Decision-Making Process of Home and Social Care Professionals Using Telemonitoring of Activities of Daily Living for Risk Assessment: Embedded Mixed Methods Multiple-Case Study (Preprint)

BACKGROUND Older adults with cognitive deficits face difficulties in recalling daily challenges and lack self-awareness, impeding home care clinicians from obtaining reliable information on functional decline and home care needs and possibly resulting in suboptimal service delivery. Activity of daily living (ADL) telemonitoring has emerged as a tool to optimize evaluation of ADL home care needs. Using ambient sensors, ADL telemonitoring gathers information about ADL behaviors such as preparing meals and sleeping. However, there is a significant gap in understanding on how ADL telemonitoring data can be integrated into clinical reasoning to better target home care services. OBJECTIVE This paper aims to describe (1) how ADL telemonitoring data are used by clinicians to maintain care recipients with cognitive deficits at home and (2) the impact of ADL telemonitoring on home care service delivery. METHODS We used an embedded mixed methods multiple-case study design to examine 3 health institutions located in the greater Montreal region in Quebec that offer public home care services. An ADL telemonitoring system—Innovative Easy Assistance System–Support for Older Adults’ Autonomy (Soutien à l’autonomie des personnes âgées in French)—was deployed within these 3 health institutions for 4 years. Subcases (care recipient, informal caregiver, and clinicians) were embedded within each case. For this paper, we used the data collected during interviews (45-60 min) with clinicians only. Quantitative metadata were also collected on each service provided to care recipients before and after the implementation of NEARS-SAPA to triangulate the qualitative data. RESULTS We analyzed 27 subcases comprising 29 clinicians who completed 57 postimplementation interviews concerning 147 telemonitoring reports. Data analysis showed a 4-step decision-making process used by clinicians: (1) extraction of relevant telemonitoring data, (2) comparison of telemonitoring data with other sources of information, (3) risk assessment of the care recipient’s ADL performance and ability to remain at home, and (4) maintenance or modification of the intervention plan. Quantitative data reporting the number of services received allowed the triangulation of qualitative data pertaining to step 4. Overall, the results suggest a stabilization in monthly services after the introduction of the ADL telemonitoring system, particularly in cases where the number of services were increasing before its implementation. This is consistent with qualitative data indicating that, in light of the telemonitoring data, most clinicians decided to maintain the current intervention plan rather than increase or reduce services. CONCLUSIONS Results suggest that ADL telemonitoring contributed to service optimization on a case-by-case basis. ADL telemonitoring may have an important role in reassuring clinicians about their risk management and the appropriateness of service delivery, especially when questions remain regarding the relevance of services. Future studies may further explore the benefits of ADL telemonitoring for public health care systems with larger-scale implementation studies. INTERNATIONAL REGISTERED REPORT RR2-10.2196/52284