Informatics for all: from provider- to patient-based applications that can include family and friends

Abstract

It is hard to believe that, just a decade ago, the technology of smart phones and the patient-centered healthcare movement were just starting to take off, and many of their current instantiations were not spelled out in visions of a connected healthcare system. Accordingly, informatics has evolved and expanded so fast in the past ten years that it is not a surprise that the volume, quality, and interest in scholarly articles describing the many facets of including providers and patients, as well as patients’ family and friends, in healthcare has increased so much that we are able to dedicate a full issue of JAMIA to research and applications in these areas. Kishore (p. 931) describes a model of the effects of online informational and emotional support on self-care behavior of HIV patients, Cheung (p. 955) evaluates a recommender app for measuring longitudinal user engagement in apps for depression and anxiety treatment, and Utrankar (p. 976) reports on technology use and preferences in supporting clinical practice guideline awareness and adherence in individuals with sickle cell disease. Additionally, Taylor (p. 989) describes the role of family and friends in helping older adults manage personal health information, while Sharko (p. 1008) describes the unique privacy needs of adolescent patients and the resulting complexity of the decision-making process. Different methods have been borrowed from various disciplines over time to fill the needs of provider-, patientand other caregiverfacing applications. Bautista (p. 1018) reports on a psychometric evaluation of a scale to measure nurses’ use of smartphones for work purposes, Reese (p. 1026) uses card sorting methods to elicit expert knowledge in an ICU setting, and Pandolfe (p. 1047) proposes an architecture for a medication reconciliation application that aims at increasing patient activation and education. While the intent of information systems is always to improve care and promote health, positive and negative consequences have been reported in the literature. In this issue of JAMIA, Nouri (p. 1089) systematically reviews criteria for assessing the quality of mHealth apps, Veinot (p. 1080) discusses how informatics interventions can worsen inequality, Meyerhoefer (p. 1054) reports on provider and patient satisfaction with the integration of ambulatory and hospital EHR systems, and Plante (p. 1074) reveals trends in user ratings and reviews of a blood pressure-measuring smartphone app. Increased data sharing of clinical data, partly due to the popularity of patient-facing applications and a realization that faster biomedical discoveries may happen with the use of “big data,” also brings important issues related to ethics and how information is relayed to users. Stahl (p. 1102) discusses the role of ethics in data governance of a large neuro-ICT project, Tao (p. 1036) discusses the effects of graphical formats of self-monitoring test results for consumers, Karpefors (p. 1069) proposes a visual summary of the incidence, significance, and temporal aspects of adverse events in clinical trials, and Wright (p. 1064) describes the development and evaluation of a user interface for reviewing clinical microbiology results. The increased availability of data for studies has yet to be paired with increased transparency of these data and analytical methods to allow easy reproduction of results. Coiera (p. 963) discusses whether health informatics suffers from replication issues. Particularly in the area of predictive models, it is important that data and methods be available to assess reproducibility and generalizability to other data sets. Reps (p. 969) proposes a standardized framework to generate and evaluate patient-level prediction models using observational healthcare data. This issue of JAMIA also includes several other articles in the area of predictive modeling: Abbas (p. 1000) describes a machine learning approach for early detection of autism, Goldstein (p. 924) proposes a model to predict ambulatory no-shows across different specialties and clinics, and KalpathyCramer (p. 945) reports on a distributed deep learning networks for medical imaging data. As the articles in this issue of JAMIA exemplify, the discipline of informatics has expanded into exciting new territory in which the intersection is no longer just of biomedical sciences and computer science, but rather of a variety of other domains involved in understanding how information systems can help improve healthcare, disease prevention and promote healthier behaviors. JAMIA has kept aligned with this expanded scope and will continue to bring the best scholarly work in informatics to our readers.