Dataset Information

The association of lacking insurance with outcomes of severe sepsis: retrospective analysis of an administrative database*.

ABSTRACT: Patients with severe sepsis have high mortality that is improved by timely, often expensive, treatments. Patients without insurance are more likely to delay seeking care; they may also receive less intense care.We performed a retrospective analysis of administrative database-Healthcare Costs and Utilization Project's Nationwide Inpatient Sample-to test whether mortality is more likely among uninsured patients hospitalized for severe sepsis.None.We used International Classification of Diseases-9th Revision, Clinical Modification, codes indicating sepsis and organ system failure to identify hospitalizations for severe sepsis among patients aged 18-64 between 2000 and 2008. We excluded patients with end-stage renal disease or solid organ transplants because very few are uninsured. We performed multivariate logistic regression modeling to examine the association of insurance status and in-hospital mortality, adjusted for patient and hospital characteristics. We performed subgroup analysis to examine whether the impact of insurance status varied by geographical region; by patient age, sex, or race; or by hospital characteristics such as teaching status, size, or ownership. We used similar methods to examine the impact of insurance status on the use of certain procedures, length of stay, and discharge destination.There were 1,600,269 discharges with severe sepsis from 2000 through 2008 in the age group 18-64 years. Uninsured people, who accounted for 7.5% of admissions with severe sepsis, had higher adjusted odds of mortality (odds ratio, 1.43; 95% CI, 1.37-1.47) than privately insured people. The higher mortality in uninsured was present in all subgroups and was similar in each year from 2000 to 2008. After adjustment, uninsured individuals had a slightly shorter length of stay than insured people and were less likely to receive five of the six interventions we examined. They were also less likely to be discharged to skilled nursing facilities or with home healthcare after discharge.Uninsured are more likely to die following admission for severe sepsis than patients with insurance, even after adjusting for potential confounders. This was not due to a hospital effect or demographic or clinical factors available in our administrative database. Further research should examine the mechanisms that lead to this association.

SUBMITTER: Kumar G

PROVIDER: S-EPMC4990450 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature

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The association of lacking insurance with outcomes of severe sepsis: retrospective analysis of an administrative database*.

Kumar Gagan G Taneja Amit A Majumdar Tilottama T Jacobs Elizabeth R ER Whittle Jeff J Nanchal Rahul R

Critical care medicine 20140301 3

<h4>Objective</h4>Patients with severe sepsis have high mortality that is improved by timely, often expensive, treatments. Patients without insurance are more likely to delay seeking care; they may also receive less intense care.<h4>Design</h4>We performed a retrospective analysis of administrative database-Healthcare Costs and Utilization Project's Nationwide Inpatient Sample-to test whether mortality is more likely among uninsured patients hospitalized for severe sepsis.<h4>Patients</h4>None.< ...[more]

PMID: 24152590

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Project description:BackgroundAlthough it has been reported that high hospital patient volume results in survival and cost benefits for several diseases, it is uncertain whether this association is applicable in burn care.MethodsWe conducted a retrospective observational study on severe burn patients, defined by a burn index ≥ 10, using 2010-2015 data from a Japanese national administrative claim database. A generalized additive mixed-effect model (GAMM) was used to evaluate the nonlinear associations between patient volume and the outcomes (in-hospital mortality, healthcare costs per admission, and hospital-free days at 90 days). Generalized linear mixed-effect regression models (GLMMs) in which patient volume was incorporated as a continuous or categorical variable (≤ 5 or > 5) were also performed. Patient severity was adjusted using the prognostic burn index (PBI) or the risk adjustment model developed in this study, simultaneously controlling for hospital-level clustering. Sensitivity analyses evaluating patients who were directly transported, those with PBI ≤ 120 and those excluding patients who died within 2 days of admission, were also performed.ResultsWe analyzed 5250 eligible severe burn patients from 737 hospitals. The PBI and the developed risk adjustment model had good discriminative ability with areas under the receiver operating characteristic curves of 0.86 and 0.89, respectively. The GAMM plots showed that in-hospital mortality and healthcare costs increased according to the increase in patient volumes; then, they reached a plateau. Fewer hospital-free days were observed in the higher volume hospitals. The GLMM model showed that patient volume (incorporated as a continuous variable) was significantly associated with increased in-hospital mortality (adjusted odds ratio [95% confidence interval (CI)] = 1.14 [1.09-1.19]), high healthcare costs (adjusted difference [95% CI] = $4876 [4436-5316]), and few hospital-free days (adjusted difference [95% CI] = - 3.1 days [- 3.4 to - 2.8]). Similar trends were observed in the analyses in which patient volume was incorporated as a categorical variable. The results of sensitivity analyses showed comparable results.ConclusionsAnalysis of Japanese nationwide administrative database demonstrated that high burn patient volume was significantly associated with increased in-hospital mortality, high healthcare costs, and few hospital-free days. Further studies are needed to validate our results.

Project description:ObjectivesThe purpose of this study was to investigate the effects of smoking on prognosis after elective surgeries. Incidence of 30-day postoperative complications was compared between propensity score-matched 'ever-smoker' and 'never-smoker' cohorts. Thirty-day mortality and medical costs during the hospital stay were also compared.Design and settingA large-scale retrospective study using deidentified administrative claims data obtained from 372 acute care hospitals across Japan using the Diagnosis Procedure Combination system (ie, a flat-fee payment system).ParticipantsInpatients who were hospitalised to undergo elective surgery.Primary and secondary outcome measuresThe primary endpoint of this study was incidence of 30-day postoperative complications. Secondary endpoints were 30-day mortality and total medical costs during hospitalisation. Comparison between ever-smokers and never-smokers was conducted using matched cohorts created by 1:1 propensity score matching.ResultsUsing 561?598 eligible patients, matched ever-smoker and never-smoker cohorts (n=1?55?593?each) were created. Ever-smokers were defined as patients with Brinkman Index ?1. The percentage of patients who were male was 76.7%, and mean ages for ever-smokers and never-smokers were 65.1±13.8 years old and 66.4±15.3 years old, respectively. The Brinkman Index of the ever-smoker cohort was 677.6±553.4. Smoking was significantly associated with higher risk of 30-day postoperative complications compared with not smoking (OR 1.15, 95%?CI 1.13 to 1.17, p<0.001). Similarly, smoking was significantly associated with postoperative 30-day mortality, with OR of 1.22 (95% CI 1.08 to 1.39, p=0.002).ConclusionsOur results suggest that smoking could be associated with risk of poor postoperative outcomes. In particular, a history of smoking may increase the risk of 30-day postoperative complications as well as that of 30-day mortality. The results suggest that smoking might have a harmful effect on postoperative outcomes irrespective of types of surgery.

Project description:Administrative data are used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score.Retrospective cohort study using 2012 administrative data from five U.S. states. Three cohorts of patients with severe sepsis were created: 1) International Classification of Diseases, 9th Revision, Clinical Modification codes for severe sepsis/septic shock, 2) Martin approach, and 3) Angus approach. The model was developed and internally validated in International Classification of Diseases, 9th Revision, Clinical Modification, cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score.Acute care, nonfederal hospitals in New York, Maryland, Florida, Michigan, and Washington.Patients in one of three severe sepsis cohorts: 1) explicitly coded (n = 108,448), 2) Martin cohort (n = 139,094), and 3) Angus cohort (n = 523,637) INTERVENTIONS: None.Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit and C-statistics, respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. Goodness-of-fit demonstrated p value of more than 0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort), suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile.Our sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data.

Project description:ObjectivesDementia is common in people over the age of 65 years, with 80% of people with dementia older than 75 years. Previous studies have linked dementia to late-life depression, but the association between dementia and mid-life depression is poorly understood. Depression is a preventable and treatable medical condition, which means it is a modifiable factor that can potentially prevent or delay dementia. This study aimed to identify the association between dementia and depression within the life course.DesignA nationwide, retrospective propensity score matched cohort study associating dementia with depression. Depression diagnosed between the ages of 45 and 64 years was classified as 'mid-life' and 'late-life' if diagnosed at 65 years or older. Patients were considered to have depression when one or more International Statistical Classification of Diseases and Related Health Problems, 10th revision codes for depression were recorded as primary or secondary diagnosis.SettingNational Health Insurance Service-National Sample Cohort database of the National Health Insurance Service in South Korea, containing patient data from 2002 to 2013.ParticipantsThe study included 1824 and 374 852 patients in the case and control groups, respectively. A logistic regression analysis with complex sampling design was performed after adjusting for covariates, using the propensity score matching method without callipers, with a 1:1 nearest neighbour matching algorithm.Primary and secondary outcome measuresThe association of mid-onset and late-onset depression with dementia in terms of sociodemographic characteristics, such as sex and age, within the Korean population.ResultsDementia was significantly associated with the presence of depression (OR=2.20, 95% CI=1.53-3.14); in particular, female patients with depression and patients aged 45-64 years with depression had increased odds of dementia (OR=2.65, 95% CI=1.78-3.93 and OR=2.72, 95% CI=1.41-5.24, respectively) CONCLUSION: Depression is an associated factor for dementia, especially among people aged 45-64 years (mid-life).

Project description:BackgroundBoth health insurance status and race independently impact colon cancer (CC) care delivery and outcomes. The relative importance of these factors in explaining racial and insurance disparities is less clear, however. This study aimed to determine the association and interaction of race and insurance with CC treatment disparities.Study settingRetrospective cohort review of a prospective hospital-based database.Methods and findingsIn this cross-sectional study, patients diagnosed with stage I to III CC in the United States were identified from the National Cancer Database (NCDB; 2006 to 2016). Multivariable regression with generalized estimating equations (GEEs) were performed to evaluate the association of insurance and race/ethnicity with odds of receipt of surgery (stage I to III) and adjuvant chemotherapy (stage III), with an additional 2-way interaction term to evaluate for effect modification. Confounders included sex, age, median income, rurality, comorbidity, and nodes and margin status for the model for chemotherapy. Of 353,998 patients included, 73.8% (n = 261,349) were non-Hispanic White (NHW) and 11.7% (n = 41,511) were non-Hispanic Black (NHB). NHB patients were less likely to undergo resection [odds ratio (OR) 0.66, 95% confidence interval [CI] 0.61 to 0.72, p < 0.001] or to receive adjuvant chemotherapy [OR 0.83, 95% CI 0.78 to 0.87, p < 0.001] compared to NHW patients. NHB patients with private or Medicare insurance were less likely to undergo resection [OR 0.76, 95% CI 0.63 to 0.91, p = 0.004 (private insurance); OR 0.59, 95% CI 0.53 to 0.66, p < 0.001 (Medicare)] and to receive adjuvant chemotherapy [0.77, 95% CI 0.68 to 0.87, p < 0.001 (private insurance); OR 0.86, 95% CI 0.80 to 0.91, p < 0.001 (Medicare)] compared to similarly insured NHW patients. Although Hispanic patients with private and Medicare insurance were also less likely to undergo surgical resection, this was not the case with adjuvant chemotherapy. This study is mainly limited by the retrospective nature and by the variables provided in the dataset; granular details such as continuity or disruption of insurance coverage or specific chemotherapy agents or dosing cannot be assessed within NCDB.ConclusionsThis study suggests that racial disparities in receipt of treatment for CC persist even among patients with similar health insurance coverage and that different disparities exist for different racial/ethnic groups. Changes in health policy must therefore recognize that provision of insurance alone may not eliminate cancer treatment racial disparities.

Project description:ObjectiveTo evaluate whether early and acquired daily fluid overload (FO), as well as fluctuations in fluid accumulation, were associated with adverse outcomes in critically ill children with severe sepsis.MethodsThis study enrolled 202 children in a pediatric intensive care unit (PICU) with severe sepsis. Early fluid overload was defined as ≥5% fluid accumulation occurring in the first 24 hours of PICU admission. The maximum daily fluid accumulation ≥5% occurring during the next 6 days in patients with at least 48 hours of PICU stay was defined as PICU-acquired daily fluid overload. The fluctuation in fluid accumulation was calculated as the difference between the maximum and the minimum daily fluid accumulation obtained during the first 7 days after admission.ResultsOf the 202 patients, 61 (30.2%) died during PICU stay. Among all patients, 41 (20.3%) experienced early fluid overload, including 9 with a FO ≥10%. Among patients with at least 48 hours of PICU stay (n = 154), 36 (23.4%) developed PICU-acquired daily fluid overload, including 2 with a FO ≥10%. Both early fluid overload (AOR = 1.20; 95% CI 1.08-1.33; P = 0.001; n = 202) and PICU-acquired daily fluid overload (AOR = 5.47 per log increase; 95% CI 1.15-25.96; P = 0.032; n = 154) were independent risk factors associated with mortality after adjusting for age, illness severity, etc. However, fluctuations in fluid accumulation were not associated with mortality after adjustment. Length of PICU stay increased with greater fluctuations in fluid accumulation in all patients with at least 48 hours of PICU stay (FO <5%, 5%-10% vs. ≥10%: 4 [3-8], 7 [4-11] vs. 10 [6-16] days; P <0.001; n = 154) and in survivors (4 [3-8], 7 [5-11] vs. 10 [5-15] days; P <0.001; n = 121). Early fluid overload achieved an area under-the-receiver-operating-characteristic curve of 0.74 (95% CI 0.65-0.82; P <0.001; n = 202) for predicting mortality in patients with severe sepsis, with a sensitivity of 67.2% and a specificity of 80.1% at the optimal cut-off value of 2.65%.ConclusionsBoth early and acquired daily fluid overload were independently associated with PICU mortality in children with severe sepsis.

Dataset Information

The association of lacking insurance with outcomes of severe sepsis: retrospective analysis of an administrative database*.

Publications

The association of lacking insurance with outcomes of severe sepsis: retrospective analysis of an administrative database*.

Similar Datasets

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