Adaptive metrics for an evolving pandemic: A dynamic approach to area-level COVID-19 risk designations.

Throughout the COVID-19 pandemic, policymakers have proposed risk metrics, such as the CDC Community Levels, to guide local and state decision-making. However, risk metrics have not reliably predicted key outcomes and have often lacked transparency in terms of prioritization of false-positive versus false-negative signals. They have also struggled to maintain relevance over time due to slow and infrequent updates addressing new variants and shifts in vaccine- and infection-induced immunity. We make two contributions to address these weaknesses. We first present a framework to evaluate predictive accuracy based on policy targets related to severe disease and mortality, allowing for explicit preferences toward false-negative versus false-positive signals. This approach allows policymakers to optimize metrics for specific preferences and interventions. Second, we propose a method to update risk thresholds in real time. We show that this adaptive approach to designating areas as "high risk" improves performance over static metrics in predicting 3-wk-ahead mortality and intensive care usage at both state and county levels. We also demonstrate that with our approach, using only new hospital admissions to predict 3-wk-ahead mortality and intensive care usage has performed consistently as well as metrics that also include cases and inpatient bed usage. Our results highlight that a key challenge for COVID-19 risk prediction is the changing relationship between indicators and outcomes of policy interest. Adaptive metrics therefore have a unique advantage in a rapidly evolving pandemic context.

Differences in Treatment Patterns and Outcomes of Acute Myocardial Infarction for Low- and High-Income Patients in 6 Countries.

Importance: Differences in the organization and financing of health systems may produce more or less equitable outcomes for advantaged vs disadvantaged populations. We compared treatments and outcomes of older high- and low-income patients across 6 countries. Objective: To determine whether treatment patterns and outcomes for patients presenting with acute myocardial infarction differ for low- vs high-income individuals across 6 countries. Design, Setting, and Participants: Serial cross-sectional cohort study of all adults aged 66 years or older hospitalized with acute myocardial infarction from 2013 through 2018 in the US, Canada, England, the Netherlands, Taiwan, and Israel using population-representative administrative data. Exposures: Being in the top and bottom quintile of income within and across countries. Main Outcomes and Measures: Thirty-day and 1-year mortality; secondary outcomes included rates of cardiac catheterization and revascularization, length of stay, and readmission rates. Results: We studied 289 376 patients hospitalized with ST-segment elevation myocardial infarction (STEMI) and 843 046 hospitalized with non-STEMI (NSTEMI). Adjusted 30-day mortality generally was 1 to 3 percentage points lower for high-income patients. For instance, 30-day mortality among patients admitted with STEMI in the Netherlands was 10.2% for those with high income vs 13.1% for those with low income (difference, -2.8 percentage points [95% CI, -4.1 to -1.5]). One-year mortality differences for STEMI were even larger than 30-day mortality, with the highest difference in Israel (16.2% vs 25.3%; difference, -9.1 percentage points [95% CI, -16.7 to -1.6]). In all countries, rates of cardiac catheterization and percutaneous coronary intervention were higher among high- vs low-income populations, with absolute differences ranging from 1 to 6 percentage points (eg, 73.6% vs 67.4%; difference, 6.1 percentage points [95% CI, 1.2 to 11.0] for percutaneous intervention in England for STEMI). Rates of coronary artery bypass graft surgery for patients with STEMI in low- vs high-income strata were similar but for NSTEMI were generally 1 to 2 percentage points higher among high-income patients (eg, 12.5% vs 11.0% in the US; difference, 1.5 percentage points [95% CI, 1.3 to 1.8 ]). Thirty-day readmission rates generally also were 1 to 3 percentage points lower and hospital length of stay generally was 0.2 to 0.5 days shorter for high-income patients. Conclusions and Relevance: High-income individuals had substantially better survival and were more likely to receive lifesaving revascularization and had shorter hospital lengths of stay and fewer readmissions across almost all countries. Our results suggest that income-based disparities were present even in countries with universal health insurance and robust social safety net systems.

Medicare Spending after 3 Years of the Medicare Shared Savings Program.

BACKGROUND: Health care providers who participate as an accountable care organization (ACO) in the voluntary Medicare Shared Savings Program (MSSP) have incentives to lower spending for Medicare patients while achieving high performance on a set of quality measures. Little is known about the extent to which early savings achieved by ACOs in the program have grown and been replicated by ACOs that entered the program in later years. ACOs that are physician groups have stronger incentives to lower spending than hospital-integrated ACOs. METHODS: Using fee-for-service Medicare claims from 2009 through 2015, we performed difference-in-differences analyses to compare changes in Medicare spending for patients in ACOs before and after entry into the MSSP with concurrent changes in spending for local patients served by providers not participating in the MSSP (control group). We estimated differential changes (i.e., the between-group difference in the change from the pre-entry period) separately for hospital-integrated ACOs and physician-group ACOs that entered the MSSP in 2012, 2013, or 2014. RESULTS: MSSP participation was associated with differential spending reductions in physician-group ACOs. These reductions grew with longer participation in the program and were significantly greater than the reductions in hospital-integrated ACOs. By 2015, the mean differential change in per-patient Medicare spending was -$474 (-4.9% of the pre-entry mean, P<0.001) for physician-group ACOs that entered in 2012, -$342 (-3.5% of the pre-entry mean, P<0.001) for those that entered in 2013, and -$156 (-1.6% of the pre-entry mean, P=0.009) for those that entered in 2014. The corresponding differential changes for hospital-integrated ACOs were -$169 (P=0.005), -$18 (P=0.78), and $88 (P=0.14), which were significantly lower than for physician-group ACOs (P<0.001). Spending reductions in physician-group ACOs constituted a net savings to Medicare of $256.4 million in 2015, whereas spending reductions in hospital-integrated ACOs were offset by bonus payments. CONCLUSIONS: After 3 years of the MSSP, participation in shared-savings contracts by physician groups was associated with savings for Medicare that grew over the study period, whereas hospital-integrated ACOs did not produce savings (on average) during the same period. (Funded by the National Institute on Aging.).

Savings or Selection? Initial Spending Reductions in the Medicare Shared Savings Program and Considerations for Reform.

Policy Points Concerns have been raised about risk selection in the Medicare Shared Savings Program (MSSP). Specifically, turnover in accountable care organization (ACO) physicians and patient panels has led to concerns that ACOs may be earning shared-savings bonuses by selecting lower-risk patients or providers with lower-risk panels. We find no evidence that changes in ACO patient populations explain savings estimates from previous evaluations through 2015. We also find no evidence that ACOs systematically manipulated provider composition or billing to earn bonuses. The modest savings and lack of risk selection in the original MSSP design suggest opportunities to build on early progress. Recent program changes provide ACOs with more opportunity to select providers with lower-risk patients. Understanding the effect of these changes will be important for guiding future payment policy. CONTEXT: The Medicare Shared Savings Program (MSSP) establishes incentives for participating accountable care organizations (ACOs) to lower spending for their attributed fee-for-service Medicare patients. Turnover in ACO physicians and patient panels has raised concerns that ACOs may be earning shared-savings bonuses by selecting lower-risk patients or providers with lower-risk panels. METHODS: We conducted three sets of analyses of Medicare claims data. First, we estimated overall MSSP savings through 2015 using a difference-in-differences approach and methods that eliminated selection bias from ACO program exit or changes in the practices or physicians included in ACO contracts. We then checked for residual risk selection at the patient level. Second, we reestimated savings with methods that address undetected risk selection but could introduce bias from other sources. These included patient fixed effects, baseline or prospective assignment, and area-level MSSP exposure to hold patient populations constant. Third, we tested for changes in provider composition or provider billing that may have contributed to bonuses, even if they were eliminated as sources of bias in the evaluation analyses. FINDINGS: MSSP participation was associated with modest and increasing annual gross savings in the 2012-2013 entry cohorts of ACOs that reached $139 to $302 per patient by 2015. Savings in the 2014 entry cohort were small and not statistically significant. Robustness checks revealed no evidence of residual risk selection. Alternative methods to address risk selection produced results that were substantively consistent with our primary analysis but varied somewhat and were more sensitive to adjustment for patient characteristics, suggesting the introduction of bias from within-patient changes in time-varying characteristics. We found no evidence of ACO manipulation of provider composition or billing to inflate savings. Finally, larger savings for physician group ACOs were robust to consideration of differential changes in organizational structure among non-ACO providers (eg, from consolidation). CONCLUSIONS: Participation in the original MSSP program was associated with modest savings and not with favorable risk selection. These findings suggest an opportunity to build on early progress. Understanding the effect of new opportunities and incentives for risk selection in the revamped MSSP will be important for guiding future program reforms.

Use of Telemedicine for Emergency Triage in an Independent Senior Living Community: Mixed Methods Study.

BACKGROUND: Older, chronically ill individuals in independent living communities are frequently transferred to the emergency department (ED) for acute issues that could be managed in lower-acuity settings. Triage via telemedicine could deter unnecessary ED transfers. OBJECTIVE: We examined the effectiveness of a telemedicine intervention for emergency triage in an independent living community. METHODS: In the intervention community, a 950-resident independent senior living community, when a resident called for help, emergency medical technician-trained staff could engage an emergency medicine physician via telemedicine to assist with management and triage. We compared trends in the proportion of calls resulting in transport to the ED (ie, primary outcome) in the intervention community to two control communities. Secondary outcomes were telemedicine use and posttransport disposition. Semistructured focus groups of residents and staff were conducted to examine attitudes toward the intervention. Qualitative data analysis used thematic analysis. RESULTS: Although the service was offered at no cost to residents, use was low and we found no evidence of fewer ED transfers. The key barrier to program use was resistance from frontline staff members, who did not view telemedicine triage as a valuable tool for emergency response, instead perceiving it as time-consuming and as undermining their independent judgment. CONCLUSIONS: Engagement of, and acceptance by, frontline providers is a key consideration in using telemedicine triage to reduce unnecessary ED transfers.

Early Performance of Accountable Care Organizations in Medicare.

BACKGROUND: In the Medicare Shared Savings Program (MSSP), accountable care organizations (ACOs) have financial incentives to lower spending and improve quality. We used quasi-experimental methods to assess the early performance of MSSP ACOs. METHODS: Using Medicare claims from 2009 through 2013 and a difference-in-differences design, we compared changes in spending and in performance on quality measures from before the start of ACO contracts to after the start of the contracts between beneficiaries served by the 220 ACOs entering the MSSP in mid-2012 (2012 ACO cohort) or January 2013 (2013 ACO cohort) and those served by non-ACO providers (control group), with adjustment for geographic area and beneficiary characteristics. We analyzed the 2012 and 2013 ACO cohorts separately because entry time could reflect the capacity of an ACO to achieve savings. We compared ACO savings according to organizational structure, baseline spending, and concurrent ACO contracting with commercial insurers. RESULTS: Adjusted Medicare spending and spending trends were similar in the ACO cohorts and the control group during the precontract period. In 2013, the differential change (i.e., the between-group difference in the change from the precontract period) in total adjusted annual spending was -$144 per beneficiary in the 2012 ACO cohort as compared with the control group (P=0.02), consistent with a 1.4% savings, but only -$3 per beneficiary in the 2013 ACO cohort as compared with the control group (P=0.96). Estimated savings were consistently greater in independent primary care groups than in hospital-integrated groups among 2012 and 2013 MSSP entrants (P=0.005 for interaction). MSSP contracts were associated with improved performance on some quality measures and unchanged performance on others. CONCLUSIONS: The first full year of MSSP contracts was associated with early reductions in Medicare spending among 2012 entrants but not among 2013 entrants. Savings were greater in independent primary care groups than in hospital-integrated groups.

Identifying and interpreting subgroups in health care utilization data with count mixture regression models.

Inpatient care is a large share of total health care spending, making analysis of inpatient utilization patterns an important part of understanding what drives health care spending growth. Common features of inpatient utilization measures such as length of stay and spending include zero inflation, overdispersion, and skewness, all of which complicate statistical modeling. Moreover, latent subgroups of patients may have distinct patterns of utilization and relationships between that utilization and observed covariates. In this work, we apply and compare likelihood-based and parametric Bayesian mixtures of negative binomial and zero-inflated negative binomial regression models. In a simulation, we find that the Bayesian approach finds the true number of mixture components more accurately than using information criteria to select among likelihood-based finite mixture models. When we apply the models to data on hospital lengths of stay for patients with lung cancer, we find distinct subgroups of patients with different means and variances of hospital days, health and treatment covariates, and relationships between covariates and length of stay.

Separable covariance models for health care quality measures across years and topics.

Public quality reports for Medicare Advantage health plans include 11 measures of patient experiences reported in the annual Consumer Assessment of Healthcare Providers and Systems surveys. Computing summaries at the health plan level (of multiple measures in multiple years) yields an array-structured random variable. To summarize associations among measures and years, we model the variance-covariance matrix governing the plan-level vectors of yearly quality measures as a Kronecker product of an across-measure matrix and an across-year matrix, or a sum of such Kronecker products. This approach extends separable covariance structure to Fay-Herriot models. In addition, we develop linear combinations of Kronecker products similar to principal components for array random variables. To each Kronecker-product term, we apply post hoc analyses suited to the corresponding dimension of the cross-classification: 1-way factor analysis for the across-measure factor and time-series analysis to the across-year factor. These methods draw out key patterns of variation in the quality measures over time and suggest new strategies for reporting quality information to consumers.

A Randomized Trial of Displaying Paid Price Information on Imaging Study and Procedure Ordering Rates.

BACKGROUND: Prior studies have demonstrated how price transparency lowers the test-ordering rates of trainees in hospitals, and physician-targeted price transparency efforts have been viewed as a promising cost-controlling strategy. OBJECTIVE: To examine the effect of displaying paid-price information on test-ordering rates for common imaging studies and procedures within an accountable care organization (ACO). DESIGN: Block randomized controlled trial for 1 year. SUBJECTS: A total of 1205 fully licensed clinicians (728 primary care, 477 specialists). INTERVENTION: Starting January 2014, clinicians in the Control arm received no price display; those in the intervention arms received Single or Paired Internal/External Median Prices in the test-ordering screen of their electronic health record. Internal prices were the amounts paid by insurers for the ACO's services; external paid prices were the amounts paid by insurers for the same services when delivered by unaffiliated providers. MAIN MEASURES: Ordering rates (orders per 100 face-to-face encounters with adult patients): overall, designated to be completed internally within the ACO, considered "inappropriate" (e.g., MRI for simple headache), and thought to be "appropriate" (e.g., screening colonoscopy). KEY RESULTS: We found no significant difference in overall ordering rates across the Control, Single Median Price, or Paired Internal/External Median Prices study arms. For every 100 encounters, clinicians in the Control arm ordered 15.0 (SD 31.1) tests, those in the Single Median Price arm ordered 15.0 (SD 16.2) tests, and those in the Paired Prices arms ordered 15.7 (SD 20.5) tests (one-way ANOVA p-value 0.88). There was no difference in ordering rates for tests designated to be completed internally or considered to be inappropriate or appropriate. CONCLUSIONS: Displaying paid-price information did not alter how frequently primary care and specialist clinicians ordered imaging studies and procedures within an ACO. Those with a particular interest in removing waste from the health care system may want to consider a variety of contextual factors that can affect physician-targeted price transparency.

Association Between Availability of a Price Transparency Tool and Outpatient Spending.

IMPORTANCE: There is increasing interest in using price transparency tools to decrease health care spending. OBJECTIVE: To measure the association between offering a health care price transparency tool and outpatient spending. DESIGN, SETTING, AND PARTICIPANTS: Two large employers represented in multiple market areas across the United States offered an online health care price transparency tool to their employees. One introduced it on April 1, 2011, and the other on January 1, 2012. The tool provided users information about what they would pay out of pocket for services from different physicians, hospitals, or other clinical sites. Using a matched difference-in-differences design, outpatient spending among employees offered the tool (n=148,655) was compared with that among employees from other companies not offered the tool (n=295,983) in the year before and after it was introduced. EXPOSURE: Availability of a price transparency tool. MAIN OUTCOMES AND MEASURES: Annual outpatient spending, outpatient out-of-pocket spending, use rates of the tool. RESULTS: Mean outpatient spending among employees offered the tool was $2021 in the year before the tool was introduced and $2233 in the year after. In comparison, among controls, mean outpatient spending changed from $1985 to $2138. After adjusting for demographic and health characteristics, being offered the tool was associated with a mean $59 (95% CI, $25-$93) increase in outpatient spending. Mean outpatient out-of-pocket spending among those offered the tool was $507 in the year before introduction of the tool and $555 in the year after. Among the comparison group, mean outpatient out-of-pocket spending changed from $490 to $520. Being offered the price transparency tool was associated with a mean $18 (95% CI, $12-$25) increase in out-of-pocket spending after adjusting for relevant factors. In the first 12 months, 10% of employees who were offered the tool used it at least once. CONCLUSIONS AND RELEVANCE: Among employees at 2 large companies, offering a price transparency tool was not associated with lower health care spending. The tool was used by only a small percentage of eligible employees.

Primary Care Physicians In Medicare Advantage Were Less Costly, Provided Similar Quality Versus Regional Average.

The use of many services is lower in Medicare Advantage (MA) compared with traditional Medicare, generating cost savings for insurers, whereas the quality of ambulatory services is higher. This study examined the role of selective contracting with providers in achieving these outcomes, focusing on primary care physicians. Assessing primary care physician costliness based on the gap between observed and predicted costs for their traditional Medicare patients, we found that the average primary care physician in MA networks was $433 less costly per patient (2.9 percent of baseline) compared with the regional mean, with less costly primary care physicians included in more networks than more costly ones. Favorable selection of patients by MA primary care physicians contributed partially to this result. The quality measures of MA primary care physicians were similar to the regional mean. In contrast, primary care physicians excluded from all MA networks were $1,617 (13.8 percent) costlier than the regional mean, with lower quality. Primary care physicians in narrow networks were $212 (1.4 percent) less costly than those in wide networks, but their quality was slightly lower. These findings highlight the potential role of selective contracting in reducing costs in the MA program.

Sex-Based Disparities in Acute Myocardial Infarction Treatment Patterns and Outcomes in Older Adults Hospitalized Across 6 High-Income Countries: An Analysis From the International Health Systems Research Collaborative.

BACKGROUND: Sex differences in acute myocardial infarction treatment and outcomes are well documented, but it is unclear whether differences are consistent across countries. The objective of this study was to investigate the epidemiology, use of interventional procedures, and outcomes for older females and males hospitalized with ST-segment-elevation myocardial infarction (STEMI) and non-ST-segment-elevation myocardial infarction (NSTEMI) in 6 diverse countries. METHODS: We conducted a serial cross-sectional cohort study of 1 508 205 adults aged ≥66 years hospitalized with STEMI and NSTEMI between 2011 and 2018 in the United States, Canada, England, the Netherlands, Taiwan, and Israel using administrative data. We compared females and males within each country with respect to age-standardized hospitalization rates, rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery within 90 days of hospitalization, and 30-day age- and comorbidity-adjusted mortality. RESULTS: Hospitalization rates for STEMI and NSTEMI decreased between 2011 and 2018 in all countries, although the hospitalization rate ratio (rate in males/rate in females) increased in virtually all countries (eg, US STEMI ratio, 1.58:1 in 2011 and 1.73:1 in 2018; Israel NSTEMI ratio, 1.71:1 in 2011 and 2.11:1 in 2018). Rates of cardiac catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery were lower for females than males for STEMI in all countries and years (eg, US cardiac catheterization in 2018, 88.6% for females versus 91.5% for males; Israel percutaneous coronary intervention in 2018, 76.7% for females versus 84.8% for males) with similar findings for NSTEMI. Adjusted mortality for STEMI in 2018 was higher for females than males in 5 countries (the United States, Canada, the Netherlands, Israel, and Taiwan) but lower for females than males in 5 countries for NSTEMI. CONCLUSIONS: We observed a larger decline in acute myocardial infarction hospitalizations for females than males between 2011 and 2018. Females were less likely to receive cardiac interventions and had higher mortality after STEMI. Sex disparities seem to transcend borders, raising questions about the underlying causes and remedies.

Changes in prenatal care and birth outcomes after federally qualified health center expansion.

OBJECTIVE: To evaluate whether the expansion of Federally Qualified Health Centers (FQHCs) improved late prenatal care initiation, low birth weight, and preterm birth among Medicaid-covered or uninsured individuals. DATA SOURCES AND STUDY SETTING: We identified all FQHCs in California using the Health Resources and Services Administration's Uniform Data System from 2000 to 2019. We used data from the U.S. Census American Community Survey to describe area characteristics. We measured outcomes in California birth certificate data from 2007 to 2019. STUDY DESIGN: We compared areas that received their first FQHC between 2011 and 2016 to areas that received it later or that had never had an FQHC. Specifically, we used a synthetic control with a staggered adoption approach to calculate non-parametric estimates of the average treatment effects on the treated areas. The key outcome variables were the rate of Medicaid or uninsured births with late prenatal care initiation (>3 months' gestation), with low birth weight (<2500 grams), or with preterm birth (<37 weeks' gestation). DATA COLLECTION/EXTRACTION METHODS: The analysis was limited to births covered by Medicaid or that were uninsured, as indicated on the birth certificate. PRINCIPAL FINDINGS: The 55 areas in California that received their first FQHC in 2011-2016 were more populous; their residents were more likely to be covered by Medicaid, to be low-income, or to be Hispanic than residents of the 48 areas that did not have an FQHC by the end of the study period. We found no statistically significant impact of the first FQHC on rates of late prenatal care initiation (ATT: -10.4 [95% CI -38.1, 15.0]), low birth weight (ATT: 0.2 [95% CI -7.1, 5.4]), or preterm birth (ATT: -7.0 [95% CI -15.5, 2.3]). CONCLUSIONS: Our results from California suggest that access to primary and prenatal care may not be enough to improve these outcomes. Future work should evaluate the impact of ongoing initiatives to increase access to maternal health care at FQHCs through targeted workforce investments.

Adaptive metrics for an evolving pandemic A dynamic approach to area-level COVID-19 risk designations.

Throughout the COVID-19 pandemic, policymakers have proposed risk metrics, such as the CDC Community Levels, to guide local and state decision-making. However, risk metrics have not reliably predicted key outcomes and often lack transparency in terms of prioritization of false positive versus false negative signals. They have also struggled to maintain relevance over time due to slow and infrequent updates addressing new variants and shifts in vaccine- and infection-induced immunity. We make two contributions to address these weaknesses of risk metrics. We first present a framework to evaluate predictive accuracy based on policy targets related to severe disease and mortality, allowing for explicit preferences toward false negative versus false positive signals. This approach allows policymakers to optimize metrics for specific preferences and interventions. Second, we propose a novel method to update risk thresholds in real-time. We show that this adaptive approach to designating areas as "high risk" improves performance over static metrics in predicting 3-week-ahead mortality and intensive care usage at both state and county levels. We also demonstrate that with our approach, using only new hospital admissions to predict 3-week-ahead mortality and intensive care usage has performed consistently as well as metrics that also include cases and inpatient bed usage. Our results highlight that a key challenge for COVID-19 risk prediction is the changing relationship between indicators and outcomes of policy interest. Adaptive metrics therefore have a unique advantage in a rapidly evolving pandemic context. Significance Statement: In the rapidly-evolving COVID-19 pandemic, public health risk metrics often become less relevant over time. Risk metrics are designed to predict future severe disease and mortality based on currently-available surveillance data, such as cases and hospitalizations. However, the relationship between cases, hospitalizations, and mortality has varied considerably over the course of the pandemic, in the context of new variants and shifts in vaccine- and infection-induced immunity. We propose an adaptive approach that regularly updates metrics based on the relationship between surveillance inputs and future outcomes of policy interest. Our method captures changing pandemic dynamics, requires only hospitalization input data, and outperforms static risk metrics in predicting high-risk states and counties.

Variation in care for patients presenting with hip fracture in six high-income countries: A cross-sectional cohort study.

BACKGROUND: Hip fractures are costly and common in older adults, but there is limited understanding of how treatment patterns and outcomes might differ between countries. METHODS: We performed a retrospective serial cross-sectional cohort study of adults aged ≥66 years hospitalized with hip fracture between 2011 and 2018 in the US, Canada, England, the Netherlands, Taiwan, and Israel using population-representative administrative data. We examined mortality, hip fracture treatment approaches (total hip arthroplasty [THA], hemiarthroplasty [HA], internal fixation [IF], and nonoperative), and health system performance measures, including hospital length of stay (LOS), 30-day readmission rates, and time-to-surgery. RESULTS: The total number of hip fracture admissions between 2011 and 2018 ranged from 23,941 in Israel to 1,219,696 in the US. In 2018, 30-day mortality varied from 3% (16% at 1 year) in Taiwan to 10% (27%) in the Netherlands. With regards to processes of care, the proportion of hip fractures treated with HA (range 23%-45%) and THA (0.2%-10%) differed widely across countries. For example, in 2018, THA was used to treat approximately 9% of patients in England and Israel but less than 1% in Taiwan. Overall, IF was the most common surgery performed in all countries (40%-60% of patients). IF was used in approximately 60% of patients in the US and Israel, but only 40% in England. In 2018, rates of nonoperative management ranged from 5% of patients in Taiwan to nearly 10% in England. Mean hospital LOS in 2018 ranged from 6.4 days (US) to 18.7 days (England). The 30-day readmission rate in 2018 ranged from 8% (in Canada and the Netherlands) to nearly 18% in England. The mean days to surgery in 2018 ranged from 0.5 days (Israel) to 1.6 days (Canada). CONCLUSIONS: We observed substantial between-country variation in mortality, surgical approaches, and health system performance measures. These findings underscore the need for further research to inform evidence-based surgical approaches.

Difference-in-differences for categorical outcomes.

OBJECTIVE: To discuss and develop difference-in-difference estimators for categorical outcomes and apply them to estimate the effect of the Affordable Care Act's Medicaid expansion on insurance coverage. DATA SOURCES: Secondary analysis of Survey on Income and Program Participation (SIPP) data on health insurance coverage types before (January 2013) and after (December 2015) Medicaid expansion in 39 US states (19 expansion and 20 non-expansion). STUDY DESIGN: We develop difference-in-difference methods for repeated measures (panel data) of categorical outcomes. We discuss scale-dependence of DID assumptions for marginal and transition effect estimates and specify a new target estimand: the difference between outcome category transitions under treatment versus no treatment. We establish causal assumptions about transitions that are sufficient to identify this and a marginal target estimand. We contrast the marginal estimands identified by the transition approach versus an additive assumption only about marginal evolution. We apply both the marginal and transition approaches to estimate the effects of Medicaid expansion on health insurance coverage types (employer-sponsored; other private, non-group; public; and uninsured). DATA EXTRACTION: We analyzed 16,027 individual survey responses from people aged 18-62 years in the 2014 SIPP panel. PRINCIPAL FINDINGS: We show that the two identifying assumptions are equivalent (on the scale of the marginals) if either the baseline marginal distributions are identical or the marginals are constant in both groups. Applying our transitions approach to the SIPP data, we estimate a differential increase in transitions from uninsured to public coverage and differential decreases in transitions from uninsured to private, non-group coverage and in remaining uninsured. CONCLUSIONS: By comparing the assumption that marginals are evolving in parallel to an assumption about transitions across outcome values, we illustrate the scale-dependence of difference-in-differences. Our application shows that studying transitions can illuminate nuances obscured by changes in the marginals.

Variation in revascularisation use and outcomes of patients in hospital with acute myocardial infarction across six high income countries: cross sectional cohort study.

OBJECTIVES: To compare treatment and outcomes for patients admitted to hospital with a primary diagnosis of ST elevation or non-ST elevation myocardial infarction (STEMI or NSTEMI) in six high income countries with very different healthcare delivery systems. DESIGN: Retrospective cross sectional cohort study. SETTING: Patient level administrative data from the United States, Canada (Ontario and Manitoba), England, the Netherlands, Israel, and Taiwan. PARTICIPANTS: Adults aged 66 years and older admitted to hospital with STEMI or NSTEMI between 1 January 2011 and 31 December 2017. OUTCOMES MEASURES: The three categories of outcomes were coronary revascularisation (percutaneous coronary intervention or coronary artery bypass graft surgery), mortality, and efficiency (hospital length of stay and 30 day readmission). Rates were standardised to the age and sex distribution of the US acute myocardial infarction population in 2017. Outcomes were assessed separately for STEMI and NSTEMI. Performance was evaluated longitudinally (over time) and cross sectionally (between countries). RESULTS: The total number of hospital admissions ranged from 19 043 in Israel to 1 064 099 in the US. Large differences were found between countries for all outcomes. For example, the proportion of patients admitted to hospital with STEMI who received percutaneous coronary intervention in hospital during 2017 ranged from 36.9% (England) to 78.6% (Canada; 71.8% in the US); use of percutaneous coronary intervention for STEMI increased in all countries between 2011 and 2017, with particularly large rises in Israel (48.4-65.9%) and Taiwan (49.4-70.2%). The proportion of patients with NSTEMI who underwent coronary artery bypass graft surgery within 90 days of admission during 2017 was lowest in the Netherlands (3.5%) and highest in the US (11.7%). Death within one year of admission for STEMI in 2017 ranged from 18.9% (Netherlands) to 27.8% (US) and 32.3% (Taiwan). Mean hospital length of stay in 2017 for STEMI was lowest in the Netherlands and the US (5.0 and 5.1 days) and highest in Taiwan (8.5 days); 30 day readmission for STEMI was lowest in Taiwan (11.7%) and the US (12.2%) and highest in England (23.1%). CONCLUSIONS: In an analysis of myocardial infarction in six high income countries, all countries had areas of high performance, but no country excelled in all three domains. Our findings suggest that countries could learn from each other by using international comparisons of patient level nationally representative data.

Multilevel empirical bayes modeling for improved estimation of toxicant formulations to suppress parasitic sea lamprey in the upper great lakes.

Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data.

Joint modeling of multiple longitudinal patient-reported outcomes and survival.

Researchers often include patient-reported outcomes (PROs) in Phase III clinical trials to demonstrate the value of treatment from the patient's perspective. These data are collected as longitudinal repeated measures and are often censored by occurrence of a clinical event that defines a survival time. Hierarchical Bayesian models having latent individual-level trajectories provide a flexible approach to modeling such multiple outcome types simultaneously. We consider the case of many zeros in the longitudinal data motivating a mixture model, and demonstrate several approaches to modeling multiple longitudinal PROs with survival in a cancer clinical trial. These joint models may enhance Phase III analyses and better inform health care decision makers.