Internal medicine residency programs were randomly assigned to standard duty-hour policies or to flexible policies without limits on shift length and time off. Interns in programs with flexible ...policies did not have a superior educational experience.
Nudge Units to Improve the Delivery of Health Care Patel, Mitesh S; Volpp, Kevin G; Asch, David A
New England journal of medicine/The New England journal of medicine,
01/2018, Volume:
378, Issue:
3
Journal Article
Peer reviewed
Open access
Key information and important choices are constantly being presented in health care. Yet often the frames or default options used are selected without attention to strategic goals. Creating a nudge ...unit in a health care system can lead to consistently better decisions.
Facebook language predicts depression in medical records Eichstaedt, Johannes C.; Smith, Robert J.; Merchant, Raina M. ...
Proceedings of the National Academy of Sciences - PNAS,
10/2018, Volume:
115, Issue:
44
Journal Article
Peer reviewed
Open access
Depression, the most prevalent mental illness, is underdiagnosed and undertreated, highlighting the need to extend the scope of current screening methods. Here, we use language from Facebook posts of ...consenting individuals to predict depression recorded in electronic medical records. We accessed the history of Facebook statuses posted by 683 patients visiting a large urban academic emergency department, 114 of whom had a diagnosis of depression in their medical records. Using only the language preceding their first documentation of a diagnosis of depression, we could identify depressed patients with fair accuracy area under the curve (AUC) = 0.69, approximately matching the accuracy of screening surveys benchmarked against medical records. Restricting Facebook data to only the 6 months immediately preceding the first documented diagnosis of depression yielded a higher prediction accuracy (AUC = 0.72) for those users who had sufficient Facebook data. Significant prediction of future depression status was possible as far as 3 months before its first documentation. We found that language predictors of depression include emotional (sadness), interpersonal (loneliness, hostility), and cognitive (preoccupation with the self, rumination) processes. Unobtrusive depression assessment through social media of consenting individuals may become feasible as a scalable complement to existing screening and monitoring procedures.
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BFBNIB, NMLJ, NUK, PNG, SAZU, UL, UM, UPUK
We studied whether medical conditions across 21 broad categories were predictable from social media content across approximately 20 million words written by 999 consenting patients. Facebook language ...significantly improved upon the prediction accuracy of demographic variables for 18 of the 21 disease categories; it was particularly effective at predicting diabetes and mental health conditions including anxiety, depression and psychoses. Social media data are a quantifiable link into the otherwise elusive daily lives of patients, providing an avenue for study and assessment of behavioral and environmental disease risk factors. Analogous to the genome, social media data linked to medical diagnoses can be banked with patients' consent, and an encoding of social media language can be used as markers of disease risk, serve as a screening tool, and elucidate disease epidemiology. In what we believe to be the first report linking electronic medical record data with social media data from consenting patients, we identified that patients' Facebook status updates can predict many health conditions, suggesting opportunities to use social media data to determine disease onset or exacerbation and to conduct social media-based health interventions.
Full text
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Several large technology companies including Apple, Google, and Samsung are entering the expanding market of population health with the introduction of wearable devices. This technology, worn in ...clothing or accessories, is part of a larger movement often referred to as the "quantified self." The notion is that by recording and reporting information about behaviors such as physical activity or sleep patterns, these devices can educate and motivate individuals toward better habits and better health. Here, Patel et al examine the use of wearable devices to effectively promote health behavior change.
New threats to effective scientific communication make it more difficult to separate science from science fiction in which patients can be harmed by misinformation or by misplaced trust. Researchers ...who produce objective science can no longer focus on simply disseminating the message, they must also defend that evidence from challenges to the validity and interpretation of their research and, at times, be proactive to ensure that unsubstantiated messages do not compete with the correct message. Scientific information and misinformation are amplified through social media and as those channels become vulnerable to scientific integrity, there are opportunities to develop countermeasures and specific strategies for vigilance and response.
Interventions that address socioeconomic determinants of health are receiving considerable attention from policy makers and health care executives. The interest is fueled in part by expected returns ...on investment. However, many current estimates of returns on investment are likely overestimated, because they are based on pre-post study designs that are susceptible to regression to the mean. We present a return-on-investment analysis that is based on a randomized controlled trial of Individualized Management for Patient-Centered Targets (IMPaCT), a standardized community health worker intervention that addresses unmet social needs for disadvantaged people. We found that every dollar invested in the intervention would return $2.47 to an average Medicaid payer within the fiscal year.
IMPORTANCE: It is unknown how much the mortality of patients with coronavirus disease 2019 (COVID-19) depends on the hospital that cares for them, and whether COVID-19 hospital mortality rates are ...improving. OBJECTIVE: To identify variation in COVID-19 mortality rates and how those rates have changed over the first months of the pandemic. DESIGN, SETTING, AND PARTICIPANTS: This cohort study assessed 38 517 adults who were admitted with COVID-19 to 955 US hospitals from January 1, 2020, to June 30, 2020, and a subset of 27 801 adults (72.2%) who were admitted to 398 of these hospitals that treated at least 10 patients with COVID-19 during 2 periods (January 1 to April 30, 2020, and May 1 to June 30, 2020). EXPOSURES: Hospital characteristics, including size, the number of intensive care unit beds, academic and profit status, hospital setting, and regional characteristics, including COVID-19 case burden. MAIN OUTCOMES AND MEASURES: The primary outcome was the hospital’s risk-standardized event rate (RSER) of 30-day in-hospital mortality or referral to hospice adjusted for patient-level characteristics, including demographic data, comorbidities, community or nursing facility admission source, and time since January 1, 2020. We examined whether hospital characteristics were associated with RSERs or their change over time. RESULTS: The mean (SD) age among participants (18 888 men 49.0%) was 70.2 (15.5) years. The mean (SD) hospital-level RSER for the 955 hospitals was 11.8% (2.5%). The mean RSER in the worst-performing quintile of hospitals was 15.65% compared with 9.06% in the best-performing quintile (absolute difference, 6.59 percentage points; 95% CI, 6.38%-6.80%; P < .001). Mean RSERs in all but 1 of the 398 hospitals improved; 376 (94%) improved by at least 25%. The overall mean (SD) RSER declined from 16.6% (4.0%) to 9.3% (2.1%). The absolute difference in rates of mortality or referral to hospice between the worst- and best-performing quintiles of hospitals decreased from 10.54 percentage points (95% CI, 10.03%-11.05%; P < .001) to 5.59 percentage points (95% CI, 5.33%-5.86%; P < .001). Higher county-level COVID-19 case rates were associated with worse RSERs, and case rate declines were associated with improvement in RSERs. CONCLUSIONS AND RELEVANCE: Over the first months of the pandemic, COVID-19 mortality rates in this cohort of US hospitals declined. Hospitals did better when the prevalence of COVID-19 in their surrounding communities was lower.
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