Health Care Utilization Trajectories Predict Nursing Home Entry Among People with MS

Thursday, June 2, 2016
Exhibit Hall
Marcia Finlayson, PhD, OT Reg (Ont), OTR , School of Rehabilitation Therapy, Queen's University, Kingston, ON, Canada
Ruth Ann Marrie, MD, PhD , University of Manitoba, Winnipeg, MB, Canada
Gregory S. Finlayson, PhD , Finlayson Consulting Inc., Kingston, ON, Canada
Okechukwu Ekuma, MSc , Manitoba Centre for Health Policy, Winnipeg, ON, Canada
Depeng Jiang, PhD , University of Manitoba, Winnipeg, ON, Canada

Background: People with MS often need increasing amounts of physical care over time, leading to nursing home (NH) entry for about 5-10% of them.  Identifying longitudinal patterns of health care utilization (HCU) that predict NH entry may aid in the early identification of individuals at risk and inform program and service development to support aging-in-place.

Objectives: To determine if 10-year HCU patterns for ambulatory physician use, prescription medication use, hospitalizations, and intensity of hospital care provide unique information about the likelihood of nursing home entry among people with MS.

Methods: We used population-based, de-identified claims data from the Population Health Research Data Repository at the Manitoba Centre for Health Policy. We applied a validated algorithm to identify all Manitobans with MS between 1984 and 2012. From this pool, cases were identified (NH entrant at any point since 2005). Cases were matched to controls (not resident in a nursing home since 2005) by age, sex, geographic region, and date of first demyelinating disease claim.

Using semi-parametric group-based trajectory approaches, we generated 10-year patterns of ambulatory physician visits, number of prescriptions, hospital days, and intensity of hospital care for all cases and controls.  Trajectory group membership was then entered into logistic regression models along with variables capturing continuity of care, major comorbidities, socioeconomic status, and urban/rural status in order to examine predictors of NH entry.

Results: We identified 226 cases and 896 controls (total =1122). The average age of the cases was 48.35 (SD=13.25) and 44.91 for the controls (SD=11.58). The percentage of females for the cases was 64%, and for the controls, 61%.  In model 1 (physician visits), higher utilization was protective of nursing home entry. In models 2 (hospitalizations), 3 (intensity of hospital care), and 4 (medication use), higher use predicted NH entry. Only in the physician visit model did the presence of comorbidities increase the likelihood of NH entry. 

Conclusions: Patterns of health care utilization over time predict the likelihood of nursing home entry among people with MS, even after accounting for sociodemographic and health related variables. These findings may help build a decision tool to aid early identification of people with MS on a trajectory to NH entry.