Healthcare Utilization Among Patients Diagnosed with COVID-19 in a Large Integrated Health System.

BACKGROUND: The demands for healthcare resources following a COVID-19 diagnosis are substantial, but not currently quantified. OBJECTIVE: To describe trends in healthcare utilization within 180 days for patients diagnosed with COVID-19 and identify patient factors associated with increased healthcare use. DESIGN: Observational cohort study. PATIENTS: A total of 64,011 patients with a test-confirmed COVID-19 diagnosis from March to September 2020 in a large integrated healthcare system in Southern California. MAIN MEASURES: Overall healthcare utilization during the 180 days following COVID-19 diagnosis, as well as encounter types and reasons for visits during the first 30 days. Poisson regression was used to identify patient factors associated with higher utilization. Analyses were performed separately for patients who were and were not hospitalized for COVID-19. KEY RESULTS: Healthcare utilization was about twice as high for hospitalized patients compared to non-hospitalized patients in all time periods. The average number of visits was highest in the first 30 days (hospitalized: 12.3 visits/30 person-days; non-hospitalized: 6.6) and gradually decreased over time. In the first 30 days, the majority of healthcare visits were telehealth encounters (hospitalized: 9.0 visits; non-hospitalized: 5.6 visits), and the most prevalent reasons for visits were COVID-related diagnoses, COVID-related symptoms, and respiratory-related conditions. For hospitalized patients, older age (≥65: RR 1.27, 95% CI 1.15-1.41), female gender (RR 1.07, 95% CI 1.05-1.09), and higher BMI (≥40: RR 1.07, 95% CI 1.03-1.10) were associated with higher total utilization. For non-hospitalized patients, older age, female gender, higher BMI, non-white race/ethnicity, former smoking, and greater number of pre-existing comorbidities were all associated with increased utilization. CONCLUSIONS: Patients with COVID-19 seek healthcare frequently within 30 days of diagnosis, placing high demands on health systems. Identifying ways to support patients diagnosed with COVID-19 while adequately providing the usual recommended care to our communities will be important as we recover from the pandemic.

Identifying patients with symptoms suspicious for COVID-19 at elevated risk of adverse events: The COVAS score.

OBJECTIVE: Develop and validate a risk score using variables available during an Emergency Department (ED) encounter to predict adverse events among patients with suspected COVID-19. METHODS: A retrospective cohort study of adult visits for suspected COVID-19 between March 1 - April 30, 2020 at 15 EDs in Southern California. The primary outcomes were death or respiratory decompensation within 7-days. We used least absolute shrinkage and selection operator (LASSO) models and logistic regression to derive a risk score. We report metrics for derivation and validation cohorts, and subgroups with pneumonia or COVID-19 diagnoses. RESULTS: 26,600 ED encounters were included and 1079 experienced an adverse event. Five categories (comorbidities, obesity/BMI ≥ 40, vital signs, age and sex) were included in the final score. The area under the curve (AUC) in the derivation cohort was 0.891 (95% CI, 0.880-0.901); similar performance was observed in the validation cohort (AUC = 0.895, 95% CI, 0.874-0.916). Sensitivity ranging from 100% (Score 0) to 41.7% (Score of ≥15) and specificity from 13.9% (score 0) to 96.8% (score ≥ 15). In the subgroups with pneumonia (n = 3252) the AUCs were 0.780 (derivation, 95% CI 0.759-0.801) and 0.832 (validation, 95% CI 0.794-0.870), while for COVID-19 diagnoses (n = 2059) the AUCs were 0.867 (95% CI 0.843-0.892) and 0.837 (95% CI 0.774-0.899) respectively. CONCLUSION: Physicians evaluating ED patients with pneumonia, COVID-19, or symptoms suspicious for COVID-19 can apply the COVAS score to assist with decisions to hospitalize or discharge patients during the SARS CoV-2 pandemic.

Variation in SARS-CoV-2 molecular test sensitivity by specimen types in a large sample of emergency department patients.

BACKGROUND: Provider-collected nasopharyngeal specimens for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) molecular testing are the standard of care in many clinical settings, but patient-collected saliva and anterior nares specimens are less invasive and more flexible alternatives. Prior studies comparing specimen types for SARS-CoV-2 molecular testing have been limited by small sample sizes and low pretest probability. We conducted a large observational study among symptomatic adults at 7 emergency departments of Kaiser Permanente Southern California to examine sensitivity of SARS-CoV-2 molecular tests by specimen type and patient characteristics. METHODS: Provider-collected nasopharyngeal/oropharyngeal (NP/OP) specimens and patient-collected saliva and anterior nares specimens were collected at the same visit and analyzed with the Roche cobas® SARS-CoV-2 assay. Patients were considered truly positive for SARS-CoV-2 if any of the three specimens was positive and negative if all three specimens were negative. Factors associated with discordant and missed positive results were examined with multivariable logistic regression. RESULTS: Of 2112 patients, 350 (16.6%) were positive for SARS-CoV-2. Sensitivity of NP/OP was 93.7% (95% confidence interval [CI] 90.6%-96.0%), sensitivity of saliva was 87.7% (83.8%-91.0%), and sensitivity of anterior nares was 85.4% (81.3%-89.0%). Patients ages 18-39 years versus ≥40 years were more likely to have discordant results [adjusted odds ratio (aOR) 1.97 (1.12-3.45)], as were patients with <4 symptoms versus ≥4 [aOR 2.43 (1.39-4.25)]. Cycle threshold values were higher for saliva and anterior nares than NP/OP specimens, as well as for specimens in discordant versus concordant sets and patients with fewer symptoms. CONCLUSION: This study provides robust evidence that patient-collected saliva and anterior nares are sensitive for SARS-CoV-2 molecular testing in emergency department settings, particularly among adults ages ≥40 years and those with multiple symptoms. Higher sensitivity of provider-collected NP/OP specimens must be weighed against the benefits of patient-collected specimens in tailored strategies for SARS-CoV-2 testing.

All-Cause and Cardiovascular-Related Mortality in CKD Patients With and Without Heart Failure: A Population-Based Cohort Study in Kaiser Permanente Southern California.

Rationale & Objective: Heart failure and chronic kidney disease (CKD) frequently coexist reflective of the strong interplay between these organ systems. A better understanding of the prevalence of different types of heart failure (preserved and reduced ejection fraction) and their subsequent mortality risks among advanced CKD patients would provide important epidemiologic insights and may pave the way for more focused and proactive management strategies. Study Design: Retrospective cohort study. Setting & Population: Patients aged ≥18 years with incident CKD (estimated glomerular filtration rate ≤45 mL/min/1.73 m2) with and without heart failure in a large integrated health care system in Southern California. Exposure: Heart failure, heart failure with preserved ejection fraction (HFpEF), heart failure with reduced ejection fraction (HFrEF). Outcomes: All-cause and cardiovascular-related mortality within one year of CKD identification. Analytical Approach: HRs were estimated using Cox proportional-hazards model for risk of all-cause mortality and Fine-Gray subdistribution hazard model for risk of cardiovascular-related mortality within 1 year. Results: The study cohort included 76,688 patients with incident CKD between 2007 and 2017, of which 14,249 (18.6%) had prevalent heart failure. Among these patients, 8,436 (59.2%) had HFpEF and 3,328 (23.3%) had HFrEF. Compared with patients without heart failure, the HR for 1-year all-cause mortality was 1.70 (95% CI, 1.60-1.80) among patients with heart failure. The HRs were 1.59 (95% CI, 1.48-1.70) for patients with HFpEF and 2.43 (95% CI, 2.23-2.65) for patients with HFrEF. Compared with patients without heart failure, the 1-year cardiovascular-related mortality HR for patients with heart failure was 6.69 (95% CI, 5.93-7.54). Cardiovascular-related mortality HR was even higher among those with HFrEF (HR, 11.47; 95% CI, 9.90-13.28). Limitations: Retrospective design with a short 1-year follow-up period. Additional variables including medication adherence, medication changes, and time-varying variables were not accounted for in this intention-to-treat analysis. Conclusions: Among patients with incident CKD, heart failure was highly prevalent with HFpEF accounting for over 70% among patients with known ejection fraction. Although the presence of heart failure was associated with higher 1-year all-cause and cardiovascular-related mortality, patients with HFrEF were the most vulnerable.

Safety of baclofen versus tizanidine for older adults with musculoskeletal pain.

BACKGROUND: Baclofen and tizanidine are both muscle relaxants that carry the risk for neuropsychiatric events in older adults but there is a lack of data directly comparing their safety. This study aimed to investigate the relative risk between these two medications in causing injury and delirium in older adults. METHODS: This was a retrospective cohort study that was completed in an integrated healthcare system in the United States and included patients aged 65 years or older who started baclofen or tizanidine for the treatment of musculoskeletal pain from January 2016 through December 2018. Outcomes included new incidence of injury (concussion, contusion, dislocation, fall, fracture, or other injuries) and delirium. The cohort was followed from the initiation of therapy until the first occurrence of any of the following events: end of the index drug exposure, end of health plan membership, death, or the study end date of December 31st, 2019. Descriptive statistics were used to compare baseline patient characteristics between baclofen and tizanidine treatment groups. Cox proportional hazards model was used to calculate adjusted hazard ratios (HRs) with 95% confidence intervals. RESULTS: The final study cohort included 12,101 and 6,027 older adults in the baclofen and tizanidine group respectively (mean age 72.2 ± 6.2 years old, 59% female). Older adults newly started on baclofen had a greater risk of injury (HR = 1.54, 95% CI = 1.21-1.96, P = < 0.001) and delirium (HR = 3.33, 95% CI = 2.11-5.26, p = <0.001) compared to those started on tizanidine. CONCLUSION: The results of this study suggest that baclofen is associated with higher incidences of injury and delirium compared to tizanidine when used for the treatment of musculoskeletal pain. Future studies should investigate if these risks are dose-related and include a comparison group not exposed to either drug.

Development and validation of the COVID-19 Hospitalized Patient Deterioration Index.

OBJECTIVES: To develop a COVID-19-specific deterioration index for hospitalized patients: the COVID Hospitalized Patient Deterioration Index (COVID-HDI). This index builds on the proprietary Epic Deterioration Index, which was not developed for predicting respiratory deterioration events among patients with COVID-19. STUDY DESIGN: A retrospective observational cohort was used to develop and validate the COVID-HDI model to predict respiratory deterioration or death among hospitalized patients with COVID-19. Deterioration events were defined as death or requiring high-flow oxygen, bilevel positive airway pressure, mechanical ventilation, or intensive-level care within 72 hours of run time. The sample included hospitalized patients with COVID-19 diagnoses or positive tests at Kaiser Permanente Southern California between May 3, 2020, and October 17, 2020. METHODS: Machine learning models and 118 candidate predictors were used to generate benchmark performance. Logit regression with least absolute shrinkage and selection operator and physician input were used to finalize the model. Split-sample cross-validation was used to train and test the model. RESULTS: The area under the receiver operating curve was 0.83. COVID-HDI identifies patients at low risk (negative predictive value [NPV] > 98.5%) and borderline low risk (NPV > 95%) of an event. Of all patients, 74% were identified as being at low or borderline low risk at some point during their hospitalization and could be considered for discharge with or without home monitoring. A high-risk group with a positive predictive value of 51% included 12% of patients. Model performance remained high in a recent cohort of patients. CONCLUSIONS: COVID-HDI is a parsimonious, well-calibrated, and accurate model that may support clinical decision-making around discharge and escalation of care.

Rate and severity of suspected SARS-Cov-2 reinfection in a cohort of PCR-positive COVID-19 patients.

OBJECTIVES: To estimate the burden and severity of suspected reinfection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: A retrospective cohort of members of Kaiser Permanente Southern California with PCR-positive SARS-CoV-2 infection between 1st March 2020 and 31st October 2020 was followed through electronic health records for subsequent positive SARS-CoV-2 tests (suspected reinfection) ≥90 days after initial infection, through 31st January 2021. Incidence of suspected reinfection was estimated using the Kaplan-Meier method. Cox proportional hazards models estimated the association of suspected reinfection with demographic and clinical characteristics, hospitalization, and date of initial infection. RESULTS: The cohort of 75 149 was predominantly Hispanic (49 648/75 149, 66.1%) and included slightly more females than males (39 736, 52.9%), with few immunocompromised patients (953, 1.3%); 315 suspected reinfections were identified, with a cumulative incidence at 270 days of 0.8% (95% confidence interval (CI) 0.7-1.0%). Hospitalization was more common at suspected reinfection (36/315, 11.4%) than initial infection (4094/75 149, 5.4%). Suspected reinfection rates were higher in females (1.0%, CI 0.8-1.2% versus 0.7%, CI 0.5-0.9%, p 0.002) and immunocompromised patients (2.1%, CI 1.0-4.2% versus 0.8%, CI 0.7-1.0%, p 0.004), and lower in children than adults (0.2%, CI 0.1-0.4% versus 0.9%, CI 0.7-1.0%, p 0.023). Patients hospitalized at initial infection were more likely to have suspected reinfection (1.2%, CI 0.6-1.7% versus 0.8%, CI 0.7-1.0%, p 0.030), as were those with initial infections later in 2020 (150-day incidence 0.4%, CI 0.2-0.5% September-October versus 0.2%, CI 0.1-0.3% March-May and 0.3%, CI 0.2-0.3% June-August, p 0.008). In an adjusted Cox proportional hazards model, being female (hazard ratio (HR) 1.44, CI 1.14-1.81), adult (age 18-39, HR 2.71, CI 1.38-5.31, age 40-59 HR 2.22, CI 1.12-4.41, age ≥60 HR 2.52, CI 1.23-5.17 versus <18 years), immunocompromised (HR 2.48, CI 1.31-4.68), hospitalized (HR 1.60, CI 1.07-2.38), and initially infected later in 2020 (HR 2.26, CI 1.38-3.71 September-October versus March-May) were significant independent predictors of suspected reinfection. CONCLUSIONS: Reinfection with SARS-CoV-2 is uncommon, with suspected reinfections more likely in women, adults, immunocompromised subjects, and those previously hospitalized for coronavirus 2019 (COVID-19). This suggests a need for continued precautions and vaccination in patients with COVID-19 to prevent reinfection.

Age-Dependent Hemoglobin A1c Therapeutic Targets Reduce Diabetic Medication Changes in the Elderly.

OBJECTIVE: To assess whether implementation of age-dependent therapeutic targets for high hemoglobin A1c (HbA1c) changed clinicians' ordering of diabetes medications for older adults. BACKGROUND: In 2016, Kaiser Permanente Southern California (KPSC) changed the therapeutic targets for alerting clinicians about high HbA1c results in the electronic health record, KP HealthConnect (KPHC). Previously, all HbA1c results ≥7.0 percent were flagged as high in adult patients with diabetes. Starting in 2016, HbA1c therapeutic targets were relaxed to <7.5 percent for patients age 65 to 75, and to <8.0 percent for patients over age 75 to reduce treatment intensity and adverse events. METHODS: This retrospective analysis used logistic regression models to calculate the change in odds of a medication change following an HbA1c result after age-dependent HbA1c flags were introduced. RESULTS: The odds of medication change decreased among patients whose HbA1c targets were relaxed: Odds Ratio (OR) 0.72 (95 percent CI 0.67-0.76) for patients age 65-75 and HbA1c 7.0 percent-7.5 percent; OR 0.72 (95 percent CI 0.65-0.80) for patients over age 75 and HbA1c 7.0 percent-7.5 percent; and OR 0.67 (95 percent CI 0.61-0.75) for patients over age 75 and HbA1c 7.5 percent-8.0 percent. In the age and HbA1c ranges for which the alerts did not change, the odds of medication change generally increased or stayed the same. There was little evidence of medication de-intensification in any group. CONCLUSIONS: These findings suggest that the change in therapeutic targets was associated with a reduction in medication intensification among older adults with diabetes.