Reporting individual surgeon outcomes does not lead to risk aversion in abdominal aortic aneurysm surgery

The Effect of Feedback on Surgeon Performance: A Narrative Review

Surgeons play a critical role in the healthcare community and provide a service that can tremendously impact patients' livelihood. However, there are relatively few means for monitoring surgeons' performance quality and seeking improvement. Surgeon-level data provide an important metric for quality improvement and future training. A narrative review was conducted to analyze the utility of providing surgeons direct feedback on their individual performance. The articles selected identified means of collecting surgeon-specific data, suggested ways to report this information, identified pertinent gaps in the field, and concluded the results of giving feedback to surgeons. There is a relative sparsity of data pertaining to the effect of providing surgeons with information regarding their individual performance. However, the literature available does suggest that providing surgeons with individualized feedback can help make meaningful improvements in the quality of practice and can be done in a way that is safe for the surgeons' reputation.

Evaluating quality in clinical care

Defining and maintaining quality is essential to surgical practice. It is only through structured approaches to assessing outcomes that we can ensure that optimal care is delivered. This article will define quality in healthcare and discuss assessment models with reference to pertinent surgical literature. National initiatives are discussed with a critical appraisal of their role and effectiveness. We discuss the aim of quality improvement initiatives and comment on reporting of outcomes. The difficult question of how to maintain quality during a crisis, such as an infectious disease pandemic, is addressed.

Anaerobic threshold as an independent predictor of mid-term survival following elective endovascular repair of abdominal aortic aneurysm

BACKGROUND

The aim of this study was to examine the value preoperative AT as predictor of postoperative survival in patients who underwent elective EVAR for repair of asymptomatic AAA.

METHODS

Consecutive patients who underwent elective EVAR between 2008 and 2018 were analyzed. Cardiopulmonary exercise testing was performed. Perioperative 30-day mortality was compared between patients who had AT ≥8 mL/kg/min and those with AT<8 mL/kg/min. Risk factors for postoperative survival following EVAR were examined using Cox's regression analysis.

RESULTS

Between 1^st January 2008 and 31^st December 2017, 430 patients underwent elective EVAR (standard device: N.=374, fenestrated/branched: N.=56); their median age was 76 years (range: 53-91 years), median AT was 9.3 (range: 5.4-16.1), and 30-day mortality was 0.9%. These patients were followed up for a median of 1630 days. There was no significant difference in perioperative 30-day mortality between patients who had AT≥8 and those who had AT<8 (χ²=1.56, P=0.22). Age (HR=1.51 [CI: 1.07-1.99], P<0.05) and AT (HR=0.59 [CI: 0.45-0.76], P=0.0003) were predictors of reduced postoperative survival following elective EVAR whereas gender (HR=0.75 [CI: 0.4-1.4], P=0.37), AAA diameter (HR=0.95 [CI: 0.77-1.16], P=0.6), and AAA morphology (HR=1.23 [CI: 0.68-1.76], P=0.95) were not.

CONCLUSIONS

Anaerobic threshold is an independent predictor of prolonged survival following elective EVAR and can be used to identify patients who receive most benefit from elective EVAR.

Impact of public release of performance data on the behaviour of healthcare consumers and providers

BACKGROUND

It is becoming increasingly common to publish information about the quality and performance of healthcare organisations and individual professionals. However, we do not know how this information is used, or the extent to which such reporting leads to quality improvement by changing the behaviour of healthcare consumers, providers, and purchasers.

OBJECTIVES

To estimate the effects of public release of performance data, from any source, on changing the healthcare utilisation behaviour of healthcare consumers, providers (professionals and organisations), and purchasers of care. In addition, we sought to estimate the effects on healthcare provider performance, patient outcomes, and staff morale.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, and two trials registers on 26 June 2017. We checked reference lists of all included studies to identify additional studies.

SELECTION CRITERIA

We searched for randomised or non-randomised trials, interrupted time series, and controlled before-after studies of the effects of publicly releasing data regarding any aspect of the performance of healthcare organisations or professionals. Each study had to report at least one main outcome related to selecting or changing care.

DATA COLLECTION AND ANALYSIS

Two review authors independently screened studies for eligibility and extracted data. For each study, we extracted data about the target groups (healthcare consumers, healthcare providers, and healthcare purchasers), performance data, main outcomes (choice of healthcare provider, and improvement by means of changes in care), and other outcomes (awareness, attitude, knowledge of performance data, and costs). Given the substantial degree of clinical and methodological heterogeneity between the studies, we presented the findings for each policy in a structured format, but did not undertake a meta-analysis.

MAIN RESULTS

We included 12 studies that analysed data from more than 7570 providers (e.g. professionals and organisations), and a further 3,333,386 clinical encounters (e.g. patient referrals, prescriptions). We included four cluster-randomised trials, one cluster-non-randomised trial, six interrupted time series studies, and one controlled before-after study. Eight studies were undertaken in the USA, and one each in Canada, Korea, China, and The Netherlands. Four studies examined the effect of public release of performance data on consumer healthcare choices, and four on improving quality.There was low-certainty evidence that public release of performance data may make little or no difference to long-term healthcare utilisation by healthcare consumers (3 studies; 18,294 insurance plan beneficiaries), or providers (4 studies; 3,000,000 births, and 67 healthcare providers), or to provider performance (1 study; 82 providers). However, there was also low-certainty evidence to suggest that public release of performance data may slightly improve some patient outcomes (5 studies, 315,092 hospitalisations, and 7502 providers). There was low-certainty evidence from a single study to suggest that public release of performance data may have differential effects on disadvantaged populations. There was no evidence about effects on healthcare utilisation decisions by purchasers, or adverse effects.

AUTHORS' CONCLUSIONS

The existing evidence base is inadequate to directly inform policy and practice. Further studies should consider whether public release of performance data can improve patient outcomes, as well as healthcare processes.