Abstract
This paper describes a healthcare cost accounting system which is under development at Duke University Medical Center. Our approach differs from current practice in that this system will dynamically adjust its resource usage estimates to compensate for variations in patient risk levels. This adjustment is made possible by introducing a new cost accounting concept, Risk-Adjusted Quantity (RQ). RQ divides case-level resource usage variances into their risk-based component (resource consumption differences attributable to differences in patient risk levels) and their non-risk-based component (resource consumption differences which cannot be attributed to differences in patient risk levels). Because patient risk level is a factor in estimating resource usage, this system is able to simultaneously address the financial and quality dimensions of case cost management. In effect, cost-effectiveness analysis is incorporated into health care cost management.
Full text
PDF
Selected References
These references are in PubMed. This may not be the complete list of references from this article.
- Califf R. M., Harrell F. E., Jr, Lee K. L., Rankin J. S., Hlatky M. A., Mark D. B., Jones R. H., Muhlbaier L. H., Oldham H. N., Jr, Pryor D. B. The evolution of medical and surgical therapy for coronary artery disease. A 15-year perspective. JAMA. 1989 Apr 14;261(14):2077–2086. [PubMed] [Google Scholar]
- Dudley R. A., Harrell F. E., Jr, Smith L. R., Mark D. B., Califf R. M., Pryor D. B., Glower D., Lipscomb J., Hlatky M. Comparison of analytic models for estimating the effect of clinical factors on the cost of coronary artery bypass graft surgery. J Clin Epidemiol. 1993 Mar;46(3):261–271. doi: 10.1016/0895-4356(93)90074-b. [DOI] [PubMed] [Google Scholar]
- Eisenberg J. M. Clinical economics. A guide to the economic analysis of clinical practices. JAMA. 1989 Nov 24;262(20):2879–2886. doi: 10.1001/jama.262.20.2879. [DOI] [PubMed] [Google Scholar]
- Harris P. J., Harrell F. E., Jr, Lee K. L., Behar V. S., Rosati R. A. Survival in medically treated coronary artery disease. Circulation. 1979 Dec;60(6):1259–1269. doi: 10.1161/01.cir.60.6.1259. [DOI] [PubMed] [Google Scholar]
- Jollis J. G., Ancukiewicz M., DeLong E. R., Pryor D. B., Muhlbaier L. H., Mark D. B. Discordance of databases designed for claims payment versus clinical information systems. Implications for outcomes research. Ann Intern Med. 1993 Oct 15;119(8):844–850. doi: 10.7326/0003-4819-119-8-199310150-00011. [DOI] [PubMed] [Google Scholar]
- Lehmann H. P., Shortliffe E. H. Thomas: building Bayesian statistical expert systems to aid in clinical decision making. Comput Methods Programs Biomed. 1991 Aug;35(4):251–260. doi: 10.1016/0169-2607(91)90003-c. [DOI] [PubMed] [Google Scholar]
- Pryor D. B., Lee K. L. Methods for the analysis and assessment of clinical databases: the clinician's perspective. Stat Med. 1991 Apr;10(4):617–628. doi: 10.1002/sim.4780100412. [DOI] [PubMed] [Google Scholar]
- Smith L. R., Milano C. A., Molter B. S., Elbeery J. R., Sabiston D. C., Jr, Smith P. K. Preoperative determinants of postoperative costs associated with coronary artery bypass graft surgery. Circulation. 1994 Nov;90(5 Pt 2):II124–II128. [PubMed] [Google Scholar]