Health Services Research © Health Research and Educational Trust DOI: 10.1111/1475-6773.12178 RESEARCH ARTICLE
Health Care Utilization and Receipt of Preventive Care for Patients Seen at Federally Funded Health Centers Compared to Other Sites of Primary Care Neda Laiteerapong, James Kirby, Yue Gao, Tzy-Chyi Yu, Ravi Sharma, Robert Nocon, Sang Mee Lee, Marshall H. Chin, Aviva G. Nathan, Quyen Ngo-Metzger, and Elbert S. Huang Objective. To compare utilization and preventive care receipt among patients of federal Section 330 health centers (HCs) versus patients of other settings. Data Sources. A nationally representative sample of adults from the Medical Expenditure Panel Survey (2004–2008). Study Design. HC patients were defined as those with ≥50 percent of outpatient visits at HCs in the first panel year. Outcomes included utilization and preventive care receipt from the second panel year. We used negative binomial and logistic regression models with propensity score adjustment for confounding differences between HC and non-HC patients. Principal Findings. Compared to non-HC patients, HC patients had fewer office visits (adjusted incidence rate ratio [aIRR], 0.63) and hospitalizations (aIRR, 0.43) (both p < .001). HC patients were more likely to receive breast cancer screening than nonHC patients (adjusted odds ratio [aOR] 2.78, p < .01). In subgroup analyses, uninsured HC patients had fewer outpatient and emergency room visits and were more likely to receive dietary advice and breast cancer screening compared to non-HC patients. Conclusions. Health centers add value to the health care system by providing socially and medically disadvantaged patients with care that results in lower utilization and maintained or improved preventive care. Key Words. Safety net, preventive care, utilization
Health centers (HCs) funded by Section 330 of the Public Health Service Act cared for approximately 21.1 million people in 2012. This program is dedicated to providing comprehensive primary care to medically vulnerable populations. The number of patients cared for at HCs is expected to grow 1498
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considerably due to increases in program funding and the expansion of the insured population, resulting from implementation of the Affordable Care Act. It is important to understand what additional value HCs provide to the health care system beyond the care provided by other primary care sites. HCs provide comprehensive primary care to patients, regardless of their ability to pay for care. Comprehensive primary care includes a unique array of enabling services (e.g., case management, translation, and transportation) and may include selected dental, behavioral health, pharmacy, and other services not typically available in primary care settings (Shi et al. 2010). HCs must be located in or serve medically underserved areas/populations, which are areas having too few primary care providers, high infant mortality, high poverty, and/or a large elderly population. Previous studies examining the impact of HCs on health care utilization have produced mixed results. Some studies have suggested that receipt of primary care at HCs decreases emergency room (ER) visits (Smith-Campbell 2005; Rust et al. 2009) and hospitalizations (Epstein 2001; Probst, Laditka, and Laditka 2009; Rothkopf et al. 2011). Among Medicaid beneficiaries, the benefit of primary care at HCs has been associated with fewer hospitalizations and ER visits for ambulatory care–sensitive conditions (Falik et al. 2001, 2006). However, other studies have found that primary care at HCs was associated with no difference in preventable hospitalizations (Gurewich et al. 2011), and at worst, increased ER visits compared to other primary care sites (Scherer and Lewis 2010). The disparate results are likely because previous studies have evaluated different populations and used various data sources. Further, while inpatient and ER visits have been extensively examined, the study of the effects of HCs on overall outpatient health care utilization has been limited. Studies on the quality of care at HCs have been generally positive (Starfield et al. 1994; Falik et al. 2001, 2006; Porterfield and Kinsinger 2002; Regan et al. 2003; Hicks et al. 2006; Shi and Stevens 2007; Goldman et al. Address correspondence to Neda Laiteerapong, M.D., M.S., University of Chicago, 5841 S. Maryland Ave., MC 2007, Chicago, IL 60637; e-mail: [email protected]. James Kirby, Ph.D., and Quyen Ngo-Metzger, M.D., M.P.H., are with the Agency for Healthcare Research and Quality, Rockville, MD. Yue Gao, M.P.H., Robert Nocon, M.H.S., Sang Mee Lee, Ph.D., Marshall H. Chin, M.D., M.P.H., Aviva G. Nathan, M.P.H., and Elbert S. Huang, M.D., M.P.H., are also with the Department of Medicine and Section of General Internal Medicine, University of Chicago, Chicago, IL. Tzy-Chyi Yu, M.H.A., Ph.D., is with the NORC at the University of Chicago, Parsippany, NJ. Ravi Sharma, Ph.D., is with the Bureau of Primary Health Care, Health Resources and Services Administration, US Department of Health and Human Services, Rockville, MD.
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2012). In the outpatient setting, HCs have performed better on some, but not all, measures of quality compared to other primary care providers (Porterfield and Kinsinger 2002; Regan et al. 2003; Hicks et al. 2006; Shi and Stevens 2007; Goldman et al. 2012). Studying the effects of HCs on utilization and quality of care has unique challenges. First, few nationally representative datasets of health care providers provide accurate identification of HCs, which leads to inaccurate identification of HC patients. Data on providers reported by patients may be inaccurate, as patients may not know if their primary care clinic is a federally funded HC or another type of community health center. Second, due to the HC mission, HC patients are more likely to be racial/ethnic minorities, uninsured or Medicaid enrollees, and have higher rates of chronic disease (Forrest and Whelan 2000; Shi et al. 2010). These important differences may be a source of confounding if not accounted for in analyses. Third, HCs are intentionally located in federally designated medically underserved areas. Thus, HC patients may be located in different geographic locations than other primary care patients and have different access to health care resources. These differences in location, which may affect utilization, have not been accounted for in previous analyses. Previous studies on HCs have left uncertainty about the effects of this safety net program on health care utilization and quality of care. We hypothesized that patients receiving care at HCs would have no difference in outpatient visits, but fewer emergency room visits and hospitalizations, and similar or better quality of care compared to similar patients receiving care at other sites. In this study, we have addressed some limitations of past work by address-matching federally funded HCs to provider addresses, including less readily available variables in adjustment for selection (e.g., quality of life), using advanced methods of adjustment (propensity scores), and adjusting for differences in patient proximity to HCs.
M ETHODS We used five panels from the Medical Expenditure Panel Survey (MEPS) (2004–2008) (N = 79,041), which is a nationally representative household survey of the noninstitutionalized civilian population performed by the Agency for Healthcare Research and Quality (AHRQ). MEPS is a 2-year panel survey and collects data in five household interviews. We also used Health Resources and Services Administration Bureau of Primary Health Care (BPHC)
Utilization and Quality for Health Center vs. Non–Health Center Patients
1501
Uniform Data System and BPHC Management Information System databases. These administrative databases include addresses of all Section 330 HCs and affiliated sites from 2004 to 2008. This project was approved by institutional review boards at the University of Chicago and NORC at the University of Chicago. We studied adults, aged ≥18 years, with ≥1 clinic (office or hospitalbased) visit in their first panel year, and who lived ≤20 miles of an HC (n = 33,137). We used data from the first panel year to identify participants to study how the site of care may affect future health care utilization. In MEPS, participants are queried at each interview whether their household used health care services and the address of each provider (Richard et al. 2012). To accurately identify visits at HCs, we compared provider addresses in MEPS to HC addresses in BPHC databases. Congruent with previous studies, we considered participants to be HC patients if the majority (≥50 percent) of their clinic visits were at HCs (Falik et al. 2001; Gurewich et al. 2012); other participants were considered non-HC patients. Because patients tend to live near their site of health care, and differences in proximity may affect their utilization of their health care site (Hadley and Cunningham 2004; Gresenz, Rogowski, and Escarce 2007), we restricted the sample to participants living ≤20 miles of an HC. Details on how this distance was calculated are available in the onlineonly supplement (Data S1). We included the MEPS year-end summary data from the first panel year on sociodemographics, health behaviors, comorbid illnesses, quality of life (Ware, Kosinski, and Keller 1996), depressed symptoms (Gilbody et al. 2007), and household geography (see Table 1 for complete variable list). We constructed variables to describe each participant’s type(s) of insurance (Medicare, Medicaid, private, Medicaid HMO, private HMO) and whether they held that insurance for the full year, part of the year, or not at all. Participants who had no health insurance for the entire first panel year were considered uninsured. We also counted the number of functional limitations with which participants reported having some difficulty (lifting 10 pounds, walking up 10 steps, walking three blocks, walking a mile, standing 20 minutes, bending/ stooping, reaching overhead, using fingers to grasp). In addition, we used U.S. Census zip code data from 2007 to 2009 on the poverty rate and proportion of minority race and Hispanics. Lastly, we included the 2006 county-level urban–rural classification from the National Center of Health Statistics. The outcomes of interest were patient-reported health care utilization and preventive care in the second panel year. Health care utilization was defined by total office visits, hospital-based outpatient visits, prescriptions
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Table 1: Adult Participants Living within Twenty Miles of a Health Center Receiving Outpatient Care in the First Panel Year (N = 33,137)
Demographics Age, years, mean (SE) Female, n (%) Marital status, n (%) Married Widowed Divorced Separated Never married Race/ethnicity, n (%) White Black Hispanic American Indian/Alaskan Native Asian Hawaiian/Pacific Islander Other Education, years, mean (SE) Percent federal poverty line, n (%)
Health Care Utilization and Receipt of Preventive Care for Patients Seen at Federally Funded Health Centers Compared to Other Sites of Primary Care Neda Laiteerapong, James Kirby, Yue Gao, Tzy-Chyi Yu, Ravi Sharma, Robert Nocon, Sang Mee Lee, Marshall H. Chin, Aviva G. Nathan, Quyen Ngo-Metzger, and Elbert S. Huang Objective. To compare utilization and preventive care receipt among patients of federal Section 330 health centers (HCs) versus patients of other settings. Data Sources. A nationally representative sample of adults from the Medical Expenditure Panel Survey (2004–2008). Study Design. HC patients were defined as those with ≥50 percent of outpatient visits at HCs in the first panel year. Outcomes included utilization and preventive care receipt from the second panel year. We used negative binomial and logistic regression models with propensity score adjustment for confounding differences between HC and non-HC patients. Principal Findings. Compared to non-HC patients, HC patients had fewer office visits (adjusted incidence rate ratio [aIRR], 0.63) and hospitalizations (aIRR, 0.43) (both p < .001). HC patients were more likely to receive breast cancer screening than nonHC patients (adjusted odds ratio [aOR] 2.78, p < .01). In subgroup analyses, uninsured HC patients had fewer outpatient and emergency room visits and were more likely to receive dietary advice and breast cancer screening compared to non-HC patients. Conclusions. Health centers add value to the health care system by providing socially and medically disadvantaged patients with care that results in lower utilization and maintained or improved preventive care. Key Words. Safety net, preventive care, utilization
Health centers (HCs) funded by Section 330 of the Public Health Service Act cared for approximately 21.1 million people in 2012. This program is dedicated to providing comprehensive primary care to medically vulnerable populations. The number of patients cared for at HCs is expected to grow 1498
Utilization and Quality for Health Center vs. Non–Health Center Patients
1499
considerably due to increases in program funding and the expansion of the insured population, resulting from implementation of the Affordable Care Act. It is important to understand what additional value HCs provide to the health care system beyond the care provided by other primary care sites. HCs provide comprehensive primary care to patients, regardless of their ability to pay for care. Comprehensive primary care includes a unique array of enabling services (e.g., case management, translation, and transportation) and may include selected dental, behavioral health, pharmacy, and other services not typically available in primary care settings (Shi et al. 2010). HCs must be located in or serve medically underserved areas/populations, which are areas having too few primary care providers, high infant mortality, high poverty, and/or a large elderly population. Previous studies examining the impact of HCs on health care utilization have produced mixed results. Some studies have suggested that receipt of primary care at HCs decreases emergency room (ER) visits (Smith-Campbell 2005; Rust et al. 2009) and hospitalizations (Epstein 2001; Probst, Laditka, and Laditka 2009; Rothkopf et al. 2011). Among Medicaid beneficiaries, the benefit of primary care at HCs has been associated with fewer hospitalizations and ER visits for ambulatory care–sensitive conditions (Falik et al. 2001, 2006). However, other studies have found that primary care at HCs was associated with no difference in preventable hospitalizations (Gurewich et al. 2011), and at worst, increased ER visits compared to other primary care sites (Scherer and Lewis 2010). The disparate results are likely because previous studies have evaluated different populations and used various data sources. Further, while inpatient and ER visits have been extensively examined, the study of the effects of HCs on overall outpatient health care utilization has been limited. Studies on the quality of care at HCs have been generally positive (Starfield et al. 1994; Falik et al. 2001, 2006; Porterfield and Kinsinger 2002; Regan et al. 2003; Hicks et al. 2006; Shi and Stevens 2007; Goldman et al. Address correspondence to Neda Laiteerapong, M.D., M.S., University of Chicago, 5841 S. Maryland Ave., MC 2007, Chicago, IL 60637; e-mail: [email protected]. James Kirby, Ph.D., and Quyen Ngo-Metzger, M.D., M.P.H., are with the Agency for Healthcare Research and Quality, Rockville, MD. Yue Gao, M.P.H., Robert Nocon, M.H.S., Sang Mee Lee, Ph.D., Marshall H. Chin, M.D., M.P.H., Aviva G. Nathan, M.P.H., and Elbert S. Huang, M.D., M.P.H., are also with the Department of Medicine and Section of General Internal Medicine, University of Chicago, Chicago, IL. Tzy-Chyi Yu, M.H.A., Ph.D., is with the NORC at the University of Chicago, Parsippany, NJ. Ravi Sharma, Ph.D., is with the Bureau of Primary Health Care, Health Resources and Services Administration, US Department of Health and Human Services, Rockville, MD.
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2012). In the outpatient setting, HCs have performed better on some, but not all, measures of quality compared to other primary care providers (Porterfield and Kinsinger 2002; Regan et al. 2003; Hicks et al. 2006; Shi and Stevens 2007; Goldman et al. 2012). Studying the effects of HCs on utilization and quality of care has unique challenges. First, few nationally representative datasets of health care providers provide accurate identification of HCs, which leads to inaccurate identification of HC patients. Data on providers reported by patients may be inaccurate, as patients may not know if their primary care clinic is a federally funded HC or another type of community health center. Second, due to the HC mission, HC patients are more likely to be racial/ethnic minorities, uninsured or Medicaid enrollees, and have higher rates of chronic disease (Forrest and Whelan 2000; Shi et al. 2010). These important differences may be a source of confounding if not accounted for in analyses. Third, HCs are intentionally located in federally designated medically underserved areas. Thus, HC patients may be located in different geographic locations than other primary care patients and have different access to health care resources. These differences in location, which may affect utilization, have not been accounted for in previous analyses. Previous studies on HCs have left uncertainty about the effects of this safety net program on health care utilization and quality of care. We hypothesized that patients receiving care at HCs would have no difference in outpatient visits, but fewer emergency room visits and hospitalizations, and similar or better quality of care compared to similar patients receiving care at other sites. In this study, we have addressed some limitations of past work by address-matching federally funded HCs to provider addresses, including less readily available variables in adjustment for selection (e.g., quality of life), using advanced methods of adjustment (propensity scores), and adjusting for differences in patient proximity to HCs.
M ETHODS We used five panels from the Medical Expenditure Panel Survey (MEPS) (2004–2008) (N = 79,041), which is a nationally representative household survey of the noninstitutionalized civilian population performed by the Agency for Healthcare Research and Quality (AHRQ). MEPS is a 2-year panel survey and collects data in five household interviews. We also used Health Resources and Services Administration Bureau of Primary Health Care (BPHC)
Utilization and Quality for Health Center vs. Non–Health Center Patients
1501
Uniform Data System and BPHC Management Information System databases. These administrative databases include addresses of all Section 330 HCs and affiliated sites from 2004 to 2008. This project was approved by institutional review boards at the University of Chicago and NORC at the University of Chicago. We studied adults, aged ≥18 years, with ≥1 clinic (office or hospitalbased) visit in their first panel year, and who lived ≤20 miles of an HC (n = 33,137). We used data from the first panel year to identify participants to study how the site of care may affect future health care utilization. In MEPS, participants are queried at each interview whether their household used health care services and the address of each provider (Richard et al. 2012). To accurately identify visits at HCs, we compared provider addresses in MEPS to HC addresses in BPHC databases. Congruent with previous studies, we considered participants to be HC patients if the majority (≥50 percent) of their clinic visits were at HCs (Falik et al. 2001; Gurewich et al. 2012); other participants were considered non-HC patients. Because patients tend to live near their site of health care, and differences in proximity may affect their utilization of their health care site (Hadley and Cunningham 2004; Gresenz, Rogowski, and Escarce 2007), we restricted the sample to participants living ≤20 miles of an HC. Details on how this distance was calculated are available in the onlineonly supplement (Data S1). We included the MEPS year-end summary data from the first panel year on sociodemographics, health behaviors, comorbid illnesses, quality of life (Ware, Kosinski, and Keller 1996), depressed symptoms (Gilbody et al. 2007), and household geography (see Table 1 for complete variable list). We constructed variables to describe each participant’s type(s) of insurance (Medicare, Medicaid, private, Medicaid HMO, private HMO) and whether they held that insurance for the full year, part of the year, or not at all. Participants who had no health insurance for the entire first panel year were considered uninsured. We also counted the number of functional limitations with which participants reported having some difficulty (lifting 10 pounds, walking up 10 steps, walking three blocks, walking a mile, standing 20 minutes, bending/ stooping, reaching overhead, using fingers to grasp). In addition, we used U.S. Census zip code data from 2007 to 2009 on the poverty rate and proportion of minority race and Hispanics. Lastly, we included the 2006 county-level urban–rural classification from the National Center of Health Statistics. The outcomes of interest were patient-reported health care utilization and preventive care in the second panel year. Health care utilization was defined by total office visits, hospital-based outpatient visits, prescriptions
1502
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Table 1: Adult Participants Living within Twenty Miles of a Health Center Receiving Outpatient Care in the First Panel Year (N = 33,137)
Demographics Age, years, mean (SE) Female, n (%) Marital status, n (%) Married Widowed Divorced Separated Never married Race/ethnicity, n (%) White Black Hispanic American Indian/Alaskan Native Asian Hawaiian/Pacific Islander Other Education, years, mean (SE) Percent federal poverty line, n (%)
