Identifying neuropsychiatric disorders in the Medicare Current Beneficiary Survey: the benefits of combining health survey and claims data

Abstract

BackgroundTo 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.MethodsOur 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.ResultsThe 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 %).ConclusionsThe 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.

Non-Cancer Chronic Pain Conditions and Risk for Incident Alzheimer’s Disease and Related Dementias in Community-Dwelling Older Adults: A Population-Based Retrospective Cohort Study of United States Medicare Beneficiaries, 2001–2013

“…The presence of ADRD at both baseline (year 1) and follow-up (years 2 and 3) was ascertained using a validated CMS algorithm (Centers for Medicare and Medicaid Services (CMS) Chronic Condition Algorithms) [ 40 ] of at least one fee-for-service claim with any of these International Classification of Diseases, ninth Edition, clinical modification (ICD-9-CM) diagnostic codes: 331.0, 331.11, 331.19, 331.2, 331.7, 290.0, 290.10, 290.11, 290.12, 290.13, 290.20, 290.21, 290.3, 290.40, 290.41, 290.42, 290.43, 294.0, 294.10, 294.11, 294.20, 294.21, 294.8, and 797, or an affirmative response to the self-reported Health Status question “Has a doctor ever told you that you had Alzheimer’s?” [ 41 ]. Using a combination of claims and survey data to ascertain ADRD has been recommended by MCBS investigators to increase capture of ADRD and has been shown to yield results similar to those of expert in-person-assessment [ 42 ].…”

The Association of Osteoarthritis and Related Pain Burden to Incident Alzheimer’s Disease and Related Dementias: A Retrospective Cohort Study of U.S. Medicare Beneficiaries

“…Outcome variable: Incident ADRD at follow-up-ADRD status at baseline (year 1) and follow-up (years 2 and 3) were ascertained using the 2001-13 Medicare FFS claims for inpatient (IP), skilled nursing facility (SNF), outpatient (OT), home health agency (HHA), and physician office (PO), as well as MCBS CU self-reported Health Status and Functioning files. To help increase capture of diagnosed ADRD, both claims and survey data were used to identify ADRD [42]. Specifically, the presence of ADRD was defined as 1) one or more FFS claims with any of the following International Classification of Diseases, ninth Edition, clinical modification (ICD-9-CM) diagnostic codes: 290.0-290.3, 331.0-331.2, 331.7, and 331.8 [43,44]; or 2) an affirmative response to the self-reported Health Status question "Has a doctor ever told you that you had Alzheimer's?…”

Treatment adequacy and remission of depression and anxiety disorders and quality of life in primary care older adults

“…Using both sources of data to identify the presence/absence of depression and anxiety disorders minimised the potential recall and social-desirability bias. Schülssler-Fiorenza Rose et colleagues [ 24 ] highlighted the importance of combining self-reported and administrative data, particularly for diseases with diagnostic codes with low sensitivity like depression. A Canadian case-study similarly highlighted the difficulties in measuring quality of care for depression using administrative database only [ 70 ].…”

“…This study design confers a number of advantages. First, it has been suggested that using either self-report or administrative data alone may underestimate the presence of mental disorders and therefore using information from both sources increases the validity of results [ 24 , 25 ]. Second, this dataset allowed to control for a number of potential confounding individual and health system factors.…”