A Digital-First Health Care Approach to Managing Pandemics: Scoping Review of Pandemic Self-triage Tools.

BACKGROUND: During the COVID-19 pandemic, many patient-facing digital self-triage tools were designed and deployed to alleviate the demand for pandemic virus triage in hospitals and physicians' offices by providing a way for people to self-assess their health status and get advice on whether to seek care. These tools, provided via websites, apps, or patient portals, allow people to answer questions, for example, about symptoms and contact history, and receive guidance on appropriate care, which might be self-care. OBJECTIVE: This scoping review aimed to explore the state of literature on digital self-triage tools that direct or advise care for adults during a pandemic and to explore what has been learned about the intended purpose, use, and quality of guidance; tool usability; impact on providers; and ability to forecast health outcomes or care demand. METHODS: A literature search was conducted in July 2021 using MEDLINE, Embase, Scopus, PsycINFO, CINAHL, and Cochrane databases. A total of 1311 titles and abstracts were screened by 2 researchers using Covidence, and of these, 83 (6.76%) articles were reviewed via full-text screening. In total, 22 articles met the inclusion criteria; they allowed adults to self-assess for pandemic virus, and the adults were directed to care. Using Microsoft Excel, we extracted and charted the following data: authors, publication year and country, country the tool was used in, whether the tool was integrated into a health care system, number of users, research question and purpose, direction of care provided, and key findings. RESULTS: All but 2 studies reported on tools developed since early 2020 during the COVID-19 pandemic. Studies reported on tools that were developed in 17 countries. The direction of care advice included directing to an emergency room, seeking urgent care, contacting or seeing a physician, being tested, or staying at home and self-isolating. Only 2 studies evaluated tool usability. No study demonstrated that the tools reduce demand on the health care system, although at least one study suggested that data can predict demand for care and that data allow monitoring public health. CONCLUSIONS: Although self-triage tools developed and used around the world have similarities in directing to care (emergency room, physician, and self-care), they differ in important ways. Some collect data to predict health care demand. Some are intended for use when concerned about health status; others are intended to be used repeatedly by users to monitor public health. The quality of triage may vary. The high use of such tools during the COVID-19 pandemic suggests that research is needed to assess and ensure the quality of advice given by self-triage tools and to assess intended or unintended consequences on public health and health care systems.

Physician and Nonphysician Estimates of Positive Predictive Value in Diagnostic v. Mass Screening Mammography: An Examination of Bayesian Reasoning.

BACKGROUND: The same test with the same result has different positive predictive values (PPVs) for people with different pretest probability of disease. Representative thinking theory suggests people are unlikely to realize this because they ignore or underweight prior beliefs when given new information (e.g., test results) or due to confusing test sensitivity (probability of positive test given disease) with PPV (probability of disease given positive test). This research examines whether physicians and MBAs intuitively know that PPV following positive mammography for an asymptomatic woman is less than PPV for a symptomatic woman and, if so, whether they correctly perceive the difference. DESIGN: Sixty general practitioners (GPs) and 84 MBA students were given 2 vignettes of women with abnormal (positive) mammography tests: 1 with prior symptoms (diagnostic test), the other an asymptomatic woman participating in mass screening (screening test). Respondents estimated pretest and posttest probabilities. Sensitivity and specificity were neither provided nor elicited. RESULTS: Eighty-eight percent of GPs and 46% of MBAs considered base rates and estimated PPV in diagnosis greater than PPV in screening. On average, GPs estimated a 27-point difference and MBAs an 18-point difference, compared to actual of 55 or more points. Ten percent of GPs and 46% of MBAs ignored base rates, incorrectly assessing the 2 PPVs as equal. CONCLUSIONS: Physicians and patients are better at intuitive Bayesian reasoning than is suggested by studies that make test accuracy values readily available to be confused with PPV. However, MBAs and physicians interpret a positive in screening as more similar to a positive in diagnosis than it is, with nearly half of MBAs and some physicians wrongly equating the two. This has implications for overdiagnosis and overtreatment.

Injury prevention and risk communication: a mental models approach.

Individuals' decisions and behaviour can play a critical role in determining both the probability and severity of injury. Behavioural decision research studies peoples' decision-making processes in terms comparable to scientific models of optimal choices, providing a basis for focusing interventions on the most critical opportunities to reduce risks. That research often seeks to identify the 'mental models' that underlie individuals' interpretations of their circumstances and the outcomes of possible actions. In the context of injury prevention, a mental models approach would ask why people fail to see risks, do not make use of available protective interventions or misjudge the effectiveness of protective measures. If these misunderstandings can be reduced through context-appropriate risk communications, then their improved mental models may help people to engage more effectively in behaviours that they judge to be in their own best interest. If that proves impossible, then people may need specific instructions, not trusting to intuition or even paternalistic protection against situations that they cannot sufficiently control. The method entails working with domain specialists to elicit and create an expert model of the risk situation, interviewing lay people to elicit their comparable mental models, and developing and evaluating communication interventions designed to close the gaps between lay people and experts. This paper reviews the theory and method behind this research stream and uses examples to discuss how the approach can be used to develop scientifically validated context-sensitive injury risk communications.