Real-World Cost-Effectiveness of Pulmonary Vein Isolation for Atrial Fibrillation: A Target Trial Approach.

OBJECTIVES: Randomized controlled trials of pulmonary vein isolation (PVI) for treating atrial fibrillation (AF) have proven the procedure's efficacy. Studies assessing its empirical cost-effectiveness outside randomized trial settings are lacking. We aimed to evaluate the effectiveness and cost-effectiveness of PVI versus medical therapy for AF. METHODS: We followed a target trial approach using the Swiss-AF cohort, a prospective observational cohort study that enrolled patients with AF between 2014 and 2017. Resource utilization and cost information were collected through claims data. Quality of life was measured with EQ-5D-3L utilities. We estimated incremental cost-effectiveness ratios (ICERs) from the perspective of the Swiss statutory health insurance system. RESULTS: Patients undergoing PVI compared with medical therapy had a 5-year overall survival advantage with a hazard ratio of 0.75 (95% CI 0.46-1.21; P = .69) and a 19.8% SD improvement in quality of life (95% CI 15.5-22.9; P < .001), at an incremental cost of 29 604 Swiss francs (CHF) (95% CI 16 354-42 855; P < .001). The estimated ICER was CHF 158 612 per quality-adjusted life-year (QALY) gained within a 5-year time horizon. Assuming similar health effects and costs over 5 additional years changed the ICER to CHF 82 195 per QALY gained. Results were robust to the sensitivity analyses performed. CONCLUSIONS: Our results show that PVI might be a cost-effective intervention within the Swiss healthcare context in a 10-year time horizon, but unlikely to be so at 5 years, if a willingness-to-pay threshold of CHF 100 000 per QALY gained is assumed. Given data availability, we find target trial designs are a valuable tool for assessing the cost-effectiveness of healthcare interventions outside of randomized controlled trial settings.

County-Level Factors Associated With Cardiovascular Mortality by Race/Ethnicity.

Background Persistent racial/ethnic disparities in cardiovascular disease (CVD) mortality are partially explained by healthcare access and socioeconomic, demographic, and behavioral factors. Little is known about the association between race/ethnicity-specific CVD mortality and county-level factors. Methods and Results Using 2017 county-level data, we studied the association between race/ethnicity-specific CVD age-adjusted mortality rate (AAMR) and county-level factors (demographics, census region, socioeconomics, CVD risk factors, and healthcare access). Univariate and multivariable linear regressions were used to estimate the association between these factors; R2 values were used to assess the factors that accounted for the greatest variation in CVD AAMR by race/ethnicity (non-Hispanic White, non-Hispanic Black, and Hispanic/Latinx individuals). There were 659 740 CVD deaths among non-Hispanic White individuals in 2698 counties; 100 475 deaths among non-Hispanic Black individuals in 717 counties; and 49 493 deaths among Hispanic/Latinx individuals across 267 counties. Non-Hispanic Black individuals had the highest mean CVD AAMR (320.04 deaths per 100 000 individuals), whereas Hispanic/Latinx individuals had the lowest (168.42 deaths per 100 000 individuals). The highest CVD AAMRs across all racial/ethnic groups were observed in the South. In unadjusted analyses, the greatest variation (R2) in CVD AAMR was explained by physical inactivity for non-Hispanic White individuals (32.3%), median household income for non-Hispanic Black individuals (24.7%), and population size for Hispanic/Latinx individuals (28.4%). In multivariable regressions using county-level factor categories, the greatest variation in CVD AAMR was explained by CVD risk factors for non-Hispanic White individuals (35.3%), socioeconomic factors for non-Hispanic Black (25.8%), and demographic factors for Hispanic/Latinx individuals (34.9%). Conclusions The associations between race/ethnicity-specific age-adjusted CVD mortality and county-level factors differ significantly. Interventions to reduce disparities may benefit from being designed accordingly.

Cost-Effectiveness of Transitional Care Services After Hospitalization With Heart Failure.

Background: Patients with heart failure (HF) discharged from the hospital are at high risk for death and rehospitalization. Transitional care service interventions attempt to mitigate these risks. Objective: To assess the cost-effectiveness of 3 types of postdischarge HF transitional care services and standard care. Design: Decision analytic microsimulation model. Data Sources: Randomized controlled trials, clinical registries, cohort studies, Centers for Disease Control and Prevention life tables, Centers for Medicare & Medicaid Services data, and National Inpatient Sample (Healthcare Cost and Utilization Project) data. Target Population: Patients with HF who were aged 75 years at hospital discharge. Time Horizon: Lifetime. Perspective: Health care sector. Intervention: Disease management clinics, nurse home visits (NHVs), and nurse case management. Outcome Measures: Quality-adjusted life-years (QALYs), costs, net monetary benefits, and incremental cost-effectiveness ratios (ICERs). Results of Base-Case Analysis: All 3 transitional care interventions examined were more costly and effective than standard care, with NHVs dominating the other 2 interventions. Compared with standard care, NHVs increased QALYs (2.49 vs. 2.25) and costs ($81 327 vs. $76 705), resulting in an ICER of $19 570 per QALY gained. Results of Sensitivity Analysis: Results were largely insensitive to variations in in-hospital mortality, age at baseline, or costs of rehospitalization. Probabilistic sensitivity analysis confirmed that transitional care services were preferred over standard care in nearly all 10 000 samples, at willingness-to-pay thresholds of $50 000 or more per QALY gained. Limitation: Transitional care service designs and implementations are heterogeneous, leading to uncertainty about intervention effectiveness and costs when applied in particular settings. Conclusion: In older patients with HF, transitional care services are economically attractive, with NHVs being the most cost-effective strategy in many situations. Transitional care services should become the standard of care for postdischarge management of patients with HF. Primary Funding Source: Swiss National Science Foundation, Research Council of Norway, and an Intermountain-Stanford collaboration.

Use of E-values for addressing confounding in observational studies-an empirical assessment of the literature.

BACKGROUND: E-values are a recently introduced approach to evaluate confounding in observational studies. We aimed to empirically assess the current use of E-values in published literature. METHODS: We conducted a systematic literature search for all publications, published up till the end of 2018, which cited at least one of two inceptive E-value papers and presented E-values for original data. For these case publications we identified control publications, matched by journal and issue, where the authors had not calculated E-values. RESULTS: In total, 87 papers presented 516 E-values. Of the 87 papers, 14 concluded that residual confounding likely threatens at least some of the main conclusions. Seven of these 14 named potential uncontrolled confounders. 19 of 87 papers related E-value magnitudes to expected strengths of field-specific confounders. The median E-value was 1.88, 1.82, and 2.02 for the 43, 348, and 125 E-values where confounding was felt likely to affect the results, unlikely to affect the results, or not commented upon, respectively. The 69 case-control publication pairs dealt with effect sizes of similar magnitude. Of 69 control publications, 52 did not comment on unmeasured confounding and 44/69 case publications concluded that confounding was unlikely to affect study conclusions. CONCLUSIONS: Few papers using E-values conclude that confounding threatens their results, and their E-values overlap in magnitude with those of papers acknowledging susceptibility to confounding. Facile automation in calculating E-values may compound the already poor handling of confounding. E-values should not be a substitute for careful consideration of potential sources of unmeasured confounding. If used, they should be interpreted in the context of expected confounding in specific fields.

Diabetes-attributable mortality in the United States from 2003 to 2016 using a multiple-cause-of-death approach.

AIMS: Deaths attributable to diabetes may be underestimated using an underlying cause of death (COD) approach in U.S. death records. This study sought to characterize the burden of diabetes deaths using a multiple-cause of death approach (underlying and contributing COD) and to identify temporal changes in co-reported causes of death among those with diabetes listed anywhere on their death records. METHODS: COD were identified using data from the National Center for Health Statistics from 2003 to 2016. We calculated age-adjusted mortality rates for diabetes as the underlying or contributing COD by race/ethnicity. We used ICD-10 codes to identify leading causes of death among those with and without diabetes on their death records. We compared temporal changes in deaths due to cardiovascular disease, cerebrovascular disease, cancer, and other causes. RESULTS: The study population included 34,313,964 decedents aged ≥25 from 2003 to 2016. Diabetes was listed as an underlying COD in approximately 3.0% (n = 1,031,000) and 6.7% (n = 2,295,510) of the death records, respectively. Decedents with diabetes listed as an underlying COD experienced a 16% decline in mortality, and the race/ethnicity-specific average annual percentage changes (AAPC) showed significant declining trends for most groups (AAPC ranged from 0.18 to -2.83%). Cardiovascular disease remained the leading underlying COD among diabetes-attributable deaths, although its proportion of deaths fell from 31 to 27% over time. Co-reported COD diversified, and were more likely to include hypertension and hypertensive renal disease among those with diabetes on their death records. CONCLUSIONS: Our findings underscore the importance of using a multiple-cause-of-death approach for more completely characterizing diabetes' contribution to mortality.

Prevalence of potentially inappropriate prescribing in a subpopulation of older European clinical trial participants: a cross-sectional study.

OBJECTIVES: To estimate and compare the prevalence and type of potentially inappropriate prescribing (PIP) and potential prescribing omissions (PPOs) among community-dwelling older adults (≥65 years) enrolled to a clinical trial in three European countries. DESIGN: A secondary analysis of the Thyroid Hormone Replacement for Subclinical Hypothyroidism Trial dataset. PARTICIPANTS: A subset of 48/80 PIP and 22/34 PPOs indicators from the Screening Tool of Older Persons Prescriptions/Screening Tool to Alert doctors to Right Treatment (STOPP/START) V2 criteria were applied to prescribed medication data for 532/737 trial participants in Ireland, Switzerland and the Netherlands. RESULTS: The overall prevalence of PIP was lower in the Irish participants (8.7%) compared with the Swiss (16.7%) and Dutch (12.5%) participants (P=0.15) and was not statistically significant. The overall prevalence of PPOs was approximately one-quarter in the Swiss (25.3%) and Dutch (24%) participants and lower in the Irish (14%) participants (P=0.04) and the difference was statistically significant. The hypnotic Z-drugs were the most frequent PIP in Irish participants, (3.5%, n=4), while it was non-steroidal anti-inflammatory drug and oral anticoagulant combination, sulfonylureas with a long duration of action, and benzodiazepines (all 4.3%, n=7) in Swiss, and benzodiazepines (7.1%, n=18) in Dutch participants. The most frequent PPOs in Irish participants were vitamin D and calcium in osteoporosis (3.5%, n=4). In the Swiss and Dutch participants, they were bone antiresorptive/anabolic therapy in osteoporosis (9.9%, n=16, 8.6%, n=22) respectively. The odds of any PIP after adjusting for age, sex, multimorbidity and polypharmacy were (adjusted OR (aOR)) 3.04 (95% CI 1.33 to 6.95, P<0.01) for Swiss participants and aOR 1.74 (95% CI 0.79 to 3.85, P=0.17) for Dutch participants compared with Irish participants. The odds of any PPOs were aOR 2.48 (95% CI 1.27 to 4.85, P<0.01) for Swiss participants and aOR 2.10 (95% CI 1.11 to 3.96, P=0.02) for Dutch participants compared with Irish participants. CONCLUSIONS: This study has estimated and compared the prevalence and type of PIP and PPOs among this cohort of community-dwelling older people. It demonstrated a significant difference in the prevalence of PPOs between the three populations. Further research is urgently needed into the impact of system level factors as this has important implications for patient safety, healthcare provision and economic costs.

The lower quality of preventive care among forced migrants in a country with universal healthcare coverage.

OBJECTIVE: To assess the association between socio-demographic factors and the quality of preventive care and chronic care of cardiovascular (CV) risk factors in a country with universal health care coverage. METHODS: Our retrospective cohort assessed a random sample of 966 patients aged 50-80years followed over 2years (2005-2006) in 4 Swiss university primary care settings (Basel/Geneva/Lausanne/Zürich). We used RAND's Quality Assessment Tools indicators and examined recommended preventive care among different socio-demographic subgroups. RESULTS: Overall patients received 69.6% of recommended preventive care. Preventive care indicators were more likely to be met among men (72.8% vs. 65.4%; p<0.001), younger patients (from 71.0% at 50-59years to 66.7% at 70-80years, p for trend=0.03) and Swiss patients (71.1% vs. 62.7% in forced migrants; p=0.001). This latter difference remained in multivariate analysis adjusted for gender, age, civil status and occupation (OR 0.68; 95% CI 0.54-0.86). Forced migrants had lower scores for physical examination and breast and colon cancer screening (all p≤0.02). No major differences were seen for chronic care of CV risk factors. CONCLUSION: Despite universal healthcare coverage, forced migrants receive less preventive care than Swiss patients in university primary care settings. Greater attention should be paid to forced migrants for preventive care.