Multidimensional work sampling to evaluate the effects of computerization in an outpatient pharmacy


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Multidimensional work sampling to evaluate the effects of computerization in an outpatient pharmacy
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vii, 113 leaves : ill. ; 29 cm.
Rascati, Karen Lewis, 1956-
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Subjects / Keywords:
Pharmacies -- organization & administration   ( mesh )
Computers   ( mesh )
Automatic Data Processing   ( mesh )
Pharmacy thesis Ph.D   ( mesh )
Dissertations, Academic -- Pharmacy -- UF   ( mesh )
bibliography   ( marcgt )
non-fiction   ( marcgt )


Thesis (Ph.D.)--University of Florida, 1986.
Bibliography: leaves 105-112.
Statement of Responsibility:
by Karen L. Rascati.
General Note:
General Note:

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University of Florida
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All applicable rights reserved by the source institution and holding location.
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oclc - 16955508
notis - ACZ7885
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In memory of

my father,

Richard D. Lewis


My deepest gratitude is expressed to the members of my

dissertation committee, especially Dr. Carole L. Kimberlin, to whom I

am deeply indebted for the time and effort, as well as the guidance

and encouragement she has supplied throughout my graduate education.

My gratitude is also extended to Dr. William McCormick, who

believed in my abilities, encouraged me to enter graduate school, and

provided useful suggestions and constructive criticism during this


I am also grateful to Robert Williams, who gave not only of his

valuable time but also provided the financial assistance necessary to

undertake this study.

I would like to thank Dr. Douglas Bradham. Though relocation

forced him to withdraw from my committee, his suggestions during the

proposal stage were helpful.

One of Dr. Bradham's most helpful suggestions was that of asking

Dr. Ralph Swain to be on my committee. Dr. Swain's insight into the

industrial engineering aspects of this study were invaluable.

I also wish to thank Paul Foley, supervisor of the outpatient

pharmacy where the study took place, and the entire staff of the

outpatient pharmacy for being cheerful subjects.

Finally, I must thank my husband, Joe, whose emotional support,

understanding, and patience throughout my years as a graduate student

is most deeply appreciated.


ACKNOWLEDGMENTS................... ........................ ii

ABSTRACT ........................................... ........... vi


1 INTRODUCTION ............................. ..............1

Theoretical Framework..................................5

2 REVIEW OF THE LITERATURE................................9

Work Measurement...................................... 9
Subjective Evaluation............................10
Direct Time Study.................................11
Work Sampling....................................14
Baseline activities..........................15
Comparison of activities.....................18
Critique of work sampling research............21
Multidimensional Work Sampling....................24
Statistical Data..................................27
Standard Time Data................................27
Summary Table....................................29
Job Satisfaction......................................29
Job Descriptive Index (JDI).......................34
Pharmacy Literature on Job Satisfaction............35

3 METHODS...............................................38

Research Objectives...................................38
Research Hypotheses...................................38
Variables and Their Measurement........................39
Setting....... .........................................40
Measuring Instruments.................................41
Multidimensional work sampling....................41

Equipment ..................................... 43
Recording of Data............................45
Direct Observation...............................47
Time Clock........................................48
Job Satisfaction.................................49
Data Analysis.........................................49
Multidimensional Work Sampling....................49
Time Clock........................................51
Job Satisfaction.................................51

4 RESULTS...............................................53

Multidimensional Work Sampling.........................53
Internal Consistency ............................69
Direct Observation....................................71
Time Clock............................................76
Job Satisfaction......................................80

5 SUMMARY AND CONCLUSIONS ...............................83


AMBULATORY PHARMACY PRACTICE...........................88

B DEFINITIONS OF DIMENSIONS.............................89

C TEST GIVEN TO EMPLOYEES................................92


E DIAGRAM OF OUTPATIENT PHARMACY...........................98

F JOB DESCRIPTIVE INDEX ................................99



BIOGRAPHICAL SKETCH.............................................113

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




May, 1986

Chairperson: Carole Kimberlin
Major Department: Pharmacy

A study was undertaken to examine the effects of computerization

in a large outpatient pharmacy. A multidimensional work sampling

technique was used to measure and compare the percent of time spent on

various tasks before and after computerization. The percent of time

spent on some clerical tasks decreased, as expected, and the percent

of time spent on the clinical task of detecting prescription problems

increased, but not significantly.

This multidimensional work sampling approach was compared with a

direct observation work sampling method to determine how well the two

correlate and in what areas they give comparable results. Findings

from this section of the study suggest that the multidimensional

approach may be more accurate at capturing the clinical aspects of

pharmacy practice than a direct observation method.

Additionally, a time clock method was used to measure and compare

the time it took to process a prescription, while a survey was used to

measure and compare employee satisfaction before and after

computerization. The time to process a prescription increased after

computerization, primarily due to the increase in time to enter

information into the computer.

The job satisfaction of the employees was similar before and

after computerization in all categories tested, and no significant

changes were found. Lastly, changes made as a result of these

findings are discussed.



The amount of time pharmacists spend on nonprofessional versus

professional tasks has been a source of concern in the profession.

Pharmacists are highly educated, requiring five to six years of higher

education, yet many spend much of their time performing tasks that do

not require the high level of skills obtained through this

education. It has been suggested that technological advances, such as

computers, could release pharmacists from routine, clerical tasks,

thus allowing more time for professional activities. In order to

assess whether computers do in fact allow more time which is used for

professional activities, the effects of computer installation on the

various activities of the pharmacist must be evaluated.


This study was designed to measure the impact of installing a

computer in the outpatient pharmacy of a large teaching hospital. A

second objective was to evaluate a new work sampling method of

collecting data.

In measuring the impact of computer installation, the time spent

on clerical and clinical activities was compared before and after

computerization based on data collected through a multidimensional

work sampling technique. In addition, the time to process a

prescription was compared using a time clock method. Third, in order

to assess the impact of computerization on the personnel involved, job

satisfaction of the employees was measured and compared before and

after computerization. In evaluating the multidimensional work

sampling technique, a sample of observations using this method was

compared with observations collected by a direct observer.

Advocates of computerization claim that computer usage will

alleviate some of the clerical tasks of order processing, which will

allow pharmacists more time to pursue clinical activities. However,

there is a dearth of literature to substantiate this claim, especially

in the outpatient setting. In fact, one study (Kohout, Broekemeir, &

Daniels, 1983) recorded a decrease in time spent counseling patients

after upgrading a computer system in an outpatient pharmacy.

The majority of previous studies used work sampling techniques

that observed the tasks of pharmacists through the use of a camera or

an observer. It may be difficult, at best, to measure clinical

activities using these techniques because many of the problem-solving

or monitoring activities are internal processes not visible to an

observer. For example, a pharmacist screening a patient profile for

interactions may be recorded as performing an order processing


A relatively new work sampling technique was used in this study

to more accurately measure clinical activities, which will in turn

allow for a more accurate comparison of these activities before and

after installation of the computer system. More specifically, this

study used a multidimensional work sampling approach which is a method

of self-reporting work activities (Robertsen, 1982).

This method of recording clinical and clerical functions allowed

for the collection of data that would be analyzed for various

purposes. One purpose would be to answer the hypotheses tested in

this study. Another would be to evaluate how well the computer met

the objectives of the pharmacy department in the hospital. The

pharmacy department had submitted a proposal for the acquisition of

the computer, which listed four primary objectives to be met by the

installation of a computer. These were:

1. The improvement of patient care by avoiding drug interactions,

increasing patient consultation, avoiding prescription

duplication, and providing accurate up-to-date patient


2. The elimination of hand processing of third-party

prescriptions, which would allow more accurate and timely


3. The provision of a more accurate method of fiscal management

by improved inventory control for controlled and noncontrolled

substances, as well as more efficient prescription pricing and


4. Bringing the pharmacy into compliance with standards of the

Joint Commission on Accreditation of Hospitals and the

American Society of Hospital Pharmacists, which recommends the

use of patient profiles. Prior to installation of the

computer, the outpatient pharmacy had not kept patient profile

records on medication use.

An evaluation of whether or not the first three objectives were met

can be determined with the data collected by this study.

Because of the spiraling costs of health care, all health

professionals, including pharmacists, are feeling the pressure to

contain costs. Many in the health care field are looking to

technological changes and job redesign in order to decrease operating

costs and/or increase job satisfaction, which would hopefully lead to

a decreased turnover of personnel. Yet often these changes are

implemented without being evaluated as to their success in reducing

costs or improving morale. Without such evaluations, administrators

may be reluctant to implement these changes even if they have the

potential to achieve the desired outcomes.

Dickson and Rodowskas (1975) and Roberts, Kvalseth, and Jermstad

(1982) contend that one way for pharmacy to reduce costs is to utilize

personnel resources more efficiently. Effective administration and

management in an institutional pharmacy was, in fact, one competency

identified as crucial by the American Society of Hospital Pharmacists

and the American Association of Colleges of Pharmacy ("Statement on

the competencies," 1975).

One way of improving the efficiency of personnel resources that

is frequently advocated is to install a computer system in order to

reduce clerical activities, so that pharmacists may spend their time

more professionally and productively. The American Pharmaceutical

Association (APhA) statement on drug control systems (1974) urges

pharmacists to use electronic data processing (EDP) to decrease paper-

handling, so that they may expand their clinical roles.

Yet installing a computer system does not guarantee improved

efficiency; one must evaluate the changes caused by the installation

(Kohout et al., 1983). The changes which must be evaluated include

not only the cost savings and shift in activities, but also the

feelings of the personnel involved. Measuring these changes is not

simple, as each task must be evaluated properly (Davis, 1979) and

reliable measures used.

As stated previously, there has not been a great deal of research

published which evaluates the impact of computer systems in hospital

pharmacies. Burleson (1982), in a comprehensive review of hospital

pharmacy computer systems, suggests that the fact that there are so

few controlled studies evaluating the effects of a computer system may

explain why there is not a greater acceptance of computer systems in

hospital pharmacies. Therefore, as all authors reviewed agreed, there

is a need for studies evaluating the effects of this new technology in

order to document its potential for reducing costs and increasing job

satisfaction of pharmacy personnel.

Theoretical Framework

This study evaluated the changes that occurred after installation

of a computer system in an outpatient pharmacy setting. This

installation of the computer was considered a work innovation. More

specifically, it was classified as a change in work design. Walton

(1983) summarizes the conception of work innovation as containing

three levels: (a) design techniques, (b) work culture ideals, and (c)

intended results. Design techniques are the elements of the work

organization that people can alter directly. Intended results are the

criteria by which to measure effectiveness. The work culture mediates

the impact of the design techniques on the intended results.

Presented below is Table 1, adapted from Walton (1983), containing

examples of each level.

Table 1
Levels of Work Innovation Conception

Level I Level II Level III
Design Techniques Work culture ideals Intended results

Job design High level skills & flexi- For business:
Pay ibility in using them Low cost
Supervisor's Role Openness Quick Delivery
Training Mutual influence Low turnover
Goal setting Equity For quality of work
Communication Trust life:
Status symbols Responsiveness Self-esteem
Leadership patterns Problem solving Security

Adapted from Walton (1983).

In this study, the framework was adapted as follows. Level I,

design technique, was the element that one can alter directly. Our

independent variable, installation of the computer, was the job design

change. Level II, work culture ideals, mediates the impact of Level

I, installation of the computer, on Level III, intended results. One

example Walton (1983) uses as a mediating factor is an increase in

high level skills and the flexibility in using them. It was

hypothesized that, as a result of the computer, less time would be

spent on clerical activities, then allowing more time to be spent on

clinical activities which require a higher level of skills.

Level III, intended results, is broken down into two subgroups:

(a) intended results for business and (b) intended results for quality

of work life. Walton (1983) includes quick delivery as an example of

an intended result for business. It was hypothesized that

installation of the computer would decrease the time it takes to

process a prescription. This, in turn, would result in faster

delivery of the prescription to the patient. Intended results for the

quality of work life include an increase in self-esteem. It was

hypothesized that the use of more complex skills would result in a

higher level of job satisfaction. The level ofjob satisfaction was

determined by surveying the employees before and after the

installation of the computer in order to assess if employees were more

satisfied after the computer was operational.

Diagramnatically, the model used in this study is as given in

Table 2.

Table 2
Levels of Work Innovation Conception Used in Current Study


Because the primary goals of this study were to evaluate the

effect of computerization on work activities and to compare two

methods of work measurement, a review of the use of work measurement

in pharmacy literature will be presented first. The measurement of

the effect of computerization on job satisfaction was a secondary

aspect of this study, so a more limited review of this literature as

it pertains specifically to pharmacy will also be presented.

Work Measurement

Methods of work measurement applicable to the practice of

pharmacy were outlined by Roberts et al. (1982). These include

subjective evaluation, statistical data, self reporting, stop-watch

time study, standard time data, and work sampling. This review will

examine the use of these techniques in pharmacy research, which will

be used to identify dimensions of the jobs of pharmacists used in

other research; sampling procedures, sample sizes and sampling frames

utilized; methods of validating the work sampling procedures which

were used; and the types of data analyses conducted.

Subjective Evaluation

Subjective evaluation is a method whereby one estimates the time

spent on various activities based on subjective judgment or past

experience. This is not a very precise method and usually deviates,

on average, 25% from the true measure (Roberts et al., 1982). Neal

(1981) used a form of subjective evaluation when analyzing the costs

and savings of a computer information system for a hospital pharmacy

department. A labor savings of 3.0 full-time equivalents (FTE) for

technicians was estimated by analyzing each job description and using

subjective evaluation to predict the impact of computerization on each


Kirking, Ascione, Thomas, and Boyd (1984) also utilized this

method when researching the relationships between computer use and

pharmacists' professional behavior. A survey of both computer users

and nonusers asked pharmacists to estimate the time they spent on

various professional activities. Mail questionnaires were sent to a

sample of southern Michigan pharmacists asking them to record the time

spent on the various activities listed, and a response rate of 65.7%

yielded 213 usable questionnaires. Those with computers reported

encountering more drug-related problems than nonusers, and more

frequent contact with physicians concerning drug-therapy problems.

There was little difference in the time spent on patient counseling.

The authors conclude that while some professional activities may

increase with the use of a computer, others may not. The authors

admit that this method has limitations, primarily the lack of

precision in estimates, but suggest that it can be a useful method for

formulating hypotheses for future research.

Direct Time Study

This method of work measurement involves straightforward timing

of specified activities as they are performed. The work must be

divided into elements that have a logical sequence, are as short as

possible, and have physically observable starting and ending points

(Hepler, 1979; Roberts et al., 1982). Direct time study is most

appropriately applied to highly repetitive technical tasks such as

determining the time it takes to fill a specific type of admixture

(Allinson, Stach, Sherrin, & Latiolais, 1979; Turco, 1992) or to

compare the time to fill various drug manufacturers' piggyback bottles

(Anderson & Soares, 1985).

Although this method is most precise for measuring relatively

short times with a detailed breakdown of the elements involved, many

researchers in hospital pharmacy use direct time study to estimate

longer and more variable activities. For example, studies have used

direct time study to collect baseline data on the time to process a

prescription (Beaman & Kotzan, 1982; Donehew & Hammerness, 1978), the

time spent on controlled substance drug distribution (Blasingame,

1969), and the time spent on clinical activities (Schwartz & Swanson,

1975), but the variance and standard deviations when reported were


Direct time methods have also been used in combination with other

methods of work measurement. Hanna (1983) combined direct time study

with statistical data measures, such as the number of new and refill

inpatient orders and the number of new and routine IV orders, in order

to determine the workload. The workload was, in turn, graphed against

the time of day in order to provide a visual method for scheduling.

Order processing turnaround time has also been measured using

this method. These studies include comparisons of turnaround time of

centralized versus decentralized systems (Hibbard, Bosso, Sward, &

Baum, 1981; Kvanz, Cummins, Bennett, & Fontana, 1982; Lomonte, Besser,

& Thomas, 1983; Reynolds, Johnson, & Longe, 1978), a comparison of

nonunit-dose versus unit-dose distribution systems (Norvell,

McAllister, & Bailey, 1983), a comparison of filling and checking

times when the pharmacy changed from twice daily to once daily cart

delivery (Galloway, Leppard, & Spartz, 1978), and comparisons of

processing times before and after computerization of an outpatient

pharmacy (Moss & Pounders, 1985; Unertl, Weiderholt, & Peterson,

1984). Although each showed a decrease in the time to process orders

after the change being studied was implemented, the variation or

standard deviation of the total times was again quite large, when it

was reported.

The studies by Moss and Pounders (1985) and Unertl et al. (1984)

are of particular interest because they deal with the effect of

computerization on outpatient prescription processing times. Unertl

et al. (1984), when evaluating the implications of installing an

outpatient pharmacy computer system, looked at both time and cost

considerations. A stop-watch time and motion study was used to

evaluate the time considerations. The observer followed 76 sets of

prescriptions (200 total) through the dispensing process before

installation and 86 sets of prescriptions (221 total) after

installation of the computer. The total dispensing time decreased

when the computer was used, but the authors contend that costs

associated with the computer were high. This might have been expected

because the pharmacy studied fills only 10,000 prescriptions per year,

or less than forty per day.

Moss and Pounders (1985) also used a stop-watch method of time

study to measure the impact of computerization on dispensing time in

an outpatient setting. The steps in processing a prescription were

divided into four categories (receipt, delay time, label generation,

and filling time) and a varying number of random samples for each step

were timed on several different days. Mean times of prescription

processing per patient were 7.0 minutes for both new and refill

prescriptions before the computer was installed compared with 6.28

minutes for new and 4.61 minutes for refill prescriptions after the

computer was installed. Computerization decreased the amount of time

spent on miscellaneous activities by 78 minutes per day, but computer-

related activities added 58.7 minutes per day. The net time savings,

assuming an average prescription volume of 176 per day, would be 196.6

minutes per day. The authors maintain that this time savings will

hopefully translate into expanded patient counseling activities and

more efficient use of the personnel, yet they did not attempt to

measure whether any of these changes had occurred.

Work Sampling

The next type of work measurement to be reviewed is work

sampling. It consists of recording a large number of instantaneous

observations, taken at random intervals, allowing one to approximate

the proportion of a worker's time spent in various activities. This

method is most applicable when multiple employees are being studied,

when events do not occur in temporal clusters, or when direct time

study may interfere with the measured activities (Hepler, 1979).

Roberts et al. (1982) summarized some advantages of work sampling as:

1. It allows for simultaneous study of several workers.

2. It yields complete information about the total observation.

3. It is the technique most acceptable to professional workers.

Barnes (1968) also pointed out the following advantages to work


1. It costs 5-50% less to do than continuous time study.

2. Observations may be spread out over weeks to minimize day to

day variations.

3. It decreases somewhat the bias that occurs when the worker

knows the continuous study is taking place at that time.

Some drawbacks of work sampling include that one must create task

categories which are mutually exclusive and exhaustive, yet keep the

number of categories manageable. Also, these categories must be

easily recognized by visual observation (Heiland & Richardson, 1957).

Two studies evaluated the work sampling method as applied to

pharmacy. Dickson (1978) looked at whether fixed interval work

sampling provided results comparable to random interval

observations. He found no significant differences between the two

methods, but cautioned that others should replicate these findings

before drawing any final conclusions.

The second study, by Segail and Kotzan (1979), compared work

sampling data from direct observation with observations sampled from

film recorded by a fixed camera. They summarized their findings as


1. Observations by the camera had limited range, whereas the

personal observer was not constrained to a limited area.

2. The camera required a more general observation form.

3. Interaction between the direct observer and the staff provided

a potential for experimental bias.

Two common objectives of pharmacy research utilizing work

sampling are (a) to document baseline workload activities to improve

task delegation or staffing patterns and (b) to compare workload

activities under different conditions (Kvanz et al., 1982). Studies

utilizing work sampling for both of these purposes will be reviewed.

Baseline activities. Examples of hospital pharmacy research

which had the purpose of documenting baseline activities in order to

improve task delegation or staffing patterns include Barsness and

Trinca (1978); Dipiro, Gousse, and Kubica (1979); Dostal, Daniels,

Roberts, and Giese (1982); Johnston (1972); Sebastian and Thielke

(1983); and Summerfield, Go, Lamy, and Derewicz (1978). Johnston

(1972) used pharmacists and pharmacy residents as observers to collect

work sampling data for an inpatient pharmacy. Over a 2-week period

12,500 observations of pharmacists and technicians were collected (the

total number of employees observed was not reported). The direct

results of this work sampling method were not discussed, but were

instead combined with workload data to calculate the number of

pharmacists and technicians needed.

Barsness and Trinca (1978) measured the time spent on

professional and nonprofessional activities performed by clinical

staff pharmacists. Three pharmacists were observed over a 1-week

period, and 2,070 observations were recorded. Findings included that

the pharmacists studied spent 72% of their time on professional

activities and 28% on nonprofessional activities.

Dostal et al. (1982) measured professional and nonprofessional

activities for satellite pharmacists under various staffing

arrangements. Ten pharmacy administrators and residents recorded

8,440 observations over a 2-week period. Thirty-seven activities were

categorized as professional or nonprofessional. Overall, 52% of the

pharmacists' time was spent on professional activities, and this

percentage increased when one pharmacist worked with more than one


Summerfield et al. (1978) studied both pharmacists and

technicians working in a satellite pharmacy using 21 categories of

activities. Over a 3-week period, 800 observations per shift were

recorded using observational work sampling. Findings included that

pharmacists spent 17.5% of their time in unproductive activities

compared with 23% for technicians. When the results of the work

sampling observations were combined with output and census data, it

was suggested that census alone was not a reliable indicator of

pharmacy workload.

Dipiro et al. (1979) utilized work sampling to determine the

amount of unproductive or underproductive activities of staff

pharmacists, again under various staffing arrangements. Observational

work sampling was used, and 7,322 observations were collected.

Thirty-three subtasks were collapsed into seven major categories.

This study reported the percent of time spent in each category as

19.5% in dispensing requiring professional judgment, 37.8% in

dispensing not requiring professional judgment, 6.5% in therapy-

related activities, 13.2% idle, 8.9% absent, 9.4% in communication and

coordination activities, and 0.5% in outpatient activities.

Sebastian and Thielke (1983) used statistical data including the

number of unused and expired large volume parenterals returned to the

pharmacy, in combination with work sampling when performing a work

analysis of an admixture service. This was the only study reviewed

where the authors state that the reliability of the observers of the

work sampling portion of the analysis was tested, but they did not

report the percent of agreement. Four procedural changes were

implemented as a result of the study (automated label preparation, use

of a new TPN base solution, batch production, and schedule changes).

Research in the community pharmacy setting have also utilized

work sampling to document pharmacists' activities (Boyd, Yung, &

Parker, 1982; Dickson & Rodowskas, 1975; Rodowskas & Gagnon, 1972).

Rodowskas and Gagnon (1972) studied 29 community pharmacies over a 4-

month period. Pharmacists and senior pharmacy student observers used

eight categories when classifying the percent of time spent on various

activities. It was reported that the majority of a pharmacist's time

(45%) was spent on clerical activities, while 8% was spent on

consultative activities.

Dickson and Rodowskas (1975) used observers in 20 chain

pharmacies to obtain baseline data on existing community pharmacy

practice. They used a work sampling technique to collect 14,400 total

observations (720 per pharmacy), and these observations were

classified into 28 task categories. Analysis of the results indicated

that manager pharmacists spent more time in clerical activities than

staff pharmacists, and that idle time was related to prescription

volume. They also reported that time spent on patient counseling was

related to staffing patterns, prescription volume, and job title, but

none of these relationships were significant.

Boyd et al. (1982) also used observational work sampling to

collect data in a community pharmacy over a 3-week time period.

Forty-four activities were divided among six categories: dispensing,

clerical, communications, education, management, and other. Findings

included that the pharmacists spent most of their time on

nonprofessional activities (82.4% as compared to 17.6% spent on

professional activities).

Comparison of activities. Hospital pharmacy research utilizing

work sampling for the purpose of comparing activities includes

comparisons of centralized versus decentralized activities of

pharmacists (John, Burkart, & Lamy, 1976) and nurses (Wadd &

Blissenbach, 1984), comprehensive versus product-oriented or

distributive activities (Nelson, Gourley, Tindall, & Anderson, 1977),

and activities before and after computer installation (Sikora &

Kotzan, 1981) or computer upgrading (Kohout et al., 1983). The first,

by John et al. (1976), used an observational work sampling method to

compare personnel activities in centralized units with those in

decentralized units of the pharmacy. Forty-one subtasks were

condensed into four major categories. These were (a) supervisory, (b)

therapy-related, (c) dispensing, and (d) educational. Pharmacists and

nonpharmacists were evaluated by using 1,083 observations for

pharmacists in the decentralized units, 1,130 observations for

nonpharmacists in the decentralized units, 1,036 observations for

pharmacists in the centralized unit, and 1,219 observations for

nonpharmacists in the centralized unit. Major findings included (a)

pharmacists in decentralized units spent more time in therapy-related

activities than pharmacists in the centralized unit and (b)

nonpharmacists in both units spent over 95% of their time in

dispensing activities.

Nelson et al. (1977) compared clinical activities of pharmacists

providing comprehensive pharmacy services with those offering product-

oriented services. Work sampling using observers was conducted over a

6-month period, and 1,451 observations were collected and divided

among 19 task categories. These results were compared with those of a

previous study of product-oriented pharmacies. Nonproductive time

(absent, idle, travel) comprised 15% of the time in the comprehensive

service type pharmacy versus 52.1% in the product-oriented service

type. The authors found that one-third of the pharmacists' time was

spent in clinical activities in the comprehensive service pharmacy,

but they do not compare this to the time spent in clinical activities

by the product-oriented pharmacies.

Sikora and Kotzan (1981) used camera-based work sampling to

record observations needed before and after computerization of an

inpatient hospital pharmacy. A total of 2,000 observations were

analyzed, comprised of 900 to 1,000 observations each from before and

after the computer installation. Originally 27 task categories were

used, but some were collapsed for statistical purposes, resulting in

21 task categories. The major findings included (a) after

computerization there was an increase in the time spent working with a

profile/CRT and (b) there was a decrease in the time spent typing.

They also reported that a tendency was found for personnel to be drawn

to the computer terminal area.

Kohout et al. (1983) compared activities in an outpatient setting

before and after the upgrading of the computer system. The new system

added profiles, drug-drug interactions, auxiliary label notification,

and prescription pricing to the existing capabilities. Work sampling

was used to collect 5,897 observations (about 750 per worker) and

these results were compared with those from a previous study of that

pharmacy. These observations were divided into four major

categories: (a) prescription processing, (b) inventory maintenance,

(c) problem solving, and (d) miscellaneous activities. After the

computer was updated, pharmacists were found to spend more time coding

prescriptions and less time on patient counseling. Although an

overall time savings occurred, further changes were suggested to

increase staff efficiency.

One study of community pharmacies also used work sampling for the

purpose of comparing activities and looked specifically at the effect

of computerization. McKay, Sharpe, Smith, and Jackson (1979) compared

seven treatment pharmacies with five control pharmacies, with a

treatment pharmacy being one that installed a computer system during

the study. All 12 sites were evaluated before and after the

installation of the computers in the treatment pharmacies. The

researchers used 105 task categories, but did not report the number of

observations conducted. The time spent on distribution of drugs was

found to increase in the treatment group after installation of the

computers. The authors explained that this increase was due to the

extra activities included in the dispensing of a prescription after

computerization (screening profiles, performing inventory, pricing,

and billing). Before the change, these activities were performed at

separate times. No statistically significant increase in professional

activities was found after computer installation.

Critique of work sampling research. Work sampling observations

should be collected over a long term to decrease the bias from

transient causes and increase the likelihood of representative

behavior (Hepler, 1979). There seems to be no consensus on the

appropriate length of the collection period, as the studies reviewed

ranged from a low of 1 week (Barsness & Trinca, 1978) to a high of 6

months (Nelson et al., 1977). On the other hand, the total number of

observations collected was more uniform, with most studies collecting

between 750 and 1,000 observations per employee observed. In

addition, few studies reported doing any check of measurement

reliability or validity. Any type of measurement used in research,

including that used in work sampling, should be evaluated in terms of

reliability and validity (Anastasi, 1976; Kerlinger, 1973). The

importance of the determination of both the reliability and validity

of measures of work performance was outlined by Landy and Farr (1983).

In observational studies, the most common reliability measure is

observer agreement, or interrater reliability (Barker, 1980).

Whenever more than one observer is used, the researcher should compare

their recordings for the same events, either during paired

observations or while observing simulated work situations such as

those on a videotape. The number of agreements divided by the number

of agreements and disagreements is a simple formula often used to

measure this type of reliability (Barker, 1980; Haynes, 1978). When

only one observer is used, the reliability of his or her observations

should be established by comparison with a standard established by

experts or by an independent trained observer. Some of the studies

reviewed utilized more than one observer to collect data (Dostal et

al., 1982; John, Burkart, & Lamy, 1976; Johnston, 1972; Nelson et al.,

1977; Summerfield et al., 1978), yet none presented data on

interobserver agreement.

In addition to interobserver agreement estimates, the reliability

of measurement systems, including observational systems, should be

evaluated on their internal consistency (Haynes, 1978; Haynes &

Wilson, 1979) as interobserver agreement data gives no information on

the consistency of the measure over time or the consistency within

homogeneous portions of an instrument (Haynes & Wilson, 1979). None

of the pharmacy studies examined reported either internal consistency

measures or estimates of the stability of the measures over time.

In addition to establishing the reliability of the instruments,

the validity of the instruments, particularly the content validity

and, perhaps, the criterion-related validity should be established.

Most of the pharmacy research did not report how the content validity

of the work dimensions were established. Only the studies which

compared two work sampling procedures (Dickson, 1978; Segail & Kotzan,

1979) compared one method of measurement with an independent criterion


The comparison studies reviewed previously used no statistical

test, a t-test, a z-test or a chi-square test to determine if a

difference existed in the activities they were comparing. The use of

a z-test or t-test for the comparison of activities in the studies of

McKay et al. (1979) and John et al. (1976) may not be an appropriate

test because both studies performed multiple tests (20 and 8,

respectively), which increases the chance of an erroneous conclusion

(Marks, 1982). A chi-square test was used in the studies of John et

al. (1979), Kohout et al. (1983), and Sikora and Kotzan (1981).

Because the chi-square test does not control for the fact that there

are multiple observations of the same subject and thus treats all

observations as independent, the large sample sizes involved lead to a

chi-square test that is overly sensitive to very slight relationships

among variables. As a possible result, all three studies found highly

significant differences (p<.O05 to _<.0001).

Multidimensional Work Sampling

One variation of work sampling that has recently been applied to

pharmacy practice is multidimensional work sampling (Hadsall et al.,

1982; Robertsen, 1982). Various dimensions of the work are defined

which, when examined together, describe the tasks being measured.

Examples of dimensions used are the activity, which is the means by

which something is accomplished; the contact, which records for whom

the activity is performed; and the function, or the purpose of the

activity. An example of an observation recorded using this method may

be the activity, contact, and function of "phone"-"physician"-"correct

problem" to describe calling a physician to discuss a drug


This procedure involves workers reporting their own activities at

randomly sampled intervals in a self-report method. When a random

audio signal is sounded, the worker picks one item from each list of

dimensions to describe the task being performed. These choices are

recorded by the worker at that time by making a series of punches on a

portable console. The data are recorded directly onto computer punch

cards and can be analyzed quickly and accurately. Robertsen (1982)

contends that advantages to this system include (a) there is no

observer bias; (b) tasks are easier to divide into mutually exclusive

and exhaustive categories; and (c) one is able to measure complex and

unobservable tasks, such as what takes place in confidential meetings,

on the phone, or in the pharmacists' head.

Self-reporting may encourage false submission of data, yet

Robertsen (1980) contends that this problem is minimized by the

multidimensional approach for three reasons. First, the data

collected is quantitative, multidimensional, and accumulated at a high

rate. It would be very difficult to falsify this type of complex data

in a consistent fashion. Secondly, if other workers are being

measured simultaneously, the subject would not wish to differ greatly

from the others. Lastly, since the subject expends his own time and

effort in recording the data, and new programs may be implemented as a

result of his effort, he has an incentive to provide accurate data.

Brisley and Dorsett (1980), in an issue of Industrial Engineering

devoted to the topic "Work Measurement in the 80's," predicted that

computers will become the primary work measurement tool in the 1980s,

and one technique to measure labor will be self-taken work sampling.

They included multidimensional work sampling as an illustration of

this type of technique.

Before the 1973 introduction of multidimensional work sampling in

the United States, more than 150 companies in Sweden, Great Britain,

Germany, and Switzerland made use of this system ("Are Executives

Efficient," 1973). Information on and utilization of this system can

be found in a book on time management (Bliss, 1976), dissertations

(Hannaway, 1978; Vorwerk, 1979), and various business journals ("Are

Executives Efficient," 1973; "Bonanza From Beeps," 1975; Rowen,

1978). Some of the applications of this system include studies of

public officials, scientists, university vice presidents, bank

executives, and health-related professionals (Robertsen, 1982).

At this time, hospital pharmacy literature includes only one

example of this technique. Hadsall et al. (1982) conducted a work

sampling project in order to demonstrate this new multidimensional

approach to work sampling. The researchers used six dimensions (which

included a total of 53 subcategories) to measure the activities of a

clinic pharmacy supervisor. A total of 908 observations were

collected over a 6-week period. Findings included that the supervisor

spent 27.3% of her time in administrative activities, 20.5% teaching,

and 7.6% dispensing. The authors concluded that multidimensional work

sampling was an effective and reliable technique which was especially

useful for measuring complex tasks, but they did not attempt to

validate the instrument, nor did they report how they established the

reliability of the procedure.

While the multidimensional work sampling technique is a new

method of work sampling, especially in pharmacy research, studies in

other fields have utilized other types of automated data collection

systems in observational research (Haynes & Wilson, 1979). Direct

computer access through punched cards or cassette tapes has made an

important contribution to behavioral observation research by

facilitating the collection and analysis of behavioral data. Systems,

such as the Senders Signals and Receivers System (SSR) developed by

Stephenson and Roberts (1977), have been used in observational

research in nursing (Gill, White, & Anderson, 1984; White, Wear, &

Stephenson, 1983). The SSR is a method of encoding data during the

observation onto an audiocasette tape for high speed transcription by

computer. Thus, while the multidimensional work sampling system

developed by Robertsen is the only automated data collection used in

pharmacy research, other types of systems have been utilized in

research reports in other disciplines.

Statistical Data

Statistical data consist of recording the number of work units

completed and comparing this to personnel time (Roberts et al.,

1982). Examples of completed work units in pharmacy research might

include the number of admixture prepared, the number of unit-doses

dispensed, or the number of outpatient prescriptions filled. By

itself, statistical data may be useful in providing only a rough

estimate of the amount of work performed (Roberts et al., 1982).

Many studies in pharmacy have used statistical data in

combination with other measures in order to adequately describe the

work itself (Hanna, 1983; Hatfield, Alessi, Brown, & Rehder, 1985;

Sebastian & Thielke, 1983). Most researchers would not, however,

consider a simple count of outputs (e.g., number of prescriptions

filled) as being an adequate description of pharmacists' activities or


Standard Time Data

The standard time for a given operation is the time required on

average for a fully trained operator to perform that activity when

working at a normal pace (Niebel, 1982). Roberts et al. (1982)

distinguishes between standard time data and predetermined motion time

systems (PMTS), but the distinction is not clear. In addition, Niebel

(1982) describes predetermined motion time systems as one method of

establishing time standards. Therefore, all of the pharmacy research

that relies on time standards which were established in previous

research will be examined in this section.

One of the first studies in pharmacy research to establish time

standards was Rothenbuhler and Archambault (1962). "Measurable" and

"nonmeasurable" activities performed in hospital pharmacies were

described and quantified in order to determine total staffing needs.

Refinements of this method are described by Bartsch, Estreller, and

Rothenbuhler (1965) and Hammel, King, and Jones (1977).

The American Hospital Association's Hospital Administrative

Services (HAS) attempted to develop a standard method of recording

units of work for all departments. Stolar and Tousignaut (1975)

modified this method to record pharmacy data through the use of

patient product units (PPUs) as a standard time measurement. Another

hospital-wide standard time measurement method is the Labor

Information System (LIS), which is used to monitor the use of

personnel. Hunt, Tuck, and Adams (1982) described the application of

this method for the purpose of monitoring pharmacy personnel.

Levin, Letcher, deLeon, and McCart (1980) developed a system of

time-weighted standards for distributive and clinical pharmacy

services, based on the measurement of patient-care units (PCUs). An

adaptation of this method was described and illustrated by Toohey,

Herrick, and Troutman (1982).

Strandberg, Smith, and Sanger (1982) attempted to formulate a

model to compare hospital pharmacy staffing patterns within groups of

similar hospitals. Regression analysis was used to identify nine

indicators that were statistically correlated with pharmacy personnel

expenditures. The authors conclude that validation of this

methodology using larger sample sizes is still needed. Similarly,

Roberts et al. (1982) contend that the applicability of standard time

data in hospital pharmacy may be limited because of the variability of

many factors within each pharmacy.

Summary Table

Many studies utilizing work measurement in pharmacy were reviewed

and, although some studies are similar, none are precisely alike.

Therefore, a table summarizing these studies is presented (Table 3),

which lists the studies chronologically and incorporates the pertinent

information from each one.

Job Satisfaction
One prominent theory relating to job satisfaction, developed by

Herzberg, is known as the Motivation-Hygiene Theory. Herzberg (1976)

identified separate factors that influence work satisfaction

(motivators) and work dissatisfaction (hygiene factors). Motivators,

also referred to in the pharmacy literature reviewed as intrinsic

factors, are concerned with the work itself and are the source of job

satisfaction. Hygiene factors, also referred to as extrinsic factors,

are associated with the work environment and are the source of job

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dissatisfaction. Herzberg contends that some of the motivators,

including the work itself, have long-term effects towards job

satisfaction and should be stressed when restructuring jobs. While

the research studies done in pharmacy have not tested the underlying

assumptions of Herzberg's theory, many researchers use terms such as

intrinsic factors or hygiene factors which are part of Herzberg's

theoretical framework.

Job Descriptive Index (JDI)

According to Smith (1974), job satisfaction is important to

measure because, under certain circumstances, lack of job satisfaction

and particularly job dissatisfaction may lead to behavior such as high

turnover and absenteeism. Smith also contends that measurement of job

satisfaction may be used as a criteria by which to measure the success

of job restructuring. In order to carry out these measurements, Smith

(1974) developed and validated an instrument known as the Job

Descriptive Index (JDI), which has been used in various work

environments including pharmacy settings (Carroll, Shultz, & Gagnon,

1982; Shoaf & Gagnon, 1980). This instrument measures five areas of

job satisfaction: the work itself, pay, opportunities for promotion,

supervisors, and coworkers. Two of these areas, the work itself and

opportunities for promotion, would be considered motivators or

intrinsic factors, while the other three would be considered hygiene

or extrinsic factors according to the Herzberg classification.

Pharmacy Literature on Job Satisfaction

Studies of pharmacists' job satisfaction have consistently found

one aspect of the work itself, the amount of time spent on clinical

skills (which utilize higher skill and education) to be related to job

satisfaction. One of these studies, by Johnson, Hamnel, and Heinen

(1977) surveyed hospital pharmacists in Michigan with a 68% response

rate. Findings include that staff pharmacists had the lowest level of

job satisfaction while clinical pharmacists had the highest level.

Similarly, Rauch (1981), when measuring satisfaction of pharmacists

who worked in army medical treatment facilities, found that

pharmacists providing patient care (a clinical activity) were

significantly more satisfied on intrinsic job measures than

pharmacists not providing patient care. Yet, they found no

significant difference on extrinsic job measures between the same


Another study (Noel, Hammel, & Bootman, 1982) looked at the job

satisfaction of both hospital pharmacists and support personnel.

Clinical and research pharmacists had the highest scores for job

satisfaction, and support personnel reported lower mean scores than

all groups of pharmacists. Additionally, a study of Michigan hospital

pharmacists (Quandt, McKercher, & Miller, 1982) found that when the

job content included clinical services, pharmacists were more

satisfied with their jobs, and suggested that any job enrichment

program should attempt to provide more clinical activities. Finally,

when institutional and community practitioners were compared (Curtiss,

Hammel, & Johnson, 1978), practitioners in apothecary-type settings

reported uniformly higher levels of satisfaction than pharmacists in

all other settings, and sources of job satisfaction were reported to

be work challenge and ability utilization.

Although each of the above studies looked only at a small segment

of institutional and community pharmacy personnel, all reached similar

conclusions concerning the relationship of clinical skills and job

satisfaction. A more recent study (Wilt, 1985) surveyed a sample of

all Florida pharmacists, community and hospital alike, to determine

their level of job and career satisfaction. Of all job aspects

measured, job role (a combination of job variety and job challenge),

correlated most highly with both job and career satisfaction.

Pharmacists with the opportunity to make use of their skills and

ability, and challenged by their work, tended to report a higher

degree of job and career satisfaction. Therefore, one suggestion to

improve job satisfaction was to alter the job to provide a greater use

of skills and abilities, and to provide a challenge in the work.


A review of various types of work measurement, including their

advantages and disadvantages, was presented. Many study designs were

previously used by pharmacy researchers, as outlined in the literature

review, but all have drawbacks. The most popular method of work

sampling is an observer-based study which consists of a researcher

trained to observe the pharmacy personnel at predetermined points in

time. But interaction between observer and the staff may provide a

potential for experimental bias (Segail & Kotzan, 1979), and this

method is costly because of the time spent by the observer (Robertsen,

1982). Cameras have also been used to observe pharmacy personnel, but

they have a limited range and can only collect very general

observations (Seigal & Kotzan, 1979). Neither of these methods allow

for observation of all tasks performed by pharmacists. Pharmacy

practice consists of many complex jobs that may not be accessible to

an observer since they may take place in a clinical setting, on the

telephone, or in a pharmacist's head.

An alternative system is the self-observation system based on

diaries, job cards, or questionnaires. But these consume an

inordinate amount of time from the employee and may be intentionally

or unintentionally biased (Robertsen, 1982). One last drawback to all

of the above methods pertains to the problem that while the tasks and

activities must be mutually exclusive and exhaustive, they should also

be few in number to optimize recording by the observer (Hadsall et

al., 1982).

After the types of work measurement were examined, the relevant

pharmacy literature utilizing work measurement was reviewed and its

major weaknesses were discussed. The major findings of this

literature were summarized in table form and used to guide decisions

on task categories and sampling framework for this study.

Finally, literature pertaining to the relationship between

clinical activities and job satisfaction was reviewed. This

literature seems to support the hypothesis that as pharmacists engage

in more clinical activities which utilize more complex skills, they

are more likely to have a higher level of job satisfaction.


This chapter will describe the research objectives, hypotheses,

and data collection procedures. The data analysis that was planned is

also outlined.

Research Objectives

The objectives of this research were to

1. Evaluate the impact of computerization of an outpatient

pharmacy on:

a. The percent of time spent on clerical functions.

b. The percent of time spent on clinical functions.

c. The amount of time it takes to fill a prescription.

d. The job satisfaction of the employees.

2. Compare the multidimensional work sampling technique with a

direct observation technique to determine the level of

agreement and the areas in which they give comparable results.

Research Hypotheses
It was hypothesized that:

1. After the computer was installed and operational:

a. The percent of time spent on clerical activities would


b. The percent of time spent on clinical activities would


c. The amount of time it takes to fill a prescription would


d. Job satisfaction of the employees would increase.

2. Multidimensional work sampling would be in substantial

agreement with the direct observation technique on clerical or

dispensing tasks, but would not agree on clinical activities

or decision making categories.

Variables and Their Measurement

The theoretical model outlined previously evaluates the impact of

job redesign on intended results for both business and the quality of

work life. Job redesign, or the installation of the computer, was the

independent variable. This was simply measured by whether the

computer was or was not in use at the time of data collection.

The dependent variables include LEVEL II--the mediating

variable--and LEVEL III--intended results for business and quality of

work life. The mediating variable in this study was the change in the

levels of skills used. This was measured by evaluating the change in

the percent of time spent on clinical and clerical activities. This

was, in turn, measured through the use of a multidimensional work

sampling technique outlined in the next section. This technique was

also compared with a direct observation work sampling technique.

The second dependent variable evaluated was the intended result

for the business, or the change in the amount of time it takes to

process a prescription. These data were collected through a time

clock technique. The final dependent variable analyzed was the

intended result for the quality of work life, or the change in job

satisfaction of the employees. This was measured through a job

satisfaction questionnaire. In summary, the variables and their

measurements are outlined as follows:

Independent variable


Dependent variable

Percent of time spent
on clinical activities

Percent of time spent
on clerical activities

Time to process a

Job satisfaction


Whether computer is installed at time
of data collection


Multidimensional work sampling and
direct observation

Multidimensional work sampling and
direct observation

Direct observation



The setting of this study is the outpatient pharmacy at Shands, a

large 475-bed teaching hospital. The outpatient pharmacy is open

Monday through Friday from 9 AM to 5:30 PM and is located on the first

floor near the outpatient clinic area. Five employees fill

approximately 260 prescriptions daily (outpatient clinic, discharge,

and employee prescriptions).

The five employees participating in the study included two full-

time pharmacists, one full-time pharmacy intern student, and one full-

time and one part-time technician. One pharmacist and one technician

from the precomputerization phase of the study were replaced by

another pharmacist and technician by the time the postcomputerization

phase of the study began.

Measuring Instruments

This section will describe the measurement techniques used. In

addition, the procedures used to obtain the data with each instrument

will be described.

Multidimensional Work Sampling

The first type of measurement used is multidimensional work

sampling, chosen because it allowed the measurement of unobservable

tasks, was not overly time consuming for employees, and was used

successfully in research in a similar pharmacy setting.

Dimensions. The multidimensional work sampling method measures

at least three components or dimensions of job-related behavior.

These are activity, function, and contact. "Activity" is the means by

which something is performed or accomplished. For example, an

activity could be a meeting, phoning, filling, or evaluating. The

"function" describes the purpose of the activity. This may include

dispensing medication, consultation/advice, or billing. "Contact"

describes the person or group for whom the activity is being

performed. This could include physician, patient, or nurse. If the

employee is not in direct contact with someone when the task is

measured, the contact of "self" is recorded. One example of coding

would be "meeting 1:1; consultation/advice; patient" for the task of

patient counseling. Hadsall et al. (1982) formulated lists of these

dimensions in their study of a clinic pharmacy (see Appendix A).

These dimensions were adjusted to accommodate the outpatient pharmacy

at Shands Hospital and the purpose of this study. These revised

dimensions were reviewed by nine expert judges familiar with the

outpatient operation in order to establish the content validity of

these dimensions. Dimensions for this study are outlined in Table 4,

and their definitions are included in Appendix B.

Clarification of the definitions of some of the functions may be

needed. Function 1, "collect/record/give patient information" refers

only to "nonprofessional" information that any employee could give or

receive and includes information such as the number of refills left,

spelling of the patient's name, or how much the prescription will

cost. Function 1 does not include the tasks identified by Function 8,

"consultation/advice," Function 9 "detect/correct duplication

problems," or Function 10 "detect/correct other prescription problems"

which are more professional tasks and usually done by the pharmacists

or, in some cases, the pharmacy intern student.

The hypotheses of this study were that after computerization

there would be an increase in professional functions and a decrease in

clerical functions. The professional functions expected to increase


Function 8--consultation/advice

Function 9--detect/correct duplication problems

Function 10--detect/correct other prescription problems

Conversely, the clerical functions expected to decrease were:

Function 2--prepare label

Function 3--price prescription

Function 5--bill prescription

Function 11--order stock

The clerical function of collecting and recording patient information

(Function 1) was expected to increase somewhat, but this increase

would be offset by a decrease in the other clerical functions listed


Training. The employees were given a list of the dimensions

identified in Table 4, along with a definition of each dimension

(Appendix B). They were asked to review the material for a meeting

which was held 1 week before data collection. At that meeting, the

definitions were explained in detail and examples of their use were

given. The employees were then given 2 days to review and ask any

questions concerning the dimensions. At the end of the 2-day period,

the employees were given a test consisting of 25 examples of tasks

which might occur in the outpatient pharmacy (Appendix C), and each

employee was asked to independently indicate the three dimensions they

would record for these tasks. The answers given were assessed for

interrater reliability by correlating each person's response to a

"norm" established by expert judges. If interrater reliability,

assessed by dividing the number of agreements by the number of

agreements and disagreements (Haynes, 1978), was less than .90,

retraining for that employee took place until the criterion was met.

Equipment. Consoles approximately the size of a desk top adding

machine were provided by the Extensor Corporation. The front of each

Table 4
Dimensions Used in Multidimensional Work Sampling


1. meeting 1:1
2. meeting 3+
3. phone
4. type
5. computer entry
6. review/check
7. sort/file
8. write/sign
9. prepare
10. transit/waiting
11. absent
12. other


patient/patient representative
other pharmacy personnel
outside pharmacist



collect/record/give patient information
prepare label
price prescription
prepare prescription
bill prescription
dispense prescription
collect payment
detect/correct prescription duplication problems
detect/correct other prescription problems
order/pick up/put up stock

console contains a plastic guide under which a computer card is

placed. Above this computer card is a plastic window where the code

list of dimensions is placed for easy reference. Approximately four

times an hour, at random intervals, a "beep" is emitted from the

console and a light corresponding to a column on the computer card is

activated. The employee is instructed to remove the stylus from its

holder (located in upper-right portion of console), and use it to

punch three holes in the appropriate column of the computer card

corresponding to the task being performed at the time of the "beep."

The employee then replaces the stylus in its holder which extinguishes

the light above that column.

When a computer card is filled, it is placed in a slot at the

back of the machine, and a new card is inserted under the plastic

guide. At the end of each week, the completed computer cards were

collected by the researcher, and sent to the Extensor Corporation for


Recording of data. Three days before data were collected,

employees were trained to use the consoles provided for recording

their tasks. Each employee was given a manual explaining the

procedure of the Extensor system, which was reviewed and discussed at

that time. On the first day of the study, each employee was given a

small console on which to record his tasks. The console was placed

near the employee's work station, and a list of the dimensions was

placed in a window on each console.

The dimensions listed in Table 4 were recorded on a console as


1. A random "beep" was emitted approximately four times per hour

for each person in the pharmacy, at which time a corresponding

light was activated on the employee's console.

2. At this time the employee chose one, and only one, item from

each dimension which described his or her activity by punching

the appropriate three areas on the computer card in the

recording machine with the stylus.

3. When an employee left the pharmacy area, he was instructed to

check the console upon returning to determine if any lights

had been activated while he was gone. If they had, the task

accomplished while the employee was absent was to be recorded

on the console.

4. Eight tasks (of three dimensions each) could be recorded per

computer card with one column for corrections. When a card

was filled, the employee was instructed to remove the card,

store it in the back of the console, and replace it with

another computer card.

5. The cards from the recording machine were collected at the end

of each week. Since approximately 900 observations per person

would permit reliable estimates (Barnes, 1968), data were

collected for six weeks (4 obs/hr X 8 hr X 5 days/wk X 6 weeks

= 960 observations).

After a GCC (General Computer Corporation) computer was installed

and operational, eight weeks were allowed for the pharmacy personnel

to become accustomed to the computer and "work the bugs out." Eight

weeks was chosen because it was felt that this was an adequate amount

of time for the employees to become accustomed to the computer, while

minimizing the time during which unrelated changes might occur in the

pharmacy operation. After the computer was installed and the second

phase of data collection was set to begin, the two new employees were

trained and the other employees were retrained in order to repeat the

6-week data collection procedure.

Direct Observation

The multidimensional approach was compared with a direct

observation approach to work sampling. A sample of approximately 15%

of the observations recorded in each 6-week period was also recorded

by direct observation to determine the accuracy of the self-reporting

technique. Observations were recorded by the principal investigator,

who had previously been the outpatient supervisor and developed the

definitions of the dimensions for this study. The observer sat in a

corner of the pharmacy which afforded a good view of the operation but

was out of the traffic pattern of the employees. Interaction was kept

at a minimum, but questions concerning the study arose occasionally

and were answered at this time.

The observer used the same dimensions listed in Table 4, with the

added option of recording a "13" if the function being performed could

not be determined. The comparison of the two methods of work sampling

using the same dimensions allowed an evaluation of the types of work

that can be measured equally well by both methods and the type which

yields different results.

Time Clock

Information regarding the amount of time it takes to process a

prescription was recorded by a time clock technique. The work flow of

the pharmacy before and the flow expected after computerization was

outlined (see Appendix 0), and it was decided that four points in time

would be recorded by three time clocks. The placement of these time

clocks is illustrated in a diagram of the outpatient pharmacy

(Appendix E). Over a 1-week period, these four points in time were

recorded for each set of prescriptions presented for a patient. These

points consisted of the times when (a) the set was received into the

pharmacy, (b) label generation was completed, (c) the filling process

was begun, and (d) the set of prescriptions was completed. These

recordings were used to calculate the following four time spans:

Process--The time to process the prescriptions for filling.

Before the computer this included logging the

prescriptions and typing the label, while after the

computer this referred to the time to input the

prescription information and print the label.

Delay-- The time from when the prescription was ready to be

filled and the time filling began.

Fill-- The time to prepare or fill the prescription orders.

Total-- The total time between the receipt and completion of the


Job Satisfaction

The job satisfaction questionnaire consisted of the Job

Descriptive Index (JDI) (see Appendix F), along with items previously

used and validated in research with pharmacists by Wilt in 1985

(Appendix G). The JDI measures five aspects of job satisfaction: the

work itself, supervision, other employees, pay, and opportunity for

promotion. It has been used in various settings and is thought to

demonstrate adequate reliability and validity (Smith, 1974).

The questionnaire used in pharmacy research (Wilt, 1985) utilizes

a 5-point Likert-type scale and includes items that measure overall

job satisfaction along with items to specifically measure the

pharmacist's satisfaction with their job tasks. Reliability and

validity of this instrument was assessed and documented by Wilt


Data Analysis

Multidimensional Work Sampling

The data generated from the multidimensional work sampling

portion of the study was directly recorded onto computer cards by the

employees through the use of a recording console. These data cards

were sent to the Extensor Corporation where this information was

processed and sent back in the form of summary and two-dimensional

frequency tables.

Data collected before and after computerization was compared

using an analysis of variance (ANOVA) procedure. This procedure was

used to determine if there was a significant difference between the

two time periods (precomputerization and postcomputerization) on the

types of functions performed. This procedure also allowed us to

assess if there was a significant difference in functions of the five

employees, or if there was a significant change in functions on a week

to week basis.

Similar studies (Kohout et al., 1983; Sikora & Kotzan, 1981) used

a chi-square test to compare data before and after computerization,

but this test is overly sensitive to changes when a large number of

observations are included in the analysis. However, a chi-square test

was also performed in order to compare these results with the analysis

of variance results as a basis of assessing the probable accuracy of

previous research findings.

Multidimensional work sampling recordings were compared with a

sample of direct observations recordings to determine the level of

agreement of the two sets of observations. The following equation was

used (Haynes, 1978):

The number of agreements
Interrater reliability = The number of agreements + disagreements

The interrater reliability was computed for all direct

observations, as well as separately for the clinical and clerical

functions identified previously. The internal consistency reliability

of the multidimensional work sampling data was assessed using the

split-half method corrected with the Spearman-Brown prophecy

formula. While this method is most commonly used in item analysis of

paper and pencil tests, it is also recommended as a way of determining

the internal consistency of observational instruments (Haynes, 1978).

Time Clock

The time it took to process a prescription was measured using a

time clock technique. Data on the time to process a prescription were

collected on each prescription that was filled in the pharmacy for one

week in both the precomputerization and postcomputerization phase of

the study. The complete information from the times recorded was used

to calculate the mean (x) and standard deviation (sd) of these

observations (n). The amount of time it took to process a

prescription before and after computerization was compared using a

two-sample t-test.

Job Satisfaction

The information collected on the job satisfaction questionnaire

was ordinal; therefore, a Wilcoxon matched pairs signed ranks test was

used to compare the scores of the employees before and after



Various types of work measurement have been used in pharmacy

research, and each has limitations. The major limitation of self-

reporting work measurement is that it may be intentionally or

unintentionally biased by the employee, whereas direct observation

methods may be biased because of the interaction that takes place

between the observer and the staff. The major limitations of the

methods used in this study are:

1. Self-reporting data may be biased, although a comparison with

direct observations will help determine to what extent this

takes place in the multidimensional approach.

2. Interaction between the observer and the staff may be a source

of bias when using a direct observation approach.

3. Results are based on the assumption that no other major

changes take place during the 8-week time lapse between

precomputer and postcomputer recording periods.

4. Because every pharmacy setting will differ somewhat, findings

cannot be generalized to other settings.

5. There are a limited number of personnel taking the job

satisfaction questionnaire so the Wilcoxon matched pairs

signed rank test may not show a difference even if one exists.

6. There was a danger of employee turnover both during data

collection periods as well as during the 2-month time lapse

between recording periods.


The findings of this study will be presented under four

sections. The first section will present the results of the

multidimensional work sampling technique which was used to measure and

compare the amount of time spent on various tasks both before and

after computerization. In the second section, the results of direct

observation work sampling are discussed. The direct observation

method was used to assess the accuracy of the multidimensional

approach and to determine in what areas these two methods gave

comparable results. The third section describes the results of a time

clock procedure used to compare the time it takes to fill

prescriptions before and after computerization. The fourth section

presents and compares the job satisfaction levels of the employees

before and after computerization.

Multidimensional Work Sampling

A multidimensional work sampling approach was used to measure the

amount of time spent on various tasks before and after

computerization. The three dimensions recorded using this technique

were "activity"--or the means by which something is performed,

"contact"--or the person for whom the activity is performed, and

"function"--which describes the purpose of the activity.


The first set of data was collected over a 6-week period in May

and June of 1985. A total of 3,096 observations were recorded by the

five employees, and these results are presented in Tables 5 through

8. Table 5 is a summary of the percent of time spent on each

activity, contact, and function. The most frequent activity was

preparation, such as prescription preparation (36.6%), followed by

typing (15.4%), writing (12.6%), and meeting with someone on a 1:1

basis (11.2%). The most frequent contact was with oneself (83.6%),

followed by the patient or his representative (8.4%), other pharmacy

personnel (3.8%), and the physician (1.1%). The most frequent

function was preparing the prescription (37.1%), followed by

collecting, recording, or giving patient information (17.3%),

preparing the label (15.7%), and stocking (3.9%).

Tables 6 through 8 are two dimensional frequency tables of the

information presented in Table 5. Table 6 presents what activity was

performed with each contact. For example, of the 8.4% of the time

spent with the patient, 7.2% was in a 1:1 meeting, while the other

1.2% was spent on the phone with the patient. Table 7 presents what

function was performed by the various activities. For example, of the

17.3% of the time spent collecting, recording, and giving patient

information, most was done on a 1:1 basis (5.6%), followed by writing

down the information (4.4%), and transferring it over the phone

(2.8%). Table 8 presents what function was performed by or for each

contact. For example, of the 17.3% of the time spent collecting,

recording, or giving information, most was done by oneself (9.8%),

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followed by with the patient (5.6%), other pharmacy personnel (.8%),

and the physician (.7%).


Computer installation and training in its use took place during

the first week of July. The second phase of data collection began 2

months later, as the supervisor felt the employees were proficient in

their use of the computer by this time. A total of 3,611 observations

were recorded during the second phase of data collection (September-

October, 1985), and the results are presented in Tables 9 through 12.

Table 9 is a summary of the time spent on each activity, contact,

and function during the postcomputerization phase of the study. The

most frequent activity during this phase was computer entry (32.8%),

followed by preparation (34.3%), meeting on a 1:1 basis (9.9%), and

absent (6.2%). The most frequent contact again was with oneself

(86.6%), followed by the patient or his representative (7.7%), other

pharmacy personnel (3.4%) and the physician (.9%). The most frequent

function was now collecting, recording, or giving patient information

(45.0%), followed by preparing the prescription (39.2%), and stocking


Tables 10 through 12 are two dimension frequency charts of the

information presented in Table 9. For example, Table 10 shows that

during this phase of the study, of the 7.7% of the time spent in

contact with the patient or his representative, 6.2% was on a 1:1

basis, while the other 1.5% was spent on the phone. Another example

from these tables shows that of the 45.0% of time spent collecting,

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recording, or giving patient information, most of this time (32.5%)

was spent on the activity of computer entry (see Table 11), while the

most frequent contact corresponding with this function was again

oneself (36.7%), followed by the patient (5.6%), other pharmacy

personnel (1.6%) and the physician (.4%) as shown in Table 12.


A comparison of "function" recordings from the two data

collection phases is presented in Table 13. The percent of time spent

on clerical Functions 2, 3, 5, and 11 decreased as hypothesized. The

total decrease of these four functions added to 26.7%, but was offset

by an 27.7% increase in time spent on the clerical Function 1,

collecting/recording/giving patient information, which was mainly due

to the time it took to enter patient data into the computer. The

percent of time spent on clinical Functions 8, 9, and 10 was small and

only Function 10, detect/correct other problems, increased from 1 to

2% after computer installation, while the other clinical functions

showed no change. A chi-square test would indicate a significant

difference in overall functions, as well as clerical and clinical

functions (j<.0001,_. .0001, and _<.005, respectively), although the

small change in clinical activities might not be considered of much

practical importance. In fact, the analysis of variance results

reported below find this difference to not be significant.

When an analysis of variance is performed on the same data, the

results do differ somewhat. Table 14 presents the results from the

analysis of variance for clerical functions. As before, the time

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Table 13
Comparison of Function Results for All Employees

% Beforea % Afterb Change
Function (n=3,096) (n=3,611)

1. Collect/record/give patient

2. Prepare label

3. Price prescription

4. Prepare prescription

5. Bill prescription

6. Dispense prescription

7. Collect payment

8. Consultation/advice

9. Detect/correct duplication

10. Detect/correct other problem

11. Order/pick up/put up stock

12. Other








** 1.1

** 0.1

** 1.0

* 3.9


45.0 +27.7

0.2 -15.5


39.2 +2.1

0.6 -7.3

0.4 -0.6

0.6 -0.5

1.1 0

Clerical functions expected to decrease.
Clinical functions expected to increase.
Before = 6 weeks observation in May-June 1985. Average Rx/day =
After = 6 weeks observation in September-October 1985. Average
Rx/day = 263.

Table 14
Analysis of Variance for Clerical Functions

Source df SS F e less than

Data Phase (A) 1 9.67 206.58 .0001

Employee (B) 4 4.43 23.64 .0001

Week (C) 5 0.07 0.29 .9149

A X B 4 4.08 21.80 .0001

B X C 20 0.61 0.65 .8280

A X C 5 0.11 0.48 .7860

Error 19 0.89

spent on clerical functions was significantly different between the

first and second phase of data collection (precomputerization and

postcomputerization), as shown by a value of p<.0001. This analysis

also suggests that there was a significant difference between

employees in the percentage of time spent on clerical functions

(p<.0001), but that there was no significant difference in the

percentage of time spent on these functions from week to week


A significant interaction between the data phase and the employee

was also indicated in Table 14 (p.O00O1). This means that some of the

employees differed more in their change of clerical functions between

the first and second data phase than others. The most probable

reasons for this interaction involves the large change in the time

spent by one employee typing prescription labels. Before

computerization, one employee was generally assigned to type the

prescription labels (Function 2) and spent over 60% of the time

performing this task. After the computer was installed, this employee

no longer typed any labels, but now spent over 50% of the time

collecting and recording information into the computer (Function 1).

Other employees also reported a decrease of time spent preparing the

label, but none recorded a change of this magnitude.

A comparison of the time spent on Function 1, collecting/

recording/giving patient information is presented in Table 15. This

function was defined as excluding any professional information

exchange and as such is a clerical function, but this function was

expected to increase after computerization. As with the other

Table 15
Analysis of Variance for Function 1

Source df SS F p less than

Data Phase (A) 1 6.37 63.00 .0001

Employee (B) 4 0.82 2.02 .1327

Week (C) 5 0.14 0.29 .9139

A X B 4 2.64 6.52 .0018

B X C 20 0.92 0.46 .9549

A X C 5 0.13 0.26 .9289

Error 19 1.92

clerical functions, there was a significant difference between the

first and second phase of data collection (precomputerization and

postcomputerization), with y<.0001, but this time the clerical

function increased significantly in the postcomputerization phase. An

interaction between the phase of data collection and the employee was

found. This, again, is probably due to the fact that one employee

spent a large proportion of time typing during the precomputerization

period, and changed to entering information into the computer

(Function 1) after computerization. The change in functions for this

employee was more drastic than for other employees and seems to be the

crucial factor in the employee-data phase interaction.

Table 16 presents the results of the analysis of variance for

clinical functions. Unlike the chi-square test results, this type of

analysis indicates that there was no significant difference in the

time spent on clinical functions between the first and second phase of

data collection (p<.8012). As with the clerical functions, this

analysis also found a significant difference between employees in the

percentage of time spent on clinical activities (p<.0044) and found no

significant differences from week to week (2<.6672).

Internal Consistency

The internal consistency of the multidimensional data was tested

by comparing functions recorded during the odd weeks (weeks 1, 3,

etc.) of data collection with those from even weeks (weeks 2, 4,

etc.). The percent of time spent on each function during odd and even

weeks was corrected using an arcsine transformation technique, which

Table 16
Analysis of Variance for Clinical Functions

Source df SS F p less than

Data Phase (A) 1 0.01 0.07 .8012

Employee (B) 4 0.77 5.41 .0044

Week (C) 5 0.11 0.65 .6672

A X B 4 0.21 1.46 .2537

B X C 20 0.89 1.25 .3177

A X C 5 0.12 0.67 .6521

Error 19 0.68

will allow percentage data to be analyzed with parametric tests.

These transformed percentages were then analyzed for internal

consistency using a split-half method corrected with the Spearman-

Brown prophecy formula. The corrected correlation for each function

appears in Table 17. The reliability estimates of Functions 7,

collect payment, and 8, consultation/advice, are relatively low (.22

and .58, respectively) probably due to the small number of

observations in these categories (see Tables 5 and 9). Reliabilities

for the other functions are relatively high (.77 to .98), which

suggests that the measuring instrument used is internally consistent.

Direct Observation

The multidimensional approach was compared with a sample of

direct observations to determine the extent to which the two

techniques are in agreement and in what areas they give comparable

results. A total of 428 observations were recorded by the observer

during the 6-week precomputerization phase of data collection (see

Table 18). Of these, 93 (22%) of the function observations did not

agree with the multidimensional recordings, which corresponds to an

overall interrater reliability of .78. The major contributor to these

disagreements was the large number (75) of direct observations

classified as "13" or "could not determine." This classification was

used if either the employee was not within view, or if the observer

could not classify the function based on visual observation alone. An

example of the latter would include viewing an employee on the phone

but not being able to discern whether the employee was giving "patient

Table 17
Internal Consistency Reliability Estimates for Each Function

Functions Internal Consistency

1. Collect/record/give patient information .89

2. Prepare label .98

3. Price prescription .84

4. Prepare prescription .83

5. Bill prescription .96

6. Dispense prescription .97

7. Collect payment .22

8. Consultation/advice .58

9. Detect/correct duplication problem .88

10. Detect/correct other problem .77

11. Order/pick up/put up stock .92

Table 18
Comparison of Multidimensional Function Recordings with
Direct Observation Function Recordings--Precomputerization

First Run--May--June 1985

Total number of direct observations 428

Number of disagreements because observer
could not determine function 75 (18%)

Number of other disagreements 18 (4%)

Total disagreements 93 (22%)

Interrater reliability overall .78

Interrater reliability of clinical functions .29

Interrater reliability of clerical functions
including Function 11 .81

Interrater reliability of clerical functions
excluding Function 11 .85

information" or "consultation/advice." The disagreements which did

not involve the "13" code comprised only 4% of the total and no

pattern to these disagreements could be determined.

It was hypothesized that the two work sampling techniques would

be in substantial agreement on clerical tasks, but not clinical

tasks. In addressing these hypotheses, the work samples where both

techniques were used were analyzed. Using the multidimensional

technique, employees recorded a clinical function (8, 9, or 10) taking

place 14 times during the precomputerization period while the observer

recorded this as occurring only four of these times, which corresponds

to an interrater reliability on clinical functions of .29. In

addition, employees recorded a clerical function (2, 3, 5, or 11)

taking place 100 times during the precomputerization period, while the

observer's recordings agreed with these functions 81 times, for an

interrater reliability on clerical functions of .81. The clerical

function of picking up stock (11) should perhaps be deleted from this

analysis because although it is a clerical function and as such

hypothesized to be visually discernable, in fact the employees were

out of view when they were picking up stock from the storeroom. If

this category is deleted the interrater reliability for clerical

functions increases to .85.

A total of 480 direct observations were recorded during the 6-

week postcomputerization phase of data collection, of which 63 (13%)

function recordings did not agree with the multidimensional recordings

(see Table 19). This corresponds to an overall interrater reliability

of .87. Again, the major portion of these disagreements (41) were as

Table 19
Comparison of Multidimensional Function Recordings with
Direct Observation Function Recordings--Postcomputerization

Second Run--September--October 1985

Total number of direct observations 480

Number of disagreements because observer
could not determine function 41 (8.5%)

Number of other disagreements 22 (4.5%)

Total disagreements 63 (13%)

Interrater reliability overall .87

Interrater reliability of clinical functions .47

Interrater reliability of clerical functions
including Function 11 .56

Interrater reliability of clerical functions
excluding Function 11 .83

a result of the "could not determine" classification used by the

observer, although the frequency of this classification was lower than

during the first collection period. The other disagreements again

comprised about 4% of the total and no pattern was found.

Using the multidimensional technique the employees recorded a

clinical function (8, 9, or 10) occurring 30 times during the

postcomputerization period, whereas the observer agreed with these

recordings 14 times for an interrater reliability on clinical function

of .47. Employees recorded a clerical function (2, 3, 5, or 11) as

occurring 18 times during this period, while the observer agreed with

10 of these recordings for an interrater reliability on clerical

functions of .56. If the function of picking up stock was again

deleted from analysis, the interrater reliability of clerical

functions increased to .83.

Time Clock

A time clock technique was used to compare the time it took to

complete a prescription before and after computerization. These data

were analyzed both for sets of prescriptions as well as per

prescription. A set of prescriptions was defined as those

prescriptions brought in at one time for one patient, and ranged from

1 to 11 independent prescriptions. The data were also analyzed

separately for new and refill prescriptions. For ease of analysis, if

a person had both new and refill prescriptions, the times were not

included in the analysis. This occurred only once in each phase of

data collection.

The first phase of data collection extended over a 1-week period

in May 1985, and consisted of time recordings of 315 new and 97 refill

prescriptions (see Table 20). The average total time to complete a

set of new prescriptions was 28.8 minutes or 20.3 minutes for each new

prescription. The average total time to complete a set of refill

prescriptions was 31.7 minutes, or 23.8 minutes for each refill

prescription. Approximately one-half of this total time was comprised

of the "delay" time span, or the time between label generation and the

beginning of the filling process.

The second set of data was collected over a 1-week period in

October 1985, almost four months after computer installation, and

consisted of time recordings from 234 new and 97 refill prescriptions

(see Table 21). The average total time to complete a set of new

prescriptions was 39.5 minutes, or 28.3 minutes for each new

prescription. The average total time to complete a set of refill

prescriptions was 43.3 minutes, or 30.3 minutes for each refill

prescription. For this set of data, well over one-half of this total

time was due to the "process" time span, or the time between receipt

of the prescription and label generation, which included the time it

took to enter patient data into the computer.

Therefore, the time to complete both new and refill prescriptions

increased after computer installation. The major reason for this

increase was the substantial time it took to enter patient information

into the computer. However, it is important to note that before the

computer was installed, the outpatient pharmacy did not keep patient

profiles, which were provided after computerization. Therefore, if it

Table 20
Comparison of New Prescription Preparation Times


Per Set of New Prescriptions

Process x 9.7 min.
sd (8.4)

Delay x 12.2 min.
sd (10.7)

Fill 7 6.9 min.
sd (7.3)

Total 7 28.8 min.
sd (15.8)

Per New Prescriptions

Process x

Delayl 7


Total 1

6.8 min.

9.2 min.

4.3 min.

20.3 min.

After Change p less than

23.1 min

7.6 min.

8.8 min.

39.5 min.

16.6 min.

5.9 min.

5.8 min.

28.3 min.

+13.4 min.

-4.6 min.

+1.9 min.

+10.7 min.

+9.8 min.

-3.3 min.

+1.5 min.

+8.0 min.








Table 21
Comparison of Refill Prescription Preparation Times


Per Set of Refill Prescriptions

Process 7 9.7 min.
sd (7.4)

Delay 7 14.6 min.
sd (12.4)

Fill 7 7.4 min.
sd (7.8)

Total 7 31.7 min.
sd (19.5)

Per Refill Prescriptions

Process 7 7.3 min.
sd (6.5)

Delayl 7 11.5 min.
sd (11.8)

Filll x 5.0 min.
sd (5.3)

Totall 7 23.8 min.
sd (17.7)

After Change p less than

23.9 min.

10.0 min.

9.4 min.

+14.2 min.

-4.6 min.

+2.0 min.




43.3 min. +11.6min. .0014

16.4 min. +9.1 min. .0001

6.9 min. -4.6 min. .0014

7.0 min. +2.0 min. .0292

30.3 min. +6.5 min. .0293

had been feasible (which it was not), a fairer comparison would have

been to ask the employees to keep manual patient profiles during the

first phase of the study. With time, as more patients become repeat

users, the time it takes to enter patient profile information should

decrease. The time to actually fill the prescription increased

slightly, but the supervisor felt that this was due to the fact that

the employees filling the prescriptions were not as consistently

rushed as before computerization, primarily because they would often

have to wait for the next set of labels to be generated by the


Job Satisfaction
Job satisfaction of the employees was measured before and after

computerization of the pharmacy. Each of the five employees were

asked to complete the Job Descriptive Index or JDI (Appendix F), and

the pharmacists were also asked to complete the Pharmacists Survey

(Appendix G).

The JDI measured five areas of job satisfaction: the work

itself, supervision, other employees, pay, and promotion. The results

(Table 22) from both phases of data collection indicate that the

employees were very satisfied with their supervision and other

employees, somewhat satisfied with the work, and dissatisfied with

opportunities for promotion. In addition pharmacists were more

satisfied with their pay than the technicians.

Again the results were similar for both sets of data. A Wilcoxon

matched pairs signed ranks test was used to determine if there was a

Table 22
Job Satisfaction--JOI Scores

Area Score Tech 1 Tech 2 Tech 3 RPh 1 RPh 2

Before Computerization

54 41
54 42
54 52
27 3
27 9

31 28 29
50 46 54
49 44 49
17 15 25
10 13 5


After Computerization



216 147 151 157 146 162

54 36 33 43 24 27
54 48 51 46 52 50
54 50 54 54 50 51
27 4 3 15 16 18
27 6 5 10 0 4

216 144 146 168 142 150


difference between the total JDI scores, or between the scores for the

work itself. No significant difference was found for either set of

scores (p<.4 and p<.6, respectively).

The Pharmacists Survey, which measures job satisfaction using a 1

to 5-point Likert type scale, indicated that the pharmacists were not

far from neutral either before or after computerization, with scores

of 2.8 and 3.2 during the first phase and 3.1 and 3.2 during the

second phase of data collection.

Although a significant difference might not be found even if one

exists because of the small number of subjects tested, the results

were strikingly similar in all categories tested. It did not appear

that there were major changes in the level of job satisfaction of the

employees tested.


One of the objectives of this study was to analyze the impact of

installing a computer in a large outpatient pharmacy. Advocates of

computerization claim that a computer will decrease the time spent on

clerical tasks, which will allow pharmacists more time to pursue

clinical activities. The literature reviewed presented mixed results

with respect to the time saved by computerization. While some studies

found an overall time savings for processing prescriptions (Kohout et

al., 1983; Moss & Pounders, 1985; Unertl et al., 1984), the findings

by Sikora and Kotzan (1981) suggest an overall increase in the time to

process a prescription. None of the work sampling literature reviewed

found an increase in professional activities, and one study (Kohout et

al., 1983) actually found a decrease in the time spent counseling


Because the work sampling techniques used in the cited literature

were not ideal for measuring clinical activities, a newer technique,

multidimensional work sampling, was used to more accurately record and

compare these types of activities. This new technique was also

compared with direct observation work sampling in order to assess its

accuracy in recording various tasks. A time clock method was used to

measure and compare the time it took to process a prescription and a

survey was used to compare the employees' job satisfaction before and

after computerization.

Results from the multidimensional work sampling data indicated

that the percent of time spent on some clerical activities decreased

after computerization, but that this was offset by an increase in the

clerical activity of collecting and recording patient information.

The percent of time spent on the clinical functions of counseling and

detecting duplications did not change. The percent of time spent on

the clinical function of detecting other prescription problems

increased from 1 to 2%, which is not a significant difference. It

should be noted here that even if a decrease in overall clerical

functions had occurred, thus providing an opportunity for more

clinical functions to be performed, it does not ensure that the

pharmacists would use the extra time for clinical functions. Training

and encouragement may be needed to promote this type of behavior


The multidimensional method of work sampling appeared to be a

reliable form of work measurement, as suggested by the relatively high

internal consistency reliabilities of most of the functions. The

analysis of variance found no significant difference from week to week

within the groups of functions analyzed, which further suggests that

the method is reliable.

Comparison of the multidimensional technique with the direct

observation technique indicated that overall disagreements, excluding

those caused by the direct observer recording "could not determine,"

equaled approximately 4% of the total observations. The large percent

of disagreements caused because the observer could not determine the

function (18% precomputerization and 8.5% postcomputerization),

suggests that the multidimensional approach may present a more

complete measure of the tasks performed. As hypothesized, the two

techniques were more highly associated on clerical functions, with

interrater reliabilities of .81 and .56, than clinical functions, with

interrater reliabilities of .29 and .47. This difference is even more

striking when the clerical function of picking up stock, which takes

place outside the pharmacy, is deleted from the analysis, since the

interrater reliabilities of the clerical functions then increased to

.85 and .83, respectively. The difference in interrater reliabilities

between clinical and clerical functions is probably due to the fact

that clinical functions are difficult to measure using direct

observation and that the multidimensional approach may be more useful

in capturing these types of activities.

Another finding of this study was that it took more time to fill

prescriptions (both new and refill) after the computer was installed

and operational. The major reason for this increase was due to the

additional time needed to enter information into the computer, as was

also suggested by the increase in the percent of time spent on the

function of collecting and recording patient information. However,

this comparison was not completely fair since the outpatient pharmacy

did not keep patient profiles before computerization. Additionally

the time spent entering information is expected to decrease with time,

as more patients who are repeat users are already included in the

computer profiling systems. Nevertheless, a definite bottleneck at

the computer entry step of prescription preparation was identified by

the data in the postcomputerization phase.

Reasons for this bottleneck included (a) the GCC computer, which

is a powerful system but, as installed, was a relatively slow system

for inputing patient information and (b) the employees responsible for

entering information into the computer were frequently interrupted by

patients waiting to drop off or pick up prescriptions. After the

results were presented to the director of pharmacy, plans were made to

inquire about upgrading the system in order to speed up input time.

Another change that took place as a result of this study was a

redefinition of work tasks. In order to alleviate the computer entry

bottleneck, the tasks of receiving and dispensing prescriptions were

delegated to other employees so that those responsible for entering

patient information into the computer would not be interrupted.

The last section of this study compared the job satisfaction of

the employees before and after computerization. The results from the

two phases of the study were strikingly similar in all categories of

job satisfaction tested. Therefore, it did not appear that there were

major changes in the level of job satisfaction of the employees

tested. Pharmacists' responsibilities before and after

computerization stayed basically the same. On an alternating basis

the pharmacist at the "A" position was responsible for receiving,

reviewing, and logging prescriptions, while the pharmacist at the "B"

position was responsible for filling prescriptions with the help of a

technician, and for checking and dispensing all finished

prescriptions. After computer installation, the pharmacist at the "B"

position seemed to be under less pressure because there was not a

continual backlog of prescriptions ready to be filled (but, again

there was a backlog at the inputing stage).

In conclusion, although various types of work redesign, including

computerization, may be implemented to improve efficiency and/or

quality of work life, the actual results of the redesign should be

assessed to determine if further changes are needed. Probably no

pharmacy manager should assume that freeing employees to perform more

professional tasks will actually impel them to do so without training

or encouragement. Individual employee data collected by the

multidimensional approach indicates that one pharmacist spent twice as

much time consulting with the patients as the other pharmacist, both

before and after computerization. Another indication that this is

probably true is research that found no correlation to exist between

the "busyness" of a pharmacy operation and the amount of consultation

that took place by pharmacists (Berardo, Kimberlin, & Wilt, 1984;

Mason & Svarstad, 1985).

Results from this study suggested that multidimensional work

sampling was a reliable method of work sampling and may be more useful

in capturing professional activities than a direct observation method

for this setting. Application of this method to other pharmacy

settings may be useful, and further studies in various settings are

highly recommended. Finally, it was also suggested that, in comparing

the results before and after the redesign is implemented, an analysis

of variance method may be more useful than a chi-square test in

determining if a significant change did in fact occur.


Activity Contact Function

Telephone Self Patient record
Meeting 1:1 Patient/patient advocate Patient assessment
Meeting 3+ Colleague (R.Ph.) Dispensing medicine
Read, study Staff (physician) Prescribing medicine
Write, dictate, sign Resident History (drug)
Prepare Medical student History (medical)
Evaluate/review Pharmacy student/preceptor Administration
Observe Nursing staff Patient billing
Think/plan Med/surg rep/vendor Consult/referral
Sort, file, retrieve Pharmacy support personnel Teaching
Transit/waiting Secretary/reception Research/learning
Other Other Other

Adapted from Hadsall et al. (1982).



1. MEETING 1:1--This includes any interaction with another person
and not necessarily just a planned meeting.

2. MEETING 3+--This includes any interaction with three or more

3. PHONE--This includes any time you are on the phone when the
machine beeps. Even if you are on hold at the time, this
activity should be chosen.

4. TYPE--This includes any time spent typing on the typewriter.

5. COMPUTER ENTRY--This includes time spent entering information
into the computer through the computer keyboard.

6. REVIEW/CHECK--This will usually deal with checking something that
has been prepared previously, like a prescription or a compound.

7. SORT/FILE/RETRIEVE--This includes putting prescriptions in order
or filing them or retrieving prescriptions from the file. This
may also include watching billing forms. It is used with the
stock function to indicate filing stock onto the shelf when you
are putting up an order.

8. WRITE/SIGN--This includes activities where you are writing
something down, for example, if you are off of the phone
transcribing the prescriptions you just received or if you are
writing a stores order. If you are on the phone and writing at
the same time, use No. 2 instead as your activity.

9. PREPARE--This may include activities such as preparing a
prescription or preparing a package for mailing. Examples of
these activities are retrieving a drug from the shelf, counting
or pricing a prescription, or packaging a mail-out prescription.

10. TRANSIT/WAITING--If the beep catches you traveling from one place
to another or waiting for your next activity, this should be
recorded. For example, if you are carrying a prescription to be
logged in.

11. ABSENT--This includes all times when you are not in the pharmacy
when the beep sounds. This includes times when you are running
errands, taking a break, or eating lunch.

12. OTHER--This includes activities not covered by the above 11


1. SELF--This includes times when you are not interacting with

2. PATIENT/PATIENT REPRESENTATIVE--This includes all customers and
the people that are with them.

3. OTHER PHARMACY PERSONNEL--This includes any pharmacy personnel,
including in-patient, stores, administrative personnel, and

4. SUPERVISOR--This includes talking to Paul when you are asking him
supervisory questions (i.e., you have a problem that is out of
the ordinary).

5. PHYSICIAN--This includes all physicians, residents, and dentists
whether or not they work at Shands.

6. NURSE--This includes LPNs and RNs.

7. CLERK--This includes emergency room and floor clerks.

8. OUTSIDE PHARMACIST--This includes pharmacists not working for

12. OTHER--This includes interaction with someone not listed in the
above items.

taking any information about the patient. One exception is that
any professional consultation or advice concerning medications
should be recorded under No. 8. Another exception is information
used during detection or correction of a prescription problem or
duplication should be recorded under No. 9 or No. 10.

2. PREPARE LABEL--This is used primarily when the prescription label
is being type. This does not include mail-out labels.

3. PRICE PRESCRIPTION--This includes finding the cost of the drug on
the shelf or in the stores book and calculation of the customer's

4. PREPARE PRESCRIPTIONS--This includes retrieving medications from
the shelf, counting the medications, compounding, and putting the
medication into containers. This also includes labeling,
packaging, and recording mail-out prescriptions and checking any
of these activities. This does not include typing or pricing the

5. BILL PRESCRIPTION--This includes filling out the billing forms,
ringing the billing forms into the cash register, and getting the
forms ready for submission.

6. DISPENSE PRESCRIPTION--This includes handing the prescription to
the patient, patient representative, nurse, or clerk.

7. COLLECT PAYMENT--This includes receiving cash, check, or a credit

8. CONSULTATION/ADVICE--This includes any professional consultation
or advice given to a patient, patient representative, doctor, or
nurse considering some aspect of medication. This does not
include information as to if the prescription is ready, or the
price, etc.

reserved for recording the function of catching a problem where
the patient already has a prescription for this medication.

signature, no strength, nonformulary item or a drug interaction.

11. ORDER/PICK UP/PUT UP STOCK--This includes writing an order,
calling in an order, picking up an order, or putting stock
away. When the computer is installed this will also include
reviewing the order printout.

12. OTHER--This includes any function not covered in the above 11



1. You are phoning in the narcotics order.

2. You are asking Lynne what the best time to take a lunch break
would be.

3. A woman is asking you the price of her prescription.

4. You are ringing the billing forms into the register.

5. You are taking a bottle of medicine from the shelf to fill a

6. You are using the calculator to determine the price of a
prescription while preparing the prescription.

7. You are on the phone with a physician because he forgot to put
the quantity on the prescription.

8. You are typing a label.

9. You are writing a patient's name in the log book.

10. You are explaining that the prescription you are handing the
patient needs to be taken with food or milk.

11. You are writing up a master card form.

12. You are writing up a billing form.

13. You come back from lunch and the red light on your machine is on.

14. You are giving a prescription to an ER clerk.

15. You are on the phone asking the floor nurse to check why you
received two prescriptions for the same medication for a patient
that is being discharged.

16. You are dropping off the billing forms and when you get back the
red light on your machine is on.

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