Do Patient Engagement IT Functionalities Influence Patient Safety Outcomes? A Study of US Hospitals.

OBJECTIVE: Patient engagement using health information technology (IT) functionalities can be a powerful tool in managing their own care for better health outcomes. Therefore, this study explores whether patient engagement IT functionalities and electronic health record (EHR) can affect patient safety outcomes. DESIGN: Using longitudinal study design for general acute care hospitals within the United States, we examine the interaction effects of EHR and patient engagement IT functionalities on patient safety outcomes (adverse incident rate) using a generalized estimating equation. SETTING: Our national sample consisted of 9759 hospital-year observations from 2014 to 2018. Overall, we found a significant association between adverse incident rate and patient engagement level and EHR adoption level. RESULTS: On average, as the combined effects of patient engagement level and EHR adoption level increases, the adverse incident rate decreases by approximately 0.49 (P < .01). Incorporating patient engagement functionalities is becoming an essential tool to improve health outcomes and will play an instrumental role in meeting meaningful use standards. CONCLUSIONS: Our study provides insights into the potential synergy between a hospital's existing EHR maturity and patient engagement health IT functionalities in affecting organizational performance. Organizational culture and capabilities pertinent to adopting patient engagement health IT functionalities infrastructure should be established first to provide the impetus for this synergy.

Intention to Use Behavioral Health Data From a Health Information Exchange: Mixed Methods Study.

BACKGROUND: Patients with co-occurring behavioral health and chronic medical conditions frequently overuse inpatient hospital services. This pattern of overuse contributes to inefficient health care spending. These patients require coordinated care to achieve optimal health outcomes. However, the poor exchange of health-related information between various clinicians renders the delivery of coordinated care challenging. Health information exchanges (HIEs) facilitate health-related information sharing and have been shown to be effective in chronic disease management; however, their effectiveness in the delivery of integrated care is less clear. It is prudent to consider new approaches to sharing both general medical and behavioral health information. OBJECTIVE: This study aims to identify and describe factors influencing the intention to use behavioral health information that is shared through HIEs. METHODS: We used a mixed methods design consisting of two sequential phases. A validated survey instrument was emailed to clinical and nonclinical staff in Alabama and Oklahoma. The survey captured information about the impact of predictors on the intention to use behavioral health data in clinical decision making. Follow-up interviews were conducted with a subsample of participants to elaborate on the survey results. Partial least squares structural equation modeling was used to analyze survey data. Thematic analysis was used to identify themes from the interviews. RESULTS: A total of 62 participants completed the survey. In total, 63% (n=39) of the participants were clinicians. Performance expectancy (ß=.382; P=.01) and trust (ß=.539; P<.001) predicted intention to use behavioral health information shared via HIEs. The interviewees (n=5) expressed that behavioral health information could be useful in clinical decision making. However, privacy and confidentiality concerns discourage sharing this information, which is generally missing from patient records altogether. The interviewees also stated that training for HIE use was not mandatory; the training that was provided did not focus specifically on the exchange of behavioral health information. CONCLUSIONS: Despite barriers, individuals are willing to use behavioral health information from HIEs if they believe that it will enhance job performance and if the information being transmitted is trustworthy. The findings contribute to our understanding of the role HIEs can play in delivering integrated care, particularly to vulnerable patients.

Predictors of Weight Change: Findings From an Employee Wellness Program.

Introduction: Employers are instituting employee wellness programs that include educational, lifestyle coaching, and weight and other condition management components to address obesity-related issues in the workplace. However, the findings of such wellness initiatives have been mixed. The purpose of this exploratory study is to determine whether the readiness for change measures are important predictors of weight loss in an employee wellness program. Methods: Retrospective data analysis of an employee wellness program conducted in the United States was conducted using data collected between 2014 and 2015 for people with BMI ≥ 30. These participants were assigned to one of two subprograms: weight management or condition management. We assessed the weight change within each program. Further, the relationship between weight change and readiness for change variables for weight, diet, and physical activity were examined by applying multiple linear regression and logistic regression models. The multivariable model included subprogram; gender; age; systolic and diastolic blood pressure; risk factor count; readiness for change for weight, activity, and diet; and stress level as covariates. Results: There were 209 participants in the weight management program and 243 participants in the condition management program who met the criteria for obesity, resulting in a final sample of 452 participants. On average, the weight change for these participants was -0.28 pounds (SD = 15.55) and there was no statistical difference between the weight change in the two programs. When compared to the reference group (maintenance), participants at the action stage of physical activity, on average, lost weight (b = -4.59, p = 0.02). Likewise, participants at the pre-contemplation stage of physical activity lost weight when compared to the maintenance group (b = -26.24, p = 0.000). Participants at the pre-contemplation stage of physical activity had higher odds of achieving at least 5% weight loss than participants at the maintenance stage (OR = 5.80, p = 0.053). Conclusion: Readiness for change for activity may be a predictor of weight change, and may predict the likelihood of achieving clinically significant weight loss. These findings can assist in targeting subjects for participation in such programs. The findings regarding the relationship between readiness for change and weight loss are counterintuitive, and further research is warranted in this area.