FACE-PC: Family centered care for older adults with multiple conditions in primary care

-
Investigator: Mijung Park, PhD, MPH, RN
Sponsor: NIH National Institute of Nursing Research

Location(s): United States

Description

 More than 60% of older adults have multiple chronic conditions and prevalence of depression is significantly higher among those with multimorbidity. Untreated/undertreated depression can lead to devastating consequences in individuals with chronic medical conditions. Thus, there is an urgent need to develop a health care model that targets this serious public health problem.

Comorbid depression and multiple medical conditions in older adults are a serious public health problem. As an important facilitator of health-related activities, families are already involved in various aspects of self-management of chronic disease in older adults. Despite the benefits they provide, informal caregiving activities currently are organized outside the medical system, which potentially creates redundant or misaligned efforts. Dr. Park's research targets patient- family dyads to optimize patients and their families' collective ability to self-manage chronic disease.
 
The purpose of this mentored research is to examine the feasibility and acceptability of the FACE-PC, a theory-driven, multi- component, technology-assisted interdisciplinary team-based care model that systematically involves family in chronic disease management. It aims to optimize the patient and family's collective ability to self-manage chronic disease. We will first refine the study protocol, using rapid cycle quality improvement approaches (Aim 1). We will then pilot test FACE-PC using mixed-methods of pragmatic clinical trial design and qualitative methodology (Aim 2). The three sub-Aims are to examine the feasibility and acceptability (Aim 2a); determine if there is evidence of the hypothesized directional effect (Aim 2b); and elicit participants' experience with FACE- PC via face-to-face exit interviews (Aim 2c). Concurrently, we will explore the feasibility of the researc methods for the subsequent R01 (Aim 3).