Quantifying opportunities for hospital cost control: medical device purchasing and patient discharge planning

To quantify the potential reduction in hospital costs from adoption of best local practices in supply chain management and discharge planning. We performed multivariate statistical analyses of the association between total variable cost per procedure and medical device price and length of stay, cont...

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Veröffentlicht in:The American journal of managed care 2014-09, Vol.20 (9), p.e418-e424
Hauptverfasser: Robinson, James C, Brown, Timothy T
Format: Artikel
Sprache:eng
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Zusammenfassung:To quantify the potential reduction in hospital costs from adoption of best local practices in supply chain management and discharge planning. We performed multivariate statistical analyses of the association between total variable cost per procedure and medical device price and length of stay, controlling for patient and hospital characteristics. Ten hospitals in 1 major metropolitan area supplied patient-level administrative data on 9778 patients undergoing joint replacement, spine fusion, or cardiac rhythm management (CRM) procedures in 2008 and 2010. The impact on each hospital of matching lowest local market device prices and lowest patient length of stay (LOS) was calculated using multivariate regression analysis controlling for patient demographics, diagnoses, comorbidities, and implications. Average variable costs ranged from $11,315 for joint replacement to $16,087 for CRM and $18,413 for spine fusion. Implantable medical devices accounted for a large share of each procedure's variable costs: 44% for joint replacement, 39% for spine fusion, and 59% for CRM. Device prices and patient length-of-stay exhibited wide variation across hospitals. Total potential hospital cost savings from achieving best local practices in device prices and patient length of stay are 14.5% for joint replacement, 18.8% for spine fusion;,and 29.1% for CRM. Hospitals have opportunities for cost reduction from adoption of best local practices in supply chain management and discharge planning.
ISSN:1088-0224
1936-2692