Effects of a mobility monitoring system on the cost of care in relation to reimbursement at Swiss nursing homes: learnings from a randomized controlled trial

Abstract

Background/objectiveNursing homes in Switzerland are under pressure to efficiently coordinate staff activities to cover their personnel costs under the care financing system. In this study, the use of a mobility monitoring system accompanied with case conferences was investigated in order to improve sleep quality and estimate the cost benefit of this intervention.MethodIn an open two-phase randomized controlled trial at three nursing homes, residents with cognitive impairment were randomly assigned to an intervention group and a control group. In the intervention group, a 10-week period of intensive use of the monitoring system and case conferences led by an advanced nurse practitioner (Phase I) was followed by 3 months of reduced use of the monitoring system and case conferences led by an internal registered nurse (Phase II). In the control group, the monitoring system was only used for data acquisition. Nurses reported the activities with a specifically developed tool. Based on the recorded activities, the cost of care was calculated. The correlating reimbursement per patient was calculated from the care levels in the Swiss reimbursement system. Data from 44 residents was included in the analysis with a linear mixed model.ResultsAlthough analysis revealed no statistically significant effects, results indicate that the use of a monitoring system can guide nurses in organizing their tasks to increase effectiveness. Information systems such as the mobility monitor can help to identify single outliers that do not correspond with the overall situation.ConclusionIn the health care system, problematic individual cases can account for a disproportionally high cost levels. It was shown that information systems can have a significant economic impact in the long run.Trial registrationThe study is registered at the German Clinical Trials Register under the Nr. DRKS-ID: DRKS00006829.

Towards Responsible Implementation of Monitoring Technologies in Institutional Care

“…For example, Niemeijer and colleagues (2014) found that implementing monitoring technologies led to cutbacks in the number of nighttime providers. However Stark and colleagues (2017) found that the use of such technology did not reduce the level of care provided or its associated cost. In fact, they found that the level of care increased significantly in both the intervention group and in the control group.…”

“…There is growing interest in collecting such data in institutional settings both continuously and passively using “intelligent” systems made up of multiple interconnected devices and artificial intelligence ( Stark, Tietz, Gattinger, Hantikainen, & Ott, 2017 ). A key assumption underpinning this interest is that technological monitoring is less intrusive than traditional methods (e.g., direct observation) and that it can enable “just-in-time” intervention with more accurate and reliable collection and processing of data ( Laplante et al, 2018 ; Potter et al, 2017 ).…”

“…Providers report that monitoring technologies disrupt their usual workflow and practices (e.g., structured care routines, infection control) and that responding to triggered alarms interferes with other (parallel) activities ( Coahran et al, 2018 ; Potter et al, 2017 ; Timmons et al, 2019 ). High rates of “false alarms” also lead to desensitization and inspire lack of trust in these technologies, both of which decrease providers’ response time and their continued engagement in traditional monitoring (e.g., nightly rounds) ( Coahran et al, 2018 ; Niemeijer et al, 2014 ; Potter et al, 2017 ; Stark et al, 2017 ; Timmons et al, 2019 ). Finally, technical malfunctioning and regular maintenance of the technologies create additional work for providers who have to not only care for patients, but also for the technologies to ensure that they operate smoothly (e.g., resetting the system, retrieving devices that are moved, recharging ( Fisher & Monahan, 2008 ; Niemeijer et al, 2014 ; Potter et al, 2017 ; Stark et al, 2017 ; Timmons et al, 2019 ).…”