Predictors of patient adherence to follow-up recommendations after an ED visit.
BACKGROUND
It is unclear whether factors identified during the emergency department (ED) visit predict noncompliance with ED recommendations.


OBJECTIVE
We sought to determine predictors of adherence to medical recommendations after an ED visit.


METHODS
We conducted a prospective, observational study at a single urban medical center. Eligible ED patients provided baseline demographic data as well as information regarding insurance status, whether they had a primary care physician (PCP), and the impact of cost of care on their ability to follow medical recommendations. Patients were contacted at least 1 week after the ED visit and answered questions regarding adherence to medical recommendations.


RESULTS
Four hundred twenty-two patients agreed to participate in the study. At follow-up, 89.7% of patients reported that they had complied with recommendations made during the ED visit. Patients who were adherent to follow-up recommendations were more likely to have a primary care provider (odds ratio [OR], 2.6; 95% confidence interval [CI], 1.1-6.1), have an annual income of greater than $35000 (OR, 2.9; 95% CI, 1.2-7.2), and report a non-Hispanic ethnicity or race (OR, 2.8; 95% CI, 1.1-7.1). Individuals who reported that cost "sometimes" or "always" impacts their ability to follow their physician's recommendations were significantly less likely to comply with ED recommendations (OR, 2.7; 95% CI, 1.3-5.6).


CONCLUSIONS
Individuals who reported that cost affects their ability to follow their physician's recommendations and those who did not have a PCP were less likely to follow ED recommendations. Identification of predictors of noncompliance during the ED visit may aid in ensuring compliance with ED recommendations.
Department of Family and Preventive Medicine-Division of Public Health, University of Utah School of Medicine, Salt Lake City, UT.
Camille
C
Broadwater-Hollifield
Department of Surgery-Division of Emergency Medicine, University of Utah School of Medicine, Salt Lake City, UT.
Troy E
TE
Madsen
Department of Family and Preventive Medicine-Division of Public Health, University of Utah School of Medicine, Salt Lake City, UT.
Christina A
CA
Porucznik
Department of Family and Preventive Medicine-Division of Public Health, University of Utah School of Medicine, Salt Lake City, UT.
David N
DN
Sundwall
Department of Surgery-Division of Emergency Medicine, University of Utah School of Medicine, Salt Lake City, UT.
Scott T
ST
Youngquist
Department of Surgery-Division of Emergency Medicine, University of Utah School of Medicine, Salt Lake City, UT.
Kajsa
K
Vlasic
Department of Family and Preventive Medicine-Division of Public Health, University of Utah School of Medicine, Salt Lake City, UT.
Lisa H
LH
Gren
D000328:Adult; D016001:Confidence Intervals; D003365:Costs and Cost Analysis; D003430:Cross-Sectional Studies; D004636:Emergency Service, Hospital / Q000191:economics* / Q000706:statistics & numerical data; D005006:Ethnicity / Q000706:statistics & numerical data; D005260:Female; D005544:Forecasting / Q000379:methods; D006786:Hospitals, Urban; D006801:Humans; D007348:Insurance, Health / Q000191:economics* / Q000706:statistics & numerical data; D008297:Male; D010349:Patient Compliance / Q000706:statistics & numerical data*; D058007:Physicians, Primary Care / Q000191:economics* / Q000706:statistics & numerical data; D011446:Prospective Studies; D012044:Regression Analysis; D057566:Self Report; D012923:Social Class; D014146:Training Support / Q000191:economics / Q000706:statistics & numerical data; D014589:Utah