The Economic and Clinical Efficiency of Point-of-Care Testing for Critically Ill Patients: A Decision-Analysis Model

Michael T. Halpern, Cynthia S. Palmer, Kit N. Simpson, Francis D. Chesley, Bryan R. Luce, Johan P. Suyderhoud, Bonnie V. Neibauer, Fawzy G. Estafanous

Research output: Contribution to journalArticle

29 Scopus citations

Abstract

Our study objective was to assess economic and clinical outcomes of use of a point-of-care (POC) blood analysis device for postoperative coronary artery bypass graft (CABG) patients. A decision analytic model was developed for patients with high expected use of blood analysis, high potential benefit from rapid turn around time of results, a large annual volume of patients, and substantial expense associated with surgery. Published literature and clinical experts provided incidence, outcome, and cost estimates associated with four clinical scenarios potentially influenced by POC testing (ventricular arrhythmias, cardiac arrest, severe postoperative bleeding, and iatrogenic anemia). We found that changes in clinical outcomes were predominantly dependent on comparative turn around time or CABG patient volume. The positive clinical impact of using POC testing was consistently associated with a positive economic impact. POC blood gas analysis may be associated with decreased incidence of adverse clinical events or earlier detection of such events, resulting in significant cost savings. This study also supports previous findings that the costs of STAT blood analysis are more personnel-related than equipment-related.

Original languageEnglish (US)
Pages (from-to)3-12
Number of pages10
JournalAmerican Journal of Medical Quality
Volume13
Issue number1
DOIs
StatePublished - Jan 1 1998

ASJC Scopus subject areas

  • Health Policy

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    Halpern, M. T., Palmer, C. S., Simpson, K. N., Chesley, F. D., Luce, B. R., Suyderhoud, J. P., Neibauer, B. V., & Estafanous, F. G. (1998). The Economic and Clinical Efficiency of Point-of-Care Testing for Critically Ill Patients: A Decision-Analysis Model. American Journal of Medical Quality, 13(1), 3-12. https://doi.org/10.1177/106286069801300102