Purpose The purpose of this study was to develop and validate a new comprehensive patient-reported measure of treatment burden – the Patient Experience with Treatment and Self-Management (PETS). Methods A conceptual framework was used to derive the PETS with items reviewed and cognitively tested with patients. A survey battery, including a pilot version of the PETS, was mailed to 838 multi-morbid patients from two healthcare institutions for validation. Results A total of 332 multi-morbid patients returned completed surveys. Diagnostics supported deletion and consolidation of some items and domains. Confirmatory factor analysis supported a domain model for scaling comprised of 9 factors: medical information, medications, medical appointments, monitoring health, interpersonal challenges, medical/healthcare expenses, difficulty with healthcare services, role/social activity limitations, and physical/mental exhaustion. Scales showed good internal consistency (alpha range: 0.79 – 0.95). Higher PETS scores, indicative of greater treatment burden, were correlated with more distress, less satisfaction with medications, lower self-efficacy, worse physical and mental health, and lower convenience of healthcare (Ps<.001). Patients with lower health literacy, less adherence to medications, and more financial difficulties reported higher PETS scores (Ps<.01). Conclusion A comprehensive patient-reported measure of treatment burden can help to better characterize the impact of treatment and self-management burden on patient well-being and guide care toward minimally disruptive medicine.

Background Bamlanivimab and casirivimab-imdevimab are authorized for treatment of high-risk patients with mild to moderate coronavirus disease-2019 (COVID-19). We compared the outcomes of patients who received these therapies to identify factors associated with hospitalization and other clinical outcomes. Methods Adult patients who received monoclonal antibody from November 19, 2020 to February 11, 2021 were selected and divided into those who received bamlanivimab (n=2747) and casirivimab-imdevimab (n=849). The 28-day all-cause and COVID-19-related hospitalizations were compared between the groups. Results The population included 3596 patients; median age was 62 years; and 50% were female. All had ≥1 medical comorbidity; 55% had multiple comorbidities. All cause- and COVID-19-related hospitalization rates at 28 days were 3.98% and 2.56%, respectively. After adjusting for medical comorbidities, there was no significant difference in all cause- and COVID-19-related hospitalization rates between bamlanivimab and casirivimab-imdevimab (adjusted HR, 1.4, 95% CI 0.9-2.2 and 1.6, 95% CI 0.8-2.7, respectively). Chronic kidney, respiratory and cardiovascular diseases, and immunocompromised status were associated with higher likelihood of hospitalization. Conclusion This observational study on the use of bamlanivimab and casirivimab-imdevimab in high-risk patients showed similarly low rates of hospitalization. The number and type of medical comorbidities are associated with hospitalizations after monoclonal antibody treatment.

Rationale Clinical decision support (CDS) tools leveraging electronic health records (EHRs) have been an approach for addressing challenges in asthma care but remain under-studied through clinical trials. Objectives To assess the effectiveness and efficiency of Asthma-Guidance and Prediction System (A-GPS), an Artificial Intelligence (AI)-assisted CDS tool, in optimizing asthma management through a randomized clinical trial (RCT). Methods This was a single-center pragmatic RCT with a stratified randomization design conducted for one year in the primary care pediatric practice of the Mayo Clinic, MN. Children (<18 years) diagnosed with asthma receiving care at the study site were enrolled along with their 42 primary care providers. Study subjects were stratified into three strata (based on asthma severity, asthma care status, and asthma diagnosis) and were blinded to the assigned groups. Measurements Intervention was a quarterly A-GPS report to clinicians including relevant clinical information for asthma management from EHRs and machine learning-based prediction for risk of asthma exacerbation (AE). Primary endpoint was the occurrence of AE within 1 year and secondary outcomes included time required for clinicians to review EHRs for asthma management. Main results Out of 555 participants invited to the study, 184 consented for the study and were randomized (90 in intervention and 94 in control group). Median age of 184 participants was 8.5 years. While the proportion of children with AE in both groups decreased from the baseline (P = 0.042), there was no difference in AE frequency between the two groups (12% for the intervention group vs. 15% for the control group, Odds Ratio: 0.82; 95%CI 0.374–1.96; P = 0.626) during the study period. For the secondary end points, A-GPS intervention, however, significantly reduced time for reviewing EHRs for asthma management of each participant (median: 3.5 min, IQR: 2–5), compared to usual care without A-GPS (median: 11.3 min, IQR: 6.3–15); p<0.001). Mean health care costs with 95%CI of children during the trial (compared to before the trial) in the intervention group were lower than those in the control group (-$1,036 [-$2177, $44] for the intervention group vs. +$80 [-$841, $1000] for the control group), though there was no significant difference (p = 0.12). Among those who experienced the first AE during the study period (n = 25), those in the intervention group had timelier follow up by the clinical care team compared to those in the control group but no significant difference was found (HR = 1.93; 95% CI: 0.82–1.45, P = 0.10). There was no difference in the proportion of duration when patients had well-controlled asthma during the study period between the intervention and the control groups. Conclusions While A-GPS-based intervention showed similar reduction in AE events to usual care, it might reduce clinicians’ burden for EHRs review resulting in efficient asthma management. A larger RCT is needed for further studying the findings. Trial registration ClinicalTrials.gov Identifier: NCT02865967.

Background & Aims Little is known in the United States (US) about the epidemiology of liver diseases that develop only during (are unique to) pregnancy. We investigated the incidence of liver diseases unique to pregnancy in Olmsted County, MN and long-term maternal and fetal outcomes. Methods We identified 247 women with liver diseases unique to pregnancy from 1996 through 2010 using the Rochester Epidemiology Project database. The crude incidence rate was calculated by the number of liver disease cases divided by 35,101 pregnancies. Results Of pregnant women with liver diseases, 134 had preeclampsia with liver dysfunction, 72 had hemolysis-associated increased levels of liver enzymes and low-platelet (HELLP) syndrome, 26 had intrahepatic cholestasis of pregnancy, 14 had hyperemesis gravidarum with abnormal liver enzymes, and 1 had acute fatty liver of pregnancy. The crude incidence of liver diseases unique to pregnancy was 0.77%. Outcomes were worse among women with HELLP or preeclampsia than the other disorders—of women with HELLP, 70% had a premature delivery, 4% had abruptio placentae, 3% had acute kidney injury, and 3% had infant death. Of women with preeclampsia, 56.0% had a premature delivery, 4% had abruptio placentae, 3% had acute kidney injury, and 0.7% had infant death. After 7 median years of follow up (range, 0–18 years), 14% of the women developed recurrent liver disease unique to pregnancy; the proportions were highest in women with initial hyperemesis gravidarum (36%) or intrahepatic cholestasis of pregnancy (35%). Women with preeclampsia were more likely to develop subsequent hepatobiliary diseases. Conclusion We found the incidence of liver disease unique to pregnancy in Olmsted County, MN to be lower than that reported from Europe or US tertiary referral centers. Maternal and fetal outcomes in Olmsted County were better than those reported from other studies, but fetal mortality was still high (0.7%–3.0%). Women with preeclampsia or HELLP are at higher risk for peri-partum complications and subsequent development of comorbidities.