Doing what matters most

In my pursuit of the JAMIA Editor-in-Chief position, I was inspired by Sandro Galea, a physician and epidemiologist, who argued in 2013 for a consequentialist epidemiology in which greater attention is paid to consequences as compared to deontological norms.¹ Derived from moral philosophy, the former focuses on the outcomes of actions while the latter emphasizes adherence to set of norms or rules for the actions, eg, in the instance of research, its methodological standards. In this, my first editorial, I share a few thoughts on what it would mean for JAMIA to reflect a consequentialist perspective.

Our field of biomedical and health informatics (including its subspecialties) has distinguished itself from the foundational sciences that inform it (eg, computer science, information science, decision science) by its motivation to improve human health, as illustrated by the definitions of biomedical informatics, nursing informatics, and clinical research informatics (Box 1).^2–4 There is no doubt that relevance to human health is fundamental to what we do as informaticians, but a consequentialist perspective requires doing what matters most⁵ to improving our outcome of interest—human health. This suggests the importance of focusing our informatics research and its translation in practice on important health issues (eg, cancer, Alzheimer’s disease, opioid use disorder, antimicrobial resistance, family caregiver role strain), upstream social determinants of health, and the challenges facing our healthcare system (eg, complexity, cost, suboptimal patient engagement, insufficient coordination, mismatch between clinician needs and the available tools to support them). Moreover, a consequentialist perspective requires constant attention to the “so what?” question.⁶

Box 1.

Example Definitions

• Biomedical informatics is the interdisciplinary field that studies and pursues the effective uses of biomedical data, information, and knowledge for scientific inquiry, problem solving, and decision making, motivated by efforts to improve human health.

• Clinical research informatics involves the use of informatics in the discovery and management of new knowledge relating to health and disease. It includes management of information related to clinical trials and also involves informatics related to secondary research use of clinical data. Clinical research informatics and translational bioinformatics are the primary domains related to informatics activities to support translational research.

• Nursing informatics is the specialty that integrates nursing science with multiple information management and analytical sciences to identify, define, manage, and communicate data, information, knowledge, and wisdom in nursing practice. Nursing informatics supports nurses, consumers, patients, the interprofessional healthcare team, and other stakeholders in their decision making in all roles and settings to achieve desired outcomes. This support is accomplished through the use of information structures, information processes, and information technology.

Aligned with a consequentialist approach, the first special focus issue during my tenure as Editor-in-Chief will be on health equity; details are provided in the Call for Papers (https://academic.oup.com/jamia/pages/cfp_health_equity). Several papers in the current issue are consistent with a consequentialist perspective, given the importance of the issues addressed to human health. For example, the mental health of military veterans is a major concern. Denneson et al⁷ demonstrate the influence of a web-based educational program for veterans who read their mental health notes online on their activation and perceived efficacy in healthcare interactions. Grasso et al⁸ lay the foundation for decreasing health disparities in lesbian, gay, bisexual, transgender, and queer people by presenting recommendations for planning and implementing the collection of accurate sexual orientation and gender identity information in electronic health records (EHRs). Zhan et al⁹ report a case study that combined survey and social media to address the significant public health issue of e-cigarette use and propose an innovative framework for social media data triangulation.

This does not mean that JAMIA will decrease its emphasis on theoretical soundness and methodological quality. In fact, the Editorial team has worked to expand our instructions to authors to provide additional guidance for data science, qualitative, and mixed methods submissions and plans to expand guidance in other areas. Several articles in this issue reflect advances in methodological approaches. Fareed et al¹⁰ extend the evidence base on studying portal use by applying a hierarchical clustering algorithm to audit log files of >200 inpatients; the resulting clusters suggest implications for tailored engagement approaches. Turer et al¹¹ report the development and validation of an algorithm that uses combinations of extractable EHR indicators (diagnosis codes, orders for laboratories, medications, and referrals) to detect recommended clinician behaviors: with attention to overweight/obesity/body mass index alone or with attention to hypertension/other comorbidities, or neither. Murray et al¹² adapt methods that allow for automated “noisy labeling” of positive and negative controls to create a machine learning silver standard as compared to a time-consuming clinician gold standard for identification of systemic lupus erythematosus. However, a consequentialist perspective implies the need for greater attention to generalizability and external validity rather than simply focusing on internal validity. For example, how representative are the study sample and setting as compared with the target population or setting, and the subsamples analyzed? With regard to increasing representativeness of study samples, Pfaff et al¹³ applied multiple informatics methods to create an electronic recruitment workflow that includes a vendor-based EHR and its associated portal with direct electronic messaging to potential recipients as well as REDCap. Although this workflow yielded lower enrollment rates than clinic recruitment, enrollment rates were higher than traditional letters, and the workflow yielded benefits in patient population access.

As you prepare your submissions to JAMIA, I ask you to think about the relevance to human health in terms of doing what matters most and to clearly delineate your answer to the “so what?” question.