Determining the structure of psychiatric visit adherence [abstract]

Abstract

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 non-adherence (no-shows) costs the US mental health care system $100 billion annually and prevents the effective use of technology driven improvements to health care quality. Previous research into this seemingly intractable problem focuses either on specific patient demographics or on redundant scheduling methods, rather than discovering the actual structure of visit non-adherence. Researchers in this study propose greatly improved prediction of and prevention of visit non-adherence is possible through a structure that combines 3 classes of determinants (patient social- economic, clinical, and logistic) with a robust algorithm. This formative study builds upon knowledge gained from three preliminary studies (carried out by the same research team) to test 25 determinants collected retrospectively from common electronic data sources with statistical and data mining analysis methods to discover their relative prognostic ability. The objective, and expected outcome, is the development of a structure for visit non-adherence capable of supporting the development of prognostic tools suitable for use in ambulatory health care services delivery.