DÄ internationalArchive31-32/2015Deaths Following Cholecystectomy and Herniotomy

Original article

Deaths Following Cholecystectomy and Herniotomy

An Analysis of Nationwide German Hospital Discharge Data From 2009 to 2013

Dtsch Arztebl Int 2015; 112: 535-43. DOI: 10.3238/arztebl.2015.0535

Nimptsch, U; Mansky, T

Background: In 2010, 158 000 cholecystectomies and 207 000 herniotomies (without bowel surgery) were performed in Germany as inpatient procedures, generally on a routine, elective basis. Deaths following such operations are rare events. We studied the potential association of death after cholecystectomy or herniotomy with risk factors that could have been detected beforehand, and we examined the types of complications that were documented in these cases.

Methods: Using nationwide hospital discharge data (DRG statistics) for the years 2009–2013, we analyzed the characteristics of patients who died in the hospital after undergoing a cholecystectomy for cholelithiasis or the repair of an inguinal, femoral, umbilical, or abdominal wall hernia. We compared these data with those of patients who survived and studied the impact of the coded comorbidities on the risk of death.

Results: In Germany, in the years 2009–2013, there were 2957 deaths after a total of 731 000 cholecystectomies (in-hospital mortality, 0.4%) and 1316 deaths after a total of 1 023 000 herniotomies without bowel surgery (0.13%). The patients who died were markedly older than those who did not, and they more commonly had comorbidities. Factors associated with a higher risk of death were age over 65 years, and comorbidities such as congestive heart failure, chronic pulmonary or hepatic disease, or poor nutritional status. Complications were coded much more often for the patients who died than for those who did not.

Conclusion: These findings suggest that there is potential for improvement in preoperative risk identification, complication avoidance, and the early recognition and treatment of complications, as well as in safe surgical technique. Measures to lower the mortality associated with herniotomy and cholecystectomy would lessen patients’ individual risk and thereby improve patient safety.

LNSLNS

Gallbladder removal (cholecystectomy) and surgical repair of an inguinal, femoral, umbilical, or abdominal hernia (herniotomy) are common surgeries. A previous analysis found that approximately 158 000 inpatient cholecystectomies and 207 000 herniotomies without concomitant bowel surgery were performed in Germany in 2010. The median annual case number per hospital was 130 cholecystectomies and 156 herniotomies (1).

Death associated with this usually routine, scheduled surgery is perceived as a rare event. In Germany, the risk of dying in hospital in connection with a cholecystectomy was 0.49% (corresponding to one death per 204 operations) in 2010. For herniotomies the hospital mortality rate was 0.13% (corresponding to one death per 759 operations) (1). This means that, statistically, in an average hospital there is one cholecystectomy-related death every 19 months and one herniotomy-related death only once every five years. This makes it difficult to identify systematic correlations in everyday clinical practice.

Information obtained from peer reviews on quality improvement which analyzed deaths associated with cholecystectomy and herniotomy indicates that there is potential for improvement in indication and in perioperative and postoperative management (2, 3). In particular, patients at increased risk of complications as a result of comorbidities should be identified as high-risk patients before surgery and be provided with appropriate care (2).

The nationwide German hospital discharge data forms a complete dataset and can therefore be used to analyze even rare events. On the basis of this data, this study investigates the characteristics of patients who died in hospital in connection with a cholecystectomy or herniotomy and compares them to the characteristics of surviving patients.

It also analyzes the effect of documented comorbidities illnesses on the risk of death and examines complications and specific interventions during the course of treatment.

Methods

Data

Using controlled remote data processing, we analyzed the nationwide Diagnosis-Related Groups Statistics (DRG Statistics) provided by the German Federal Statistical Office's Research Data Center (4). The nationwide DRG Statistics contain the data records of all acute inpatient hospital cases reimbursed according to the DRG system. This information includes age and sex, diagnoses (coded according to ICD-10-GM International Classification of Diseases, 10th Revision, German Modification) and procedures (coded according to the Surgery and Procedure Coding System [OPS, Operationen- und Prozedurenschlüssel]), hours of mechanical ventilation, and discharge mode for every inpatient case.

In order for analysis to cover sufficient deaths to provide statistical power, data for the years 2009 to 2013 were included and analyzed cumulatively.

Case definition

The units of analysis are inpatient hospital cases in which a patient underwent a cholecystectomy or herniotomy. Cholecystectomies include gallbladder removal for gallstones (cholelithiasis), excluding malignant neoplasias, extended cholecystectomies, and those performed concomitantly with other surgeries were excluded. Herniotomies are defined as surgeries for inguinal, femoral, umbilical, or abdominal hernia, excluding those with concomitant bowel surgery (eTable 1). Analyses are limited to patients aged 20 years or over.

Case definition
Case definition
eTable 1
Case definition

Comorbidities, complications, specific interventions

Comorbidities are taken to include conditions that probably existed prior to inpatient admission (e.g. heart failure, chronic lung disease) and that represent potential risk factors for in-hospital death (59). Complications include events that are classified as complications in the ICD (e.g. surgical complications such as accidental perforation and suture failure) and serious conditions that would contraindicate the surgery in question (e.g. pulmonary embolism, acute kidney failure) and therefore probably first occurred during treatment. Comorbidities and complications were identified using the coded diagnoses (eTable 2).

Definition of variables
Definition of variables
eTable 2
Definition of variables
Crude mortality rates stratified by patient characteristics
Crude mortality rates stratified by patient characteristics
eTable 3
Crude mortality rates stratified by patient characteristics

In addition, specific interventions that indicate complicated patient progress were also investigated. These include, for example, blood transfusions of more than six units and relaparatomies, identified using coded procedures (eTable 2). Inpatients receiving mechanical ventilation for longer than 24 hours were also identified, on the basis of documented mechanical ventilation duration.

Analysis

Patient characteristics, comorbidities, complications, and interventions were stratified by survival status. The effects of age, sex, and comorbidities on the in-hospital mortality risk were analyzed using odds ratios that estimate the risk of death when a characteristic (e.g. a comorbidity) is present in relation to the risk of death when the characteristic is not present. In addition to crude odds ratios, odds ratios adjusted for age, sex, and comorbidities are also provided. These were calculated using generalized logistic regression (10). The adjusted odds ratios quantify the change in risk independently of the effects of other factors in the regression equation. The statistical significance of the odds ratios was assessed using 95% confidence intervals. The discriminatory power of the regression models was assessed using the c-statistic, which is equivalent to the area under the ROC (receiver operating characteristic) curve (11, 12). This measure describes the association of deaths predicted by the regression model and observed deaths. c-values can range between 0.5 (no discrimination) and 1.0 (perfect discrimination). All calculations were performed using SAS version 9.3.

Results

Patient characteristics

Approximately 731 000 cases of cholecystectomy for cholelithiasis and 1 023 000 cases of herniotomy without concomitant bowel surgery were identified during the study period. Between 2009 and 2013, the in-hospital mortality rate for cholecystectomy remained steady at 0.4%. For herniotomy in-hospital mortality was 0.14% from 2009 to 2011, 0.11% in 2012, and 0.13% in 2013. A total of 2957 deaths occurred following cholecystectomy and 1316 following herniotomy during the study period (Table 1).

Patient characteristics by year
Patient characteristics by year
Table 1
Patient characteristics by year

Stratified analysis of the characteristics of surviving and deceased patients shows, unsurprisingly, that for both procedures those who died were substantially older than those who survived. For cholecystectomy the proportion of females was slightly lower among those who died than among those who survived; for herniotomies it was somewhat higher. Almost all comorbidities analyzed were recorded more frequently among those who died than among those who survived. At least one of the analyzed comorbidities had been coded in 99% of deaths following cholecystectomy and 91% of deaths following herniotomy. The mean duration of hospital stay was also substantially longer for patients who died (Table 2).

Patient characteristics by survival status
Patient characteristics by survival status
Table 2
Patient characteristics by survival status

Factors associated with the risk of death following
cholecystectomy

For cholecystectomy, the crude figures indicate that ages over 65 years are associated with a risk of death 27 times higher than that of younger patients. After adjustment for sex and comorbidities, the risk of death for patients aged over 65 remains 10 times as high as for younger patients, independently of other factors. According to the crude figures, female sex appears to be associated with a lower risk of death, but this correlation is no longer discernible after adjustment (Table 3).

Crude and adjusted odds ratios for in-hospital death
Crude and adjusted odds ratios for in-hospital death
Table 3
Crude and adjusted odds ratios for in-hospital death

The crude odds ratios of all analyzed comorbidities other than obesity indicate an association with an increased risk of death. After adjustment, an increased risk independent of other factors remains for most comorbidities. The strongest association occurs in patients with heart failure or dilated cardiomyopathy, whose risk of death is 3.6 times higher than that of patients for whom no such comorbidity is coded. Patients with malnutrition and those with coagulation disorders both have a 3.5-fold risk increase. Inflammatory conditions at the surgical site (cholangitis, acute cholecystitis, or biliary pancreatitis) are associated with 3.2-fold increase in the risk of death. In patients with chronic liver disease, chronic pancreatitis, or chronic kidney failure the risk of death is more than twice as high as in patients without these comorbidities. Other comorbidities associated with a significantly increased risk of death according to the adjusted odds ratios are cardiac arrhythmias, chronic ischemic heart disease, atherosclerosis, chronic lung disease, diabetes mellitus, and peritoneal adhesions. For obesity, both the crude and the adjusted analysis actually indicate a protective effect. This means that cholecystectomy patients for whom obesity is coded as a secondary diagnosis have a lower risk of dying in the hospital. Following adjustment, patients with hypertension also have a lower risk of death than patients for whom it is not coded. Aortic or mitral valve defects and severe kidney disease showed no significant effect on the risk of death after adjustment (Table 3).

The c-value of the regression model was 0.925. This means that the model has a high power of discrimination and can differentiate very well between patients who died and those who survived on the basis of the variables used here.

Factors associated with the risk of death following herniotomy

In herniotomy patients, after adjustment age over 65 years is associated with a more than 5-fold increase in the risk of death. Women have more than twice the risk of dying in the hospital of men according to both crude and adjusted figures (Table 3).

According to the crude figures, all comorbidities appear to be associated with an increased risk of death. After adjustment a greatly increased risk remains for several comorbidities: the risk of death in malnourished patients is eight times higher than in those for whom malnutrition is not coded. Chronic liver disease is associated with an almost six-fold increase in risk. There is a more than four-fold increase in risk associated with coagulation disorders, malignant neoplasias, and heart failure. For patients with chronic kidney failure the risk of death is 2.7 times higher. Other significant increases in risk are found in patients with cardiac arrhythmias, atherosclerosis, chronic lung disease, and diabetes mellitus.

After adjustment, the increase in risk for chronic pancreatitis is no longer significant. No effect on the risk of death was identified for chronic ischemic heart disease, aortic or mitral valve defects, severe kidney disease, or obesity. The secondary diagnosis hypertension is associated with a reduced risk of death according to adjusted figures (Table 3).

The regression model has a c-value of 0.847, indicating a very good power of discrimination.

Complications and specific interventions

All the complications investigated were coded more frequently for patients who died than for those who survived. Sepsis was recorded for 37% of deceased cholecystectomy patients and 17% of deceased herniotomy patients. Other common complications were acute kidney failure (37% and 29% respectively), pneumonia (29% and 27%), cardiogenic shock (17% and 21%), other shock (11% and 9%), and cardiovascular or cerebrovascular events such as myocardial infarction or stroke (9% and 11%). Surgical complications (e.g. hemorrhage, accidental perforation, suture failure) were recorded in 19% of deaths following cholecystectomy and 13% of deaths following herniotomy. In total, at least one of the investigated complications was coded for 83% of deaths following cholecystectomy and 78% of deaths following herniotomy (Table 4).

Complications and specific interventions by survival status
Complications and specific interventions by survival status
Table 4
Complications and specific interventions by survival status

The Figure displays the crude mortality rates for complications. This shows that almost all the analyzed complications are associated with a substantially worse prognosis for survival. Mortality rates of more than 10% were found for patients with thrombotic, cardiovascular, cerebrovascular, or serious cardiac events; acute kidney failure; pneumonia; sepsis; coagulation-related complications; and peritonitis.

Crude mortality rate stratified by complication
Crude mortality rate stratified by complication
Figure
Crude mortality rate stratified by complication

The analyzed interventions were also recorded more frequently in patients who died than in those who survived: intensive care was recorded for more than half of cholecystectomy patients who died and 37% of herniotomy patients who died. Ventilation lasting more than 24 hours was administered to 44% of those who died following cholecystectomy and 26% of those who died following herniotomy. Blood transfusions of more than six units, which provide indirect evidence of hemorrhage as a complication, were recorded for 18% of patients who died after cholecystectomy and 10% of patients who died after herniotomy. Relaparotomy or repeat surgery was coded for 11% of deaths following cholecystectomy and 5% of deaths following herniotomy. Resuscitation was performed on 18% of cholecystectomy patients who died and 23% of herniotomy patients who died.

Autopsies were documented for 0.4% of deaths following cholecystectomy and 0.5% of deaths following herniotomy (Table 4).

Discussion

Despite the rarity of these events, the nationwide German database used for this study allowed more than 4000 deaths to be analyzed and compared to 1.75 million surviving patients. This large number of cases made it possible to show common characteristics of patients who died and to investigate the effect of coded comorbidities on the risk of in-hospital death.

In this study comorbidities are identified solely on the basis of corresponding diagnoses being recorded in inpatient data records. As coding of a comorbidity implies that personnel were aware of it during clinical treatment, there may be potential for optimization using a risk-adapted approach in indication, preparation for surgery, and perioperative and postoperative care.

Most comorbidities examined here were associated with a significant increase in the risk of death. The effects of, for example, cardiovascular diseases; chronic lung, liver, or kidney disease; and malnutrition on the risk of complications or death following surgery, including visceral surgery, are well documented in the literature (79). Identifying such risks is therefore a central part of preoperative preparation (13). Accurate medical history taking and careful physical examination are the basis for identification of diseases that have not previously been detected or have not been adequately treated and affect perioperative risk (14, 15). To the extent that these are factors that can be altered, and if surgery is not so urgent as to make this impossible, preoperative optimization can reduce the risk of complications. This concerns, for example, nutrition therapy for malnourished patients (16, 17) and optimization of treatment for heart failure (18).

Analysis of complications and interventions indicates that there may be potential for optimizing the management of complications (19). This concerns prevention or early identification and adequate treatment of nosocomial infections (20), cardiac events (21), kidney injury (22), and other conditions. In addition, the results of our study suggest that there are further aspects of patient safety in which action is required in German healthcare (23). For example, the frequency of coded surgical complications and blood transfusions in patients who died indicates that it may be possible to improve safety in surgery still further. An effective tool for preventing intraoperative complications and reducing mortality in patients undergoing surgery is surgical safety checklists (24), comprehensive use of which is recommended for all surgeries (25). Regular morbidity and mortality conferences at which the treatment team analyzes unexpected deaths or complications are also seen as the standard for perioperative medicine (26).

As far as can be determined on the basis of comparable publications, in-hospital mortality following cholecystectomy and herniotomy is no higher in Germany than in other industrialized countries. In-hospital mortality for laparoscopic cholecystectomy is 0.5% in the USA, for example (27). In Denmark, 30-day mortality rates of 0.35% for cholecystectomy (28) and 0.5% in herniotomy (29) were reported. The results of this analysis do indicate, however, that mortality related to these surgeries in Germany could be reduced. This is also suggested by the findings of statutory external quality assurance for cholecystectomy: in 2013 deaths were identified despite a low mortality risk in 169 hospitals (30).

Limitations

The characteristics analyzed here may be biased by erroneous or selective diagnosis coding. It is therefore possible, for example, that comorbidities are more likely to be perceived when treatment is complicated and are therefore coded more frequently in patients who died than in those who survived. This kind of bias would lead to an overestimate of the association between comorbidities and risk of death.

Conclusion

Deaths are strongly associated with coded comorbidities that are usually identifiable before surgery, even for routine surgeries such as cholecystectomy and herniotomy that are low in complexity and usually scheduled. Unlike in high-risk surgeries, because such deaths are rare in individual hospitals awareness of such patient-specific risk factors in such apparently simple surgeries may not always be sufficient. In addition to determining patient-specific risks on the basis of patients’ medical history as a requirement for risk-adapted treatment planning, preparation, and execution, there may be potential for improving the management of complications.

Reducing mortality for herniotomy and cholecystectomy would save only a few lives in absolute terms. For the patients, however, who usually consider a herniotomy or cholecystectomy low risk surgery, appropriate steps would contribute substantially to reducing their individual risk. In addition, measures to prevent deaths might reduce complication rates as well as mortality and therefore improve overall patient safety.

Conflict of interest statement

The Department of Structural Advancement and Quality Management in Health Care, for which the authors work, is an endowed professorship of Helios Kliniken GmbH.

Manuscript received on 20 August 2014, revised version accepted on
29 April 2015.

Translated from the original German by Caroline Shimakawa-Devitt, M.A.

Corresponding author:
Ulrike Nimptsch
Technische Universität Berlin, Fachgebiet Strukturentwicklung
und Qualitätsmanagement im Gesundheitswesen
Steinplatz 2, 10623 Berlin, Germany
ulrike.nimptsch@tu-berlin.de

@Supplementary material
eTables:
www.aerzteblatt-international.de/15m0535

1.
Nimptsch U, Mansky T: Krankheitsspezifische Versorgungsmerkmale in Deutschland: Analyse anhand der Bundesauswertung der German Inpatient Quality Indicators (G-IQI). Dtsch Med Wochenschr 2012; 137: 1449–57 CrossRef MEDLINE
2.
Burgard G: Low Risk Operationen bei High Risk Patienten. In: Krahwinkel W, Meier-Hellmann A, Zacher J: Peer Review. Sicher ist besser. Medizinisch Wissenschaftliche Verlagsgesellschaft: Berlin 2013; 49–56.
3.
Frieling T: Cholecystektomie bei Leberzirrhose – eine Hochrisikokonstellation. In: Krahwinkel W, Meier-Hellmann A, Zacher J: Peer Review. Sicher ist besser. Berlin: Medizinisch Wissenschaftliche Verlagsgesellschaft 2013; 145–147.
4.
Forschungsdatenzentren der statistischen Ämter des Bundes und der Länder: Datenangebot | Fallpauschalenbezogene Krankenhausstatistik (DRG-Statistik). Wiesbaden: Forschungsdatenzentren der statistischen Ämter des Bundes und der Länder. www.forschungsdatenzentren.de/bestand/drg/index.asp (last accessed on 15 May 2015).
5.
Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Medical Care 1998; 36: 8–27 CrossRef
6.
AOK-Bundesverband, Forschungs- und Entwicklungsinstitut für das Sozial- und Gesundheitswesen Sachsen-Anhalt (FEISA), Helios Kliniken, Wissenschaftliches Institut der AOK (WIdO): Qualitätssicherung der stationären Versorgung mit Routinedaten (QSR) – Abschlussbericht. Bonn: WIdO 2007.
7.
Shah N, Hamilton M: Clinical review: Can we predict which patients are at risk of complications following surgery? Crit Care 2013; 17: 226 CrossRef MEDLINE PubMed Central
8.
Grade M, Quintel M, Ghadimi M: Standard perioperative management in gastrointestinal surgery. Langenbecks Arch Surg 2011; 396: 591–606 CrossRef MEDLINE PubMed Central
9.
Kuppinger D, Hartl WH, Bertok M, et al.: Nutritional screening for risk prediction in patients scheduled for abdominal operations. Br J Surg 2012; 99: 728–37 CrossRef MEDLINE
10.
Hanley JA, Negassa A, Edwardes MD, Forrester JE: Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol 2003; 157: 364–75 CrossRef
11.
Cook NR: Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007; 115: 928–35 CrossRef MEDLINE
12.
LaValley MP: Statistical primer for cardiovascular research. Logistic regression. Circulation 2008; 117: 2395–9 CrossRef MEDLINE
13.
Reppel M, Weil J: Einschränkung der Operationsfähigkeit. Was muss der Internist wissen? Internist 2010; 51:442–50 CrossRef MEDLINE
14.
Böhmer AB, Wappler F, Zwißler B: Assessing preoperative risk—from routine tests to individualized investigation. Dtsch Arztebl Int 2014; 111: 437–46 VOLLTEXT
15.
Deutsche Gesellschaft für Anästhesiologie und Intensivmedizin, Deutsche Gesellschaft für Innere Medizin, Deutsche Gesellschaft für Chirurgie: Präoperative Evaluation erwachsener Patienten vor elektiven, nichtkardiochirurgischen Eingriffen. Kardiologe 2011; 5: 13–26 CrossRef
16.
Khatib-Chahidi K, Troja A, Kramer M, Klompmaker M, Raab HR, Antolovic D: Präoperatives Management bei Mangelernährten in der Viszeralchirurgie. Chirurg 2014; 85: 520–8 CrossRef MEDLINE
17.
Gustafsson UO, Ljungqvist O: Perioperative nutritional management in digestive tract surgery. Curr Opin Clin Nutr Metab Care 2011; 14: 504–9 CrossRef MEDLINE
18.
Upshaw J, Kiernan MS: Preoperative cardiac risk assessment for noncardiac surgery in patients with heart failure. Curr Heart Fail Rep 2013; 10: 147–56 CrossRef MEDLINE
19.
Ghaferi AA, Birkmeyer JD, Dimick JB: Variation in hospital mortality associated with inpatient surgery. N Engl J Med 2009; 361: 1368–75 CrossRef MEDLINE
20.
Gastmeier P, Brunkhorst F, Schrappe M, Kern W, Geffers C: Wie viele nosokomiale Infektionen sind vermeidbar? Dtsch Med Wochenschr 2010; 135: 91–3 CrossRef MEDLINE
21.
Devereaux PJ, Goldman L, Yusuf S, Gilbert K, Leslie K, Guyatt GH: Surveillance and prevention of major perioperative ischemic cardiac events in patients undergoing noncardiac surgery: a review. CMAJ 2005; 173: 779–88 CrossRef MEDLINE PubMed Central
22.
Brienza N, Giglio MT, Marucci M: Preventing acute kidney injury after noncardiac surgery. Curr Opin Crit Care 2010; 16: 353–8 CrossRef MEDLINE
23.
Hölscher UM, Gausmann P, Haindl H, et al.: Patientensicherheit als nationales Gesundheitsziel: Status und notwendige Handlungsfelder für die Gesundheitsversorgung in Deutschland. Z Evid Fortbild Qual Gesundhwes 2014; 108: 6–14 CrossRef MEDLINE
24.
Haynes AB, Weiser TG, Safe Surgery Saves Lives Study Group, et al.: A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med 2009; 360: 491–9 CrossRef MEDLINE
25.
Fudickar A, Hörle K, Wiltfang J, Bein B: The effect of the WHO Surgical Safety Checklist on complication rate and communication. Dtsch Arztebl Int 2012; 109: 695−701 VOLLTEXT
26.
Richter A: Chirurgische Standards der perioperativen Patientenbehandlung. Chirurg 2012; 83: 343–50 CrossRef MEDLINE
27.
Murphy MM, Ng SC, Simons JP, Csikesz NG, Shah SA, Tseng JF: Predictors of major complications after laparoscopic cholecystectomy: surgeon, hospital, or patient? J Am Coll Surg 2010; 211: 73–80 CrossRef MEDLINE
28.
Harboe KM, Bardram L: Nationwide quality improvement of cholecystectomy: results from a national database. Int J Qual Health Care 2011; 23: 565–73 CrossRef MEDLINE
29.
Helgstrand F, Rosenberg J, Kehlet H, Jorgensen LN, Bisgaard T: Nationwide prospective study of outcomes after elective incisional hernia repair. J Am Coll Surg 2013; 216: 217–28 CrossRef MEDLINE
30.
AQUA – Institut für angewandte Qualitätsförderung und Forschung im Gesundheitswesen GmbH: Qualitätsreport 2013. AQUA-Institut: Göttingen 2014; 17.
Department of Structural Advancement and Quality Management in Health Care, Technische Universität Berlin: Ulrike Nimptsch, Prof. Dr. med. Mansky
Crude mortality rate stratified by complication
Crude mortality rate stratified by complication
Figure
Crude mortality rate stratified by complication
Key messages
Patient characteristics by year
Patient characteristics by year
Table 1
Patient characteristics by year
Patient characteristics by survival status
Patient characteristics by survival status
Table 2
Patient characteristics by survival status
Crude and adjusted odds ratios for in-hospital death
Crude and adjusted odds ratios for in-hospital death
Table 3
Crude and adjusted odds ratios for in-hospital death
Complications and specific interventions by survival status
Complications and specific interventions by survival status
Table 4
Complications and specific interventions by survival status
Case definition
Case definition
eTable 1
Case definition
Definition of variables
Definition of variables
eTable 2
Definition of variables
Crude mortality rates stratified by patient characteristics
Crude mortality rates stratified by patient characteristics
eTable 3
Crude mortality rates stratified by patient characteristics
1.Nimptsch U, Mansky T: Krankheitsspezifische Versorgungsmerkmale in Deutschland: Analyse anhand der Bundesauswertung der German Inpatient Quality Indicators (G-IQI). Dtsch Med Wochenschr 2012; 137: 1449–57 CrossRef MEDLINE
2.Burgard G: Low Risk Operationen bei High Risk Patienten. In: Krahwinkel W, Meier-Hellmann A, Zacher J: Peer Review. Sicher ist besser. Medizinisch Wissenschaftliche Verlagsgesellschaft: Berlin 2013; 49–56.
3.Frieling T: Cholecystektomie bei Leberzirrhose – eine Hochrisikokonstellation. In: Krahwinkel W, Meier-Hellmann A, Zacher J: Peer Review. Sicher ist besser. Berlin: Medizinisch Wissenschaftliche Verlagsgesellschaft 2013; 145–147.
4.Forschungsdatenzentren der statistischen Ämter des Bundes und der Länder: Datenangebot | Fallpauschalenbezogene Krankenhausstatistik (DRG-Statistik). Wiesbaden: Forschungsdatenzentren der statistischen Ämter des Bundes und der Länder. www.forschungsdatenzentren.de/bestand/drg/index.asp (last accessed on 15 May 2015).
5.Elixhauser A, Steiner C, Harris DR, Coffey RM: Comorbidity measures for use with administrative data. Medical Care 1998; 36: 8–27 CrossRef
6.AOK-Bundesverband, Forschungs- und Entwicklungsinstitut für das Sozial- und Gesundheitswesen Sachsen-Anhalt (FEISA), Helios Kliniken, Wissenschaftliches Institut der AOK (WIdO): Qualitätssicherung der stationären Versorgung mit Routinedaten (QSR) – Abschlussbericht. Bonn: WIdO 2007.
7.Shah N, Hamilton M: Clinical review: Can we predict which patients are at risk of complications following surgery? Crit Care 2013; 17: 226 CrossRef MEDLINE PubMed Central
8.Grade M, Quintel M, Ghadimi M: Standard perioperative management in gastrointestinal surgery. Langenbecks Arch Surg 2011; 396: 591–606 CrossRef MEDLINE PubMed Central
9.Kuppinger D, Hartl WH, Bertok M, et al.: Nutritional screening for risk prediction in patients scheduled for abdominal operations. Br J Surg 2012; 99: 728–37 CrossRef MEDLINE
10.Hanley JA, Negassa A, Edwardes MD, Forrester JE: Statistical analysis of correlated data using generalized estimating equations: an orientation. Am J Epidemiol 2003; 157: 364–75 CrossRef
11.Cook NR: Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 2007; 115: 928–35 CrossRef MEDLINE
12.LaValley MP: Statistical primer for cardiovascular research. Logistic regression. Circulation 2008; 117: 2395–9 CrossRef MEDLINE
13.Reppel M, Weil J: Einschränkung der Operationsfähigkeit. Was muss der Internist wissen? Internist 2010; 51:442–50 CrossRef MEDLINE
14.Böhmer AB, Wappler F, Zwißler B: Assessing preoperative risk—from routine tests to individualized investigation. Dtsch Arztebl Int 2014; 111: 437–46 VOLLTEXT
15.Deutsche Gesellschaft für Anästhesiologie und Intensivmedizin, Deutsche Gesellschaft für Innere Medizin, Deutsche Gesellschaft für Chirurgie: Präoperative Evaluation erwachsener Patienten vor elektiven, nichtkardiochirurgischen Eingriffen. Kardiologe 2011; 5: 13–26 CrossRef
16.Khatib-Chahidi K, Troja A, Kramer M, Klompmaker M, Raab HR, Antolovic D: Präoperatives Management bei Mangelernährten in der Viszeralchirurgie. Chirurg 2014; 85: 520–8 CrossRef MEDLINE
17.Gustafsson UO, Ljungqvist O: Perioperative nutritional management in digestive tract surgery. Curr Opin Clin Nutr Metab Care 2011; 14: 504–9 CrossRef MEDLINE
18.Upshaw J, Kiernan MS: Preoperative cardiac risk assessment for noncardiac surgery in patients with heart failure. Curr Heart Fail Rep 2013; 10: 147–56 CrossRef MEDLINE
19.Ghaferi AA, Birkmeyer JD, Dimick JB: Variation in hospital mortality associated with inpatient surgery. N Engl J Med 2009; 361: 1368–75 CrossRef MEDLINE
20.Gastmeier P, Brunkhorst F, Schrappe M, Kern W, Geffers C: Wie viele nosokomiale Infektionen sind vermeidbar? Dtsch Med Wochenschr 2010; 135: 91–3 CrossRef MEDLINE
21.Devereaux PJ, Goldman L, Yusuf S, Gilbert K, Leslie K, Guyatt GH: Surveillance and prevention of major perioperative ischemic cardiac events in patients undergoing noncardiac surgery: a review. CMAJ 2005; 173: 779–88 CrossRef MEDLINE PubMed Central
22.Brienza N, Giglio MT, Marucci M: Preventing acute kidney injury after noncardiac surgery. Curr Opin Crit Care 2010; 16: 353–8 CrossRef MEDLINE
23.Hölscher UM, Gausmann P, Haindl H, et al.: Patientensicherheit als nationales Gesundheitsziel: Status und notwendige Handlungsfelder für die Gesundheitsversorgung in Deutschland. Z Evid Fortbild Qual Gesundhwes 2014; 108: 6–14 CrossRef MEDLINE
24.Haynes AB, Weiser TG, Safe Surgery Saves Lives Study Group, et al.: A surgical safety checklist to reduce morbidity and mortality in a global population. N Engl J Med 2009; 360: 491–9 CrossRef MEDLINE
25.Fudickar A, Hörle K, Wiltfang J, Bein B: The effect of the WHO Surgical Safety Checklist on complication rate and communication. Dtsch Arztebl Int 2012; 109: 695−701 VOLLTEXT
26.Richter A: Chirurgische Standards der perioperativen Patientenbehandlung. Chirurg 2012; 83: 343–50 CrossRef MEDLINE
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