title: Identifying neuropsychiatric disorders in the Medicare Current Beneficiary Survey: the benefits of combining health survey and claims data.
abstract: To address the impact of using multiple sources of data in the United States Medicare Current Beneficiary Survey (MCBS) compared to using only one source of data to identify those with neuropsychiatric diagnoses.
  
  
  
  Our data source was the 2010 MCBS with associated Medicare claims files (N = 14, 672 beneficiaries). The MCBS uses a stratified multistage probability sample design to select a nationally representative sample of Medicare beneficiaries. We excluded those participants in Medicare Health Maintenance Organizations (n = 3894) and performed a cross-sectional analysis. We classified neuropsychiatric conditions according to four broad categories: intellectual/developmental disorders, neurological conditions affecting the central nervous system (Neuro-CNS), dementia, and psychiatric conditions. To account for different baseline prevalence differences of the categories we calculated the relative increase in prevalence that occurred from adding information from claims in addition to the absolute increase to allow comparison among categories.
  
  
  
  The estimated proportion of the sample with neuropsychiatric disorders increased to 50.0 (both sources) compared to 38.9 (health survey only) and 33.2 (claims only) with an overlap between sources of only 44.1 %. Augmenting health survey data with claims led to an increase in estimated percentage of intellectual/developmental disorders, psychiatric disorders, Neuro-CNS disorders and dementia of 1.3, 5.9, 11.5 and 3.8 respectively. In the community sample, the largest relative increases were seen for dementia (147.6 %) and Neuro-CNS disorders (87.4 %). With the exception of dementia, larger relative increases were seen in the facility sample with the greatest being for intellectual/developmental disorders (121.5 %) and Neuro-CNS disorders (93.8 %).
  
  
  
  The magnitude of potentially underestimated sample proportions using health survey only data varied strikingly according to the category of diagnosis and setting. Augmentation of survey data with claims appears essential particularly when attempting to estimate proportion of the sample affected by conditions that cause cognitive impairment which may affect ability to self-report. Augmenting proxy survey data with claims data also appears to be essential when ascertaining proportion of the facility-dwelling sample affected by neuropsychiatric disorders.
authors.affiliation: Spinal Cord Injury Service, Veterans Affairs Palo Alto Health Care System, 3801 Miranda Ave (MC 140), Palo Alto, CA, 94304, USA. cms@alumni.med.upenn.edu.|Department of Neurosurgery, Stanford University, Stanford, California, USA. cms@alumni.med.upenn.edu.
authors.forename: Sophia Miryam
authors.identifier: 0000-0002-6311-6671
authors.initials: SM
authors.lastname: Schüssler-Fiorenza Rose
authors.affiliation: Department of Biostatistics and Epidemiology, The Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA, 19104-6021, USA.
authors.forename: Dawei
authors.initials: D
authors.lastname: Xie
authors.affiliation: Geriatric Psychiatry Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA.|VISN 4 Mental Illness Research Education and Clinical Center, Corporal Michael J. Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA.
authors.forename: Joel E
authors.initials: JE
authors.lastname: Streim
authors.affiliation: Department of Biostatistics and Epidemiology, The Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA, 19104-6021, USA.
authors.forename: Qiang
authors.initials: Q
authors.lastname: Pan
authors.affiliation: Department of Biostatistics and Epidemiology, The Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Drive, Blockley Hall, Philadelphia, PA, 19104-6021, USA.
authors.forename: Pui L
authors.initials: PL
authors.lastname: Kwong
authors.affiliation: Department of Physical Medicine and Rehabilitation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, 19104, USA.
authors.forename: Margaret G
authors.initials: MG
authors.lastname: Stineman
mesh_terms: D000368:Aged; D002493:Central Nervous System Diseases / Q000453:epidemiology*; D003430:Cross-Sectional Studies; D003704:Dementia / Q000453:epidemiology; D005260:Female; D006279:Health Maintenance Organizations; D006306:Health Surveys; D006801:Humans; D007344:Insurance Claim Reporting; D008607:Intellectual Disability / Q000453:epidemiology*; D008297:Male; D006278:Medicare; D001523:Mental Disorders / Q000453:epidemiology*; D015995:Prevalence; D057566:Self Report; D014481:United States / Q000453:epidemiology
keywords: Administrative claims; Central nervous system diseases; Dementia; Developmental disabilities; Health surveys; Intellectual disability; MCBS; Medicare Current Beneficiary Survey; Mental disorders; Residential facilities