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Provider profiling and performance-based incentive programs have expanded in recent years but need a theoretical framework for measuring and comparing the ;;value'' of clinical care across medical providers. Cost-effectiveness analysis provides such a framework but has rarely been used outside of the treatment choice context. The authors present a profiling framework based on cost-effectiveness methods and illustrate their approach using data on in-hospital survival and the cost of care for a heart attack from a sample of Massachusetts hospitals during fiscal year 2003. They model each outcome using hierarchical models that allow performance to vary across hospitals as a function of a latent quality effect and an effect of case mix. They also estimate incremental outcomes by conditioning on each hospital's pair of random effects, using indirect standardization to estimate ;;expected'' outcomes, and then taking their difference. Incremental cost and effectiveness outcomes are combined using incremental net monetary benefits. Using cost-effectiveness methods to profile hospital ;;value'' permits the comparison of the benefit of a service relative to the cost using existing societal weights. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVE. The Centers for Medicare and Medicaid Services (CMS) report quality of care for patients hospitalized with acute myocardial infarction (AMI), congestive heart failure (CHF), and community-acquired pneumonia (CAP) with the intention of rewarding superior performing hospitals. The aim of the study was to compare identification of superior hospitals for providing financial rewards using 2 different scoring systems: a latent score that weights individual clinical performance measures according to how well each discriminated hospital quality and a raw sum score (the system adopted by CMS). METHODS: This observational cohort study used 2761 acute care hospitals in the United States reporting AMI clinical performance measures, 3271 reporting CHF measures, and 3714 hospitals reporting CAP measures. For each clinical condition, the main outcome measures included the average raw sum score, the latent score estimated from an item response theory (IRT) model, and the percentage of false negative superior designations made on the basis of raw sum scores relative to latent scores. RESULTS: The average raw sum score was highest for AMI (88.8%) and lower for CHF (73.1%) and CAP (76.3%). AMI measures were equally nondiscriminating of hospital quality; hospital discharge instruction was most discriminating of CHF quality; pneumococcal vaccination was most discriminating of CAP quality. False negative rates varied 2-fold: AMI (10%), CHF (16%), and CAP (24%). CONCLUSIONS: Neither the AMI raw sum score nor latent score discriminates hospital quality due to ceiling effects. Current methods for aggregating measures result in different hospital superior designations than those based on the latent score. Organizations that financially reward hospitals on the basis of such scores need to assess predictive validity of scores and determine a minimum level of classification accuracy. [ABSTRACT FROM AUTHOR]

To complement the current process measures for treating patients with heart attacks and with heart failure, which target gaps in quality but do not capture patient outcomes, the Centers for Medicare and Medicaid Services (CMS) has proposed the public reporting of hospital-level thirty-day mortality for these conditions in 2007. We present the case for including measurements of outcomes in the assessment of hospital performance, focusing on the care of patients with heart attacks and with heart failure. Recent developments in the methodology and standards for outcomes measurement have laid the groundwork for incorporating outcomes into performance monitoring efforts for these conditions. [ABSTRACT FROM AUTHOR]

BACKGROUND: One approach to improving quality of care is to encourage physicians to follow evidence-based practice guidelines. Examples of evidence-based guidelines are the PORT recommendations for the treatment of schizophrenia. However, few studies have examined the relationship between adherence to guidelines and patient outcomes in clinical settings. OBJECTIVE: The purpose of this article is to report the relationship between guideline adherence to antipsychotic medication dose and self-reported health status, side effects, and perceptions of care. RESEARCH DESIGN: This report is based on a subsample of patients from a larger prospective observational study of disabled Massachusetts Medicaid beneficiaries treated for schizophrenia. SUBJECTS: Participants were 329 acutely ill, vulnerable, high-risk Medicaid adult beneficiaries enrolled after visiting any 1 of 8 psychiatric emergency screening teams for hospital admission evaluation. MEASURES: Dose levels, symptoms, and functioning from medical records; self-reports as data collected from BASIS-32, SF-12, and CABHS; and paid health benefit claims for psychiatric treatment were measured. RESULTS: Approximately 40% of the patients in this study had daily antipsychotic doses well above the recommended range, but there was no evidence that their health status was better than those on doses below 1000 CPZ units recommended for acute episodes. High-dose levels had no relationship to baseline symptom profile or referral source. CONCLUSIONS: There was no evidence that health status was better on higher-than-recommended doses, but we cannot conclude that lower doses for some would have led to poorer outcomes. Physicians who believe that higher doses are more therapeutic for patients need to demand rigorous effectiveness research that tests whether there are benefits of higher doses and determine the ratio of those benefits to the clinical costs, including the risk of side effects. [ABSTRACT FROM AUTHOR]

Context: The Centers for Medicare & Medicaid Services (CMS) and the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) measure and report quality process measures for acute myocardial infarction (AMI), but little is known about how these measures are correlated with each other and the degree to which inferences about a hospital's outcomes can be made from its performance on publicly reported processes.Objective: To determine correlations among AMI core process measures and the degree to which they explain the variation in hospital-specific, risk-standardized, 30-day mortality rates.Design, Setting, and Participants: We assessed hospital performance in the CMS/JCAHO AMI core process measures using 2002-2003 data from 962 hospitals participating in the National Registry of Myocardial Infarction (NRMI) and correlated these measures with each other and with hospital-level, risk-standardized, 30-day mortality rates derived from Medicare claims data.Main Outcome Measures: Hospital performance on AMI core measures; hospital-specific, risk-standardized, 30-day mortality rates for AMI patients aged 66 years or older.Results: We found moderately strong correlations (correlation coefficients > or =0.40; P values <.001) for all pairwise comparisons between beta-blocker use at admission and discharge, aspirin use at admission and discharge, and angiotensin-converting enzyme inhibitor use, and weaker, but statistically significant, correlations between these medication measures and smoking cessation counseling and time to reperfusion therapy measures (correlation coefficients <0.40; P values <.001). Some process measures were significantly correlated with risk-standardized, 30-day mortality rates (P values <.001) but together explained only 6.0% of hospital-level variation in risk-standardized, 30-day mortality rates for patients with AMI.Conclusions: The publicly reported AMI process measures capture a small proportion of the variation in hospitals' risk-standardized short-term mortality rates. Multiple measures that reflect a variety of processes and also outcomes, such as risk-standardized mortality rates, are needed to more fully characterize hospital performance. [ABSTRACT FROM AUTHOR]

Background: Since the 1990s, parity laws have been implemented to reduce inequities in mental health coverage compared with that for general medical conditions. It is unclear if parity under managed care is associated with improvements in mental health treatment quality. Major depressive disorder (MDD) is a prevalent but often undetected and undertreated and thus could potentially benefit from parity implementation.Objective: The objective of this study was to examine the association between parity implementation and changes in MDD treatment quality in the Federal Employees' Health Benefits (FEHB) Program.Methods: We conducted retrospective analyses of insurance claims data. Logistic regression models estimated quality changes for MDD-diagnosed enrollees from pre- to postparity.Subjects: Subjects included MDD-diagnosed FEHB insured enrollees, aged 18-64, across multiple states and 6 FEHB plans before (1999-2000) and after (2001-2002) parity implementation.Measures: Measures included receipt of any antidepressant or psychotherapy within a given calendar year of diagnosis; receipt of appropriate psychotherapy frequency/intensity and duration; and pharmacotherapy duration during acute-phase treatment episodes.Results: Postparity, several plans improved significantly in the likelihood of receiving antidepressant medication. In the acute-phase episodes, the greatest improvement was seen in the likelihood of follow up >or=4 months. Few or no other changes were observed in the acute-phase treatment intensity or duration quality measures.Conclusions: Parity under managed care was associated with modest improvements. The observed improvements were consistent with secular trends in MDD treatment. Whereas mental health parity is an important policy goal, these results highlight its limitations: improving the financing of care may not be sufficient to improve quality. [ABSTRACT FROM AUTHOR]

Background. Drop-out, often accompanied by treatment non-compliance, is common in psychiatric trials. Methodologists have criticized the use of a traditional intention-to-treat (ITT) approach in such cases, and have proposed alternative methods. We set out to describe and assess methods for estimation of a treatment effect when the trial is 'broken'.Method. We describe a stratified method of moments (SMOM) estimator that assesses treatment effects on subjects who are willing to comply with all the treatments under study. A simulation study and a re-analysis of data from an antipsychotics trial are used to compare SMOM to ITT, as-treated, and adequate estimators.Results. The new estimator retains good statistical properties under different levels of non-compliance and drop-out mechanisms. The re-analysis indicates that SMOM yields more precise results.Conclusions. Although the traditional ITT approach provides a valid method to estimate treatment effects, it can be biased in the presence of treatment non-compliance and drop-out. It is critical that researchers move beyond traditional approaches when trials are broken. A key first step is to consider non-compliance and drop-out as two independent phenomena, tracking and reporting rates separately. [ABSTRACT FROM AUTHOR]

Objective: To examine whether availability of cardiac services at the admitting hospital affects case-selection for angiography and one-year survival following angiography, within groups of patients who have similar clinical need for angiography according to published criteria.Study Setting: Elderly Medicare beneficiaries (37,788) discharged with a diagnosis of acute myocardial infarction (AMI) from hospitals in seven U.S. states between February 1994 and July 1995. We focused on patients who were eligible to receive angiography 12 or more hours after symptom onset.Data Collection: Data were abstracted from patient's medical records, Medicare National Claims Standard Analytic Files, Health Care Financing Administration (HCFA) Provider of Service File and Health Insurance Master File.Methods: Admitting hospitals were classified as offering no cardiac services, angiography only, or revascularization. Case-selection differences across these three types of hospitals were examined by comparing relative risk of receiving angiography for various patient and hospital characteristics. Relative differences in one-year survival rate, comparing patients who received angiography to those who did not, were estimated within each hospital type and clinical need category (necessary, appropriate, or uncertain) after matching on propensity to receive angiography.Principal Findings: Compared to patients for whom angiography was deemed necessary, the relative risk of receiving angiography among those for whom it was deemed of uncertain benefit was 0.58, 0.79, and 0.92 (p-value of homogeneity test < 0.001) at hospitals offering no cardiac services, angiography only, and revascularization, respectively. There was no significant difference in survival following angiography across hospital types, overall as well as within clinical need categories.Conclusions: Despite increased case selection at hospitals with on-site cardiac services, there was no evidence of increase in the survival rate associated with angiography use at these hospitals. [ABSTRACT FROM AUTHOR]

Estimating the value of spending on medical treatments in a health care system involves relating output, measured in terms of effectiveness, to cost, measured in terms of spending. Although information on spending at the system level often exists in administrative data, such as insurance claims, information on effectiveness is not always available. An inferential tool available to researchers in this context is elicitation. The authors develop an approach to elicit effectiveness parameters and apply it to a panel of 10 experts to estimate predictive Hamilton Depression Rating Scale scores representing postambulatory treatment outcomes. The elicited parameters are used to estimate outcomes associated with 120 acute phase treatments for major depression within a privately insured health insurance system. The outcome-adjusted price per full remission episode is estimated for each acute treatment, and corresponding 95% percentile bootstrap intervals are calculated. The average spendingfor all observed treatments was $473 (SE = 478), with a depression-free adjusted price per case of $5,995 (95% confidence interval = $5,959-$6,031). [ABSTRACT FROM AUTHOR]

Objective: To develop a prediction model of death within 30 days of hospital admission for Medicare patients with acute myocardial infarction that would permit use of risk-adjusted mortality rates as hospital quality measures.Design: Retrospective cohort study using data created from medical charts and administrative files.Setting: All acute care hospitals in Alabama, Connecticut, Iowa, or Wisconsin.Patients: A cohort of 14,581 patients with acute myocardial infarction covered by Medicare in 1993.Results: The unadjusted 30-day mortality rate was 21%, ranging from 18% in Connecticut to 23% in Alabama. The 4 largest contributors to variability in mortality rates were mean arterial pressure, age, respiratory rate, and serum urea nitrogen level. The area under the receiver operator characteristic curve was 0.79 in a developmental sample of 10 936 patients and 0.78 in a validation sample of 3645 patients. Based on admission variables, we were able to explain 27% of the variability in 30-day mortality rates. During the index admission, aspirin, beta-blockers, angiotensin-converting enzyme inhibitors, and thrombolytic agents were used in 72%, 39%, 32%, and 15% of patients, respectively. Explained variation increased by 6 percentage points to 33% when drug therapies and revascularization procedures performed during the index admission were added to the model predictors.Conclusions: Short-term mortality remains high for elderly patients with acute myocardial infarction, and a large percentage of variation remains unexplained after controlling for admission severity. Part of the unexplained variability can be explained by the location of the admitting hospital; some of the remaining unexplained variation may reflect differences in quality of care or unmeasured differences in disease severity. Researchers should develop quality indicators based on process measures for acute myocardial infarction and should incorporate these measures into mortality models to determine whether quality accounts for variation in 30-day mortality rates beyond that explained by clinical status at admission. [ABSTRACT FROM AUTHOR]

This paper presents a complete custom full-digital instrumentation device that was designed for real-time neutron flux estimation, especially for nuclear reactor in-core measurement using subminiature Fission Chambers (FCs). Entire fully functional small-footprint design (about 1714 LUTs) is implemented on FPGA. It enables real-time acquisition and analysis of multiple channels neutron's flux both in counting mode and Campbelling mode. Experimental results obtained from this brand new device are consistent with simulation results and show good agreement within good uncertainty. This device paves the way for new applications perspectives in real-time nuclear reactor monitoring.

The value of mental health services is regularly questioned in health policy debates. Although all health services are being asked to demonstrate their value, there are special concerns about this set of services because spending on mental health care has grown markedly over the past twenty years. We propose a method for using administrative data to develop a comprehensive assessment of value for mental health care, which we call systems cost-effectiveness (SCE). We apply the method to acute-phase treatment of depression in a large insured population. Our results show that SCE of treatment for depression has improved during the 1990s. [ABSTRACT FROM AUTHOR]

During the initial year of the COVID-19 pandemic, a disproportionate share of COVID-19-related deaths occurred among nursing home residents. Initial estimates of all-cause mortality rates also spiked in early and late 2020 before falling to near or below historical rates by early 2021. During the first 3 years of the pandemic, the US nursing home resident population also decreased by 18% (239 000 fewer residents) compared with pre-pandemic levels. After accounting for these population changes, the all-cause nursing home mortality rate has remained above pre-pandemic levels through the middle of 2023. The peak was in December 2020 at 5692 deaths per 100 000 residents, which was 19% higher than estimates not accounting for the population decrease., Competing Interests: Conflicts of interest Please see ICMJE form(s) for author conflicts of interest. These have been provided as supplementary materials., (© The Author(s) 2024. Published by Oxford University Press on behalf of Project HOPE - The People-To-People Health Foundation, Inc.)

Background: Exposure to second-generation antipsychotics (SGAs) carries a risk of type 2 diabetes, but questions remain about the diabetogenic effects of SGAs., Aims: To assess the diabetes risk associated with two frequently used SGAs., Method: This was a retrospective cohort study of adults with schizophrenia, bipolar I disorder or severe major depressive disorder (MDD) exposed during 2008-2013 to continuous monotherapy with aripiprazole or olanzapine for up to 24 months, with no pre-period exposure to other antipsychotics. Newly diagnosed type 2 diabetes was quantified with targeted minimum loss-based estimation; risk was summarised as the restricted mean survival time (RMST), the average number of diabetes-free months. Sensitivity analyses were used to evaluate potential confounding by indication., Results: Aripiprazole-treated patients had fewer diabetes-free months compared with olanzapine-treated patients. RMSTs were longer in olanzapine-treated patients, by 0.25 months [95% CI: 0.14, 0.36], 0.16 months [0.02, 0.31] and 0.22 months [0.01, 0.44] among patients with schizophrenia, bipolar I disorder and severe MDD, respectively. Although some sensitivity analyses suggest a risk of unobserved confounding, E-values indicate that this risk is not severe., Conclusions: Using robust methods and accounting for exposure duration effects, we found a slightly higher risk of type 2 diabetes associated with aripiprazole compared with olanzapine monotherapy regardless of diagnosis. If this result was subject to unmeasured selection despite our methods, it would suggest clinician success in identifying olanzapine candidates with low diabetes risk. Confirmatory research is needed, but this insight suggests a potentially larger role for olanzapine in the treatment of well-selected patients, particularly for those with schizophrenia, given the drug's effectiveness advantage among them.

Objective: To evaluate the effectiveness of a clinical decision support system (CDSS) in improving the use of guideline accordant antihypertensive treatment in primary care settings in China., Design: Pragmatic, open label, cluster randomised trial., Setting: 94 primary care practices in four urban regions of China between August 2019 and July 2022: Luoyang (central China), Jining (east China), and Shenzhen (south China, including two regions)., Participants: 94 practices were randomised (46 to CDSS, 48 to usual care). 12 137 participants with hypertension who used up to two classes of antihypertensives and had a systolic blood pressure <180 mm Hg and diastolic blood pressure <110 mm Hg were included., Interventions: Primary care practices were randomised to use an electronic health record based CDSS, which recommended a specific guideline accordant regimen for initiation, titration, or switching of antihypertensive (the intervention), or to use the same electronic health record without CDSS and provide treatment as usual (control)., Main Outcome Measures: The primary outcome was the proportion of hypertension related visits during which an appropriate (guideline accordant) treatment was provided. Secondary outcomes were the average reduction in systolic blood pressure and proportion of participants with controlled blood pressure (<140/90 mm Hg) at the last scheduled follow-up. Safety outcomes were patient reported antihypertensive treatment related events, including syncope, injurious fall, symptomatic hypotension or systolic blood pressure <90 mm Hg, and bradycardia., Results: 5755 participants with 23 113 visits in the intervention group and 6382 participants with 27 868 visits in the control group were included. Mean age was 61 (standard deviation 13) years and 42.5% were women. During a median 11.6 months of follow-up, the proportion of visits at which appropriate treatment was given was higher in the intervention group than in the control group (77.8% (17 975/23 113) v 62.2% (17 328/27 868); absolute difference 15.2 percentage points (95% confidence interval (CI) 10.7 to 19.8); P<0.001; odds ratio 2.17 (95% CI 1.75 to 2.69); P<0.001). Compared with participants in the control group, those in the intervention group had a 1.6 mm Hg (95% CI -2.7 to -0.5) greater reduction in systolic blood pressure (-1.5 mm Hg v 0.3 mm Hg; P=0.006) and a 4.4 percentage point (95% CI -0.7 to 9.5) improvement in blood pressure control rate (69.0% (3415/4952) v 64.6% (3778/5845); P=0.07). Patient reported antihypertensive treatment related adverse effects were rare in both groups., Conclusions: Use of a CDSS in primary care in China improved the provision of guideline accordant antihypertensive treatment and led to a modest reduction in blood pressure. The CDSS offers a promising approach to delivering better care for hypertension, both safely and efficiently., Trial Registration: ClinicalTrials.gov NCT03636334., Competing Interests: Competing interests: All authors have completed the ICMJE uniform disclosure form at https://www.icmje.org/disclosure-of-interest/ and declare: support from the Chinese Academy of Medical Sciences and the Sanming Project of Medicine in Shenzhen; in the past three years, HMK received options for Element Science and Identifeye and payments from F-Prime for advisory roles, and he is a cofounder of, and holds equity in, Hugo Health, Refactor Health, and Ensight-AI, and he is associated with research contracts through Yale University from Janssen, Kenvue, and Pfizer; no other relationships or activities that could appear to have influenced the submitted work., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: The authors sought to examine trends in stimulant initiation and follow-up care for attention-deficit hyperactivity disorder (ADHD) via telemedicine., Methods: This retrospective longitudinal study used national, deidentified commercial health insurance outpatient claims among children (ages 2-17 years; N=535,629) and adults (ages 18-64 years; N=2,116,160) from January 2019 through April 2022. Regression analyses were used to examine risk for stimulant initiation, whether initiation occurred via telemedicine or in-person care, and receipt of a follow-up visit., Results: The mean monthly adjusted number of stimulant initiations per 100,000 enrollees was similar for children before and during the COVID-19 pandemic (prepandemic, 57 initiations; during pandemic, 56 initiations) but increased for adults (prepandemic, 27 initiations; during pandemic, 33 initiations). Initiations via telemedicine peaked at 53%-57% in April 2020 and dropped to about 14% among children and 28% among adults in April 2022. Telemedicine initiations were significantly more common among psychiatrists than among other prescribers (OR=3.70, 95% CI=3.38-4.06 [children]; OR=3.02, 95% CI=2.87-3.17 [adults]) and less common for rural residents (OR=0.57, 95% CI=0.40-0.82 [children]; OR=0.75, 95% CI=0.61-0.92 [adults]). Follow-up care was significantly more common among individuals whose care was initiated via telemedicine than among those receiving in-person care (OR=1.09, 95% CI=1.00-1.19 [children]; OR=1.61, 95% CI=1.53-1.69 [adults])., Conclusions: Many stimulant treatments were initiated via telemedicine. Proposed rules to prohibit controlled substance prescribing without an in-person evaluation would require significant changes in current practice, potentially limiting access to stimulant medications for ADHD., Competing Interests: Dr. Mehrotra has received fees related to telemedicine from Black Opal Ventures, Commonwealth of Massachusetts, NORC, Pew Charitable Trust, and Sanofi. The other authors report no financial relationships with commercial interests.

Contemporary data collection strategies, storage capabilities, and modern statistical methodology have made retrospective analyses of observational databases commonplace. Such databases afford opportunities to learn about the effectiveness and risks of interventions or health behaviors that generally cannot be randomized. In this issue of NEJM Evidence , Cho et al. 1 assemble survey data and cohort data from four countries to quantify the association between age-sex-specific smoking cessation and mortality. The authors conclude that smoking cessation at any age is associated with lower excess overall mortality risk and lower death from diseases made more common by smoking. It is difficult to argue with this conclusion - to question the magnitude of the associations is not.

Importance: Individuals of racial and ethnic minority groups may be less likely to use telemedicine in part due to lack of access to technology (ie, digital divide). To date, some studies have found less telemedicine use by individuals of racial and ethnic minority groups compared with White individuals, and others have found the opposite. What explains these different findings is unclear., Objective: To quantify racial and ethnic differences in the receipt of telemedicine and total visits with and without accounting for demographic and clinical characteristics and geography., Design, Setting, and Participants: This cross-sectional study included individuals who were continuously enrolled in traditional Medicare from March 2020 to February 2022 or until death., Exposure: Race and ethnicity, which was categorized as Black non-Hispanic, Hispanic, White non-Hispanic, other (defined as American Indian/Pacific Islander, Alaska Native, and Asian), and unknown/missing., Main Outcomes and Measures: Total telemedicine visits (audio-video or audio); total visits (telemedicine or in-person) per individual during the study period. Multivariable models were used that sequentially adjusted for demographic and clinical characteristics and geographic area to examine their association with differences in telemedicine and total visit utilization by documented race and ethnicity., Results: In this national sample of 14 305 819 individuals, 7.4% reported that they were Black, 5.6% Hispanic, and 4.2% other race. In unadjusted results, compared with White individuals, Black individuals, Hispanic individuals, and individuals of other racial groups had 16.7 (95% CI, 16.1-17.3), 32.9 (95% CI, 32.3-33.6), and 20.9 (95% CI, 20.2-21.7) more telemedicine visits per 100 beneficiaries, respectively. After adjustment for clinical and demographic characteristics and geography, compared with White individuals, Black individuals, Hispanic individuals, and individuals of other racial groups had 7.9 (95% CI, -8.5 to -7.3), 13.2 (95% CI, -13.9 to -12.6), and 9.2 (95% CI, -10.0 to -8.5) fewer telemedicine visits per 100 beneficiaries, respectively. In unadjusted and fully adjusted models, and in 2019 and the second year of the COVID-19 pandemic, Black individuals, Hispanic individuals, and individuals of other racial groups continued to have fewer total visits than White individuals., Conclusions and Relevance: The results of this cross-sectional study of US Medicare enrollees suggest that although nationally, Black individuals, Hispanic individuals, and individuals of other racial groups received more telemedicine visits during the pandemic and disproportionately lived in geographic regions with higher telemedicine use, after controlling for geographic region, Black individuals, Hispanic individuals, and individuals of other racial groups received fewer telemedicine visits than White individuals.