Health care triage alternatives and the influence of health insurance, education and race

WliENT

EdLJCATiON

ANdCouNSE[iNG ELSEVIER

Patient Education and Counseling 28 (1996) 287-296

Health care triage alternatives and the influence of health insurance, education and race Bradley C. Martin, Matthew Perri III*, Jeffrey A. Kotzan Pharmacy

Care Administration,

College of Pharmacy.

University

of Georgia,

Athens,

GA 30602-2354.

USA

Received 12 September 1995; accepted 21 November 1995

The relationship between one of Andersen’s enabling factors, health insurance status and the choice of a pharmacist as the initial contact in the health care system wasexamined via telephone surveys.Eighty-seven percent of the sample reported having some form of health insurance. Of all intended health care provider contacts, pharmacists wereselected as the initial contact 21% of the time. Logistic regression identified insurance status, education and race as significant (alpha < 0.05) covariates in the model. The odds ratios generated from the logit model indicated that non-whites, persons with less education and no health insurance were more likely to select a pharmacist for triage. The study concluded that uninsured persons were nearly twice as likely to seek pharmacist triage than insured individuals. Pharmacists may be tilling an important triage gap for individuals who have limited tinancial accessto traditional sourcesof physician care. Keywords:Triage; Health insurance; Pharmacist counseling;

1. Introduction

Pharmacists have been long recognized as health care consultants for individuals suffering from various symptoms, often serving as the first point of contact with the health care system. This may in part explain why some states such as Florida, New Mexico, California, Mississippi, Missouri, Nevada, New Mexico, Oregon, South Dakota and Washington have granted limited prescribing l Corresponding author, Tel: +I-706-5425365; Fax: +l-7065425228; E-mail: [email protected].

Uninsured;

Self-care

rights to pharmacists [ 1,2]. Nearly every practicing retail pharmacist dispenses valuable information daily to a broad array of community patrons in need of advice on how to best treat diverse ailments [3]. However, empirical research documenting these activities has been scant. Most studies on this subject have relied on persons entering pharmacies presumably to have prescriptions filled, seek advice, or purchase overthe-counter (OTC) medicines. One study observing persons patronizing pharmacies in the Cincinnati area reported that 13% of persons entering pharmacies asked medical related questions [4].

073%3991/9%09.50 0 1995 Elsevier Science Ireland Ltd. All rights reserved PII 0738-3991(96)00855-5

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Another California based study demonstrated that 17% of all requests of pharmacists were of professional (medical) nature [5]. These studies suggest that pharmacists are frequently relied upon to disseminate medical information, but, due to the non-random selection of pharmacies and patrons these findings can only be cautiously generalized. Additionally, since these studies used persons already patronizing pharmacies it is impossible to know to what extent the general population utilizes the pharmacist as a source of medical information. In a study designed to assess what information patients most want from pharmacists it was found that patients want a wide variety of information [6]. For example, patients feel pharmacists should provide counseling about prescribed medications. Additionally, pharmacists should provide information and counseling to patients about diseases for which medications are prescribed (e.g. diabetes, AIDS, hypertension, hyperlipidemia). Patients also indicated a desire for recomendations of over-the-counter products (i.e. vitamins, diet pills, cough and cold preparations, femme care products, foot and skin care products) and specific areas such as sports injuries and eye care. The effect of pharmacist counseling was measured by observing changes in over-thecounter (OTC) purchasing behavior and physician referrals in California [7]. This study identified sizeable changes in purchasing behavior due to pharmacist counseling and physician referrals for 40.1% of those counseled. The question to be answered is what prompts persons to seek counsel and to what extent the general population solicits advice from pharmacists. Theoretical constructs of care seeking behavior have been put forward such as the health belief model and the theory of reasoned action. However, these theories provide little direction for determining which health care providers people choose first [8]. Studies describing health seeking behavior subsequent to some symptomology ignore the pharmacist as an entry point into the health care system, focussing largely on physician contacts and self-care [9]. The Andersen-Newman behavioral model [lo] presents the use of health care as a function of:

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(1) Need - illness related factors (2) Enabling factors - income, insurance, health manpower, medical facilities, etc. (3) Predisposing factors - age, social class, race, etc. This model would suggest that the above factors are related to medical utilization and that if medical utilization can be operationalized as a continuum of no treatment to physician utilization, these factors may be useful in determining whether an individual self-treats, seeks pharmacist triage, or physician triage. There have been a wealth of studies documenting the relationship between these factors and medical utilization and are well described in a review article by Hulka and Wheat

t111. Another theory elucidating the potential determinants why patients might choose pharmacists as the initial point of contact for health care delivery is economic in nature. Since persons without health insurance face higher out-of-pocket costs (price of health care), the economic theory of consumer demand would indicate that the health insurance status of individuals may cue persons to certain types of providers through a price mechanism [ 121. Since most pharmacists provide consultation free of charge, persons suffering from various symptoms may be more likely to seek pharmacist triage and advice first. Given that 3 l-36 million (15- 17%) Americans are without any form of health insurance on any one given day, it is important to determine where these individuals initially seek care when suffering from various symptoms [ 131. It may be hypothesized that given the free consultation services offered at most community pharmacies, individuals without insurance may turn to their pharmacist as a cost effective point of health care delivery. 1.1. Objectives This research project sought to determine the initial health care provider for persons suffering from a variety of common symptoms. This study is theoretically derived from the AndersenNewman model of medical utilization and the economic theory of consumer demand. Specifical-

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ly, the objectives of this study were to: (1) describe the point of initial contact in the health system for persons who would be suffering from various disease symptomology and (2) determine if the initial selection of a health care provider is influenced by the health insurance status of the individual. 2. Methods 2.1. Survey instrument An abbreviated g-item scale based on a disease symptomology index published by Stoller et al. [14] was developed to determine the intended point of first contact, if any, to the health care system. The symptom index published by Stoller et al. was adapted for use in a phone survey. The symptoms represent the illness factors that would prompt patients to utilize medical care. The nine symptoms used in this survey were: nasal congestion, headache, difficult breathing/shortness of breath, rash, diarrhea, muscle or joint pain, constipation, obesity (weight loss) and gastrointestinal upset. Specifically, each of the nine symptom items ascertained the intentions of the respondents by asking them, “if you were suffering from symptom would you first go see or ask a physician, go see or ask a pharmacist, go see or ask some other health care provider, self-treat the symptom, or take no action...“ Responses were then categorized into six intended triage categories: pharmacist, physician, other health care provider, self-treat, no action, or don’t know/response not determined. The ordering of the responses for physician/pharmacist were randomly reversed between responses to circumvent any ordering bias. The ‘go see or ask some other health care provider’ category was selected to capture other potential medical consultations such as chiropractors, social workers and neighborhood mental health centers collectively. Other non- pharmacist/physician encounters were collapsed into a general catch-all category based on the findings of the Stoller study which indicated that a majority of elderly self-treat most symptoms and that other non-physician/pharmacist triage were selected infrequently [ 141. Two items assessed the insurance status of respondents. The first item was a point estimate of

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the respondent’s current insurance status determining if respondents were insured the day the telephone interview took place. The second item sought to determine the type of insurance coverage if the respondents indicated they had insurance. The point estimate of insurance status is consistent with the Andersen-Newman enabling factors. Finally, seven items were developed to ascertain demographic information including educational attainment, income, sex, race, age and marital status. This survey was conducted as part of a larger biannual telephone survey regularly conducted by the University of Georgia Survey Research Center (UGASRC). A total of 46 items were included in the final survey, 28 of which were not directly related to this research project. The survey items were pretested with 20 local phone interviews and minor modifications to the survey instrument were made to improve the clarity of the survey items. No revisions were made to the survey items relating to the triage of medical symptoms or to the two items assessing health insurance status. 2.2. Subjects and survey methoa3 The telephone survey was designed to provide a probability sample of all telephone households by using a random digit dialing procedure. All telephone households including unlisted and new telephone listings were eligible for the survey by using the random digit dialing process. This procedure produces a self-weighting representative crosssection of the Georgia population. Respondents eligible for the survey once a household was selected were adults, age greater than or equal to 18. A random procedure known as the ‘last birthday’ method was utilized to select a respondent once a household had been contacted. This method provides a probability sample within a household based on the premise that the assignment of a birth date is a random process. If an interview could not be conducted with a resident of the household with the most recent birthday, substitute members of the household were permitted to complete the interview. Phone surveys were conducted at the UGASRC

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by supervised, trained interviewers between 25 May 1994 and 7 June 1994. Interviewers attended two 3-h training sessions which covered survey methods, standard procedures of the telephone interview, in-depth explanation of the survey instrument and a practice session. A supervisor is present at all times during the interview process and approximately 25% of all interviews were monitored as a quality check. 2.3. Analysis Given the dichotomous nature of the dependent variable (seeking or not seeking pharmacist consultation), logistic regression was employed to isolate the independent effect of insurance status on the initial selection of a health care provider (151. The logistic regression coefficients for insurance status were transformed to yield log-odds ratios with 95% confidence limits about the odds ratios. The odds ratios indicate how many more times likely a person without insurance initially contacts a pharmacist over an insured individual. To capture the effect of insurance status on the likelihood to consult with a pharmacist for triage independent of the arbitrarily chosen symptoms, the dependent variable was set at 1 if the respondent indicated they would consult a pharmacist for any of the nine symptoms and 0 if they indicated no pharmacist consultations. Other covariates

y = PO+PI XL+P2x2+Pax3 + P,x4+ PIx. +P.X6+I%x7+E, Y

=

0

no pharmacist

I - at least

one

consultations pharmactst

X,

=

0 - health msurance I no health msurance

X,

=

0 - no post I - some (m

high post

X,

=

Age

X,

=

(Age):

X,

=

(Age)’

X,

=

0 - non-white I white

X,

=

0 female I - male

school high

school

for consultanon

any

of for

the the

educatmnltrammg educatmnhrammg

years)

Fig. 1. Logistic regression model.

rime rime

symptoms symptoms

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were included in the model to control for the predisposing demographic factors in the model. Race, sex and educational attainment were included in the model as dichotomous variables. There were three terms for age in the logit model: a simple linear term, a quadratic term and a cubic term. The quadratic term and the cubic term were used in addition to the linear term to permit the modal modeling of age where the probability of seeking a pharmacist may initially increase, peak, then decrease with age. Similarly, an OLS regression model was employed to model the impact of insurance status on the number of pharmacist consultations using the same model specification as the logit model (Fig. 1).

3. Results 3.1. Survey respondents A total of 2033 phone numbers throughout the state of Georgia were dialed. Of the 2033 numbers dialed, 1506 were not eligible for the survey resulting in 527 eligible households for the survey. Numbers were not considered eligible for the survey and subsequently excluded for a variety of reasons including number not working/changed, business, no answer/busy, answering machine, strange noise (modem) and wrong number. For the remaining 527 eligible households, 414 complete interviews were obtained for a response rate of 78.6%. Partial interviews were obtained for 9 respondents and 104 eligible households refused. The resulting sample of 414 respondents, detailed in Table 1, is roughly similar to the state population in terms of demographics. The average age of respondents was 44 years, 60% of the respondents were females and 81% of the respondents were white. As might be expected with a survey of telephoned households, however, the respondents were slightly older, more likely to be white, more likely to be female and more likely to have sought some college education than the state population as a whole (x2, P < 0.05). Despite the statistical differences, the respondents are loosely comparable with the state population with the exception of the noted differences that would be expected of

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Table 1 Demographic profde of respondents and Georgia residents Survey respondents

Al+

18-24 25-44 45-54 55-64 65 + Race? white Non-white !&TX a Male Female Education’ O-11 years H.S. Diploma Some college College graduate Advanced degree Insuranceb Uninsured Insured

1990 US census (Georgia)

n

%

n

%

42 184 78 51 56

10.22% 44.77% 18.98% 12.41% 13.63%

765 730 2 277 430 696 567 518 720 681747

15.5% 46.1% 14.1% 10.5% 13.8%

334 78

81.07% 18.93%

4 599 533 1 878 683

71.0% 29.0%

167 247

40.34% 59.66%

3 141935 3 336 281

48.5% 51.5%

53 112 137 77 34

12.83% 27.12% 33.17% 18.64% 8.23%

897 889 913 316 524 540 552 310 197 474

52 361

12.6% 87.4%

1425000 5053080

29.10% 29.6% 17.0% 17.9% 6.4% 16.1% 83.9%

“x2 significant at a=O.OS, comparing the distribution of respondents within the demographic categories with the expectancies generated from the Census data. bInsurance status of Georgia population is 3-year average (1990-1992) Source: US Bureau of Census, Current Population Reports, 1994 [16].

Table 2 Intended point of initial contact for nine clinical symptoms Symptom

Nasal congestion Diarrhea Constipation Gastrointestinal Rash Muscle/joint pain Headache Difftculty breathing/shortness of breath Diet

Pharmacist consultation

Physician consultation

Other H.C. consultationa

No H.C. consultation b

n

W)

n

W)

n

(“N

n

(W

60

(14.6) (12.4) (10.7) (10.4) (10.3)

70 52 22 35 259 167 18

(17.0) (12.7) (5.4) (8.5) (63.8) (40.8) (4.4)

7 6 5 2 14 I1 1

(1.7) (1.5)

(0.2)

275 301 339 332 91 204 374

(66.7) (73.4) (82.7) (80.6) (22.5) (49.9) (91.0)

362 87

(88.3) (21.4)

I2 7

(2.9) (1.7)

28 306

(75.3)

51 44 43 42 27 18 8 6

(6.6) (4.4)

(2.0) (1.5)

(1.2) (0.5) (3.4) (2.7)

(6.8)

sPersons intending to consult a health care professional other than a pharmacist or physician. bPersons intending to self-treat the symptom without consulting a health care professional or take no action and not treat the symptom.

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a survey of telephoned households which are less likely to include very low income households. The self-reported insurance status of the respondents indicate that an overwhelming majority of respondents had insurance the day the interview took place. Over 87% of the respondents indicated that they had some health insurance which is higher than the estimated statewide rate of insured of 84%, though the difference was not significantly significant. Of those insured, 81% had private/ employer sponsored health insurance, 12% were receiving Medicare benefits and 5% had insurance provided by Medicaid. For nine (2%) of the insured respondents, the type of insurance could not be ascertained. 3.2. Intended actions toward the nine symptoms On average, respondents intended to consult a health provider 39% of the time. The intention of respondents to seek consultation/triage from a health care provider varied considerably by symptom (Table 2). Shortness of breath was the symptom most associated with the intent to consult a health care provider (intended by 93% of respondents) and headache was the symptom least associated with consulting a health care provider (intended by 9% of respondents). With the excep tion of three symptoms (rash, shortness of breath and muscle/joint pain), the majority of respon-

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dents indicated that they intended to self-treat the symptom. Self-treating the symptom was intended by 63% of respondents for nasal congestion, 85% of respondents for headache, 70% for diarrhea, 77% for constipation and 71% of respondents for weight loss. Respondents rarely indicated that ‘no action’ was intended for any of the nine symptoms. The selection of a health care provider was also influenced by the symptom presented to the respondent as depicted in Table 2. For two of the symptoms, constipation and gastrointestinal, the pharmacist was most often selected as the health care provider of choice for persons intending to seek counsel from a medical care provider. When a health care provider was sought, pharmacists, on average, were the intended initial point of contact 21% of the time. For five of the nine symptoms (nasal congestion, diarrhea, constipation, gastrointestinal upset and rash) at least 10% of respondents intended to seek counsel from a pharmacist. By observing the intentions of the respondents as a set, it was found that 35% of respondents intended to seek triage from a pharmacist for at least one of the nine symptoms. For six of the nine symptoms, a physician was most frequently cited as the initial point of contact for persons intending to seek counsel from a health care provider. Intended physician contacts accounted for 75% of all intended health care provider consults over the nine symptoms. The

Table 3 L.ogistic regression results Variable a_

Variable coding

IllSUWlCC~

0 - No insurance 1 - Insurance 0 - No college 1 - At least some college O-Female 1 - Male 0 - Non-white l-White 18-91 (age in years) 324-8281 (age years)* 5832-753 571 (age years)3

EdUCiStiOll

Gender Race Age Ad AIF’ aP < 0.05

for Wald x2 test.

Coeffkient

Log odds ratio

95% C.I. odds ratio

-0.6405

0.527

0.281-0.991

-0.8306

0.436

0.281-0.677

-0.0766

0.926

0.594-1.444

-0.5494 0.0501 -0.0012 0.0000

0.577 1.051 0.999 1.000

0.343-0.972 0.800-1.380 0.993-1.005 1.000-1.000

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selection of a physician ranged from a high of 88% of respondents hypothetically suffering from shortness of breath to a low of 4% of respondents suffering from headache. Rarely were health care providers other than pharmacists or physicians cited as possible points of triage. 3.3. The influence of insurance status on the selection of a health care provider Proportionately more uninsured persons intended to seek pharmacist triage for at least one of the symptoms than insured persons (48% uninsured vs. 33% insured). The effect of insurance status also appears to influence the intention to consult a physician. For example, 18% of insured persons intended to seek counsel from a physician when suffering from nasal congestion contrasted with only 8% for uninsured persons. This pattern of insured respondents proportionately intending to seek more care from a physician than uninsured persons persisted for seven of the nine symptoms (nasal congestion, shortness of breath, rash, diarrhea, joint pain, weight loss and gastrointestinal upset). To isolate the. independent effect of insurance status on the selection of a pharmacist as the initial health care provider for any of the nine symptoms, a logit model was estimated. The logit model coefficients, log odds ratios and confidence limits ap-

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pear in Table 3. The model appears to be a reasonable tit based on a significant log likelihood test comparing the full model with the intercept only (P = 0.0002) and a 66.8% concordance between predicted and actual values of the dependent variable. The coefficients and odds ratios for insurance status, educational attainment and race are all significant at QL= 0.05 in the original logit model (Wald x2 and 95% confidence limit about log odds ratios). The remaining non-significant covariates were retained in the model to avoid the potential for mis-specification errors. The odds ratio for insurance status indicates that respondents with insurance are approximately half as likely as respondents without health insurance to seek pharmacist triage for at least one of the nine - symptoms. Conversely, uninsured respondents are approximately 1.9 times as likely to seek pharmacist triage than their respective counterparts with ins :ance. As for the other two significant covariates, the odds ratios suggest that non-whites and persons without any postsecondary training are 1.7 and 2.3 times as likely to seek pharmacist triage than their respective counterparts. An OLS estimation with the same independent covariates regressed on the sum of intended RPh contacts was performed to validate the directionality of the findings obtained from the original logit model. Originally, the dependent variable

Table 4 OLS regression results Variable

Variable coding

Insurance

0 - No Insurance I - Insurance 0 -- No college 1 - At least some college 0 -- Female 1 -- Male 0 -- Non-white 1 -- White 18-91 (age in years) 324 -8281 (age years)2 5832-753 571 (age years)3

Education Gender RaCe Age Age2 Age3 “P

< 0.05 for r test Ho: Coefficient = 0.

Coefficient

r for Ho: coefficient = 0

95% C.I. coeffkient

-0.258

-2.413

-O&8--0.048

-0.258

-3.598

-0.398--O. 117

-0.010

-0.147

-0.150-0.129

-0.217 0.015 -0.ooo1 0.0000

-2.466 0.348 -0.604 0.719

-0.389--0.044 -0.068-0.098 -0.002-0.001 -o.ooo-o.ooo

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was set equal to the sum of intended pharmacist contacts in the OLS model. A histogram of the dependent variable revealed that the underlying distribution was skewed (range O-7; mean 0.73). To temper the skewness of the dependent variable and subsequent residuals obtained from OLS estimation, a square root transformation of the dependent variable was used in a new model with the same covariates (range O-2.65; mean 0.48). This transformation proved to improve the fit slightly as the observed F-value and R* improved with the use of the transformed dependent variable. The final model with the transformed dependent variable was significant (QW = 5.064, P < 0.0001) with a modest R* equal to 0.0816. The OLS coefficients, detailed in Table 4, mirror the findings of the logistic model. Consistent with the logistic results, the OLS coefficient for insurance status indicates that individuals without insurance intend to seek significantly more pharmacist triage than those with health benefits. The racial and educational differences revealed in the logistic model are also substantiated with the OLS model, where it is found that non-whites and individuals without post-secondary education intend to seek more pharmacist triage/consultation. Since the dependent variable was transformed, the interpretation of the magnitude of the coefficient can only be interpreted as incremental changes about the mean of the covariates. 4. Discussion Previous research on the relationship between disease symptomology and the selection of an initial contact with a health care provider has focussed primarily on the patient-physician encounter. In the pharmacy arena, research has focussed exclusively on pharmacy patrons with no population-based studies determining the frequency of pharmacist triage for a generalizable population. This survey of Georgia residents demonstrates that while physicians are the most sought after health care providers for most symptoms, pharmacists account for a significant proportion of intended triage contacts. Approximately 35% of persons intended to consult with a pharmacist for at least one of the nine symptoms presented and

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pharmacist triage accounted for 21% of all intended health care consults. This is an appreciable number of intended pharmacist consults with large potential saving to the health care system. Caution should be exercised in extrapolating these findings since it was found that the study sample was slightly more educated, slightly older, had proportionately more females and whites than the general Georgia population. These differences were statistically significant; however, the deviations were not greatly disparate. Consistent with expectations, pharmacist triage was proportionately greater for uninsured persons. Uninsured persons were nearly twice as likely to seek pharmacist triage than insured individuals controlling for confounders such as race and educational attainment. The economic explanation for this is that most pharmacists provide consultation free of charge. This is an important finding since little is known about the access of uninsured persons to primary care. If the intentions of these respondents parallel actual behavior, pharmacists may be filling the primary care gap for these persons with limited financial access to primary care. It should also be noted that the majority of patients indicated that they intended to first try to self-treat most of the nine symptoms presented. This finding affrms the influence of enabling factors on medical utilization and is consistent with the economic theory of consumer demand. This consumer confidence in pharmacists ability to handle certain symptoms on their own may be the result of many factors. For example, health information is now more widely available than in the past and armed with such information consumers may have greater confidence in their ability to make health decisions. Also, with the recent prescription to over-the-counter medication switches there are more and better over-the-counter medications available to consumers. The concern over controlling health care costs may also be a driving force in self-treatment. Regardless of the reason, self-medication appears to be an option for many patients. The high numbers of patients who intend to self-treat should emphasize to the health care practitioner the importance of assessing prior self-treatment when patients do seek advice from

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Table 5 Practice implications Because a majority of patients appear to be self-treating many symptoms, health professionals should be aware of this in making therapeutic recommendations. The uninsured may be seeking triage from pharmacists in greater proportions than the insured. Pharmacists and physicians should develop methods to manage the quality and effectivenessof the triage function. Pharmacists may need to develop payment strategies for the provision of triage. Pharmacists should educate patients about triage functions that may be provided as a part of pharmaceutical care delivery.

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model [lo]. Knowing the ratios associated with these demographic variables, one could statistically adjust for differences across populations, affording greater precision in the estimation of the rate of intended pharmacist triage across populations. Finally, this survey assessed the behavioral intentions of respondents hypothetically suffering from nine common symptoms/conditions. No previous studies describe the rate of pharmacist consultation by disease symptomology thus precluding comparison. The nine symptoms selected in this survey were arbitrarily chosen form a much larger universe of symptoms. As evidenced in this study, the rate of intended pharmacist/ physician triage varies greatly with the symptom presented. Given the high inter-symptom variability, these results can only be generalized to the same set of symptoms.

pharmacists, physicians and other health practitioners (Table 5). References 4.1. Limitations This research project sought to determine the intended initial selection of a health care provider for a representative sample of Georgia residents who were not necessarily suffering from any symptoms the day the interview took place. However, intentions are frequently used to pattern actual behavior when longitudinal measures of actual behavior are too prohibitive to collect. To the extent intentions deviate from actual behavior, these results are limited. Further, as with most samples of a population, the sample selected may not be representative of the surveyed population. Random digit dialing (a probability method) should have minimized this problem in the selection of individual households. These results could only be cautiously generalized to larger populations such as the United States. There are many potential confounders that could not be collected and analyzed to provide ratios permitting comparisons across populations. However, two confounders, race and educational attainment have been shown to influence the intention to seek pharmacist triage. This finding is consistent with the empirically documented predisposing factors of the Andersen-Newman

VI Assessment of the Florida self-care consultant law using

patient profile and prescription audit methods. DICP Ann Phannacother 1990; 24: 931-935. PI Chi J. Texas, North Dakota, VA sign on to R.Ph. prescribing, Hospital Pharmacist Report, July 1995; p. 13. 131 NARD. Pharmacists can save money and lives. NARD J, July 1993; 15. [41 Selya RIM. Pharmacies as alternative sources of medical care: the case of Cincinnati. Sot Sci Med 1988; 26: 409-416. PI Linn LS, Lawrence GD. Requests made in community pharmacies. Am J Phann 1978; 68: 492-493. Kl Francisco G, Petri M, Pritchard FL. Pharmaceutical Care in the Community Chain Pharmacy Setting, Final Report to the American Association of Colleges of Pharmacy, July 1995. [71 Nichol MB, McCombs JS, Johnson RA, Spacapan S, Sclar DA. The effects of consultation on over-thecounter medication purchasing decisions. Med Care 1992; 30: 989-1003. 181 Lauver D. A theory of care-seeking behavior. Image J Nurs Sch 1992; 24: 281-287. 191 Wilkinson IF, Darby DN, Mant A. Self-care and selfmedication: an evaluation of individuals’ health care decisions. Med Care 1987; 25: 965-978. WI Andersen R, Newman JF. Societal and individual determinants of medical care utilization in the United States. Milbank Mem Fund Q 1973; 5: 235-51. [III Hulka BS, Wheat JR. Patterns of utilization: the patient wrsneotive. Med Care 1985: 23: 438-460.

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1121 Silberberg E. The Structure of Economics: A Mathematical Analysis, second edition, 1990. New York: McGrawHill, pp. 299-389. 1131 Friedman E. The uninsured: from dilemma to crisis. J Am Med Assoc 1991; 265: 2491-2497. [14] Staller EP, Forster LE, Portugal S. Self-care response to

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symptoms by older people: a health diary study of illness behavior. Med Care 1993; 31: 24-42. [lS] Hosmer DW, Lemeshow S. Applied Logistic Regression. New York: John Wiley, 1989. [16] US Bureau of the Census. Statistical Abstract of the United States: 1994 (114th edition.) Washington, DC, p. 118.