Premium
Patient Heal Thyself: Reducing Hospital Readmissions with Technology‐Enabled Continuity of Care and Patient Activation
Author(s) -
Queenan Carrie,
Cameron Kellas,
Snell Alan,
Smalley Julia,
Joglekar Nitin
Publication year - 2019
Publication title -
production and operations management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.279
H-Index - 110
eISSN - 1937-5956
pISSN - 1059-1478
DOI - 10.1111/poms.13080
Subject(s) - health care , continuity of care , intervention (counseling) , patient experience , patient care , nursing , process (computing) , measure (data warehouse) , psychology , medical emergency , medicine , computer science , data mining , economic growth , economics , operating system
Patients’ skills, knowledge, and motivation to actively engage in their health care are assessed with the patient activation measure ( PAM ). The literature on the role of PAM , when patient counseling is coupled with a technology enabled continuity of care intervention, is scant. We model the patient–health care provider feedback loop and learning through error corrections to explore the relations between continuity of care, PAM and patient readmissions. We test this model using data from a randomized, controlled field experiment. Our data show a direct effect of technology‐enabled continuity of care, together with its interaction with PAM , reduces readmissions over the base case without technology enabled continuity of care. Using exploratory analysis, we further show how a machine learning algorithm can be used to predict PAM , that can potentially furnish health care providers with useful information during the process of supporting their patients.