BACKGROUND/OBJECTIVE:In multisite studies, a common data model (CDM) standardizes dataset organization, variable definitions, and variable code structures and can support distributed data processing. We describe the development of a CDM for a study of virtual visit implementation in 3 Kaiser Permanente (KP) regions. METHODS:We conducted several scoping reviews to inform our study's CDM design: (1) virtual visit mode, implementation timing, and scope (targeted clinical conditions and departments); and (2) extant sources of electronic health record data to specify study measures. Our study covered the period from 2017 through June 2021. Integrity of the CDM was assessed by a chart review of random samples of virtual and in-person visits, overall and by specific conditions of interest (neck or back pain, urinary tract infection, major depression). RESULTS:The scoping reviews identified a need to address differences in virtual visit programs across the 3 KP regionsto harmonize measurement specifications for our research analyses. The final CDM contained patient-level, provider-level, and system-level measures on 7,476,604 person-years for KP members aged 19 years and above. Utilization included 2,966,112 virtual visits (synchronous chats, telephone visits, video visits) and 10,004,195 in-person visits. Chart review indicated the CDM correctly identified visit mode on>96% (n=444) of visits, and presenting diagnosis on >91% (n=482) of visits. CONCLUSIONS:Upfront design and implementation of CDMs may be resource intensive. Once implemented, CDMs, like the one we developed for our study, provide downstream programming and analytic efficiencies by harmonizing, in a consistent framework, otherwise idiosyncratic temporal and study site differences in source data.

Background Racial/ethnic disparities during the first six months of the COVID-19 pandemic led to differences in COVID-19 testing and adverse outcomes. We examine differences in testing and adverse outcomes by race/ethnicity and sex across a geographically diverse and system-based COVID-19 cohort collaboration. Methods Observational study among adults (≥18 years) within six US cohorts from March 1, 2020 to August 31, 2020 using data from electronic health record and patient reporting. Race/ethnicity and sex as risk factors were primary exposures, with health system type (integrated health system, academic health system, or interval cohort) as secondary. Proportions measured SARS-CoV-2 testing and positivity; attributed hospitalization and death related to COVID-19. Relative risk ratios (RR) with 95% confidence intervals quantified associations between exposures and main outcomes. Results 5,958,908 patients were included. Hispanic patients had the highest proportions of SARS-CoV-2 testing (16%) and positivity (18%), while Asian/Pacific Islander patients had the lowest portions tested (11%) and White patients had the lowest positivity rates (5%). Men had a lower likelihood of testing (RR = 0.90 [0.89–0.90]) and a higher positivity risk (RR = 1.16 [1.14–1.18]) compared to women. Black patients were more likely to have COVID-19-related hospitalizations (RR = 1.36 [1.28–1.44]) and death (RR = 1.17 [1.03–1.32]) compared with White patients. Men were more likely to be hospitalized (RR = 1.30 [1.16–1.22]) or die (RR = 1.70 [1.53–1.89]) compared to women. These racial/ethnic and sex differences were reflected in both health system types. Conclusions This study supports evidence of disparities by race/ethnicity and sex during the COVID-19 pandemic that persisted even in healthcare settings with reduced barriers to accessing care. Further research is needed to understand and prevent the drivers that resulted in higher burdens of morbidity among certain Black patients and men.

Disease characterization of Post-Acute Sequelae of SARS-CoV-2 (PASC) does not account for pre-existing conditions and time course of incidence. We utilized longitudinal data and matching to a COVID PCR-negative population to discriminate PASC conditions over time within our patient population during 2020. Clinical Classification Software was used to identify PASC condition groupings. Conditions were specified acute and persistent (occurring 0-30 days post COVID PCR and persisted 30-120 days post-test) or late (occurring initially 30-120 days post-test). We matched 3:1 COVID PCR-negative COVIDPCR-positive by age, sex, testing month and service area, controlling for pre-existing conditions up to four years prior; 28,118 PCR-positive to 70,293 PCR-negative patients resulted. We estimated PASC risk from the matched cohort. Risk of any PASC condition was 12% greater for PCR-positive patients in the late period with a significantly higher risk of anosmia, cardiac dysrhythmia, diabetes, genitourinary disorders, malaise, and nonspecific chest pain. Our findings contribute to a more refined PASC definition which can enhance clinical care.

ABSTRACTImportanceUnderstanding the severity of post-vaccination COVID-19 breakthrough illness among people with HIV (PWH) can inform vaccine guidelines and risk-reduction recommendations.ObjectiveEstimate the rate and risk of severe breakthrough illness among vaccinated PWH and people without HIV (PWoH) who experience a breakthrough infection.Design, setting, and participantsThe Corona-Infectious-Virus Epidemiology Team (CIVET-II) collaboration consists of four US longitudinal cohorts from integrated health systems and academic centers. Adults (≥18 years old), in-care, fully vaccinated by June 30, 2021 with HIV, and matched PWoH (on date fully vaccinated, age group, race/ethnicity, and sex) were the source population. Those who experienced a post-vaccination SARS-CoV-2 breakthrough infection were eligible. Severe COVID-19 breakthrough illness was defined as hospitalization due to COVID-19. Discrete time proportional hazards models estimated adjusted hazard ratios (aHR) and 95% confidence intervals ([,]) of severe breakthrough illness by HIV status adjusting for demographics, COVID-19 vaccine type, and clinical factors. The proportion of patients requiring mechanical ventilation or died was compared by HIV status.ExposureHIV infectionOutcomeSevere COVID-19 breakthrough illness, defined as hospitalization within 28 days after a breakthrough SARS-CoV-2 infection with a primary or secondary COVID-19 discharge diagnosis.ResultsAmong 1,241 PWH and 2,408 PWoH with breakthrough infections, the cumulative incidence of severe illness in the first 28 days was low and comparable between PWoH and PWH (7.3% vs. 6.7%, respectively, risk difference=-0.67% [-2.58%, 1.23%]). The risk of severe breakthrough illness was 59% higher in PWH with CD4 counts <350 cells/mm3 compared with PWoH (aHR=1.59 [0.99, 2.46]). In multivariable analyses among PWH, being female, older, having a cancer diagnosis, and lower CD4 count increased the risk of severe breakthrough illness, while previous COVID-19 reduced the risk. Among all patients, 10% were mechanically ventilated and 8% died, with no difference by HIV status.Conclusions and RelevanceThe risk of severe COVID-19 breakthrough illness within 28 days of a breakthrough infection was low among vaccinated PWH and PWoH. However, PWH with moderate and severe immune suppression had a higher risk of severe breakthrough infection. Recommendations for additional vaccine doses and risk-reduction strategies for PWH with moderate immune suppression may be warranted.Key PointsQuestionIn 2021, among fully vaccinated people with COVID-19 breakthrough illness, was the risk of severe illness higher in people with HIV (PWH) compared to people without HIV (PWoH)?FindingsPWH with <350 cells/mm3 have a 59% increased risk of severe breakthrough illness compared to PWoH.MeaningVaccinations effectively reduce the risk of severe COVID-19 infection in both PWH and PWoH; however, PWH having a CD4 count <350 cells/mm3 are at higher risk of severe breakthrough infection compared to PWoH. PWH with moderate immune suppression should be considered for additional vaccine dosages and other risk-reduction measures.

Background: It is not definitively known if persons with HIV (PWH) are more likely to be SARS-CoV-2 tested or test positive than persons without HIV (PWoH). We describe SARS-CoV-2 testing and positivity in 6 large geographically and demographically diverse cohorts of PWH and PWoH in the United States. Setting: The Corona Infectious Virus Epidemiology Team comprises 5 clinical cohorts within a health system (Kaiser Permanente Northern California, Oakland, CA; Kaiser Permanente Mid-Atlantic States, Rockville, MD; University of North Carolina Health, Chapel Hill, NC; Vanderbilt University Medical Center, Nashville, TN; and Veterans Aging Cohort Study) and 1 interval cohort (Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study). Methods: We calculated the proportion of patients SARS-CoV-2 tested and the test positivity proportion by HIV status from March 1 to December 31, 2020. Results: The cohorts ranged in size from 1675 to 31,304 PWH and 1430 to 3,742,604 PWoH. The proportion of PWH who were tested for SARS-CoV-2 (19.6%-40.5% across sites) was significantly higher than PWoH (14.8%-29.4%) in the clinical cohorts. However, among those tested, the proportion of patients with positive SARS-CoV-2 tests was comparable by HIV status; the difference in proportion of SARS-CoV-2 positivity ranged from 4.7% lower to 1.4% higher. Conclusions: Although PWH had higher testing proportions compared with PWoH, we did not find evidence of increased positivity in 6 large, diverse populations across the United States. Ongoing monitoring of testing, positivity, and COVID-19-related outcomes in PWH are needed, given availability, response, and durability of COVID-19 vaccines; emergence of SARS-CoV-2 variants; and latest therapeutic options.

Importance: Recommendations for additional doses of COVID vaccine are restricted to people with HIV who have advanced disease or unsuppressed HIV viral load. Understanding SARS-CoV-2 infection risk post-vaccination among PWH is essential for informing vaccination guidelines. Objective: Estimate the risk of breakthrough infections among fully vaccinated people with (PWH) and without (PWoH) HIV in the US. Design, setting, and participants: The Corona-Infectious-Virus Epidemiology Team (CIVET)-II cohort collaboration consists of 4 longitudinal cohorts from integrated health systems and academic health centers. Each cohort identified individuals ≥18 years old, in-care, and fully vaccinated for COVID-19 through 30 June 2021. PWH were matched to PWoH on date fully vaccinated, age group, race/ethnicity, and sex at birth. Incidence rates per 1,000 person-years and cumulative incidence of breakthrough infections with 95% confidence intervals ([,]) were estimated by HIV status. Cox proportional hazards models estimated adjusted hazard ratios (aHR) of breakthrough infections by HIV status adjusting for demographic factors, prior COVID-19 illness, vaccine type (BNT162b2, [Pfizer], mRNA-1273 [Moderna], Jansen Ad26.COV2.S [J&J]), calendar time, and cohort. Risk factors for breakthroughs among PWH, were also investigated. Exposure: HIV infection Outcome: COVID-19 breakthrough infections, defined as laboratory evidence of SARS-CoV-2 infection or COVID-19 diagnosis after an individual was fully vaccinated. Results: Among 109,599 individuals (31,840 PWH and 77,759 PWoH), the rate of breakthrough infections was higher in PWH versus PWoH: 44 [41, 48] vs. 31 [29, 33] per 1,000 person-years. Cumulative incidence at 210 days after date fully vaccinated was low, albeit higher in PWH versus PWoH overall (2.8% versus 2.1%, log-rank p<0.001, risk difference=0.7% [0.4%, 1.0%]) and within each vaccine type. Breakthrough infection risk was 41% higher in PWH versus PWoH (aHR=1.41 [1.28, 1.56]). Among PWH, younger age (18–24 versus 45–54), history of COVID-19 prior to fully vaccinated date, and J&J vaccination (versus Pfizer) were associated with increased risk of breakthroughs. There was no association of breakthrough with HIV viral load suppression or CD4 count among PWH. Conclusions and Relevance: COVID-19 vaccination is effective against infection with SARS-CoV-2 strains circulating through 30 Sept 2021. PWH have an increased risk of breakthrough infections compared to PWoH. Recommendations for additional vaccine doses should be expanded to all PWH.

Introduction: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are important events that may precipitate other adverse outcomes. Accurate AECOPD event identification in electronic administrative data is essential for improving population health surveillance and practice management. Objective: Develop codified algorithms to identify moderate and severe AECOPD in two US healthcare systems using administrative data and electronic medical records, and validate their performance by calculating positive predictive value (PPV) and negative predictive value (NPV). Methods: Data from two large regional integrated health systems were used. Eligible patients were identified using International Classification of Diseases (Ninth Edition) COPD diagnosis codes. Two algorithms were developed: one to identify potential moderate AECOPD by selecting outpatient/emergency visits associated with AECOPD-related codes and antibiotic/systemic steroid prescriptions; the other to identify potential severe AECOPD by selecting inpatient visits associated with corresponding codes. Algorithms were validated via patient chart review, adjudicated by a pulmonologist. To estimate PPV, 300 potential moderate AECOPD and 250 potential severe AECOPD events underwent review. To estimate NPV, 200 patients without any AECOPD identified by the algorithms (100 patients each without moderate or severe AECOPD) during the two years following the index date underwent review to identify AECOPD missed by the algorithm (false negatives). Results: The PPVs (95% confidence interval [CI]) for both moderate and severe AECOPD were high: 293/298 (98.3% [96.1-99.5]) and 216/225 (96.0% [92.5-98.2]), respectively. NPV was lower for moderate AECOPD (75.0% [65.3-83.1]) than for severe AECOPD (95.0% [88.7-98.4]). Results were consistent across both healthcare systems. Conclusion: This study developed healthcare utilization-based algorithms to identify moderate and severe AECOPD in two separate healthcare systems. PPV for both algorithms was high; NPV was lower for the moderate algorithm. Replication and consistency of results across two healthcare systems support the external validity of these findings.

Abstract Objectives The aim of this study was to identify delays in early pre-sepsis diagnosis in emergency departments (ED) using the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach. Methods SPADE methodology was employed using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (KPMAS). Study cohort included KPMAS members ≥18 years with ≥1 sepsis hospitalization 1/1/2013–12/31/2018. A look-back analysis identified treat-and-release ED visits in the month prior to sepsis hospitalizations. Top 20 diagnoses associated with these ED visits were identified; two diagnosis categories were distinguished as being linked to downstream sepsis hospitalizations. Observed-to-expected (O:E) and temporal analyses were performed to validate the symptom selection; results were contrasted to a comparison group. Demographics of patients that did and did not experience sepsis misdiagnosis were compared. Results There were 3,468 sepsis hospitalizations during the study period and 766 treat-and-release ED visits in the month prior to hospitalization. Patients discharged from the ED with fluid and electrolyte disorders (FED) and altered mental status (AMS) were most likely to have downstream sepsis hospitalizations (O:E ratios of 2.66 and 2.82, respectively). Temporal analyses revealed that these symptoms were overrepresented and temporally clustered close to the hospitalization date. Approximately 2% of sepsis hospitalizations were associated with prior FED or AMS ED visits. Conclusions Treat-and-release ED encounters for FED and AMS may represent harbingers for downstream sepsis hospitalizations. The SPADE approach can be used to develop performance measures that identify pre-sepsis.

Abstract Objectives Delays in sepsis diagnosis can increase morbidity and mortality. Previously, we performed a Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) “look-back” analysis to identify symptoms at risk for delayed sepsis diagnosis. We found treat-and-release emergency department (ED) encounters for fluid and electrolyte disorders (FED) and altered mental status (AMS) were associated with downstream sepsis hospitalizations. In this “look-forward” analysis, we measure the potential misdiagnosis-related harm rate for sepsis among patients with these symptoms. Methods Retrospective cohort study using electronic health record and claims data from Kaiser Permanente Mid-Atlantic States (2013–2018). Patients ≥18 years with ≥1 treat-and-release ED encounter for FED or AMS were included. Observed greater than expected sepsis hospitalizations within 30 days of ED treat-and-release encounters were considered potential misdiagnosis-related harms. Temporal analyses were employed to differentiate case and comparison (superficial injury/contusion ED encounters) cohorts. Results There were 4,549 treat-and-release ED encounters for FED or AMS, 26 associated with a sepsis hospitalization in the next 30 days. The observed (0.57%) minus expected (0.13%) harm rate was 0.44% (absolute) and 4.5-fold increased over expected (relative). There was a spike in sepsis hospitalizations in the week following FED/AMS ED visits. There were fewer sepsis hospitalizations and no spike in admissions in the week following superficial injury/contusion ED visits. Potentially misdiagnosed patients were older and more medically complex. Conclusions Potential misdiagnosis-related harms from sepsis are infrequent but measurable using SPADE. This look-forward analysis validated our previous look-back study, demonstrating the SPADE approach can be used to study infectious disease syndromes.

Assessing quality care for people with HIV (PWH) should not be limited to reporting on HIV Care Continuum benchmarks, particularly viral suppression rates. At Kaiser Permanente Mid-Atlantic States (KPMAS), an integrated health system providing HIV care in the District of Columbia, Maryland, and Virginia, we created a comprehensive measure of HIV quality care, including both preventative measures and clinical outcomes. We included PWH ≥18 years old with ≥6 months KPMAS membership between 2015 and 2018. Process quality metrics (QMs) include: pneumococcal vaccination and influenza vaccination; primary care physician (PCP) and/or HIV/infectious disease (HIV/ID) visits with additional HIV/ID visit; antiretroviral treatment medication fills; and syphilis and gonorrhea/chlamydia screenings. Outcome QMs include HIV RNA <200/mL and other measurements within normal range [blood pressure, body mass index (BMI), hemoglobin, blood sugar, alanine transaminase, low-density lipoproteins, estimated glomerular filtration rate]; no hospitalization/emergency department visit; no new depression diagnosis; remaining or becoming a nonsmoker. Logistic models estimated odds of achieving QMs associated with sex, age, race/ethnicity, insurance type, and HIV risk. A total of 4996 observations were analyzed. 45.6% met all process QMs, while 19.6% met all outcome QMs. Least frequently met process QM was PCP or HIV/ID visit (74.5%); least met outcome QM was BMI (60.2%). Significantly lower odds of achieving all QMs among women {odds ratio (OR) = 0.63 [95% confidence interval (CI): 0.49-0.81]} and those with Medicaid and Medicare [vs. commercial; OR = 0.48 (95% CI: 0.30-0.76) and 0.47 (95% CI: 0.31-0.71)]. Broadening the scope of HIV patient care QMs beyond viral suppression helps identify opportunities for improvement. Successful process metrics do not necessarily coincide with greater outcome metrics.

Kaiser Permanente Mid-Atlantic States (KPMAS) members are increasingly utilizing electronic encounter types, such as telephone appointments and secure messaging for healthcare purposes, although their impact on health outcomes is unknown. We evaluated whether use of alternative encounters by adult human immunodeficiency virus (HIV)-infected patients affected the likelihood of achieving viral suppression (VS). Our study population of 3114 patients contributed 6520 patient-years between 2014 and 2016. We compared VS (HIV RNA <200 copies/mL) by number of in-person visits (1 or ≥2), with further stratification for additional phone and/or e-mail encounters (none, phone only, e-mail only, and both phone and e-mail). Rate ratios (RRs) for VS by number of in-person visits and encounter types were obtained from Poisson modeling, adjusting for age, sex, race/ethnicity, and HIV risk. Compared to those with ≥2 visits, patients with one in-person visit alone were significantly less likely to achieve VS (RR = 0.93; 95% confidence interval, CI: [0.87-1.00]), as were those with one in-person visit plus a telephone encounter (0.93; [0.90-0.97]). We did not find significant differences in VS comparing patients with one in-person visit plus e-mail only (RR = 1.00; 95% CI: [0.97-1.02]) or plus e-mail and telephone (0.99; [0.97-1.01]) to those with ≥2 in-person visits. If supplemented by e-mail communications (with or without telephone contact), patients with one in-person visit per year had similar estimated rates of VS compared with ≥2 in-person visits. More research is needed to know if these findings apply to other care systems.