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The net effect of the pandemic mitigation strategies on childhood mortality is not known. During the first year of the COVID-19 pandemic, mitigation policies and behaviors were widespread, and although vaccinations and effective treatments were not yet widely available, the risk of death from SARS-CoV-2 infection was low. In that first year, there was a 7% decrease in medical (“natural causes”) mortality among children ages 0-9 during the first pandemic year (5% among infants 1 year was absent. However, smaller increases in external (“non-natural causes”) mortality were also observed during the study period, which decreased the overall number of pediatric deaths averted during both years and the pandemic period. In total, 1,468 fewer all-cause pediatric deaths than expected occurred in the United States during the first 24 months of the COVID-19 pandemic.

IntroductionThe US continued to record all-cause excess mortality after the rollout of vaccines. We sought to quantify excess mortality by state and compare these rates to primary series vaccination completion levels.MethodsObservational cohort, US and state-level data. Expected monthly deaths were modeled using pre-pandemic US and state-level data (2015-2020). Mortality data was accessed from CDC public reporting.ResultsWe find that in a two-year period since the rollout of vaccines, the US recorded >874,000 excess deaths. Vaccination rates and excess mortality were most strongly correlated in first two periods before the Omicron variant.ConclusionThe association between vaccination and lower excess mortality rates was strongest in 2021 and early 2022, prior to high population rates of infection-acquired immunity. The findings underscore the benefits of the rapid vaccination rollout campaign and the continued need to boost at-risk populations.

IntroductionThe US has continued to see excess mortality through the Delta and Omicron periods. We sought to quantify excess mortality on a state level and calculate potential deaths averted if all states matched the excess mortality rates of those with the 10 lowest excess mortality rates.MethodsObservational cohort, US and state-level data. Expected monthly deaths were modeled using pre-pandemic US and state-level data (2015-2020). Mortality data was accessed from CDC public reporting.ResultsWe find that during the Delta and Omicron waves, the US recorded over 596,000 excess deaths. 60% of the nation’s total excess mortality during these periods could have been averted if all states had excess mortality rates equal to those with the 10 lowest excess mortality rates.ConclusionWith large differences in excess mortality across US states in this 15-month study period, we note that a significant portion of deaths could have been averted with higher vaccination rates, improved mitigation policies, and adherence to other behaviors.

BackgroundThe popular beta-binomial approach to estimate the reliability of healthcare quality measures (Adams et al. 2010New England Journal of Medicine) may yield grossly over-estimated reliabilities for providers with event rates equal to 0% or 100%.ObjectiveImprove the beta-binomial approach to yield more reasonable reliability estimates for providers with event rates equal to 0% or 100%.MethodWe revise the beta-binomial approach by substituting Bayesian estimates with various priors for the crude event rates. We evaluate the new reliability estimates using Monte Carlo studies and two real-world measure examples.Results and conclusionThe revised beta-binomial approach based on Jeffreys non-informative prior yields more reasonable reliability estimates for providers with event rates equal to 0% or 100% and statistically outperforms the original beta-binomial approach regarding bias and standard errors.

IntroductionExcess mortality does not depend on labeling the cause of death and is an accurate representation of the pandemic population-level effects. A comprehensive evaluation of all-cause excess mortality in the United States during the first two years of the COVID-19 pandemic, stratified by age, sex, region, and race/ethnicity can provide insight into the extent and variation in harm.MethodsWith Centers for Disease Control and Prevention (CDC)/National Center for Health Statistics (NCHS) data from 2014-2022, we use seasonal autoregressive integrated moving averages (sARIMA) to estimate excess mortality during the pandemic, defined as the difference between the number of observed and expected deaths. We continuously correct monthly expected deaths to reflect the decreased population owing to cumulative pandemic-associated excess deaths recorded. We calculate excess mortality for the total US population, and by age, sex, US census division, and race/ethnicity.ResultsFrom March 1, 2020, through February 28, 2022, there were 1.17 million excess deaths in the United States. Overall, mortality was 20% higher than expected during the study period. Of the excess deaths, 799,477 (68%) were among residents aged 65 and older. The largest relative increase in all-cause mortality was 27% among adults ages 18-49 years. Males comprised most of the excess mortality (57%), but this predominance declined with age. A higher relative mortality occurred among non-Hispanic American Indian/Alaskan Native, non-Hispanic Black, non-Hispanic Native Hawaiian and Other Pacific Islander, Hispanic people. Excess mortality differed by region; the highest rates were in the South, including in the population ages ≥65 years. Excess mortality rose and fell contemporaneously with COVID-19 waves.ConclusionIn the first two years of the pandemic, the US experienced 1.17 million excess deaths, with greater relative increases in all-cause mortality among men, in American Indian/Alaskan Native, Black and Hispanic people, and the South.

ImportanceSelected glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium glucose cotransporter-2 inhibitors (SGLT2i) have cardioprotective effects in patients with type 2 diabetes and elevated cardiovascular risk. Prescription of these agents by clinicians and their consistent use by patients are essential to realize their benefits.ObjectiveTo assess the patterns of use and prescription fills of GLP-1RAs and SGLT-2i.DesignCross-sectional for medication use and prospective for prescription fills in 2018-2020SettingNationwide de-identified US administrative claims database of Medicare Advantage and commercially insured adults.ParticipantsIndividuals 18 years of age and older with type 2 diabetesExposuresComorbidities representing guideline-directed indications of atherosclerotic cardiovascular disease (ASCVD) for GLP-1RAs, and ASCVD, heart failure, and diabetic nephropathy for SGLT2i.Main Outcomes and MeasuresMedication use and monthly fill rates for 12 months following initiation of therapy by calculating the proportion of days with consistent medication use.ResultsAmong 587,657 individuals with type 2 diabetes, 80,196 (13.6%) were prescribed GLP-1RAs and 68,149 (11.5%) SGLT2i during 2018-2020. This represented 12.9% and 10.5% of individuals with indications for each medication, respectively. Based on monthly counts of new prescriptions, there were no changes in the uptake of either drug class during 2019-2020. Among new initiators, fill rate was 52.5% for GLP-1RAs and 52.9% for SGLT2i one year after initiation. One-year fill rates were higher for patients with commercial insurance than those with Medicare Advantage plans for both GLP-1RAs (59.3% vs 51.0%, p-valueConclusions and RelevanceIn 2018-2020, use of GLP-1RAs and SGLT2i remained limited to fewer than 1 in 8 individuals with type 2 diabetes meeting criteria for evidence-based guideline and professional society recommendations, with one-year fill rates around 50%. The low and inconsistent use of these medications compromises their longitudinal health outcomes benefits in a period of expanding indications for their use.

BackgroundWe sought to quantify whether there were statistically significant disparities along race and ethnicity lines during the early rollout of Covid-19 vaccine booster doses in the United States. We also studied whether such disparities replicated or widened disparities that had already been observed during the initial series rollout as of 2 months earlier (Janssen) or 6 months earlier (Pfizer-BioNTech or Moderna), which comprised the booster-eligible population.MethodsThis cross-sectional study of US adults (ages ≥18 years) used public data from US Centers for Disease Control and Prevention. The observed shares of vaccine doses for each race and ethnicity were compared to the expected shares, predicted based upon the compositions of the booster-eligible and initial series-eligible populations.ResultsAs of November 16, 2021, 123.5 million US adults were eligible for a booster dose of either the Pfizer-BioNTech, Moderna, or Janssen vaccines. Of these, 21.7 million had received a booster dose, among whom race and ethnicity information was available for 18.8 million booster recipients.A statistically significant higher share of Non-Hispanic White and Non-Hispanic Multiple/Other race individuals had received a booster vaccination than projected based on the composition of the booster-eligible population. A statistically significant lower share of Hispanic, Non-Hispanic American Indian/Alaskan Native, Non-Hispanic Asian, Non-Hispanic Black, and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals had received a booster vaccination than expected based on the booster-eligible population. A secondary analysis of the booster-eligible population found that some of these disparities had already occurred at the time of the initial series. However, the booster campaign widened all of those disparities and added new disparities for Non-Hispanic American Indian/Alaskan Native and Non-Hispanic Native Hawaiian/Other Pacific Islander individuals.ConclusionDisparities in Covid-19 vaccine administration on race and ethnicity lines occurred during the initial series rollout in the US. However, these disparities were not merely replicated but widened by the early booster rollout.

BackgroundAll-cause excess mortality (the number of deaths that exceed projections in any period) has been widely reported during the Covid-19 pandemic. Whether excess mortality has occurred during the Delta wave is less well understood.MethodsWe performed an observational study using data from the Massachusetts Department of Health. Five years of US Census population data and CDC mortality statistics were applied to a seasonal autoregressive integrated moving average (sARIMA) model to project the number of expected deaths for each week of the pandemic period, including the Delta period (starting in June 2021, extending through August 28th 2021, for which mortality data are >99% complete). Weekly Covid-19 cases, Covid-19-attributed deaths, and all-cause deaths are reported. County-level excess mortality during the vaccine campaign are also reported, with weekly rates of vaccination in each county that reported 100 or more all-cause deaths during any week included in the study period.ResultsAll-cause mortality was not observed after March 2021, by which time over 75% of persons over 65 years of age in Massachusetts had received a vaccination. Fewer deaths than expected (which we term ‘deficit mortality’) occurred both during the summer of 2020, the spring of 2021 and during the Delta wave (beginning June 13, 2021 when Delta isolates represented >10% of sequenced cases). After the initial wave in the spring of 2020, more Covid-19-attributed deaths were recorded that all-cause excess deaths, implying that Covid-19 was misattributed as the underlying cause, rather than a contributing cause of death in some cases.ConclusionIn a state with high vaccination rates, excess mortality has not been recorded during the Delta period. Deficit mortality has been recorded during this period.

ObjectiveReal-world data have been critical for rapid-knowledge generation throughout the COVID-19 pandemic. To ensure high-quality results are delivered to guide clinical decision making and the public health response, as well as characterize the response to interventions, it is essential to establish the accuracy of COVID-19 case definitions derived from administrative data to identify infections and hospitalizations.MethodsElectronic Health Record (EHR) data were obtained from the clinical data warehouse of the Yale New Haven Health System (Yale, primary site) and 3 hospital systems of the Mayo Clinic (validation site). Detailed characteristics on demographics, diagnoses, and laboratory results were obtained for all patients with either a positive SARS-CoV-2 PCR or antigen test or ICD-10 diagnosis of COVID-19 (U07.1) between April 1, 2020 and March 1, 2021. Various computable phenotype definitions were evaluated for their accuracy to identify SARS-CoV-2 infection and COVID-19 hospitalizations.ResultsOf the 69,423 individuals with either a diagnosis code or a laboratory diagnosis of a SARS-CoV-2 infection at Yale, 61,023 had a principal or a secondary diagnosis code for COVID-19 and 50,355 had a positive SARS-CoV-2 test. Among those with a positive laboratory test, 38,506 (76.5%) and 3449 (6.8%) had a principal and secondary diagnosis code of COVID-19, respectively, while 8400 (16.7%) had no COVID-19 diagnosis. Moreover, of the 61,023 patients with a COVID-19 diagnosis code, 19,068 (31.2%) did not have a positive laboratory test for SARS-CoV-2 in the EHR. Of the 20 cases randomly sampled from this latter group for manual review, all had a COVID-19 diagnosis code related to asymptomatic testing with negative subsequent test results. The positive predictive value (precision) and sensitivity (recall) of a COVID-19 diagnosis in the medical record for a documented positive SARS-CoV-2 test were 68.8% and 83.3%, respectively. Among 5,109 patients who were hospitalized with a principal diagnosis of COVID-19, 4843 (94.8%) had a positive SARS-CoV-2 test within the 2 weeks preceding hospital admission or during hospitalization. In addition, 789 hospitalizations had a secondary diagnosis of COVID-19, of which 446 (56.5%) had a principal diagnosis consistent with severe clinical manifestation of COVID-19 (e.g., sepsis or respiratory failure). Compared with the cohort that had a principal diagnosis of COVID-19, those with a secondary diagnosis had a more than 2-fold higher in-hospital mortality rate (13.2% vs 28.0%, PConclusionsCOVID-19 diagnosis codes misclassified the SARS-CoV-2 infection status of many people, with implications for clinical research and epidemiological surveillance. Moreover, the codes had different performance across two academic health systems and identified groups with different risks of mortality. Real-world data from the EHR can be used to in conjunction with diagnosis codes to improve the identification of people infected with SARS-CoV-2.

Introduction The COVID-19 pandemic has been associated with substantial rates of all-cause excess mortality. The contribution of external causes of death to excess mortality including drug overdose, homicide, suicide, and unintentional injuries during the initial outbreak in the United States is less well documented. Methods Using public data published by the National Center for Health Statistics on February 10, 2021, we measured monthly excess mortality (the gap between observed and expected deaths) from five external causes using national-level data published by National Center for Health Statistics; assault (homicide); intentional self-harm (suicide); accidents (unintentional injuries); and motor vehicle accidents. We used seasonal autoregressive integrated moving average (sARIMA) models developed with cause-specific monthly mortality counts and US population data from 2015-2019 and estimated the contribution of individual cause-specific mortality to all-cause excess mortality from March-July 2020. Results From March-July, 2020, 212,825 (95% CI 136,236-290,776) all-cause excess deaths occurred in the US). There were 8,540 excess drug overdoses (all intents) (95% CI 5,106 to 11,975), accounting for 4% of all excess mortality; 1,455 excess homicide deaths (95% CI 708 to 2202, accounting for 0.7% of excess mortality; 5,492 excess deaths due to unintentional accidents occurred (95% CI 85 to 10,899, accounting for 2.6% of excess mortality. Though a non-significantly 135 (95% CI -1361 to 1,630) more MVA deaths were recorded during the study period, a significant decrease in April (525; 95% CI -817 to -233) and significant increases in June-July (965; 95% CI 348 to 1,587) were observed. Suicide deaths were statistically lower than projected by 2,067 (95% CI 941-3,193 fewer deaths). Meaning Excess deaths from drug overdoses, homicide, and addicents occurred during the pandemic but represented a small fraction of all-cause excess mortality. The excess external causes of death, however, still represent thousands of lives lost. Notably, deaths from suicide were lower than expected and therefore did not contribute to excess mortality.

ObjectivesWe identify a correction for excess mortality that takes the sudden unexpected changes in the size of the United States population into account.DesignThis is a weekly cross-sectional analysis of all-cause mortality since week 5, 2020. We describe and apply a simple correction that takes population changes into account in order to provide corrected weekly estimates of expected deaths for 2020 and 2021.SettingThe United States.ParticipantsAll United States residents.InterventionsThe covid-19 pandemic.Main outcome measuresExpected and excess mortality for the United States during the covid-19 period.ResultsAs of week 53, 2020 (ending January 2, 2021), approximately >10,200 more excess deaths have occurred in the United States than could be detected if expected deaths projections were not amended to reflect population decreases during 2020. The figure is projected to rise to >12,600 (>600 weekly) by week 5, 2021. Assuming recent excess mortality and pandemic-associated visa reductions continue until the earliest time herd immunity could be approached resulting from a combination of infections and vaccinations (week 17, 2021), if point estimates of expected deaths are not corrected, expected deaths will be overestimated (and therefore potential excess mortality underestimated) by ∼43,000 during 2021, or >53,300 since the outbreak of the pandemic measurement period (beginning week 5, 2020). By late December 2021, weekly expected death differences are projected to approach 1,000 per week.ConclusionsCurrent models measuring excess mortality should be revised immediately so that public health officials do not lose the ability to detect ongoing excess mortality as the population changes continue to compound, lowering the number of weekly expected deaths. A similar approach should be used in the middle and late phases of all future pandemics.

IntroductionCoronavirus disease-19 (COVID-19) has caused a marked increase in all-cause deaths in the United States, mostly among adults aged 65 and older. Because younger adults have far lower infection fatality rates, less attention has been focused on the mortality burden of COVID-19 in this demographic.MethodsWe performed an observational cohort study using public data from the National Center for Health Statistics at the United States Centers for Disease Control and Prevention, and CDC Wonder. We analyzed all-cause mortality among adults ages 25-44 during the COVID-19 pandemic in the United States. Further, we compared COVID-19-related deaths in this age group during the pandemic period to all drug overdose deaths and opioid-specific overdose deaths in each of the ten Health and Human Services (HHS) regions during the corresponding period of 2018, the most recent year for which data are available.ResultsAs of September 6, 2020, 74,027 all-cause deaths occurred among persons ages 25-44 years during the period from March 1st to July 31st, 2020, 14,155 more than during the same period of 2019, a 23% relative increase (incident rate ratio 1.23; 95% CI 1.21–1.24), with a peak of 30% occurring in May (IRR 1.30; 95% CI 1.27-1.33). In HHS Region 2 (New York, New Jersey), HHS Region 6 (Arkansas, Louisiana, New Mexico, Oklahoma, Texas), and HHS Region 9 (Arizona, California, Hawaii, Nevada), COVID-19 deaths exceeded 2018 unintentional opioid overdose deaths during at least one month. Combined, 2,450 COVID-19 deaths were recorded in these three regions during the pandemic period, compared to 2,445 opioid deaths during the same period of 2018.MeaningWe find that COVID-19 has likely become the leading cause of death—surpassing unintentional overdoses—among young adults aged 25-44 in some areas of the United States during substantial COVID-19 outbreaks.NoteThe data presented here have since been updated. As a result, an additional 1,902 all-cause deaths occurring among US adults ages 25-44 during the period of interest are not accounted for in this manuscript.

ImportanceThe coronavirus disease 2019 (COVID-19) outbreak has been associated with decreases in acute myocardial infarction diagnoses (AMI) and admissions in the United States. Whether this affected heart disease deaths is unknown.ObjectiveTo determine whether changes in heart disease deaths occurred during the early pandemic period in the US, we analyzed areas without large COVID-19 outbreaks. This isolated the effect of decreased healthcare-seeking behavior during the early outbreak.Design, Setting, and ParticipantsWe performed an observational study of heart disease-specific mortality using National Center for Health Statistics data (NCHS). Weekly provisional counts were disaggregated by jurisdiction of occurrence during 2019 and 2020 for all-cause deaths, COVID-19 deaths, and heart disease deaths. For the primary analysis, jurisdictions were included if; 1) There was no all-cause excess mortality during the early pandemic period (weeks 14–17, 2020); 2) The completeness of that data was estimated by NCHS to be >97% as of July 22, 2020, and; 3) Decreases in emergency department (ED) visits occurred during the study period. We compared heart disease death rates during the early pandemic period with corresponding weeks in 2019 and a pre-pandemic control period of 2020 as a sensitivity analysis. Incident rate and rate ratios were calculated.ExposureThe US COVID-19 outbreak.Main Outcomes and MeasuresIncidence of heart disease deaths.ResultsTwelve states met the primary inclusion criteria, capturing 747,375,188 person-weeks for the early pandemic period and 740,987,984 person-weeks for the 2019 control period. The mean incidence rate (per 100,000 person-weeks) for heart disease in states without excess deaths during the early pandemic period was 3.95 (95% CI 3.83 to 4.06) versus 4.19 (95% CI 4.14 to 4.23) during the corresponding period in 2019. The incident rate ratio (2020/2019) was 0.91 (95% CI 0.87 to 0.97). No state recorded an increase from either the corresponding period in 2019 or the 2020 prepandemic control period. Two states recorded fewer heart disease deaths.Conclusions and RelevanceThis observational study found a decrease in heart disease deaths during the early US outbreak in regions without significant COVID-19 burdens, despite decreases in ED utilization. Long term follow-up data are needed.

Importance: A seroprevalence study can estimate the percentage of people with SARS-CoV-2 antibodies in the general population. Most existing reports have used a convenience sample, which may bias their estimates. Objective: To estimate the seroprevalence of antibodies against SARS-CoV-2 based on a random sample of adults living in Connecticut between March 1 and June 1, 2020. Design: Cross-sectional. Setting: We sought a representative sample of Connecticut residents who completed a survey between June 4 and June 23, 2020 and underwent serology testing for SARS-CoV-2-specific IgG antibodies between June 10 and July 6, 2020. Participants: 505 respondents, aged ≥18 years, residing in non-congregate settings who completed both the survey and the serology test. Main outcomes and measures: We estimated the seroprevalence of SARS-CoV-2-specific IgG antibodies among the overall population and across pre-specified subgroups. We also assessed the prevalence of symptomatic illness, risk factors for virus exposure, and self-reported adherence to risk mitigation behaviors among this population. Results: Of the 505 respondents (mean age 50 [±17] years; 54% women; 76% non-Hispanic White individuals) included, 32% reported having at least 1 symptom suggestive of COVID-19 since March 1, 2020. Overall, 18 respondents had SARS-CoV-2-specific antibodies, resulting in the state-level weighted seroprevalence of 3.1 (90% CI 1.4-4.8). Individuals who were asymptomatic had significantly lower seroprevalence (0.6% [90% CI 0.0-1.5]) compared with the overall state estimate, while those who reported having had ≥1 and ≥2 symptoms had a seroprevalence of 8.0% (90% CI 3.1-12.9) and 13.0% (90% CI 3.5-22.5), respectively. All 9 of the respondents who reported previously having a positive coronavirus test were positive for SARS-CoV-2-specific IgG antibodies. Nearly two-third of respondents reported having avoided public places (74%) and small gatherings of family or friends (75%), and 97% reported wearing a mask outside their home, at least part of the time. Conclusions and relevance: These estimates indicate that most people in Connecticut do not have detectable levels of antibodies against SARS-CoV-2. There is a need for continued adherence to risk mitigation behaviors among Connecticut residents, to prevent resurgence of COVID-19 in this region.

The SARS-CoV-2 pandemic is associated with a reduction in hospitalization for an acute cardiovascular conditions. In a major health system in Massachusetts, there was a 43% reduction in these types of hospitalizations in March 2020 compared with March 2019.4 Whether mortality rates from heart disease have changed over this period is unknown.We assembled information from the National Center for Health Statistics (Centers for Disease Control and Prevention) for 118,356,533 person-weeks from Week 1 (ending January 4) through Week 17 (ending April 25) of 2020 for the state of Massachusetts. We found that heart disease deaths are unchanged during the Covid-19 pandemic period as compared to the corresponding period of 2019. This is despite reports that admissions for acute myocardial infarction have fallen during this time.

Background: Whether angiotensin-converting enzyme (ACE) Inhibitors and angiotensin receptor blockers (ARBs) mitigate or exacerbate SARS-CoV-2 infection remains uncertain. In a national study, we evaluated the association of ACE inhibitors and ARB with coronavirus disease-19 (COVID-19) hospitalization and mortality among individuals with hypertension. Methods: Among Medicare Advantage and commercially insured individuals, we identified 2,263 people with hypertension, receiving ≥1 antihypertensive agents, and who had a positive outpatient SARS-CoV-2 test (outpatient cohort). In a propensity score-matched analysis, we determined the association of ACE inhibitors and ARBs with the risk of hospitalization for COVID-19. In a second study of 7,933 individuals with hypertension who were hospitalized with COVID-19 (inpatient cohort), we tested the association of these medications with in-hospital mortality. We stratified all our assessments by insurance groups. Results: Among individuals in the outpatient and inpatient cohorts, 31.9% and 29.8%, respectively, used ACE inhibitors and 32.3% and 28.1% used ARBs. In the outpatient study, over a median 30.0 (19.0 - 40.0) days after testing positive, 12.7% were hospitalized for COVID-19. In propensity score-matched analyses, neither ACE inhibitors (HR, 0.77 [0.53, 1.13], P = 0.18), nor ARBs (HR, 0.88 [0.61, 1.26], P = 0.48), were significantly associated with risk of hospitalization. In analyses stratified by insurance group, ACE inhibitors, but not ARBs, were associated with a significant lower risk of hospitalization in the Medicare group (HR, 0.61 [0.41, 0.93], P = 0.02), but not the commercially insured group (HR: 2.14 [0.82, 5.60], P = 0.12; P-interaction 0.09). In the inpatient study, 14.2% died, 59.5% survived to discharge, and 26.3% had an ongoing hospitalization. In propensity score-matched analyses, neither use of ACE inhibitor (0.97 [0.81, 1.16]; P = 0.74) nor ARB (1.15 [0.95, 1.38]; P = 0.15) was associated with risk of in-hospital mortality, in total or in the stratified analyses. Conclusions: The use of ACE inhibitors and ARBs was not associated with the risk of hospitalization or mortality among those infected with SARS-CoV-2. However, there was a nearly 40% lower risk of hospitalization with the use of ACE inhibitors in the Medicare population. This finding merits a clinical trial to evaluate the potential role of ACE inhibitors in reducing the risk of hospitalization among older individuals, who are at an elevated risk of adverse outcomes with the infection.

BackgroundThere is conflicting evidence about whether the Hospital Readmission Reduction Program (HRRP) is associated with an increase in mortality.MethodsIn a cohort of Medicare beneficiaries hospitalized with heart failure (HF), we compared two published approaches to evaluating the association of HRRP and risk-adjusted 30-day mortality, including changes in average mortality across periods and changes in slope of monthly mortality rates across discrete periods. We also tested various methods with simulated data that was designed with an inflection in mortality.ResultsWe identified 4,313,523 hospitalizations for HF, 1,788,219 for AMI, and 3,758,111 for pneumonia. Monthly slope-change models identified an increase in mortality for HF and pneumonia in the pre-HRRP period (PConclusionA national policy incentivizing efforts to reduce readmission did not increase the risk of mortality.

BackgroundThe evaluation of trends in patient outcomes requires adjustment for the changes in case-mix over time and, thus, could be influenced by the expansion of code slots on inpatient claims that occurred in January 2011. We tested the hypothesis that the changes in code slots caused an artifactual increase in the case mix over time compared with a strategy that restricted inpatient codes to the same number of slots over time, excluding consideration of codes beyond the first 9 after the expansion.MethodsIn Medicare claims over a 5-year period spanning the inpatient code slot expansion (2008-2012), we created cohorts of hospitalizations for heart failure (HF), acute myocardial infarction (AMI) and pneumonia, common hospitalization conditions included in federal policies. We obtained information on risk factors for 30-day post-discharge mortality or readmission for each condition from inpatient facility Medicare claims, outpatient facility claims and professional (or carrier) claims. We evaluated the effects of additional codes captured from the expanded slots in inpatient claims on the number of risk factors or model covariates, overall and based on their contribution to the risk of mortality or readmission. We modelled the effects of code expansion on risk-assessment using an interrupted time series framework.ResultsThere were 2,102,509 eligible hospitalizations for HF, 872,734 for AMI and 1,824,079 for pneumonia. The average number of risk factors increased across all covariate selection strategies. There was a larger increase in monthly average covariate count that included all codes at the time of the code slot increase relative to a strategy that consistently used only 9 inpatient codes (level change in interrupted time series model, 0.9% [95% CI 0.7% to 1.1%] in HF, 0.6% [0.5% to 0.7%] for AMI and 0.6% [0.4% to 0.8%] for pneumonia). Using both inpatient and outpatient/carrier codes for assessing risk factors, there was a smaller difference between strategies using 9 inpatient codes, compared with all inpatient claims (relative excess increase in covariates by 0.6% [0.4% to 0.8%] in HF, 0.4% [0.3% to 0.5%] for AMI, and 0.3% [0.1% to 0.6%] in pneumonia). However, the additional codes were limited to covariates with small contributions to the risk-adjustment models for mortality, without a significant inflection in measured risk of mortality across code expansion (P>0.05 in interrupted time-series models). Measured readmission risk increased with using only inpatient claims for risk assessment, but not if all outpatient and carrier claims were also used (P>0.05 in interrupted time-series models).ConclusionsThe expansion of inpatient code slots did not meaningfully affect the measurement of the risk of mortality or readmission, especially if comprehensive inpatient and outpatient claims are used, because the additional covariates only included conditions with a modest influence on risk adjusted models. The use of all versus limited codes after the code slot expansion has a minimal effect on evaluating trends in these conditions.

Background With incentives to reduce readmission rates in the United States, there are concerns that patients who need hospitalization after a recent hospital discharge may be denied access, which would increase their risk of mortality. Objective We determined whether patients with hospitalizations for conditions covered by national readmission programs who received care in emergency department (ED) or observation units but were not hospitalized within 30 days had an increased risk of death. We also evaluated temporal trends in post-discharge acute care utilization in inpatient units, emergency department (ED) and observation units for these patients. Design, Setting, and Participants In this observational study of national Medicare claims data for 2008-2016, we identified patients ≥65 years hospitalized with heart failure (HF), acute myocardial infarction (AMI), or pneumonia, conditions included in the HRRP. Main Outcomes and Measures Post-discharge 30-day mortality according to patients’ 30-day acute care utilization. Acute care utilization in inpatient and observation units, and the ED during the 30-day and 31-90-day post-discharge period. Results There were 3,772,924 hospitalizations for HF, 1,570,113 for AMI, and 3,131,162 for pneumonia. The overall post-discharge 30-day mortality was 8.7% for HF, 7.3% for AMI, and 8.4% for pneumonia. Risk-adjusted mortality increased annually by 0.05% (95% CI, 0.02% to 0.08%) for HF, decreased by 0.06% (95% CI, −0.09% to −0.04%) for AMI, and did not significantly change for pneumonia. Specifically, mortality increased for HF patients who did not utilize any post-discharge acute care, increasing at a rate of 0.08% per year (95% CI, 0.05% to 0.12%), exceeding the overall absolute annual increase in post-discharge mortality in heart failure, without an increase in mortality in observation units or the ED. Concurrent with a reduction in 30-day readmission rates, 30-day observation stays and visits to the ED increased across all 3 conditions during and beyond the post-discharge 30-day period. There was no significant change in overall 30-day post-acute care utilization. Conclusions The only condition with an increasing mortality through the study period was HF; the increase preceded the policy and was not present among those received ED or observation unit care without hospitalization. Overall, during this period, there was not a significant change in the overall 30-day post-discharge acute care utilization. What is already known on this topic Among Medicare beneficiaries hospitalized for heart failure, mortality in the 30-day post-discharge period has been increasing over the past several years. However, the relationship between post-discharge acute care and mortality in the early post-discharge period remains poorly understood. Observation units and the emergency departments (ED) have increasingly been used as avenues for patient care in the United States. However, the utilization of these services in the early post-discharge period for conditions targeted in the Hospital Readmissions Reduction Program (HRRP), and the outcomes of patients in these settings, is required to appropriately evaluate the effects of the program. What this study adds Among conditions targeted in the HRRP, patients with heart failure, but not those with acute myocardial infarction or pneumonia, experienced increase in post-discharge 30-day mortality. This increase preceded the announcement of the program and was concentrated among individuals who sought no post-discharge acute care, nearly half of whom had been discharged to hospice. Despite increasing utilization of observation units and the ED in the post-discharge period, care in these settings was not associated with increased mortality risk.