Explore the vast range of titles available.

Background National working groups identify the need for return on investment research conducted from the purchaser perspective; however, the field has not developed standardized methods for measuring the basic components of return on investment, including costing out the value of work productivity loss due to illness. Recent literature is divided on whether the most commonly used method underestimates or overestimates this loss. The goal of this manuscript is to characterize between and within variation in the cost of work productivity loss from illness estimated by the most commonly used method and its two refinements. Methods One senior health benefit specialist from each of 325 companies employing 100+ workers completed a cross-sectional survey describing their company size, industry and policies/practices regarding work loss which allowed the research team to derive the variables needed to estimate work productivity loss from illness using three methods. Compensation estimates were derived by multiplying lost work hours from presenteeism and absenteeism by wage/fringe. Disruption correction adjusted this estimate to account for co-worker disruption, while friction correction accounted for labor substitution. The analysis compared bootstrapped means and medians between and within these three methods. Results The average company realized an annual $617 (SD = $75) per capita loss from depression by compensation methods and a $649 (SD = $78) loss by disruption correction, compared to a $316 (SD = $58) loss by friction correction (p < .0001). Agreement across estimates was 0.92 (95% CI 0.90, 0.93). Conclusion Although the methods identify similar companies with high costs from lost productivity, friction correction reduces the size of compensation estimates of productivity loss by one half. In analyzing the potential consequences of method selection for the dissemination of interventions to employers, intervention developers are encouraged to include friction methods in their estimate of the economic value of interventions designed to improve absenteeism and presenteeism. Business leaders in industries where labor substitution is common are encouraged to seek friction corrected estimates of return on investment. Health policy analysts are encouraged to target the dissemination of productivity enhancing interventions to employers with high losses rather than all employers. Trial registration Clinical trials registration number: NCT01013220 .

The potential association between bivalent COVID-19 vaccination and ischemic stroke remains uncertain, despite several studies conducted thus far. This study aimed to evaluate the risk of ischemic stroke following bivalent COVID-19 vaccination during the 2022-2023 season. A self-controlled case series study was conducted among members aged 12 years and older who experienced ischemic stroke between September 1, 2022, and March 31, 2023, in a large health care system. Ischemic strokes were identified using International Classification of Diseases, Tenth Revision codes in emergency departments and inpatient settings. Exposures were Pfizer-BioNTech or Moderna bivalent COVID-19 vaccination. Risk intervals were prespecified as 1-21 days and 1-42 days after bivalent vaccination; all non-risk-interval person-time served as the control interval. The incidence of ischemic stroke was compared in the risk interval and control interval using conditional Poisson regression. We conducted overall and subgroup analyses by age, history of SARS-CoV-2 infection, and coadministration of influenza vaccine. When an elevated risk was detected, we performed a chart review of ischemic strokes and analyzed the risk of chart-confirmed ischemic stroke. With 4933 ischemic stroke events, we found no increased risk within the 21-day risk interval for the 2 vaccines and by subgroups. However, risk of ischemic stroke was elevated within the 42-day risk interval among individuals aged younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day; the relative incidence (RI) was 2.13 (95% CI 1.01-4.46). Among those who also had a history of SARS-CoV-2 infection, the RI was 3.94 (95% CI 1.10-14.16). After chart review, the RIs were 2.34 (95% CI 0.97-5.65) and 4.27 (95% CI 0.97-18.85), respectively. Among individuals aged younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the RI was 2.62 (95% CI 1.13-6.03) before chart review and 2.24 (95% CI 0.78-6.47) after chart review. Stratified analyses by sex did not show a significantly increased risk of ischemic stroke after bivalent vaccination. While the point estimate for the risk of chart-confirmed ischemic stroke was elevated in a risk interval of 1-42 days among individuals younger than 65 years with coadministration of Pfizer-BioNTech bivalent and influenza vaccines on the same day and among individuals younger than 65 years who received Moderna bivalent vaccine and had a history of SARS-CoV-2 infection, the risk was not statistically significant. The potential association between bivalent vaccination and ischemic stroke in the 1-42-day analysis warrants further investigation among individuals younger than 65 years with influenza vaccine coadministration and prior SARS-CoV-2 infection. Furthermore, the findings on ischemic stroke risk after bivalent COVID-19 vaccination underscore the need to evaluate monovalent COVID-19 vaccine safety during the 2023-2024 season.

IntroductionPublic health efforts to reduce opioid overdose fatalities include educating people at risk and expanding access to naloxone, a medication that reverses opioid-induced respiratory depression. People receiving long-term opioid therapy (LTOT) are at increased risk for overdose, yet naloxone uptake in this population remains low. The objective of this study was to determine if a targeted, digital health intervention changed patient risk behaviour, increased naloxone uptake and increased knowledge about opioid overdose prevention and naloxone.MethodsWe conducted a pragmatic randomised clinical trial among patients prescribed LTOT in a healthcare delivery system in Colorado. Participants were randomly assigned to receive an animated overdose prevention and naloxone educational video (intervention arm) or usual care (control arm). The 6 min video was designed to educate patients about opioid overdose and naloxone, increase overdose risk perception and prompt them to purchase naloxone from the pharmacy. Over an 8-month follow-up, opioid risk behaviour was assessed with the Opioid-Related Behaviours in Treatment survey instrument, and overdose and naloxone knowledge was measured with the Prescription Opioid Overdose Knowledge Scale after viewing the video at baseline. Naloxone dispensations were evaluated using pharmacy data over a 12-month period. Data were analysed with generalised linear mixed effects and log-binomial regression models.ResultsThere were 519 participants in the intervention arm and 485 participants in the usual care arm. Opioid risk behaviour did not differ between the study arms over time (study arm by time interaction p=0.93). There was no difference in naloxone uptake between the arms (risk ratio 1.13, 95% CI 0.77 to 1.66). Knowledge was significantly greater in the intervention arm compared with usual care (p<0.001).ConclusionsA targeted, digital health intervention video effectively increased knowledge about opioid overdose and naloxone, without increasing opioid risk behaviour. Naloxone uptake did not differ between the intervention and usual care arms.Trial registration numberNCT03337009.

COVID-19 vaccination is crucial in combating the COVID-19 pandemic. Messenger RNA COVID-19 vaccines were initially authorized as a 2-dose primary series and have been widely used in the United States; completing the 2-dose primary series offers protection against infection, severe illness, and death. Understanding the risk factors for not completing the 2-dose primary series is critical to evaluate COVID-19 vaccination programs and promote completion of the 2-dose primary series. This study examined potential risk factors for not completing a 2-dose primary series of mRNA COVID-19 vaccination. We conducted a retrospective cohort study among members aged ≥18 years from a large integrated health care system, Kaiser Permanente Southern California, from December 14, 2020, to June 30, 2022. Noncompletion of the 2-dose primary series was defined as not completing the second dose within 6 months after receipt of the first dose. Crude noncompletion rates were estimated overall and by demographic characteristics, health care use patterns, comorbidity, and community-level socioeconomic factors. A Poisson regression model was fit to examine associations of individual-level and community-level risk factors with noncompletion of the 2-dose primary series. Among 2.5 million recipients of ≥1 dose of mRNA COVID-19 vaccines, 3.3% (n=81,202) did not complete the second dose within 6 months. Members aged 25-44 years, 65-74 years, and ≥75 years were less likely to not complete the 2-dose primary series than those aged 18-24 years, while members aged 45-64 years were more likely to not complete the 2-dose primary series (adjusted risk ratio [aRR] 1.13, 95% CI 1.10-1.15). Male sex was associated with a higher risk of noncompletion (aRR 1.17, 95% CI 1.15-1.19). Hispanic and non-Hispanic Black race/ethnicity were associated with a lower risk of noncompletion (range aRR 0.78-0.91). Having Medicaid and prior influenza vaccination were associated with a higher risk of noncompletion. Having SARS-CoV-2 infection, experiencing an adverse event, or having an inpatient and emergency department visit during the minimum recommended dose intervals were associated with a higher risk of not completing the 2-dose primary series (aRR 1.98, 95% CI 1.85-2.12; 1.99, 95% CI 1.43-2.76; and 1.85, 95% CI 1.77-1.93, respectively). Those who received the first dose after June 30, 2021, were more likely to not complete the 2-dose primary series within 6 months of receipt of the first dose. Despite limitations such as being a single-site study and the inability to consider social factors such as employment and vaccine attitudes, our study identified several risk factors for not completing a 2-dose primary series of mRNA vaccination, including being male; having Medicaid coverage; and experiencing SARS-CoV-2 infection, adverse events, or inpatient and emergency department visits during the minimum recommended dose intervals. These findings can inform future efforts in developing effective strategies to enhance vaccination coverage and improve the completion rate of necessary doses.

Understanding the long-term impact of the COVID-19 pandemic on health care utilization is important to health care organizations and policy makers for strategic planning, as well as to researchers when designing studies that use observational electronic health record data during the pandemic period. This study aimed to evaluate the changes in health care utilization across all care settings among a large, diverse, and insured population in the United States during the COVID-19 pandemic. We conducted a retrospective cohort study within 8 health care organizations participating in the Vaccine Safety Datalink Project using electronic health record data from members of all ages from January 1, 2017, to December 31, 2021. The visit rates per person-year were calculated monthly during the study period for 4 health care settings combined as well as by inpatient, emergency department (ED), outpatient, and telehealth settings, both among all members and members without COVID-19. Difference-in-difference analysis and interrupted time series analysis were performed to assess the changes in visit rates from the prepandemic period (January 2017 to February 2020) to the early pandemic period (April-December 2020) and the later pandemic period (July-December 2021), respectively. An exploratory analysis was also conducted to assess trends through June 2023 at one of the largest sites, Kaiser Permanente Southern California. The study included more than 11 million members from 2017 to 2021. Compared with the prepandemic period, we found reductions in visit rates during the early pandemic period for all in-person care settings. During the later pandemic period, overall use reached 8.36 visits per person-year, exceeding the prepandemic level of 7.49 visits per person-year in 2019 (adjusted percent change 5.1%, 95% CI 0.6%-9.9%); inpatient and ED visits returned to prepandemic levels among all members, although they remained low at 0.095 and 0.241 visits per person-year, indicating a 7.5% and 8% decrease compared to pre-pandemic levels among members without COVID-19, respectively. Telehealth visits, which were approximately 42% of the volume of outpatient visits during the later pandemic period, were increased by 97.5% (95% CI 86.0%-109.7%) from 0.865 visits per person-year in 2019 to 2.35 visits per person-year in the later pandemic period. The trends in Kaiser Permanente Southern California were similar to those of the entire study population. Visit rates from January 2022 to June 2023 were stable and appeared to be a continuation of the use levels observed at the end of 2021. Telehealth services became a mainstay of the health care system during the late COVID-19 pandemic period. Inpatient and ED visits returned to prepandemic levels, although they remained low among members without evidence of COVID-19. Our findings provide valuable information for strategic resource allocation for postpandemic patient care and for designing observational studies involving the pandemic period.

BACKGROUND Renin-angiotensin-aldosterone system (RAAS) inhibitors are associated with hyperkalemia, but there is little evidence demonstrating patients who receive potassium monitoring have a lower rate of hyperkalemia. OBJECTIVE To evaluate the association between potassium monitoring and serious hyperkalemia-associated adverse outcomes among patients with diabetes newly initiating RAAS inhibitor therapy. DESIGN Retrospective observational study. PARTICIPANTS Patients with diabetes without end-stage renal disease initiating RAAS inhibitor therapy between 2001 and 2006 at three integrated health care systems. MEASUREMENTS Potassium monitoring and first hyperkalemia-associated adverse event during the initial year of therapy. Hyperkalemia-associated adverse events included hospitalizations, emergency department visits or deaths within 24 h of hyperkalemia diagnosis and/or diagnostic potassium ≥6 mmol/l. Incidence rates were calculated in person-years (p-y). We used inverse probability propensity score weighting to adjust for differences between patients with and without monitoring; Poisson regression was used to obtain adjusted relative risks. RESULTS A total of 19,391 of 27,355 patients (71%) received potassium monitoring. Serious hyperkalemia-associated events occurred at an incidence rate of 10.2 per 1,000 p-y. Compared to patients without monitoring, adjusted relative risk of hyperkalemia-associated adverse events among all patients with monitoring was 0.50 (0.37, 0.66); in the subset of patients who also had chronic kidney disease (n = 2,176), adjusted relative risk was 0.29 (0.18, 0.46). CONCLUSIONS Patients prescribed RAAS inhibitors who have both diabetes and chronic kidney disease and receive potassium monitoring are less likely to experience a serious hyperkalemia-associated adverse event compared to similar patients who did not receive potassium monitoring. This evidence supports existing consensus-based guidelines.

We performed a simulation study to compare four study designs [(matched-cohort, vaccinated-only (risk-interval) cohort, case–control, and self-controlled case-series (SCCS)] in the context of vaccine safety active surveillance. For each combination of various incidence levels (3, 30, 300 per 10 5 person-years) and relative risks (RR 1.5–18), 100 case sets were infused into the cohort, matching 10 5 vaccinated to 10 5 unvaccinated on age and gender. The matched-cohort was converted into weekly accumulated data intervals with the other three study design samples drawn from each. Analyses were with appropriate regression models. The signal detection time was the first week where the log likelihood ratio (LLR) exceeded the upper boundary from the MaxSPRT sequential analysis method. Empirical type I (false positive) and type II (power) error rates and risk estimate bias were also calculated. The matched-cohort design exhibited the shortest detection time, lowest false positive rate and highest empirical power followed by the risk-interval cohort, SCCS, and case–control. In most monitoring weeks, the risk estimate bias was smallest for the cohort, followed by the risk-interval, SCCS and case–control designs. The cohort study design performed the best in the sequential analysis of active surveillance for vaccine safety. The risk-interval cohort and SCCS designs offer reasonable and efficient alternatives, especially if selection bias is a concern. Future research should address seasonality or age effects.

Background Individuals prescribed long-term opioid therapy (LTOT) have increased risk of readmission and death after hospital discharge. The risk of opioid overdose during the immediate post-discharge time period is unknown. Objective To examine the association between time since hospital discharge and opioid overdose among individuals prescribed LTOT. Design Self-controlled risk interval analysis. Participants Adults prescribed LTOT with at least one hospital discharge at a safety-net health system and a non-profit healthcare organization in Colorado. Main Measures We identified individuals prescribed LTOT who were discharged from January 2006 through June 2019. The outcome was a composite of fatal and non-fatal opioid overdoses during a 90-day post-discharge observation period, identified using electronic health record (EHR) and vital statistics data. Risk intervals included days 0–6 after index and subsequent hospital discharges. Control intervals ranged from days 7 to 89 after index discharge and included all other time during the observation period that did not fall within a risk interval or time readmitted during a subsequent hospitalization, which was excluded. Poisson regression was used to estimate incidence rate ratios (IRR) and 95% confidence intervals (CI) for overdose events during risk in comparison to control intervals. Key Results We identified 7695 adults (63.3% over 55 years, 59.4% female, 20.3% Hispanic) who experienced 9499 total discharges during the study period. Twenty-one overdoses occurred during their observation periods (1174 per 100,000 person-years [9 in risk, 12 in control]). Overdose risk was significantly higher during the risk interval in comparison to the control interval (IRR 6.92; 95% CI 2.92–16.43). Conclusion During the first 7 days after hospital discharge, individuals prescribed LTOT appear to be at elevated risk for opioid overdose. Clarifying mechanisms of overdose risk may help inform in-hospital and post-discharge prevention strategies.