Dataset Information

An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.

ABSTRACT:

Background

Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia.

Methodology/principal findings

Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older with a principal discharge diagnosis of pneumonia. Candidate risk-adjustment variables included patient demographics, administrative diagnosis codes from the index hospitalization, and all inpatient and outpatient encounters from the year before admission. The model derivation cohort included 224,608 pneumonia cases admitted to 4,664 hospitals in 2000, and validation cohorts included cases from each of years 1998-2003. We compared model-derived state-level standardized mortality estimates with medical record-derived state-level standardized mortality estimates using data from the Medicare National Pneumonia Project on 50,858 patients hospitalized from 1998-2001. The final model included 31 variables and had an area under the Receiver Operating Characteristic curve of 0.72. In each administrative claims validation cohort, model fit was similar to the derivation cohort. The distribution of standardized mortality rates among hospitals ranged from 13.0% to 23.7%, with 25(th), 50(th), and 75(th) percentiles of 16.5%, 17.4%, and 18.3%, respectively. Comparing model-derived risk-standardized state mortality rates with medical record-derived estimates, the correlation coefficient was 0.86 (Standard Error?=?0.032).

Conclusions/significance

An administrative claims-based model for profiling hospitals for pneumonia mortality performs consistently over several years and produces hospital estimates close to those using a medical record model.

SUBMITTER: Bratzler DW

PROVIDER: S-EPMC3075250 | biostudies-literature | 2011 Apr

REPOSITORIES: biostudies-literature

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Publications

An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.

Bratzler Dale W DW Normand Sharon-Lise T SL Wang Yun Y O'Donnell Walter J WJ Metersky Mark M Han Lein F LF Rapp Michael T MT Krumholz Harlan M HM

PloS one 20110412 4

<h4>Background</h4>Outcome measures for patients hospitalized with pneumonia may complement process measures in characterizing quality of care. We sought to develop and validate a hierarchical regression model using Medicare claims data that produces hospital-level, risk-standardized 30-day mortality rates useful for public reporting for patients hospitalized with pneumonia.<h4>Methodology/principal findings</h4>Retrospective study of fee-for-service Medicare beneficiaries age 66 years and older ...[more]

PMID: 21532758

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Project description:BackgroundGiven the increased attention to sepsis at the population level there is a need to assess hospital performance in the care of sepsis patients using widely-available administrative data. The goal of this study was to develop an administrative risk-adjustment model suitable for profiling hospitals on their 30-day mortality rates for patients with sepsis.MethodsWe conducted a retrospective cohort study using hospital discharge data from general acute care hospitals in Pennsylvania in 2012 and 2013. We identified adult patients with sepsis as determined by validated diagnosis and procedure codes. We developed an administrative risk-adjustment model in 2012 data. We then validated this model in two ways: by examining the stability of performance assessments over time between 2012 and 2013, and by examining the stability of performance assessments in 2012 after the addition of laboratory variables measured on day one of hospital admission.ResultsIn 2012 there were 115,213 sepsis encounters in 152 hospitals. The overall unadjusted mortality rate was 18.5%. The final risk-adjustment model had good discrimination (C-statistic = 0.78) and calibration (slope and intercept of the calibration curve = 0.960 and 0.007, respectively). Based on this model, hospital-specific risk-standardized mortality rates ranged from 12.2 to 24.5%. Comparing performance assessments between years, correlation in risk-adjusted mortality rates was good (Pearson's correlation = 0.53) and only 19.7% of hospitals changed by more than one quintile in performance rankings. Comparing performance assessments after the addition of laboratory variables, correlation in risk-adjusted mortality rates was excellent (Pearson's correlation = 0.93) and only 2.6% of hospitals changed by more than one quintile in performance rankings.ConclusionsA novel claims-based risk-adjustment model demonstrated wide variation in risk-standardized 30-day sepsis mortality rates across hospitals. Individual hospitals' performance rankings were stable across years and after the addition of laboratory data. This model provides a robust way to rank hospitals on sepsis mortality while adjusting for patient risk.

Project description:BackgroundLowering hospital readmission rates has become a primary target for the Centers for Medicare & Medicaid Services, but studies of the relationship between adherence to the recommended hospital care processes and readmission rates have provided inconsistent and inconclusive results.ObjectiveTo examine the association between hospital performance on Medicare's Hospital Compare process quality measures and 30-day readmission rates for patients with acute myocardial infarction (AMI), heart failure and pneumonia, and for those undergoing major surgery.Design, setting and participantsWe assessed hospital performance on process measures using the 2007 Hospital Inpatient Quality Reporting Program. The process measures for each condition were aggregated in two separate measures: Overall Measure (OM) and Appropriate Care Measure (ACM) scores. Readmission rates were calculated using Medicare claims.Main outcome measureRisk-standardized 30-day all-cause readmission rate was calculated as the ratio of predicted to expected rate standardized by the overall mean readmission rate. We calculated predicted readmission rate using hierarchical generalized linear models and adjusting for patient-level factors.ResultsAmong patients aged ≥ 66 years, the median OM score ranged from 79.4 % for abdominal surgery to 95.7 % for AMI, and the median ACM scores ranged from 45.8 % for abdominal surgery to 87.9 % for AMI. We observed a statistically significant, but weak, correlation between performance scores and readmission rates for pneumonia (correlation coefficient R = 0.07), AMI (R = 0.10), and orthopedic surgery (R = 0.06). The difference in the mean readmission rate between hospitals in the 1st and 4th quartiles of process measure performance was statistically significant only for AMI (0.25 percentage points) and pneumonia (0.31 percentage points). Performance on process measures explained less than 1 % of hospital-level variation in readmission rates.ConclusionsHospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.

Project description:Risk-standardized 30-day mortality and hospital readmission rates for pneumonia are increasingly being tied to hospital reimbursement to incentivize the delivery of high-quality care. Such measures may be susceptible to gaming by recoding patients with pneumonia to a primary diagnosis of sepsis or respiratory failure. We sought to determine the degree to which hospitals can game mortality or readmission measures and change their rankings by recoding patients with pneumonia.Simulated experimental study of 2,906 U.S. acute care hospitals with at least 25 admissions for pneumonia using 2009 Medicare data.Elderly (age ? 65 yr) Medicare fee-for-service beneficiaries hospitalized with pneumonia. Patients eligible for recoding to sepsis or respiratory failure were those with a principal International Classification of Diseases, 9th Edition, Clinical Modification, discharge code for pneumonia and secondary codes for respiratory failure or acute organ dysfunction.None.We measured the number of hospitals that improved their pneumonia mortality or readmission rates after recoding eligible patients. When a sample of 100 hospitals with pneumonia mortality rates above the 50th percentile recoded all eligible patients to sepsis or respiratory failure, 90 hospitals (95% CI, 84-95) improved their mortality rate (mean improvement, 1.09%; 95% CI, 0.94-1.28%) and 41 hospitals dropped below the 50th percentile (95% CI, 33-52). When a sample of 100 hospitals with pneumonia readmission rates above the 50th percentile recoded all eligible patients, 66 hospitals (95% CI, 54-75) improved their readmission rate (mean improvement, 0.34%; 95% CI, 0.19-0.45%) and 15 hospitals (95% CI, 9-22) dropped below the 50th percentile.Hospitals can improve apparent pneumonia mortality and readmission rates by recoding pneumonia patients. Centers for Medicare and Medicaid Services should consider changes to their methods used to calculate hospital-level pneumonia outcome measures to make them less susceptible to gaming.

Project description:ImportancePneumonia often leads to functional decline during and after hospitalization and is a leading cause of hospital readmissions. Physical and occupational therapists help improve functional mobility and may be of help in this population.ObjectiveTo evaluate whether use of physical and occupational therapy in the acute care hospital is associated with 30-day hospital readmission risk or death.Design, setting, and participantsThis cohort study included the electronic health records and administrative claims data of 30 746 adults discharged alive with a primary or secondary diagnosis of pneumonia or influenza-related conditions from January 1, 2016, to March 30, 2018. Patients were treated at 12 acute care hospitals in a large health care system in western Pennsylvania. Data for this study were analyzed from September 2019 through March 2020.ExposuresNumber of physical and occupational therapy visits during the acute care stay categorized as none, low (1-3), medium (4-6), or high (>6).Main outcomes and measuresOutcomes were 30-day hospital readmission or death. Generalized linear mixed models were estimated to examine the association of therapy use and outcomes, controlling for patient demographic and clinical characteristics. Subgroup analyses were conducted for patients older than 65 years, for patients with low functional mobility scores, for patients discharged to the community, and for patients discharged to a post-acute care facility (ie, skilled nursing or inpatient rehabilitation facility).ResultsOf 30 746 patients, 15 507 (50.4%) were men, 26 198 (85.2%) were White individuals, and the mean (SD) age was 67.1 (17.4) years. The 30-day readmission rate was 18.4% (5645 patients), the 30-day death rate was 3.7% (1146 patients), and the rate of either outcome was 19.7% (6066 patients). Relative to no therapy visits, the risk of 30-day readmission or death decreased as therapy visits increased (1-3 visits: odds ratio, 0.98; 95% CI, 0.89-1.08; 4-6 visits: odds ratio, 0.89; 95% CI, 0.79-1.01; >6 visits: odds ratio, 0.86; 95% CI, 0.75-0.98). The association was stronger in the subgroup with low functional mobility and in individuals discharged to a community setting.Conclusions and relevanceIn this study, the number of therapy visits received was inversely associated with the risk of readmission or death. The association was stronger in the subgroups of patients with greater mobility limitations and those discharged to the community.

Project description:BackgroundHospital-acquired pneumonia (HAP) is the most common hospital-acquired infection in China with substantial morbidity and mortality. But no specific risk assessment model has been well validated in patients with HAP. The aim of this study was to investigate the published risk assessment models that could potentially be used to predict 30-day mortality in HAP patients in non-surgical departments.MethodsThis study was a single-center, retrospective study. In total, 223 patients diagnosed with HAP from 2012 to 2017 were included in this study. Clinical and laboratory data during the initial 24 hours after HAP diagnosis were collected to calculate the pneumonia severity index (PSI); consciousness, urea nitrogen, respiratory rate, blood pressure, and age ≥65 years (CURB-65); Acute Physiology and Chronic Health Evaluation II (APACHE II); Sequential Organ Failure Assessment (SOFA); and Quick Sequential Organ Failure Assessment (qSOFA) scores. The discriminatory power was tested by constructing receiver operating characteristic (ROC) curves, and the areas under the curve (AUCs) were calculated.ResultsThe all-cause 30-day mortality rate was 18.4% (41/223). The PSI, CURB-65, SOFA, APACHE II, and qSOFA scores were significantly higher in non-survivors than in survivors (all P < 0.001). The discriminatory abilities of the APACHE II and SOFA scores were better than those of the CURB-65 and qSOFA scores (ROC AUC: APACHE II vs. CURB-65, 0.863 vs. 0.744, Z = 3.055, P = 0.002; APACHE II vs. qSOFA, 0.863 vs. 0.767, Z = 3.017, P = 0.003; SOFA vs. CURB-65, 0.856 vs. 0.744, Z = 2.589, P = 0.010; SOFA vs. qSOFA, 0.856 vs. 0.767, Z = 2.170, P = 0.030). The cut-off values we defined for the SOFA, APACHE II, and qSOFA scores were 4, 14, and 1.ConclusionsThese results suggest that the APACHE II and SOFA scores determined during the initial 24 h after HAP diagnosis may be useful for the prediction of 30-day mortality in HAP patients in non-surgical departments. The qSOFA score may be a simple tool that can be used to quickly identify severe infections.

Project description:BackgroundEpidemiological studies have demonstrated an association between red blood cell distribution width (RDW) and the prognosis of pneumonia-associated diseases. However, prognostic value of RDW in patients with ventilator-associated pneumonia (VAP) has yet to be investigated. This study aimed to explore the association between RDW and in-hospital mortality in VAP patients and explore predictive value of RDW for VAP patients.MethodsThis retrospective cohort study included 1,543 VAP patients from the Medical Information Mart for Intensive Care IV database 2008-2019. The primary outcome was considered to 30-day in-hospital mortality of VAP patients in this study. Non-high RDW level group was defined as <15 %, and high RDW level group as ≥15%. The possible confounding factors were screened by least absolute shrinkage and selection operator regression. Univariate and multivariate COX regression analyses were used for the assessment on the association of RDW and 30-day in-hospital mortality in VAP patients. We also performed subgroup analyses. Furthermore, a comparative analysis of RDW and sequential organ failure assessment (SOFA) score and simplified acute physiology score II (SAPS II) were performed by receiver operating characteristic (ROC) curves.ResultsThe 30-day in-hospital mortality of VAP patients was approximately 19.05%. After adjusting all confounding factors, high RDW was associated with 30-day in-hospital mortality among VAP patients by using non-high RDW as the reference [hazard ratio (HR) =1.29, 95% confidence interval (CI): 1.01-1.63]. Additionally, the relationship was also robust in several populations, such as patients were younger than 60 years, or had not a history of congestive heart failure, or had a history of sepsis, or had not received renal replacement therapy, or had a duration of mechanical ventilation for more than 7 days. The result of ROC indicated that RDW had a better prognostic value in predicting 30-day in-hospital mortality for VAP patients than SOFA score and SAPS II score.ConclusionHigh RDW level is associated with an increased 30-day in-hospital mortality. The RDW is a promising biomarker in predicting 30-day in-hospital mortality for patients admitted to the ICU, regardless of VAP.

Dataset Information

An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.

Background

Methodology/principal findings

Conclusions/significance

Publications

An administrative claims model for profiling hospital 30-day mortality rates for pneumonia patients.

Similar Datasets

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