Key PointsQuestionWhat are the characteristics, clinical presentation, and outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19) in the US?FindingsIn this case series that included 5700 patients hospitalized with COVID-19 in the New York City area, the most common comorbidities were hypertension, obesity, and diabetes. Among patients who were discharged or died (n = 2634), 14.2% were treated in the intensive care unit, 12.2% received invasive mechanical ventilation, 3.2% were treated with kidney replacement therapy, and 21% died.MeaningThis study provides characteristics and early outcomes of patients hospitalized with COVID-19 in the New York City area.

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OBJECTIVE:To determine the prevalence of medical errors related to the discontinuity of care from an inpatient to an outpatient setting, and to determine if there is an association between these medical errors and adverse outcomes. PATIENTS:Eighty-six patients who had been hospitalized on the medicine service at a large academic medical center and who were subsequently seen by their primary care physicians at the affiliated outpatient practice within 2 months after discharge.DESIGN: Each patient's inpatient and outpatient medical record was reviewed for the presence of 3 types of errors related to the discontinuity of care from the inpatient to the outpatient setting: medication continuity errors, test follow-up errors, and work-up errors. MEASUREMENTS:Rehospitalizations within 3 months after the initial postdischarge outpatient primary care visit.MAIN RESULTS: Forty-nine percent of patients experienced at least 1 medical error. Patients with a work-up error were 6.2 times (95%confidence interval [95% CI], 1.3 to 30.3) more likely to be rehospitalized within 3 months after the first outpatient visit. We did not find a statistically significant association between medication continuity errors (odds ratio [OR], 2.5; 95%CI, 0.7 to 8.8) and test follow-up errors (OR, 2.4; 95%CI, 0.3 to 17.1) with rehospitalizations. CONCLUSION:We conclude that the prevalence of medical errors related to the discontinuity of care from the inpatient to the outpatient setting is high and may be associated with an increased risk of rehospitalization.KEY WORDS: medical errors; continuity of care; discharge plan; discharge summary. J GEN INTERN MED 2003;18:646±651. A dverse events in hospitalized patients have been associated with the discontinuity of care that occurs during the handoff of patient care from one hospital-based physician to another, 1 and there is evidence that improved communication between hospital-based physicians may decrease adverse events. 2 However, relatively little attention has been given to the spectrum of medical errors and adverse events that are caused by inadequate communication between hospital-based physicians and outpatient primary care providers (PCPs). Physicians caring for hospitalized patients often formulate discharge plans that include medication regimens that are to be continued after discharge, scheduled outpatient tests and procedures, and test results that are pending at discharge and that need to be followed up by the outpatient PCP. The Institute of Medicine defines a medical error as``failure of a planned action to be completed as intended. '' 3 Based on this definition, failure to implement the intended discharge plan for a recently hospitalized patient constitutes a medical error, assuming the PCP concurs with the plan or, if not, fails to change the plan. However, studies have shown that less than half of all PCPs are provided information about the discharge medications and plans for their recently hospitalized patients, 4±6 this despite evidence that access to relevant discharge in...

The greater New York City (NYC) area, including the 5 boroughs and surrounding counties, has a high incidence of coronavirus disease 2019 (COVID-19), 1 and health care personnel (HCP) working there have a high exposure risk. HCP have expressed concerns about access to testing so that infection spread to patients, other HCP, and their families can be minimized. 2 The Northwell Health System, the largest in New York State, sought to address this concern by offering voluntary antibody testing to all HCP. We investigated the prevalence of antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among HCP and associations with demographics, primary work location and type, and suspicion of virus exposure.Methods | All Northwell HCP (employees) were provided with personal protective equipment from March 7, 2020, onward. SARS-CoV-2 testing by reverse transcriptase-polymerase chain reaction (PCR) began March 7, 2020, and was available for any HCP who had COVID-19-like symptoms or suspected exposure. From April 20, 2020, to June 23, 2020, all Northwell HCP were offered free, voluntary antibody testing, regardless of symptoms, at 52 sites in the greater NYC area. HCP missing all identifying data were excluded. Testing was for qualitative IgG or total immunoreactivity to SARS-CoV-2. 3 Seven different assays were used (eTable in the Supplement); Northwell Health Laboratories validated all testing.The main outcome was seroprevalence. Seroprevalence with 95% confidence interval was calculated by the exact binomial technique. HCP reported demographics, primary work location, job function, direct patient care, work on a COVID or non-COVID unit, and their level of suspicion of virus exposure: "Do you believe you were infected with COVID-19?"

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Clinical experience provides clinicians with an intuitive sense of which findings on history, physical examination, and investigation are critical in making an accurate diagnosis, or an accurate assessment of a patient's fate. A clinical decision rule (CDR) is a clinical tool that quantifies the individual contributions that various components of the history, physical examination, and basic laboratory results make toward the diagnosis, prognosis, or likely response to treatment in a patient. Clinical decision rules attempt to formally test, simplify, and increase the accuracy of clinicians' diagnostic and prognostic assessments. Existing CDRs guide clinicians, establish pretest probability, provide screening tests for common problems, and estimate risk. Three steps are involved in the development and testing of a CDR: creation of the rule, testing or validating the rule, and assessing the impact of the rule on clinical behavior. Clinicians evaluating CDRs for possible clinical use should assess the following components: the method of derivation; the validation of the CDR to ensure that its repeated use leads to the same results; and its predictive power. We consider CDRs that have been validated in a new clinical setting to be level 1 CDRs and most appropriate for implementation. Level 1 CDRs have the potential to inform clinical judgment, to change clinical behavior, and to reduce unnecessary costs, while maintaining quality of care and patient satisfaction. JAMA. 2000;284:79-84

IMPORTANCE There is consensus that incorporating clinical decision support into electronic health records will improve quality of care, contain costs, and reduce overtreatment, but this potential has yet to be demonstrated in clinical trials.OBJECTIVE To assess the influence of a customized evidence-based clinical decision support tool on the management of respiratory tract infections and on the effectiveness of integrating evidence at the point of care. DESIGN, SETTING, AND PARTICIPANTSIn a randomized clinical trial, we implemented 2 well-validated integrated clinical prediction rules, namely, the Walsh rule for streptococcal pharyngitis and the Heckerling rule for pneumonia. INTERVENTIONS AND MAIN OUTCOMES AND MEASURESThe intervention group had access to the integrated clinical prediction rule tool and chose whether to complete risk score calculators, order medications, and generate progress notes to assist with complex decision making at the point of care. RESULTSThe intervention group completed the integrated clinical prediction rule tool in 57.5% of visits. Providers in the intervention group were significantly less likely to order antibiotics than the control group (age-adjusted relative risk, 0.74; 95% CI, 0.60-0.92). The absolute risk of the intervention was 9.2%, and the number needed to treat was 10.8. The intervention group was significantly less likely to order rapid streptococcal tests compared with the control group (relative risk, 0.75; 95% CI, 0.58-0.97; P = .03). CONCLUSIONS AND RELEVANCEThe integrated clinical prediction rule process for integrating complex evidence-based clinical decision report tools is of relevant importance for national initiatives, such as Meaningful Use.TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT01386047

Thromboembolic events, including venous thromboembolism (VTE) and arterial thromboembolism (ATE), and mortality from subclinical thrombotic events occur frequently in coronavirus disease 2019 (COVID-19) inpatients. Whether the risk extends postdischarge has been controversial. Our prospective registry included consecutive patients with COVID-19 hospitalized within our multihospital system from 1 March to 31 May 2020. We captured demographics, comorbidities, laboratory parameters, medications, postdischarge thromboprophylaxis, and 90-day outcomes. Data from electronic health records, health informatics exchange, radiology database, and telephonic follow-up were merged. Primary outcome was a composite of adjudicated VTE, ATE, and all-cause mortality (ACM). Principal safety outcome was major bleeding (MB). Among 4906 patients (53.7% male), mean age was 61.7 years. Comorbidities included hypertension (38.6%), diabetes (25.1%), obesity (18.9%), and cancer history (13.1%). Postdischarge thromboprophylaxis was prescribed in 13.2%. VTE rate was 1.55%; ATE, 1.71%; ΑCM, 4.83%; and MB, 1.73%. Composite primary outcome rate was 7.13% and significantly associated with advanced age (odds ratio [OR], 3.66; 95% CI, 2.84-4.71), prior VTE (OR, 2.99; 95% CI, 2.00-4.47), intensive care unit (ICU) stay (OR, 2.22; 95% CI, 1.78-2.93), chronic kidney disease (CKD; OR, 2.10; 95% CI, 1.47-3.0), peripheral arterial disease (OR, 2.04; 95% CI, 1.10-3.80), carotid occlusive disease (OR, 2.02; 95% CI, 1.30-3.14), IMPROVE-DD VTE score ≥4 (OR, 1.51; 95% CI, 1.06-2.14), and coronary artery disease (OR, 1.50; 95% CI, 1.04-2.17). Postdischarge anticoagulation was significantly associated with reduction in primary outcome (OR, 0.54; 95% CI, 0.47-0.81). Postdischarge VTE, ATE, and ACM occurred frequently after COVID-19 hospitalization. Advanced age, cardiovascular risk factors, CKD, IMPROVE-DD VTE score ≥4, and ICU stay increased risk. Postdischarge anticoagulation reduced risk by 46%.