Present-at-admission diagnoses improve mortality risk adjustment and allow more accurate assessment of the relationship between volume of lung cancer operations and mortality risk

Lung cancer mortality and associated predictors: systematic review using 32 scientific research findings

Background

Cancer is a chronic disease brought on by mutations to the genes that control our cells' functions and become the most common cause of mortality and comorbidities. Thus, this study aimed to assess the comprehensive and common mortality-related risk factors of lung cancer using more than thirty scientific research papers.

Methods

Possible risk factors contributing to lung cancer mortality were assessed across 201 studies sourced from electronic databases, including Google Scholar, Cochrane Library, Web of Science (WOS), EMBASE, Medline/PubMed, the Lung Cancer Open Research Dataset Challenge, and Scopus. Out of these, 32 studies meeting the eligibility criteria for meta-analysis were included. Due to the heterogeneous nature of the studies, a random-effects model was applied to estimate the pooled effects of covariates.

Results

The overall prevalence of mortality rate was 10% with a 95% confidence interval of 6 and 16%. Twenty studies (62.50%) studies included in this study considered the ages of lung cancer patients as the risk factors for mortality. Whereas, eighteen (56.25%) and thirteen (40.63%) studies incorporated the gender and smoking status of patients respectively. The comorbidities of lung cancer mortality such as cardiovascular disease, hypertension, diabetes, and pneumonia were also involved in 7 (21.90%), 6 (18.75%), 5 (15.63%), and 2 (6.25%) studies, respectively. Patients of older age are more likely to die as compared to patients of younger age. Similarly, lung patients who had smoking practice were more likely to die as compared to patients who hadn't practiced smoking.

Conclusion

The mortality rate of lung cancer patients is considerably high. Older age, gender, stage, and comorbidities such as cardiovascular, hypertension, and diabetes have a significant positive effect on lung cancer mortality. The study results will contribute to future research, management, and prevention strategies for lung cancer.

Short-term adjusted outcomes for heart failure

PURPOSE

Heart failure (HF) is recognized as a major problem in industrialized countries. Short-term adjusted outcomes are indicators of quality for care process during/after hospitalization. Our aim is to evaluate, for patients with principal diagnosis of HF, in-hospital mortality and 30-day readmissions for all-causes using two different risk adjustment (RA) tools.

METHODS AND RESULTS

We used data from the hospital discharge abstract (HD) of a retrospective cohort of patients (2002-2007) admitted in Tuscan hospitals, Italy. Considered outcomes were in-hospital mortality and readmission at 30 days. We compared the All-Patients Refined Diagnosis Related Groups (APR-DRG) system and the Elixhauser Index (EI). Logistic regression was performed and models were compared using the C statistic (C). examined records were 58.202. Crude in-hospital mortality was 9.7%. Thirty-day readmission was 5.1%. The APR-DRG class of risk of death (ROD) was a predictive factor for in-hospital mortality; the APR-DRG class of severity was not significantly associated with 30-day readmissions (P>0.05). EI comorbidities which were more strongly associated with outcomes were nonmetastatic cancer for in-hospital mortality (odds ratio, OR 2.25, P<0.001), uncomplicated and complicated diabetes for 30-day hospital readmissions (OR 1.20 and 1.34, P<0.001). The discriminative abilities for in-hospital mortality were sufficient for both models (C 0.67 for EI, C 0.72 for APR-DRG) while they were low for 30-day readmissions rate (C 0.53 and 0.52).

CONCLUSIONS

Age, gender, APR-DRG ROD and some Elixhauser comorbidities are predictive factors of outcomes; only the APR-DRG showed an acceptable ability to predict hospital mortality while none of them was satisfactory in predicting the readmissions within 30 days.

Capturing diagnosis-timing in ICD-coded hospital data: recommendations from the WHO ICD-11 topic advisory group on quality and safety

PURPOSE

To develop a consensus opinion regarding capturing diagnosis-timing in coded hospital data.

METHODS

As part of the World Health Organization International Classification of Diseases-11th Revision initiative, the Quality and Safety Topic Advisory Group is charged with enhancing the capture of quality and patient safety information in morbidity data sets. One such feature is a diagnosis-timing flag. The Group has undertaken a narrative literature review, scanned national experiences focusing on countries currently using timing flags, and held a series of meetings to derive formal recommendations regarding diagnosis-timing reporting.

RESULTS

The completeness of diagnosis-timing reporting continues to improve with experience and use; studies indicate that it enhances risk-adjustment and may have a substantial impact on hospital performance estimates, especially for conditions/procedures that involve acutely ill patients. However, studies suggest that its reliability varies, is better for surgical than medical patients (kappa in hip fracture patients of 0.7-1.0 versus kappa in pneumonia of 0.2-0.6) and is dependent on coder training and setting. It may allow simpler and more precise specification of quality indicators.

CONCLUSIONS

As the evidence indicates that a diagnosis-timing flag improves the ability of routinely collected, coded hospital data to support outcomes research and the development of quality and safety indicators, the Group recommends that a classification of 'arising after admission' (yes/no), with permitted designations of 'unknown or clinically undetermined', will facilitate coding while providing flexibility when there is uncertainty. Clear coding standards and guidelines with ongoing coder education will be necessary to ensure reliability of the diagnosis-timing flag.

Comparative effectiveness of robotically assisted compared with laparoscopic adnexal surgery for benign gynecologic disease

OBJECTIVE

To perform a population-based analysis to compare the complications and cost of laparoscopic and robotically assisted adnexal surgery.

METHODS

A nationwide database was used to analyze the use and outcomes of robotically assisted adnexal surgery from 2009 to 2012. Multivariable mixed effects regression models were developed to examine predictors of use of robotic surgery. After propensity score matching, complications and cost were compared between robotically assisted and laparoscopic surgery.

RESULTS

Eighty-seven thousand five hundred fourteen women were identified. From 2009 to 2012, performance of robotic-assisted oophorectomy increased from 3.5% (95% confidence interval [CI] 3.2-3.8%) to 15.0% (95% CI 14.4-15.6%), whereas robotically assisted cystectomy rose from 2.4% (95% CI 2.0-2.7%) to 12.9% (95% CI 12.2-13.5%). The overall complication rate was 7.1% (95% CI 4.0-10.2%) for robotically assisted compared with 6.0% (95% CI 2.9-9.1%) for laparoscopic oophorectomy (odds ratio [OR] 1.20, 95% CI 1.00-1.45; P=.052). Robotic-assisted oophorectomy was associated with a higher rate of intraoperative complications (3.4% compared with 2.1%, OR 1.60, 95% CI 1.21-2.13). The overall complication rate was 3.7% (95% CI -0.8 to 8.2%) after robotically assisted compared with 2.7% (95% CI -1.8 to 7.2%) for laparoscopic cystectomy (OR 1.38, 95% CI 0.95-1.99). The intraoperative complication rate was higher for robotically assisted cystectomy (2.0% compared with 0.9%, OR 2.40, 95% CI 1.31-4.38). Compared with laparoscopy, robotically assisted oophorectomy was associated with $2,504 (95% CI $2,356-2,652) increased total costs and robotically assisted cystectomy $3,310 (95% CI $3,082-3,581) higher costs.

CONCLUSION

Use of robotically assisted adnexal surgery increased rapidly. Compared with laparoscopic surgery, robotically assisted adnexal surgery is associated with substantially greater costs and a small, but statistically significant, increase in intraoperative complications.

The challenge of achieving 1% operative mortality for coronary artery bypass grafting: a multi-institution Society of Thoracic Surgeons Database analysis

OBJECTIVES

Cardiothoracic surgical leadership recently challenged the surgical community to achieve an operative mortality rate of 1.0% for the performance of isolated coronary artery bypass grafting (CABG). The possibility of achieving this goal remains unknown due to the increasing number of high-risk patients being referred for CABG. The purpose of our study was to identify a patient population in which this operative mortality goal is achievable relative to the estimated operative risk.

METHODS

Patient records from a multi-institution (17 centers) Society of Thoracic Surgeons (STS) database for primary, isolated CABG operations (2001-2012) were analyzed. Multiple logistic regression modeling with spline functions for calculated STS predicted risk of mortality (PROM) was used to rigorously assess the relationship between estimated patient risk and operative mortality, adjusted for operative year and surgeon volume.

RESULTS

A total of 34,416 patients (average patient age, 63.9 ± 10.7 years; 27% [n = 9190] women) incurred an operative mortality rate of 1.87%. Median STS predicted risk of mortality was 1.06% (interquartile range, 0.60%-2.13%) and median surgeon CABG volume was 544 (interquartile range, 303-930) operations over the study period. After risk adjustment for the confounding influence of surgeon volume and operative year, the association between STS PROM and operative mortality was highly significant (P < .0001). More importantly, the adjusted spline function revealed that an STS PROM threshold value of 1.27% correlated with a 1.0% probability of death, accounting for 57.3% (n = 19,720) of the total study population. Further, the STS PROM demonstrated a limited predictive capacity for operative mortality for STS PROM > 25% as observed to expected mortality began to diverge.

CONCLUSIONS

Achieving the goal of 1.0% operative mortality for primary, isolated CABG is feasible in appropriately selected patients in the modern surgical era. However, this goal may be achieved in only 60% of CABG patients without other improvements in processes of care. Calculated STS PROM can be used to strongly identify patients with estimated mortality risk <1.27% to achieve this goal, but it appears limited in its predictive capacity for those patients with estimated risk >25.0%. These data provide a foundation for further study to determine if 1.0% mortality for CABG is achievable nationwide.

Incidence, predictors, and outcomes associated with postoperative atrial fibrillation after major noncardiac surgery

BACKGROUND

Although major noncardiac surgery is common, few large-scale studies have examined the incidence and consequences of post-operative atrial fibrillation (POAF) in this population. We sought to define the incidence of POAF and its impact on outcomes after major noncardiac surgery.

METHODS

Using administrative data, we retrospectively reviewed the hospital course of adults who underwent major noncardiac surgery at 375 US hospitals over a 1-year period. Clinically significant POAF was defined as atrial fibrillation occurring during hospitalization that necessitated therapy.

RESULTS

Of 370,447 patients, 10,957 (3.0%) developed clinically significant POAF while hospitalized. Of patients with POAF, 7,355 (67%) appeared to have pre-existing atrial fibrillation and 3,602 (33%) had newly diagnosed atrial fibrillation. Black patients had a lower risk of POAF (adjusted odds ratio, 0.53; 95% CI, 0.48-0.59; P < .001). Patients with POAF had higher mortality (adjusted odds ratio, 1.72; 95% CI, 1.59-1.86; P < .001), markedly longer length of stay (adjusted relative difference, +24.0%; 95% CI, +21.5% to +26.5%; P < .001), and higher costs (adjusted difference, +$4,177; 95% CI, +$3,764 to +$4,590; P < .001). These findings did not differ by whether POAF was a recurrence of pre-existing atrial fibrillation, or a new diagnosis.

CONCLUSION

POAF following noncardiac surgery is not uncommon and is associated with increased mortality and cost. Our study identifies risk factors for POAF, which appear to include race. Strategies are needed to not only prevent new POAF, but also improve management of patients with pre-existing atrial fibrillation.

The relationship between hospital lung cancer resection volume and patient mortality risk

OBJECTIVE

To evaluate the volume-outcome relationship after lung cancer resection using 3 alternative measures of the effect of volume.

SUMMARY BACKGROUND DATA

Many studies of lung cancer resection indicate that hospital volume predicts mortality. However, controversy exists regarding the strength and validity of this association. Because thresholds of procedure volume are used to recommend the regionalization of care, investigation of the validity of the volume-outcome relationship is necessary.

METHODS

Lung cancer resection patients were identified in the 2007 Nationwide Inpatient Sample. Hospital volume was measured using 3 different methods: as a continuous linear function, as a nonlinear function using restricted cubic splines, and as the frequently used method of quintile categories. The statistical significance of the relationship between hospital volume and mortality risk was assessed, adjusted for patient age, comorbid disease, and for correlated events within hospitals.

RESULTS

Forty thousand four hundred and sixty lung cancer resection patients from 436 hospitals were identified. All 3 models demonstrated excellent performance characteristics (C index = 0.92, Nagelkerke R = 0.37). No significant association was demonstrated between hospital procedure volume and in-hospital mortality when measured as a linear or nonlinear function using splines. However, a statistically significant relationship was found for volume categorized into quintiles, although its relative contribution to the predictive capacity of the model was very small (likelihood ratio = 2.55, P = 0.04).

CONCLUSIONS

The apparent impact of hospital lung cancer resection volume on mortality is dependent on how volume is defined and entered into the regression equation. Hospital lung cancer resection volume is not a predictor of mortality and should not be used as a proxy measure for surgical quality.

Statin use and postoperative atrial fibrillation after major noncardiac surgery

BACKGROUND

Although statin lipid-lowering medications likely reduce perioperative ischemic complications, few data exist to describe statins' effects on risk for and outcomes of atrial fibrillation following noncardiac surgery.

OBJECTIVE

To examine the association between treatment with statin medications and clinically significant postoperative atrial fibrillation (POAF) following major noncardiac surgery.

METHODS

A retrospective cohort study of patients aged 18 years or older who underwent major noncardiac surgery between January 1, 2008, and December 31, 2008. Cases of clinically significant POAF were selected by using a combination of International Classification of Diseases-9 codes and clinical variables. We defined statin users as those whose pharmacy data included a charge for a statin drug on the day of surgery, the day after surgery, or both.

RESULTS

Of 370,447 patients, 10,957 (3.0%) developed clinically significant POAF; overall, 79,871 (21.6%) received a perioperative statin. Patients receiving statins were generally older (68.8 vs 61.1 years; P <.001) and more likely to be receiving a beta-blocker (50.3% vs 21.6%; P < .001). Statin use was associated with a lower unadjusted rate of POAF (2.6% vs 3.0%; P < .001). After adjustment for patient risk factors and surgery type, odds for POAF remained significantly lower among statin-treated patients (adjusted odds ratio = 0.79; 95% confidence interval = 0.71-0.87; P < .001). Statin use was not associated with differences in cost, length of stay, or mortality among patients who developed POAF.

CONCLUSION

Treatment with statin agents appears to be associated with a lower risk for clinically significant POAF following major noncardiac surgery.

The accuracy of present-on-admission reporting in administrative data

OBJECTIVE

To test the accuracy of reporting present-on-admission (POA) and to assess whether POA reporting accuracy differs by hospital characteristics.

DATA SOURCES

We performed an audit of POA reporting of secondary diagnoses in 1,059 medical records from 48 California hospitals.

STUDY DESIGN

We used patient discharge data (PDD) to select records with secondary diagnoses that are powerful predictors of mortality and could potentially represent comorbidities or complications among patients who either had a primary procedure of a percutaneous transluminal coronary angioplasty or a primary diagnosis of acute myocardial infarction, community-acquired pneumonia, or congestive heart failure. We modeled the relationship between secondary diagnoses POA reporting accuracy (over-reporting and under-reporting) and hospital characteristics.

DATA COLLECTION

We created a gold standard from blind reabstraction of the medical records and compared the accuracy of the PDD against the gold standard.

PRINCIPAL FINDINGS

The PDD and gold standard agreed on POA reporting in 74.3 percent of records, with 13.7 percent over-reporting and 11.9 percent under-reporting. For-profit hospitals tended to overcode secondary diagnoses as present on admission (odds ratios [OR] 1.96; 95 percent confidence interval [CI] 1.11, 3.44), whereas teaching hospitals tended to undercode secondary diagnoses as present on admission (OR 2.61; 95 percent CI 1.36, 5.03).

CONCLUSIONS

POA reporting of secondary diagnoses is moderately accurate but varies by hospitals. Steps should be taken to improve POA reporting accuracy before using POA in hospital assessments tied to payments.

Impact of Diagnosis-Timing Indicators on Measures of Safety, Comorbidity, and Case Mix Groupings From Administrative Data Sources

CONTEXT

Many attempts to identify hospital complications rely on secondary diagnoses from billing data. To be meaningful, diagnosis codes must distinguish between diagnoses after admission and those existing before admission.

OBJECTIVE

To assess the influence of diagnoses at admission on patient safety, comorbidity, severity measures, and case mix groupings for Medicare reimbursement.

DESIGN

Cross-sectional association of various diagnosis-based clinical and performance measures with and without diagnosis present on admission.

SETTING

Hospital discharges from Mayo Clinic Rochester hospitals in 2005 (N = 60,599).

PATIENTS

All hospital inpatients including surgical, medical, pediatric, maternity, psychiatric, and rehabilitation patients. About 33% of patients traveled more than 120 miles for care.

MAIN OUTCOME MEASURES

Hospital patient safety indicators, comorbidity, severity, and case mix measures with and without diagnoses present at admission.

RESULTS

Over 90% of all diagnoses were present at admission whereas 27.1% of all inpatients had a secondary diagnosis coded in-hospital. About one-third of discharges with a safety indicator were flagged because of a diagnosis already present at admission, more likely among referral patients. In contrast, 87% of postoperative hemorrhage, 22% of postoperative hip fractures, and 54% of foreign bodies left in wounds were coded as in-hospital conditions. Severity changes during hospitalization were observed in less than 8% of discharges. Slightly over 3% of discharges were assigned to higher weight diagnosis-related groups based on an in-hospital complication.

CONCLUSIONS

In general, many patient safety indicators do not reliably identify adverse hospital events, especially when applied to academic referral centers. Except as noted, conditions recorded after admission have minimal impact on comorbidity and severity measures or on Medicare reimbursement.

National survey of non-small cell lung cancer in the United States: epidemiology, pathology and patterns of care

PURPOSE

To determine the epidemiology, pathology and patterns of care for patients with non-small cell lung cancer (NSCLC) in the United States.

METHODS

In 2001 the National Cancer Data Base, under direction of the American College of Surgeons, conducted a patient care evaluation study in 719 hospitals. We collected information on patient demographics and histories, diagnostic and staging methods, pathology, and initial treatment.

RESULTS

Information on 40,909 patients was obtained; 93% were smokers. Slightly more than half were older than 70 years; 58.5% were male and 35% had adenocarcinoma. Comorbid conditions were present in 71.8% and 22% had a prior malignancy. A chest CT scan was performed in 92% of patients and PET scans in 19.3%. Mediastinoscopy was performed in 20.3%. 67.2% of patients had Stage III or IV disease. More of the Hispanic, Asian or Black patients than White had Stage IV disease (p<0.01). Treatment was multimodality in a little over 30% of patients. Surgery alone was primarily utilized for patients in Stage I or II. Choice of treatment correlated more with stage and age than comorbidities.

CONCLUSION

Our results substantiated the pattern of increasing proportions of women with NSCLC and the increasing frequency of adenocarcinoma. Most patients presented with Stage III or IV disease. Ethnic minorities were more likely to present in late stage disease than Whites. Treatment strategies depended more on stage and age than comorbid burden. Older patients were less likely to receive surgery and more likely to be treated with radiation only or have no treatment.

Present-at-admission diagnoses improved mortality risk adjustment among acute myocardial infarction patients

OBJECTIVE

Hospital mortality outcomes for acute myocardial infarction (AMI) patients are a focus of quality improvement programs conducted by government agencies. AMI mortality risk-adjustment models using administrative data typically adjust for baseline differences in mortality risk with a limited set of common and definite comorbidities. In this study, we present an AMI mortality risk-adjustment model that adjusts for comorbid disease and for AMI severity using information from secondary diagnoses reported as present at admission for California hospital patients.

STUDY DESIGN AND SETTING

AMI patients were selected from California hospital administrative data for 1996 through 1999 according to criteria used by the California Hospital Outcomes Project Report on Heart Attack Outcomes, a state-mandated public report that compares hospital mortality outcomes. We compared results for the new model to two mortality risk-adjustment models used to assess hospital AMI mortality outcomes by the state of California, and to two other models used in prior research.

RESULTS

The model using present-at-admission diagnoses obtained substantially better discrimination between predicted survival and inpatient death than the other models we considered.

CONCLUSION

AMI mortality risk-adjustment methods can be meaningfully improved using present-at-admission diagnoses to identify comorbid disease and conditions related closely to AMI.