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OBJECTIVES: To describe real-time changes in medical visits (MVs), visit mode, and patient-reported visit experience associated with rapidly deployed care reorganization during the coronavirus disease 2019 (COVID-19) pandemic. STUDY DESIGN: Cross-sectional time series from September 29, 2019, through June 20, 2020. METHODS: Responding to official public health and clinical guidance, team-based systematic structural changes were implemented in a large, integrated health system to reorganize and transition delivery of care from office-based to virtual care platforms. Overall and discipline-specific weekly MVs, visit mode (office-based, telephone, or video), and associated aggregate measures of patient-reported visit experience were reported. A 38-week time-series analysis with March 8, 2020, and May 3, 2020, as the interruption dates was performed. RESULTS: After the first interruption, there was a decreased weekly visit trend for all visits (β3 = --388.94; P < .05), an immediate decrease in office-based visits (β2 = --25,175.16; P < .01), increase in telephone-based visits (β2 = 17,179.60; P < .01), and increased video-based visit trend (β3 = 282.02; P < .01). After the second interruption, there was an increased visit trend for all visits (β5 = 565.76; P < .01), immediate increase in video-based visits (β4 = 3523.79; P < .05), increased office-based visit trend (β5 = 998.13; P < .01), and decreased trend in video-based visits (β5 = --360.22; P < .01). After the second interruption, there were increased weekly long-term visit trends for the proportion of patients reporting "excellent" as to how well their visit needs were met for all visits (β5 = 0.17; P < .01), telephone-based visits (β5 = 0.34; P < .01), and video-based visits (β5 = 0.32; P < .01). Video-based visits had the highest proportion of respondents rating "excellent" as to how well their scheduling and visit needs were met. CONCLUSIONS: COVID-19 required prompt organizational transformation to optimize the patient experience. [ABSTRACT FROM AUTHOR]

Obesity is a worldwide health problem leading to a range of health consequences. This review summarizes the known effects of obesity on the musculoskeletal system. Specifically, the effects of obesity on the shoulders, spine, knees, feet and other areas related to sports medicine are examined. [ABSTRACT FROM AUTHOR]

Obesity is a worldwide health problem leading to a range of health consequences. This review summarizes the known effects of obesity on the musculoskeletal system. Specifically, the effects of obesity on the shoulders, spine, knees, feet and other areas related to sports medicine are examined. [ABSTRACT FROM AUTHOR]

Objectives: The US Center for Disease Control and Prevention's National Death Index (NDI) is a gold standard for mortality data, yet matching patients to the database depends on accurate and available key identifiers. Our objective was to evaluate NDI data for future healthcare research studies with mortality outcomes., Methods: We used a Kaiser Permanente Mid-Atlantic States' Virtual Data Warehouse (KPMAS-VDW) sourced from the Social Security Administration and electronic health records on members enrolled between 1 January 2005 to 31 December 2017. We submitted data to NDI on 1 036 449 members. We compared results from the NDI best match algorithm to the KPMAS-VDW for vital status and death date. We compared probabilistic scores by sex and race and ethnicity., Results: NDI returned 372 865 (36%) unique possible matches, 663 061 (64%) records not matched to the NDI database and 522 (<1%) rejected records. The NDI algorithm resulted in 38 862 records, presumed dead, with a lower percentage of women, and Asian/Pacific Islander and Hispanic people than presumed alive. There were 27 306 presumed dead members whose death dates matched exactly between the NDI results and VDW, but 1539 did not have an exact match. There were 10 017 additional deaths from NDI results that were not present in the VDW death data., Conclusions: NDI data can substantially improve the overall capture of deaths. However, further quality control measures were needed to ensure the accuracy of the NDI best match algorithm., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)