Literature DB >> 35043402

A national assessment of legacy versus new generation Medicaid data.

Jessy K Nguyen1, Prachi Sanghavi1.   

Abstract

OBJECTIVE: To compare the performance of Medicaid legacy, Medicaid new generation, and Medicare claims on data analytic tasks. DATA SOURCES: Medicaid Analytic eXtract (MAX) claims (legacy) of 100% beneficiaries in 2011 (all states except Idaho), 2012 (all states), 2013 (28 states), and 2014 (17 states); 2016 Transformed Medicaid Statistical Information System Analytic Files (TAF) claims (new generation) of 100% beneficiaries from all states; Medicare claims of 20% beneficiaries in 2011-2014, 2016. STUDY
DESIGN: We focused on the chain of events that starts with an out-of-hospital medical emergency and ends with hospital death or survival to discharge. We developed six data quality indicators to assess ambulance variables; linkage between claims; external cause of injury code reporting; and death reporting on hospital discharge status codes. For the latter, we estimated injury severity and modeled its association with death in the Medicare population. We used the model to compare reported versus expected deaths by injury severity in the Medicaid population. Datasets were compared by state and fee-for-service versus managed care. DATA EXTRACTION
METHODS: Medicare and Medicaid beneficiaries with emergency ambulance transports. PRINCIPAL
FINDINGS: Medicare claims had high performance across indicators and states; MAX claims substantially underperformed on multiple indicators in most states. For example, most states reported external cause codes for over 90% of Medicare but less than 15% of Medicaid injury cases. Medicaid fee-for-service did not consistently perform better than Medicaid managed care. Compared with MAX, TAF claims performed significantly better on some indicators but continued to have poor external cause code reporting. Finally, MAX and TAF managed care records reported deaths at discharge in the range of expected deaths; however, fee-for-service claims might have underreported high-severity injury deaths.
CONCLUSIONS: New generation Medicaid claims performed better than legacy claims on some indicators, but much more improvement is needed to allow high-quality policy analysis.
© 2022 Health Research and Educational Trust.

Entities:  

Keywords:  Medicaid; Medicare; data quality; death reporting; injuries; medical emergencies

Mesh:

Year:  2022        PMID: 35043402      PMCID: PMC9264472          DOI: 10.1111/1475-6773.13937

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.734


  21 in total

1.  Assessing the usability of MAX 2008 encounter data for comprehensive managed care.

Authors:  Vivian L H Byrd; Allison Hedley Dodd
Journal:  Medicare Medicaid Res Rev       Date:  2013-03-28

2.  The Injury Severity Score revisited.

Authors:  W S Copes; H R Champion; W J Sacco; M M Lawnick; S L Keast; L W Bain
Journal:  J Trauma       Date:  1988-01

3.  Mortality among seriously injured patients treated in remote rural trauma centers before and after implementation of a statewide trauma system.

Authors:  N Clay Mann; R J Mullins; J R Hedges; D Rowland; M Arthur; A D Zechnich
Journal:  Med Care       Date:  2001-07       Impact factor: 2.983

4.  The effect of organized systems of trauma care on motor vehicle crash mortality.

Authors:  A B Nathens; G J Jurkovich; P Cummings; F P Rivara; R V Maier
Journal:  JAMA       Date:  2000-04-19       Impact factor: 56.272

5.  A modification of the injury severity score that both improves accuracy and simplifies scoring.

Authors:  T Osler; S P Baker; W Long
Journal:  J Trauma       Date:  1997-12

6.  Racial and ethnic disparities among enrollees in Medicare Advantage plans.

Authors:  John Z Ayanian; Bruce E Landon; Joseph P Newhouse; Alan M Zaslavsky
Journal:  N Engl J Med       Date:  2014-12-11       Impact factor: 91.245

7.  A national assessment of legacy versus new generation Medicaid data.

Authors:  Jessy K Nguyen; Prachi Sanghavi
Journal:  Health Serv Res       Date:  2022-02-21       Impact factor: 3.734

8.  Open-access programs for injury categorization using ICD-9 or ICD-10.

Authors:  David E Clark; Adam W Black; David H Skavdahl; Lee D Hallagan
Journal:  Inj Epidemiol       Date:  2018-04-09

9.  The effect of integration of hospitals and post-acute care providers on Medicare payment and patient outcomes.

Authors:  R Tamara Konetzka; Elizabeth A Stuart; Rachel M Werner
Journal:  J Health Econ       Date:  2018-02-07       Impact factor: 3.883

10.  Assessment of nursing home reporting of major injury falls for quality measurement on nursing home compare.

Authors:  Prachi Sanghavi; Shengyuan Pan; Daryl Caudry
Journal:  Health Serv Res       Date:  2019-12-29       Impact factor: 3.402

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  1 in total

1.  A national assessment of legacy versus new generation Medicaid data.

Authors:  Jessy K Nguyen; Prachi Sanghavi
Journal:  Health Serv Res       Date:  2022-02-21       Impact factor: 3.734

  1 in total

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