Electronic Health Record Usability When Caring for Children With Medical Complexity.

OBJECTIVES: To evaluate usability of and clinician satisfaction with the electronic health record (EHR) in the context of caring for children with medical complexity (CMC) at a large academic pediatric hospital and to identify key areas for targeted improvements. METHODS: Cross-sectional study of pediatric faculty and advanced practice providers across several pediatric specialties using an online Research Electronic Data Capture survey. EHR usability was measured with 6 validated questions from the National Usability-Focused Health Information System Scale, and satisfaction with common EHR functionalities was measured with 6 original Likert-scale questions and 3 free-text questions. Results were analyzed with bivariate testing. RESULTS: More than half of providers completed the survey (n = 81, response rate 56%). When asked 6 positively-phrased, validated usability questions, a majority of respondents either agreed or were neutral. Respondents were most dissatisfied with information quality of the summary view and most satisfied with physician communication. Older respondents were less satisfied with EHR usability (P < .01). Focusing on functionalities needed for CMC, the majority of respondents were dissatisfied with the chart review process. More respondents were dissatisfied with order entry (P = .002) and documentation (P = .017) when caring for CMC compared with caring for other patients. The most cited challenges were locating recent patient data, performing an accurate medication reconciliation, and lack of specialized documentation templates. CONCLUSIONS: Clinicians are less satisfied with common EHR functionalities when caring for CMC compared with caring for all other patients. Targeted interventions to improve usability and common EHR functionalities for CMC are necessary to improve the user experience.

Social media: A new tool for outbreak surveillance.

Social media platforms allow users to share news, ideas, thoughts, and opinions on a global scale. Data processing methods allow researchers to automate the collection and interpretation of social media posts for efficient and valuable disease surveillance. Data derived from social media and internet search trends have been used successfully for monitoring and forecasting disease outbreaks such as Zika, Dengue, MERS, and Ebola viruses. More recently, data derived from social media have been used to monitor and model disease incidence during the coronavirus disease 2019 (COVID-19) pandemic. We discuss the use of social media for disease surveillance.