Restricted accessResearch articleFirst published online 2015-12
Assessing the Representativeness of Medical Expenditure Panel Survey Inpatient Utilization Data for Individuals With Psychiatric and Nonpsychiatric Conditions
Sampling and reporting biases in the Medical Expenditure Panel Survey (MEPS) survey could render data on inpatient utilization that are not representative for individuals with severe psychiatric conditions. The authors assessed the representativeness of MEPS data on psychiatric inpatient utilization, by comparing MEPS estimates of total annual psychiatric and nonpsychiatric inpatient admissions and bed days, and mean length of stay, for nonelderly U.S. adults in calendar years 2005 to 2010 (N = 9,288) to estimates from the Nationwide Inpatient Sample (NIS), a nationally representative inpatient care database derived from hospitals’ administrative records (N = 21,934,378). Compared with the NIS, the MEPS indicated 34% as many psychiatric admissions and 86% as many nonpsychiatric admissions, while mean psychiatric length of stay was greater in MEPS than in NIS. In MEPS data, underrepresentation of psychiatric inpatient utilization at community hospitals may result in measurement distortions for commonly used statistics on psychiatric inpatient utilization and costs.
Agency for Healthcare Research and Quality. (2002). Changes in the NIS sampling and weighting strategy for 1998. Rockville, MD: Author.
2.
Agency for Healthcare Research and Quality. (2013a). Clinical Classifications Software (CCS) for ICD-9-CM (Healthcare Cost and Utilization Project, 2013). Rockville, MD: Author. Retrieved from www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
3.
Agency for Healthcare Research and Quality. (2013b). Overview of the Nationwide Inpatient Sample (NIS) (Healthcare Cost and Utilization Project). Rockville, MD: Author.
4.
AizcorbeA.LiebmanE.PackS.CutlerD. M.ChernewM. E.RosenA. B. (2012). Measuring health care costs of individuals with employer-sponsored health insurance in the US: A comparison of survey and claims data. Statistical Journal of the IAOS, 28(1), 43-51.
5.
BernardD.CowanC.SeldenT.CaiL.CatlinA.HefflerS. (2012). Reconciling medical expenditure estimates from the MEPS and NHEA, 2007. Medicare & Medicaid Research Review, 2(4), E1-E19.
6.
BhandariA.WagnerT. (2006). Self-reported utilization of health care services: Improving measurement and accuracy. Medical Care Research and Review, 63, 217-235.
7.
CannellC. F.MillerP. V.OksenbergL. (1981). Research on interviewing techniques. Sociological Methodology, 12, 389-437.
8.
ClarkR. E.RickettsS. K.McHugoG. J. (1996). Measuring hospital use without claims: A comparison of patient and provider reports. Health Services Research, 31, 153-169.
9.
CohenJ. W.MonheitA. C.BeauregardK. M.CohenS. B.LefkowitzD. C.PotterD. E.. . . ArnettR. H.III., (1996). The Medical Expenditure Panel Survey: A national health information resource. Inquiry, 33, 373-389.
10.
CookB. L.ZuvekasS. H.CarsonN.WayneG. F.VesperA.McGuireT. G. (2014). Assessing racial/ethnic disparities in treatment across episodes of mental health care. Health Services Research, 49, 206-229.
11.
Des JarlaisD. C.PaoneD.MillikenJ.TurnerC. F.MillerH.GribbleJ.. . . FriedmannS. R. (1999). Audio-computer interviewing to measure risk behaviour for HIV among injecting drug users: A quasi-randomised trial. The Lancet, 353, 1657-1661.
12.
DismukeC. E.EgedeL. E. (2011). Association of serious psychological distress with health services expenditures and utilization in a national sample of US adults. General Hospital Psychiatry, 33, 311-317.
13.
DixonL.PostradoL.DelahantyJ.FischerP. J.LehmanA. (1999). The association of medical comorbidity in schizophrenia with poor physical and mental health. Journal of Nervous and Mental Disease, 187, 496-502.
14.
GarfieldR. L.ZuvekasS. H.LaveJ. R.DonohueJ. M. (2011). The impact of national health care reform on adults with severe mental disorders. American Journal of Psychiatry, 168, 486-494.
15.
GellerJ. L. (2000). Excluding institutions for mental diseases from federal reimbursement for services: Strategy or tragedy?Psychiatric Services, 51, 1397-1403.
16.
GfroererJ.LesslerJ.ParsleyT. (1997). Studies of nonresponse and measurement error in the national household survey on drug abuse. In HarrisonL.HughesA. (Eds.), The validity of self-reported drug use: Improving the accuracy of survey estimates (NIDA Research Monograph 167, pp. 273-295). Rockville, MD: National Institute on Drug Abuse.
17.
GoldingJ. M.GonglaP.BrownellA. (1988). Feasibility of validating survey self-reports of mental health service use. American Journal of Community Psychology, 16(1), 39-51.
18.
HarrisonL.HughesA. (Eds.). (1997). The validity of self-reported drug use: Improving the accuracy of survey estimate (NIDA Research Monograph 167). Rockville, MD: National Institute on Drug Abuse.
19.
HimelhochS.McCarthyJ. F.GanoczyD.MedoffD.DixonL.BlowF. (2007). Understanding associations between serious mental illness and HIV among veterans: A national multivariate analysis. Psychiatric Services, 58, 1165-1172.
20.
HimelhochS.WellerW. E.WuA. W.AndersonG. F.CooperL. A. (2004). Chronic medical illness, depression, and use of acute medical services among Medicare beneficiaries. Medical Care, 42, 512-521.
21.
JonesD. R.MaciasC.BarreiraP. J.FisherW. H.HargreavesW. A.HardingC. M. (2004). Prevalence, severity, and co-occurrence of chronic physical health problems of persons with serious mental illness. Psychiatric Services, 55, 1250-1257.
22.
JordanJ. M.BeaghenM. A. (2011). Analysis of the variances of American Community Survey estimates of the group quarters population. Washington, DC: U.S. Census Bureau, Economics and Statistics Administration.
23.
KatonW. (1996). The impact of major depression on chronic medical illness. General Hospital Psychiatry, 18, 215-219.
24.
KilleenT. K.BradyK. T.GoldP. B.TysonC.SimpsonK. N. (2004). Comparison of self-report versus agency records of service utilization in a community sample of individuals with alcohol use disorders. Drug and Alcohol Dependence, 73, 141-147.
25.
LittleR. J. (1993). Post-stratification: A modeler’s perspective. Journal of the American Statistical Association, 88, 1001-1012.
26.
MachlinS. R.ChowdhuryS. R.Ezzati-RiceT.DiGaetanoR.GokselH.WunL. M.KashiharaD. (2010). Estimation procedures for the Medical Expenditure Panel Survey household component (Methodology Report No. 24). Rockville, MD: Agency for Healthcare Research and Quality. Retrieved from http://www.meps.ahrq.gov/mepsweb/data_files/publications/mr24/mr24.pdf
27.
MachlinS.CohenJ.ElixhauserA.BeauregardK.SteinerC. (2009). Sensitivity of household reported medical conditions in the Medical Expenditure Panel Survey. Medical Care, 47, 618-625.
28.
MarcusS. C.OlfsonM. (2010). National trends in the treatment for depression from 1998 to 2007. Archives of General Psychiatry, 67, 1265-1273.
29.
RosenbergS. D.GoodmanL. A.OsherF. C.SwartzM. S.EssockS. M.ButterfieldM. I.. . . SalyersM. P. (2001). Prevalence of HIV, hepatitis B, and hepatitis C in people with severe mental illness. American Journal of Public Health, 91(1), 31-37.
30.
SladeE. P.DixonL. B.SemmelS. (2010). Trends in the duration of emergency department visits, 2001-2006. Psychiatric Services, 61, 878-884.
31.
SokalJ.MessiasE.DickersonF. B.KreyenbuhlJ.BrownC. H.GoldbergR. W.DixonL. B. (2004). Comorbidity of medical illnesses among adults with serious mental illness who are receiving community psychiatric services. Journal of Nervous and Mental Disease, 192, 421-427.
32.
TullochA. D.FearonP.DavidA. S. (2011). Length of stay of general psychiatric inpatients in the United States: Systematic review. Administration and Policy in Mental Health and Mental Health Services Research, 38, 155-168.
33.
ZuvekasS. H.OlinG. L. (2009a). Accuracy of medicare expenditures in the Medical Expenditure Panel Survey. Inquiry, 46(1), 92-108.
34.
ZuvekasS. H.OlinG. L. (2009b). Validating household reports of health care use in the Medical Expenditure Panel Survey. Health Services Research, 44(5Pt. 1), 1679-1700.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
