Patient Heal Thyself: Reducing Hospital Readmissions with Technology‐Enabled Continuity of Care and Patient Activation

Abstract

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.

Chronic Patients’ Activation and Its Association with Stress, Anxiety, Depression, and Quality of Life: A Survey in Southeast Iran

“…This concept refers to the actions and activities performed by the patient to improve his/her illness. Patients being activated to manage their conditions had a positive effect on self-management and improved health outcomes [ 8 , 9 ]. Assessing patient activation after a life-threatening illness provides opportunities for healthcare providers to develop care plans tailored to the patients' needs before their discharges [ 10 ].…”

Unit work environment, psychological empowerment and support for patient activation among nurses

“…Patients who are actively involved in their own health care have better health outcomes and lower health care costs (Hibbard et al., 2013; Queenan et al., 2019). As patients interact more often with nurses than other health care professionals in hospital settings, nurses play a key role in improving the patients' self‐management skills (van Hooft et al., 2015).…”

“…Patient activation indicates the extent of patient engagement as an active agent in the self‐management of health with relevant knowledge, skills and confidence (Hibbard et al., 2004; Pelletier & Stichler, 2013). Patients with higher levels of activation have been found to have lower rates of hospital readmission and higher functional health status (Queenan et al., 2019; Yadav et al., 2020). Nurses, the largest group of health professionals in hospital settings, play a critical role in ensuring that patients are actively involved in decision‐making and self‐care management of their own health and care (Pelletier & Stichler, 2013).…”

OM Forum—Supply Chain Thinking in Healthcare: Lessons and Outlooks

“…The surge in data availability, in conjunction with growing computer power, has allowed healthcare analytics tools, such as AI and machine learning, to play an expanding role in the advancement of healthcare. For example, machine learning is now used to inform diagnosis (Miotto et al 2018), make predictions (Finlay 2018), develop prescriptive treatment algorithms (Champagne et al 2018, Jameson andLongo 2015a), reduce readmissions (Liu et al 2018, Queenan et al 2019, and objectively evaluate physicians (Foster et al 2018) (see Guha and Kumar (2018) for an overview of how big data analytics has been applied in the healthcare domain and for a roadmap of future research). Moreover, health information exchanges, facilitated by technologies like blockchain (Babich and Hilary 2019), may lead to more efficient hSCs by minimizing transaction costs and wastes (e.g., fraud, counterfeits).…”