pharmacy Claims 5,199 4,642 70 487
% Generic Pharmacy Claims 45% 44% 56% 47%
Total Inpatient Admits 155 133 2 20
Total Inpatient Admits/1000 Members 59.5 53.5 48.8 59.0
Total Inpatient Days 398 329 6 63
Total Inpatient Days/1000 Members 152.8 132.3 146.3 185.8
Total ACS Admits (Standard) 48 42 0 6
Total ACS Admits/1000 Members (Standard) 18.4 16.9 0.0 17.7
Total ACS Admits (AHCA) 25 21 0 4
Total ACS Admits/1000 Members (AHCA) 9.6 8.4 0.0 11.8
Total ACS Admits (Either) 51 45 0 6
Total ACS Admits/1000 Members (Either) 19.6 18.1 0.0 17.7
Total Office Visits (only CPT codes) 5,211 4,862 25 324
Total Office Visits/1000 Members 2,000.38 1,954.97 609.76 955.75
Total Office Visits
(CPT codes and 00, 11, 71, 72) 5181 4,835 25 321
Total Office Visits/1000 Members 1,988.9 1,944.1 609.8 946.9
Total Office Visits (extended CPT codes) 5,926 5,532 29 365
Total Office Visits/1000 Members 2,274.9 2,224.4 707.3 1,076.7

* NetPass enrollment in Highlands County started to 'kick in' in Sept. 2003, which might result in underestimated
averages.









Table 31: Utilization by Plan Type; Area 6 Highlands County, SSI Only

Area 6 Highlands County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass*
PhyTrust)
Total Members 966 931 20 147
Total Users 961 927 20 146
Total Member Months 8,025 7,174 115 736
Total ER Visits 764 701 8 55
Total Urgent ER Claims 457 417 4 36
% Urgent ER (Urgent/ER) 60% 59% 50% 65%
ER Visits/1000 Members 790.9 753.0 400.0 374.1
Total Pharmacy Claims 21,901 20,265 260 1,376
Pharmacy/1000 Members 22,671.8 21,766.9 13,000.0 9,360.5
Total Generic Pharmacy Claims 9,330 8,614 91 625
% Generic Pharmacy Claims 43% 43% 35% 45%
Total Inpatient Admits 201 183 2 16
Total Inpatient Admits/1000 Members 208.1 196.6 100.0 108.8
Total Inpatient Days 987 881 7 99
Total Inpatient Days/1000 Members 1,021.7 946.3 350.0 673.5
Total ACS Admits (Standard) 62 56 1 5
Total ACS Admits/1000 Members (Standard) 64.2 60.2 50.0 34.0
Total ACS Admits (AHCA) 35 32 0 3
Total ACS Admits/1000 Members (AHCA) 36.2 34.4 0.0 20.4
Total ACS Admits (Either) 67 61 1 5
Total ACS Admits/1000 Members (Either) 69.4 65.5 50.0 34.0
Total Office Visits (only CPT codes) 3,704 3,402 28 274
Total Office Visits/1000 Members 3,834.4 3,654.1 1,400.0 1,863.9
Total Office Visits
(CPT codes and 00, 11, 71, 72) 3,647 3,
Total Office Visits/1000 Members 3,775.4 3,598.3 1,400.0 1,829.9
Total Office Visits (extended CPT codes) 4,009 3,685 34 290
Total Office Visits/1000 Members 4,150.1 3,958.1 1,700.0 1,972.8

* NetPass enrollment in Highlands County started to 'kick in' in Sept. 2003, which might result in underestimated
averages.








Table 32: Utilization by Plan Type; Area 6 Hillsborough County TANF Only

Area 6 Hillsborough County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 23,114 17,765 5,760 2,467
Total Users 22,918 17,582 5,729 2,459
Total Member Months 137,834 96,228 32,490 9,116
Total ER Visits 7,315 5,254 1,540 521
Total Urgent ER Claims 5,029 3,607 1,070 352
% Urgent ER (Urgent/ER) 69% 69% 69% 68%
ER Visits/1000 Members 316.5 295.8 267.4 211.2
Total Pharmacy Claims 84,430 62,275 17,672 4,483
Pharmacy/1000 Members 3,652.8 3,505.5 3,068.1 1,817.2
Total Generic Pharmacy Claims 38,565 28,232 8,245 2,088
% Generic Pharmacy Claims 46% 45% 47% 47%
Total Inpatient Admits 854 628 160 66
Total Inpatient Admits/1000 Members 36.9 35.4 27.8 26.8
Total Inpatient Days 3,040 2,208 645 187
Total Inpatient Days/1000 Members 131.5 124.3 112.0 75.8
Total ACS Admits (Standard) 206 147 40 19
Total ACS Admits/1000 Members (Standard) 8.9 8.3 6.9 7.7
Total ACS Admits (AHCA) 115 83 23 9
Total ACS Admits/1000 Members (AHCA) 5.0 4.7 4.0 3.6
Total ACS Admits (Either) 220 155 43 22
Total ACS Admits/1000 Members (Either) 9.5 8.7 7.5 8.9
Total Office Visits (only CPT codes) 29,121 21,083 6,443 1,595
Total Office Visits/1000 Members 1,259.9 1,186.8 1,118.6 646.5
Total Office Visits
28,152 20,238 6,370 1,544
(CPT codes and 00, 11, 71, 72) 28,152 20,
Total Office Visits/1000 Members 1,218.0 1,139.2 1,105.9 625.9
Total Office Visits (extended CPT codes) 34,652 25,029 7,621 2,002
Total Office Visits/1000 Members 1,499.2 1,408.9 1,323.1 811.5








Table 33: Utilization by Plan Type; Area 6 Hillsborough County, SSI Only

Area 6 Hillsborough County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 9,914 8,169 1,963 671
Total Users 9,890 8,142 1,959 670
Total Member Months 81,631 63,828 14,494 3,309
Total ER Visits 6,356 5,052 1,037 267
Total Urgent ER Claims 3,732 2,907 658 167
% Urgent ER (Urgent/ER) 59% 58% 63% 63%
ER Visits/1000 Members 641.1 618.4 528.3 397.9
Total Pharmacy Claims 270,921 235,709 27,947 7,265
Pharmacy/1000 Members 27,327.1 28,854.1 14,236.9 10,827.1
Total Generic Pharmacy Claims 123,410 107,261 12,720 3,429
% Generic Pharmacy Claims 46% 46% 46% 47%
Total Inpatient Admits 2,014 1,609 293 112
Total Inpatient Admits/1000 Members 203.1 197.0 149.3 166.9
Total Inpatient Days 11,717 9,570 1,339 808
Total Inpatient Days/1000 Members 1,181.9 1,171.5 682.1 1,204.2
Total ACS Admits (Standard) 448 363 69 16
Total ACS Admits/1000 Members (Standard) 45.2 44.4 35.2 23.8
Total ACS Admits (AHCA) 259 206 42 11
Total ACS Admits/1000 Members (AHCA) 26.1 25.2 21.4 16.4
Total ACS Admits (Either) 472 381 73 18
Total ACS Admits/1000 Members (Either) 47.6 46.6 37.2 26.8
Total Office Visits (only CPT codes) 34,624 29,557 3,947 1,120
Total Office Visits/1000 Members 3,492.4 3,618.2 2,010.7 1,669.2
Total Office Visits
32,334 27,413 3,835 1,086
(CPT codes and 00, 11, 71, 72) 32,334 27,41
Total Office Visits/1000 Members 3,261.4 3,355.7 1,953.6 1,618.5
Total Office Visits (extended CPT codes) 38,138 32,293 4,614 1,231
Total Office Visits/1000 Members 3,846.9 3,953.1 2,350.5 1,834.6









Table 34: Utilization by Plan Type; Area 6 Manatee County, TANF Only

Area 6 Manatee County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass*
PhyTrust)
Total Members 4,033 3,409 2,248 118
Total Users 3,971 3,341 2,240 118
Total Member Months 24,883 14,531 10,186 166

Total ER Visits 1,432 840 580 12
Total Urgent ER Claims 956 557 393 6
% Urgent ER (Urgent/ER) 67% 66% 68% 50%
ER Visits/1000 Members 355.1 246.4 258.0 101.7

Total Pharmacy Claims 13,652 8,917 4,642 93
Pharmacy/1000 Members 3,385.1 2,615.7 2,064.9 788.1
Total Generic Pharmacy Claims 6,087 3,827 2,215 45
% Generic Pharmacy Claims 45% 43% 48% 48%

Total Inpatient Admits 162 100 60 2
Total Inpatient Admits/1000 Members 40.2 29.3 26.7 16.9
Total Inpatient Days 526 375 148 3
Total Inpatient Days/1000 Members 130.4 110.0 65.8 25.4
Total ACS Admits (Standard) 28 17 11 0
Total ACS Admits/1000 Members (Standard) 6.9 5.0 4.9 0.0
Total ACS Admits (AHCA) 21 11 10 0
Total ACS Admits/1000 Members (AHCA) 5.2 3.2 4.4 0.0
Total ACS Admits (Either) 30 18 12 0
Total ACS Admits/1000 Members (Either) 7.4 5.3 5.3 0.0

Total Office Visits (only CPT codes) 4,191 2,709 1,458 24
Total Office Visits/1000 Members 1,039.2 794.7 648.6 203.4
Total Office Visits
Total Office Visits 4,185 2,704 1,457 24
(CPT codes and 00, 11, 71, 72) 4,185 2,704 1,457 24
Total Office Visits/1000 Members 1,037.7 793.2 648.1 203.4
Total Office Visits (extended CPT codes) 4,897 3,092 1,773 32
Total Office Visits/1000 Members 1,214.2 907.0 788.7 271.2
NetPass enrollment in Manatee County
started to 'kick in' in March 2004, which
might result in underestimated averages.








Table 35: Utilization by Plan Type; Area 6 Manatee County, SSI Only

Area 6 Manatee County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass*
PhyTrust)
Total Members 1,362 1,271 607 70
Total Users 1,355 1,261 607 70
Total Member Months 11,160 7,745 3,256 159

Total ER Visits 1,063 835 218 10
Total Urgent ER Claims 597 461 130 6
% Urgent ER (Urgent/ER) 56% 55% 60% 60%
ER Visits/1000 Members 780.5 657.0 359.1 142.9
Total Pharmacy Claims 32,968 26,688 5,873 407

Pharmacy/1000 Members 24,205.6 20,997.6 9,675.5 5,814.3
Total Generic Pharmacy Claims 15,530 12,523 2,821 186
% Generic Pharmacy Claims 47% 47% 48% 46%

Total Inpatient Admits 305 238 61 6
Total Inpatient Admits/1000 Members 223.9 187.3 100.5 85.7
Total Inpatient Days 1,674 1,295 358 21
Total Inpatient Days/1000 Members 1,229.1 1,018.9 589.8 300.0
Total ACS Admits (Standard) 69 58 9 2
Total ACS Admits/1000 Members (Standard) 50.7 45.6 14.8 28.6
Total ACS Admits (AHCA) 43 39 3 1
Total ACS Admits/1000 Members (AHCA) 31.6 30.7 4.9 14.3
Total ACS Admits (Either) 72 61 9 2
Total ACS Admits/1000 Members (Either) 52.9 48.0 14.8 28.6

Total Office Visits (only CPT codes) 4,116 3,326 713 77
Total Office Visits/1000 Members 3,022.0 2,616.8 1,174.6 1,100.0
Total Office Visits
(CPT codes and 00, 11, 71, 72) ........ ..... ....
Total Office Visits/1000 Members 2,986.0 2,598.7 1,133.4 1,085.7
Total Office Visits (extended CPT codes) 4,443 3,574 789 80
Total Office Visits/1000 Members 3,262.1 2,812.0 1,299.8 1,142.9
* NetPass enrollment in Manatee County started to 'kick in' in March 2004, which might result in underestimated
averages.








Table 36: Utilization by Plan Type; Area 6, Polk County, TANF Only

Area 6 Polk County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 10,310 7,940 2,229 1,706
Total Users 10,197 7,827 2,220 1,701
Total Member Months 59,779 40,294 12,244 7,241
Total ER Visits 4,193 2,867 773 553
Total Urgent ER Claims 3,012 2,051 593 368
% Urgent ER (Urgent/ER) 72% 72% 77% 67%
ER Visits/1000 Members 406.7 361.1 346.8 324.2

Total Pharmacy Claims 34,435 23,635 6,586 4,214
Pharmacy/1000 Members 3,340.0 2,976.7 2,954.7 2,470.1
Total Generic Pharmacy Claims 15,554 10,852 2,582 2,120
% Generic Pharmacy Claims 45% 46% 39% 50%

Total Inpatient Admits 372 258 55 59
Total Inpatient Admits/1000 Members 36.1 32.5 24.7 34.6
Total Inpatient Days 1,128 750 211 167
Total Inpatient Days/1000 Members 109.4 94.5 94.7 97.9
Total ACS Admits (Standard) 91 63 18 10
Total ACS Admits/1000 Members (Standard) 8.8 7.9 8.1 5.9
Total ACS Admits (AHCA) 59 42 10 7
Total ACS Admits/1000 Members (AHCA) 5.7 5.3 4.5 4.1
Total ACS Admits (Either) 95 65 19 11
Total ACS Admits/1000 Members (Either) 9.2 8.2 8.5 6.4

Total Office Visits (only CPT codes) 12,546 8,540 2,595 1,411
Total Office Visits/1000 Members 1,216.9 1,075.6 1,164.2 827.1
Total Office Visits
12,500 8,510 2,589 1,401
(CPT codes and 00, 11, 71, 72) 12500 8510 2589 1401
Total Office Visits/1000 Members 1,212.4 1,071.8 1,161.5 821.2
Total Office Visits (extended CPT codes) 14,643.0 9,816.0 3,163.0 1,664.0
Total Office Visits/1000 Members 1,420.3 1,236.3 1,419.0 975.4








Table 37: Utilization by Plan Type; Area 6 Polk County, SSI Only

Area 6 Polk County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 3,835 3,288 510 602
Total Users 3,814 3,265 507 601
Total Member Months 29,808 23,597 3,300 2,911
Total ER Visits 2,664 2,228 191 245
Total Urgent ER Claims 1,628 1,355 130 143
% Urgent ER (Urgent/ER) 61% 61% 68% 58%
ER Visits/1000 Members 694.7 677.6 374.5 407.0
Total Pharmacy Claims 80,831 70,677 4,503 5,651
Pharmacy/1000 Members 21,077.2 21,495.4 8,829.4 9,387.0
Total Generic Pharmacy Claims 37,164 32,830 1,711 2,623
% Generic Pharmacy Claims 46% 46% 38% 46%
Total Inpatient Admits 705 579 44 82
Total Inpatient Admits/1000 Members 183.8 176.1 86.3 136.2
Total Inpatient Days 3,190 2,575 216 399
Total Inpatient Days/1000 Members 831.8 783.2 423.5 662.8
Total ACS Admits (Standard) 201 166 14 21
Total ACS Admits/1000 Members (Standard) 52.4 50.5 27.5 34.9
Total ACS Admits (AHCA) 116 95 10 11
Total ACS Admits/1000 Members (AHCA) 30.2 28.9 19.6 18.3
Total ACS Admits (Either) 212 174 15 23
Total ACS Admits/1000 Members (Either) 55.3 52.9 29.4 38.2
Total Office Visits (only CPT codes) 11,067 9,467 817 783
Total Office Visits/1000 Members 2,885.8 2,879.3 1,602.0 1,300.7
Total Office Visits
10,861 9,303 796 762
(CPT codes and 00, 11, 71, 72) 10,861 6
Total Office Visits/1000 Members 2,832.1 2,829.4 1,560.8 1,265.8
Total Office Visits (extended CPT codes) 12,009 10,190 975 844
Total Office Visits/1000 Members 3,131.4 3,099.1 1,911.8 1,402.0









Table 38: Utilization by Plan Type; Area 9 Palm Beach County, TANF Only

Area 9 Palm Beach County June 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 16,765 11,503 68 6,018
Total Users 15,891 10,896 55 5,645
Total Member Months 120,945 80,557 390 39,998

Total ER Visits 6,764 4,328 16 2,420
Total Urgent ER Claims 4,001 2,554 6 1,441
% Urgent ER (Urgent/ER) 59% 59% 38% 60%
ER Visits/1000 Members 403.5 376.2 235.3 402.1

Total Pharmacy Claims 77,699 51,350 297 26,052
Pharmacy/1000 Members 4,634.6 4,464.1 4,367.6 4,329.0
Total Generic Pharmacy Claims 33,046 20,896 142 12,008
% Generic Pharmacy Claims 43% 41% 48% 46%

Total Inpatient Admits 1,095 712 1 382
Total Inpatient Admits/1000 Members 65.3 61.9 14.7 63.5
Total Inpatient Days 4,017 2,666 1 1,350
Total Inpatient Days/1000 Members 239.6 231.8 14.7 224.3
Total ACS Admits (Standard) 271 173 0 98
Total ACS Admits/1000 Members (Standard) 16.2 15.0 0.0 16.3
Total ACS Admits (AHCA) 156 104 0 52
Total ACS Admits/1000 Members (AHCA) 9.3 9.0 0.0 8.6
Total ACS Admits (Either) 287 187 0 100
Total ACS Admits/1000 Members (Either) 17.1 16.3 0.0 16.6

Total Office Visits (only CPT codes) 25,339 17,554 67 7,718
Total Office Visits/1000 Members 1,511.4 1,526.0 985.3 1,282.5
Total Office Visits
Total Office25,284 17,517 67 7,700
(CPT codes and 00, 11, 71, 72) 25,284 17,517 ...67 7,700
Total Office Visits/1000 Members 1,508.1 1,522.8 985.3 1,279.5
Total Office Visits (extended CPT codes) 29,524 20,463 70 8,991
Total Office Visits/1000 Members 1,761.0 1,778.9 1,029.4 1,494.0








Table 39: Utilization by Plan Type; Area 9 Palm Beach County, SSI Only

Area 9 Palm Beach County June 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass
PhyTrust)
Total Members 6,379 4,449 47 2,181
Total Users 6,273 4,363 47 2,147
Total Member Months 62,420 42,145 376 19,899

Total ER Visits 5,704 4,021 20 1,663
Total Urgent ER Claims 2,638 1,834 5 799
% Urgent ER (Urgent/ER) 46% 46% 25% 48%
ER Visits/1000 Members 894.2 903.8 425.5 762.5

Total Pharmacy Claims 192,899 139,977 836 52,086
Pharmacy/1000 Members 30,239.7 31,462.6 17,787.2 23,881.7
Total Generic Pharmacy Claims 86,230 61,411 326 24,493
% Generic Pharmacy Claims 45% 44% 39% 47%

Total Inpatient Admits 2,651 1,850 18 783
Total Inpatient Admits/1000 Members 415.6 415.8 383.0 359.0
Total Inpatient Days 14,354 10,055 75 4,224
Total Inpatient Days/1000 Members 2,250.2 2,260.1 1,595.7 1,936.7
Total ACS Admits (Standard) 443 344 2 97
Total ACS Admits/1000 Members (Standard) 69.4 77.3 42.6 44.5
Total ACS Admits (AHCA) 299 239 0 60
Total ACS Admits/1000 Members (AHCA) 46.9 53.7 0.0 27.5
Total ACS Admits (Either) 480 365 2 113
Total ACS Admits/1000 Members (Either) 75.2 82.0 42.6 51.8

Total Office Visits (only CPT codes) 24,461 17,994 108 6,359
Total Office Visits/1000 Members 3,834.6 4,044.5 2,297.9 2,915.6
Total Office Visits
24,213 17,811 108 6,294
(CPT codes and 00, 11, 71, 72) 24,213 17,811 ....108 6,29
Total Office Visits/1000 Members 3,795.7 4,003.4 2,297.9 2,885.8
Total Office Visits (extended CPT codes) 26,440 19,408 116 6,916
Total Office Visits/1000 Members 4,144.9 4,362.3 2,468.1 3,171.0









Table 40: Utilization by Plan Type; Area 10 Broward County, TANF Only

Area 10 Broward County April 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass PSN
PhyTrust)
Total Members 30,450 22,088 3,022 3,016 4,243
Total Users 29,019 21,068 2,849 2,836 3,993
Total Member Months 213,882 153,077 17,427 19,273 24,105
Total ER Visits 11,098 7,451 960 1,138 1,549
Total Urgent ER Claims 6,473 4,387 559 647 880
% Urgent ER (Urgent/ER) 58% 59% 58% 57% 57%
ER Visits/1000 Members 364.5 337.3 317.7 377.3 365.1
Total Pharmacy Claims 111,400 78,439 9,506 11,996 11,459
Pharmacy/1000 Members 3,658.5 3,551.2 3,145.6 3,977.5 2,700.7
Total Generic Pharmacy Claims 47,606 32,478 4,271 5,293 5,564
% Generic Pharmacy Claims 43% 41% 45% 44% 49%
Total Inpatient Admits 1,610 1,015 161 183 251
Total Inpatient Admits/1000 Members 52.9 46.0 53.3 60.7 59.2
Total Inpatient Days 5,822 3,592 568 696 966
Total Inpatient Days/1000 Members 191.2 162.6 188.0 230.8 227.7
Total ACS Admits (Standard) 377 279 27 25 46
Total ACS Admits/1000 Members (Standard) 12.4 12.6 8.9 8.3 10.8
Total ACS Admits (AHCA) 232 170 18 9 35
Total ACS Admits/1000 Members (AHCA) 7.6 7.7 6.0 3.0 8.2
Total ACS Admits (Either) 395 292 30 25 48
Total ACS Admits/1000 Members (Either) 13.0 13.2 9.9 8.3 11.3
Total Office Visits (only CPT codes) 38,593 30,332 2,539 3,568 2,154
Total Office Visits/1000 Members 1,267.4 1,373.2 840.2 1,183.0 507.7
Total Office Visits
Scoes a 00, 71,72) 37,168 30,040 2,520 3,534 1,074
(CPT codes and 00, 11, 71, 72)
Total Office Visits/1000 Members 1,220.6 1,360.0 833.9 1,171.8 253.1
Total Office Visits (extended CPT codes) 46,592 36,722 2,910 4,121 2,839
Total Office Visits/1000 Members 1,530.1 1,662.5 962.9 1,366.4 669.1









Table 41: Utilization by Plan Type; Area 10 Broward County, SSI Only

Area 10 Broward County April 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass PSN
PhyTrust)
Total Members 12,239 8,346 1,325 1,661 1,807
Total Users 12,003 8,192 1,294 1,621 1,737
Total Member Months 116,675 78,086 9,799 14,690 14,100

Total ER Visits 11,439 7,534 808 1,513 1,584
Total Urgent ER Claims 5,000 3,298 358 645 699
% Urgent ER (Urgent/ER) 44% 44% 44% 43% 44%
ER Visits/1000 Members 934.6 902.7 609.8 910.9 876.6

Total Pharmacy Claims 371,313 266,076 23,424 39,740 42,073
Pharmacy/1000 Members 30,338.5 31,880.7 17,678.5 23,925.3 23,283.3
Total Generic Pharmacy Claims 158,293 111,860 10,363 17,343 18,727
% Generic Pharmacy Claims 43% 42% 44% 44% 45%

Total Inpatient Admits 5,204 3,509 338 716 641
Total Inpatient Admits/1000 Members 425.2 420.4 255.1 431.1 354.7
Total Inpatient Days 30,525 19,988 1,856 4,426 4,255
Total Inpatient Days/1000 Members 2,494.1 2,394.9 1,400.8 2,664.7 2,354.7
Total ACS Admits (Standard) 802 574 38 82 108
Total ACS Admits/1000 Members (Standard) 65.5 68.8 28.7 49.4 59.8
Total ACS Admits (AHCA) 462 337 19 40 66
Total ACS Admits/1000 Members (AHCA) 37.7 40.4 14.3 24.1 36.5
Total ACS Admits (Either) 842 602 40 87 113
Total ACS Admits/1000 Members (Either) 68.8 72.1 30.2 52.4 62.5

Total Office Visits (only CPT codes) 41,114 30,791 2,416 4,506 3,401
Total Office Visits/1000 Members 3,359.3 3,689.3 1,823.4 2,712.8 1,882.1
Total Office Visits
(CPT codes and 00, 71, 72) 38,585 29,532 2,268 4,318 2,467
(CPT codes and 00, 11, 71, 72)
Total Office Visits/1000 Members 3,152.6 3,538.5 1,711.7 2,599.6 1,365.2
Total Office Visits (extended CPT codes) 46,467 34,573 2,731 5,452 3,711
Total Office Visits/1000 Members 3,796.6 4,142.5 2,061.1 3,282.4 2,053.7









Table 42: Utilization by Plan Type; Area 11 Miami-Dade County, TANF Only

Area 11 Miami-Dade County April 2003 March 2004
TANF Only MediPass
(excluding
Total NetPass and PhyTrust NetPass PSN
PhyTrust)
Total Members 80,132 55,634 6,969 13,752 8,232
Total Users 76,286 53,051 6,463 12,969 7,718
Total Member Months 570,456 377,823 43,059 92,476 57,098
Total ER Visits 24,886 15,979 1,685 3,838 3,384
Total Urgent ER Claims 14,190 9,428 956 2,238 1,568
% Urgent ER (Urgent/ER) 57% 59% 57% 58% 46%
ER Visits/1000 Members 310.6 287.2 241.8 279.1 411.1

Total Pharmacy Claims 467,998 342,750 27,528 73,570 24,150
Pharmacy/1000 Members 5,840.3 6,160.8 3,950.1 5,349.8 2,933.7
Total Generic Pharmacy Claims 194,814 141,165 12,139 30,844 10,666
% Generic Pharmacy Claims 42% 41% 44% 42% 44%

Total Inpatient Admits 4,405 2,875 327 744 459
Total Inpatient Admits/1000 Members 55.0 51.7 46.9 54.1 55.8
Total Inpatient Days 15,358 10,157 1,131 2,562 1,508
Total Inpatient Days/1000 Members 191.7 182.6 162.3 186.3 183.2
Total ACS Admits (Standard) 1,015 688 64 154 109
Total ACS Admits/1000 Members (Standard) 12.7 12.4 9.2 11.2 13.2
Total ACS Admits (AHCA) 587 398 36 87 66
Total ACS Admits/1000 Members (AHCA) 7.3 7.2 5.2 6.3 8.0
Total ACS Admits (Either) 1072 721 69 167 115
Total ACS Admits/1000 Members (Either) 13.4 13.0 9.9 12.1 14.0

Total Office Visits (only CPT codes) 150,247 113,053 8,188 24,632 4,374
Total Office Visits/1000 Members 1,875.0 2,032.1 1,174.9 1,791.2 531.3
Total Office Visits
(CPT codes and 00, 11, 71, 145,445 111,678 8,064 24,312 1,391
(CPT codes and 00, 11, 71, 72) .....
Total Office Visits/1000 Members 1,815.1 2,007.4 1,157.1 1,767.9 169.0
Total Office Visits (extended CPT codes) 169,287 127,032 9,273 27,731 5,251
Total Office Visits/1000 Members 2,112.6 2,283.4 1,330.6 2,016.5 637.9








Table 43: Utilization by Plan Type; Area 11 Miami-Dade County, SSI Only

Area 11 Miami-Dade County April 2003 March 2004
SSI Only MediPass
(excluding
Total NetPass and PhyTrust NetPass PSN
PhyTrust)
Total Members 41,711 30303 3224 6251 4484
Total Users 41,316 27810 2729 5569 3811
Total Member Months 428,568 301,872 26,236 58,528 41,932
Total ER Visits 29,020 20,327 1,415 3,336 3,942
Total Urgent ER Claims 10,339 7,192 569 1,293 1,285
% Urgent ER (Urgent/ER) 36% 35% 40% 39% 33%
ER Visits/1000 Members 695.7 670.8 438.9 533.7 879.1
Total Pharmacy Claims 1,897,101 1,455,868 88,637 215,784 136,812
Pharmacy/1000 Members 45,482.0 48,043.7 27,492.9 34,519.9 30,511.2
Total Generic Pharmacy Claims 818,077 629,575 38,708 92,032 57,762
% Generic Pharmacy Claims 43% 43% 44% 43% 42%
Total Inpatient Admits 17,065 12,581 781 1,832 1,871
Total Inpatient Admits/1000 Members 409.1 415.2 242.2 293.1 417.3
Total Inpatient Days 107,573 80,663 5,143 11,106 10,661
Total Inpatient Days/1000 Members 2,579.01 2,661.88 1,595.22 1,776.68 2,377.56
Total ACS Admits (Standard) 2,891 2,129 113 296 353
Total ACS Admits/1000 Members (Standard) 69.3 70.3 35.0 47.4 78.7
Total ACS Admits (AHCA) 1,591 1,124 45 168 254
Total ACS Admits/1000 Members (AHCA) 38.1 37.1 14.0 26.9 56.6
Total ACS Admits (Either) 3019 2221 115 306 377
Total ACS Admits/1000 Members (Either) 72.4 73.3 35.7 49.0 84.1
Total Office Visits (only CPT codes) 207,812 162,754 9,736 27,169 8,153
Total Office Visits/1000 Members 4,982.2 5,370.9 3,019.9 4,346.3 1,818.2
Total Office Visits
T c s and 00, 1,71,72) 195,943 157,865 9,324 26,316 2,438
(CPT codes and 00, 11, 71, 72)
Total Office Visits/1000 Members 4,697.6 5,209.6 2,892.1 4,209.9 543.7
Total Office Visits (extended CPT codes) 229,502 180,437 10,742 29,773 8,550
Total Office Visits/1000 Members 5,502.2 5,954.4 3,331.9 4,762.9 1,906.8












Table 44: Summary of Utilization by Plan Type-Pasco County



Pasco County Summary-Significant Differences Shown
Compared to MediPass (IRR)

FNP PT PSN

Total ER Visits 0.90 NA

Urgent ER Visits 0.91 NA

Pharmacy Claims 0.79 0.91 NA

Generic Pharmacy Claims 0.88 0.95 NA

Inpatient Admits 1.40 NA

Inpatient Days 1.60 1.33 NA

ACS Admissions (Standard) 0.64 NA

ACS Admissions (AHCA) 0.30 NA

ACS Admissions (Either) 0.47 0.64 NA

Office Visits I 2.78 3.11 NA

Office Visits II 2.74 3.11 NA

Office Visits 111 2.90 3.09 NA


Result tables are available by request.











Table 45: Summary of Utilization by Plan Type-Pinellas County


Pinellas County Summary-Significant Differences Shown


Compared to MediPass (IRR)


FNP


PSN


Total ER Visits 1.10 0.90 NA

Urgent ER Visits 1.11 0.90 NA

Pharmacy Claims 0.84 0.93 NA

Generic Pharmacy Claims 0.96 NA

Inpatient Admits 1.49 NA

Inpatient Days 1.29 NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 2.38 2.51 NA

Office Visits II 2.36 2.52 NA

Office Visits 111 2.40 2.58 NA


Result tables are available by request.











Table 46: Summary of Utilization by Plan Type-Hardee County


Hardee County Summary-Significant Differences Shown


Total ER Visits

Urgent ER Visits


Compared to MediPass (IRR)


PSN

NA

NA


Pharmacy Claims 0.68 0.88 NA

Generic Pharmacy Claims 0.96 NA

Inpatient Admits 0.78 NA

Inpatient Days 0.70 NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 2.38 2.87 NA

Office Visits II 2.39 2.86 NA

Office Visits 111 2.41 2.84 NA


Result tables are available by request.











Table 47: Summary of Utilization by Plan Type-Highlands County



Highlands County Summary-Significant Differences Shown
Compared to MediPass (IRR)


FNP


PSN


Total ER Visits 1.50 NA

Urgent ER Visits 1.57 NA

Pharmacy Claims 0.88 0.88 NA

Generic Pharmacy Claims NA

Inpatient Admits NA

Inpatient Days NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 2.45 NA

Office Visits II 2.46 NA

Office Visits 111 2.44 NA


Result tables are available by request.











Table 48: Summary of Utilization by Plan Type-Hillsborough County



Hillsborough County Summary-Significant Differences Shown
Compared to MediPass (IRR)

FNP PT PSN

Total ER Visits 10.90 1.04 NA

Urgent ER Visits 1.11 1.11 NA

Pharmacy Claims 0.83 0.93 NA

Generic Pharmacy Claims 0.88 0.97 NA

Inpatient Admits 0.82 NA

Inpatient Days 0.78 NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 2.51 2.59 NA

Office Visits II 2.54 2.68 NA

Office Visits 111 2.58 2.60 NA

Result tables are available by request.











Table 49: Summary of Utilization by Plan Type-Manatee County


Manatee County Summary-Significant Differences Shown


Compared to MediPass (IRR)


FNP


PSN


Total ER Visits NA

Urgent ER Visits NA

Pharmacy Claims 1.20 0.82 NA

Generic Pharmacy Claims 0.91 NA

Inpatient Admits NA

Inpatient Days NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 3.29 3.22 NA

Office Visits II 3.29 3.20 NA

Office Visits 111 3.26 3.38 NA


Result tables are available by request.











Table 50: Summary of Utilization by Plan Type-Polk County



Polk County Summary-Significant Differences Shown
Compared to MediPass (IRR)

FNP PT PSN

Total ER Visits 0.92 NA

Urgent ER Visits NA

Pharmacy Claims 0.84 0.92 NA

Generic Pharmacy Claims 0.94 0.87 NA

Inpatient Admits 0.75 NA

Inpatient Days 0.83 NA

ACS Admissions (Standard) NA

ACS Admissions (AHCA) NA

ACS Admissions (Either) NA

Office Visits I 2.78 2.62 NA

Office Visits II 2.77 2.62 NA

Office Visits 111 2.84 2.72 NA

Result tables are available by request.











Table 51: Summary of Utilization by Plan Type-Palm Beach County



Palm Beach County Summary-Significant Differences Shown
Compared to MediPass (IRR)

FNP PT PSN

Total ER Visits 0.96 NA NA

Urgent ER Visits NA NA

Pharmacy Claims 0.89 NA NA

Generic Pharmacy Claims 0.94 NA NA

Inpatient Admits 0.89 NA NA

Inpatient Days 0.84 NA NA

ACS Admissions (Standard) 0.76 NA NA

ACS Admissions (AHCA) 0.67 NA NA

ACS Admissions (Either) 0.79 NA NA

Office Visits I 1.23 NA NA

Office Visits II 1.24 NA NA

Office Visits 111 1.25 NA NA

Result tables are available by request.











Table 52: Summary of Utilization by Plan Type-Broward County



Broward County Summary-Significant Differences Shown
Compared to MediPass (IRR)

FNP PT PSN

Total ER Visits 0.92 1.20

Urgent ER Visits 1.19

Pharmacy Claims 0.84 0.92 0.78

Generic Pharmacy Claims 0.94 0.87 0.83

Inpatient Admits 0.87 0.91

Inpatient Days 0.83 0.89

ACS Admissions (Standard) 0.77

ACS Admissions (AHCA) 0.75

ACS Admissions (Either) 0.80

Office Visits I 1.20 1.09 0.55

Office Visits II 1.20 1.09 0.32

Office Visits III 1.22 1.07 0.57


Result tables are available by request.











Table 53: Summary of Utilization by Plan Type-Miami-Dade County


Miami-Dade County Summary-Significant Differences Shown


Compared to MediPass (IRR)


Total ER Visits 0.93 0.96 0.14

Urgent ER Visits 0.94 1.20

Pharmacy Claims 0.92 0.78 0.69

Generic Pharmacy Claims 0.92 0.82 0.69

Inpatient Admits 0.91 0.89

Inpatient Days 0.99

ACS Admissions (Standard) 0.86 0.83

ACS Admissions (AHCA) 0.78 1.28

ACS Admissions (Either) 0.88 0.84 1.10

Office Visits I 1.19 1.12 0.37

Office Visits II 1.18 1.12 0.12

Office Visits III 1.19 1.13 0.37


Result tables are available by request.




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