Background: Patient safety is a priority for all healthcare institutions, mainly for ethical reasons but also for the related economic issues. For implementing effective safety improvement programs, it is necessary to monitor processes and assess performances. Statistical process control is a useful methodology for monitoring performance and processes and healthcare literature suggests the use of control charts for monitoring patient safety metrics. Challenges may occur when applying statistical quality improvement methods often due to the difficulty of combining commercial software with the hospitals information systems. Furthermore, commercial software for control charts can be expensive for hospital units that often struggle with budget constraints. Objectives: In this work, we describe the experience of the AUSL of Romagna that designed, developed and implemented desktop application to obtain control charts for monitoring inpatient falls. Methodology: A multidisciplinary team created a software tool based on R, an open source software for statistical computing, that properly combined with the existing hospital information system, allows, upon request, to generate a Shewhart u-control chart for monitoring the monthly falls rates. The tool had been implemented in twenty nine hospital units. Results: The main results indicated that control charts, not only allowed to increase process understanding by assessing the process’ steady-state behavior and identifying changes that indicate either improvement or deterioration safety performance, but also enabled hospital safety managers to identify some critical issues in data collection. Consequently, where necessary, improvement actions had been implemented. It is worth noting that the use of open source software led to a considerable cost reduction and made the customization of the software tool easy. Adverse events cannot be completely eliminated. However, the experience gained by the AUSL of Romagna developing this project has shown that the use of an automatic real-time monitoring system is very effective in reducing the time dedicated to the bureaucratic aspects of patient safety. This allows healthcare professionals to spend more time on the substance of patient safety.
Nunzia Boccaforno, E.P. (2020). Process control charts in falls prevention: the work path and the experience developed in the AUSL of Romagna. Milano : Università Bocconi, Centre for Research on Health and Social Care Management (CERGAS).
Process control charts in falls prevention: the work path and the experience developed in the AUSL of Romagna
Michele Scagliarini
2020
Abstract
Background: Patient safety is a priority for all healthcare institutions, mainly for ethical reasons but also for the related economic issues. For implementing effective safety improvement programs, it is necessary to monitor processes and assess performances. Statistical process control is a useful methodology for monitoring performance and processes and healthcare literature suggests the use of control charts for monitoring patient safety metrics. Challenges may occur when applying statistical quality improvement methods often due to the difficulty of combining commercial software with the hospitals information systems. Furthermore, commercial software for control charts can be expensive for hospital units that often struggle with budget constraints. Objectives: In this work, we describe the experience of the AUSL of Romagna that designed, developed and implemented desktop application to obtain control charts for monitoring inpatient falls. Methodology: A multidisciplinary team created a software tool based on R, an open source software for statistical computing, that properly combined with the existing hospital information system, allows, upon request, to generate a Shewhart u-control chart for monitoring the monthly falls rates. The tool had been implemented in twenty nine hospital units. Results: The main results indicated that control charts, not only allowed to increase process understanding by assessing the process’ steady-state behavior and identifying changes that indicate either improvement or deterioration safety performance, but also enabled hospital safety managers to identify some critical issues in data collection. Consequently, where necessary, improvement actions had been implemented. It is worth noting that the use of open source software led to a considerable cost reduction and made the customization of the software tool easy. Adverse events cannot be completely eliminated. However, the experience gained by the AUSL of Romagna developing this project has shown that the use of an automatic real-time monitoring system is very effective in reducing the time dedicated to the bureaucratic aspects of patient safety. This allows healthcare professionals to spend more time on the substance of patient safety.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.