Literature DB >> 2681546

Medicaid data as a resource for epidemiologic studies: strengths and limitations.

R A Bright1, J Avorn, D E Everitt.   

Abstract

Large claims databases from third-party insurance programs such as Medicaid have attracted the interest of epidemiologists because of their enormous size and apparent comprehensiveness. Over 20 million people are covered by the various state Medicaid programs and most states maintain detailed computerized records of all reimbursed health care encounters on a recipient-specific basis. For states covering medication costs, data on drug exposures are particularly complete and accurate. However, Medicaid claims data also have many limitations that can pose major methodological difficulties. Foremost among these is the uneven validity and completeness of the diagnoses appearing on claims. Likewise, the unique identification of specific program participants is not straightforward, although useful approaches can often be developed to track individuals over time. Consideration of the limitations as well as the possible strengths of claims-based data makes it possible to choose appropriate study hypotheses as well as to attempt solutions, where possible, to the biases of this methodology.

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Year:  1989        PMID: 2681546     DOI: 10.1016/0895-4356(89)90158-3

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  43 in total

1.  Mental health services for youths in foster care and disabled youths.

Authors:  S dosReis; J M Zito; D J Safer; K L Soeken
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2.  Improved comorbidity adjustment for predicting mortality in Medicare populations.

Authors:  Sebastian Schneeweiss; Philip S Wang; Jerry Avorn; Robert J Glynn
Journal:  Health Serv Res       Date:  2003-08       Impact factor: 3.402

Review 3.  Drug utilisation studies as tools in health economics.

Authors:  J A Sacristán; J Soto
Journal:  Pharmacoeconomics       Date:  1994-04       Impact factor: 4.981

4.  Child sociodemographic characteristics and common psychiatric diagnoses in medicaid encounter data: are they valid?

Authors:  Penelope K Knapp; Michael S Hurlburt; Eric C Kostello; Heather Ladd; Lingqi Tang; Bonnie T Zima
Journal:  J Behav Health Serv Res       Date:  2006-10       Impact factor: 1.505

5.  A cross-national study of the persistence of antihypertensive medication use in the elderly.

Authors:  Boris L G van Wijk; William H Shrank; Olaf H Klungel; Sebastian Schneeweiss; M Alan Brookhart; Jerry Avorn
Journal:  J Hypertens       Date:  2008-01       Impact factor: 4.844

6.  Drug-utilization study on Curaçao.

Authors:  L E Visser; M H Oosterveld; G I Vos; L T De Jong-Van den Berg
Journal:  Pharm World Sci       Date:  1993-04-23

7.  Treatment patterns for prostate cancer: comparison of Medicare claims data to medical record review.

Authors:  Steven T Fleming; Ann S Hamilton; Susan A Sabatino; Gretchen G Kimmick; Xiao-Cheng Wu; Jean B Owen; Bin Huang; Wenke Hwang
Journal:  Med Care       Date:  2014-09       Impact factor: 2.983

8.  Measuring prevention more broadly: an empirical assessment of CHIPRA core measures.

Authors:  Nir Menachemi; Justin Blackburn; David J Becker; Michael A Morrisey; Bisakha Sen; Cathy Caldwell
Journal:  Medicare Medicaid Res Rev       Date:  2013-08-22

Review 9.  Using administrative data to study persons with disabilities.

Authors:  Lisa I Iezzoni
Journal:  Milbank Q       Date:  2002       Impact factor: 4.911

10.  Record linkage to obtain birth outcomes for the evaluation of screening biomarkers in pregnancy: a feasibility study.

Authors:  Samantha J Lain; Charles S Algert; Vitomir Tasevski; Jonathan M Morris; Christine L Roberts
Journal:  BMC Med Res Methodol       Date:  2009-07-09       Impact factor: 4.615

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