Funnel Plots and Their Emerging Application in Surgery

Mayer, Erik; Bottle, Alex; Rao, Christopher; Darzi, Ara; Athanasiou, Thanos

doi:10.1097/sla.0b013e31819a47b1

Cited by 51 publications

(35 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We used a funnel plot to explore the relationship between total surgeon case load and PAL rate, 17 including control limits (95% and 99% confidence intervals) around the average PAL rate in our study. Because unadjusted case volume does not account for variations in patient populations between surgeons, we developed risk-adjusted models for surgeon annual case load effect, adjusting for case mix and clustering.…”

Section: Methodsmentioning

confidence: 99%

A clinical prediction model for prolonged air leak after pulmonary resection

Attaar

Winger

Luketich

et al. 2017

The Journal of Thoracic and Cardiovascular Surgery

View full text Add to dashboard Cite

Objective Prolonged air leak increases cost and worsens outcomes after pulmonary resection. We aimed to develop a clinical prediction tool for prolonged air leak using pretreatment and intraoperative variables. Methods Patients who underwent pulmonary resection for lung cancer/nodules (1/2009-6/2014) were stratified by prolonged parenchymal air leak (>5 days). Using backward stepwise logistic regression with bootstrap resampling for internal validation, candidate variables were identified and a nomogram risk calculator developed. Results A total of 2317 patients underwent pulmonary resection for lung cancer/nodules. Prolonged air leak (8.6%, n=200) was associated with significantly longer hospital stay (median 10 versus 4 days; p<0.001). Final model variables associated with increased risk included low percent forced expiratory volume in 1 second, smoking history, bilobectomy, higher annual surgeon caseload, prior chest surgery, Zubrod score>2, and interaction terms for right-sided thoracotomy and wedge-resection by thoracotomy. Wedge resection, higher body mass index, and unmeasured percent forced expiratory volume in 1 second were protective. Derived nomogram discriminatory accuracy was 76% (95% CI 0.72–0.79) and facilitated patient stratification into low, intermediate and high risk groups with monotonic increase in observed prolonged air leaks (2.0%; 8.9 %; and 19.2%, respectively; p-value<0.001). Intermediate and high risk patients were 4.80 (95% CI 2.86–8.07) and 11.86 times (95% CI 7.21–19.52) more likely to have prolonged air leak compared to low risk patients. Conclusions Using readily available candidate variables, our nomogram predicts increasing risk of prolonged air leak with good discriminatory ability. Risk stratification can support surgical decision-making, and help initiate proactive, patient-specific surgical management.

show abstract

Section: Methodsmentioning

confidence: 99%

A clinical prediction model for prolonged air leak after pulmonary resection

Attaar

Winger

Luketich

et al. 2017

The Journal of Thoracic and Cardiovascular Surgery

View full text Add to dashboard Cite

show abstract

“…Funnel plots are a graphical method of representing performance data in healthcare 24 . Structural characteristics of high-and low-mortality outlying NHS hospital Trusts (those exceeding, and falling below, the second standard deviation confidence limits) were compared to identify differences that might account for any variability in risk-adjusted mortality.…”

Section: Discussionmentioning

confidence: 99%

Mortality in high-risk emergency general surgical admissions

Symons¹,

Moorthy²,

Almoudaris³

et al. 2013

British Journal of Surgery

168

135

View full text Add to dashboard Cite

Background: There is increasing evidence of variable standards of care for patients undergoing emergency general surgery in the National Health Service (NHS). The aim of this study was to quantify and explore variability in mortality amongst high-risk emergency general surgery admissions to English NHS hospital Trusts. Methods:The Hospital Episode Statistics (HES) database was used to identify high-risk emergency general surgery diagnoses (greater than 5 per cent national 30-day mortality rate). Adults admitted to English NHS Trusts with these diagnoses between 2000 and 2009 were included in the study. Thirty-day in-hospital mortality was adjusted for patient and hospital factors. Trusts were grouped into high-and low-mortality outliers, and resource availability was compared between high-and low-mortality outlier institutions. Results: Some 367 796 patients admitted to 145 hospital Trusts were included in the study; the 30-day mortality rate was 15·6 per cent (institutional range 9·2-18·2 per cent). Fourteen and 24 hospitalTrusts were identified as high-and low-mortality outlier institutions respectively. Intensive care and high-dependency bed resources, as well as greater institutional use of computed tomography (CT), were independent predictors of reduced mortality (P < 0·001). Low-mortality outlying Trusts had significantly more intensive care beds per 1000 hospital beds (20·8 versus 14·0; P = 0·017) and made significantly greater use of CT (24·6 versus 17·2 scans per bed per year; P < 0·001) and ultrasonography (42·5 versus 30·2 scans per bed per year; P < 0·001). Conclusion:There is significant variability in mortality risk between hospital Trusts treating highrisk emergency general surgery patients. Equitable access to essential hospital resources may reduce variability in outcomes.

show abstract

“…We compared the sets of RRs using linear and non-linear correlation. As funnel plots are increasingly used to identify providers with unusually 'good' or 'poor' performance, 34,35 we noted that the number and proportion of hospitals with outcome rates beyond 95% and 99.8% control limits. This was done for each outcome and patient group.…”

Section: Methods Specific To Objectivementioning

confidence: 99%

Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study

Bottle

Honeyford

Chowdhury

et al. 2018

Health Serv Deliv Res

Self Cite

View full text Add to dashboard Cite

BackgroundHeart failure (HF) and chronic obstructive pulmonary disease (COPD) lead to unplanned hospital activity, but our understanding of what drives this is incomplete.ObjectivesTo model patient, primary care and hospital factors associated with readmission and mortality for patients with HF and COPD, to assess the statistical performance of post-discharge emergency department (ED) attendance compared with readmission metrics and to compare all the results for the two conditions.DesignObservational study.SettingEnglish NHS.ParticipantsAll patients admitted to acute non-specialist hospitals as an emergency for HF or COPD.InterventionsNone.Main outcome measuresOne-year mortality and 30-day emergency readmission following the patient’s first unplanned admission (‘index admission’) for HF or COPD.Data sourcesPatient-level data from Hospital Episodes Statistics were combined with publicly available practice- and hospital-level data on performance, patient and staff experience and rehabilitation programme website information.ResultsOne-year mortality rates were 39.6% for HF and 24.1% for COPD and 30-day readmission rates were 19.8% for HF and 16.5% for COPD. Most patients were elderly with multiple comorbidities. Patient factors predicting mortality included older age, male sex, white ethnicity, prior missed outpatient appointments, (long) index length of hospital stay (LOS) and several comorbidities. Older age, missed appointments, (short) LOS and comorbidities also predicted readmission. Of the practice and hospital factors we considered, only more doctors per 10 beds [odds ratio (OR) 0.95 per doctor;p < 0.001] was significant for both cohorts for mortality, with staff recommending to friends and family (OR 0.80 per unit increase;p < 0.001) and number of general practitioners (GPs) per 1000 patients (OR 0.89 per extra GP;p = 0.004) important for COPD. For readmission, only hospital size [OR per 100 beds = 2.16, 95% confidence interval (CI) 1.34 to 3.48 for HF, and 2.27, 95% CI 1.40 to 3.66 for COPD] and doctors per 10 beds (OR 0.98;p < 0.001) were significantly associated. Some factors, such as comorbidities, varied in importance depending on the readmission diagnosis. ED visits were common after the index discharge, with 75% resulting in admission. Many predictors of admission at this visit were as for readmission minus comorbidities and plus attendance outside the day shift and numbers of admissions that hour. Hospital-level rates for ED attendance varied much more than those for readmission, but the omega statistics favoured them as a performance indicator.LimitationsData lacked direct information on disease severity and ED attendance reasons; NHS surveys were not specific to HF or COPD patients; and some data sets were aggregated.ConclusionsFollowing an index admission for HF or COPD, older age, prior missed outpatient appointments, LOS and many comorbidities predict both mortality and readmission. Of the aggregated practice and hospital information, only doctors per bed and numbers of hospital beds were strongly associated with either outcome (both negatively). The 30-day ED visits and diagnosis-specific readmission rates seem to be useful performance indicators.Future workHospital variations in ED visits could be investigated using existing data despite coding limitations. Primary care management could be explored using individual-level linked databases.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

show abstract

Funnel Plots and Their Emerging Application in Surgery

Cited by 51 publications

References 27 publications

A clinical prediction model for prolonged air leak after pulmonary resection

A clinical prediction model for prolonged air leak after pulmonary resection

Mortality in high-risk emergency general surgical admissions

Factors associated with hospital emergency readmission and mortality rates in patients with heart failure or chronic obstructive pulmonary disease: a national observational study

Contact Info

Product

Resources

About