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37The Permanente Journal/ Summer 2012/ Volume 16 No. 3

ORIGINAL RESEARCH & CONTRIBUTIONS

Introduction Data from the memberships of inte-

grated health care organizations offer several advantages for health researchers, including large samples and availability of electronic health records (EHR) that pro- vide diagnostic codes, pharmacy records, vaccination records, and membership char- acteristics.1-9 In some cases, these data may be augmented by comprehensive inpatient and outpatient progress notes, radiologic images, and reports.10-12 These features facilitate researchers in performing stud- ies of health disparities, long-term patient outcomes, and comparative effectiveness in a timely and cost-efficient manner.

Most US health plan members, however, receive health insurance through the em- ployer of at least one family member. This covered individual may be healthier and may have other advantages, such as more years of education than the general popu- lation, thus raising concern that findings from studies performed in integrated health care settings may not be generalizable to younger or disadvantaged portions of the US population. Furthermore, because low socioeconomic status may be associated with poor health outcomes,13-15 a healthy worker effect may bias findings from stud- ies in these settings by underestimating the magnitude of the effect of important

predictors for poor health outcomes that are also associated with low socioeco- nomic status or by failing to identify such predictors in entirety.

The purpose of this study was to com- pare the sociodemographic characteristics of the members of a large integrated health care organization, Kaiser Permanente Southern California (KPSC), with the cen- sus population of the Southern California coverage area.

Methods Setting and Design

An integrated health care system, KPSC provides comprehensive health care for more than 3.4 million of the 23 million residents of Southern California. Members receive medical care in 14 hospitals and more than 197 medical offices in 10 coun- ties of Southern California: Imperial, Kern, Los Angeles, Orange, Riverside, San Ber- nardino, San Diego, San Luis Obispo, Santa Barbara, and Ventura. Medical information is captured in complete EHR that include all inpatient and outpatient progress notes; pharmacy records; radiology reports and images; and membership characteristics, including race/ethnicity and language preference, both written and spoken. Mem- bers can obtain KPSC insurance coverage through employer-based plans, individual plans, and Medicare or state-subsidized health care for the indigent.

For this study, we identified all individ- uals who were members of KPSC at any time in the years 2000 and 2010. Sociode- mographic information was collected at the time of Health Plan enrollment, and

Corinna Koebnick, PhD, MS, is a Research Scientist for Kaiser Permanente Research and Evaluation in Pasadena, CA. E-mail: corinna. [email protected]. Annette M Langer-Gould, MD, PhD, MS, is a Research Scientist for Kaiser Permanente Research and Evaluation in

Pasadena, CA. E-mail: [email protected]. Michael K Gould, MD, MS, is a Research Scientist for Kaiser Permanente Research and Evaluation in Pasadena, CA. E-mail: [email protected]. Chun R Chao, PhD, MS, is a Research Scientist for Kaiser Permanente

Research and Evaluation in Pasadena, CA. E-mail: [email protected]. Rajan L Iyer, MPH, is a Research Associate for Kaiser Permanente Research and Evaluation in Pasadena, CA. E-mail: [email protected]. Ning Smith, PhD, is a Biostatistician for Kaiser Permanente Research

and Evaluation in Pasadena, CA. E-mail: [email protected]. Wansu Chen, MS, is the Group Leader of Biostatistics, Programming & Database Development for Kaiser Permanente Research and Evaluation in Pasadena, CA. E-mail: [email protected]. Steven J Jacobsen,

MD, PhD, is the Director of Research for Kaiser Permanente Research and Evaluation in Pasadena, CA. E-mail: [email protected].

Sociodemographic Characteristics of Members of a Large, Integrated Health Care System: Comparison with US Census Bureau Data Corinna Koebnick, PhD, MS; Annette M Langer-Gould, MD, PhD, MS; Michael K Gould, MD, MS; Perm J 2012 Summer;16(3):37-41 Chun R Chao, PhD, MS; Rajan L Iyer, MPH; Ning Smith, PhD; Wansu Chen, MS; Steven J Jacobsen, MD, PhD

Abstract Background: Data from the memberships of large, integrated health care systems can

be valuable for clinical, epidemiologic, and health services research, but a potential selection bias may threaten the inference to the population of interest.

Methods: We reviewed administrative records of members of Kaiser Permanente Southern California (KPSC) in 2000 and 2010, and we compared their sociodemographic characteristics with those of the underlying population in the coverage area on the basis of US Census Bureau data.

Results: We identified 3,328,579 KPSC members in 2000 and 3,357,959 KPSC mem- bers in 2010, representing approximately 16% of the population in the coverage area. The distribution of sex and age of KPSC members appeared to be similar to the census reference population in 2000 and 2010 except with a slightly higher proportion of 40 to 64 year olds. The proportion of Hispanics/Latinos was comparable between KPSC and the census refer- ence population (37.5% vs 38.2%, respectively, in 2000 and 45.2% vs 43.3% in 2010). However, KPSC members included more blacks (14.9% vs 7.0% in 2000 and 10.8% vs 6.5% in 2010). Neighborhood educational levels and neighborhood household incomes were generally similar between KPSC members and the census reference population, but with a marginal underrepresentation of individuals with extremely low income and high education.

Conclusions: The membership of KPSC reflects the socioeconomic diversity of the Southern California census population, suggesting that findings from this setting may provide valid inference for clinical, epidemiologic, and health services research.

38 The Permanente Journal/ Summer 2012/ Volume 16 No. 3

ORIGINAL RESEARCH & CONTRIBUTIONS Sociodemographic Characteristics of Members of a Large, Integrated Health Care System: Comparison with US Census Bureau Data

missing or incorrect information may have been updated during inpatient and outpatient medical visits. The institutional review board of KPSC reviewed and ap- proved the study protocol.

Race and Ethnicity We categorized race as white, black,

American Indian/Alaskan Native, Asian/ Pacific Islander, multiple races, and other

races. Ethnicity was classified as Hispanic or non-Hispanic. Race and ethnicity infor- mation for KPSC members was extracted from administrative records, a method previously validated against birth certifi- cate information.16

Socioeconomic Status As indicators of socioeconomic status,

we used three different measures: neigh-

borhood education, neighborhood income, and participation in Medi-Cal (Medicaid) or other state-subsidized health care coverage programs. Neighborhood education and neighborhood income were estimated on the basis of the linkage of Health Plan members’ addresses via geocoding (Geospatial Entity Object Coding) with US Census block data.17

Reference Populations The reference populations included all

residents of the 10 counties of Southern California who were included in the 2000 and 2010 censuses. Information about the Southern California census populations was retrieved from the US Census Bureau files using the full data set through the Web-based query portal (www.census. gov). Census information on sex, race, ethnicity, education, household income, households with income below the pov- erty level, and public assistance income were extracted from demographic profile summary files. To match Health Plan administrative records, we collapsed the available race categories from the census questionnaire to the following categories: white, black, American Indian/Alaskan Native, Asian/Pacific Islander, multiple races, and other race.

Statistical Analysis We report descriptive statistics for vari-

ables of interest in the KPSC population and the Southern California reference population. We report similar descriptive statistics stratified by age group only for the year 2000, because these data were not available for the census population in 2010. We did not perform formal statistical tests to identify differences between the two populations. Because of the large popula- tion size, even small —but not necessarily relevant—differences between populations would result in a significant test result.

Results Members of KPSC in 2000 and 2010

represented approximately 16.1% of the census reference population in the KPSC coverage area (Table 1). The overall distribution of gender and age of KPSC members appeared to be similar to the census reference population in 2000 and 2010, with the exception that the 40- to 64-year-old age group was marginally

Table 1. Demographic characteristicsa

2000 2010 Demographic characteristic Census KPSC Census KPSC Total population (N) 20,637,512 3,328,579 22,680,010 3,657,959 Sex

Male 49.8 48.9 49.7 48.4 Female 50.2 51.1 50.3 51.6

Age group, years 0 to 9 16.0 15.3 13.6 12.9 10 to 14 7.8 8.0 7.2 7.5 15 to 19 7.3 7.5 7.9 8.1 20 to 39 31.1 29.1 29.1 26.2 40 to 64 27.6 30.8 31.3 34.1 ≥65 10.9 9.2 10.9 11.2

Raceb

Non-Hispanic white 42.3 46.3 36.4 34.0 Hispanic white 15.3 22.7 20.5 36.9 Black 7.0 14.9 6.5 10.8 American Indian/Alaska Native 0.9 0.2 0.9 0.3 Asian/Pacific Islander 9.9 8.6 11.8 10.1 Other races 19.9 7.1 19.3 7.5 Multiple races 4.7 0.3 4.6 0.4

Hispanic or Latinob 38.2 37.5 43.3 45.2 Neighborhood educationc

Less than high school 25.8 25.2 21.3 21.4 High school graduate 20.0 20.9 20.9 23.0 Some college or associate degree 29.5 30.6 29.1 29.9 Bachelor’s degree 16.0 15.2 18.5 17.0 Graduate or professional degree 8.7 7.9 10.1 8.7

Neighborhood household incomec

<$10,000 8.8 8.1 6.1 5.9 $10,000 to $14,999 5.9 5.6 5.3 3.4 $15,000 to $24,999 12.1 11.8 10.3 8.4 $25,000 to $34,999 11.9 11.9 9.5 9.1 $35,000 to $49,999 15.4 15.9 13.4 13.2 $50,000 to $74,999 19.0 20.3 17.7 19.0 $75,000 to $99,999 11.1 11.8 12.4 14.4 $100,000 to $149,999 9.6 9.6 14.0 15.4 ≥$150,000 6.1 5.0 11.2 11.2

a Data are percentages of subjects unless otherwise indicated. Some data do not total to 100% because of rounding. b For KPSC, information about race and ethnicity was based on administrative records among those with known race ethnicity (members with unknown race: 43.7% in 2000 and 24.9% in 2010). c Neighborhood income and education are not reported income and education but are estimated on the basis of members’ addresses using neighborhood income and education from US Census tract information. KPSC = Kaiser Permanente Southern California.

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ORIGINAL RESEARCH & CONTRIBUTIONS Sociodemographic Characteristics of Members of a Large, Integrated Health Care System: Comparison with US Census Bureau Data

overrepresented among KPSC members (30.8% vs 27.6% in 2000 and 34.1% vs 31.3% in 2010; Table 1).

The proportion of Hispanics/Latinos was comparable between KPSC and the census reference population in 2000 (37.5% vs 38.2%) and 2010 (45.2% vs 43.3%). However, KPSC members included more blacks in both 2000 and 2010 (14.9% vs 7.0% in 2000 and 10.8% vs 6.5% in 2010). Non-Hispanic whites were slightly over- represented among KPSC members in 2000, but in 2010 this group was somewhat underrepresented (46.3% vs 42.3% in 2000 and 34.0% vs 36.4% in 2010).

Whereas the KPSC membership and the census reference population had similar proportions of Hispanics in both 2000 and 2010, the census population included fewer self-reported Hispanic whites and more individuals who classified them- selves as “other race” in these years.

Neighborhood educational level and neighborhood household income were generally similar between KPSC members and the census reference population (Table 1). However, slightly fewer KPSC members in 2010 resided in neighbor- hoods with household incomes below $25,000 (17.7% vs 21.6%, respectively), or in neighborhoods with a higher percent- age of college graduates (25.7% vs 28.6%).

Approximately 1.7% of KPSC mem- bers received services paid by Medi-Cal, California’s state-subsidized health care program (Figure 1). The proportion of

KPSC members who received health care coverage by Medi-Cal and other state- subsidized programs increased from 0.7% to 1.6% among adults and from 4.4% to 16.1% among youths between 2000 and 2010. In the coverage area of Southern California, an estimated 11.6% had an income below the poverty level, and 5.1% received public assistance in 2000, whereas in 2010 an estimated 16.2% had an income below the poverty level and 4.0% received public assistance.

Members of KPSC between 0 and 19 years of age were generally similar

in demographic characteristics to the census reference population in 2000a

(Table 2). Members of KPSC represented 15.2% of 0 to 9 year olds, 16.5% of 10 to 14 year olds, and 16.5% of 15 to 19 year olds in the Southern California coverage area. Differences in racial/ ethnic groups between KPSC youth and Southern California census youth were similar to the differences observed in the overall populations of all ages, although the higher proportion of blacks seen in KPSC was even more pronounced among 10 to 19 year olds.

Figure 1. Proportion of Kaiser Permanente Southern California (KPSC) members who receive health care coverage by Medi-Cal (Medicaid) and other state-subsidized programs, by age group.

Adults were defined as 18 years of age or older, and children were defined as younger than 18 years of age. (Cut off age determined by Medicaid/Medi-Cal eligibility.)

Table 2. Demographic characteristics of youth in 2000, by age group 0 to 9 years 10 to 14 years 15 to 19 years

Demographic characteristic KPSC Census KPSC Census KPSC Census Total population (N) 510,477 3,310,416 267,431 1,596,627 248,709 1,514,947 Sex (%)

Male 51.0 51.2 50.8 51.2 50.7 51.7 Female 48.0 48.8 49.2 48.8 49.3 48.3

Race (%)a

Non-Hispanic white 28.0 28.6 27.5 32.8 36.4 33.2 Hispanic white 42.0 20.7 37.0 18.1 34.3 17.0 Black 13.0 7.5 19.0 8.4 18.9 7.8 American Indian/Alaska Native 0.2 1.0 0.2 1.1 0.3 1.1 Asian/Pacific Islander 7.4 7.4 6.9 8.6 7.0 9.9 Other races 9.0 27.5 8.9 24.9 8.2 25.5 Multiple races 0.4 7.3 0.5 6.3 0.6 5.7

Hispanic or Latino (%) 50.4 53.1 47.2 47.2 43.2 46.2 a Some data do not total to 100% because of rounding. KPSC = Kaiser Permanente Southern California.

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ORIGINAL RESEARCH & CONTRIBUTIONS Sociodemographic Characteristics of Members of a Large, Integrated Health Care System: Comparison with US Census Bureau Data

Adult KPSC members were generally similar to the census reference popula- tion in 2000 (Table 3). Members of KPSC represented 15.1% of 20 to 39 year olds,

19.9% of 40 to 64 year olds, and 14.6% of people aged 65 years and older in the Southern Cali- fornia coverage area. Differences in racial/ethnic groups between KPSC adults and Southern Cali- fornia census adults were similar to the differences observed in the overall populations of all ages, although in both KPSC and census reference populations the proportion of Hispanics was significantly lower in adults 40 years and older.

Discussion The main finding of this study is that

the KPSC population appeared to be similar to the Southern California census reference population in 2000 and 2010. All ages and all racial/ethnic and socio- economic groups were represented in the KPSC population. Adults aged 40 to 64 years, who likely represent a stable work- ing population, were only marginally over- represented among KPSC members, and the extremely poor and highly educated were only marginally underrepresented among KPSC members in 2010. In general, there were no grossly apparent differences in education or income level between KPSC and the reference population, as would be expected with a healthy insured

effect or healthy worker bias. The similar proportions of low-income individuals in KPSC and the reference population likely reflect the large number of Medi-Cal re- cipients who are KPSC members. Despite small differences in the proportion of demographic groups, we demonstrated large numbers of KPSC members in all subgroups across the spectrum of age, race and ethnicity, and socioeconomic groups, including a large number of indi- viduals under the poverty threshold and enrolled in subsidized programs to cover health insurance. Our findings suggest that results from studies conducted in the KPSC population may be generalizable to the Southern California population.

The healthy worker bias is an example of a selection bias that can lead to an underestimation of morbidity because of a better health status of the workforce compared with the general population (which also includes people who are too sick to work). Comparably, an insured population may be healthier than the general population because health insur- ance is often employer sponsored. On the other hand, about 83% of individuals in California had health insurance coverage in 2009.18 Managed care organizations pro- vide care for a wide range of individuals receiving care through different channels, including employer-based care, family members, and programs subsidized by the state. This diversity makes healthy worker bias and gross differences in socioeconomic characteristics between

the insured and the underlying population less likely to occur.

Although we did not find strong evi- dence for a healthy worker bias, we can- not exclude the possibility of a mixture of healthy insured effect through attractive KP benefit plans masked by an over- representation of members with chronic illnesses because competitor plans are more expensive or do not cover expen- sive drug costs. If a strong healthy worker bias were present, one would expect an overrepresentation of the stable work- ing population manifested by more men aged 40 to 65 years, and with a higher socioeconomic status compared with the geographic reference population.

Beyond healthy worker bias, health insurance benefit structures also influence the health of its members by discourag- ing chronically ill members through caps, high copays, and/or deductibles, and by attracting the healthiest of the healthy by offering very low premiums. However, it is possible that competitor plans, by offering high copays for medications and restricting access to specialists, for instance, are more expensive than KPSC and less convenient for those with chronic illnesses. It is not possible to determine how such factors influence the health of the KPSC membership by examining demographic characteristics alone.

On a national level, our findings indicate that the KPSC population may be particularly useful for examining the comparative effectiveness of interven-

Table 3. Demographic characteristics of adults in 2000, by age group 20 to 39 years 40 to 64 years ≥65 years

Demographic characteristic KPSC Census KPSC Census KPSC Census Total population (N) 969,395 6,403,335 1,024,723 5,708,965 307,844 2,103,222 Sex (%)

Male 48.6 51.5 48.1 49.0 46.0 42.0 Female 51.4 48.5 51.9 51.0 54.0 58.0

Race (%)a

Non-Hispanic white 35.7 36.2 48.4 52.8 67.9 67.9 Hispanic white 32.4 16.6 20.6 11.6 12.0 9.3 Black or African American 14.6 6.9 14.7 7.0 11.2 5.5 American Indian/Alaska Native 0.3 1.0 0.2 0.8 0.1 0.5 Asian/Pacific Islander 8.8 10.5 9.7 11.4 6.1 9.1 Other races 7.8 24.1 6.4 13.1 2.6 5.6 Multiple races 0.5 4.7 0.1 3.3 0.1 2.2

Hispanic or Latino (%) 48.0 44.0 29.8 26.6 15.0 15.8 a Some data do not total to 100% because of rounding. KPSC = Kaiser Permanente Southern California.

… the KPSC population may be particularly

useful for examining the comparative

effectiveness of interventions

across sociodemographic

subgroups.

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ORIGINAL RESEARCH & CONTRIBUTIONS Sociodemographic Characteristics of Members of a Large, Integrated Health Care System: Comparison with US Census Bureau Data

tions across sociodemographic subgroups. The diversity and large number of KPSC members make it possible to conduct subgroup analyses aimed at identifying sources of heterogeneity on the basis of demographic factors and estimating risks within such subgroups. In this way, studies conducted in KPSC could help to accomplish this important objective of comparative effectiveness research.19 Risk estimates generated from such subgroups and general trends are likely to be general- izable in most instances. However, findings from such studies, particularly absolute rates, may not always be generalizable on a national level. On the other hand, the spectrum of illness and conditions seen in this setting are more likely to mirror the general population than studies conducted in tertiary care centers or referral clinics.

Health disparities have previously been attributed to the lack of health insur- ance.20 The ethnic and racial diversity of the KPSC population and the large size of these racial and ethnic groups make KPSC an ideal setting to investigate health disparities that persist despite equal ac- cess to care.

Limitations of these data include the well-known limitations of the US Census, including undercounting certain minority groups and misclassification of Hispanic whites as “other.” Another issue is miss- ing race and ethnicity information among KPSC members, particularly in 2000. We cannot exclude that differences in the proportion of missing values may partially explain the observed differences between KPSC members in 2000 and 2010 or dif- ferences between KPSC members and the census population. This may be especially true for the higher proportion of blacks among KP members. Previous research investigating the quality of race and ethnicity information in KPSC children has shown that missing race is mostly at random with the exception of black chil- dren, who have a slightly higher chance of having race information in their EHRs.16

Another potential limitation is the reliance on geocoding to obtain a KPSC member’s neighborhood education and income instead of self-reported education and income. Neighborhood education and income may or may not exactly reflect an individual’s education or income living in that neighborhood. However, it will

accurately reflect the distribution of the population when used for studies that include very large populations, as seen here. In addition, we were unable to compare education, income, and demo- graphics by age group strata with the 2010 US Census because these data are not available. Finally, because our goal was to evaluate overall comparability, we did not perform formal statistical tests to identify differences between the two populations. Given the very large samples, we would expect that differences between groups would be highly significant even when trivial in magnitude or importance.

Strengths of the KPSC population in- clude its similarity to the geographic refer- ence population from which it is drawn, resulting in relatively large Hispanic, black, and Asian populations among children and adults.

In conclusion, the diversity of the KPSC membership along with the comprehen- sive medical records make this an ideal population to address clinical, epidemio- logic, and health services-related ques- tions where race or ethnicity, age, and all but the extreme ends of the income spectrum play key roles. v

a Cut off for Eligibility for Medicaid/Medi-Cal is age 18 years (as seen in Figure 1); census data, how- ever, came from aggregated tables using age 19 years as the cut off. To have comparable groups, age 19 was used for our characteristics data.

Disclosure Statement The author(s) have no conflicts of interest

to disclose.

Acknowledgments This research was supported by Kaiser

Permanente Direct Community Benefit Funds. Kathleen Louden, ELS, of Louden Health

Communications provided editorial assistance.

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