PMID- 15230940
OWN - NLM
STAT- MEDLINE
DCOM- 20040813
LR  - 20181113
IS  - 0017-9124 (Print)
IS  - 0017-9124 (Linking)
VI  - 39
IP  - 4 Pt 1
DP  - 2004 Aug
TI  - Coding response to a case-mix measurement system based on multiple diagnoses.
PG  - 1027-45
AB  - OBJECTIVE: To examine the hospital coding response to a payment model using a 
      case-mix measurement system based on multiple diagnoses and the resulting impact 
      on a hospital cost model. DATA SOURCES: Financial, clinical, and supplementary 
      data for all Ontario short stay hospitals from years 1997 to 2002. STUDY DESIGN: 
      Disaggregated trends in hospital case-mix growth are examined for five years 
      following the adoption of an inpatient classification system making extensive use 
      of combinations of secondary diagnoses. Hospital case mix is decomposed into base 
      and complexity components. The longitudinal effects of coding variation on a 
      standard hospital payment model are examined in terms of payment accuracy and 
      impact on adjustment factors. PRINCIPAL FINDINGS: Introduction of the refined 
      case-mix system provided incentives for hospitals to increase reporting of 
      secondary diagnoses and resulted in growth in highest complexity cases that were 
      not matched by increased resource use over time. Despite a pronounced coding 
      response on the part of hospitals, the increase in measured complexity and case 
      mix did not reduce the unexplained variation in hospital unit cost nor did it 
      reduce the reliance on the teaching adjustment factor, a potential proxy for case 
      mix. The main implication was changes in the size and distribution of predicted 
      hospital operating costs. CONCLUSIONS: Jurisdictions introducing extensive 
      refinements to standard diagnostic related group (DRG)-type payment systems 
      should consider the effects of induced changes to hospital coding practices. 
      Assessing model performance should include analysis of the robustness of 
      classification systems to hospital-level variation in coding practices. 
      Unanticipated coding effects imply that case-mix models hypothesized to perform 
      well ex ante may not meet expectations ex post.
FAU - Preyra, Colin
AU  - Preyra C
AD  - Department of Health Policy, Management and Evaluation, University of Toronto, 
      Canada. Colin@preyra.com
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Health Serv Res
JT  - Health services research
JID - 0053006
SB  - IM
MH  - *Comorbidity
MH  - Cost Allocation
MH  - Diagnosis-Related Groups/*classification/economics
MH  - Efficiency, Organizational
MH  - Forms and Records Control/*methods
MH  - Health Services Research
MH  - *Hospital Costs
MH  - Hospital Information Systems/*organization & administration
MH  - Humans
MH  - Inpatients/*classification
MH  - Medical Records/*classification
MH  - Models, Econometric
MH  - Ontario
MH  - Regression Analysis
MH  - Reimbursement Mechanisms
PMC - PMC1361050
EDAT- 2004/07/03 05:00
MHDA- 2004/08/17 10:00
PMCR- 2006/08/01
CRDT- 2004/07/03 05:00
PHST- 2004/07/03 05:00 [pubmed]
PHST- 2004/08/17 10:00 [medline]
PHST- 2004/07/03 05:00 [entrez]
PHST- 2006/08/01 00:00 [pmc-release]
AID - HESR270 [pii]
AID - 10.1111/j.1475-6773.2004.00270.x [doi]
PST - ppublish
SO  - Health Serv Res. 2004 Aug;39(4 Pt 1):1027-45. doi: 
      10.1111/j.1475-6773.2004.00270.x.