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Hoffmann, R. A wiki for the life sciences where authorship matters. Nature Genetics (2008)
 
MeSH Review

Risk Adjustment

 
 
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Psychiatry related information on Risk Adjustment

 

High impact information on Risk Adjustment

  • RESULTS: Variables that added significantly to the discriminative power of risk-adjustment models included sociodemographic (age, sex, prescription drug coverage), clinical (asthma severity), and health status (SF-36 PCS and MCS) [2].
  • CONCLUSIONS: This nonrandom variability in reporting can potentially bias utilization studies as well as risk-adjustment outcome estimates of techniques that rely on reporting of these procedures (eg, APR-DRG and AHRQ CCS) [3].
  • OBJECTIVE: To examine the ability of RxRisk-V to predict concurrent and prospective costs of care in VHA and compare the performance of RxRisk-V to a simple age/gender model, the original RxRisk, and two leading diagnosis-based risk adjustment approaches: Adjusted Clinical Groups and Diagnostic Cost Groups/Hierarchical Condition Categories [4].
  • STUDY DESIGN: Concurrent risk adjustment models were fitted and tested using the DCG/HCC model [5].
  • CONCLUSION: The SLE-specific risk adjustment index developed from diagnoses recorded in administrative discharge abstracts performed similarly to the generic Charlson index in correctly classifying mortality outcomes, but the SLE-specific index stratified patients by their level of risk of mortality better than the Charlson index [6].
 

Biological context of Risk Adjustment

 

Associations of Risk Adjustment with chemical compounds

  • CareScience, Inc. is a public company (NASDAQ: CARE) that originated ten years ago to commercialize risk adjustment and complication predictions developed by the Wharton School of Business and the University of Pennsylvania School of Medicine. Over the past decade, the company has grown to approximately 200 clients and 150 employees [8].
  • There were no significant differences in death/MI/SRI at 30 days (P =.465), death/MI at 30 days (P =.264), and stroke at 30 days with the type of heparin use (P =.201) after propensity risk adjustment [9].
  • CONCLUSIONS: Use of morphine either alone or in combination with nitroglycerin for patients presenting with NSTE ACS was associated with higher mortality even after risk adjustment and matching on propensity score for treatment [10].
 

Gene context of Risk Adjustment

  • We also describe the evolution of quality measurement in nursing homes, a recent CMS project to improve measures through risk adjustment and other refinements, the use of these measures in a pilot of the NHQI, and the lessons learned for future work in this area [11].
  • Two major multi-institutional efforts have attempted to measure case complexity: the Risk Adjustment in Congenital Heart Surgery-1 and the Aristotle Complexity Score [12].
  • CONCLUSION: It is feasible to develop clinically credible risk adjustment models for the outcomes of decline in PCS and MCS [13].
  • Because risk selection continues to be profitable under the current risk adjustment formula, fast growing HMO and PPO plans are (mis)used to attract good risks rather than to contain costs [14].
  • The objective of this preliminary study was to propose risk adjustments on the CHSRA indicators for future use in France. METHODS: The unit of analysis was residents assessments (558) in eight French facilities wich voluntarily participated to the experimentation of the Resident Assessment Instrument (RAI) from January 1996 to June 1999 [15].

References

  1. Predictors of patient-reported physical and mental health 6 months after percutaneous coronary revascularization. Nash, I.S., Curtis, L.H., Rubin, H. Am. Heart J. (1999) [Pubmed]
  2. Is risk-adjustor selection more important than statistical approach for provider profiling? Asthma as an example. Huang, I.C., Dominici, F., Frangakis, C., Diette, G.B., Damberg, C.L., Wu, A.W. Medical decision making : an international journal of the Society for Medical Decision Making. (2005) [Pubmed]
  3. Underreporting of computed tomography and magnetic resonance imaging procedures in inpatient claims data. Dismuke, C.E. Medical care. (2005) [Pubmed]
  4. Predicting costs of care using a pharmacy-based measure risk adjustment in a veteran population. Sales, A.E., Liu, C.F., Sloan, K.L., Malkin, J., Fishman, P.A., Rosen, A.K., Loveland, S., Paul Nichol, W., Suzuki, N.T., Perrin, E., Sharp, N.D., Todd-Stenberg, J. Medical care. (2003) [Pubmed]
  5. Diagnostic cost groups (DCGs) and concurrent utilization among patients with substance abuse disorders. Rosen, A.K., Loveland, S.A., Anderson, J.J., Hankin, C.S., Breckenridge, J.N., Berlowitz, D.R. Health services research. (2002) [Pubmed]
  6. Development and testing of a systemic lupus-specific risk adjustment index for in-hospital mortality. Ward, M.M. J. Rheumatol. (2000) [Pubmed]
  7. International pediatric cardiac assistance in Croatia: results of the 10 year program. Novick, W.M., Anić, D., Ivancan, V., Di Sessa, T.G. Croat. Med. J. (2004) [Pubmed]
  8. Business models for health care decision support. Gaughan, P. Studies in health technology and informatics. (2003) [Pubmed]
  9. Promise of combined low-molecular-weight heparin and platelet glycoprotein IIb/IIIa inhibition: results from Platelet IIb/IIIa Antagonist for the Reduction of Acute coronary syndrome events in a Global Organization Network B (PARAGON B). Mukherjee, D., Mahaffey, K.W., Moliterno, D.J., Harrington, R.A., Yadav, J.S., Pieper, K.S., Gallup, D., Dyke, C., Roe, M.T., Berdan, L., Lauer, M.S., Mänttäri, M., White, H.D., Califf, R.M., Topol, E.J. Am. Heart J. (2002) [Pubmed]
  10. Association of intravenous morphine use and outcomes in acute coronary syndromes: results from the CRUSADE Quality Improvement Initiative. Meine, T.J., Roe, M.T., Chen, A.Y., Patel, M.R., Washam, J.B., Ohman, E.M., Peacock, W.F., Pollack, C.V., Gibler, W.B., Peterson, E.D. Am. Heart J. (2005) [Pubmed]
  11. Achieving improvement through nursing home quality measurement. Harris, Y., Clauser, S.B. Health care financing review. (2002) [Pubmed]
  12. Computerized outcomes analysis for congenital heart disease. Jacobs, J.P., Maruszewski, B. Curr. Opin. Pediatr. (2005) [Pubmed]
  13. Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration. Selim, A.J., Berlowitz, D., Fincke, G., Rogers, W., Qian, S., Lee, A., Cong, Z., Selim, B.J., Ren, X.S., Rosen, A.K., Kazis, L.E. International journal for quality in health care : journal of the International Society for Quality in Health Care / ISQua. (2006) [Pubmed]
  14. Growing importance of capitation in Switzerland. Beck, K. Health care management science. (2000) [Pubmed]
  15. Risk adjustment of quality indicators in French long term care facilities for elderly people. A preliminary study. Moty, C., Barberger-Gateau, P., De Sarasqueta, A.M., Teare, G.F., Henrard, J.C. Revue d'épidémiologie et de santé publique. (2003) [Pubmed]
 
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