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

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.

Evaluation of Attention Switching and Duration of Electronic Inbox Work Among Primary Care Physicians.

Importance: Primary care physicians (PCPs) report multitasking during workdays while processing electronic inbox messages, but scant systematic information exists on attention switching and its correlates in the health care setting. Objectives: To describe PCPs' frequency of attention switching associated with electronic inbox work, identify potentially modifiable factors associated with attention switching and inbox work duration, and compare the relative association of attention switching and other factors with inbox work duration. Design, Setting, and Participants: This cross-sectional study of the work of 1275 PCPs in an integrated group serving 4.5 million patients used electronic health record (EHR) access logs from March 1 to 31, 2018, to evaluate PCPs' frequency of attention switching. Statistical analysis was performed from October 15, 2018, to August 28, 2020. Main Outcomes and Measures: Attention switching was defined as switching between the electronic inbox, other EHR work, and non-EHR periods. Inbox work duration included minutes spent on electronic inbox message views and related EHR tasks. Multivariable models controlled for the exposures. Results: The 1275 PCPs studied (721 women [56.5%]; mean [SD] age, 45.9 [8.5] years) had a mean (SD) of 9.0 (7.6) years of experience with the medical group and received a mean (SD) of 332.6 (148.3) (interquartile range, 252-418) new inbox messages weekly. On workdays, PCPs made a mean (SD) of 79.4 (21.8) attention switches associated with inbox work and did a mean (SD) 64.2 (18.7) minutes of inbox work over the course of 24 hours on workdays. In the model for attention switching, each additional patient secure message beyond the reference value was associated with 0.289 (95% CI, 0.217-0.362) additional switches, each additional results message was associated with 0.203 (95% CI, 0.127-0.278) additional switches, each additional request message was associated with 0.190 (95% CI, 0.124-0.257) additional switches, and each additional administrative message was associated with 0.262 (95% CI, 0.166-0.358) additional switches. Having a panel (a list of patients assigned to a primary care team) with more elderly patients (0.144 switches per percentage increase [95% CI, 0.009-0.278]) and higher inbox work duration (0.468 switches per additional minute of inbox work [95% CI, 0.411-0.524]) were also associated with higher attention switching involving the inbox. In the model for inbox work duration, each additional patient secure message beyond the reference value was associated with 0.151 (95% CI, 0.085-0.217) additional minutes, each additional results message was associated with 0.338 (95% CI, 0.272-0.404) additional minutes, each additional request message was associated with 0.101 (95% CI, 0.041-0.161) additional minutes, and each additional administrative message was associated with 0.179 (95% CI, 0.093-0.265) additional minutes. A higher percentage of the panel's patients initiating messages (0.386 minutes per percentage increase [95% CI, 0.026-0.745]) and attention switches (0.373 minutes per switch [95% CI, 0.328-0.419]) were also associated with higher inbox work duration. In addition, working at a medical center where all PCPs had high inbox work duration was independently associated with high or low inbox work duration. Conclusions and Relevance: This study suggests that PCPs make frequent attention switches during workdays while processing electronic inbox messages. Message quantity was associated with both attention switching and inbox work duration. Physician and patient panel characteristics had less association with attention switching and inbox work duration. Assisting PCPs with message quantity might help modulate both attention switching and inbox work duration.

Physicians' electronic inbox work patterns and factors associated with high inbox work duration.

OBJECTIVES: Electronic health record systems are increasingly used to send messages to physicians, but research on physicians' inbox use patterns is limited. This study's aims were to (1) quantify the time primary care physicians (PCPs) spend managing inboxes; (2) describe daily patterns of inbox use; (3) investigate which types of messages consume the most time; and (4) identify factors associated with inbox work duration. MATERIALS AND METHODS: We analyzed 1 month of electronic inbox data for 1275 PCPs in a large medical group and linked these data with physicians' demographic data. RESULTS: PCPs spent an average of 52 minutes on inbox management on workdays, including 19 minutes (37%) outside work hours. Temporal patterns of electronic inbox use differed from other EHR functions such as charting. Patient-initiated messages (28%) and results (29%) accounted for the most inbox work time. PCPs with higher inbox work duration were more likely to be female (P < .001), have more patient encounters (P < .001), have older patients (P < .001), spend proportionally more time on patient messages (P < .001), and spend more time per message (P < .001). Compared with PCPs with the lowest duration of time on inbox work, PCPs with the highest duration had more message views per workday (200 vs 109; P < .001) and spent more time on the inbox outside work hours (30 minutes vs 9.7 minutes; P < .001). CONCLUSIONS: Electronic inbox work by PCPs requires roughly an hour per workday, much of which occurs outside scheduled work hours. Interventions to assist PCPs in handling patient-initiated messages and results may help alleviate inbox workload.

Primary Care Physicians' Experiences With and Strategies for Managing Electronic Messages.

Importance: The increasing use of electronic communications has enhanced access to physicians for patients and clinical staff. Primary care physicians (PCPs) have anecdotally identified electronic inbox management as a new source of work-related stress. Objectives: To describe PCPs' experiences managing their electronic inboxes and to characterize the array of management strategies developed by individual physicians and practice groups. Design, Setting, and Participants: This qualitative study was conducted in 8 medical centers of a large group practice with more than 4 million patients in diverse settings and a mature electronic health record. The group encourages patients to use portal secure messaging to enhance access to their physicians and the care experience. Semistructured interviews were conducted with 24 internists and family medicine physicians identified via snowball sampling. Interviews were conducted July through November 2018. Data analysis was conducted between November 2018 and April 2019. Main Outcomes and Measures: Audio recorded interviews were transcribed and analyzed using thematic analysis to identify major themes and subthemes. Results: The 24 participants (12 women [50.0%]; mean [SD] age, 45.5 [6.5] years), including 9 department chiefs and 15 PCPs, had a mean (SD) of 16.8 (7.8) years since medical school graduation. Participants described substantial changes in medical practice due to electronic communication, including perceived patient expectations to receive rapid responses to portal secure messages. They described portal secure messaging as useful for building relationships with patients, but also reported that electronic message management has created new stressors, including erosion of work-life boundaries and anxiety associated with unlimited inbox volume. Individual PCPs used a diverse array of strategies, including multitasking during and outside work and delegating to medical assistants. Chiefs described group-level strategies, including reserving clinic time for inbox management, coverage systems for vacation and sick days, physician-to-physician training, and interdisciplinary teams to share messaging work. Conclusions and Relevance: Individual physicians and local practice groups have developed a wide array of strategies for electronic inbox management. The volume of electronic messages and PCPs' perceptions that patients expect rapid responses have created new stressors in primary care practice. Medical groups and health systems can support PCPs by facilitating knowledge transfer among physicians about inbox management strategies and further developing team structures for inbox coverage.

Mortality is associated with inflammation, anemia, specific diseases and treatments, and molecular markers.

Lifespan is a complex trait, and longitudinal data for humans are naturally scarce. We report the results of Cox regression and Pearson correlation analyses using data of the Study of Health in Pomerania (SHIP), with mortality data of 1518 participants (113 of which died), over a time span of more than 10 years. We found that in the Cox regression model based on the Bayesian information criterion, apart from chronological age of the participant, six baseline variables were considerably associated with higher mortality rates: smoking, mean attachment loss (i.e. loss of tooth supporting tissue), fibrinogen concentration, albumin/creatinine ratio, treated gastritis, and medication during the last 7 days. Except for smoking, the causative contribution of these variables to mortality was deemed inconclusive. In turn, four variables were found to be associated with decreased mortality rates: treatment of benign prostatic hypertrophy, treatment of dyslipidemia, IGF-1 and being female. Here, being female was an undisputed causative variable, the causal role of IFG-1 was deemed inconclusive, and the treatment effects were deemed protective to the degree that treated subjects feature better survival than respective controls. Using Cox modeling based on the Akaike information criterion, diabetes, mean corpuscular hemoglobin concentration, red blood cell count and serum calcium were also associated with mortality. The latter two, together with albumin and fibrinogen, aligned with an"integrated albunemia" model of aging proposed recently.

Advanced Running Performance by Genetic Predisposition in Male Dummerstorf Marathon Mice (DUhTP) Reveals Higher Sterol Regulatory Element-Binding Protein (SREBP) Related mRNA Expression in the Liver and Higher Serum Levels of Progesterone.

Long-term-selected DUhTP mice represent a non-inbred model for inborn physical high-performance without previous training. Abundance of hepatic mRNA in 70-day male DUhTP and control mice was analyzed using the Affymetrix mouse array 430A 2.0. Differential expression analysis with PLIER corrected data was performed using AltAnalyze. Searching for over-representation in biochemical pathways revealed cholesterol metabolism being most prominently affected in DUhTP compared to unselected control mice. Furthermore, pathway analysis by AltAnalyze plus PathVisio indicated significant induction of glycolysis, fatty acid synthesis and cholesterol biosynthesis in the liver of DUhTP mice versus unselected control mice. In contrast, gluconeogenesis was partially inactivated as judged from the analysis of hepatic mRNA transcript abundance in DUhTP mice. Analysis of mRNA transcripts related to steroid hormone metabolism inferred elevated synthesis of progesterone and reduced levels of sex steroids. Abundance of steroid delta isomerase-5 mRNA (Hsd3b5, FC 4.97) was increased and steroid 17-alpha-monooxygenase mRNA (Cyp17a1, FC -11.6) was massively diminished in the liver of DUhTP mice. Assessment of steroid profiles by LC-MS revealed increased levels of progesterone and decreased levels of sex steroids in serum from DUhTP mice versus controls. Analysis of hepatic mRNA transcript abundance indicates that sterol regulatory element-binding protein-1 (SREBP-1) may play a major role in metabolic pathway activation in the marathon mouse model DUhTP. Thus, results from bioinformatics modeling of hepatic mRNA transcript abundance correlated with direct steroid analysis by mass spectrometry and further indicated functions of SREBP-1 and steroid hormones for endurance performance in DUhTP mice.

Inbred mouse strains reveal biomarkers that are pro-longevity, antilongevity or role switching.

Traditionally, biomarkers of aging are classified as either pro-longevity or antilongevity. Using longitudinal data sets from the large-scale inbred mouse strain study at the Jackson Laboratory Nathan Shock Center, we describe a protocol to identify two kinds of biomarkers: those with prognostic implication for lifespan and those with longitudinal evidence. Our protocol also identifies biomarkers for which, at first sight, there is conflicting evidence. Conflict resolution is possible by postulating a role switch. In these cases, high biomarker values are, for example, antilongevity in early life and pro-longevity in later life. Role-switching biomarkers correspond to features that must, for example, be minimized early, but maximized later, for optimal longevity. The clear-cut pro-longevity biomarkers we found reflect anti-inflammatory, anti-immunosenescent or anti-anaemic mechanisms, whereas clear-cut antilongevity biomarkers reflect inflammatory mechanisms. Many highly significant blood biomarkers relate to immune system features, indicating a shift from adaptive to innate processes, whereas most role-switching biomarkers relate to blood serum features and whole-body phenotypes. Our biomarker classification approach is applicable to any combination of longitudinal studies with life expectancy data, and it provides insights beyond a simplified scheme of biomarkers for long or short lifespan.