Using electronic data sources to understand the determinants of psychiatric visit non-adherence.
Technology cannot be effectively used to drive improvements in health care quality and health care cost reduction until significantly more healthcare visits are attended. Visit attendance is often perceived as an intractable problem. This formative study identified and analyzed a set of visit adherence determinants to delineate a structure of adherence. The study is distinguished from previous work because it employs three types of determinants (socio-economic, diagnosis, and logistical), captured from an ADT system and an EMR, to predict visit non-adherence.
Alafaireet
Patricia E
PE
Department of Health Management & Informatics, University of Missouri, Columbia, MO, USA.
Houghton
Howard L
HL
Savage
Grant T
GT
Gong
Yang
Y
D000555:Ambulatory Care Information Systems; D057225:Data Mining / Q000379:methods*; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D008499:Medical Records; D008605:Mental Health Services / Q000706:statistics & numerical data; D010349:Patient Compliance / Q000523:psychology*; D010865:Pilot Projects; D011570:Psychiatry; D012189:Retrospective Studies; D012959:Socioeconomic Factors