BACKGROUND Ambulating medical inpatients may improve outcomes, but this practice is often overlooked by nurses who have competing clinical duties. OBJECTIVE This study aimed to assess the feasibility and effectiveness of dedicated mobility technician‐assisted ambulation in older inpatients. DESIGN This study was a single‐blind randomized controlled trial. SETTING Patients aged ≥60 years and admitted as medical inpatients to a tertiary care center were recruited. INTERVENTION Patients were randomized into two groups to participate in the ambulation protocol administered by a dedicated mobility technician. Usual care patients were not seen by the mobility technician but were not otherwise restricted in their opportunity to ambulate. MEASUREMENTS Primary outcomes were length of stay and discharge disposition. Secondary outcomes included change in mobility measured by six‐clicks score, daily steps measured by Fitbit, and 30‐day readmission. RESULTS Control (n = 52) and intervention (n = 50) groups were not significantly different at baseline. Of patients randomized to the intervention group, 74% participated at least once. Although the intervention did not affect the primary outcomes, the intervention group took nearly 50% more steps than the control group (P = .04). In the per protocol analysis, the six‐clicks score significantly increased (P = .04). Patients achieving ≥400 steps were more likely to go home (71% vs 46%, P = .01). CONCLUSIONS Attempted ambulation three times daily overseen by a dedicated mobility technician was feasible and increased the number of steps taken. A threshold of 400 steps was predictive of home discharge. Further studies are needed to establish the appropriate step goal and the effect of assisted ambulation on hospital outcomes.

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BACKGROUND: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial. OBJECTIVE: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization, and intensive care unit (ICU) admission. DESIGN: Retrospective cohort study with overlap propensity score weighting. PARTICIPANTS: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N = 72,909) from March 8-June 9, 2020, stratified by HCW and patient-facing status. MAIN MEASURES: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. KEY RESULTS: Of 72,909 individuals tested, 9.0% (551) of 6145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than the non-HCW (median age 39.7 vs. 57.5, p < 0.001) with more females (proportion of males 21.5 vs. 44.9%, p < 0.001), higher reporting of COVID-19 exposure (72 vs. 17%, p < 0.001), and fewer comorbidities. However, the overlap propensity score weighted proportions were 8.9 vs. 7.7 for HCW vs. non-HCW having a positive test with weighted odds ratio (OR) 1.17, 95% confidence interval (CI) 0.99-1.38. Among those testing positive, weighted proportions for hospitalization were 7.4 vs. 15.9 for HCW vs. non-HCW with OR of 0.42 (CI 0.26-0.66) and for ICU admission: 2.2 vs. 4.5 for HCW vs. non-HCW with OR of 0.48 (CI 0.20-1.04). Those HCW identified as patient facing compared to not had increased odds of a positive SARS-CoV-2 test (OR 1.60, CI 1.08-2.39, proportions 8.6 vs. 5.5), but no statistically significant increase in hospitalization (OR 0.88, CI 0.20-3.66, proportions 10.2 vs. 11.4) and ICU admission (OR 0.34, CI 0.01-3.97, proportions 1.8 vs. 5.2). CONCLUSIONS: In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patientfacing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.

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This study describes a new method to directly quantify the cost of defensive medicine. Defensive medicine appears to have minimal impact on primary care costs.

Background: Understanding the impact of the COVID-19 pandemic on healthcare workers (HCW) is crucial.Objective: Utilizing a health system COVID-19 research registry, we assessed HCW risk for COVID-19 infection, hospitalization and intensive care unit (ICU) admission.Design: Retrospective cohort study with overlap propensity score weighting.Participants: Individuals tested for SARS-CoV-2 infection in a large academic healthcare system (N=72,909) from March 8-June 9 2020 stratified by HCW and patient-facing status. Main Measures: SARS-CoV-2 test result, hospitalization, and ICU admission for COVID-19 infection. Key Results: Of 72,909 individuals tested, 9.0% (551) of 6,145 HCW tested positive for SARS-CoV-2 compared to 6.5% (4353) of 66,764 non-HCW. The HCW were younger than non-HCW (median age 39.7 vs. 57.5, p<0.001) with more females (proportion of males 21.5 vs. 44.9%, p<0.001), higher reporting of COVID-19 exposure (72 vs. 17 %, p<0.001) and fewer comorbidities. However, the overlap propensity score weighted proportions were 8.9 vs. 7.7 for HCW vs. non-HCW having a positive test with weighted odds ratio (OR) 1.17, 95% confidence interval (CI) 0.99-1.38. Among those testing positive, weighted proportions for hospitalization were 7.4 vs.15.9 for HCW vs. non-HCW with OR of 0.42 (CI 0.26-0.66) and for ICU admission: 2.2 vs.4.5 for HCW vs. non-HCW with OR of 0.48 (CI 0.20 -1.04). Those HCW identified as patient-facing compared to not had increased odds of a positive SARS-CoV-2 test (OR 1.60, CI 1.08-2.39, proportions 8.6 vs. 5.5), but no statistically significant increase in hospitalization (OR 0.88, CI 0.20-3.66, proportions 10.2 vs. 11.4) and ICU admission (OR 0.34, CI 0.01-3.97, proportions 1.8 vs. 5.2).Conclusions: In a large healthcare system, HCW had similar odds for testing SARS-CoV-2 positive, but lower odds of hospitalization compared to non-HCW. Patient-facing HCW had higher odds of a positive test. These results are key to understanding HCW risk mitigation during the COVID-19 pandemic.

Background: Venous thromboembolism (VTE) prophylaxis is recommended for hospitalized medical patients at high risk for VTE. Multiple risk assessment models exist, but few have been compared in large data sets. Methods: We constructed a derivation cohort using 6 years of data from 13 hospitals to identify risk factors associated with developing VTE within 14 days of admission. VTE was identified using a complex algorithm combining administrative codes and clinical data. We developed a multivariable prediction model and applied it to 2 validation cohorts: a temporal cohort, including two additional years and a cross-validation, in which we refit the model excluding one hospital at a time, and applied the refitted model to the holdout hospital. Performance was evaluated using the C-statistic. Results: The derivation cohort included 160,928 patients with a 14-day VTE rate of 0.79%. The final multivariable model contained 13 patient risk factors. The model had an optimism corrected C-statistic of 0.80 and good calibration. The temporal validation cohort included 55,301 patients, with a VTE rate of 0.74%. Based on the c-statistic, the Cleveland Clinic Model (CCM) outperformed the Padua model (0.76 vs. 0.72, p<0.01). The CCM was more sensitive (65.8% vs. 60.4%, p=0.05) and more specific (74.9% vs. 71.4%, p<.001), with higher positive (1.9% vs. 1.5%, p<.001) and negative predictive values (99.7% vs. 99.6%, p=0.01). C-statistics for the CCM at individual hospitals ranged from 0.64 to 0.76. Conclusion: A new VTE risk assessment model outperformed the Padua model. After further validation it could be recommended for widespread use.

Our understanding of the pathogenesis of idiopathic thrombotic thrombocytopenic purpura (TTP) has increased, but remains incomplete, particularly with respect to cases of suspected TTP that are either unresponsive to therapeutic plasma exchange (TPE) or have normal ADAMTS13 (a disintegrin-like and metalloprotease with thrombospondin type 1 motif 13) activity. A 53-year-old woman presented with severe anemia (hemoglobin 1.8 g/dL) and clinical and laboratory findings consistent with TTP in conjunction with acute cocaine use. The patient was treated with TPE until the pre-treatment ADAMTS13 activity was reported as normal without evidence of an inhibitor. TPE was stopped and the patient continued to improve without treatment. This patient's microangiopathic hemolytic anemia (MAHA) appeared to be secondary to cocaine use. The proposed pathogenesis is likely a combination of cocaine-induced vasoconstriction, vascular damage, platelet activation, and procoagulation. This is the fifth published report of cocaine-induced MAHA and to our knowledge the first with ADAMTS13 testing.