With the emergence of the novel SARS-CoV-2 and the disease it causes; COVID-19, compliance with/adherence to protective measures is needed. Information is needed on which measures are, or are not, being undertaken. Data collected from the COVID Impact Survey, conducted by the non-partisan and objective research organization NORC at the University of Chicago on April, May, and June of 2020, were analyzed through weighted Quasi-Poisson regression modeling to determine the association of demographics, socioeconomics, and health conditions with protective health measures taken at the individual level in response to COVID-19. The three surveys included data from 18 regional areas including 10 states (CA, CO, FL, LA, MN, MO, MT, NY, OR, and TX) and 8 Metropolitan Statistical Areas (Atlanta, GA; Baltimore, MD; Birmingham, AL; Chicago, IL; Cleveland and Columbus, OH; Phoenix, AZ; and Pittsburgh, PA). Individuals with higher incomes, insurance, higher education levels, large household size, age 60+, females, minorities, those who have asthma, have hypertension, overweight or obese, and those who suffer from mental health issues during the pandemic were significantly more likely to report taking precautionary protective measures relative to their counterparts. Protective measures for the three subgroups with a known relationship to COVID-19 (positive for COVID-19, knowing an individual with COVID-19, and knowing someone who had died from COVID-19) were strongly associated with the protective health measures of washing hands, avoiding public places, and canceling social engagements. This study provides first baseline data on the response to the national COVID-19 pandemic at the individual level in the US. The found heterogeneity in the response to this pandemic by different variables can inform future research and interventions to reduce exposure to the novel SARS-CoV-2 virus.

Background: Naltrexone, a medication for addiction treatment (MAT), is an FDA-approved medication recommended for the treatment of alcohol use disorder (AUD). Despite the high prevalence of AUD and efficacy of naltrexone, only a small percentage of individuals with AUD receive treatment. Objectives: To identify trends for the prescription of naltrexone in AUD admissions in substance use treatment centers across the U.S. Methods: Data from the 2000–2018 U.S. Treatment Episode Data Set: Admissions (TEDS-A) were used in temporal trend analysis of naltrexone prescription in admissions that only used alcohol. Data from the 2019 National Survey of Substance Abuse Treatment Services (N-SSATS) were also used to characterize medication use among AUD clients across different treatment service settings. Results: Treatment of AUD with naltrexone was 0.49% in 2000 and tripled from 0.53% in 2015 to 1.64% in 2018 in AUD admissions (p < 0.0001 for the Cochran–Armitage trend test). Women, middle-aged adults, and admissions for clients living in the Northeast U.S. were more likely to be prescribed naltrexone than their respective counterparts, as were admissions with prior treatment episodes and referrals through alcohol/drug use care providers, who paid for treatment primarily through private insurance, used alcohol daily in the month prior to admission, and waited 1–7 days to enter treatment. Naltrexone was more commonly prescribed by AUD admissions compared to acamprosate and disulfiram and was more frequently prescribed in residential and outpatient services as opposed to hospital inpatient services. Conclusions: Naltrexone remains underutilized for AUD, and factors that influence prescription of medication are multifaceted. This study may contribute to the creation of effective interventions aimed at reducing naltrexone disparities for AUD.

Background: Preterm birth (PTB) represents a significant public health problem in the United States and throughout the world. Accurate identification of preterm labor (PTL) evaluation visits is the first step in conducting PTB-related research. Objective: We aimed to develop a validated computerized algorithm to identify PTL evaluation visits and extract cervical length (CL) measures from electronic health records (EHRs) within a large integrated health care system. Methods: We used data extracted from the EHRs at Kaiser Permanente Southern California between 2009 and 2020. First, we identified triage and hospital encounters with fetal fibronectin (fFN) tests, transvaginal ultrasound (TVUS) procedures, PTL medications, or PTL diagnosis codes within 240/7-346/7 gestational weeks. Second, clinical notes associated with triage and hospital encounters within 240/7-346/7 gestational weeks were extracted from EHRs. A computerized algorithm and an automated process were developed and refined by multiple iterations of chart review and adjudication to search the following PTL indicators: fFN tests, TVUS procedures, abdominal pain, uterine contractions, PTL medications, and descriptions of PTL evaluations. An additional process was constructed to extract the CLs from the corresponding clinical notes of these identified PTL evaluation visits. Results: A total of 441,673 live birth pregnancies were identified between 2009 and 2020. Of these, 103,139 pregnancies (23.35%) had documented PTL evaluation visits identified by the computerized algorithm. The trend of pregnancies with PTL evaluation visits slightly decreased from 24.41% (2009) to 17.42% (2020). Of the first 103,139 PTL visits, 19,439 (18.85%) and 44,423 (43.97%) had an fFN test and a TVUS, respectively. The percentage of first PTL visits with an fFN test decreased from 18.06% at 240/7 gestational weeks to 2.32% at 346/7 gestational weeks, and TVUS from 54.67% at 240/7 gestational weeks to 12.05% in 346/7 gestational weeks. The mean (SD) of the CL was 3.66 (0.99) cm with a mean range of 3.61-3.69 cm that remained stable across the study period. Of the pregnancies with PTL evaluation visits, the rate of PTB remained stable over time (20,399, 19.78%). Validation of the computerized algorithms against 100 randomly selected records from these potential PTL visits showed positive predictive values of 97%, 94.44%, 100%, and 96.43% for the PTL evaluation visits, fFN tests, TVUS, and CL, respectively, along with sensitivity values of 100%, 90%, and 90%, and specificity values of 98.8%, 100%, and 98.6% for the fFN test, TVUS, and CL, respectively. Conclusions: The developed computerized algorithm effectively identified PTL evaluation visits and extracted the corresponding CL measures from the EHRs. Validation against this algorithm achieved a high level of accuracy. This computerized algorithm can be used for conducting PTL- or PTB-related pharmacoepidemiologic studies and patient care reviews.

Background: Migraine is a common neurological disorder characterized by repeated headaches of varying intensity. The prevalence and severity of migraine headaches disproportionally affects women, particularly during the postpartum period. Moreover, migraines during pregnancy have been associated with adverse maternal outcomes, including preeclampsia and postpartum stroke. However, due to the lack of a validated instrument for uniform case ascertainment on postpartum migraine headache, there is uncertainty in the reported prevalence in the literature. Objective: The aim of this study was to evaluate the completeness and accuracy of reporting postpartum migraine headache coding in a large integrated health care system’s electronic health records (EHRs) and to compare the coding quality before and after the implementation of the International Classification of Diseases, 10th revision, Clinical Modification (ICD-10-CM) codes and pharmacy records in EHRs. Methods: Medical records of 200 deliveries in all 15 Kaiser Permanente Southern California hospitals during 2 time periods, that is, January 1, 2012 through December 31, 2014 (International Classification of Diseases, 9th revision, Clinical Modification [ICD-9-CM] coding period) and January 1, 2017 through December 31, 2019 (ICD-10-CM coding period), were randomly selected from EHRs for chart review. Two trained research associates reviewed the EHRs for all 200 women for postpartum migraine headache cases documented within 1 year after delivery. Women were considered to have postpartum migraine headache if either a mention of migraine headache (yes for diagnosis) or a prescription for treatment of migraine headache (yes for pharmacy records) was noted in the electronic chart. Results from the chart abstraction served as the gold standard and were compared with corresponding diagnosis and pharmacy prescription utilization records for both ICD-9-CM and ICD-10-CM coding periods through comparisons of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), as well as the summary statistics of F-score and Youden J statistic (J). The kappa statistic (κ) for interrater reliability was calculated. Results: The overall agreement between the identification of migraine headache using diagnosis codes and pharmacy records compared to the medical record review was strong. Diagnosis coding (F-score=87.8%; J=82.5%) did better than pharmacy records (F-score=72.7%; J=57.5%) when identifying cases, but combining both of these sources of data produced much greater accuracy in the identification of postpartum migraine cases (F-score=96.9%; J=99.7%) with sensitivity, specificity, PPV, and NPV of 100%, 99.7%, 93.9%, and 100%, respectively. Results were similar across the ICD-9-CM (F-score=98.7%, J=99.9%) and ICD-10-CM coding periods (F-score=94.9%; J=99.6%). The interrater reliability between the 2 research associates for postpartum migraine headache was 100%. Conclusions: Neither diagnostic codes nor pharmacy records alone are sufficient for identifying postpartum migraine cases reliably, but when used together, they are quite reliable. The completeness of the data remained similar after the implementation of the ICD-10-CM coding in the EHR system.

Preeclampsia remains one of the leading causes of perinatal mortality worldwide. Little is known about the modifiable risk factors that can be identified and addressed early in pregnancy to reduce the risk of preeclampsia and its associated adverse outcomes. We sought to determine if there is a synergistic effect of prepregnancy body-mass index and obstructive sleep apnea (OSA) on the risk of preeclampsia. We conducted a retrospective cohort study of singleton pregnancies delivered in Kaiser Permanente Southern California hospitals between January 1, 2010, and December 31, 2020 (n = 342,349). Preeclampsia and sleep apnea were ascertained using clinical diagnosis codes. Body mass index (BMI) in kg/m2 measured during prenatal care visits was categorized as normal (18.5–24.9), overweight (25–29.9), and obese (≥30). Multivariable logistic regression was used to estimate adjusted relative risks (aRR) and 95% confidence intervals (CI). Compared with normal weight in pregnancy, overweight (aRR : 1.6; 95% CI: 1.5, 1.7) and obese BMI (aRR: 2.5; 95% CI: 2.4, 2.6) were associated with an increased risk of preeclampsia. Independent of prepregnancy body-mass index, a pregnancy with OSA was associated with an increased risk of preeclampsia (aRR: 2.2; 95% CI: 1.8, 2.6). Compared with normal weight without the diagnosis of OSA in a pregnancy, overweight (aRR: 4.6; 95% CI: 2.9, 7.4) and obese BMI (aRR: 3.8; 95% CI: 3.2, 4.6) with the diagnosis of OSA were associated with an increased risk of preeclampsia. OSA and elevated body-mass index have an independent and additive relationship with preeclampsia. Overweight women at risk of preeclampsia should be advised of a higher likelihood of developing preeclampsia when both conditions occur together and may benefit from close monitoring and early interventions for these modifiable risk factors.