Dataset Information

Risk-Adjusted In-Hospital Mortality Models for Congestive Heart Failure and Acute Myocardial Infarction: Value of Clinical Laboratory Data and Race/Ethnicity.

ABSTRACT:

Objective

To examine the impact of key laboratory and race/ethnicity data on the prediction of in-hospital mortality for congestive heart failure (CHF) and acute myocardial infarction (AMI).

Data sources

Hawaii adult hospitalizations database between 2009 and 2011, linked to laboratory database.

Study design

Cross-sectional design was employed to develop risk-adjusted in-hospital mortality models among patients with CHF (n = 5,718) and AMI (n = 5,703).

Data collection/extraction methods

Results of 25 selected laboratory tests were requested from hospitals and laboratories across the state and mapped according to Logical Observation Identifiers Names and Codes standards. The laboratory data were linked to administrative data for each discharge of interest from an all-payer database, and a Master Patient Identifier was used to link patient-level encounter data across hospitals statewide.

Principal findings

Adding a simple three-level summary measure based on the number of abnormal laboratory data observed to hospital administrative claims data significantly improved the model prediction for inpatient mortality compared with a baseline risk model using administrative data that adjusted only for age, gender, and risk of mortality (determined using 3M's All Patient Refined Diagnosis Related Groups classification). The addition of race/ethnicity also improved the model.

Conclusions

The results of this study support the incorporation of a simple summary measure of laboratory data and race/ethnicity information to improve predictions of in-hospital mortality from CHF and AMI. Laboratory data provide objective evidence of a patient's condition and therefore are accurate determinants of a patient's risk of mortality. Adding race/ethnicity information helps further explain the differences in in-hospital mortality.

SUBMITTER: Lim E

PROVIDER: S-EPMC4545336 | biostudies-literature | 2015 Aug

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Risk-Adjusted In-Hospital Mortality Models for Congestive Heart Failure and Acute Myocardial Infarction: Value of Clinical Laboratory Data and Race/Ethnicity.

Lim Eunjung E Cheng Yongjun Y Reuschel Christine C Mbowe Omar O Ahn Hyeong Jun HJ Juarez Deborah T DT Miyamura Jill J Seto Todd B TB Chen John J JJ

Health services research 20150615

<h4>Objective</h4>To examine the impact of key laboratory and race/ethnicity data on the prediction of in-hospital mortality for congestive heart failure (CHF) and acute myocardial infarction (AMI).<h4>Data sources</h4>Hawaii adult hospitalizations database between 2009 and 2011, linked to laboratory database.<h4>Study design</h4>Cross-sectional design was employed to develop risk-adjusted in-hospital mortality models among patients with CHF (n = 5,718) and AMI (n = 5,703).<h4>Data collection/ex ...[more]

PMID: 26073945

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Project description:IntroductionMeasurement of mortality in patients with acute myocardial infarction (AMI), congestive heart failure (CHF) and pneumonia (PN) is a high priority since these are common reasons for hospitalization. However, mortality in patients with inflammatory bowel disease (IBD) that are hospitalized for these common medical conditions is unknown.MethodsA retrospective review of the 2005-2011 National Inpatient Sample (NIS), (approximately a 20% sample of discharges from community hospitals) was performed. A dataset for all patients with ICD-9-CM codes for primary diagnosis of acute myocardial infarction, pneumonia or congestive heart failure with a co-diagnosis of IBD, Crohn's disease (CD) or ulcerative colitis (UC). 1:3 propensity score matching between patients with co-diagnosed disease vs. controls was performed. Continuous variables were compared between IBD and controls. Categorical variables were reported as frequency (percentage) and analyzed by Chi-square tests or Fisher's exact test for co-diagnosed disease vs. control comparisons. Propensity scores were computed through multivariable logistic regression accounting for demographic and hospital factors. In-hospital mortality between the groups was compared.ResultsPatients with IBD, CD and UC had improved survival after AMI compared to controls. 94/2280 (4.1%) of patients with IBD and AMI died, compared to 251/5460 (5.5%) of controls, p = 0.01. This represents a 25% improved survival in IBD patients that were hospitalized with AMI. There was a 34% improved survival in patients with CD and AMI. There was a trend toward worsening survival in patients with IBD and CHF. Patients with CD and PN had improved survival compared to controls. 87/3362 (2.59%) patients with CD and PN died, compared to 428/10076 (4.25%) of controls, p < .0001. This represents a 39% improved survival in patients with CD that are hospitalized for PN.ConclusionIBD confers a survival benefit for patients hospitalized with AMI. A diagnosis of CD benefits survival in patients that are hospitalized with PN.

Project description:Background Prior studies have reported disparities by race in the management of acute myocardial infarction (MI), with many studies having limited covariates or now dated. We examined racial and ethnic differences in the management of MI, specifically non-ST-segment-elevation MI (NSTEMI), in a large, socially diverse cohort of insured patients. We hypothesized that the racial and ethnic disparities in the receipt of coronary angiography or percutaneous coronary intervention would persist in contemporary data. Methods and Results We identified individuals presenting with incident, type I NSTEMI from 2017 to 2019 captured by a health claims database. Race and ethnicity were categorized by the database as Asian, Black, Hispanic, or White. Covariates included demographics (age, sex, race, and ethnicity); Elixhauser variables, including cardiovascular risk factors and other comorbid conditions; and social factors of estimated annual household income and educational attainment. We examined rates of coronary angiography and percutaneous coronary intervention by race and ethnicity and income categories and in multivariable-adjusted models. We identified 87 094 individuals (age 73.8±11.6 years; 55.6% male; 2.6% Asian, 13.4% Black, 11.2% Hispanic, 72.7% White) with incident NSTEMI events from 2017 to 2019. Individuals of Black race were less likely to undergo coronary angiography (odds ratio [OR], 0.93; [95% CI, 0.89-0.98]) and percutaneous coronary intervention (OR, 0.86; [95% CI, 0.81-0.90]) than those of White race. Hispanic individuals were less likely (OR, 0.88; [95% CI, 0.84-0.93]) to undergo coronary angiography and percutaneous coronary intervention (OR, 0.85; [95% CI, 0.81-0.89]) than those of White race. Higher annual household income attenuated differences in the receipt of coronary angiography across all racial and ethnic groups. Conclusions We identified significant racial and ethnic differences in the management of individuals presenting with NSTEMI that were marginally attenuated by higher household income. Our findings suggest continued evidence of health inequities in contemporary NSTEMI treatment.

Project description:ImportanceBreast cancer (BC) is the second leading cause of cancer death in women, and there is a substantial disparity in BC mortality by race, especially for early-onset BC in Black women. Many guidelines recommend starting BC screening from age 50 years; however, the current one-size-fits-all policy to start screening all women from a certain age may not be fair, equitable, or optimal.ObjectiveTo provide race and ethnicity-adapted starting ages of BC screening based on data on current racial and ethnic disparities in BC mortality.Design, setting, and participantsThis nationwide population-based cross-sectional study was conducted using data on BC mortality in female patients in the US who died of BC in 2011 to 2020.ExposuresProxy-reported race and ethnicity information was used. The risk-adapted starting age of BC screening by race and ethnicity was measured based on 10-year cumulative risk of BC-specific death. Age-specific 10-year cumulative risk was calculated based on age group-specific mortality data without modeling or adjustment.Main outcomes and measuresDisease-specific mortality due to invasive BC in female patients.ResultsThere were BC-specific deaths among 415 277 female patients (1880 American Indian or Alaska Native [0.5%], 12 086 Asian or Pacific Islander [2.9%], 62 695 Black [15.1%], 28 747 Hispanic [6.9%], and 309 869 White [74.6%]; 115 214 patients died before age 60 years [27.7%]) of any age in the US in 2011 to 2020. BC mortality per 100 000 person-years for ages 40 to 49 years was 27 deaths in Black females, 15 deaths in White females, and 11 deaths in American Indian or Alaska Native, Hispanic, and Asian or Pacific Islander females. When BC screening was recommended to start at age 50 years for all females with a 10-year cumulative risk of BC death of 0.329%, Black females reached this risk threshold level 8 years earlier, at age 42 years, whereas White females reached it at age 51 years, American Indian or Alaska Native and Hispanic females at age 57 years, and Asian or Pacific Islander females 11 years later, at age 61 years. Race and ethnicity-adapted starting ages for Black females were 6 years earlier for mass screening at age 40 years and 7 years earlier for mass screening at age 45 years.Conclusions and relevanceThis study provides evidence-based race-adapted starting ages for BC screening. These findings suggest that health policy makers may consider a risk-adapted approach to BC screening in which individuals who are at high risk are screened earlier to address mortality due to early-onset BC before the recommended age of mass screening.

Dataset Information

Risk-Adjusted In-Hospital Mortality Models for Congestive Heart Failure and Acute Myocardial Infarction: Value of Clinical Laboratory Data and Race/Ethnicity.

Objective

Data sources

Study design

Data collection/extraction methods

Principal findings

Conclusions

Publications

Risk-Adjusted In-Hospital Mortality Models for Congestive Heart Failure and Acute Myocardial Infarction: Value of Clinical Laboratory Data and Race/Ethnicity.

Similar Datasets

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