JMIR Publications

ABSTRACT

Background:

With a world-wide increase in the elderly population, and an associated increase in healthcare utilization and costs, preventing avoidable emergency department visits and hospitalizations is becoming a global priority. A personal emergency response system (PERS), consisting of an alarm button and a means to establish a live connection to a response center, can help elderly live at home longer independently. In addition, individual risk assessment through predictive modeling can help indicate what PERS subscribers are at elevated risk of hospital transport, so that early intervention becomes possible.

Objective:

For a population of German PERS subscribers, the aim is to evaluate whether a case manager, supported by prediction models of hospital transport, can identify at-risk subscribers at an early stage and recommend targeted interventions to reduce the risk of hospitalization. The primary outcome of the study is the number of hospitalizations in the intervention and matched control groups.

Methods:

As part of the ‘Sicher Zuhause’ program, an intervention group of 500 PERS subscribers are tracked for a period of 8 months. During this period, risk scores are determined daily by a predictive model of hospital transport, and at-risk participants may receive phone calls from a case manager, who assesses the health status of the participant and recommends interventions. The healthcare utilization of the intervention group will be compared to a group of matched controls, retrospectively drawn from a population of PERS subscribers who receive no interventions.

Results:

Differences in healthcare utilization and costs between the intervention group and the matched controls will be determined based on reimbursement records. In addition, qualitative data will be collected on the participants’ satisfaction with the 'Sicher Zuhause' program and on the utilization of the interventions offered as part of the program.

Conclusions:

The evaluation of the study will offer insight into whether a combination of predictive analytics and case manager-driven interventions can help in avoiding hospital admissions for PERS subscribers in Germany living at home independently. In the future, this may lead to improved quality of life and reduced medical costs for the population of the study. Clinical Trial: Deutsches Register Klinischer Studien (DRKS), Trial ID: DRKS00017328.