Validation of US CDC National Death Index mortality data, focusing on differences in race and ethnicity.

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.

Validation of diagnosis codes to identify hospitalized COVID-19 patients in health care claims data.

PURPOSE: Health plan claims may provide complete longitudinal data for timely, real-world population-level COVID-19 assessment. However, these data often lack laboratory results, the standard for COVID-19 diagnosis. METHODS: We assessed the validity of ICD-10-CM diagnosis codes for identifying patients hospitalized with COVID-19 in U.S. claims databases, compared to linked laboratory results, among six Food and Drug Administration Sentinel System data partners (two large national insurers, four integrated delivery systems) from February 20-October 17, 2020. We identified patients hospitalized with COVID-19 according to five ICD-10-CM diagnosis code-based algorithms, which included combinations of codes U07.1, B97.29, general coronavirus codes, and diagnosis codes for severe symptoms. We calculated the positive predictive value (PPV) and sensitivity of each algorithm relative to laboratory test results. We stratified results by data source type and across three time periods: February 20-March 31 (Time A), April 1-30 (Time B), May 1-October 17 (Time C). RESULTS: The five algorithms identified between 34 806 and 47 293 patients across the study periods; 23% with known laboratory results contributed to PPV calculations. PPVs were high and similar across algorithms. PPV of U07.1 alone was stable around 93% for integrated delivery systems, but declined over time from 93% to 70% among national insurers. Overall PPV of U07.1 across all data partners was 94.1% (95% CI, 92.3%-95.5%) in Time A and 81.2% (95% CI, 80.1%-82.2%) in Time C. Sensitivity was consistent across algorithms and over time, at 94.9% (95% CI, 94.2%-95.5%). CONCLUSION: Our results support the use of code U07.1 to identify hospitalized COVID-19 patients in U.S. claims data.

Patient experience after modifying visit delivery during the COVID-19 pandemic.

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 (ß3 = -388.94; P < .05), an immediate decrease in office-based visits (ß2 = -25,175.16; P < .01), increase in telephone-based visits (ß2 = 17,179.60; P < .01), and increased video-based visit trend (ß3 = 282.02; P < .01). After the second interruption, there was an increased visit trend for all visits (ß5 = 565.76; P < .01), immediate increase in video-based visits (ß4 = 3523.79; P < .05), increased office-based visit trend (ß5 = 998.13; P < .01), and decreased trend in video-based visits (ß5 = -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 (ß5 = 0.17; P < .01), telephone-based visits (ß5 = 0.34; P < .01), and video-based visits (ß5 = 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.

Lower resource utilization for patients with healed diabetic foot ulcers during participation in a prevention program with foot temperature monitoring.

INTRODUCTION: We assessed the impact of a diabetic foot ulcer prevention program incorporating once-daily foot temperature monitoring on hospitalizations, emergency department and outpatient visits, and rates of diabetic foot ulcer recurrence and lower extremity amputations for patients with recently healed foot ulcers. RESEARCH DESIGN AND METHODS: In this retrospective analysis of real-world data, we enrolled 80 participants with a healed diabetic foot ulcer in a year-long foot ulcer recurrence prevention program. Four outpatient centers within a large integrated healthcare system in the USA contributed to enrollment. We evaluated diabetic foot-related outcomes and associated resource utilization for participants during three periods: the 2 years before the program, the year during the program, and after the program ended. We reported unadjusted resource utilization rates during the program and the periods before and after it. We then adjusted rates of outcomes in each phase using an interrupted time series approach, explicitly controlling for overall trends in resource utilization and recurrence during the three periods. RESULTS: Our unadjusted data showed high initial rates of resource utilization and recurrence before enrollment in the program, followed by lower rates during the program, and higher rates of resource utilization and similar rates of recurrence in the period following the end of the program. The adjusted data showed lower rates of hospitalizations (relative risk reduction (RRR)=0.52; number needed to treat (NNT)=3.4), lower extremity amputations (RRR=0.71; NNT=6.4), and outpatient visits (RRR=0.26; absolute risk reduction (ARR)=3.5) during the program. We also found lower rates of foot ulcer recurrence during the program in the adjusted data, particularly for wounds with infection or greater than superficial depth (RRR=0.91; NNT=4.4). CONCLUSIONS: We observed lower rates of healthcare resource utilization for high-risk participants during enrollment in a diabetic foot prevention program incorporating once-daily foot temperature monitoring. TRIAL REGISTRATION NUMBER: NCT04345016.

The effect of obesity on orthopaedic conditions.

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.