BackgroundHealth information is increasingly being digitally stored and exchanged. The public is regularly collecting and storing health-related data on their own electronic devices and in the cloud. Diabetes prevention is an increasingly important preventive health measure, and diet and exercise are key components of this. Patients are turning to online programs to help them lose weight. Despite primary care physicians being important in patients’ weight loss success, there is no exchange of information between the primary care provider (PCP) and these online weight loss programs. There is an emerging opportunity to integrate this data directly into the electronic health record (EHR), but little is known about what information to share or how to share it most effectively. This study aims to characterize the preferences of providers concerning the integration of externally generated lifestyle modification data into a primary care EHR workflow.MethodsWe performed a qualitative study using two rounds of semi-structured interviews with primary care providers. We used an iterative design process involving primary care providers, health information technology software developers and health services researchers to develop the interface.ResultsUsing grounded-theory thematic analysis 4 themes emerged from the interviews: 1) barriers to establishing healthy lifestyles, 2) features of a lifestyle modification program, 3) reporting of outcomes to the primary care provider, and 4) integration with primary care. These themes guided the rapid-cycle agile design process of an interface of data from an online diabetes prevention program into the primary care EHR workflow.ConclusionsThe integration of external health-related data into the EHR must be embedded into the provider workflow in order to be useful to the provider and beneficial for the patient. Accomplishing this requires evaluation of that clinical workflow during software design. The development of this novel interface used rapid cycle iterative design, early involvement by providers, and usability testing methodology. This provides a framework for how to integrate external data into provider workflow in efficient and effective ways. There is now the potential to realize the importance of having this data available in the clinical setting for patient engagement and health outcomes.

Nonallergic rhinitis (NAR) subjects present clinically with similar symptoms to subjects with allergic rhinitis, but which mechanistically are not IgE- mediated. NAR is difficult to study because of multiple, as yet unknown, disease mechanisms and lack of biomarkers and diagnostic tests. The purpose of this proof of concept pilot study was to develop an environmental exposure chamber (EEC) model to simulate weather conditions in a controlled setting to objectively diagnose NAR subjects and ultimately to investigate novel NAR therapies. Thirty-seven subjects with a history of NAR confirmed by negative skin-prick test to a panel of aeroallergens were tested with cold dry air (CDA) and temperature change challenges. Objective (acoustic rhinometry [AcR] and nasal secretions) and subjective measures (total nasal symptom scores [TNSSs]: congestion, rhinorrhea, and postnasal drip [0-3]) were collected. Data was presented as mean ± SEM and statistical significance was assessed by paired t-test. The NAR EEC AcR responders to CDA had a significant decrease in mean minimal cross-sectional area (MCA; a measure of nasal patency) of 22.2 ± 2.43% (p < 0.0001) and 6.7 ± 7.22% (not statistically significant) at 30 and 60 minutes, respectively, with a concomitant increase in TNSS of 1.0 ± 0.24 U and 1.4 ± 0.30 U, respectively. AcR responders to temperature change showed a significant decrease in mean MCA to warm air of 16.0 ± 3.82% (p < 0.001) and 19.4 ± 3.88% (p < 0.0001) at 30 and 60 minutes, respectively, with an increase of TNSS of 0.4 ± 0.25 U and 0.4 ± 0.27 U, respectively. With rapid conversion to cold air, further decrease in mean MCA accompanied by an increase in TNSS was observed at 30 and 60 minutes. Increase in rhinorrhea was highest for CDA and the cold air phase of the temperature change challenge. Using the NAR EEC model, significant symptoms were induced in response to simulated weather changes in NAR patient responders. This proof of concept pilot study shows that the EEC model provides a consistent and reliable method to phenotype weather-induced NAR subjects that could be used to investigate disease mechanisms and novel therapies for NAR.

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