Diego A Martinez1,2,3, Jiarui Cai3,4, Jimi B Oke5,6, Andrew S Jarrell7, Felipe Feijoo8, Jeffrey Appelbaum3, Eili Klein1,9,10, Sean Barnes11, Scott R Levin1,2. 1. Department of Emergency Medicine, Johns Hopkins University, Baltimore, Maryland, USA. 2. Department of Health Sciences Informatics, Johns Hopkins University, Baltimore, Maryland, USA. 3. Department of Operations, Johns Hopkins Health System, Baltimore, Maryland, USA. 4. Department of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, Maryland, USA. 5. Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. 6. Department of Civil and Environmental Engineering, University of Massachusetts Amherst, Massachusetts, USA. 7. Department of Pharmacy, The Johns Hopkins Hospital, Baltimore, Maryland, USA. 8. Escuela de Ingeniería Industrial, Pontificia Universidad Católica de Valparaíso, Valparaíso, Chile. 9. Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland, USA. 10. Center for Disease Dynamics, Economics and Policy, Washington, DC, USA. 11. Department of Decision, Operations and Information Technologies, University of Maryland, College Park, Maryland, USA.
Abstract
OBJECTIVE: Timely availability of intravenous infusion pumps is critical for high-quality care delivery. Pumps are shared among hospital units, often without central management of their distribution. This study seeks to characterize unit-to-unit pump sharing and its impact on shortages, and to evaluate a system-control tool that balances inventory across all care areas, enabling increased availability of pumps. MATERIALS AND METHODS: A retrospective study of 3832 pumps moving in a network of 5292 radiofrequency and infrared sensors from January to November 2017 at The Johns Hopkins Hospital in Baltimore, Maryland. We used network analysis to determine whether pump inventory in one unit was associated with inventory fluctuations in others. We used a quasi-experimental design and segmented regressions to evaluate the effect of the system-control tool on enabling safe inventory levels in all care areas. RESULTS: We found 93 care areas connected through 67,111 pump transactions and 4 discernible clusters of pump sharing. Up to 17% (95% confidence interval, 7%-27%) of a unit's pump inventory was explained by the inventory of other units within its cluster. The network analysis supported design and deployment of a hospital-wide inventory balancing system, which resulted in a 44% (95% confidence interval, 36%-53%) increase in the number of care areas above safe inventory levels. CONCLUSIONS: Network phenomena are essential inputs to hospital equipment fleet management. Consequently, benefits of improved inventory management in strategic unit(s) are capable of spreading safer inventory levels throughout the hospital.
OBJECTIVE: Timely availability of intravenous infusion pumps is critical for high-quality care delivery. Pumps are shared among hospital units, often without central management of their distribution. This study seeks to characterize unit-to-unit pump sharing and its impact on shortages, and to evaluate a system-control tool that balances inventory across all care areas, enabling increased availability of pumps. MATERIALS AND METHODS: A retrospective study of 3832 pumps moving in a network of 5292 radiofrequency and infrared sensors from January to November 2017 at The Johns Hopkins Hospital in Baltimore, Maryland. We used network analysis to determine whether pump inventory in one unit was associated with inventory fluctuations in others. We used a quasi-experimental design and segmented regressions to evaluate the effect of the system-control tool on enabling safe inventory levels in all care areas. RESULTS: We found 93 care areas connected through 67,111 pump transactions and 4 discernible clusters of pump sharing. Up to 17% (95% confidence interval, 7%-27%) of a unit's pump inventory was explained by the inventory of other units within its cluster. The network analysis supported design and deployment of a hospital-wide inventory balancing system, which resulted in a 44% (95% confidence interval, 36%-53%) increase in the number of care areas above safe inventory levels. CONCLUSIONS: Network phenomena are essential inputs to hospital equipment fleet management. Consequently, benefits of improved inventory management in strategic unit(s) are capable of spreading safer inventory levels throughout the hospital.
Authors: Truls Ostbye; David F Lobach; Dianne Cheesborough; Ann Marie M Lee; Katrina M Krause; Vic Hasselblad; Darryl Bright Journal: J Med Syst Date: 2003-08 Impact factor: 4.460
Authors: Alisa J Hamilton; Alexandra T Strauss; Diego A Martinez; Jeremiah S Hinson; Scott Levin; Gary Lin; Eili Y Klein Journal: Antimicrob Steward Healthc Epidemiol Date: 2021-10-07