Data-driven identification of risk factors of patient satisfaction at a large urban academic medical center

Background: The Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey is the first publicly reported nationwide survey to evaluate and compare hospitals. Increasing patient satisfaction is an important goal as it aims to achieve a more effective and efficient healthcare delivery system. In this study, we develop and apply an integrative, data-driven approach to identify clinical risk factors that associate with patient satisfaction outcomes. Methods: We included 1,771 unique adult patients who completed the HCAHPS survey and were discharged from the inpatient Medicine service from 2010 to 2012. We collected 266 clinical features including patient demographics, lab measurements, medications, disease categories, and procedures. We developed and applied a data-driven approach to identify risk factors that associate with patient satisfaction outcomes. Findings: We identify 102 significant risk factors associating with 18 surveyed questions. The most significantly recurrent clinical risk factors were: self-evaluation of health, education level, Asian, White, treatment in BMT oncology division, being prescribed a new medication. Patients who were prescribed pregabalin were less satisfied particularly in relation to communication with nurses and pain management. Explanation of medication usage was associated with communication with nurses (q = 0.001); however, explanation of medication side effects was associated with communication with doctors (q = 0.003). Overall hospital rating was associated with hospital environment, communication with doctors, and communication about medicines. However, patient likelihood to recommend hospital was associated with hospital environment, communication about medicines, pain management, and communication with nurse. Conclusions: Our study identified a number of putatively novel clinical risk factors for patient satisfaction that suggest new opportunities to better understand and manage patient satisfaction. Hospitals can use a data-driven approach to identify clinical risk factors for poor patient satisfaction to support development of specific interventions to improve patients' experience of care.