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Racial Disparities in Hospital Length of Stay for Asthma: Implications for Economic Policies

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Abstract

Asthma is one of the most common health burdens on American families. An understanding of how the costs of asthma are distributed across communities is essential to realizing cost savings from preventative care. We model the household’s utilization of hospital services using Grossman’s health production framework. We then test for differences in asthma-related hospitalizations by race using inpatient records from the Massachusetts Division of Health Care Finance. On average black and nonwhite-Hispanic patients stayed between one-third and one-fourth of a day less than similar white patients which translates into a difference in expenditures of $8 million over 1994–2002. The difference in expenditures raises questions for market-based methodologies to value health and for policies directed at reducing inequalities in health outcomes.

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Notes

  1. Other disciplines have well-developed theories of health behaviors. For example Andersen (1995) provides a review of the behavioral model from a sociologist’s perspective. Glanz et al. (2002) describe the variety of models used in public health. These models have different focuses that can enrich the Grossman model, but they do not invalidate the premise of the Grossman model.

  2. Our categories for payer types were based on the general payer categories as constructed by the Massachusetts Division of Health Care Finance and Policy (DHCFP). There is a one-to-one correspondence between the Medicaid, Medicaid managed, self-pay, and HMO categories used by DHCFP and our analysis. In our analysis the category “commercial” includes two categories used by the DHCFP (commercial and Blue Cross). Our category “commercial managed” includes the categories Blue Cross managed, commercial managed and PPO and other managed. Details on the inpatient data are in the data documentation manuals, available at http://www.mass.gov/Eeohhs2/docs/dhcfp/r/hdd/hdd_fy06.pdf.

  3. Although Medicare is available to some individuals younger than 65 who meet specific criteria, we exclude those individuals in order to reduce unmeasured heterogeneity.

  4. Details on these variables and other data can be found in the inpatient documentation manuals, available at http://www.mass.gov/Eeohhs2/docs/dhcfp/r/hdd/hdd_fy06.pdf.

  5. Individuals with a secondary diagnosis for any of these confounding conditions were excluded: renal failure (ICD-9 code 584.x–586.x) transplant (ICD-9 code V42.x), AIDS (042.x, 279.x, 031.0), chronic obstructive pulmonary disease not asthma (492.x–495.x), diabetes (250.x), or cancer (140.x–208.9).

  6. There were no missing data for gender, age, hospital identifier or payer type.

  7. Subsequent admissions within two years of first admission.

  8. Total excess expenditures are calculated as the sum over all payer types of the product of the difference in the expected length of stay, the price per day, and the count of white admissions.

  9. Recall that there were 29,802 admissions that met the criteria for our study: aged 18–65, with an asthma diagnosis and no confounding condition, and self-reported race of white, black/African American or Hispanic.

References

  • Acton, J. P. (1975). Nonmonetary factors in the demand for medical services: Some empirical evidence. The Journal of Political Economy, 83(3), 595–614.

    Article  Google Scholar 

  • Agee, M. D., & Crocker, T. D. (1996). Parental altruism and child lead exposure: Inferences from the demand for chelation therapy. Journal of Human Resources, 31(3), 677–691.

    Article  Google Scholar 

  • Agency for Healthcare Research and Quality. (2001). Guide to prevention quality indicators: Hospital admission for ambulatory care sensitive conditions. Report 02-R0203. Rockville, MD: Department of Health and Human Services.

  • Akinbami, L. (2006, November). Asthma prevalence, health care use and mortality: United States, 2003–2005. National Center for Health Statistics, Health E-Stats. Retrieved 20 Dec 2008, from http://www.cdc.gov/nchs/products/pubs/pubd/hestats/ashtma03-05/asthma03-05.htm.

  • Akinbami, L., & Schoendorf, K. (2002). Trends in childhood asthma: Prevalence, health care utilization and mortality. Pediatrics, 110(2), 315–322.

    Article  Google Scholar 

  • Allison, P. D., & Waterman, R. P. (2002). Fixed-effects negative binomial regression models. Sociological Methodology, 32, 247–265.

    Article  Google Scholar 

  • Andersen, R. M. (1995). Revisiting the behavioral model and access to medical care: Does it matter? Journal of Health and Social Behavior, 36(1), 1–10.

    Article  Google Scholar 

  • Angus, D., Linde-Zwirble, W., Sirio, C., Rotondi, A., Chelluri, L., & Newbold, C. (1996). The effect of managed care on ICU length of stay: Implications for medicare. Journal of American Medical Association., 276, 1075–1082.

    Article  Google Scholar 

  • Ash, M., & Brandt, S. (2006). Disparities in asthma hospitalization in Massachusetts. American Journal of Public Health, 96(2), 358–362.

    Article  Google Scholar 

  • Bach, P., Cramer, L., Warren, J., & Begg, C. (1999). Racial differences in the treatment of early-stage lung cancer. The New England Journal of Medicine, 341(16), 1198–1205.

    Article  Google Scholar 

  • Banerji, A., Clark, S., Afilalo, M., Blanda, M., Cydulka, R., & Camargo, C. (2006). Prospective multicenter study of acute asthma in younger versus older adults presenting to the emergency department. Journal of the American Geriatric Society, 54, 48–55.

    Article  Google Scholar 

  • Baram, D., Daroowalla, F., Garcia, R., Zhang, G., Chen, J., Healy, E., et al. (2008). Use of the all patient refined-diagnosis related group (APR-DRG) risk of mortality score as a severity adjustor in the medical ICU. Clinical Medicine: Circulatory, Respiratory and Pulmonary Medicine, 2, 19–25. Retrieved 2nd Dec 2008, from Libertas Academica.

    Google Scholar 

  • Barr, D. A. (2008). Health disparities in the United States. Baltimore, MD: The Johns Hopkins University Press.

    Google Scholar 

  • Basu, A., Paltiel, A. D., & Pollack, H. A. (2008). Social costs of robbery and the cost-effectiveness of substance abuse treatment. Health Economics, 17(8), 927–946.

    Article  Google Scholar 

  • Baydar, N., Joesch, J., Kieckhefer, G., Kim, H., & Greek, A. (2007). Employment behaviors of mothers who have a child with asthma. Journal of Family and Economic Issues, 28(3), 337–355.

    Article  Google Scholar 

  • Bentley, T. G., Willett, W. C., Weinstein, M. C., & Kuntz, K. M. (2006). Population-level changes in folate intake by age, gender, and race/ethnicity after folic acid fortification. American Journal of Public Health, 96(11), 2040–2047.

    Article  Google Scholar 

  • Berg, G. D., & Chattopadhyay, S. K. (2004). Determinants of hospital length of stay for cervical dysplasia and cervical cancer: Does managed care matter? American Journal of Managed Care, 10, 33–38.

    Google Scholar 

  • Brandon, P. D. (2000). Child care utilization among working mothers raising children with disabilities. Journal of Family and Economic Issues, 21(4), 343–364.

    Article  Google Scholar 

  • Brasel, K. J., Lim, H. J., Nirula, R., & Weigelt, J. A. (2007). Length of stay: An appropriate quality measure? Archives of Surgery, 142(5), 461–466.

    Article  Google Scholar 

  • Bratton, S., Odetola, F., McCollegan, J., Cabana, M., Levy, F., & Keenan, H. (2005). Regional variation in ICU care for pediatric patients with asthma. Journal of Pediatrics, 147, 355–361.

    Article  Google Scholar 

  • Broyles, R. W. (1990). Efficiency, costs, and quality: The New Jersey experience revisited. Inquiry: A Journal of Medical Care Organization, Provision and Financing, 27(1), 86–96.

    Google Scholar 

  • Broyles, R. W., & Rosko, M. D. (1985). A qualitative assessment of the Medicare prospective payment system. Social Science and Medicine, 20(11), 1185–1190.

    Article  Google Scholar 

  • Burns, L. R., & Wholey, D. R. (1991). The effects of patient, hospital, and physician characteristics on length of stay and mortality. Medical Care, 29(3), 251–271.

    Article  Google Scholar 

  • Butz, A. M., Malveaux, F. J., Eggleston, P., Thompson, L., Huss, K., Kolodner, K., et al. (1995). Social factors associated with behavioral problems in children with asthma. Clinical Pediatrics, 34(11), 581–590.

    Article  Google Scholar 

  • Cameron, A. C., & Trivedi, P. K. (1998). Regression analysis of count data. New York: Cambridge University Press.

    Google Scholar 

  • Cameron, A. C., Trivedi, P. K., Milne, F., & Piggott, J. (1988). A microeconomic model of the demand for health care and health insurance in Australia. Review of Economic Studies, 55(181), 85–106.

    Google Scholar 

  • Canto, J., Rogers, W., French, W., Gore, J., Chandra, N., & Barron, H. (2000). Payer type and the utilization of hospital resources in acute myocardinal infarction a: A report from the national registry of myocardial infarction. Archives of Internal Medicine, 160, 817–823.

    Article  Google Scholar 

  • Chamberlain, J., Joseph, J., Patel, K., & Pollack, M. (2007). Differences in severity-adjusted pediatric hospitalization rates are associated with race/ethnicity. Pediatrics, 119(6), e1319–e1324.

    Article  Google Scholar 

  • Chi, P., & Hsin, P. (1999). Medical utilization and health expenditure of the elderly in Taiwan. Journal of Family and Economic Issues, 20, 251–270.

    Article  Google Scholar 

  • Christiansen, S. C., & Zuraw, B. L. (2002). Serving the underserved: School-based asthma intervention programs. Journal of Asthma, 39, 463–472.

    Article  Google Scholar 

  • Claudio, L., Tulton, L., Doucette, J., & Landrigan, P. J. (1999). Socioeconomic factors and asthma hospitalization rates in New York city. Journal of Asthma, 36(4), 343–350.

    Article  Google Scholar 

  • Cooper-Patrick, L., Gallo, J. J., Gonzales, J. J., Vu, H. T., Powe, N. R., Nelson, C., et al. (1999). Race, gender, and partnership in the patient-physician relationship. Journal of American Medical Association, 282(6), 583–589.

    Article  Google Scholar 

  • Corbie-Smith, G., Thomas, S. B., & St. George, D. M. M. (2002). Distrust, race, and research. Archives of Internal Medicine, 162(21), 2458–2463.

    Article  Google Scholar 

  • Cunningham, P. (2008). Trade-offs getting tougher: Problems paying medical bills increase for U.S. families, 2003–2007. Washington, DC: Center for Studying Health System Change.

    Google Scholar 

  • Cutler, D. M. (1995). The incidence of adverse medical outcomes under prospective payment. Econometrica, 63(1), 29–50.

    Article  Google Scholar 

  • Cutler, D. M., McClellan, M., & Newhouse, J. P. (2000). How does managed care do it? RAND Journal of Economics, 31(3), 526–548.

    Article  Google Scholar 

  • DHCFP. Division of Health Care Finance and Policy. (2005). Preventable hospitalization in Massachusetts: Update for fiscal years 2002 and 2003. Commonwealth of Massachusetts.

  • Dickie, M. (2004). Defensive behavior and damage cost methods. In T. C. Brown, K. J. Boyle, & P. A. Champ (Eds.), A primer on nonmarket valuation (pp. 395–444). Norwell, MA: Kluwer Publishers.

    Google Scholar 

  • Dickie, M., & Gerking, S. (1991). Willingness to pay for ozone control: Inferences from the demand for medical care. Journal of Environmental Economics and Management, 21(1), 1–16.

    Article  Google Scholar 

  • Diez Roux, A. V., Kiefe, C. I., Jacobs, D. R., Haan, M., Jackson, S. A., Nieto, F. J., et al. (2001). Area characteristics and individual-level socioeconomic position indicators in three population-based epidemiologic studies. Annals of Epidemiology, 11(6), 395–405.

    Article  Google Scholar 

  • Ellis, R. P., & Ruhm, C. J. (1988). Incentives to transfer patients under alternative reimbursement mechanisms. Journal of Public Economics, 37(3), 381–394.

    Article  Google Scholar 

  • Epstein, A., Stern, R., Tognetti, J., Begg, C., Hartley, R., Cumella, E., et al. (1988). The association of patients’ socioeconomic characteristics with the length of hospital stay and hospital charges within diagnosis-related groups. New England Journal of Medicine, 318(24), 1579–1585.

    Google Scholar 

  • Fan, J. X., & Zuiker, V. S. (1998). A comparison of household budget allocation patterns between Hispanic Americans and non-Hispanic white Americans. Journal of Family and Economic Issues, 19(2), 151–174.

    Article  Google Scholar 

  • Friedberg, L., & Webb, A. (2006). Determinants and consequences of bargaining power in households. National Bureau of Economic Research Working Paper Series, No. 12367.

  • Gass, E. (2008). Hospital admissions: An examination of race and health insurance. International Journal of Human Sciences, 5(1), 1–22.

    Google Scholar 

  • Geronimus, A., & Bound, J. (1998). Use of Census-based aggregate variables to proxy for socio-economic group: Evidence form national samples. American Journal of Epidemiology, 148(5), 475–486.

    Google Scholar 

  • Geronimus, A., Bound, J., & Neidert, L. (1996). On the validity of using Census geocode characteristics to proxy individual socioeconomic characteristics. Journal of the American Statistical Society, 91(434), 529–537.

    Google Scholar 

  • Gilleskie, D. B. (1998). A dynamic stochastic model of medical care use and work absence. Econometrica, 66(1), 1–45.

    Article  Google Scholar 

  • Glanz, K., Rimer, B. K., & Lewis, F. M. (Eds.). (2002). Health behavior and health education (3rd ed.). San Francisco: Jossey-Bass.

    Google Scholar 

  • Greene, W. (2008). Functional forms for the negative binomial model for count data. Economics Letters, 99(3), 585–590.

    Article  Google Scholar 

  • Grossman, M. (1972). The demand for health. New York: National Bureau of Economic Research.

    Google Scholar 

  • Guimarães, P. (2008). The fixed effects negative binomial model revisited. Economics Letters, 99(1), 63–66.

    Article  Google Scholar 

  • Gustafsson, P. A., Björkstén, B., & Kjellman, N. I. (1994). Family dysfunction in asthma: A prospective study of illness development. The Journal of Pediatrics, 125(3), 493–498.

    Article  Google Scholar 

  • Haley, J, & Fragale, M. (n.d.). Health insurance, access, and use: Massachusetts: Tabulations from the 1999 national survey of America’s families SP-05. The Urban Institute. Retrieved 2nd Dec 2008, from http://www.urban.org/UploadedPDF/310392_MA_HealthProfile.pdf.

  • Hausman, J., Hall, B. H., & Griliches, Z. (1984). Econometric models for count data with an application to the patents-R&D relationship. Econometrica, 52(4), 909–938.

    Article  Google Scholar 

  • Hebert, P. L., Frick, K. D., Kane, R. L., & McBean, A. M. (2005). The causes of racial and ethnic differences in influenza vaccination rates among elderly medicare beneficiaries. Health Services Research, 40(2), 517–538.

    Article  Google Scholar 

  • Hofferth, S. L., Forry, N. D., & Peters, H. E. (2010). Child support, father–child contact, and preteens’ involvement with nonresidential fathers: Racial/ethnic differences. Journal of Family and Economic Issues, 31(1), 14–32.

    Article  Google Scholar 

  • Huang, Z., LaFleur, B., Chamberlain, J., Guagliardo, M., & Joseph, J. (2002). Inpatient childhood asthma treatment. Relationship between hospital characteristics to length of stay and cost: Analyses of New York state discharge data, 1995. Archives of Pediatric and Adolescent Medicine, 156(1), 67–72.

    Google Scholar 

  • Kaiser Family Foundation. (2008). Survey brief #7773. http://www.kff.org/kaiserpolls/7773.cfm. Accessed 22 May 2009.

  • Kaiser State Health Facts. (2007). Distribution of the nonelderly with medicaid by race/ethnicity––states, statehealthfacts.org. Retrieved 2 Dec 2008, from http://www.statehealthfacts.org/comparetable.jsp?ind=158&cat=3&sub=42&yr=85&typ=2.

  • Keating, N. L., Landrum, M. B., Guadagnoli, E., Winer, E. P., & Ayanian, J. Z. (2006). Factors related to underuse of surveillance mammography among breast cancer survivors. Journal of Clinical Oncology, 24(1), 85–94.

    Article  Google Scholar 

  • Keith, V., Kronenfeld, J., Rivers, P., & Liang, S. (2005). Assessing the effects of race and ethnicity on use of complementary and alternative therapies in the USA. Ethnicity & Health, 10(1), 19–32.

    Article  Google Scholar 

  • Khaliq, A. A., Broyles, R. W., & Roberton, M. (2003). The use of hospital care: Do insurance status, prospective payment, and the unit of payments make a difference? Journal of Health and Human Services Administration, 25(4), 471–496.

    Google Scholar 

  • Koren, H. S. (1995). Associations between criteria air pollutants and asthma. Environmental Health Perspectives, 103(Suppl 6), 235–242.

    Article  Google Scholar 

  • Krieger, N., Chen, J., Waterman, P., Rehkopf, D., & Subramanian, S. V. (2005). Painting a truer picture of US socioeconomic and racial/ethnic health inequalities: The public health disparities geocoding project. American Journal of Public Health, 95(2), 312–323.

    Article  Google Scholar 

  • Krieger, N., Waterman, P., Chen, J., Soobader, M., Subramanian, S. V., & Carson, R. (2002). Zip code caveat: Bias due to spatiotemporal mismatches between zip codes and US Census––defined geographical areas—the public health disparities geocoding project. American Journal of Public Health, 92(7), 1100–1102.

    Article  Google Scholar 

  • Krishnan, J. A., Diette, G. B., Skinner, E. A., Clark, B. D., Steinwachs, D., & Wu, A. W. (2001). Race and sex differences in consistency of care with national asthma guidelines in managed care organizations. Archives of Internal Medicine, 161(13), 1660–1668.

    Article  Google Scholar 

  • Kruzewski, M. (2006). Disparities in repeat emergency room visits. Unpublished master’s thesis, University of Massachusetts, Amherst.

  • Lane, K., Kang, J., & Banaji, M. (2007). Implicit social cognition and law. Annual Review of Law and Social Science, 3, 427–451.

    Article  Google Scholar 

  • Lask, B. (2003). Motivating children and adolescents to improve adherence. The Journal of Pediatrics, 143(4), 430–433.

    Article  Google Scholar 

  • Lawrence, C. (2001). The id, the ego, and equal protection: Reckoning with unconscious racism. In T. Davis, K. Johnson, & G. Martinez (Eds.), A reader on race, civil rights and American law: A multiracial approach (pp. 127–130). Durham, N.C.: Carolina Academic Press.

    Google Scholar 

  • Levy, H., & Meltzer, D. (2008). The impact of health insurance on health. Annual Review of Public Health, 29, 399–409.

    Article  Google Scholar 

  • Lieu, T. A., Lozano, P., Finkelstein, J. A., Chi, F. W., Jensvold, N. G., Capra, A. M., et al. (2002). Racial/ethnic variation in asthma status and management practices among children in managed Medicaid. Pediatrics, 109(5), 857–865.

    Article  Google Scholar 

  • Lin, S., Fitzgerald, E., Hwang, S., Munsie, J. P., & Stark, A. (1999). Asthma hospitalization rates and socioeconomic status in New York state (1987–1993). Journal of Asthma, 36(3), 239–251.

    Article  Google Scholar 

  • Lundberg, S., & Pollak, R. A. (2007). The American family and family economics. Journal of Economic Perspectives, 21(2), 3–26.

    Article  Google Scholar 

  • MA Division of Health Care Finance and Policy. (2001). Hospital summary utilization data files. Retrieved 2nd Dec 2008, from http://www.mass.gov/Eeohhs2/docs/dhcfp/r/hsudf/01/cm09_2001.xls.

  • MacLean, W. E., Perrin, J. M., Gortmaker, S., & Pierre, C. B. (1992). Psychological adjustment of children with asthma: Effects of illness severity and recent stressful life events. Journal of Pediatric Psychology, 17(2), 159–171.

    Article  Google Scholar 

  • Manning, W. G., Newhouse, J. P., Duan, N., Keeler, E. B., Lelbowitz, A., & Marquis, M. S. (1987). Health insurance and the demand for medical care: Evidence from a randomized experiment. American Economic Review, 77(3), 251–277.

    Google Scholar 

  • Massachusetts Division of Health Care Finance and Policy. (2007). Massachusetts household survey on health insurance status, 2007. Retrieved 2nd Dec 2008, from http://www.mass.gov/Eeohhs2/docs/dhcfp/r/pubs/08/hh_survey_07.ppt.

  • Massachusetts Health Care Quality and Cost Council. (2008). Annual report. Retrieved 20th Dec 2008, from http://www.mass.gov/Ihqcc/docs/annual_report.pdf.

  • Massachusetts Senate Committee on Post Audit and Oversight. (2002). Attacking asthma––combating an epidemic among our children. Retrieved 20th Dec 2008, from http://www.mass.gov/legis/senate/asthma.htm.

  • MassCHIP. (2008). Massachusetts community health information profile [Computer software]. Massachusetts Department of Public Health. http://masschip.state.ma.us/.

  • McClellan, M. B., & Newhouse, J. P. (2000). Overview of the special supplement issue. Health Services Research, 35(5 Pt 2), 1061–1069.

    Google Scholar 

  • Mello, M. M., Stearns, S. C., & Norton, E. C. (2002). Do medicare HMOs still reduce health services use after controlling for selection bias? Health Economics, 11(4), 323–340.

    Article  Google Scholar 

  • Merrill, C. T., Stranges, E., & Steiner, C. (2008). Hospital stays for asthma among adults, 2005. HCUP statistical brief #54, Agency for Healthcare Research and Quality. Retrieved 10 Dec 2008, from http://www.hcup-us.ahrq.gov/reports/statbriefs/sb54.pdf.

  • Miller, W., Robinson, L. A., & Lawrence, R. S. (2006). Valuing health for regulatory cost-effectiveness analysis. Institute of Medicine. Washington, D.C.: National Academies Press.

    Google Scholar 

  • Mimura, Y. (2008). Housing cost burden, poverty status, and economic hardship among low-income families. Journal of Family and Economic Issues, 29, 152–165.

    Article  Google Scholar 

  • Miners, L. (1988). Individual vs household determinants of the demand for medical care: A study of rural families. Journal of Family and Economic Issues, 9(1), 33–54.

    Article  Google Scholar 

  • Muurinen, J. (1982). Demand for health: A generalised Grossman model. Journal of Health Economics, 1(1), 5–28.

    Article  Google Scholar 

  • Newhouse, J. P., & Phelps, C. E. (1974). Price and income elasticities for medical care services. In The economics of health and medical care: Proceeding of a conference of the International Economics Association. Retrieved 2 Dec 2008, from http://www.rc.rand.org/pubs/reports/2008/R1197.pdf.

  • Nocon, A., & Booth, T. (1991). The social impact of asthma. Family Practice, 8(1), 37–41.

    Article  Google Scholar 

  • Phipps, S. A. A. (1991). Family systems functioning, family health roles, and utilization of physical health services. Journal of Family and Economic Issues, 12(1), 23–41.

    Article  Google Scholar 

  • Picone, G., Wilson, R. M., & Chou, S. (2003). Analysis of hospital length of stay and discharge destination using hazard functions with unmeasured heterogeneity. Health Economics, 12(12), 1021–1034.

    Article  Google Scholar 

  • Pohlmeier, W., & Ulrich, V. (1995). An econometric model of the two-part decisionmaking process in the demand for health care. Journal of Human Resources, 30(2), 339–361.

    Article  Google Scholar 

  • Samuels, B. N., Novack, A. H., Martin, D. P., & Connell, F. A. (1998). Comparison of length of stay for asthma by hospital type. Pediatrics, 101(4), e13.

    Article  Google Scholar 

  • Sclar, D. A., Robison, L. M., Gavrun, C., & Skaer, T. L. (2008). Hospital length of stay for children and adolescents diagnosed with depression: Is primary payer an influencing factor? General Hospital Psychiatry, 30(1), 73–76.

    Article  Google Scholar 

  • Shields, A. E., Comstock, C., & Weiss, K. B. (2004). Variations in asthma care by race/ethnicity among children enrolled in a state Medicaid program. Pediatrics, 113(3), 496–504.

    Article  Google Scholar 

  • Silber, J. H., Rosenbaum, P. R., Even-Shoshan, O., Shabbout, M., Zhang, X., Bradlow, E. T., et al. (2003). Length of stay, conditional length of stay, and prolonged stay in pediatric asthma. Health Services Research, 38(3), 867–886.

    Article  Google Scholar 

  • Smedley, B. D., Stith, A. Y., & Nelson, A. R. (Eds.). (2003). Unequal treatment: Confronting racial and ethnic disparities in health care. Institute of medicine. Washington, D.C.: National Academies Press.

    Google Scholar 

  • Smith, D. H., Malone, D. C., Lawson, K. A., Okamoto, L. J., Battista, C., & Saunders, W. B. (1997). A national estimate of the economic costs of asthma. American Journal of Respiratory and Critical Care Medicine, 156(3), 787–793.

    Google Scholar 

  • Source Software. (1998, June 30). Realigned zip codes. Retrieved July 1, 2008, from http://sourcesoft.com/tech8.html.

  • Tanaka, M., Gundegmaa, J., Kaiser, M., et al. (2007). Racial disparities in hypertension disorders of pregnancy in New York State: A 10-year longitudinal population-based study. American Journal of Public Health, 97(10), 163–170.

    Google Scholar 

  • Todd, J., Amon, C., Griggs, A., Poole, S., & Berman, S. (2006). Increased rates of morbidity, mortality, and charges for hospitalized children with public or no health insurance as compared with children with private insurance in Colorado and the United States. Pediatrics, 118, 577–585.

    Article  Google Scholar 

  • Urbano, F. L. (2008). Review of the NAEEP 2007 expert panel report (epr-3) on asthma diagnosis and treatment guidelines. Journal of Managed Care Pharmacy, 14(1), 41–49.

    Google Scholar 

  • US Census Bureau. (n.d.). Census 2000, summary file 1 and summary file 3; generated by Peter St. Marie; using American FactFinder. Retrieved 20 Dec 2008, from http://factfinder.census.gov/.

  • US Census Bureau. (2000). Census 2000 ZCTAs zip code tabulation areas technical documentation. http://www.census.gov/geo/ZCTA/zcta_tech_doc.pdf.

  • US Department of Health and Human Services. (n.d.). The medical expenditure panel survey, Insurance component state and metro area tables. Retrieved 20 Dec 2008, from http://www.meps.ahrq.gov/mepsweb/data_stats/quick_tables_search.jsp?component=2&subcomponent=2.

  • Van Houtven, C. H., & Norton, E. C. (2004). Informal care and health care use of older adults. Journal of Health Economics, 23(6), 1159–1180.

    Article  Google Scholar 

  • Wagstaff, A. (1986). The demand for health: Some new empirical evidence. Journal of Health Economics, 5(3), 195–233.

    Article  Google Scholar 

  • Wasilewski, Y., Clark, N., Evans, D., Feldman, C. H., Kaplan, D., Rips, J., et al. (1988). The effect of paternal social support on maternal disruption caused by childhood asthma. Journal of Community Health, 13(1), 33–42.

    Article  Google Scholar 

  • Weiss, K. B., & Sullivan, S. D. (2001). The health economics of asthma and rhinitis. I. Assessing the economic impact. Journal of Allergy and Clinical Immunology, 107(1), 3–8.

    Article  Google Scholar 

  • White-Means, S., & Rubin, R. (2004). Trade-offs between formal home health care and informal family caregiving. Journal of Family and Economic Issues, 25(3), 335–358.

    Article  Google Scholar 

  • Williams, F. L., Hagler, A., Martin, M. A., Pritchard, M., & Bailey, W. C. (1991). Predictors of out-of-pocket medical expenditures in low-income households. Journal of Family and Economic Issues, 12(1), 43–62.

    Google Scholar 

  • Williams, D., & Rucker, T. (2000). Understanding and addressing racial disparities in health care. Health Care Financing Review, 21(4), 75–90.

    Google Scholar 

  • Wooldridge, J. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: MIT Press.

    Google Scholar 

  • Zhan, C., Miller, M. R., Wong, H., & Meyer, G. S. (2004). The effects of HMO penetration on preventable hospitalizations. Health Services Research, 39(2), 345–361.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Resource Economics and Center for Public Policy and Administration, University of Massachusetts Amherst, 219 Stockbridge Hall, Amherst, MA, 01003, USA

    Sylvia Brandt

  2. Department of Health Sciences, University of Massachusetts Amherst, Amherst, MA, 01003, USA

    Peter St. Marie

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  1. Sylvia Brandt
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  2. Peter St. Marie
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Correspondence to Sylvia Brandt.

Appendix

Appendix

See Tables 6, 7, 8, 9

Table 6 Negative binomial regression with fixed effects
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Table 7 Multinomial logit regression results by payer type (n = 16,048)
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Table 8 Negative binomial regression with fixed effects and instrumental variables (n = 16,048)
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Table 9 Negative binomial regression with dummy variables for hospitals
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Brandt, S., Marie, P.S. Racial Disparities in Hospital Length of Stay for Asthma: Implications for Economic Policies. J Fam Econ Iss 32, 152–169 (2011). https://doi.org/10.1007/s10834-010-9201-8

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