Objective : Health insurers and policy makers are increasingly examining the hospital mortality rate as an indicator of hospital quality and performance. To be meaningful, a risk-adjustment of the death rates must be implemented. This study reviewed 5 severity measurement methods and applied them to the same data set to determine whether judgments regarding the severity-adjusted hospital mortality rates were sensitive to the specific severity measure. Methods : The medical records of 584 patients who underwent coronary artery bypass graft surgery in 6 general hospitals during 1996 and 1997 were reviewed by trained nurses. The MedisGroups, Disease Staging, Computerized Severity Index, APACHE III and KDRG were used to quantify severity of the patients. The predictive probability of death was calculated for each patient in the sample from a multivariate logistic regression model including the severity score, age and sex to evaluate the hospitals' performance, the ratio of the observed number of deaths to the expected number for each hospital was calculated. Results : The overall in-hospital mortality rate was 7.0%, ranging from 2.7% to 15.7% depending on the particular hospital. After the severity adjustment, the mortality rates for each hospital showed little difference according to the severity measure. The 5 severity measurement methods varied in their statistical performance. All had a higher c statistic and $R^2$ than the model containing only age and sex. There was a little difference in the relative hospital performance evaluation by the severity measure. Conclusion : These results suggest that judgments regarding a hospital's performance based on severity adjusted mortality can be sensitive to the severity measurement method. Although the 5 severity measures regarding hospital performance concurred, more often than would be expected by chance, the assessment of an individual hospital mortality rates varied by the different severity measurement method used.
Objectives: To propose a risk-adjustment model with using insurance claims data and to analyze whether or not the outcomes of non-emergent and isolated coronary artery bypass graft surgery (CABG) differed between the low- and high-volume hospitals for the patients who are at different levels of surgical risk. Methods: This is a cross-sectional study that used the 2002 data of the national health insurance claims. The study data set included the patient level data as well as all the ICD-10 diagnosis and procedure codes that were recorded in the claims. The patient's biological, admission and comorbidity information were used in the risk-adjustment model. The risk factors were adjusted with the logistic regression model. The subjects were classified into five groups based on the predicted surgical risk: minimal (<0.5%), low (0.5% to 2%), moderate (2% to 5%), high (5% to 20%), and severe (=20%). The differences between the low- and high-volume hospitals were assessed in each of the five risk groups. Results: The final risk-adjustment model consisted of ten risk factors and these factors were found to have statistically significant effects on patient mortality. The C-statistic (0.83) and Hosmer-Lemeshow test ($x^2=6.92$, p=0.55) showed that the model's performance was good. A total of 30 low-volume hospitals (971 patients) and 4 high-volume hospitals (1,087 patients) were identified. Significant differences for the in-hospital mortality were found between the low- and high-volume hospitals for the high (21.6% vs. 7.2%, p=0.00) and severe (44.4% vs. 11.8%, p=0.00) risk patient groups. Conclusions: Good model performance showed that insurance claims data can be used for comparing hospital mortality after adjusting for the patients' risk. Negative correlation was existed between surgery volume and in-hospital mortality. However, only patients in high and severe risk groups had such a relationship.
In recent decades, decreasing trends in esophageal cancer mortality have been observed across China. We here describe esophageal cancer mortality trends in Linzhou city, a high-incidence region of esophageal cancer in China, during 1988-2010 and make a esophageal cancer mortality projection in the period 2011-2020 using a Bayesian approach. Age standardized mortality rates were estimated by direct standardization to the World population structure in 1985. A Bayesian age-period-cohort (BAPC) analysis was carried out in order to investigate the effect of the age, period and birth cohort on esophageal cancer mortality in Linzhou during 1988-2010 and to estimate future trends for the period 2011-2020. Age-adjusted rates for men and women decreased from 1988 to 2005 and changed little thereafter. Risk increased from 30 years of age until the very elderly. Period effects showed little variation in risk throughout 1988-2010. In contrast, a cohort effect showed risk decreased greatly in later cohorts. Forecasting, based on BAPC modeling, resulted in a increasing burden of mortality and a decreasing age standardized mortality rate of esophageal cancer in Linzhou city. The decrease of esophageal cancer mortality risk since the 1930 cohort could be attributable to the improvements of socialeconomic environment and lifestyle. The standardized mortality rates of esophageal cancer should decrease continually. The effect of aging on the population could explain the increase in esophageal mortality projected for 2020.
Objectives: While recent studies showed that coffee consumption reduced the risk of all-cause mortality, no study has examined the effect of coffee consumption on all-cause mortality related to sleep disorders. We aimed to examine whether sleep-related disorders would differently affect the association between coffee consumption and the risk of all-cause mortality among 8,075 adults aged 40 to 69 years. Methods: In a prospective cohort study, the study participants were biennially followed up for 12 years from 2001 to 2012. On each follow-up visit, the participants underwent comprehensive tests including anthropometric examinations, interviewer-administered questionnaires, and biochemical tests. Coffee consumption frequency and the amount were measured using a semi-quantitative food frequency questionnaire. Using death certificate data from Korean National Statistical Office, the vital status of each study participant was identified. Sleep-related disorders were examined with interviewer-administered questionnaires. We estimated Hazard ratios and the corresponding 95% confidence intervals from Cox Proportional Hazard models. Multivariable models were established after adjusting for center, total caloric intake, age, gender, body mass index, physical activity, education, smoking, drinking, hypertension, diabetes, total cholesterol, c-reactive protein, energy-adjusted food groups of refined grains, vegetables, fruits, meat, fish, and dairy. Results: Compared with those who had no coffee consumption, participants who had about three cups of coffee per day showed a reduced risk of all-cause mortality, after adjusting for covariates. Those who had a sleep-related disorder showed no significant effect of coffee consumption on the risk of all-cause mortality, whereas those who had no sleep-related disorders showed significantly reduced risk of all-cause mortality. Conclusions: Our findings suggested that approximately three cups of coffee per day would be beneficial to reduce the risk of all-cause mortality only among adults with no sleep-related disorders. Coffee consumption should be prudent for those with sleep-related symptoms.
Background: Sepsis is an emergency condition with high mortality and morbidity rate. There are limited data on the association of cancer as a risk factor for mortality in sepsis patients in the emergency department (ED). Materials and Methods: This retrospective study was conducted at the ED, Faculty of Medicine, Ramathibodi Hospital, Bangkok, Thailand. The study period was between January 1st and December $31^{st}$, 2014. The inclusion criteria were as follows: adult patients over 15 years of age who presented at the ED with suspicion of sepsis, received treatment at the ED, and whose blood culture was found to be positive. Clinical data were recorded from medical records including the Mortality in Emergency Department Sepsis score (MEDS score). The primary outcome of this study was mortality at one month. Multivariate logistic regression analysis was used to identify independent factors associated with death. Results: During the study period, there were 775 eligible patients. The two most common pathogens identified from blood cultures were Staphylococcus aureus (193 patients; 24.9%) and Escherichia coli (158 patients; 20.4%). At one month after presenting at the ED, 110 patients (14.2%) had died. There were four significant factors for death, having cancer, being on an endotracheal tube, initial diagnosis of bacteremia, and high MED scores. Having cancer had an adjusted OR of 2.12 (95% CI of 1.29, 3.47). Conclusions: Cancer patients have double the risk of mortality if presenting with sepsis at the ED.
Objectives: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. Methods: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. Results: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. Conclusions: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.
Objective : We aimed to examine trends in critically ill neurology-neurosurgery (NNS) patients who were admitted to the intensive care unit (ICU) in South Korea and identify risk factors for in-hospital mortality after ICU admission in NNS patients. Methods : This nationwide population-based retrospective cohort study enrolled adult NNS adult patients admitted to the ICU from 2010 to 2019 extracted from the National Health Insurance Service in South Korea. The critically ill NNS patients were defined as those whose main admission departments were neurology or neurosurgery at ICU admission. The number of ICU admission, age, and total cost for hospitalization from 2010 to 2019 in critically ill NNS patients were examined as trend information. Moreover, multivariable logistic regression modeling was used to identify risk factors for in-hospital mortality among critically ill NNS patients. Results : We included 845474 ICU admission cases for 679376 critically ill NNS patients in South Korea between January 1, 2010 to December 31, 2019. The total number of ICU admissions among NNS patients was 79522 in 2010, which increased to 91502 in 2019. The mean age rose from 62.8 years (standard deviation [SD], 15.6) in 2010 to 66.6 years (SD, 15.2) in 2019, and the average total cost for hospitalization per each patient consistently increased from 6206.1 USD (SD, 5218.5) in 2010 to 10745.4 USD (SD, 10917.4) in 2019. In-hospital mortality occurred in 75455 patients (8.9%). Risk factors strongly associated with increased in-hospital mortality were the usage of mechanical ventilator (adjusted odds ratio [aOR], 19.83; 95% confidence interval [CI], 19.42-20.26; p<0.001), extracorporeal membrane oxygenation (aOR, 3.49; 95% CI, 2.42-5.02; p<0.001), and continuous renal replacement therapy (aOR, 6.47; 95% CI, 6.02-6.96; p<0.001). In addition, direct admission to ICU from the emergency room (aOR, 1.38; 95% CI, 1.36-1.41; p<0.001) and brain cancer as the main diagnosis (aOR, 1.30; 95% CI, 1.22-1.39; p<0.001) are also potential risk factors for increased in-hospital mortality. Conclusion : In South Korea, the number of ICU admissions increased among critically ill NNS patients from 2010 to 2019. The average age and total costs for hospitalization also increased. Some potential risk factors are found to increase in-hospital mortality among critically ill NNS patients.
Background: Acute pulmonary embolism (APE) is a fatal disease with varying clinical characteristics and imaging. The aim of this study was to define the clinical characteristics, risk factors, and outcomes in patients with APE at a university hospital in Thailand. Methods: Patients diagnosed with APE and admitted to our institute between January 1, 2017 and December 31, 2022 were retrospectively enrolled. The clinical characteristics, investigations, and outcomes were recorded. Results: Over the 6-year study period, 369 patients were diagnosed with APE. The mean age was 65 years; 64.2% were female. The most common risk factor for APE was malignancy (46.1%). In-hospital mortality rate was 23.6%. The computed tomography pulmonary artery revealed the most proximal clots largely in segmental pulmonary artery (39.0%), followed by main pulmonary artery (36.3%). This distribution was consistent between survivors and non-survivors. Multivariate logistic regression analysis revealed that APE mortality was associated with active malignancy, higher serum creatinine, lower body mass index (BMI), and tachycardia with adjusted odds ratio (95% confidence interval [CI]) of 3.70 (1.59 to 8.58), 3.54 (1.35 to 9.25), 2.91 (1.26 to 6.75), and 2.54 (1.14 to 5.64), respectively. The prediction model was constructed with area under the curve of 0.77 (95% CI, 0.70 to 0.84). Conclusion: The overall mortality rate among APE patients was 23.6%, with APE-related death accounting for 5.1%. APE mortality was associated with active malignancy, higher serum creatinine, lower BMI, and tachycardia.
Objectives: Prospective studies on vaccination status and mortality related to coronavirus disease 2019 (COVID-19) in low-resource settings are still limited. We assessed the association between vaccination status (full, partial, or none) and in-hospital mortality among COVID-19 patients at most hospitals in Jakarta, Indonesia during the Delta predomination wave. Methods: We conducted a retrospective cohort study among hospitalized COVID-19 patients who met the study criteria (>18 years old and admitted for inpatient treatment because of laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection). We linked individual-level data in the hospital admission database with vaccination records. Several socio-demographic and clinical characteristics were also analyzed. A Cox proportional hazards regression model was used to explore the association between vaccination status and in-hospital mortality in this patient group. Results: In total, 40 827 patients were included in this study. Of these, 70% were unvaccinated (n=28 543) and 19.3% (n=7882) died during hospitalization. The mean age of the patients was 49 years (range, 35-59), 53.2% were female, 22.0% had hypertension, and 14.2% were treated in the intensive care unit, and the median hospital length of stay across the group was 9 days. Our study showed that the risk of in-hospital mortality among fully and partially vaccinated patients was lower than among unvaccinated adults (adjusted hazard ratio [aHR], 0.43; 95% confidence interval [CI], 0.40 to 0.47 and aHR, 0.70; 95% CI, 0.64 to 0.77, respectively). Conclusions: Vaccinated patients had fewer severe outcomes among hospitalized adults during the Delta wave in Jakarta. These features should be carefully considered by healthcare professionals in treating adults within this patient group.
Purpose: This study was conducted to determine the incidence, causative pathogens, risk factors and mortality for early onset sepsis in the first three days in very low birth weight infants. Methods: The medical records of 1,124 very low birth weight infants admitted to the neonatal intensive care unit of Samsung Medical Center between November 1994 and December 2008 were retrospectively reviewed. The incidence, causative pathogens, risk factors, and mortality for early onset sepsis in the first 3 days of life in very low birth weight infants were evaluated. Results: Early onset sepsis, as confirmed by positive blood cultures, was present in 17 of 1,124 infants (1.5%). Sixty-four percent of the isolated pathogens were gram-positive bacteria and 35% of the isolated pathogens were gram-negative bacteria. The dominant pathogens of early onset sepsis included Staphylococcus aureus (23.5%), Esherichia coli (23.5%), and Enterococcus (17.6%). Vaginal delivery (adjusted odds ratio [OR], 3.7; 95% confidence interval [CI], 1.3-10.3; P=0.01) was associated with early onset sepsis. The overall mortality (adjusted hazard ratio, 3.0; 95% CI, 1.4-6.5; adjusted P=0.0039) and mortality within 72 hours of life (adjusted hazard ratio, 6.5; 95% CI, 2.2-18.9; adjusted P=0.0005) of infants with early onset sepsis were higher than that of uninfected infants. Conclusion: Early onset sepsis remains an uncommon, but potentially lethal problem among very low birth weight infants. Knowledge of the likely causative organisms and risk factors for early onset sepsis can aid in instituting prompt and appropriate therapy, in order to minimize mortality.
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