Predictors of Healthcare Utilization in Family Caregivers of Persons with a Primary Malignant Brain Tumor

Authors: Isabella Goldberg, Dr. Paula Sherwood, Dr. Susan Sereika, Dr. Hedi Donovan and Jason Weimer Faulty Mentor: Dr. Paula Sherwood Department: Acute and Tertiary Care University of Pittsburgh, School of Nursing 366 Victoria Bldg, 3500 Victoria Street, Pittsburgh, PA 15261

Background: The established link between providing care and negative outcomes in caregivers’ physical health provides support for the hypothesis that caregivers under more stress may have an increase in healthcare utilization. The purpose of this analysis is to determine sociodemographic, physical, and clinical characteristics associated with differential markers of healthcare utilization. 
Methods: Data from 110 caregivers of persons with a brain tumor were obtained from a NIH-funded trial (R01-NR013170; Co-PIs Sherwood and Donovan). Baseline self-report data regarding health care utilization (HCU) were utilized for this analysis. HCU was operationalized as: 1) number of visits to primary care providers, 2) nature of the visit, 3) number of prescription medications, 4) number of comorbid conditions, and 5) change in comorbid conditions. Predictors included caregiver gender, age, insurance status, relationship to care recipient, depressive symptoms (Center for Epidemiologic Studies-Depression Scale), employment, number of hours providing care per day, care recipient tumor type, caregiver mastery (Pearlin and Schooler) and caregiver burden (Caregiver Reaction Assessment). Logistic and linear regression models were run separately for each outcome variable.
Results: Caregiver employment and burden significantly predicted number of primary care provider appointments (p=0.04 and p<0.01 respectively). Employment significantly (p=0.04) affected preventive versus illness related visit (along with a trend for depressive symptoms (p=0.07). Depressive symptoms, burden/self-esteem (trend) and burden/abandonment were significantly associated with whether comorbid conditions deteriorated (p<0.01, p= 0.07 and p<0.01). Age (p<0.01) and employment (p<0.01) were significantly associated with number of prescription medications. Age (p<0.01), depressive symptoms (trend, p=0.06) and caregiver burden/abandonment (p=0.03) were significantly associated with number of comorbid conditions. 
Conclusions: Findings suggest that both patient and caregiver characteristics affect HCU. Data also support the primary care provider’s role in identifying caregivers at risk for deteriorating health and increased HCU and intervene to help caregivers take adequate self-care measures. 

Additional Abstract Information

Presenter: Isabella Goldberg

Institution: University of Pittsburgh School of Nursing

Type: Poster

Subject: Nursing & Public Health

Status: Approved

Time and Location

Session: Poster 9
Date/Time: Wed 12:00pm-1:00pm
Session Number: 6017