Ensuring high-quality primary care for women: Predictors of success

Women’s Health Issues 16 (2006) 22–29

ENSURING HIGH-QUALITY PRIMARY CARE FOR WOMEN: PREDICTORS OF SUCCESS Bevanne A. Bean-Mayberry, MD, MHSa,bⴱ, Chung-Chou H. Chang, PhDb, Melissa A. McNeil, MD, MPHa,b, and Sarah Hudson Scholle, DrPHc,d a

Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA Center for Research on Health Care, Division of General Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA c Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA d Research and Analysis, National Committee for Quality Assurance, Washington, DC, USA

b

Received 11 November 2003; received in revised form 12 October 2004; accepted 10 December 2004

Background. Provider gender, provider specialty, and clinic setting affect quality of primary care delivery for women, but previous research has not examined these factors in combination. The purpose of this study is to determine whether separate or combined effects of provider gender, availability of gynecologic services from the provider, and women’s clinic setting improve patient ratings of primary care. Methods. Women veterans receiving care in women’s clinics or traditional primary care at 10 Veteran’s Affair (VA) medical centers completed a mailed questionnaire (N ⴝ 1321, 61%) rating four validated domains of primary care (preference for provider, communication, coordination, and accumulated knowledge). For each domain, summary scores were calculated and dichotomized into perfect score (maximum score) versus other. Multiple logistic regressions were used to estimate the probability of a perfect score in each domain while controlling for patient characteristics and site. Results. Female provider was significantly associated with perfect ratings for communication and coordination. Providing gynecologic care was significantly associated with perfect ratings for male and female providers. Patients who used a women’s clinic and had a female provider who gave gynecologic care had perfect or nearly perfect ratings for preference for provider, communication, and accumulated knowledge. Conclusion. Gynecologic services are linked to patient ratings of primary care separate from and in synergy with the effect of female provider. Male and female providers should consider offering routine gynecologic services or working in coordination with a setting that provides gynecologic services. Health care evaluations should assess scope of services for provider and practice.

Background For women, primary care goals such as access, communication, continuity, comprehensiveness, and coor-

Dr. Bean-Mayberry’s project was funded by the Department of Veterans Affairs, Veteran’s Integrated Service Network 4, Competitive Pilot Project Funds in 2000. Dr. Scholle is supported in part by the National Center of Excellence in Women’s Health at MageeWomens Hospital. ⴱ Correspondence to: B.A. Bean-Mayberry, Center for Health Equity Research and Promotion, VA Pittsburgh Healthcare System, University Drive C (151-C), Pittsburgh, PA 15240. E-mail: [email protected] Copyright © 2006 by the Jacobs Institute of Women’s Health. Published by Elsevier Inc.

dination (Flocke, 1997; Institute of Medicine, 1994, Safran et al., 1998; Starfield, 1992) are often difficult to achieve owing to the fragmentation of health care services. Prior research indicates that variation in care for women may occur owing to provider gender, the division between general and gynecologic services, and the use of gender-specific practice settings. The literature focused on provider gender and receipt of clinical preventive services demonstrates that women who use female generalist providers are more likely to receive routine gynecologic and mammography services (Franks & Clancy, 1993; Kreuter et al., 1995; Lurie et al., 1993; Lurie et al., 1997) and more gender1049-3867/06 $-See front matter. doi:10.1016/j.whi.2005.12.002

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specific counseling (Franks & Clancy, 1993; Kreuter et al., 1995) compared to women who use male generalists. In contrast, male and female gynecologists tend to provide similar preventive care to women (Sonenstein, Ku & Schulte, 1995). The specialization and segregation of general medical care and reproductive care contributes to the overall fragmentation of women’s health care (Weisman, 1996, 1998). This schism most likely contributes to the finding that one third to one half of women surveyed use multiple providers, specifically, a gynecologist and generalist physician (Henderson, Weisman & Grason, 2002; Weisman, 1996, 1998) for overall health care. This use of multiple providers for overall health care may result in either higher costs for care owing to overutilization or gaps in care owing to poor coordination of multiple health care relationships (Weisman, 1996). In addition, some women prefer going to a gynecologist for their pap smears and pelvic exams rather than a generalist physician (Pemberton et al., 1998), and 2 prior studies show that women are more likely to receive gender-specific care (pap smear, pelvic exam, or mammogram) from the gynecologist compared to the generalist (Weisman, 1996; Lurie et al., 1997). Part of this variation in care may be related to the fact that these gender-specific services have been overwhelmingly provided by gynecologists versus family physicians or internists during the past decade (Scholle et al., 2002). However, more internists are beginning to offer these services (Scholle et al., 2002). This new transition combined with the findings that women prefer to receive their gynecologic care from the same site that provides general medical care and that women are more likely to obtain these gender-specific services from a site where they obtain usual care (Sonenstein, et al., 1995) suggests that women may be likely to seek multiple services from one site or, perhaps, one provider. Recent research has also compared practice settings where women receive care to understand whether these clinical settings that offer combined genderspecific and general medical care (women’s health centers or clinics) provide improved care for women patients. Women who use specialized women’s health settings have comparable or higher quality measures (e.g., preventive screening) (Anderson et al., 2002; Harpole et al., 2000; Phelan et al., 2000; Webb & Opdahl, 1996) and higher satisfaction (Anderson et al., 2002) compared to women in other community settings with traditional primary care. These findings suggest that regular providers who are female or who practice in a women’s health setting may enhance the delivery of comprehensive services to patients (Harpole, et al., 2000). However, in these previous studies, the majority of providers in women’s health settings were female and in one study, the providers overlapped between clinic settings (Phelan et al., 2000).

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These clinical and organizational issues make it difficult to determine whether the effect on quality measures is associated with provider gender, a provider’s scope of services, or an integrated outpatient setting. Other research indicates that some women prefer female physicians and gender-specific practice settings (i.e., women’s health centers or clinics; Cassard et al., 1997; Chandler, Chandler & Dabbs, 2000; Webb & Opdahl, 1996). These findings introduce the issue of selection bias and patient preference in samples used for health care ratings. Whereas previous analyses have examined the individual effect of provider gender, provider specialty, or health care setting on satisfaction and other quality measures, no publication has examined the individual and combined effects of provider gender, gynecologic services by the provider, and use of a women’s clinic setting. The purpose of this study is to determine whether the individual and combined (or synergistic) effects of primary care provider gender, availability of routine gynecologic services from the provider, and clinic setting improve patient ratings of primary care achievement. Our hypotheses are the following: women in general primary care settings will have higher primary care quality ratings if 1) the regular provider is female, 2) the regular provider manages routine gynecologic care, and 3) the patient participates in a gender-specific women’s health setting. These methods allow us to look for both individual and synergistic effects among the 3 factors compared to patients who see male providers, have no gynecologic care from the provider, and do not participate in women’s health settings. To scrutinize these factors, we examined the effects associated with best outcomes or perfect patient ratings in primary care.

Methods Setting and study design The Veteran’s Affairs (VA) setting was selected because multiple women’s clinics have been established within the VA system since the passing of the 1992 Veterans Health Care Act, and because patients in this VA region are generally assigned into women’s clinics based on VA administrative decisions rather than patient preference. The study uses data from a 10-site survey of women veterans selected from 1 VA regional network in Pennsylvania, Delaware, and West Virginia. This primary care study was completed in conjunction with a patient satisfaction project on women veterans described previously (Bean-Mayberry et al., 2003). This study is based on an analytic sample of 1,080 respondents who completed the anonymous mail survey and identified a regular provider. All sites offer outpatient care for women veterans through either traditional primary care clinics or designated women’s clinics. At locations where

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a comprehensive women’s clinic is present, the VA administration assigns all new women patients to the women’s clinic. Women who have been receiving care in a VA for a long period of time are often already assigned to traditional primary care clinic. At locations that may have a limited women’s clinic (screening clinic) or no women’s clinic, patients are uniformly assigned to a traditional primary care clinic. This assignment process, although not random, reduces the effect of potential selection bias discussed in the community samples of women’s clinic patients. To distinguish clinic setting from site in the VA, we identify enrollment at a women’s clinic versus traditional primary care clinic where the population served is likely to be approximately 95% male. Study population We used administrative data from the outpatient care files in the VA National Patient Care Database (VA Information Resource Center, 2000) to identify all unique female veteran patients with an outpatient visit at 1 of the 10 regional VA medical centers between March 1, 1999, and March 1, 2000. From the sample of women who met inclusion criteria (veteran status and at least one women’s clinic or traditional primary care clinic visit during the selected time period), we selected a stratified random sample by site. We created 2 clinic groups at each site: 1) women who had at least 1 visit to a women’s clinic and 2) women who had at least 1 traditional primary care clinic visit but no women’s clinic visits. Target recruitment involved 250 patients from each VA site, with 170 from women’s clinic and 80 from traditional primary care clinic. Two of 10 sites did not have a women’s clinic at the time of the sample selection. For both of these sites, 170 patients were randomly sampled from the traditional primary care clinic only. Our random sample consisted of 2,315 female patients identified from the 10 VA medical centers. Within this group, we mailed 2,161 surveys and received 1,321 in return for an overall response rate of 61%. We used the VA administrative database to compare the demograph-

2315 Total Random Sample 80 Deceased

74 Not Delivered

2161 Anonymous Surveys Mailed

1321 Overall Response Rate 61%

1080 Regular Provider Analytic Sample 50%

Figure 1. Selection of analytic sample.

Table 1. Patient characteristics and provider–service– clinic settings (n ⫽ 1,080) Factor Age (y) ⬍40 40–64 ⱖ65 Race, white Education High school Some college/technical training College graduate Married Annual income ⬎$20,000 Health status: Very good/excellent Enrollment in women’s clinic Provider–service–clinic combinations Female PCP ⫹ GYN ⫹ WC Female PCP ⫹ WC Female PCP ⫹ GYN Female PCP only Male PCP ⫹ GYN and/or ⫹ WC Male PCP only

Percentage 14.8 43.4 41.8 89.5 30.5 45.7 23.8 33.6 37.7 31.6 52.4 29.1 10.3 11.8 16.0 17.0 16.0

Abbreviations: PCP, primary care provider; GYN, gynecologic care by provider; WC, women’s clinic.

ics of all respondents (N ⫽ 1,321) to the overall random sample because the survey was anonymous. In general, respondent characteristics included older age, white race, and income above $20,000 (Bean-Mayberry et al., 2003). Within this group of 1,321 patients, 1,080 (50% of sample; 82% of respondents) identified a regular provider and remained in the analyses for primary care quality. The selection of the analytic sample and patient characteristics are described in Figure 1 and Table 1, respectively. Procedures We obtained Institutional Review Board approval at each of the ten VA sites prior to the initiation of data collection. We implemented a modified 3-step version of the total design method for collecting the survey data (Dillman, 1991). The initial mailing included a cover letter describing the study, the anonymous questionnaire with directions, and a postage-paid return envelope. This initial packet was followed at week 1 by a reminder/thank you postcard and then at week 2 by a second mailing of the survey packet and postage-paid return envelope to all patients. Measures Independent variables: Provider, service, and clinic characteristics. We focused on 3 health care characteristics: 1) provider gender; 2) gynecologic care performed by provider; and 3) patient participation in a women’s clinic setting. In this manuscript, provider refers to a “regular provider or primary care provider at the

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VA.” Both the survey and directions page used this same language. Patients reported whether they had a regular provider (yes/no/do not know) and the provider gender (male/female). Each patient was also asked if she used her provider for routine gynecologic care (yes/no). Clinic setting (women’s clinic or traditional primary care clinic) was obtained from the VA National Patient Care Database, which stores outpatient clinic information. To examine the differential effect of the combinations of provider gender, provider service, and clinic setting on the outcome measures, all combinations of the three independent variables were stratified. Because of small cell sizes for 3 subgroups, patients with male providers who provided gynecologic care, patients with male providers not providing gynecologic care but enrolled in women’s clinic, and patients who had both male providers who gave gynecologic care and were also using women’s clinics were all combined. From the 8 possible combinations, 6 categories for the provider–service– clinic groups were created (see Table 1). Demographics and health. Demographic data included age, race (white versus all other categories), marital status (married versus all other categories), level of education (high school, technical training beyond high school or some college, and college graduate), household income for 1999 (ordinal levels of $10,000 were listed and later dichotomized to ⱕ$20,000 versus ⬎$20,000), and site. Perception of overall health status was determined by a single item question widely used as a health-related quality of life measure and anchored from poor to excellent (poor, fair, good, very good, or excellent; Ware, Kosinski & Keller, 1996). Dependent variable: Patient ratings of primary care. Patient perceptions of primary care were measured using the validated 19-item Components of Primary Care Index (CPCI) (Flocke, 1997). This tool has demonstrated that primary care ratings are associated with the receipt of more preventive services and with more person-focused provider interactions (Flocke, Stange & Goodwin, 1998; Flocke, Miller & Crabtree, 2002). The CPCI consists of 4 multi-item primary care domains that assess the patient–provider relationship, namely, patient preference for regular provider, interpersonal communication with provider, coordination of care, and accumulated knowledge. Patient preference for provider incorporates the primary care concepts of first contact and continuity (Starfield, 1992). Accumulated knowledge is the patient’s perception that the physician (or provider) knows her values and preferences about medical issues, clearly understands her health needs, and knows the family medical history. Also, the idea that the patient and physician had “been through a lot together” was considered a part of this attribute (Flocke, 1997). For the CPCI,

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Flocke evaluated internal consistency reliability for each domain and obtained acceptable values which ranged from 0.68 – 0.79 (Flocke, 1997). Responses were rated on a 6-point Likert scale from strongly disagree to strongly agree. Domain summary scores were calculated by adding the individual item ratings and dividing by the number of items completed in a domain. We adjusted summary scores for 1–2 missing items by reducing the denominator. No imputations for missing items occurred. Analysis First, we prepared descriptive statistics for each CPCI item including mean, median, standard deviation, and percent perfect (highest score) to look at the overall scoring trends in our sample (Table 2). Second, we compared patient characteristics along the 6 provider– service– clinic combinations to look for differences between the groups. For each patient, we calculated 4 summary scores corresponding to each primary care domain (outcome variable). To identify factors associated with best outcomes and to address the skew of the data toward higher ratings, domain summary scores were dichotomized into perfect scores (the highest summary score) versus all other ratings. In the domain of accumulated knowledge, the cut point was adjusted to include the 2 highest categories with ratings of 5 or 6 (nearly perfect score) to increase the frequency of responses available for a valid analysis. Nearly perfect scores account for a patient’s consistent choice of 5 in a rating system from 1 to 6 for each item in a domain. Next, we examined the relationship between the provider–service– clinic combinations and the primary care domain ratings using ␹2 techniques to look for differences between the groups. We used multiple logistic regression techniques to test for differences in primary care ratings while controlling for patient characteristics, perceived health status, and site. Each logistic regression model allowed comparisons of perfect versus less than perfect ratings for each primary care outcome. Each provider–service– clinic combination was compared to the referent group of women who used a male provider, did not receive gynecologic care from their provider, and did not attend women’s clinics. The covariates included age, race, marital status, education level, overall health status, and site. All results were considered significant if the associated p-value was ⬍ .05. Data analyses were performed using SPSS version 10 (SPSS Inc., Chicago, Ill.), and STATA, version 7 (STATA Corp., College Station, Tex, USA). Results Few differences in patient demographics occurred across the provider–service– clinic combinations. Women older than 65 were more likely to report seeing a provider (male or female) who did not cover gynecologic care

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Table 2. Item analysis of the components of primary care index (n ⫽ 1,080) Item Continuity (patient preference for provider) I go to this provider for almost all of my medical care. I want one provider to coordinate all of the health care that I receive. If I am sick, I would always contact a provider in this office first. My medical care improves when I see the same provider that I have seen before. It is very important to me to see my regular provider. I rarely see the same provider when I go for medical care. (R)† Overall perfect score on this scale Interpersonal communication I can easily talk about personal things with this provider. I don’t always feel comfortable asking questions of this provider. (R) This provider always explains things to my satisfaction. Sometimes this provider does not listen to me. (R) Overall perfect score on this scale Coordination of care This provider does not always know about the care I have received at other places. (R) This provider communicates with the other health providers I see. This provider knows the results of my visits to other doctors. This provider always follows up on a problem I’ve had, either at the next visit or by phone. Overall perfect score on this scale Accumulated knowledge The provider does not know my medical history very well. (R) This provider knows a lot about the rest of my family. This provider clearly understands my health needs. This provider and I have been through a lot together. How many years have you been a patient of this provider?‡ Overall nearly perfect score on this scale¶

Mean

Median

SD*

% Highest score

4.57 4.98 4.20 4.95

5.0 6.0 5.0 6.0

1.71 1.57 1.98 1.49

43.9 57.2 39.9 50.5

5.29 5.24

6.0 6.0

1.21 1.39

60.6 64.4 23.1

4.31 4.71 4.70 5.03

5.0 6.0 5.0 6.0

1.73 1.70 1.52 1.53

35.7 51.8 41.5 56.2 25.8

4.49

5.0

1.78

43.6

3.69 4.14 4.34

4.0 5.0 5.0

1.92 1.84 1.79

24.3 32.5 35.8 16.4

4.59 2.99 4.60 3.32 3.92

5.0 3.0 5.0 3.0 4.0

1.71 1.81 1.54 1.86 1.85

44.9 13.1 38.0 18.6 25.0 6.8

Note: Patient ratings range from 1 ⫽ strongly disagree to 6 ⫽ strongly agree. *Standard deviation. †(R) ⫽ Item reverse scored. 1 ⫽ strongly agree to 6 ⫽ strongly disagree. ‡Years were converted to categorical responses where 1 ⫽ 0 years to 6 ⫽ ⬎4 years as a patient of the provider. ¶ Nearly perfect scores include the percentage of patients with the 2 highest response categories for each item.

compared to younger women. These women were also less likely to be enrolled in a women’s clinic. Minority women were more likely to be enrolled in women’s clinics and to identify a female provider who gave gynecologic care. No difference among the provider– service– clinic combinations was evident by education, marital status, income, or perceived health status. (Data not shown.) Male providers who offer gynecologic services or who have patients enrolled in the women’s clinic were more likely to have perfect ratings for coordination (odds ratio [OR] 3.0, 95% confidence interval [CI] 1.2, 7.0) and borderline scores for continuity (OR 2.1, 95% CI 1.0, 4.4) compared to the referent group (male providers with no gynecologic services and no association with women’s clinic; Table 3). Female provider alone was significantly associated with perfect ratings in 2 domains: communication (OR 2.9, 95% CI 1.4, 5.8) and coordination (OR 3.7, 95% CI 1.5, 9.0). Patients of female providers who delivered gynecologic care more often reported perfect scores in 3 of 4 domains: continuity (OR 4.0, 95% CI 1.8, 8.7), communication (OR 2.7, 95% CI 1.3, 5.5), and

coordination (OR 2.8, 95% CI 1.1, 7.1). Finally, the combination of female provider, gynecologic services, and women’s clinic setting also showed significant, positive associations in 3 of 4 domains: continuity (OR 4.7, 95% CI 2.3, 9.6), communication (OR 2.7, 95% CI 1.4, 5.3), and accumulated knowledge (OR 6.1, 95% CI 1.3, 28.5). Coordination of care trended in the same direction for this group but was not statistically significant (OR 2.3, 95% CI 1.0, 5.5). Regarding the other covariates, middle and older age had significant positive associations with perfect ratings for continuity and coordination. In contrast, advanced education (college graduate status) was negatively associated with both continuity and coordination, and white race and poorer overall health were negatively associated with accumulated knowledge (see Table 3).

Discussion Similar to prior studies on patient–physician communication (Hall & Roter, 1998; Roter & Hall, 1998; Roter,

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Table 3. Contribution of provider–service– clinic setting to adjusted probability of a perfect score for each primary care domain Provider–service–clinic characteristics

Female PCP ⫹ GYN ⫹ WC* Female PCP ⫹ WC Female PCP ⫹ GYN Female PCP only Male PCP ⫹ GYN ⫹ and/ or WC Male PCP (referent group) Patient characteristics Age 40–64 Age ⱖ65 White race Married Income ⬎ $20,000 Some college College graduate Health status

Continuity (Patient Preference for Provider)

Communication

Coordination

Accumulated Knowledge

Adjusted OR

95% CI

Adjusted OR

95% CI

Adjusted OR

95% CI

Adjusted OR

95% CI

4.7 1.8 4.0 2.2 2.1

(2.3, 9.7) (0.7, 4.1) (1.8, 8.7) (0.9, 4.5) (1.0, 4.4)

2.7 1.8 2.7 2.9 1.3

(1.4, 5.3) (0.8, 4.0) (1.3, 5.5) (1.4, 5.8) (0.6, 2.6)

2.3 2.7 2.8 3.7 3.0

(1.0, 5.5) (1.0, 7.1) (1.1, 7.1) (1.5, 9.0) (1.2, 7.0)

6.1 4.0 4.6 3.8 2.6

(1.3, 28.5) (0.7, 22.5) (0.9, 22.8) (0.8, 19.2) (0.5, 13.0)

— — 2.7 2.7 1.1 0.8 1.4 0.7 0.6 1.1

— — (1.4, 5.0) (1.3, 5.1) (0.5, 2.1) (0.6, 1.2) (0.9, 2.1) (0.5, 1.1) (0.3, 0.9) (0.8, 1.7)

— — 1.7 1.5 1.4 0.9 1.0 0.7 0.7 1.3

— — (1.0, 2.8) (0.8, 2.6) (0.7, 2.7) (0.6, 1.3) (0.7, 1.5) (0.5, 1.0) (0.4, 1.1) (0.9, 1.9)

— — 2.8 3.1 1.3 1.0 0.9 0.8 0.5 1.0

— — (1.3, 6.0) (1.4, 6.9) (0.6, 2.8) (0.7, 1.6) (0.6, 1.5) (0.5, 1.2) (0.3, 0.9) (0.6, 1.5)

— — 1.5 1.4 0.3 1.1 0.9 1.1 1.0 0.3

— — (0.6, 3.7) (0.5, 3.8) (0.1, 0.9) (0.6, 2.0) (0.5, 1.8) (0.5, 2.0) (0.4, 2.3) (0.2, 0.7)

Note: Regression includes adjustment for age, race, marital status, income, education, overall health status, and all 10 VA sites. Abbreviations: PCP, primary care provider; GYN, gynecologic care by provider; WC, women’s clinic.

Hall & Aoki, 2002), this study indicates that provider gender correlates with higher scores on certain primary care domains such as interpersonal communication and coordination of care. However, unlike prior studies, our study identified 2 remarkable factors. First, obtaining gynecologic care or being involved with a women’s clinic setting improved the ratings of male providers. Second, providing gynecologic care improved the ratings of female providers above and beyond gender alone. For female providers, gender appeared as an independent predictor alone, but gynecologic care and gynecologic care combined with the women’s clinic setting show relationships with the breadth and magnitude of primary care ratings. Thus, gynecologic care appears influential for the ratings of both male and female providers. The women’s clinic setting adds to the ratings effect of female providers only when combined with gynecologic care. This finding suggests that primary care quality is a function of multiple factors related to providers and practices or, perhaps, convenience in obtaining those services (“one stop shopping”). For patients who had male providers, the women’s clinic association cannot be disentangled from the gynecologic service because they were merged for the analysis. Repeat examination of the raw data indicated that 111 of the 174 patients in this group (64%) had male providers and were associated with women’s clinics but received no gynecologic care from their regular provider. The remaining 63 patients received gynecologic care from their male provider. Owing to the small subgroups, we were not able to identify the individual effects of gynecologic care separate from women’s clinic setting for male providers. However, the data analysis and

findings remain important for understanding the influences on primary care ratings beyond the effect of provider gender. In contrast, the combination of female provider with patient enrollment in women’s clinics (but no gynecologic care) did not yield multiple positive, significant associations. Yet, when both gynecologic services by provider and enrollment in a women’s clinic were present, ratings of continuity, communication, and accumulated knowledge showed stronger associations, and coordination had a similar trend. Thus, clinic setting appears important when gynecologic care is managed by a female provider. Future studies need to examine the specific services by a provider or the organization of services within an outpatient setting to uncover the effects on quality ratings. Additionally, we found that middle and older age women placed great value on primary care goals such as continuity and coordination in the VA. Having comprehensive services available in primary care settings may be more important in this demographic age group when general medical and gynecologic services are routinely needed and fragmentation of care may easily occur. Limitations Several limitations arose in this study. First, generalizability is limited because our findings are only from women in the VA healthcare system. Second, nonrespondents could not be identified. Although nonrespondents may differ from respondents, we have no indication that the characteristics of nonrespondents in this sample would vary by gender of provider, services of provider, or clinic setting. Third, no infor-

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mation was collected on insurance status or health care use outside the VA. Veterans who use 2 or more systems of care may have different ratings of satisfaction (Borowsky & Cowper, 1999) and possibly other primary care measures. Recent data show that insurance status and changes in insurance influence primary care relationships, patient ratings, and the receipt of services (Henderson & Weisman, 2001; Safran et al., 2001). Last, we were unable to examine the effect of provider specialty (internist, family practitioner, gynecologist, or other) on the primary care ratings. Such items have been shown to have an effect on preventive services in primary care settings (Cassard et al., 1997).

Conclusions This study was able to capture the effect of provider gender, presence of routine gynecologic services from the provider and clinical setting in one study. It indicates that although gender may be a factor, it does not act alone or predict the highest primary care rating scores by female patients. The ratings are multifactorial in nature and not necessarily captured by methods we have previously utilized for surveying patients. Our methods addressed the recognized limitations of the prior studies and, therefore, had no overlapping providers between sites, covered multiple sites across a regional area (including academic and nonacademic affiliated VA settings), and included both genderspecific and traditional primary care settings. Other than 1 exception, we kept to our intended methods to analyze the data based on the best outcome (highest score) and not use lower values for determining the effect of the independent variables. We believe that this reinforces the validity of our findings. We additionally ran regression models for “nearly perfect ratings” versus all other ratings for each primary care domain, and our overall results did not change. Thus, our attentiveness to associations with the perfect score did not skew or cloak the findings in our population. We recognize that the pursuit of perfection in primary care may not be clinically practical; however, the understanding of what determines the best patient primary care ratings is both practical and necessary. This study points out that primary care providers who offer a broader scope of services to women obtain higher ratings of primary care. Specifically, male and female providers achieve higher ratings when they offer more comprehensive services to women patients. Thus, primary care providers should consider expanding their scope of services to include routine gynecologic care or consider being aligned with a clinical center or setting that offers these additional services (through either primary care or specialty care). Further research and evaluations need to explore how

provider or clinic scope of services affects primary care quality and satisfaction. Such information is valuable because these factors or resultant patient ratings may influence health system decisions to support certain provider–service– clinic setting combinations that provide comprehensive patient care.

Acknowledgements This work was presented in part at the 25th Annual Meeting of the Society of General Internal Medicine, Atlanta, Georgia, May 2002, and the 11th Annual Congress on Women’s Health, Hilton Head Island, South Carolina, June 2003.We gratefully acknowledge the work of Mary Kelley and Melissa Skanderson for their assistance with VA administrative data. We thank Nancy Graves for her dedication to survey collection and database management. We also appreciate the vigilant attention that Kathy Brickett and Nichole Bayliss provided for our manuscript preparation.

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