A Web-Based Patient Tool for Preventive Health

Background: The Internet is a promising medium for engaging the community in preventive care and health promotion, particularly among those who do not routinely access health care. Objective: The authors pilot-tested a novel website that translates evidence-based preventive health guidelines into a patient health education tool. The web-based tool allows individuals to enter their health risk factors and receive a tailored checklist of recommended preventive health services based on up-to-date guidelines from the US Preventive Services Task Force and the Advisory Committee on Immunization Practices. Methods: The authors conducted surveys and in-depth interviews among a purposive sample of adults from an urban African American community who pilot-tested the website in a standardized setting. Interviews were designed to assess the usability, navigability, and content of the website and capture patient perceptions about its educational value and usefulness. Each interview was audiotaped, transcribed, and examined using the constant comparative method. Results: Twenty-five participants piloted the tool: 96% found it easy to use and 64% reported learning something new. Many participants reported that, in addition to improving clinical preventive care (the intended purpose), the website could serve as a stand-alone tool to improve self-awareness and motivate behavior change. Conclusions: A web-based tool designed to translate preventive health guidelines for the community may serve the dual purpose of improving the delivery of preventive health care and encouraging health promotion. The website developed here is publicly available for use by practitioners and the community

Comparison of Diagnostic Recommendations from Individual Physicians versus the Collective Intelligence of Multiple Physicians in Ambulatory Cases Referred for Specialist Consultation

Background: Studies report higher diagnostic accuracy using the collective intelligence (CI) of multiple clinicians compared with individual clinicians. However, the diagnostic process is iterative, and unexplored is the value of CI in improving clinical recommendations leading to a final diagnosis. Methods: To compare the appropriateness of diagnostic recommendations advised by individual physicians versus the CI of physicians, we entered actual consultation requests sent by primary care physicians to specialists onto a web-based CI platform capable of collecting diagnostic recommendations (next steps for care) from multiple physicians. We solicited responses to 35 cases (12 endocrinology, 13 gynecology, 10 neurology) from ≥3 physicians of any specialty through the CI platform, which aggregated responses into a CI output. The primary outcome was the appropriateness of individual physician recommendations versus the CI output recommendations, using recommendations agreed upon by 2 specialists in the same specialty as a gold standard. The secondary outcome was the recommendations’ potential for harm. Results: A total of 177 physicians responded. Cases had a median of 7 respondents (interquartile range: 5–10). Diagnostic recommendations in the CI output achieved higher levels of appropriateness (69%) than recommendations from individual physicians (45%; χ2 = 5.95, P = 0.015). Of the CI recommendations, 54% were potentially harmful, as compared with 41% of individuals’ recommendations (χ2 = 2.49, P = 0.11). Limitations: Cases were from a single institution. CI was solicited using a single algorithm/platform. Conclusions: When seeking specialist guidance, diagnostic recommendations from the CI of multiple physicians are more appropriate than recommendations from most individual physicians, measured against specialist recommendations. Although CI provides useful recommendations, some have potential for harm. Future research should explore how to use CI to improve diagnosis while limiting harm from inappropriate tests/therapies

Bolstering diagnostic reasoning skills with adaptive learning

PurposeAdaptive learning emerges when precise assessment informs delivery of educational materials. This study will demonstrate how data from Human Dx, a case-based e-learning platform, can characterize an individual's diagnostic reasoning skills, and deliver tailored content to improve accuracy.MethodsPearson Chi-square analysis was used to assess variability in accuracy across three groups of participants (attendings, residents, and medical students) and three categories of cases (core medical, surgical, and other). Logistic regression analyses were conducted to explore the relationship between solve duration and accuracy. Mean accuracy and duration were calculated for 370 individuals. Repeated measures analysis of variance (ANOVA) were used to assess variability for an individual solver across the three categories.ResultsThere were significant differences in accuracy across the three groups and the three categories (p < 0.001). Individual solvers have significant variance in accuracy across the three categories. Shorter solve duration predicted higher accuracy. Patterns of performance were identified; four profiles are highlighted to demonstrate potential adaptive learning interventions.ConclusionsHuman Dx can assess diagnostic reasoning skills. When weaknesses are identified, adaptive learning strategies can push content to promote skill development. This has implications for customizing curricular elements to improve the diagnostic skills of healthcare professionals

Mobile phone diabetes project led to improved glycemic control and net savings for Chicago plan participants

Even with the best health care available, patients with chronic illnesses typically spend no more than a few hours a year in a health care setting, while their outcomes are largely determined by their activities during the remaining 5,000 waking hours of the year. As a widely available, low-cost technology, mobile phones are a promising tool to use in engaging patients in behavior change and facilitating self-care between visits. We examined the impact of a six-month mobile health (mHealth) demonstration project among adults with diabetes who belonged to an academic medical center’s employee health plan. In addition to pre-post improvements in glycemic control (p = 0.01) and patients’ satisfaction with overall care (p = 0.04), we observed a net cost savings of 8.8 percent. Those early results suggest that mHealth programs can support health care organizations’ pursuit of the triple aim of improving patients’ experiences with care, improving population health, and reducing the per capita cost of health care