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Objective: To develop and validate an expanded obstetric comorbidity score for predicting severe maternal morbidity that can be applied consistently across contemporary U.S. patient discharge data sets.Methods: Discharge data from birth hospitalizations in California during 2016-2017 were used to develop the score. The outcomes were severe maternal morbidity, defined using the Centers for Disease Control and Prevention index, and nontransfusion severe maternal morbidity (excluding cases where transfusion was the only indicator of severe maternal morbidity). We selected 27 potential patient-level risk factors for severe maternal morbidity, identified using International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes. We used a targeted causal inference approach integrated with machine learning to rank the risk factors based on adjusted risk ratios (aRRs). We used these results to assign scores to each comorbidity, which sum to a single numeric score. We validated the score in California and national data sets and compared the performance to that of a previously developed obstetric comorbidity index.Results: Among 919,546 births, the rates of severe maternal morbidity and nontransfusion severe maternal morbidity were 168 and 74 per 10,000 births, respectively. The highest risk comorbidity was placenta accreta spectrum (aRR of 30.5 for severe maternal morbidity and 54.7 for nontransfusion severe maternal morbidity) and the lowest was gestational diabetes mellitus (aRR of 1.06 for severe maternal morbidity and 1.12 for nontransfusion severe maternal morbidity). Normalized scores based on the aRR were developed for each comorbidity, which ranged from 1 to 59 points for severe maternal morbidity and from 1 to 36 points for nontransfusion severe maternal morbidity. The overall performance of the expanded comorbidity scores was good (C-statistics were 0.78 for severe maternal morbidity and 0.84 for nontransfusion severe maternal morbidity in California data and 0.82 and 0.87, respectively, in national data) and improved on prior comorbidity indices developed for obstetric populations. Calibration plots showed good concordance between predicted and actual risks of the outcomes.Conclusion: We developed and validated an expanded obstetric comorbidity score to improve comparisons of severe maternal morbidity rates across patient populations with different comorbidity case mixes. [ABSTRACT FROM AUTHOR]

Background: It is estimated that vaccinating 50%-70% of school-aged children for influenza can produce population-wide indirect effects. We evaluated a city-wide school-located influenza vaccination (SLIV) intervention that aimed to increase influenza vaccination coverage. The intervention was implemented in ≥95 preschools and elementary schools in northern California from 2014 to 2018. Using a matched cohort design, we estimated intervention impacts on student influenza vaccination coverage, school absenteeism, and community-wide indirect effects on laboratory-confirmed influenza hospitalizations.Methods and Findings: We used a multivariate matching algorithm to identify a nearby comparison school district with pre-intervention characteristics similar to those of the intervention school district and matched schools in each district. To measure student influenza vaccination, we conducted cross-sectional surveys of student caregivers in 22 school pairs (2017 survey, N = 6,070; 2018 survey, N = 6,507). We estimated the incidence of laboratory-confirmed influenza hospitalization from 2011 to 2018 using surveillance data from school district zip codes. We analyzed student absenteeism data from 2011 to 2018 from each district (N = 42,487,816 student-days). To account for pre-intervention differences between districts, we estimated difference-in-differences (DID) in influenza hospitalization incidence and absenteeism rates using generalized linear and log-linear models with a population offset for incidence outcomes. Prior to the SLIV intervention, the median household income was $51,849 in the intervention site and $61,596 in the comparison site. The population in each site was predominately white (41% in the intervention site, 48% in the comparison site) and/or of Hispanic or Latino ethnicity (26% in the intervention site, 33% in the comparison site). The number of students vaccinated by the SLIV intervention ranged from 7,502 to 10,106 (22%-28% of eligible students) each year. During the intervention, influenza vaccination coverage among elementary students was 53%-66% in the comparison district. Coverage was similar between the intervention and comparison districts in influenza seasons 2014-2015 and 2015-2016 and was significantly higher in the intervention site in seasons 2016-2017 (7%; 95% CI 4, 11; p < 0.001) and 2017-2018 (11%; 95% CI 7, 15; p < 0.001). During seasons when vaccination coverage was higher among intervention schools and the vaccine was moderately effective, there was evidence of statistically significant indirect effects: The DID in the incidence of influenza hospitalization per 100,000 in the intervention versus comparison site was -17 (95% CI -30, -4; p = 0.008) in 2016-2017 and -37 (95% CI -54, -19; p < 0.001) in 2017-2018 among non-elementary-school-aged individuals and -73 (95% CI -147, 1; p = 0.054) in 2016-2017 and -160 (95% CI -267, -53; p = 0.004) in 2017-2018 among adults 65 years or older. The DID in illness-related school absences per 100 school days during the influenza season was -0.63 (95% CI -1.14, -0.13; p = 0.014) in 2016-2017 and -0.80 (95% CI -1.28, -0.31; p = 0.001) in 2017-2018. Limitations of this study include the use of an observational design, which may be subject to unmeasured confounding, and caregiver-reported vaccination status, which is subject to poor recall and low response rates.Conclusions: A city-wide SLIV intervention in a large, diverse urban population was associated with a decrease in the incidence of laboratory-confirmed influenza hospitalization in all age groups and a decrease in illness-specific school absence rate among students in 2016-2017 and 2017-2018, seasons when the vaccine was moderately effective, suggesting that the intervention produced indirect effects. Our findings suggest that in populations with moderately high background levels of influenza vaccination coverage, SLIV programs are associated with further increases in coverage and reduced influenza across the community. [ABSTRACT FROM AUTHOR]

Vietnamese Americans have high rates of hepatitis B virus (HBV) infection but low rates of knowledge and screening. A population-based survey conducted in 2011 of Vietnamese Americans in two geographic areas (n = 1666) was analyzed. The outcome variables were having heard of HBV and a score summarizing knowledge of HBV transmission. Most respondents (86.0%) had heard of HBV. Correct knowledge of transmission ranged from 59.5% for sex, 68.1% for sharing toothbrushes, 78.6% for during birth, and 85.0% for sharing needles. In multivariable analyses, factors associated with having heard of HBV and higher knowledge included Northern California residence, longer U.S. residence, higher education, family history of HBV, and discussing HBV with family/friends. Higher income was associated with having heard of HBV. English fluency and being U.S.-born were associated with higher knowledge. Interventions to increase knowledge of HBV transmission are needed to decrease this health disparity among Vietnamese Americans. [ABSTRACT FROM AUTHOR]

BACKGROUND: Opioid prescribing patterns, including those after surgery, have been implicated as a significant contributor to the US opioid crisis. A plethora of interventions--from nudges to reminders--have been deployed to improve prescribing behavior, but reasons for persistent outlier behavior are often unknown. STUDY DESIGN: Our institution employs multiple prescribing resources and a near real-time, feedback-based intervention to promote appropriate opioid prescribing. Since 2019, an automated system has emailed providers when a prescription exceeds the 75th percentile of typical opioid consumption for a given procedure--as defined by institutional data collection. Emails include population consumption metrics and an optional survey on rationale for prescribing. Responses were analyzed to understand why providers choose to prescribe atypically large discharge opioid prescriptions. We then compared provider prescriptions against patient consumption. RESULTS: During the study period, 10,672 eligible postsurgical patients were discharged; 2,013 prescriptions (29.4% of opioid prescriptions) exceeded our institutional guideline. Surveys were completed by outlier prescribers for 414 (20.6%) encounters. Among patients where both consumption data and prescribing rationale surveys were available, 35.2% did not consume any opioids after discharge and 21.5% consumed <50% of their prescription. Only 93 (39.9%) patients receiving outlier prescriptions were outlier consumers. Most common reasons for prescribing outlier amounts were attending preference (34%) and prescriber analysis of patient characteristics (34%). CONCLUSIONS: The top quartile of opioid prescriptions did not align with, and often far exceeded, patient postdischarge opioid consumption. Providers cite assessment of patient characteristics as a common driver of decision-making, but this did not align with patient usage for approximately 50% of patients. [ABSTRACT FROM AUTHOR]

We measured the effectiveness of a city-wide school-located influenza vaccination (SLIV) program implemented in over 102 elementary schools in Oakland, California. We conducted a retrospective cohort study among Kaiser Permanente Northern California (KPNC) members of all ages residing in either the intervention or a multivariate-matched comparison site from September 2011 - August 2017. Outcomes included medically attended acute respiratory illness (MAARI), influenza hospitalization, and Oseltamivir prescriptions. We estimated difference-in-differences (DIDs) in 2014–15, 2015–16, and 2016–17 using generalized linear models and adjusted for race, ethnicity, age, sex, health plan, and language. Pre-intervention member characteristics were similar between sites. The proportion of KPNC members vaccinated for influenza by KPNC or the SLIV program was 8–11% higher in the intervention site than the comparison site during the intervention period. Among school-aged children, SLIV was associated with lower Oseltamivir prescriptions per 1,000 (DIDs: −3.5 (95% CI −5.5, −1.5) in 2015–16; −4.0 (95% CI −6.5, −1.6) in 2016–17) but not with other outcomes. SLIV was associated with lower MAARI per 1,000 in adults 65 + years (2014–15: −13.2, 95% CI –23.2, −3.2; 2015–16: −21.5, 95% CI −31.1, −11.9; 2016–17: −13.0, 95% CI –23.2, −2.9). There were few significant associations with other outcomes among adults. A city-wide SLIV intervention was associated with higher influenza vaccination coverage, lower Oseltamivir prescriptions in school-aged children, and lower MAARI among people over 65 years, suggesting possible indirect effects of SLIV among older adults. [ABSTRACT FROM AUTHOR]

Background: Increasing influenza vaccination coverage in school-aged children may substantially reduce community transmission. School-located influenza vaccinations (SLIV) aim to promote vaccinations by increasing accessibility, which may be especially beneficial to race/ethnicity groups that face high barriers to preventative care. Here, we evaluate the effectiveness of a city-wide SLIV program by race/ethnicity from 2014 to 2018., Methods: We used multivariate matching to pair schools in the intervention district in Oakland, CA with schools in a comparison district in West Contra Costa County, CA. We distributed cross-sectional surveys to measure caregiver-reported student vaccination status and estimated differences in vaccination coverage levels and reasons for non-vaccination between districts stratifying by race/ethnicity. We estimated difference-in-differences (DID) of laboratory confirmed influenza hospitalization incidence between districts stratified by race/ethnicity using surveillance data., Results: Differences in influenza vaccination coverage in the intervention vs. comparison district were larger among White (2017-18: 21.0% difference [95% CI: 9.7%, 32.3%]) and Hispanic/Latino (13.4% [8.8%, 18.0%]) students than Asian/Pacific Islander (API) (8.9% [1.3%, 16.5%]), Black (5.9% [-2.2%, 14.0%]), and multiracial (6.3% [-1.8%, 14.3%)) students. Concerns about vaccine effectiveness or safety were more common among Black and multiracial caregivers. Logistical barriers were less common in the intervention vs. comparison district, with the largest difference among White students. In both districts, hospitalizations in 2017-18 were higher in Blacks (Intervention: 111.5 hospitalizations per 100,00; Comparison: 134.1 per 100,000) vs. other races/ethnicities. All-age influenza hospitalization incidence was lower in the intervention site vs. comparison site among White/API individuals in 2016-17 (DID -25.14 per 100,000 [95% CI: -40.14, -10.14]) and 2017-18 (-36.6 per 100,000 [-52.7, -20.5]) and Black older adults in 2017-18 (-282.2 per 100,000 (-508.4, -56.1]), but not in other groups., Conclusions: SLIV was associated with higher vaccination coverage and lower influenza hospitalization, but associations varied by race/ethnicity. SLIV alone may be insufficient to ensure equitable influenza outcomes., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: EP reports prior grant support from the Shoo the Flu organization during her work at the Alameda County Public Health Department. PDK and TL report grant support from the U.S. Centers for Disease Control and Prevention to the California Emerging Infections Program., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Importance: Medically complex patients are a heterogeneous group that contribute to a substantial proportion of health care costs. Coordinated efforts to improve care and reduce costs for this patient population have had limited success to date., Objective: To define distinct patient clinical profiles among the most medically complex patients through clinical interpretation of analytically derived patient clusters., Design, Setting, and Participants: This cohort study analyzed the most medically complex patients within Kaiser Permanente Northern California, a large integrated health care delivery system, based on comorbidity score, prior emergency department admissions, and predicted likelihood of hospitalization, from July 18, 2018, to July 15, 2019. From a starting point of over 5000 clinical variables, we used both clinical judgment and analytic methods to reduce to the 97 most informative covariates. Patients were then grouped using 2 methods (latent class analysis, generalized low-rank models, with k-means clustering). Results were interpreted by a panel of clinical stakeholders to define clinically meaningful patient profiles., Main Outcomes and Measures: Complex patient profiles, 1-year health care utilization, and mortality outcomes by profile., Results: The analysis included 104 869 individuals representing 3.3% of the adult population (mean [SD] age, 70.7 [14.5] years; 52.4% women; 39% non-White race/ethnicity). Latent class analysis resulted in a 7-class solution. Stakeholders defined the following complex patient profiles (prevalence): high acuity (9.4%), older patients with cardiovascular complications (15.9%), frail elderly (12.5%), pain management (12.3%), psychiatric illness (12.0%), cancer treatment (7.6%), and less engaged (27%). Patients in these groups had significantly different 1-year mortality rates (ranging from 3.0% for psychiatric illness profile to 23.4% for frail elderly profile; risk ratio, 7.9 [95% CI, 7.1-8.8], P < .001). Repeating the analysis using k-means clustering resulted in qualitatively similar groupings. Each clinical profile suggested a distinct collaborative care strategy to optimize management., Conclusions and Relevance: The findings suggest that highly medically complex patient populations may be categorized into distinct patient profiles that are amenable to varying strategies for resource allocation and coordinated care interventions.