More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

PURPOSE: The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload. METHODS: This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments. RESULTS: From the pre-COVID-19 pandemic year (May 2019 to February 2020) to the most recent study year (April 2022 to March 2023), the average time PCPs spent in the EHR per 8 hours of scheduled clinic appointments increased (+28.4 minutes, 7.8%), as did time in orders (+23.1 minutes, 58.9%), inbox (+14.0 minutes, 24.4%), chart review (+7.2 minutes, 13.0%), notes (+2.9 minutes, 2.3%), outside scheduled hours on days with scheduled appointments (+6.4 minutes, 8.2%), and on unscheduled days (+13.6 minutes, 19.9%). Primary care physicians received more patient medical advice requests (+5.4 messages, 55.5%) and prescription messages (+2.3, 19.5%) per 8 hours of scheduled clinic appointments, but fewer patient calls (-2.8, -10.5%) and results messages (-0.3, -2.7%). While total time in the EHR continued to increase in the final study year (+7.7 minutes, 2.0%), inbox time decreased slightly from the year prior (-2.2 minutes, -3.0%). Primary care physicians' average aFTE decreased 5.2% from 0.66 to 0.63 over 4 years. CONCLUSIONS: Primary care physicians' time in the EHR continues to grow. While PCPs' inbox time may be stabilizing, it is still substantially higher than pre-pandemic levels. It is imperative health systems develop strategies to change the EHR workload trajectory to minimize PCPs' occupational stress and mitigate unnecessary reductions in effective physician workforce resulting from the increased EHR burden.

Refining Vendor-Defined Measures to Accurately Quantify EHR Workload Outside Time Scheduled With Patients.

Accurately quantifying clinician time spent on electronic health record (EHR) activities outside the time scheduled with patients is critical for understanding occupational stress associated with ambulatory clinic environments. We make 3 recommendations regarding EHR workload measures that are intended to capture time working in the EHR outside time scheduled with patients, formally defined as work outside of work (WOW): (1) separate all time working in the EHR outside of time scheduled with patients from time working in the EHR during time scheduled with patients, (2) do not exclude any time before or after scheduled time with patients, and (3) encourage the EHR vendor and research communities to develop and standardize validated, vendor-agnostic methods for measuring active EHR use. Attributing all EHR work outside time scheduled with patients to WOW, regardless of when it occurs, will produce an objective and standardized measure better suited for use in efforts to reduce burnout, set policy, and facilitate research.

Reproducibility across single-cell RNA-seq protocols for spatial ordering analysis.

As newer single-cell protocols generate increasingly more cells at reduced sequencing depths, the value of a higher read depth may be overlooked. Using data from three different single-cell RNA-seq protocols that lend themselves to having either higher read depth (Smart-seq) or many cells (MARS-seq and 10X), we evaluate their ability to recapitulate biological signals in the context of spatial reconstruction. Overall, we find gene expression profiles after spatial reconstruction analysis are highly reproducible between datasets despite being generated by different protocols and using different computational algorithms. While UMI-based protocols such as 10X and MARS-seq allow for capturing more cells, Smart-seq's higher sensitivity and read-depth allow for analysis of lower expressed genes and isoforms. Additionally, we evaluate trade-offs for each protocol by performing subsampling analyses and find that optimizing the balance between sequencing depth and number of cells within a protocol is necessary for efficient use of resources. Our analysis emphasizes the importance of selecting a protocol based on the biological questions and features of interest.

Age-based versus Risk-based Mammography Screening in Women 40-49 Years Old: A Cross-sectional Study.

Background Risk-based screening in women 40-49 years old has not been evaluated in routine screening mammography practice. Purpose To use a cross-sectional study design to compare the trade-offs of risk-based and age-based screening for women 45 years of age or older to determine short-term outcomes. Materials and Methods A retrospective cross-sectional study was performed by using a database of 20 539 prospectively interpreted consecutive digital screening mammograms in 10 280 average-risk women aged 40-49 years who were screened at an academic medical center between January 1, 2006, and December 31, 2013. Two hypothetical screening scenarios were compared: an age-based (≥45 years) scenario versus a risk-based (a 5-year risk of breast cancer greater than that of an average 50-year-old) scenario. Risk factors for risk-based screening included family history, race, age, prior breast biopsy, and breast density. Outcomes included breast cancers detected at mammography, false-positive mammograms, and benign biopsy findings. Short-term outcomes were compared by using the χ2 test. Results The screening population included 71 148 screening mammograms in 24 928 women with a mean age of 55.5 years ± 8.9 (standard deviation) (age range, 40-74 years). In women 40-49 years old, usual care included 50 screening-detected cancers, 1787 false-positive mammograms, and 384 benign biopsy results. The age-based (≥45 years) screening strategy revealed more cancers than did the risk-based strategy (34 [68%] vs 13 [26%] of 50; P < .001), while prompting more false-positive mammograms (899 [50.3%] vs 216 [12.1%] of 1787; P < .001) and benign biopsy results (175 [45.6%] vs 49 [12.8%] of 384; P < .001). The risk-based strategy demonstrated low levels of eligibility (few screenings) in the 40-44-year age group. Differences in outcomes in the 45-49-year age group explained the overall hypothetical screening strategy differences. Conclusion Risk-based screening for women 40-49 years old includes few women in the 40-44-year age range. Significant trade-offs in the 45-49-year age group explain the overall difference between hypothetical screening scenarios, both of which reduce the benefits as well as the harms of mammography for women 40-49 years old. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Joe and Hayward in this issue.

Lineage Reprogramming of Fibroblasts into Proliferative Induced Cardiac Progenitor Cells by Defined Factors.

Several studies have reported reprogramming of fibroblasts into induced cardiomyocytes; however, reprogramming into proliferative induced cardiac progenitor cells (iCPCs) remains to be accomplished. Here we report that a combination of 11 or 5 cardiac factors along with canonical Wnt and JAK/STAT signaling reprogrammed adult mouse cardiac, lung, and tail tip fibroblasts into iCPCs. The iCPCs were cardiac mesoderm-restricted progenitors that could be expanded extensively while maintaining multipotency to differentiate into cardiomyocytes, smooth muscle cells, and endothelial cells in vitro. Moreover, iCPCs injected into the cardiac crescent of mouse embryos differentiated into cardiomyocytes. iCPCs transplanted into the post-myocardial infarction mouse heart improved survival and differentiated into cardiomyocytes, smooth muscle cells, and endothelial cells. Lineage reprogramming of adult somatic cells into iCPCs provides a scalable cell source for drug discovery, disease modeling, and cardiac regenerative therapy.

The quantitative potential for breast tomosynthesis imaging.

PURPOSE: Due to its limited angular scan range, breast tomosynthesis has lower resolution in the depth direction, which may limit its accuracy in quantifying tissue density. This study assesses the quantitative potential of breast tomosynthesis using relatively simple reconstruction and image processing algorithms. This quantitation could allow improved characterization of lesions as well as image processing to present tomosynthesis images with the familiar appearance of mammography by preserving more low-frequency information. METHODS: All studies were based on a Siemens prototype MAMMOMAT Novation TOMO breast tomo system with a 45 degrees total angular span. This investigation was performed using both simulations and empirical measurements. Monte Carlo simulations were conducted using the breast tomosynthesis geometry and tissue-equivalent, uniform, voxelized phantoms with cuboid lesions of varying density embedded within. Empirical studies were then performed using tissue-equivalent plastic phantoms which were imaged on the actual prototype system. The material surrounding the lesions was set to either fat-equivalent or glandular-equivalent plastic. From the simulation experiments, the effects of scatter, lesion depth, and background material density were studied. The empirical experiments studied the effects of lesion depth, background material density, x-ray tube energy, and exposure level. Additionally, the proposed analysis methods were independently evaluated using a commercially available QA breast phantom (CIRS Model 11A). All image reconstruction was performed with a filtered backprojection algorithm. Reconstructed voxel values within each slice were corrected to reduce background nonuniformities. RESULTS: The resulting lesion voxel values varied linearly with known glandular fraction (correlation coefficient R2 > 0.90) under all simulated and empirical conditions, including for the independent tests with the QA phantom. Analysis of variance performed on the fit line parameters revealed statistically significant differences between the two different background materials and between 28 kVp and the remaining energies (26, 30, and 32 kVp) for the dense experimental phantom. How ever, no significant differences arose between different energies for the fatty phantom, nor for any of the many other combinations of parameters. CONCLUSIONS: These strong linear relationships suggest that breast tomosynthesis image voxel values, after being corrected by our outlined methods, are highly positively correlated with true tissue density. This consistent linearity implies that breast tomosynthesis imaging indeed has potential to be quantitative.