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1. Physician Stress During Electronic Health Record Inbox Work: In Situ Measurement With Wearable Sensors

   https://doi.org/10.2196/24014  

   Akbar, Fatema ; Mark, Gloria ; Prausnitz, Stephanie ; Warton, E Margaret ; East, Jeffrey A ; Moeller, Mark F ; Reed, Mary E ; Lieu, Tracy A ( January 2021 , JMIR Medical Informatics)

   null (Ed.)

   Background Increased work through electronic health record (EHR) messaging is frequently cited as a factor of physician burnout. However, studies to date have relied on anecdotal or self-reported measures, which limit the ability to match EHR use patterns with continuous stress patterns throughout the day. Objective The aim of this study is to collect EHR use and physiologic stress data through unobtrusive means that provide objective and continuous measures, cluster distinct patterns of EHR inbox work, identify physicians’ daily physiologic stress patterns, and evaluate the association between EHR inbox work patterns and physician physiologic stress. Methods Physicians were recruited from 5 medical centers. Participants (N=47) were given wrist-worn devices (Garmin Vivosmart 3) with heart rate sensors to wear for 7 days. The devices measured physiological stress throughout the day based on heart rate variability (HRV). Perceived stress was also measured with self-reports through experience sampling and a one-time survey. From the EHR system logs, the time attributed to different activities was quantified. By using a clustering algorithm, distinct inbox work patterns were identified and their associated stress measures were compared. The effects of EHR use on physician stress were examined using a generalized linear mixed effects model. Results Physicians spent an average of 1.08 hours doing EHR inbox work out of an average total EHR time of 3.5 hours. Patient messages accounted for most of the inbox work time (mean 37%, SD 11%). A total of 3 patterns of inbox work emerged: inbox work mostly outside work hours, inbox work mostly during work hours, and inbox work extending after hours that were mostly contiguous to work hours. Across these 3 groups, physiologic stress patterns showed 3 periods in which stress increased: in the first hour of work, early in the afternoon, and in the evening. Physicians in group 1 had the longest average stress duration during work hours (80 out of 243 min of valid HRV data; P=.02), as measured by physiological sensors. Inbox work duration, the rate of EHR window switching (moving from one screen to another), the proportion of inbox work done outside of work hours, inbox work batching, and the day of the week were each independently associated with daily stress duration (marginal R2=15%). Individual-level random effects were significant and explained most of the variation in stress (conditional R2=98%). Conclusions This study is among the first to demonstrate associations between electronic inbox work and physiological stress. We identified 3 potentially modifiable factors associated with stress: EHR window switching, inbox work duration, and inbox work outside work hours. Organizations seeking to reduce physician stress may consider system-based changes to reduce EHR window switching or inbox work duration or the incorporation of inbox management time into work hours. 

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2. Quantifying the impact of telemedicine and patient medical advice request messages on physicians' work-outside-work

   https://doi.org/10.1038/s41746-024-01001-2  

   Mandal, Soumik ; Wiesenfeld, Batia M. ; Mann, Devin M. ; Szerencsy, Adam C. ; Iturrate, Eduardo ; Nov, Oded ( February 2024 , npj Digital Medicine)

   The COVID-19 pandemic has boosted digital health utilization, raising concerns about increased physicians’ after-hours clinical work (work-outside-work”). The surge in patients’ digital messages and additional time spent on work-outside-work by telemedicine providers underscores the need to evaluate the connection between digital health utilization and physicians’ after-hours commitments. We examined the impact on physicians’ workload from two types of digital demands - patients’ messages requesting medical advice (PMARs) sent to physicians’ inbox (inbasket), and telemedicine. Our study included 1716 ambulatory-care physicians in New York City regularly practicing between November 2022 and March 2023. Regression analyses assessed primary and interaction effects of (PMARs) and telemedicine on work-outside-work. The study revealed a significant effect ofPMARs on physicians’ work-outside-work and that this relationship is moderated by physicians’ specialties. Non-primary care physicians or specialists experienced a more pronounced effect than their primary care peers. Analysis of their telemedicine load revealed that primary care physicians received fewerPMARs and spent less time in work-outside-work with more telemedicine. Specialists faced increasedPMARs and did more work-outside-work as telemedicine visits increased which could be due to the difference in patient panels. ReducingPMARvolumes and efficient inbasket management strategies needed to reduce physicians’ work-outside-work. Policymakers need to be cognizant of potential disruptions in physicians carefully balanced workload caused by the digital health services.

    

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3. The Impact of Telemedicine on Physicians’ After-hours Electronic Health Record “Work Outside Work” During the COVID-19 Pandemic: Retrospective Cohort Study

   https://doi.org/10.2196/34826  

   Lawrence, Katharine ; Nov, Oded ; Mann, Devin ; Mandal, Soumik ; Iturrate, Eduardo ; Wiesenfeld, Batia ( January 2022 , JMIR Medical Informatics)

   Background Telemedicine as a mode of health care work has grown dramatically during the COVID-19 pandemic; the impact of this transition on clinicians’ after-hours electronic health record (EHR)–based clinical and administrative work is unclear. Objective This study assesses the impact of the transition to telemedicine during the COVID-19 pandemic on physicians’ EHR-based after-hours workload (ie, “work outside work”) at a large academic medical center in New York City. Methods We conducted an EHR-based retrospective cohort study of ambulatory care physicians providing telemedicine services before the pandemic, during the acute pandemic, and after the acute pandemic, relating EHR-based after-hours work to telemedicine intensity (ie, percentage of care provided via telemedicine) and clinical load (ie, patient load per provider). Results A total of 2129 physicians were included in this study. During the acute pandemic, the volume of care provided via telemedicine significantly increased for all physicians, whereas patient volume decreased. When normalized by clinical load (ie, average appointments per day by average clinical days per week), telemedicine intensity was positively associated with work outside work across time periods. This association was strongest after the acute pandemic. Conclusions Taking physicians’ clinical load into account, physicians who devoted a higher proportion of their clinical time to telemedicine throughout various stages of the pandemic engaged in higher levels of EHR-based after-hours work compared to those who used telemedicine less intensively. This suggests that telemedicine, as currently delivered, may be less efficient than in-person–based care and may increase the after-hours work burden of physicians. 

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4. Fecundability in relation to use of mobile computing apps to track the menstrual cycle

   https://doi.org/10.1093/humrep/deaa176  

   Stanford, Joseph B ; Willis, Sydney K ; Hatch, Elizabeth E ; Rothman, Kenneth J ; Wise, Lauren A ( September 2020 , Human Reproduction)

   Abstract STUDY QUESTION To what extent does the use of mobile computing apps to track the menstrual cycle and the fertile window influence fecundability among women trying to conceive? SUMMARY ANSWER After adjusting for potential confounders, use of any of several different apps was associated with increased fecundability ranging from 12% to 20% per cycle of attempt. WHAT IS KNOWN ALREADY Many women are using mobile computing apps to track their menstrual cycle and the fertile window, including while trying to conceive. STUDY DESIGN, SIZE, DURATION The Pregnancy Study Online (PRESTO) is a North American prospective internet-based cohort of women who are aged 21–45 years, trying to conceive and not using contraception or fertility treatment at baseline. PARTICIPANTS/MATERIALS, SETTING, METHODS We restricted the analysis to 8363 women trying to conceive for no more than 6 months at baseline; the women were recruited from June 2013 through May 2019. Women completed questionnaires at baseline and every 2 months for up to 1 year. The main outcome was fecundability, i.e. the per-cycle probability of conception, which we assessed using self-reported data on time to pregnancy (confirmed by positive home pregnancy test) in menstrual cycles. On the baseline and follow-up questionnaires, women reported whether they used mobile computing apps to track their menstrual cycles (‘cycle apps’) and, if so, which one(s). We estimated fecundability ratios (FRs) for the use of cycle apps, adjusted for female age, race/ethnicity, prior pregnancy, BMI, income, current smoking, education, partner education, caffeine intake, use of hormonal contraceptives as the last method of contraception, hours of sleep per night, cycle regularity, use of prenatal supplements, marital status, intercourse frequency and history of subfertility. We also examined the impact of concurrent use of fertility indicators: basal body temperature, cervical fluid, cervix position and/or urine LH. MAIN RESULTS AND THE ROLE OF CHANCE Among 8363 women, 6077 (72.7%) were using one or more cycle apps at baseline. A total of 122 separate apps were reported by women. We designated five of these apps before analysis as more likely to be effective (Clue, Fertility Friend, Glow, Kindara, Ovia; hereafter referred to as ‘selected apps’). The use of any app at baseline was associated with 20% increased fecundability, with little difference between selected apps versus other apps (selected apps FR (95% CI): 1.20 (1.13, 1.28); all other apps 1.21 (1.13, 1.30)). In time-varying analyses, cycle app use was associated with 12–15% increased fecundability (selected apps FR (95% CI): 1.12 (1.04, 1.21); all other apps 1.15 (1.07, 1.24)). When apps were used at baseline with one or more fertility indicators, there was higher fecundability than without fertility indicators (selected apps with indicators FR (95% CI): 1.23 (1.14, 1.34) versus without indicators 1.17 (1.05, 1.30); other apps with indicators 1.30 (1.19, 1.43) versus without indicators 1.16 (1.06, 1.27)). In time-varying analyses, results were similar when stratified by time trying at study entry (<3 vs. 3–6 cycles) or cycle regularity. For use of the selected apps, we observed higher fecundability among women with a history of subfertility: FR 1.33 (1.05–1.67). LIMITATIONS, REASONS FOR CAUTION Neither regularity nor intensity of app use was ascertained. The prospective time-varying assessment of app use was based on questionnaires completed every 2 months, which would not capture more frequent changes. Intercourse frequency was also reported retrospectively and we do not have data on timing of intercourse relative to the fertile window. Although we controlled for a wide range of covariates, we cannot exclude the possibility of residual confounding (e.g. choosing to use an app in this observational study may be a marker for unmeasured health habits promoting fecundability). Half of the women in the study received a free premium subscription for one of the apps (Fertility Friend), which may have increased the overall prevalence of app use in the time-varying analyses, but would not affect app use at baseline. Most women in the study were college educated, which may limit application of results to other populations. WIDER IMPLICATIONS OF THE FINDINGS Use of a cycle app, especially in combination with observation of one or more fertility indicators (basal body temperature, cervical fluid, cervix position and/or urine LH), may increase fecundability (per-cycle pregnancy probability) by about 12–20% for couples trying to conceive. We did not find consistent evidence of improved fecundability resulting from use of one specific app over another. STUDY FUNDING/COMPETING INTEREST(S) This research was supported by grants, R21HD072326 and R01HD086742, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, USA. In the last 3 years, Dr L.A.W. has served as a fibroid consultant for AbbVie.com. Dr L.A.W. has also received in-kind donations from Sandstone Diagnostics, Swiss Precision Diagnostics, FertilityFriend.com and Kindara.com for primary data collection and participant incentives in the PRESTO cohort. Dr J.B.S. reports personal fees from Swiss Precision Diagnostics, outside the submitted work. The remaining authors have nothing to declare. TRIAL REGISTRATION NUMBER N/A. 

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5. High levels of objectively measured physical activity across adolescence and adulthood among the Pokot pastoralists of Kenya

   https://doi.org/10.1002/ajhb.23205  

   Sayre, M. Katherine ; Pike, Ivy L. ; Raichlen, David A. ( December 2018 , American Journal of Human Biology)

   Levels of physical activity (PA) across the lifespan are important predictors of physical fitness, impacting individual health, and longevity. Individuals living in industrialized societies are often characterized as more sedentary than those who live in small‐scale societies, and this inactivity is generally linked with increased incidence of chronic disease, especially during aging. However, less empirical data exist regarding levels and patterns of PA across the lifespan among small‐scale societies compared with industrialized societies. The goal of this study was to characterize PA among the Pokot pastoralists of rural northern Kenya.

   PA was measured in 40 participants ranging in age from 14 to 78 years using ActiGraph wrist‐worn accelerometers. Wear time spanned 24–77 hours, with a modal wear time of 50 hours.

   We show that the Pokot spend large amounts of time in moderate‐to‐vigorous physical activity (MVPA), achieving an average of 99.14 ± 7.25 minutes per day in MVPA. Males and younger participants tended to spend more time in MVPA. However, older participants were still physically active and engaged in over 50 minutes per day of MVPA.

   The Pokot are highly physically active from adolescence through adulthood. Other pastoralist groups may display a similar pattern of PA. During human evolution, lifespans increased, and lifestyles were characterized by a relatively high level of physical activity. The human aging process may be adapted for activity throughout life, and lifelong activity may have played an important role in increases in human longevity during evolution.

    

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