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2.
J Am Heart Assoc ; 9(6): e014907, 2020 Mar 17.
Artigo em Inglês | MEDLINE | ID: mdl-32172654

RESUMO

Background Patients who survive acute myocardial infarction (AMI) are at high risk for recurrence. We determined whether rehospitalizations after AMI further increased risk of recurrent AMI. Methods and Results The study included Medicare fee-for-service patients aged ≥65 years discharged alive after AMI from acute-care hospitals in fiscal years 2009-2014. The outcome was recurrent AMI within 1 year of the index AMI. The Clinical Classifications Software (CCS) was used to classify rehospitalizations into disease categories. A Cox regression model was fit accounting for CCS-specific hospitalizations as time-varying variables and patient characteristics at discharge for the index AMI, adjusting for the competing risk of death. The rate of 1-year recurrent AMI was 5.3% (95% CI, 5.27%-5.41%), and median (interquartile range) time from discharge to recurrent AMI was 115 (34-230) days. Eleven disease categories (diabetes mellitus, anemia, hypertension, coronary atherosclerosis, chest pain, heart failure, pneumonia, chronic obstructive pulmonary disease, gastrointestinal hemorrhage, renal failure, complication of implant or graft) were associated with increased risk of recurrent AMI. Septicemia was associated with lower recurrence risk. Hazard ratios ranged from 1.6 (95% CI, 1.55-1.70, heart failure) to 1.1 (95% CI, 1.04-1.25, pneumonia) to 0.6 (95% CI, 0.58-0.71, septicemia). Conclusions Patient risk of recurrent AMI changed based on the occurrence of hospitalizations after the index AMI. Improving post-acute care to prevent unplanned rehospitalizations, especially rehospitalizations for chronic diseases, and extending the focus of outcomes measures to condition-specific rehospitalizations within 30 days and beyond is important for the secondary prevention of AMI.

3.
J Am Heart Assoc ; 9(4): e013606, 2020 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-32063087

RESUMO

Background More than 600 000 coronary stents are implanted during percutaneous coronary interventions (PCIs) annually in the United States. Because no real-world surveillance system exists to monitor their long-term safety, claims data are often used for this purpose. The extent to which adverse events identified with claims data can be reasonably attributed to a specific medical device is uncertain. Methods and Results We used deterministic matching to link the NCDR (National Cardiovascular Data Registry) CathPCI Registry to Medicare fee-for-service claims for patients aged ≥65 years who underwent PCI with drug-eluting stents (DESs) between July 1, 2009 and December 31, 2013. We identified subsequent PCIs within 1 year of the index procedure in Medicare claims as potential safety events. We linked these subsequent PCIs back to the NCDR CathPCI Registry to ascertain how often the revascularization could be reasonably attributed to the same coronary artery as the index PCI (ie, target vessel revascularization). Of 415 306 DES placements in 368 194 patients, 33 174 repeat PCIs were identified in Medicare claims within 1 year. Of these, 28 632 (86.3%) could be linked back to the NCDR CathPCI Registry; 16 942 (51.1% of repeat PCIs) were target vessel revascularizations. Of these, 8544 (50.4%) were within a previously placed DES: 7652 for in-stent restenosis and 1341 for stent thrombosis. Of 16 176 patients with a claim for acute myocardial infarction in the follow-up period, 4446 (27.5%) were attributed to the same coronary artery in which the DES was implanted during the index PCI (ie, target vessel myocardial infarction). Of 24 288 patients whose death was identified in claims data, 278 (1.1%) were attributed to the same coronary artery in which the DES was implanted during the index PCI. Conclusions Most repeat PCIs following DES stent implantation identified in longitudinal claims data could be linked to real-world registry data, but only half could be reasonably attributed to the same coronary artery as the index procedure. Attribution among those with acute myocardial infarction or who died was even less frequent. Safety signals identified using claims data alone will require more in-depth examination to accurately assess stent safety.

4.
Health Serv Res ; 55(2): 259-272, 2020 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31916243

RESUMO

OBJECTIVE: To investigate risk-adjusted, 30-day postdischarge heart failure mortality and readmission rates stratified by hospital teaching intensity. DATA SOURCES AND STUDY SETTING: A total of 709 221 Medicare fee-for-service beneficiaries discharged from 3135 US hospitals between 1/1/2013 and 11/30/2014 with a principal diagnosis of heart failure. STUDY DESIGN: Hospitals were classified as Council of Teaching Hospitals and Health Systems (COTH) major teaching hospitals, non-COTH teaching hospitals, and nonteaching hospitals. Hospital teaching status was linked with MedPAR patient data and FY2016 Hospital Readmission Reduction Program penalties. Index hospitalization survival probabilities were estimated with hierarchical logistic regression and used to stratify index hospitalization survivors into severity deciles. Decile-specific models were estimated for 30-day postdischarge readmission and mortality. Thirty-day postdischarge outcomes were estimated by teaching intensity and penalty categories. PRINCIPAL FINDINGS: Averaged across deciles, adjusted 30-day COTH hospital readmission rates were, on a relative scale ([COTH minus nonteaching] ÷ nonteaching), 1.63 percent higher (95% CI: 0.89 percent, 2.25 percent) than at nonteaching hospitals, but their average adjusted 30-day postdischarge mortality rates were 11.55 percent lower (95% CI: -13.78 percent, -9.37 percent). Penalized COTH hospitals had the highest readmission rates of all categories (23.99 percent [95% CI: 23.50 percent, 24.49 percent]) but the lowest 30-day postdischarge mortality (8.30 percent [95% CI: 7.99 percent, 8.57 percent] vs 9.84 percent [95% CI: 9.69 percent, 9.99 percent] for nonpenalized, nonteaching hospitals). CONCLUSIONS: Heart failure readmission penalties disproportionately impact major teaching hospitals and inadequately credit their better postdischarge survival.

6.
Biostatistics ; 21(1): 102-121, 2020 01 01.
Artigo em Inglês | MEDLINE | ID: mdl-30084949

RESUMO

In stepped wedge designs (SWD), clusters are randomized to the time period during which new patients will receive the intervention under study in a sequential rollout over time. By the study's end, patients at all clusters receive the intervention, eliminating ethical concerns related to withholding potentially efficacious treatments. This is a practical option in many large-scale public health implementation settings. Little statistical theory for these designs exists for binary outcomes. To address this, we utilized a maximum likelihood approach and developed numerical methods to determine the asymptotic power of the SWD for binary outcomes. We studied how the power of a SWD for detecting risk differences varies as a function of the number of clusters, cluster size, the baseline risk, the intervention effect, the intra-cluster correlation coefficient, and the time effect. We studied the robustness of power to the assumed form of the distribution of the cluster random effects, as well as how power is affected by variable cluster size. % SWD power is sensitive to neither, in contrast to the parallel cluster randomized design which is highly sensitive to variable cluster size. We also found that the approximate weighted least square approach of Hussey and Hughes (2007, Design and analysis of stepped wedge cluster randomized trials. Contemporary Clinical Trials 28, 182-191) for binary outcomes under-estimates the power in some regions of the parameter spaces, and over-estimates it in others. The new method was applied to the design of a large-scale intervention program on post-partum intra-uterine device insertion services for preventing unintended pregnancy in the first 1.5 years following childbirth in Tanzania, where it was found that the previously available method under-estimated the power.

7.
JAMA Netw Open ; 2(11): e1915604, 2019 Nov 01.
Artigo em Inglês | MEDLINE | ID: mdl-31730185

RESUMO

Importance: Some uncertainty exists about whether hospital variations in cost are largely associated with differences in case mix. Objective: To establish whether the same patients admitted with the same diagnosis (heart failure or pneumonia) at 2 different hospitals incur different costs associated with the hospital's Medicare payment profile. Design, Setting, and Participants: This observational cohort study used Centers for Medicare & Medicaid Services (CMS) discharge data of patients with a principal diagnosis of heart failure (n = 1615) or pneumonia (n = 708) occurring between July 1, 2013, and June 30, 2016. Patients were individuals aged 65 years or older who were enrolled in Medicare fee-for-service Part A and Part B and were discharged from nonfederal, short-term, acute care or critical access hospitals in the United States. Data were analyzed from March 16, 2018, to September 25, 2019. Main Outcomes and Measures: The CMS heart failure and pneumonia payment measure cohorts were divided into 2 random samples. In the first sample, hospitals were classified into payment quartiles for heart failure and pneumonia. In the second sample, patients with 2 admissions for heart failure or pneumonia, one in a lowest-quartile hospital and one in a highest-quartile hospital more than 1 month apart, were identified. Standardized Medicare payments for these patients were compared for the lowest- and the highest-quartile payment hospitals. Results: The study sample included 1615 patients with heart failure (mean [SD] age, 78.7 [8.0] years; 819 [50.7%] male) and 708 with pneumonia (mean [SD] age, 78.3 [8.0] years; 401 [56.6%] male). The observed 30-day mortality rates for patients among lowest- compared with highest-payment hospitals were not significantly different. The median (interquartile range) hospital 30-day risk-standardized mortality rates were 8.1% (7.7%-8.5%) for heart failure and 11.3% (10.7%-12.1%) for pneumonia. The 30-day episode payment for hospitalization for the same patients at the lowest-payment hospitals was $2118 (95% CI, $1168-$3068; P < .001) lower for heart failure and $2907 (95% CI, $1760-$4054; P < .001) lower for pneumonia than at the highest-payment hospitals. More than half of the difference was associated with the payment during the index hospitalization ($1425 [95% CI, $695-$2154; P < .001] for heart failure and $1659 [95% CI, $731-$2588; P < .001] for pneumonia). Conclusions and Relevance: This study found that the same Medicare beneficiaries who were admitted with the same diagnosis to hospitals with the highest payment profiles incurred higher costs than when they were admitted to hospitals with the lowest payment profiles. The findings suggest that variations in payments to hospitals are, at least in part, associated with the hospitals independently of non-time-varying patient characteristics.

8.
Med Decis Making ; 39(5): 583-592, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-31375050

RESUMO

Modeling dose-response relationships of drugs is essential to understanding their safety effects on patients under realistic circumstances. While intention-to-treat analyses of clinical trials provide the effect of assignment to a particular drug and dose, they do not capture observed exposure after factoring in nonadherence and dropout. We develop a Bayesian method to flexibly model the dose-response relationships of binary outcomes with continuous treatment, permitting multiple evidence sources, treatment effect heterogeneity, and nonlinear dose-response curves. In an application, we examine the risk of excessive weight gain for patients with schizophrenia treated with the second-generation antipsychotics paliperidone, risperidone, or olanzapine in 14 clinical trials. We define exposure as total cumulative dose (daily dose × duration) and convert to units equivalent to 100 mg of olanzapine (OLZ doses). Averaging over the sample population of 5891 subjects, the median dose ranged from 0 (placebo randomized participants) to 6.4 OLZ doses (paliperidone randomized participants). We found paliperidone to be least likely to cause excessive weight gain across a range of doses. Compared with 0 OLZ doses, at 5.0 OLZ doses, olanzapine subjects had a 15.6% (95% credible interval: 6.7, 27.1) excess risk of weight gain; corresponding estimates for paliperidone and risperidone were 3.2% (1.5, 5.2) and 14.9% (0.0, 38.7), respectively. Moreover, compared with nonblack participants, black participants had a 6.8% (1.0, 12.4) greater risk of excessive weight gain at 10.0 OLZ doses of paliperidone. Nevertheless, our findings suggest that paliperidone is safer in terms of weight gain risk than risperidone or olanzapine for all participants at low to moderate cumulative OLZ doses.

9.
JAMA Netw Open ; 2(8): e198406, 2019 Aug 02.
Artigo em Inglês | MEDLINE | ID: mdl-31411709

RESUMO

Importance: Predicting payments for particular conditions or populations is essential for research, benchmarking, public reporting, and calculations for population-based programs. Centers for Medicare & Medicaid Services (CMS) models often group codes into disease categories, but using single, rather than grouped, diagnostic codes and leveraging present on admission (POA) codes may enhance these models. Objective: To determine whether changes to the candidate variables in CMS models would improve risk models predicting patient total payment within 30 days of hospitalization for acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Design, Setting, and Participants: This comparative effectiveness research study used data from Medicare fee-for-service hospitalizations for AMI, HF, and pneumonia at acute care hospitals from July 1, 2013, through September 30, 2015. Payments across multiple care settings, services, and supplies were included and adjusted for geographic and policy variations, corrected for inflation, and winsorized. The same data source was used but varied for the candidate variables and their selection, and the method used by CMS for public reporting that used grouped codes was compared with variations that used POA codes and single diagnostic codes. Combinations of use of POA codes, separation of index admission diagnoses from those in the previous 12 months, and use of individual International Classification of Diseases, Ninth Revision, Clinical Modification codes instead of grouped diagnostic categories were tested. Data analysis was performed from December 4, 2017, to June 10, 2019. Main Outcomes and Measures: The models' goodness of fit was compared using root mean square error (RMSE) and the McFadden pseudo R2. Results: Among the 1 943 049 total hospitalizations of the study participants, 343 116 admissions were for AMI (52.5% male; 37.4% aged ≤74 years), 677 044 for HF (45.5% male; 25.9% aged ≤74 years), and 922 889 for pneumonia (46.4% male; 28.2% aged ≤74 years). The mean (SD) 30-day payment was $23 103 ($18 221) for AMI, $16 365 ($12 527) for HF, and $17 097 ($12 087) for pneumonia. Each incremental model change improved the pseudo R2 and RMSE. Incorporating all 3 changes improved the pseudo R2 of the patient-level models from 0.077 to 0.129 for AMI, from 0.042 to 0.129 for HF, and from 0.114 to 0.237 for pneumonia. Parallel improvements in RMSE were found for all 3 conditions. Conclusions and Relevance: Leveraging POA codes, separating index from previous diagnoses, and using single diagnostic codes improved payment models. Better models can potentially improve research, benchmarking, public reporting, and calculations for population-based programs.

10.
JAMA Netw Open ; 2(7): e197314, 2019 Jul 03.
Artigo em Inglês | MEDLINE | ID: mdl-31314120

RESUMO

Importance: Risk adjustment models using claims-based data are central in evaluating health care performance. Although US Centers for Medicare & Medicaid Services (CMS) models apply well-vetted statistical approaches, recent changes in the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) coding system and advances in computational capabilities may provide an opportunity for enhancement. Objective: To examine whether changes using already available data would enhance risk models and yield greater discrimination in hospital-level performance measures. Design, Setting, and Participants: This comparative effectiveness study used ICD-9-CM codes from all Medicare fee-for-service beneficiary claims for hospitalizations for acute myocardial infarction (AMI), heart failure (HF), or pneumonia among patients 65 years and older from July 1, 2013, through September 30, 2015. Changes to current CMS mortality risk models were applied incrementally to patient-level models, and the best model was tested on hospital performance measures to model 30-day mortality. Analyses were conducted from April 19, 2018, to September 19, 2018. Main Outcomes and Measures: The main outcome was all-cause death within 30 days of hospitalization for AMI, HF, or pneumonia, examined using 3 changes to current CMS mortality risk models: (1) incorporating present on admission coding to better exclude potential complications of care, (2) separating index admission diagnoses from those of the 12-month history, and (3) using ungrouped ICD-9-CM codes. Results: There were 361 175 hospital admissions (mean [SD] age, 78.6 [8.4] years; 189 225 [52.4%] men) for AMI, 716 790 hospital admissions (mean [SD] age, 81.1 [8.4] years; 326 825 [45.6%] men) for HF, and 988 225 hospital admissions (mean [SD] age, 80.7 [8.6] years; 460 761 [46.6%] men) for pneumonia during the study; mean 30-day mortality rates were 13.8% for AMI, 12.1% for HF, and 16.1% for pneumonia. Each change to the models was associated with incremental gains in C statistics. The best model, incorporating all changes, was associated with significantly improved patient-level C statistics, from 0.720 to 0.826 for AMI, 0.685 to 0.776 for HF, and 0.715 to 0.804 for pneumonia. Compared with current CMS models, the best model produced wider predicted probabilities with better calibration and Brier scores. Hospital risk-standardized mortality rates had wider distributions, with more hospitals identified as good or bad performance outliers. Conclusions and Relevance: Incorporating present on admission coding and using ungrouped index and historical ICD-9-CM codes were associated with improved patient-level and hospital-level risk models for mortality compared with the current CMS models for all 3 conditions.

12.
JAMA Netw Open ; 2(3): e191938, 2019 03 01.
Artigo em Inglês | MEDLINE | ID: mdl-30874787

RESUMO

Importance: Medicare and other organizations have focused on improving quality of care for patients with acute myocardial infarction (AMI) over the last 2 decades. However, there is no comprehensive perspective on the evolution of outcomes for AMI during that period, and it is unknown whether temporal changes varied by patient subgroup, hospital, or county. Objective: To provide a comprehensive evaluation of national trends in inpatient outcomes and costs of AMI during this period. Design, Setting, and Participants: This cohort study included analysis of data from a sample of 4 367 485 Medicare fee-for-service beneficiaries aged 65 years or older from January 1, 1995, through December 31, 2014, across 5680 hospitals in the United States. Analyses were conducted from January 15 to June 5, 2018. Main Outcomes and Measures: Thirty-day all-cause mortality at the patient, hospital, and county levels. Additional outcomes included 30-day all-cause readmissions; 1-year recurrent AMI; in-hospital mortality; length of hospital stay; 2014 Consumer Price Index-adjusted median Medicare inpatient payment per AMI discharge; and rates of catheterization, percutaneous coronary intervention, and coronary artery bypass graft surgery. Results: The cohort included 4 367 485 Medicare fee-for-service patients aged 65 years or older hospitalized for AMI during the study period. Between 1995 and 2014, the mean (SD) age of patients increased from 76.9 (7.2) to 78.2 (8.7) years, the percentage of female patients declined from 49.5% to 46.1%, the percentage of white patients declined from 91.0% to 86.2%, and the percentage of black patients increased from 5.9% to 8.0%. There were declines in AMI hospitalizations (914 to 566 per 100 000 beneficiary-years); 30-day mortality (20.0% to 12.4%; difference, 7.6 percentage points; 95% CI, 7.3-7.8 percentage points); 30-day all-cause readmissions (21.0% to 15.3%; difference, 5.7 percentage points; 95% CI, 5.4-6.0 percentage points); and 1-year recurrent AMI (7.1% to 5.1%; difference, 2.0 percentage points; 95% CI, 1.8-2.2 percentage points). There were increases in the 2014 Consumer Price Index-adjusted median (interquartile range) Medicare inpatient payment per AMI discharge ($9282 [$6969-$12 173] to $11 031 [$8099-$16 861]); 30-day inpatient catheterization (44.2% to 59.9%; difference, 15.7 percentage points; 95% CI, 15.4-16.0 percentage points); and inpatient percutaneous coronary intervention (18.8% to 43.3%; difference, 24.5 percentage points; 95% CI, 24.2-24.7 percentage points). Coronary artery bypass graft surgery rates decreased from 14.4% to 10.2% (difference, 4.2 percentage points; 95% CI, 3.9-4.3 percentage points). There was heterogeneity by hospital and county in the mortality changes over time. Conclusions and Relevance: This study shows marked improvements in short-term mortality and readmissions, with an increase in in-hospital procedures and payments, for the increasingly smaller number of Medicare beneficiaries with AMI.


Assuntos
Infarto do Miocárdio , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Ponte de Artéria Coronária/estatística & dados numéricos , Feminino , Hospitalização/estatística & dados numéricos , Humanos , Masculino , Medicare , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/mortalidade , Infarto do Miocárdio/terapia , Estados Unidos/epidemiologia
13.
J Thorac Cardiovasc Surg ; 158(1): 110-124.e9, 2019 07.
Artigo em Inglês | MEDLINE | ID: mdl-30772041

RESUMO

OBJECTIVES: Beginning in 2002, all 14 Massachusetts nonfederal cardiac surgery programs submitted Society of Thoracic Surgeons (STS) National Database data to the Massachusetts Data Analysis Center for mandatory state-based analysis and reporting, and to STS for nationally benchmarked analyses. We sought to determine whether longitudinal prevalences and trends in risk factors and observed and expected mortality differed between Massachusetts and the nation. METHODS: We analyzed 2003 to 2014 expected (STS predicted risk of operative [in-hospital + 30-day] mortality), observed, and risk-standardized isolated coronary artery bypass graft mortality using Massachusetts STS data (N = 39,400 cases) and national STS data (N = 1,815,234 cases). Analyses included percentage shares of total Massachusetts coronary artery bypass graft volume and expected mortality rates of 2 hospitals before and after outlier designation. RESULTS: Massachusetts patients had significantly higher odds of diabetes, peripheral vascular disease, low ejection fraction, and age ≥75 years relative to national data and lower odds of shock (odds ratio, 0.66; 99% confidence interval, 0.53-0.83), emergency (odds ratio, 0.57, 99% confidence interval, 0.52-0.61), reoperation, chronic lung disease, dialysis, obesity, and female sex. STS predicted risk of operative [in-hospital + 30-day] mortality for Massachusetts patients was higher than national rates during 2003 to 2007 (P < .001) and no different during 2008 to 2014 (P = .135). Adjusting for STS predicted risk of operative [in-hospital + 30-day] mortality, Massachusetts patients had significantly lower odds (odds ratio, 0.79; 99% confidence interval, 0.66-0.96) of 30-day mortality relative to national data. Outlier programs experienced inconsistent, transient influences on expected mortality and their percentage shares of Massachusetts coronary artery bypass graft cases. CONCLUSIONS: During 12 years of mandatory public reporting, Massachusetts risk-standardized coronary artery bypass graft mortality was consistently and significantly lower than national rates, expected rates were comparable or higher, and evidence for risk aversion was conflicting and inconclusive.


Assuntos
Ponte de Artéria Coronária/estatística & dados numéricos , Notificação de Abuso , Idoso , Procedimentos Cirúrgicos Cardíacos/efeitos adversos , Procedimentos Cirúrgicos Cardíacos/mortalidade , Procedimentos Cirúrgicos Cardíacos/estatística & dados numéricos , Ponte de Artéria Coronária/efeitos adversos , Ponte de Artéria Coronária/mortalidade , Bases de Dados como Assunto , Feminino , Mortalidade Hospitalar , Humanos , Masculino , Massachusetts/epidemiologia , Pessoa de Meia-Idade
14.
Circ Cardiovasc Qual Outcomes ; 11(12): e004763, 2018 12.
Artigo em Inglês | MEDLINE | ID: mdl-30562069

RESUMO

BACKGROUND: Little is known about real-world facility-level preferences for cardiac resynchronization therapy devices with (CRT-D) and without (CRT-P) defibrillator backup. We quantify this variation at the facility level and exploit this variation to compare outcomes of patients receiving these 2 devices. METHODS AND RESULTS: Claims data from fee-for-service Medicare beneficiaries were used to identify new CRT-P and CRT-D implants, 2006 to 2012. We modeled factors associated with receipt of each device, and compared mortality, hospitalizations, and reoperations for patients receiving each using both logistic regression and instrumental variable analysis to account for confounding. Among 71 459 device recipients (CRT-P, 11 925; CRT-D, 59 534; 31% women), CRT-P recipients were older, more likely to be women, and had more comorbidities. Variation in device selection among facilities was substantial: After adjustment for patient characteristics, the odds of receiving a CRT-P (versus CRT-D) device were 7.6× higher for a patient treated at a facility in the highest CRT-P use quartile versus a facility in the lowest CRT-P use quartile. Logistic modeling suggested a survival advantage for CRT-D devices but with falsification end points indicating residual confounding. By contrast, in the instrumental variable analysis using facility variability as the proposed instrument, clinical characteristics and falsification end points were well balanced, and 1-year mortality in patients who received CRT-P versus CRT-D implants did not differ, while CRT-P patients had a lower probability of hospitalizations and reoperations in the year following implant. CONCLUSIONS: CRT-P versus CRT-D selection varies substantially among facilities, adjusted for clinical factors. After instrumental variable adjustment for clinical covariates and facility preference, survival was no different between the devices. Therefore, CRT-P may be preferred for Medicare beneficiaries considering new CRT implantation.


Assuntos
Dispositivos de Terapia de Ressincronização Cardíaca/tendências , Terapia de Ressincronização Cardíaca/tendências , Desfibriladores Implantáveis/tendências , Cardioversão Elétrica/tendências , Disparidades em Assistência à Saúde/tendências , Insuficiência Cardíaca/terapia , Padrões de Prática Médica/tendências , Demandas Administrativas em Assistência à Saúde , Idoso , Idoso de 80 Anos ou mais , Terapia de Ressincronização Cardíaca/efeitos adversos , Terapia de Ressincronização Cardíaca/mortalidade , Tomada de Decisão Clínica , Bases de Dados Factuais , Cardioversão Elétrica/efeitos adversos , Cardioversão Elétrica/instrumentação , Cardioversão Elétrica/mortalidade , Feminino , Insuficiência Cardíaca/diagnóstico , Insuficiência Cardíaca/mortalidade , Insuficiência Cardíaca/fisiopatologia , Humanos , Masculino , Medicare , Seleção de Pacientes , Fatores de Risco , Fatores de Tempo , Resultado do Tratamento , Estados Unidos
16.
Biom J ; 60(4): 721-733, 2018 07.
Artigo em Inglês | MEDLINE | ID: mdl-29682785

RESUMO

High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem.


Assuntos
Biometria/métodos , Vasos Coronários/cirurgia , Stents Farmacológicos , Metais , Pontuação de Propensão , Teorema de Bayes , Humanos , Modelos Estatísticos
18.
Health Aff (Millwood) ; 37(1): 104-110, 2018 01.
Artigo em Inglês | MEDLINE | ID: mdl-29309217

RESUMO

There are wide disparities in health across the US population. The identification of geographic health priority areas for Medicare could inform efforts to eliminate health disparities and improve health care. In a sample of 3,282 counties with more than 73 million unique Medicare beneficiaries in the period 1999-2014, we identified geographical areas-"hot spots"-with persistently higher adjusted mortality rates for older adults compared with the rest of the country. During the study period, the risk-standardized mortality rates decreased from 5.52 percent to 4.61 percent (a 0.91-percentage-point change) for the priority areas and from 5.16 percent to 4.11 percent (a 1.05-percentage-point change) for other areas. Faced with decisions surrounding allocation of scarce resources and marked geographic disparities, the identification and prioritization of hot spots may be one way to eliminate disparities and improve health care.


Assuntos
Geografia Médica/estatística & dados numéricos , Prioridades em Saúde/estatística & dados numéricos , Medicare/estatística & dados numéricos , Mortalidade , Idoso , Idoso de 80 Anos ou mais , Acesso aos Serviços de Saúde , Disparidades em Assistência à Saúde , Humanos , Estados Unidos
19.
Health Serv Res ; 53(2): 608-631, 2018 04.
Artigo em Inglês | MEDLINE | ID: mdl-28994106

RESUMO

OBJECTIVES: To investigate the association between hospital safety culture and 30-day risk-adjusted mortality for Medicare patients with acute myocardial infarction (AMI) in a large, diverse hospital cohort. SUBJECTS: The final analytic cohort consisted of 19,357 Medicare AMI discharges (MedPAR data) linked to 257 AHRQ Hospital Survey on Patient Safety Culture surveys from 171 hospitals between 2008 and 2013. STUDY DESIGN: Observational, cross-sectional study using hierarchical logistic models to estimate the association between hospital safety scores and 30-day risk-adjusted patient mortality. Odds ratios of 30-day, all-cause mortality, adjusting for patient covariates, hospital characteristics (size and teaching status), and several different types of safety culture scores (composite, average, and overall) were determined. PRINCIPAL FINDINGS: No significant association was found between any measure of hospital safety culture and adjusted AMI mortality. CONCLUSIONS: In a large cross-sectional study from a diverse hospital cohort, AHRQ safety culture scores were not associated with AMI mortality. Our study adds to a growing body of investigations that have failed to conclusively demonstrate a safety culture-outcome association in health care, at least with widely used national survey instruments.


Assuntos
Administração Hospitalar/estatística & dados numéricos , Medicare/estatística & dados numéricos , Infarto do Miocárdio/mortalidade , Cultura Organizacional , Gestão da Segurança/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Feminino , Número de Leitos em Hospital/estatística & dados numéricos , Mortalidade Hospitalar , Hospitais de Ensino/estatística & dados numéricos , Humanos , Modelos Logísticos , Masculino , Segurança do Paciente , Características de Residência/estatística & dados numéricos , Medição de Risco , Estados Unidos
20.
JAMA Netw Open ; 1(5): e182044, 2018 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-30646146

RESUMO

Importance: Although studies have described differences in hospital outcomes by patient race and socioeconomic status, it is not clear whether such disparities are driven by hospitals themselves or by broader systemic effects. Objective: To determine patterns of racial and socioeconomic disparities in outcomes within and between hospitals for patients with acute myocardial infarction, heart failure, and pneumonia. Design, Setting, and Participants: Retrospective cohort study initiated before February 2013, with additional analyses conducted during the peer-review process. Hospitals in the United States treating at least 25 Medicare fee-for-service beneficiaries aged 65 years or older in each race (ie, black and white) and neighborhood income level (ie, higher income and lower income) for acute myocardial infarction, heart failure, and pneumonia between 2009 and 2011 were included. Main Outcomes and Measures: For within-hospital analyses, risk-standardized mortality rates and risk-standardized readmission rates for race and neighborhood income subgroups were calculated at each hospital. The corresponding ratios using intraclass correlation coefficients were then compared. For between-hospital analyses, risk-standardized rates were assessed according to hospitals' proportion of patients in each subgroup. These analyses were performed for each of the 12 analysis cohorts reflecting the unique combinations of outcomes (mortality and readmission), demographics (race and neighborhood income), and conditions (acute myocardial infarction, heart failure, and pneumonia). Results: Between 74% (3545 of 4810) and 91% (4136 of 4554) of US hospitals lacked sufficient racial and socioeconomic diversity to be included in this analysis, with the number of hospitals eligible for analysis varying among cohorts. The 12 analysis cohorts ranged in size from 418 to 1265 hospitals and from 144 417 to 703 324 patients. Within included hospitals, risk-standardized mortality rates tended to be lower among black patients (mean [SD] difference between risk-standardized mortality rates in black patients compared with white patients for acute myocardial infarction, -0.57 [1.1] [P = .47]; for heart failure, -4.7 [1.3] [P < .001]; and for pneumonia, -1.0 [2.0] [P = .05]). However, risk-standardized readmission rates among black patients were higher (mean [SD] difference between risk-standardized readmission rates in black patients compared with white patients for acute myocardial infarction, 4.3 [1.4] [P < .001]; for heart failure, 2.8 [1.8] [P < .001], and for pneumonia, 3.7 [1.3] [P < .001]). Intraclass correlation coefficients ranged from 0.68 to 0.79, indicating that hospitals generally delivered consistent quality to patients of differing races. While the coefficients in the neighborhood income analysis were slightly lower (0.46-0.60), indicating some heterogeneity in within-hospital performance, differences in mortality rates and readmission rates between the 2 neighborhood income groups were small. There were no strong, consistent associations between risk-standardized outcomes for white or higher-income neighborhood patients and hospitals' proportion of black or lower-income neighborhood patients. Conclusions and Relevance: Hospital performance according to race and socioeconomic status was generally consistent within and between hospitals, even as there were overall differences in outcomes by race and neighborhood income. This finding indicates that disparities are likely to be systemic, rather than localized to particular hospitals.


Assuntos
Disparidades nos Níveis de Saúde , Hospitais/estatística & dados numéricos , Classe Social , Grupo com Ancestrais do Continente Africano/etnologia , Grupo com Ancestrais do Continente Africano/estatística & dados numéricos , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Grupos de Populações Continentais/estatística & dados numéricos , Grupo com Ancestrais do Continente Europeu/etnologia , Grupo com Ancestrais do Continente Europeu/estatística & dados numéricos , Planos de Pagamento por Serviço Prestado/estatística & dados numéricos , Feminino , Insuficiência Cardíaca/epidemiologia , Insuficiência Cardíaca/etnologia , Hospitalização/estatística & dados numéricos , Humanos , Masculino , Medicare/estatística & dados numéricos , Pessoa de Meia-Idade , Infarto do Miocárdio/epidemiologia , Infarto do Miocárdio/etnologia , Pneumonia/epidemiologia , Pneumonia/etnologia , Estudos Retrospectivos , Estados Unidos
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