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PubMed2005

Impact of age on in-hospital mortality of surgical patients in a German university hospital.

Although the frequency of major surgical procedures in elderly patients is increasing, the impact of age as an independent factor on in-hospital mortality and capacity planning is uncertain. Therefore, we analyzed how age, gender, number of diagnoses, and number of operations per patient are reflecting the demographic changes going on in the last decade. Furthermore, we analyzed the influence of age, main diagnoses, and comorbidities on in-hospital mortality, and cost factors, like duration of in-hospital stay, number of operations, and stay at the intensive care unit using multiple regression analysis. One thousand four hundred and sixty-nine patients hospitalized in 1990, and 5,718 patients hospitalized during 1998-2000 at the surgical department of a German university hospital were recruited. The average age of the patients increased significantly from the year 1990 to 1999 (by 4 years). The overall in-hospital mortality of the elderly patients (above 70 years of age) declined from 18.6% in 1990 to 7.6% in 2000. The number of diagnoses increased from 1.27 to 3.5 per patient. Age is a significant, independent risk factor for in-hospital mortality (odd's ratio (OR), 2.2), prolonged stay at intensive care unit (OR, 1.8), reoperation (OR, 1.3), and prolonged hospitalization (OR, 1.8). Nevertheless, oncologic diseases and pre-existing comorbidities are also significant independent factors for the clinical course and costs resulting from treating elderly patients. We conclude that decisions for surgical treatment should not be solely based on patient's age. The demographic changes in Europe result in an over-proportional increase in expenditures, which should be included when planning the capacities of a surgical department.

Age Factors↗

PubMed1999

Was the decreasing trend in hospital mortality from heart failure attributable to improved hospital care? The Oregon experience, 1991-1995.

OBJECTIVE: To assess the trend in risk-adjusted hospital mortality from heart failure. STUDY DESIGN: Oregon hospital discharge data from 1991 through 1995 were analyzed. PATIENTS AND METHODS: A total of 29,530 hospitalizations because of heart failure in elderly patients (age > or = 65 years) were identified from International Classification of Diseases, 9th Revision, codes 428.0-428.9. The logistic regression and life table analyses were used to assess the risk-adjusted trend in hospital mortality from heart failure. RESULTS: From 1991 through 1995, 1757 (5.9%) patients with heart failure died in the hospital; 920 (52.4%) of them died within 3 days. The percentage of patients discharged to skilled nursing facilities increased from 6.1% in 1991 to 9.8% in 1995 (P value for trend < .001), whereas the percentage of patients discharged directly to home decreased from 69.2% in 1991 to 62.4% in 1995 (P value for trend < .001). The mean length of stay decreased from 5.15 days in 1991 to 3.97 days in 1995. The age- and sex-standardized mortality rate decreased by 33.8% from 7.4 in 1991 to 4.8 in 1995 (P value for trend < .01). Additional adjustment for comorbidity using multiple logistic regression revealed a greater reduction of 41.0% in the mortality rate (odds ratio = 0.59; 95% confidence interval = 0.50, 0.69) and a reduction of 46.0% in the 3-day mortality rate (odds ratio = 0.54; 95% confidence interval = 0.43, 0.67) across the 5-year period. Life table analysis showed consistently lower cumulative mortality rates during the first week after admission in 1995 compared with those in 1991 (P < .001). CONCLUSION: There was a decreasing trend over time in the risk-adjusted hospital mortality rates from heart failure, which was not an artifact of decreasing length of stay. Our findings raised the possibility of improved hospital care for heart failure in Oregon.

Aged↗

PubMed2005

The relationship of functional status, nutritional assessment, and severity of illness to in-hospital mortality.

BACKGROUND: Prediction of in-hospital mortality may direct hospital resources towards those patients most at risk. A number of single domain risk instruments have been developed, indicating that functional status, nutritional assessment, and severity of illness individually predict in-hospital mortality. The interaction among these predictors is less well described. OBJECTIVE: To determine the relationship of functional status, nutritional assessment, and severity of illness to in-hospital mortality. DESIGN, SETTING, SUBJECTS: Cohort study of 1712 consecutive admissions over a one year period to an Internal Medical Service at a tertiary university teaching hospital. MAIN OUTCOME MEASURES: Death during hospital admission. RESULTS: Dependency in activities of daily living (OR = 3.37, 95% CI 1.78 to 6.37, p = 0.0002) and body mass index less than 20 (OR = 2.38, 95% CI 1.20 to 4.74, p = 0.01) predicted in-hospital mortality after adjusting for nutritional risk assessment, and severity of illness score. CONCLUSIONS: Impairment in functional status and low body mass index produce the best predictors of inhospital mortality, after adjusting for nutritional risk and severity of illness score. Among these factors, functional impairment may be amenable to correction.

Activities of Daily Living↗

PubMed1999

[Borderline between emergencies and hospitalization in the analysis of hospital mortality].

BACKGROUND: The analysis of hospital mortality rate as a measure of care quality is usually restricted to death occurred at hospital wards, and no consideration is given to deaths occurred at the Emergency Department. Therefore, the information from a fundamental hospital area goes without analysis. METHODS: The following characteristics of decreased individuals at the Emergency Department (n = 79) and hospital wards (n = 280) in the Costa del Sol Hospital (Marbella, Málaga, Spain) during 1997 were compared: age, sex, main diagnosis at admission, main diagnosis specificity, and number of secondary diagnoses. A reevaluation of hospital mortality rates was made after data from ED deaths had been added. RESULTS: The addition of deaths occurred at the ED meant a relevant increase in hospital mortality rates: 57% for heart failure, 30% for stroke, and 25% for myocardial infarction. Twenty percent of deaths at the ED had non-specific diagnosis versus 5% at wards (p < 0.0001; 95%CI: 6.03; 24.15). Deaths at the ED had 2.9 +/- 1.3 secondary diagnoses versus 4.9 +/- 2.0 in deaths at hospital wards (p < 0.0001; 95%CI: 1.6; 2.4). CONCLUSIONS: Deaths at the ED make up a relevant proportion of the total deaths and should be incorporated to the hospital mortality analysis. Deficiencies in the collection of clinical information were observed in this ED. Therefore, adjustments for severity--an essential issue for comparing mortality rates between centers--might be precluded.

Aged↗

PubMedDate not supplied

Factors predicting in-hospital mortality in patients with cirrhosis hospitalized with gastro-esophageal variceal hemorrhage.

AIM: To identify factors at the time of admission that predict in-hospital mortality in patients with gastro-esophageal variceal hemorrhage. METHODS: Case records of patients admitted with gastro-esophageal variceal hemorrhage between January 1998 and October 2003 were retrospectively analyzed. Relevant clinical and laboratory parameters and their relationship to mortality, were studied. Clinical parameters assessed included Child-Pugh class, ascites, portosystemic encephalopathy (PSE) and occurrence of rebleed within 24 hours of esophago-gastroduodenoscopy. The laboratory parameters assessed were: hemoglobin, prothrombin time, serum bilirubin, creatinine and albumin. RESULTS: Of the 343 patients admitted during the study period, 30 (8.7%) died in hospital. Serum bilirubin (2.4 versus 1.6 mg/dL) and serum creatinine (2.1 vs 1.1 mg/dL) levels were higher among non-survivors than among survivors. Non-survivors were also more likely to suffer from PSE (53%) than survivors (17%), while re-bleeding within 24 hours of endoscopy occurred in 40% and 5% of these groups, respectively. On multivariate analysis, serum creatinine > 1.5 mg/dL at the time of admission (p < 0.001), serum bilirubin > 3 mg/dL (p < 0.001), presence of PSE (p = 0.003) and rebleed within 24 hours of endoscopy (p < 0.001) were significant predictors of mortality. CONCLUSION: Serum creatinine and bilirubin levels, presence of PSE and re-bleeding within 24 hours of initial endoscopy are independent predictors of mortality in patients with gastro-esophageal variceal bleeding.

Blood Coagulation Tests↗

PubMed1991

Relationship of hospitalized stroke rate and in-hospital mortality to the decline in US stroke mortality.

Data from the National Hospital Discharge Survey was used to estimate the admission rate and in-hospital mortality for US stroke patients from 1970 to 1987. Over this period the hospital admission rate increased from 5.0 per 1,000 population to 5.5 per 1,000, while the in-hospital mortality fell from 18.6 to 10.0% of discharges. When patients experiencing general or late effects or transient ischemic attacks were excluded, the hospital admission rate increased from 2.8 to 4.8 per 1,000 and in-hospital mortality fell from 26 to 12% of discharges. Admission rates increased from 1970 to 1987 for both hemorrhagic strokes and cerebral infarctions, but fell for ill-defined cerebrovascular events, presumably reflecting increased use of computed tomography and magnetic resonance imaging during this period. Mortality for hemorrhagic strokes decreased from 45 to 30% of discharges, mortality for infarctions decreased from 24 to 13% and mortality for ill-defined events fell from 24 to 17%. There are several limitations with the use of the National Hospital Discharge Survey data to estimate changes in hospital admission rates and in-hospital mortality. However, these data suggest a greater role for decreasing case fatality in explaining nationwide declines in stroke mortality rates than has generally been acknowledged.

Acute Disease↗

PubMed2000

In-hospital mortality after transurethral resection of the prostate in Victorian public hospitals.

BACKGROUND: The purpose of the present paper was (i) to identify trends in in-hospital mortality after transurethral resection of the prostate (TURP) in Victorian public hospitals; and (ii) to explore associations between in-hospital mortality after TURP and age, adverse events, type of admission (emergency/planned), location of the hospital (metropolitan/rural), teaching status of the hospital and length of stay. METHODS: Trends in in-hospital mortality after TURP and the associations between in-hospital mortality and the aforementioned variables were studied using International Classification of Diseases, 9th revision, Clinical Modification (ICD-9-CM) coded Victorian hospital morbidity data from public hospitals between 1987-88 and 1994-95. Crude and adjusted odds ratios (OR) and 95% confidence intervals (CI) were based on univariate and multivariate logistic regression, respectively. RESULTS: After adjustment for age, comorbidity, and other confounding variables, the trend in mortality reduction over time was highly significant (P for trend < 0.0001, 95% CI for trend: 0.84-0.95). Highly significant associations with mortality were observed for emergency admissions (OR = 1.99, P < 0.0001), presence of adverse events (OR = 2.69, P < 0.0001), length of hospital stay (P for trend < 0.0001, 95% for trend: 1.88-2.15) and age (P for trend < 0.0001; 95% CI for trend: 1.26-1.48). CONCLUSIONS: Routinely collected data from hospitals can provide tentative evidence of improved effectiveness of a surgical treatment, provided analysis takes careful account of potential sources of bias, especially those related to possible changes in case selection over time. These kinds of data should stimulate a joint effort between clinicians, quality assurance experts and epidemiologists to confirm this attribution, and to locate the causative factors.

Adult↗

PubMed1993

State experience with Medicare hospital mortality: how does New York State compare?

1987 Medicare hospital mortality statistics for 255 New York hospitals (including 57 hospitals in New York City) were compared with 4,617 hospitals located in other states. An analysis of covariance examined how overall Medicare hospital mortality rates differed across states; these rates were adjusted for expected mortality, hospital bed size, and major teaching status. This study tested for the hypothesis that New York State had an average 30-day post-admission Medicare mortality rate significantly different from the mean hospital mortality rate for all states. The results indicated that New York State was -0.43 percentage points below the average risk-adjusted mortality rate of the other states (p < 0.0001). Although it remains speculative to what extent differences in adjusted Medicare hospital mortality are a function of quality of care, these results indicate that New York's historically high level of hospital regulation has not resulted in inferior patient outcomes.

Hospital Mortality↗

PubMed1995

Influence of ejection fraction on hospital mortality, morbidity, and costs for CABG patients.

BACKGROUND: Preoperative ejection fraction (EF) has been shown to adversely affect postoperative hospital mortality and morbidity for patients undergoing isolated coronary artery bypass grafting. METHODS: To investigate influence of EF on isolated coronary artery bypass grafting outcomes (overall hospital mortality, hospital cardiac mortality, hospital morbidity, and hospital costs), data were reviewed from 1,354 consecutive patients who underwent isolated coronary artery bypass grafting between January 1, 1990, and April 30, 1992, at a single nonprofit hospital. Overall hospital mortality was 4.06% (cardiac, 2.36%). Hospital morbidity was 14.25% (including mortality). Hospital costs (not charges) averaged $16,673 per patient. To explore the impact of preoperative EF, EF was stratified into regular intervals. Each interval was then compared with regard to hospital mortality, morbidity, and average costs. A new statistical tool, discharge analysis, was developed to analyze the cost data. This was necessary because previous efforts at cost analysis have used tools inappropriate for real world cost data. RESULTS: The statistical analysis showed that patients with EF of 0.40 or greater had the best outcomes (lowest mortality, morbidity, and cost). Once the EF is 0.40 or greater the EF does not carry further predictive value. At EF less than 0.40, patients with EF less than 0.30 have a poorer outcome than patients with EF of 0.30 to 0.39. CONCLUSIONS: (1) Ejection fraction is a valid predictor of mortality, morbidity and resource utilization based on statistical analysis. (2) Patients can be broadly grouped as having EF greater than 0.40, less than 0.30, or from 0.30 to 0.39 with regard to clinical and cost outcomes. (3) Postoperative length of stay is not predicted by risk-adjusted EF. (4) A new tool, discharge analysis, is presented to facilitate cost analysis.

Aged↗

PubMed2004

[Hospital mortality and length of stay: comparison between public and private hospitals in Ribeirão Preto, São Paulo State, Brazil].

Performance assessment in health services is essential. The comparison of performance indicators requires the use of risk adjustment strategies. The objective of this paper was to assess variations in clinical performance, measured by hospital mortality and length of stay, between private and public hospitals, while taking into account the hospital case mix. This study is located in the Ribeirão Preto region in São Paulo State, Brazil. From 1996 to 1998, 32,906 patients admitted with cardiovascular and respiratory diagnoses were studied. Variables used for risk adjustment of performance indicators were: sex, age, principal diagnosis, and severity measures based on co-morbidity. Clinical performance in public hospitals as measured by adjusted hospital mortality (OR = 0.41) was better than in private hospitals. Public and private hospitals were not statistically different concerning patients' length of stay. Although some conceptual and methodological problems persist, hospital mortality and other adjusted performance indicators should be considered as useful tools to identify health services' performance problems.

Adolescent↗

PubMedDate not supplied

[Quality of data or quality of care? Comparison of diverse standarization methods by clinical severity, based on the discharge form, in the analysis of hospital mortality].

Using discharge abstract data, we analysed hospital mortality comparing four different methods of risk adjustment. All patients discharged from the S. Giovanni Battista (Molinette) hospital in Turin (Italy) between January 1996 and June 1999 (n = 169,746) were classified with All Patient Refined--Diagnosis Related Groups (APR-DRG). A first analysis evaluated the time trend of hospital mortality by semester. A second analysis compared hospital mortality during the last 12 months among eight units of internal medicine (n = 5592). All comparisons were made through logistic regression models. As the quality of discharge abstracts increased during time and showed variation among units with similar patients, all comparisons were repeated using four models, characterised by increasing predictivity and sensitivity to quality of data. In addition to crude comparisons (A), the other models included as risk factors: B) age and emergency admission; C) same as 'B' plus expected mortality by APR-DRG; D) same as 'B' plus expected mortality by APR-DRG and risk of death subclass. If no risk factors were considered (A), hospital mortality showed an increasing trend, with an odds ratio (OR) of 1.02 by semester, with a 95% confidence interval (CI) between 1.01 and 1.03. The association was weakened when age and mode of admission were taken into account (B) and disappeared when the APR-DRG expected mortality was also considered (C) (OR = 1.00; CI = 0.98-1.01). Finally, if the comparisons were adjusted also for the expected mortality by APR-DRG and risk of death subclass (D) a reversed trend appeared (OR = 0.95; CI = 0.94-0.97). The comparison among the units of internal medicine gave discordant results according to the method used to adjust for confounders. The most striking variations were detected for those units with the best and the worst clinical data. The unit with the poorer clinical data (average number of diagnoses per patient = 2.9) showed a crude OR of 1.38 (CI = 0.99-1.93) and an adjusted OR (D) of 1.71 (CI = 1.10-2.66); the unit with the best quality of data (average number of diagnoses per patient = 4.4) changed the OR from 1.55 (CI = 1.06-2.26) (A) to 0.66 (CI = 0.37-1.17) (D). In conclusion, these results confirm the high sensitivity of the APR-DRG classification to the quality of data and, more in general, suggest to be prudent when using powerful instruments like this to assess quality of care, especially if the quality of data among the units compared is less than optimal or not homogeneous.

Hospital Mortality↗

PubMed2006

In-hospital mortality for children with hypoplastic left heart syndrome after stage I surgical palliation: teaching versus nonteaching hospitals.

OBJECTIVES: Teaching hospitals are perceived to provide a higher quality of care for the treatment of rare disease and complex patients. A substantial proportion of stage I palliation for hypoplastic left heart syndrome (HLHS) may be performed in nonteaching hospitals. This study compares the in-hospital mortality of stage I palliation between teaching and nonteaching hospitals. METHODS: The authors conducted a retrospective cohort study using the Kids' Inpatient Database 1997 and 2000. Patients with HLHS undergoing stage I palliation were identified using International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic and procedural codes. RESULTS: Seven hundred fifty-four and 880 discharges of children with HLHS undergoing stage I palliation in 1997 and 2000, respectively, were identified. The in-hospital mortality for the study population was 28% in 1997 and 24% in 2000. Twenty percent of stage I palliation operations were performed in nonteaching hospitals in 1997. Two percent of operations were performed in nonteaching hospitals in 2000. In 1997 only, in-hospital mortality remained higher in nonteaching hospitals after controlling for stage I palliation hospital volume and condition-severity diagnoses. Low-volume hospitals performing stage I palliation were associated with increased in-hospital mortality in 1997 and 2000. CONCLUSIONS: Patients with HLHS undergoing stage I palliation in nonteaching hospitals experienced increased in-hospital mortality in 1997. A significant reduction in the number of stage I palliation procedures performed in nonteaching hospitals occurred between 1997 and 2000. This centralization of stage I palliation into teaching hospitals, along with advances in postoperative medical and surgical care for these children, was associated with a decrease in mortality. Patients in low-volume hospitals performing stage I palliation continued to experience increased mortality in 2000.

Adolescent↗

PubMed1997

Weak associations between hospital mortality rates for individual diagnoses: implications for profiling hospital quality.

OBJECTIVES: This study examined the consistency of hospital mortality rates across different diagnoses. METHODS: Standardized mortality ratios for patients discharged in 1991 from US hospitals were determined via the Medicare Hospital Information Report. RESULTS: Correlations between standardized mortality ratios for different diagnoses were relatively weak, ranging from .03 to .34. Agreement between hospital rankings (based on standardized mortality ratios), as measured by the weighted kappa statistic, was also weak. CONCLUSIONS: The present results indicate that hospital mortality rates for individual diagnoses are weakly associated. Thus, it may not be valid to generalize conclusions about hospital performance from a single diagnosis.

Coronary Artery Bypass↗

PubMed2000

Development and testing of a systemic lupus-specific risk adjustment index for in-hospital mortality.

OBJECTIVE: Valid comparison of patient outcomes among hospitals requires adjustment for differences in the severity of patients' illness. Disease-specific indexes of severity of illness may permit more accurate risk adjustment than generic indexes. The objective of this study was to develop a systemic lupus-specific risk adjustment index for in-hospital mortality, and to compare its performance to that of the generic Charlson index. METHODS: A systemic lupus-specific risk adjustment index was developed using discharge abstract data from a 50% random sample (n = 4994) of patients with systemic lupus erythematosus (SLE) hospitalized on an emergent or urgent basis in California from 1991 to 1994 (n = 9989). The index was tested on the remaining members of the sample. Candidate variables for the index were the diagnoses included in the original Charlson index, and nephritis, chronic renal failure, pericarditis, pleuritis, psychosis, seizures, hemolytic anemia, and thrombocytopenia. Multivariate logistic regression analysis was used to identify the set of variables that best differentiated those patients who died in the hospital from those who survived, and to provide the weights for construction of the index. RESULTS: In the derivation set of patients, the SLE-specific index accurately predicted in-hospital mortality (area under the receiver operating characteristic curve c = 0.79). In the test set, the SLE-specific index (c = 0.72) was similar to the original Charlson index (c = 0.74) in its ability to predict in-hospital mortality (p = 0.32). However, the SLE-specific index accounted for substantially more variation in the risk of mortality among patients (R2 = 0.069) than did the Charlson index (R2 = 0.036). Use of the SLE-specific index rather than the Charlson index for risk adjustment did not alter the association between hospital experience and the probability of in-hospital mortality. Results were similar in the subgroups of patients with emergent hospitalizations and those with emergent hospitalizations due to SLE. CONCLUSION: The SLE-specific risk adjustment index developed from diagnoses recorded in administrative discharge abstracts performed similarly to the generic Charlson index in correctly classifying mortality outcomes, but the SLE-specific index stratified patients by their level of risk of mortality better than the Charlson index. Adjustment for SLE-specific risks of mortality did not alter the association between hospital experience and the risk of in-hospital mortality.

Adolescent↗

PubMed1993

[Relationship between nosocomial infection and hospital mortality. Multicenter study].

BACKGROUND: Hospital mortality related to infections acquired in the hospital setting has not been well studied in Spain. We carried out a study of seven hospitals in order to assess and quantify the problem. METHODS: The study period included three months of observations (between November 1, 1989 and January 31, 1990), and data pertaining to all deaths of patients hospitalized for a minimum of 24 hours were collected. The number of people admitted within the study period was 16,025, and the number of deaths registered and included in our study was 488 (3%). The data were obtained from the patient's medical history one week after death as well as from the hospital physicians on the case. In order to quantify the interobserver variability derived from the classification criteria, the simple kappa index was calculated and averaged to form an ordinal scale. RESULTS: 216 (44.3%) of 488 deaths included in our study had no infection, 138 (28%) had an infection no-hospital-associated, and 134 (27%) had nosocomial infection (50-10%--"causally related to death", 59-12%--"contributing to death", and 25-5%--"not related to death"). The lower respiratory tract infections, bacteremias and surgical wound infections were the most related to cause of death. Staphylococcus aureus was the pathogen most frequently associated with the infections found at the time of death. CONCLUSIONS: Those patients admitted with non-fatal diseases made up the greatest percentage (39.9%) of deaths from nosocomial infections. The infection was considered the direct cause of death in 18.8% of these cases, although the differences found had no statistical significance.

Cause of Death↗

PubMed1999

Predictors of in-hospital mortality following operative management of hip fractures.

OBJECTIVE: To identify predictors of in-hospital mortality and hospital stay following hip fractures. DESIGN: Retrospective cohort study of 185 consecutive patients. SETTING: Tertiary Care University Hospital. PARTICIPANTS: Individuals requiring operative treatment of a proximal femoral fracture excluding those individuals < 50 years old, with femoral head or subtrochanteric fractures, and significant co-morbidity. OUTCOMES: In-hospital mortality and length of hospital stay (days). RESULTS: 116 patients met the inclusion criteria. Predictors of in-hospital mortality from logistic regression analysis included male gender (odds ratio with 95% CI: 5.5, 1.5-20.5), admission from a long term care facility (5.5, 1.4-22.6), age greater than 90 years (4.5, 0.9-22.1), and living at home with support (0.2, 0.03-0.9). Predictors of hospital stay from multivariate regression analysis in order of magnitude included presence of a post-operative complication (odds ratio with 95% CI: 14.1, 4.7-44), living at home with support (3.4, 1.3-8.9) and older age (> 85 years) (2.7, 1.0-7.3). Moreover, confusion, urinary tract infections and decubitus ulcers accounted for greater than 50% of all complications encountered. A trend between the number of positive predictors and length of hospital stay was observed. CONCLUSIONS: Elderly individuals admitted from a long term care facility are at high risk of mortality following operative fixation of hip fractures. Early recognition and aggressive management of post-operative complications such as confusion, urinary tract infections and decubitus ulcers through careful patient monitoring may decrease hospital stays in those that survive.

Aged↗

PubMed2005

Impact of hospital and surgeon volume on in-hospital mortality from radical cystectomy: data from the health care utilization project.

PURPOSE: We determined the influence of hospital and surgeon volume on various outcome parameters after radical cystectomy for bladder cancer. MATERIALS AND METHODS: All inpatient discharges after radical cystectomy for bladder cancer (1988 to 1999) from the Health Care Utilization Project-Nationwide Inpatient Sample were included in the analysis. Hospital and individual surgeon volume of discharges per year were separated into terciles. Outcome measures were in-hospital mortality, length of stay (LOS), and inflation adjusted charge per admission. Mortality was compared among hospital volume levels using the Mantel-Haenszel chi-square test while the LOS and charges were compared using ANOVA. Multivariate linear and logistic regression analyses were used to adjust for confounding factors. All the analyses were also performed in 3 different age strata (younger than 50 years, 50 to 69 years and 70 years or more). RESULTS: There were 13,964 patients who underwent radical cystectomy. Overall in-hospital mortality was 408 of 13,964 (2.9%), average LOS was 14 days (+/- SD 10.28) and average charges were 47,146 dollars (+/- SD 45,263 dollars). In-hospital mortality was significantly associated with higher volume particularly for patients older than 50 years. Surgeon volume did not influence in-hospital mortality except for patients in the 50 to 69-year-old age group. Results of multivariate regression analysis demonstrated hospital volume was a significant predictor of in-hospital mortality but this effect was lost when controlling for surgeon volume. LOS was significantly higher for low volume surgeons. High volume hospitals had lower average total charges compared with the low and moderate volume hospitals. CONCLUSIONS: Hospital and surgeon volume have a significant impact on in-hospital mortality and LOS after radical cystectomy. Radical cystectomy performed at a higher volume center may result in lower charges and shorter hospital stay while decreasing the likelihood of in-hospital mortality.

Aged↗

PubMed2006

Learning from death: a hospital mortality reduction programme.

PROBLEM: There are wide variations in hospital mortality. Much of this variation remains unexplained and may reflect quality of care. SETTING: A large acute hospital in an urban district in the North of England. DESIGN: Before and after evaluation of a hospital mortality reduction programme. STRATEGIES FOR CHANGE: Audit of hospital deaths to inform an evidence-based approach to identify processes of care to target for the hospital strategy. Establishment of a hospital mortality reduction group with senior leadership and support to ensure the alignment of the hospital departments to achieve a common goal. Robust measurement and regular feedback of hospital deaths using statistical process control charts and summaries of death certificates and routine hospital data. Whole system working across a health community to provide appropriate end of life care. Training and awareness in processes of high quality care such as clinical observation, medication safety and infection control. EFFECTS: Hospital standardized mortality ratios fell significantly in the 3 years following the start of the programme from 94.6 (95% confidence interval 89.4, 99.9) in 2001 to 77.5 (95% CI 73.1, 82.1) in 2005. This translates as 905 fewer hospital deaths than expected during the period 2002-2005. LESSONS LEARNT: Improving the safety of hospital care and reducing hospital deaths provides a clear and well supported goal from clinicians, managers and patients. Good leadership, good information, a quality improvement strategy based on good local evidence and a community-wide approach may be effective in improving the quality of processes of care sufficiently to reduce hospital mortality.

England↗