Where is my infusion pump? Harnessing network dynamics for improved hospital equipment fleet management

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.

Keywords: efficiency; electronic health records; machine learning; organizational; radio frequency identification device; systems analysis.

Figure 1.

Infusion pump sharing relationships between hospital units.

Figure 2.

Infusion pump sharing network in The Johns Hopkins Hospital. (A) The movement of PC unit (PCU)–type infusion pumps and (B) the movement of large-volume pump (LVP)–type infusion pumps. Each node represents a hospital unit (node number legend is presented in the Hospital Unit Name Glossary section of the Supplementary Appendix). The size of the nodes and the thickness of the ties are proportional to the volume of pump movement. The interior color of the nodes indicates cluster assignation based on eigencentrality. To measure if cluster assignation was statistically significant, we used the bootstrapping-based procedure presented in Fortunato and Hric to compare the observed clustering against random clustering in 1000 networks of same topology. All P values were <.001, and therefore we conclude that clustering presented in panels A and B are larger than expected by chance alone. (C) The network centrality distribution in each cluster. Analysis of standard deviation revealed that network centrality in the neurosciences cluster was much less variable than in the other clusters (P = .0436 and .0459 for neurosciences vs oncology and neurosciences vs perioperative, respectively; Flinger-Killen test of homogeneity of variances). No statistically significant differences in medians were detected (all P values >.05 in Kruskal-Wallis test of differences of medians).

Figure 3.

Effect of operational distance and sharing relationship from alters with reduced inventory on the probability of an ego reducing its inventory. (A) The mean effect of an ego’s operational proximity to other units with reduced inventory. Tukey's range test measured no statistically significant difference between degree of operational connectivity 1 and 2 (P = .89). (B) The mean effect of an ego’s pump-sharing relationships; a positive (ie, “+”) relationship with alters means that more infusion pumps were transferred from the alters to the ego on average during the study timeframe, negative (ie, “-”) means the opposite, and neutral (ie, “=”) means the average number of pump transactions between ego and alters was similar. Tukey's range test measured no statistically significant differences among positive, neutral, and negative relationships (Ps = .07, .43, and .37, respectively). D: degree.

Figure 4.

Hospital units above periodic automatic replenishment (PAR) level before vs after introduction of a quality improvement initiative to increase availability of infusion pumps in The Johns Hopkins Hospital, and timeline of events key to implementation. PAR level is the minimum amount of infusion pump inventory needed to meet the daily infusion therapy demand while providing a buffer in case of unexpected demand. (A) The percentage of hospital units that are above PAR level for PC unit (PCU)–type infusion pumps while (B) large-volume pump (LVP)–type infusion pumps. Individual data markers represent the average percentage of hospital units above PAR level at 7 a.m. displayed by week; solid lines represent predicted percentage from segmented regressions, including 95% confidence intervals. The arrows indicate key dates in the development and implementation of the quality improvement initiative. The asterisk indicates that segmented regressions include hourly bed occupancy and total number of pumps seen in the real-time location system (RTLS) as fixed effects. The letter a indicates the start of biweekly multidisciplinary discussions about how to increase infusion pump availability in hospital units through improved fleet management. The letter b indicates observation of infusion pump underutilization in units in which patients are commonly disconnected from infusion therapy and over utilization in units in which patients are commonly initiated on infusion therapy. The letter c indicates biweekly discussions about infusion pump utilization held with the infusion pump work workgroup. The letter d indicates that the electronic redistribution system is implemented for all hospital units. The letter e indicates the weekly electronic report to hospital operations leadership about the number of units at their required infusion pump inventory levels.