Open science, COVID-19, and the news: Exploring controversies in the circulation of early SARS-CoV-2 genomic epidemiology research.

Some early English language news coverage of COVID-19 epidemiology focused on studies that examined how SARS-CoV-2 (the coronavirus that causes COVID-19) was evolving at the genetic level. The use of phylogenetic methods to analyse pathogen genetic sequence data to understand disease dynamics is called 'molecular' or 'genomic' epidemiology. Many research groups in this subfield utilise open science practices, which can involve the circulation of early unreviewed findings on publicly-accessible venues online. From March to May 2020, media outlets covered early SARS-CoV-2 genomic studies that claimed to have discovered types of SARS-CoV-2 that had mutated to be more transmissible. We use methods from Science and Technology Studies (STS) to examine three cumulative cases in which unripe facts about SARS-CoV-2 genomics moved out of scientific publics and into mainstream news. The three cases are: (1) 'A More "Aggressive" Strain of SARS-CoV-2?', (2) 'Eight SARS-CoV-2 Strains?', and (3) 'A "More Contagious," "Mutant" Strain?' In each case, findings were called into question and reporters' framing was overly sensational. We interpret the COVID-19 pandemic as a 'stress-test' for open science practices, and argue that it is important for stakeholders to understand changes in scientific publication and dissemination processes in the wake of the pandemic.

Alternatives to sharing COVID-19 data with law enforcement: Recommendations for stakeholders.

During the COVID-19 pandemic, in some jurisdictions, police have become involved in enforcing coronavirus-related measures. Relatedly, several North American jurisdictions have established COVID-19 data sharing protocols with law enforcement. Research across a range of fields has demonstrated that involving police in matters of public health disproportionately impacts the most vulnerable and does more harm than good. This is reflected in the consensus against COVID-19 criminalization that has emerged among civil society organizations focused on HIV, human rights, and harm reduction. The European Data Protection Board has also released guidelines against re-uses of COVID-19 data for law enforcement purposes. This article offers an overview of the harms of criminalizing illnesses and strategies for health stakeholders to seek alternatives to sharing COVID-19 data with police agencies while facilitating interoperability with healthcare first responders. It also presents case studies from two North American jurisdictions - Ontario and Minnesota - that have established routine COVID-19 data sharing with police. We recommended seven alternatives, including designating COVID-19 data as sensitive and implementing segmented interoperability with first responder agencies. These guidelines can help ensure that health information technology platforms do not become vehicles for the criminalization of COVID-19, and that health data stay within the health system.

Phenotyping as disciplinary practice: data infrastructure and the interprofessional conflict over drug use in California.

The narrative of the digital phenotype as a transformative vector in healthcare is nearly identical to the concept of "data drivenness" in other fields such as law enforcement. We examine the role of a prescription drug monitoring program (PDMP) in California-a computerized law enforcement surveillance program enabled by a landmark Supreme Court case that upheld "broad police powers"-in the interprofessional conflict between physicians and law enforcement over the jurisdiction of drug use. We bring together interview passages, clinical artifacts, and academic and gray literature to investigate the power relations between police, physicians, and patients to show that prescribing data appear to the physician as evidence of problematic patient behavior by the patients, and to law enforcement as evidence of physician misconduct. In turn, physicians have adopted a disciplinary approach to patients, using quasi-legalistic documents to litigate patient behavior. We conclude that police powers have been used to pave data infrastructure through a contested jurisdiction, and law enforcement have used that infrastructure to enroll physicians into the work of disciplining patients.

A scoping review of qualitative research in JAMIA: past contributions and opportunities for future work.

OBJECTIVE: Qualitative methods are particularly well-suited to studying the complexities and contingencies that emerge in the development, preparation, and implementation of technological interventions in real-world clinical practice, and much remains to be done to use these methods to their full advantage. We aimed to analyze how qualitative methods have been used in health informatics research, focusing on objectives, populations studied, data collection, analysis methods, and fields of analytical origin. METHODS: We conducted a scoping review of original, qualitative empirical research in JAMIA from its inception in 1994 to 2019. We queried PubMed to identify relevant articles, ultimately including and extracting data from 158 articles. RESULTS: The proportion of qualitative studies increased over time, constituting 4.2% of articles published in JAMIA overall. Studies overwhelmingly used interviews, observations, grounded theory, and thematic analysis. These articles used qualitative methods to analyze health informatics systems before, after, and separate from deployment. Providers have typically been the main focus of studies, but there has been an upward trend of articles focusing on healthcare consumers. DISCUSSION: While there has been a rich tradition of qualitative inquiry in JAMIA, its scope has been limited when compared with the range of qualitative methods used in other technology-oriented fields, such as human-computer interaction, computer-supported cooperative work, and science and technology studies. CONCLUSION: We recommend increased public funding for and adoption of a broader variety of qualitative methods by scholars, practitioners, and policy makers and an expansion of the variety of participants studied. This should lead to systems that are more responsive to practical needs, improving usability, safety, and outcomes.

How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

OBJECTIVE: The United States faces an opioid crisis. Integrating prescription drug monitoring programs into electronic health records offers promise to improve opioid prescribing practices. This study aimed to evaluate 2 different user interface designs for prescription drug monitoring program and electronic health record integration. MATERIALS AND METHODS: Twenty-four resident physicians participated in a randomized controlled experiment using 4 simulated patient cases. In the conventional condition, prescription opioid histories were presented in tabular format, and computerized clinical decision support (CDS) was provided via interruptive modal dialogs (ie, pop-ups). The alternative condition featured a graphical opioid history, a cue to visit that history, and noninterruptive CDS. Two attending pain specialists judged prescription appropriateness. RESULTS: Participants in the alternative condition wrote more appropriate prescriptions. When asked after the experiment, most participants stated that they preferred the alternative design to the conventional design. CONCLUSIONS: How patient information and CDS are presented appears to have a significant influence on opioid prescribing behavior.

Medication safety alert fatigue may be reduced via interaction design and clinical role tailoring: a systematic review.

OBJECTIVE: Alert fatigue limits the effectiveness of medication safety alerts, a type of computerized clinical decision support (CDS). Researchers have suggested alternative interactive designs, as well as tailoring alerts to clinical roles. As examples, alerts may be tiered to convey risk, and certain alerts may be sent to pharmacists. We aimed to evaluate which variants elicit less alert fatigue. MATERIALS AND METHODS: We searched for articles published between 2007 and 2017 using the PubMed, Embase, CINAHL, and Cochrane databases. We included articles documenting peer-reviewed empirical research that described the interactive design of a CDS system, to which clinical role it was presented, and how often prescribers accepted the resultant advice. Next, we compared the acceptance rates of conventional CDS-presenting prescribers with interruptive modal dialogs (ie, "pop-ups")-with alternative designs, such as role-tailored alerts. RESULTS: Of 1011 articles returned by the search, we included 39. We found different methods for measuring acceptance rates; these produced incomparable results. The most common type of CDS-in which modals interrupted prescribers-was accepted the least often. Tiering by risk, providing shortcuts for common corrections, requiring a reason to override, and tailoring CDS to match the roles of pharmacists and prescribers were the most common alternatives. Only 1 alternative appeared to increase prescriber acceptance: role tailoring. Possible reasons include the importance of etiquette in delivering advice, the cognitive benefits of delegation, and the difficulties of computing "relevance." CONCLUSIONS: Alert fatigue may be mitigated by redesigning the interactive behavior of CDS and tailoring CDS to clinical roles. Further research is needed to develop alternative designs, and to standardize measurement methods to enable meta-analyses.

Improving the design of California's prescription drug monitoring program.

OBJECTIVE: The US CDC identified prescription drug monitoring programs (PDMPs) as a tool to address the contemporary opioid crisis, but few studies have investigated PDMP usability and effectiveness from the users' perspective. Even fewer have considered how practices differ across medical domains. In this study, we aimed to address these gaps, soliciting perspectives on PDMPs from providers contending with the opioid crisis: physicians working in emergency departments (EDs) and pain management clinics. We aimed to provide practical design recommendations to improve PDMP workflow integration, as well as controlled substance history retrieval, interpretation, and decision support. METHODS: We conducted 16 in-depth semi-structured interviews with practicing emergency and pain physicians regarding their procedures, problems, and proposed solutions surrounding their use of CURES, California's PDMP. We investigated design problems in CURES by combining users' feedback with our usability inspection, drawing upon an extensive body of design literature. Then, we generated alternatives using design methods. RESULTS: We found CURES's design did not accommodate the unique information needs of different medical domains. Further, clinicians had trouble accessing CURES and retrieving patients' controlled substance histories, mainly due to usability problems that could be addressed with little technical adjustment. Additionally, CURES rendered patient histories in large, cluttered tables, devoid of overview or context, making interpretation difficult and precarious. Lastly, our interviewees had rarely noticed or used advanced features, such as decision support. DISCUSSION AND CONCLUSION: Usability barriers inhibited adoption and effective use. We provide practical recommendations for improving opioid control by way of improving PDMP design, based on interviewees' suggestions and research-based design principles. Our findings have implications for other disciplines, including surgery and primary care.

Thinking Together: Modeling Clinical Decision-Support as a Sociotechnical System.

Computerized clinical decision-support systems are members of larger sociotechnical systems, composed of human and automated actors, who send, receive, and manipulate artifacts. Sociotechnical consideration is rare in the literature. This makes it difficult to comparatively evaluate the success of CDS implementations, and it may also indicate that sociotechnical context receives inadequate consideration in practice. To facilitate sociotechnical consideration, we developed the Thinking Together model, a flexible diagrammatical means of representing CDS systems as sociotechnical systems. To develop this model, we examined the literature with the lens of Distributed Cognition (DCog) theory. We then present two case studies of vastly different CDSSs, one almost fully automated and the other with minimal automation, to illustrate the flexibility of the Thinking Together model. We show that this model, informed by DCog and the CDS literature, are capable of supporting both research, by enabling comparative evaluation, and practice, by facilitating explicit sociotechnical planning and communication.