Need for Sexual, Reproductive, and Mental Health Promotion Among Diverse College Students in a COVID-19 Era.

In 2020, the COVID-19 pandemic forced unprecedented disruptions in higher education operations. While the adverse mental health effects experienced by college students due to these changes are well documented, less is known about the impact on their sexual and reproductive health (SRH), and the reciprocal relationships between SRH and mental health among adolescents and emerging adults. This position paper reviews existing literature on the effects of the COVID-19 pandemic on SRH, sexual violence, unintended pregnancy, sexually transmitted illness and human immunodeficiency virus rates and highlights issues specific to college-aged males, females, racial/ethnic and sexual minorities, and individuals with disabilities. The need to conceptualize SRH as an integral component of normal development, overall health, and well-being in the context of COVID-19 is discussed. The need to prioritize the design and implementation of developmentally appropriate, evidence-based SRH interventions specifically targeting college students is identified. Furthermore, an intergenerational approach to SRH that includes parents/caregivers and/or college faculty and staff (e.g., coaches, trainers) could facilitate comprehensive SRH prevention programming that enhances sexual violence prevention training programs currently mandated by many colleges. Policies and programs designed to mitigate adverse pandemic-related exacerbations in negative SRH outcomes are urgently needed and should be included in mainstream clinical psychology, not only focused on preventing unwanted outcomes but also in promoting rewarding interpersonal relationships and overall well-being. Recommendations for clinical psychologists and mental health researchers are made.

Using Potentially Preventable Severe Maternal Morbidity to Monitor Hospital Performance.

BACKGROUND: The Centers for Disease Control and Prevention (CDC) measure of severe maternal morbidity (SMM) quantifies the burden of SMM but is not restricted to potentially preventable SMM. The authors adapted the CDC SMM measure for this purpose and evaluated it for use as a hospital performance measure. METHODS: Guidelines for defining performance SMM (pSMM) were (1) exclusion of preexisting conditions from outcome; (2) exclusion of inconsistently documented outcomes; and (3) risk adjustment for conditions that preceded hospitalization. California maternal hospital discharge data from 2016 to 2017 were used for model development, and 2018 data were used for model testing and evaluation of hospital performance. Separate models were developed for hospital types (Community, Teaching, Integrated Delivery System [IDS], and IDS Teaching), generating model-based expected pSMM values. Observed-to-expected (O/E) ratios were calculated for hospitals and used to categorize them as overperforming, average performing, or underperforming using 95% confidence intervals. Performance categories were compared for pSMM vs. CDC SMM (excluding blood transfusion). RESULTS: The overall 2016-2018 pSMM rate was 0.44%. All hospital types had over- and underperformers, and the proportions of Community, Teaching, IDS, and IDS Teaching hospitals whose performance differed from their performance on the CDC SMM measure were 12.1%, 25.0%, 38.9%, and 66.7%, respectively. CONCLUSION: The rate of potentially preventable SMM as defined by pSMM (0.44%) was less than half the previously published rate of CDC SMM (1.03%). pSMM identified differences in performance across hospitals, and pSMM and CDC SMM classified hospitals' performances differently. pSMM may be suitable for hospital comparisons because it identifies potentially preventable, hospital-acquired SMM that should be responsive to quality improvement activities.

Severe Maternal Morbidity in California Hospitals: Performance Based on a Validated Multivariable Prediction Model.

BACKGROUND: Severe maternal morbidity (SMM) is under development as a quality indicator for maternal health care. The aim of this study is to evaluate California hospital performance based on a standardized SMM measure. METHODS: California maternal hospital delivery discharge data from 2016 to 2017 were used to develop logistic regression models for SMM, adjusted for clinical risk factors at admission. Data from 2018 were used to test the models and evaluate hospital performance. SMM was defined per the Centers for Disease Control and Prevention, including (excluding) blood transfusion. Independent models were developed for each hospital type: community, teaching, integrated delivery system (IDS), and IDS teaching. Within each type, model-based expected SMM values and observed-to-expected (O/E) ratios were calculated for each hospital. For each hospital type, hospitals were ranked by O/E ratio, and over- and underperforming hospitals were identified using 95% confidence intervals. RESULTS: Rates of SMM including (excluding) transfusion by hospital type were 1.7% (0.9%) for community, 2.7% (1.5%) for teaching, 2.3% (1.2%) for IDS, and 3.0% (1.6%) for IDS teaching hospitals. In higher-volume community hospitals (≥ 500 births/year), the proportion of underperformers including (excluding) transfusion was 20.7% (11.0%). Summing over all hospital types, 25.3% (14.9%) of hospitals were identified as underperformers in that they experienced significantly more SMM events than expected including (excluding) transfusion. CONCLUSION: California hospital discharge data demonstrated significant hospital variation in standardized childbirth SMM. These data suggest that a standardized SMM measure may help guide and monitor statewide quality improvement efforts.

A scoping review of severe maternal morbidity: describing risk factors and methodological approaches to inform population-based surveillance.

BACKGROUND: Current interest in using severe maternal morbidity (SMM) as a quality indicator for maternal healthcare will require the development of a standardized method for estimating hospital or regional SMM rates that includes adjustment and/or stratification for risk factors. OBJECTIVE: To perform a scoping review to identify methodological considerations and potential covariates for risk adjustment for delivery-associated SMM. SEARCH METHODS: Following the guidelines for Preferred Reporting Items for Systematic Reviews and Meta-analyses Extension for Scoping Reviews, systematic searches were conducted with the entire PubMed and EMBASE electronic databases to identify publications using the key term "severe maternal morbidity." SELECTION CRITERIA: Included studies required population-based cohort data and testing or adjustment of risk factors for SMM occurring during the delivery admission. Descriptive studies and those using surveillance-based data collection methods were excluded. DATA COLLECTION AND ANALYSIS: Information was extracted into a pre-defined database. Study design and eligibility, overall quality and results, SMM definitions, and patient-, hospital-, and community-level risk factors and their definitions were assessed. MAIN RESULTS: Eligibility criteria were met by 81 studies. Methodological approaches were heterogeneous and study results could not be combined quantitatively because of wide variability in data sources, study designs, eligibility criteria, definitions of SMM, and risk-factor selection and definitions. Of the 180 potential risk factors identified, 41 were categorized as pre-existing conditions (e.g., chronic hypertension), 22 as obstetrical conditions (e.g., multiple gestation), 22 as intrapartum conditions (e.g., delivery route), 15 as non-clinical variables (e.g., insurance type), 58 as hospital-level variables (e.g., delivery volume), and 22 as community-level variables (e.g., neighborhood poverty). CONCLUSIONS: The development of a risk adjustment strategy that will allow for SMM comparisons across hospitals or regions will require harmonization regarding: a) the standardization of the SMM definition; b) the data sources and population used; and c) the selection and definition of risk factors of interest.