Literature DB >> 6237993

DRGs and hospital case records: implications for Medicare case mix accuracy.

A N Johnson, G L Appel.   

Abstract

As Medicare moves to DRG-based prospective payment, it is not clear whether the federal government has adequate data upon which to formulate DRG prices and assess hospital case mix. This study compares the Medicare case mix of Minneapolis-St. Paul hospitals based on the historical information submitted for billing purposes on the Medicare claim with the actual case mix of hospitals as described in the medical record chart. It was found that for the same patients, the DRG based on the claim matched the DRG on the medical record approximately half of the time. These "mismatches" resulted in a statistically significant understatement of hospitals' case mix, and have obvious implications for the setting of DRG prices and equitable hospital reimbursement.

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Year:  1984        PMID: 6237993

Source DB:  PubMed          Journal:  Inquiry        ISSN: 0046-9580            Impact factor:   1.730


  7 in total

1.  Catch Me if You Can: Acute Events Hidden in Structured Chronic Disease Diagnosis Descriptions Show Detectable Recording Patterns in EHR.

Authors:  Franck Diaz-Garelli; Kristin M Lenoir; Brian J Wells
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Measuring diagnoses: ICD code accuracy.

Authors:  Kimberly J O'Malley; Karon F Cook; Matt D Price; Kimberly Raiford Wildes; John F Hurdle; Carol M Ashton
Journal:  Health Serv Res       Date:  2005-10       Impact factor: 3.402

3.  Using computers to identify complications after surgery.

Authors:  L L Roos; S M Cageorge; E Austen; K N Lohr
Journal:  Am J Public Health       Date:  1985-11       Impact factor: 9.308

4.  Workflow Differences Affect Data Accuracy in Oncologic EHRs: A First Step Toward Detangling the Diagnosis Data Babel.

Authors:  Franck Diaz-Garelli; Roy Strowd; Virginia L Lawson; Maria E Mayorga; Brian J Wells; Thomas W Lycan; Umit Topaloglu
Journal:  JCO Clin Cancer Inform       Date:  2020-06

5.  What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality.

Authors:  Franck Diaz-Garelli; Roy Strowd; Tamjeed Ahmed; Thomas W Lycan; Sean Daley; Brian J Wells; Umit Topaloglu
Journal:  JCO Clin Cancer Inform       Date:  2021-05

6.  Biopsy Records Do Not Reduce Diagnosis Variability in Cancer Patient EHRs: Are We More Uncertain After Knowing?

Authors:  Jose-Franck Diaz-Garelli; Brian J Wells; Caleb Yelton; Roy Strowd; Umit Topaloglu
Journal:  AMIA Jt Summits Transl Sci Proc       Date:  2018-05-18

7.  A tale of three subspecialties: Diagnosis recording patterns are internally consistent but Specialty-Dependent.

Authors:  Jose-Franck Diaz-Garelli; Roy Strowd; Tamjeed Ahmed; Brian J Wells; Rebecca Merrill; Javier Laurini; Boris Pasche; Umit Topaloglu
Journal:  JAMIA Open       Date:  2019-08-05
  7 in total

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