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Health information technology is a leading cause of clinician burnout and career dissatisfaction, often because it is poorly designed by nonclinicians who have limited knowledge of clinicians' information needs and health care workflow.Describe how we engaged primary care clinicians and their patients in an iterative design process for a software application to enhance clinician-patient diet discussions.Descriptive study of the steps followed when involving clinicians and their at-risk patients in the design of the content, layout, and flow of an application for collaborative dietary goal setting. This began with individual clinician and patient interviews to detail the desired informational content of the screens displayed followed by iterative reviews of intermediate and final versions of the program and its outputs.Primary care clinicians practicing in an urban federally qualified health center and two academic primary care clinics, and their patients who were overweight or obese with diet-sensitive conditions.Descriptions of the content, format, and flow of information from pre-visit dietary history to the display of evidence-based, guideline-driven suggested goals to final display of dietary goals selected, with information on how the patient might reach them and patients' confidence in achieving them.Through three iterations of design and review, there was substantial evolution of the program's content, format, and flow of information. This involved "tuning" of the information desired: from too little, to too much, to the right amount displayed that both clinicians and patients believed would facilitate shared dietary goal setting.Clinicians' well-founded criticisms of the design of health information technology can be mitigated by involving them and their patients in the design of such tools that clinicians may find useful, and use, in their everyday medical practice.

Objective To develop a computational system that uses dietary recall data to prioritize behavioral goals to facilitate efficient, personalized collaborative goal-setting in primary care. Use of Theory or Research The Chronic Care Model posits that synergy between the healthcare system and patient self-management will improve chronic disease outcomes. Thus, improving how diet is addressed in primary care could augment the benefit of dietary self-management. Collaborative goal-setting with primary care providers (PCPs) can facilitate patient behavior change. However, PCPs lack time and training to set effective diet goals with patients. NutriPCP aims to address this gap by presenting PCPs with a set of evidence-based goals prioritized using patient data. Target Audience PCPs Program Description NutriPCP uses ASA24 diet recall data to compute patient status for each of 9 previously developed, MyPlate-based goals (eg, “Make half my grains whole”). NutriPCP's inference engine consists of Python rule statements that synthesize a patient's data and compare it to evidence-based targets for nutrient consumption personalized for patient characteristics (eg, kcal intake/sex/age). PCPs are then presented with a list of the patient's status for each goal prioritized by degree of improvement needed. Evaluation Methods We tested our inference engine with test data (n = 12), and our team of nutrition, technology, and clinical experts validated the output. We used NHANES data to establish reasonable population-wide estimates. Results Testing revealed challenges for goal prioritization because datasets reflected consumption far from evidence-based targets. Therefore, we created standardized ranges to improve variability for relative ranking across goals. For goals with upper and lower limits (eg, “Reduce portion size”) we added warnings for inadequate intake. Conclusion We demonstrated that computational rules can automatically process recall data into prioritized behavioral goals. To our knowledge, this is the first system that personalizes MyPlate recommendations based on an individual's data. This has implications for nutrition education in primary care. Future research will examine implementation feasibility for PCPs and patients.