Relationship between electronic health records strategy and user satisfaction: a longitudinal study using clinicians' online reviews.

OBJECTIVE: We investigated how the electronic health records (EHRs) strategies concerning EHR sourcing and vendor switching impact user satisfaction over time. MATERIALS AND METHODS: This study used a novel longitudinal dataset created by scraping clinicians' Glassdoor.com reviews on 109 US health systems from 2012 to 2017 and combining it with the Healthcare Information and Management Systems Society (HIMSS) database. We performed sentiment analysis of clinician reviews to construct our main dependent variable, user satisfaction. Our main independent variables, EHR single sourcing and vendor switching, were constructed using the HIMSS database. RESULTS: Our fixed effects model showed that as health systems gain more experience with EHR, a single vendor sourcing strategy was associated with higher user satisfaction. Further, there was no significant impact of vendor switching on user satisfaction. CONCLUSION: This work adds to the current understanding of EHR-driven clinician burnout using a novel longitudinal dataset. We show how organizational-level EHR strategy can impact user satisfaction and that providers and EHR vendors can mine clinician reviews online to understand their evolving needs and sentiments.

Triple Aim and the Hospital Readmission Reduction Program.

OBJECTIVES: Despite substantial attention on hospital readmission rates, the impact of the Hospital Readmission Reduction Program (HRRP) on a comprehensive set of Triple Aim goals has not been studied: improve hospital quality, reduce cost, and improve patient experience. METHODS: We analyze inpatient claims data from 2006 to 2015 from the Dallas Fort Worth Hospital Council Foundation with a panel of 27,397 patients with chronic obstructive pulmonary disease and congestive heart failure. We deploy a quasi-natural experiment using a difference-in-difference specification to estimate the effect of HRRP effect on readmission rates, length of stay (LOS), and hospital satisfaction. RESULTS: We find that the likelihood of 30-day readmissions declined by 2.6%, average LOS decreased by 7.9%, and overall hospital rating increased by 2.1% among hospitals that fell under the scope of the HRRP, compared to non-HRRP hospitals. Our results provide evidence of a spillover effect of the HRRP in terms of its impact not only on Medicare patients, but across all insurance types, and other performance measures such as cost and patient experience. CONCLUSION: Our findings indicate that HRRP hospitals do not trade-off reductions in readmission rates with lower quality across other patient health outcomes. Rather, we find evidence that the HRRP has affected all 3 dimensions of the Triple Aim with respect to patient and hospital outcomes.

User reactions to COVID-19 screening chatbots from reputable providers.

OBJECTIVES: The objective was to understand how people respond to coronavirus disease 2019 (COVID-19) screening chatbots. MATERIALS AND METHODS: We conducted an online experiment with 371 participants who viewed a COVID-19 screening session between a hotline agent (chatbot or human) and a user with mild or severe symptoms. RESULTS: The primary factor driving user response to screening hotlines (human or chatbot) is perceptions of the agent's ability. When ability is the same, users view chatbots no differently or more positively than human agents. The primary factor driving perceptions of ability is the user's trust in the hotline provider, with a slight negative bias against chatbots' ability. Asian individuals perceived higher ability and benevolence than did White individuals. CONCLUSIONS: Ensuring that COVID-19 screening chatbots provide high-quality service is critical but not sufficient for widespread adoption. The key is to emphasize the chatbot's ability and assure users that it delivers the same quality as human agents.