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Studying Prescription Drug Use and Outcomes With Medicaid Claims Data

Strengths, Limitations, and Strategies

Dados Bibliográficos

ID9099262
AutoresStephen Crystal (0000-0003-0366-7583, Institute of Health Services and Policy Research, autor correspondente), Ayse Akincigil, Ayşe Akıncıgil (0000-0002-8624-5038, Institute of Health Services and Policy Research, autor correspondente), Scott Bilder (Institute of Health Services and Policy Research, autor correspondente), James Walkup (Institute of Health Services and Policy Research, autor correspondente), James T Walkup
Ano2007
Volume45
Fascículo10
PáginasS58-S65
Data de publicação2007-10-01
Peer ReviewedSim
Open AccessNão
TipoARTICLE
PeriódicoMedical Care (JOURNAL)
Identificadores do periódicoISSN: 0025-7079 • E-ISSN: 1537-1948
EditoraOvid Technologies (Wolters Kluwer Health) (PUBLISHER)
DOI10.1097/mlr.0b013e31805371bf
PMID17909385
PMCIDPMC2486436
OpenAlexW2030597325
IdiomaEN
Citações recebidas11
Referências citadas32

Medicaid claims and eligibility data, particularly when linked to other sources of patient-level and contextual information, represent a powerful and under-used resource for health services research on the use and outcomes of prescription drugs. However, their effective use poses many methodological and inferential challenges. This article reviews strengths, limitations, challenges, and recommended strategies in using Medicaid data for research on the initiation, continuation, and outcomes of prescription drug therapies. Drawing from published research using Medicaid data by the investigators and other groups, we review several key validity and methodological issues. We discuss strategies for claims-based identification of diagnostic subgroups and procedures, measuring and modeling initiation and persistence of regimens, analysis of treatment disparities, and examination of comorbidity patterns. Based on this review, we discuss "best practices" for appropriate data use and validity checking, approaches to statistical modeling of longitudinal patterns in the presence of typical challenges, and strategies for strengthening the power and potential of Medicaid datasets. Finally, we discuss policy implications, including the potential for the research use of Medicare Part D data and the need for further initiatives to systematically develop and optimally use research datasets that link Medicaid and other sources of clinical and outcome information

Alternative medicine · Data science · Health care · Identification (biology) · Medicaid · Medical prescription · MEDLINE · Outcomes research · Prescription drug · Advanced Causal Inference Techniques · Computer Science · Health Systems, Economic Evaluations, Quality of Life · Medication Adherence and Compliance · Medicine · Nursing

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Obras citantes distintas11
Citações por ano0,58
Intervalo de citações2007 - 2025 (19)
Velocidade de citaçãorecent
Altamente citadoNão
Tipos de citaçãoNeutras: 9
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