OBJECTIVE: To investigate causes of discrepancies in the association between early pregnancy oral glucocorticoid (OGC) use and preterm birth risk among women with rheumatoid arthritis (RA) in health care utilization data from California Medicaid (Medi-Cal) and the prospective cohort MotherToBaby Pregnancy Studies. METHODS: Separately, we estimated risk ratios (RRs) between OGC exposure before gestational day 140 and preterm birth risk in data from Medi-Cal (2007-2013; n = 844) and MotherToBaby (2003-2014; n = 528). We explored differences in socioeconomic status, OGC dose distribution, exposure misclassification, and confounding by RA severity across the data sources. RESULTS: Preterm birth risk in women without OGC was 17.3% in Medi-Cal and was 9.7% in MotherToBaby. There was no association between OGC and preterm birth in Medi-Cal (adjusted RR 1.00 [95% confidence interval (95% CI) 0.71, 1.42]), and a 1.85-fold (95% CI 1.20, 2.84) increased preterm birth risk in MotherToBaby. When restricting each sample to women with a high-school diploma or less, preterm birth risk following no OGC exposure was 15.9% in Medi-Cal and 16.7% in MotherToBaby; adjusted RRs were 1.16 (95% CI 0.74, 1.80) in Medi-Cal and 0.81 (95% CI 0.25, 2.64) in MotherToBaby. Cumulative OGC dose was higher in MotherToBaby (median 684 mg) than in Medi-Cal (median 300 mg). An OGC dose of ≤300 mg was not associated with increased preterm birth risk. Exposure misclassification and confounding by RA severity were unlikely explanations of differences. CONCLUSION: Higher baseline preterm birth risk and lower OGC dose distribution in Medi-Cal may explain the discrepancies. Studies are needed to understand the effects of autoimmune disease severity and undertreatment on preterm birth risk in low-income populations.

Background

There is limited information regarding the impact of dose and gestational timing of oral corticosteroid (OCS) use on preterm birth (PTB), especially among women with asthma.

Objectives

To evaluate OCS dose and timing on PTB for asthma and, as a comparison, systemic lupus erythematosus (SLE).

Methods

We used health care data from California Medicaid enrollees linked to birth certificates (2007-2013), identifying women with asthma (n = 22,084) and SLE (n = 1174). We estimated risk ratios (RR) for OCS cumulative dose trajectories and other disease-related medications before gestational day 140 and hazard ratios (HR) for time-varying exposures after day 139.

Results

For asthma, PTB risk was 14.0% for no OCS exposure and 14.3%, 16.8%, 20.5%, and 32.7% in low, medium, medium-high, and high cumulative dose trajectory groups, respectively, during the first 139 days. The high-dose group remained associated with PTB after adjustment (adjusted RR [aRR]: 1.46; 95% confidence interval [CI]: 1.00, 2.15). OCS dose after day 139 was not clearly associated with PTB, nor were controller medications. For SLE, PTB risk for no OCS exposure was 24.9%, and it was 39.1% in low- and 61.2% in high-dose trajectory groups. aRR were 1.80 (95% CI: 1.34, 2.40) for high and 1.24 (95% CI: 0.97, 1.58) for low groups. Only prednisone equivalent dose >20 mg/day after day 139 was associated with increased PTB (adjusted HR: 2.54; 95% CI: 1.60, 4.03).

Conclusions

For asthma, higher OCS doses early in pregnancy, but not later, were associated with increased PTB. For SLE, higher doses early and later in pregnancy were associated with PTB.

PURPOSE: Using a novel, electronic health record (EHR)-based approach, to estimate the prevalence of prescription medication use at 2, 4, and 6 months postpartum among lactating individuals. METHODS: We utilized automated EHR data from a US health system that records infant feeding information at well-child visits. We linked mothers who received prenatal care to their infants born May 2018-June 2019, and we required infants to have ≥1 well-child visit between 31 and 90 days of life (i.e., 2-month well-child visit with a ±1 month window). Mothers were classified as lactating at the 2-month well-child visit if their infant received breast milk at the 2-month well-child visit. For subsequent well-child visits at 4 and 6 months, mothers were considered lactating if their infant was still receiving breast milk. RESULTS: We identified 6013 mothers meeting inclusion criteria, and 4158 (69.2%) were classified as lactating at the 2-month well-child visit. Among those classified as lactating, the most common medication classes dispensed around the 2-month well-child visit were oral progestin contraceptives (19.1%), selective serotonin reuptake inhibitors (8.8%), first generation cephalosporins (4.3%), thyroid hormones (3.5%), nonsteroidal anti-inflammatory agents (3.4%), penicillinase-resistant penicillins (3.1%), topical corticosteroids (2.9%), and oral imidazole-related antifungals (2.0%). The most common medication classes were similar around the 4 and 6-month well-child visits although prevalence estimates were often lower. CONCLUSIONS: Progestin-only contraceptives, antidepressants, and antibiotics were the most dispensed medications among lactating mothers. With routine collection of breastfeeding information, mother-infant linked EHR data may overcome limitations in previous studies of medication utilization during lactation. These data should be considered for studies of medication safety during lactation given the need for human safety data.

Objective

To evaluate the associations between oral corticosteroid (OCS) dose early and late in pregnancy and preterm birth (PTB) among women with RA.

Methods

Pregnant women in the MotherToBaby Pregnancy Studies (2003-2014) with RA (n = 528) were included in the primary analysis. Information was collected by phone interview and from medical records. We estimated risk ratios (RR) for OCS dose trajectories and other disease-related medications before gestational day 140 and hazard ratios (HR) for time-varying exposures after gestational day 139.

Results

PTB risk was 15.5% overall. Compared with no OCS, PTB risk was increased in high (adjusted (a)RR: 4.77 (95% CI: 2.76, 8.26)) and medium (aRR: 1.81 (95% CI: 1.10, 2.97)) cumulative OCS dose trajectories during the first 139 gestational days. The low cumulative trajectory group was associated with an increased risk of PTB that was not statistically significant (aRR: 1.38 (95% CI: 0.79, 2.38)), and DMARDs were not associated with PTB (biologic DMARDs aHR: 1.08 (95% CI: 0.70, 1.66); non-biologic DMARDs aHR: 0.87 (95% CI: 0.55, 1.38)). OCS exposure to ⩾10 mg of prednisone equivalent daily dose after gestational day 139 vs none was associated with increased PTB rate (aHR: 2.45 (95% CI: 1.32, 4.56)), whereas <10 mg was associated with a modestly increased rate of PTB that was not statistically significant (aHR: 1.18 (95% CI: 0.60, 2.30)).

Conclusion

Higher OCS doses vs no OCS use, both earlier and later in pregnancy, were associated with an increase in PTB among women with RA.

OBJECTIVE: To examine the cost-effectiveness of a community-based Diabetes Prevention Program (DPP) for Medicaid beneficiaries from the perspective of the health care sector. DATA SOURCES/STUDY SETTING: A total of 847 Medicaid enrollees at high risk for type 2 diabetes participating in a community-based DPP. STUDY DESIGN: Pre- and post clinical outcome and cost data were used as inputs into a validated diabetes simulation model. The model was used to evaluate quality-adjusted life years (QALYs) and health care costs over a 40-year time horizon from the perspective of the health care sector. DATA COLLECTION/EXTRACTION METHODS: Clinical outcome and cost data were derived from a study examining the effect of financial incentives on weight loss. PRINCIPAL FINDINGS: Study participants lost an average of 4.2 lb (p < .001) and increased high-density lipoprotein cholesterol by 1.75 mg/dl (p = .002). Intervention costs, which included financial incentives for participation and weight loss, were $915 per participant. The incremental cost-effectiveness ratio was estimated to be $14,011 per QALY but was sensitive to the time horizon studied. CONCLUSIONS: Widespread adoption of community-based DPP has the potential to reduce diabetes and cardiovascular-related morbidity and mortality for low-income persons at high risk for diabetes and may be a cost-effective investment for Medicaid programs.

Background

Limited data exist on population-based risks and risk ratios (RRs) of coronavirus disease 2019 (COVID-19)-associated hospitalizations and clinical outcomes stratified by age and race/ethnicity.

Methods

Using data from electronic health records and claims from 4 US health systems for the period March 2020-March 2021, we calculated risk and RR by age and race/ethnicity for COVID-19-associated hospitalizations and clinical outcomes among adults (≥18 years). COVID-19-associated hospitalizations were defined based on COVID-19 discharge codes or a positive severe acute respiratory syndrome coronavirus 2 result. Proportions of acute exacerbations of underlying conditions were estimated among hospitalized patients with select underlying conditions, stratified by age and race/ethnicity.

Results

Among 2.6 million adults included in the patient cohort, 6879 had COVID-19-associated hospitalizations during March 2020-March 2021 (risk: 264 per 100 000 population). Compared with younger, non-Hispanic White adults, non-Hispanic Black and Hispanic adults aged ≥65 years had the highest hospitalization risk ratios (RR, 8.6; 95% CI, 7.6-9.9; and RR, 9.3; 95% CI, 8.5-10.3, respectively). Among hospitalized adults with COVID-19 and renal disease or cardiovascular disease, the highest proportion of acute renal failure (55.5%) or congestive heart failure (43.9%) occurred in older, non-Hispanic Black patients. Among hospitalized adults with chronic lung disease or asthma, the highest proportion of respiratory failure (62.9%) or asthma exacerbation (66.7%) occurred in older, Hispanic patients.

Conclusions

During the first year of the US COVID-19 pandemic in this cohort, older non-Hispanic Black and Hispanic adults had the highest relative risks of COVID-19-associated hospitalization and adverse outcomes and, among those with select underlying conditions, the highest occurrences of acute exacerbations of underlying conditions.

We sought to develop and validate a clinical calculator that can be used to quantify risk for appendicitis on a continuous scale for patients with acute abdominal pain. The pediatric appendicitis risk calculator (pARC) was developed and validated through secondary analyses of 3 distinct cohorts. The derivation sample included visits to 9 pediatric emergency departments between March 2009 and April 2010. The validation sample included visits to a single pediatric emergency department from 2003 to 2004 and 2013 to 2015. Variables evaluated were as follows: age, sex, temperature, nausea and/or vomiting, pain duration, pain location, pain with walking, pain migration, guarding, white blood cell count, and absolute neutrophil count. We used stepwise regression to develop and select the best model. Test performance of the pARC was compared with the Pediatric Appendicitis Score (PAS). The derivation sample included 2423 children, 40% of whom had appendicitis. The validation sample included 1426 children, 35% of whom had appendicitis. The final pARC model included the following variables: sex, age, duration of pain, guarding, pain migration, maximal tenderness in the right-lower quadrant, and absolute neutrophil count. In the validation sample, the pARC exhibited near perfect calibration and a high degree of discrimination (area under the curve: 0.85; 95% confidence interval: 0.83 to 0.87) and outperformed the PAS (area under the curve: 0.77; 95% confidence interval: 0.75 to 0.80). By using the pARC, almost half of patients in the validation cohort could be accurately classified as at <15% risk or ≥85% risk for appendicitis, whereas only 23% would be identified as having a comparable PAS of <3 or >8. In our validation cohort of patients with acute abdominal pain, the pARC accurately quantified risk for appendicitis.

Background

Appendicitis is a common surgical emergency in children, yet diagnosis can be challenging. An electronic health record (EHR) based, clinical decision support (CDS) system called Appy CDS was designed to help guide management of pediatric patients with acute abdominal pain within the Health Care Systems Research Network (HCSRN).

Objectives

To describe the development and implementation of a clinical decision support tool (Appy CDS) built independently but synergistically at two large HCSRN affiliated health systems using well-established platforms, and to assess the tool's Triage component, aiming to identify pediatric patients at increased risk for appendicitis.

Results

Despite differences by site in design and implementation, such as the use of alerts, incorporating gestalt, and other workflow variations across sites, using simple screening questions and automated exclusions, both systems were able to identify a population with similar appendicitis rates (11.8 percent and 10.6 percent), where use of the full Appy CDS would be indicated.

Discussion

These 2 HCSRN sites designed Appy CDS to capture a population at risk for appendicitis and deliver CDS to that population while remaining locally relevant and adhering to organizational preferences. Despite different approaches to point-of-care CDS, the sites have identified similar cohorts with nearly identical background rates of appendicitis.

Next steps

The full Appy CDS tool, providing personalized risk assessment and tailored recommendations, is undergoing evaluation as part of a pragmatic cluster randomized trial aiming to reduce reliance on advanced diagnostic imaging. The novel approaches to CDS we present could serve as the basis for future ED interventions.

Objectives

Pediatric appendicitis remains a challenging diagnosis in the emergency department (ED). Available risk prediction algorithms may contribute to excessive ED imaging studies. Incorporation of physician gestalt assessment could help refine predictive tools and improve diagnostic imaging decisions.

Methods

This study was a subanalysis of a parent study that prospectively enrolled patients ages 5 to 20.9 years with a chief complaint of abdominal pain presenting to 11 community EDs within an integrated delivery system between October 1, 2016, and September 30, 2018. Prior to diagnostic imaging, attending emergency physicians enrolled patients with ≤5 days of right-sided or diffuse abdominal pain using a Web-based application embedded in the electronic health record. Predicted risk (gestalt) of acute appendicitis was prospectively entered using a sliding scale from 1% to 100%. As a planned secondary analysis, we assessed the performance of gestalt via c-statistics of receiver operating characteristic (ROC) curves; tested associations between gestalt performance and patient, physician, and facility characteristics; and examined clinical characteristics affecting gestalt estimates.

Results

Of 3,426 patients, 334 (9.8%) had confirmed appendicitis. Physician gestalt had excellent ROC curve characteristics (c-statistic = 0.83, 95% confidence interval = 0.81 to 0.85), performing particularly well in the low-risk strata (appendicitis rate = 1.1% in gestalt 1%-10% range, negative predictive value of 98.9% for appendicitis diagnosis). Physicians with ≥5 years since medical school graduation demonstrated improved gestalt performance over those with less experience (p = 0.007). All clinical characteristics tested, except pain <24 hours, were significantly associated with physician gestalt value (p < 0.05).

Conclusion

Physician gestalt for acute appendicitis diagnosis performed well, especially in low-risk patients and when employed by experienced physicians.