Glenn Arnold

Using quality indicators in anaesthesia: feeding back data to improve care

After recent UK policy developments, considerable attention has been focused upon how clinical specialties measure and report on the quality of care delivered to patients. Defining the right indicators alone is insufficient to close the feedback loop. This narrative review aims to describe and synthesize a diverse body of research relevant to the question of how information from quality indicators can be fed back and used effectively to improve care. Anaesthesia poses certain challenges in the identification of valid outcome indicators sensitive to variations in anaesthetic care. Metrics collected during the immediate post-anaesthetic recovery period, such as patient temperature, patient-reported quality of recovery, and pain and nausea, provide potentially useful information for the anaesthetist, yet this information is not routinely fed back. Reviews of the effects of feeding back performance data to healthcare providers suggest that this may result in small to moderate positive effects upon outcomes and professional practice, with stronger effects where feedback is integrated within a broader quality improvement strategy. The dominant model for use of data within quality improvement is based upon the industrial process control approach, in which care processes are monitored continuously for process changes which are rapidly detectable for corrective action. From this review and experience of implementing these principles in practice, effective feedback from quality indicators is timely, credible, confidential, tailored to the recipient, and continuous. Considerable further work is needed to understand how information from quality indicators can be fed back in an effective way to clinicians and clinical units, in order to support revalidation and continuous improvement.

BIS and Entropy in the elderly.

The interaction of many poorly defined, physiological, pharmacological, and pathological factors make titration of general anaesthesia in the elderly difficult. There may be a potential clinical benefit using the processed electroencephalogram (EEG) to monitor hypnotic level in this population. We prospectively studied 16 patients aged over 65 years having hip fractures repaired under general anaesthesia by experienced anaesthetists blinded to Bispectral Index (BISXP) and Entropy values. Pre‐induction EEG indices did not correlate with age or mini‐mental state examination (MMSE). During maintenance of anaesthesia, BISXP and Response Entropy (RE) values were within the recommended range of 40–60, 45% and 32% of the total time, respectively. BISXP and Response Entropy (RE) values were above 60 for 11% and 13% of the total time, respectively, and below 40 for 44% and 55% of the total time, respectively. BISXP correlated well with RE in 12 patients, but in the other four patients there was a difference of more than 20 points between BISXP and RE.

Developing effective feedback on quality of anaesthetic care: what are its most valuable characteristics from a clinical perspective?

Objectives Research suggests that better feedback from quality and safety indicators leads to enhanced capability of clinicians and departments to improve care and change behaviour. The aim of the current study was to investigate the characteristics of feedback perceived by clinicians to be of most value. Methods Data were collected using a survey designed as part of a wider evaluation of a data feedback initiative in anaesthesia. Eighty-nine consultant anaesthetists from two English NHS acute Trusts completed the survey. Multiple linear regression with hierarchical variable entry was used to investigate which characteristics of feedback predict its perceived usefulness for monitoring variation and improving care. Results The final model demonstrated that the relevance of the quality indicators to the specific service area (β = 0.64, p = 0.01) and the credibility of the data as coming from a trustworthy, unbiased source (β = 0.55, p = 0.01) were the significant predictors, having controlled for all other covariates. Conclusion For clinicians to engage with effective quality monitoring and feedback, the perceived local relevance of indicators and trust in the credibility of the resulting data are paramount.

Continuous monitoring and feedback of quality of recovery indicators for anaesthetists: a qualitative investigation of reported effects on professional behaviour

Background Research suggests that providing clinicians with feedback on their performance can result in professional behaviour change and improved clinical outcomes. Departments would benefit from understanding which characteristics of feedback support effective quality monitoring, professional behaviour change and service improvement. This study aimed to report the experience of anaesthetists participating in a long-term initiative to provide comprehensive personalized feedback to consultants on patient-reported quality of recovery indicators in a large London teaching hospital. Methods Semi-structured interviews were conducted with 13 consultant anaesthetists, six surgical nursing leads, the theatre manager and the clinical coordinator for recovery. Transcripts were qualitatively analysed for themes linked to the perceived value of the initiative, its acceptability and its effects upon professional practice. Results Analysis of qualitative data from participant interviews suggested that effective quality indicators must address areas that are within the control of the anaesthetist. Graphical data presentation, both longitudinal (personal variation over time) and comparative (peer-group distributions), was found to be preferable to summary statistics and provided useful and complementary perspectives for improvement. Developing trust in the reliability and credibility of the data through co-development of data reports with clinical input into areas such as case-mix adjustment was important for engagement. Making feedback specifically relevant to the recipient supported professional learning within a supportive and open collaborative environment. Conclusions This study investigated the requirements for effective feedback on quality of anaesthetic care for anaesthetists, highlighting the mechanisms by which feedback may translate into improvements in practice at the individual and peer-group level.

ENHANCED FEEDBACK FROM PERIOPERATIVE QUALITY INDICATORS: STUDYING THE IMPACT OF A COMPLEX QUALITY IMPROVEMENT INTERVENTION

Introduction Prior to this project, anaesthetists rarely received systematic feedback on the experience of patients in recovery. This could help to improve perioperative practice. Preliminary audits demonstrated variations in patient temperature, pain and nausea measures. Mapping the perioperative workflow revealed that delays in patient transfer from the Post Anaesthetic Care Unit (PACU) was stretching resources and threatening patient experience. We hypothesised that implementing sustained monitoring and feedback of data from perioperative quality indicators using an industrial process control approach would stimulate improvement on key outcomes at individual and system levels. Methods A continuous monitoring and feedback initiative was launched drawing upon improvement science theory and quality improvement methods such as process mapping, iterative development and Statistical Process Control (SPC). Data on core temperature, patient reported pain, nausea and quality of recovery was collected for all elective surgical patients passing through the main surgical suite of a large academic teaching hospital by trained PACU nurses. Monthly reports on ward-transfer times and quality of recovery data were posted in the recovery unit and sent to ward managers to make variations in workflow visible across the care pathway. Personalised monthly reports were developed and distributed to individual consultant anaesthetists to provide detailed longitudinal and normative feedback on performance and details of special cases as an aid to improving use of analgesics and antiemetics, perioperative normothermia and to facilitate personal professional development. A comprehensive parallel evaluation and multiprofessional engagement workstream was undertaken to ensure ownership and acceptability of the initiative. The evaluation used a comprehensive mixed method quasi-experimental design, with a longitudinal qualitative component to capture the experience of users, evaluative surveys at multiple time-points and quantitative analysis using SPC and interrupted time series models to determine impact upon perioperative process and outcome indicators. Results Qualitative and quantitative analysis of the experience of anaesthetists using the feedback demonstrated high perceived value and acceptability of the initiative. A range of critical enablers for this type of intervention were identified from regression analysis, including the local relevance and credibility of the data. Analysis of SPC charts revealed large variation in transfer times between different surgical wards attributable to variations in bed management and staffing practices. Nausea and Pain scores had remained relatively stable at the department level with sub-group analysis revealing variation across individuals, due to case load. Interrupted time series analysis showed a significant increase in the mean temperature of patients arriving in recovery associated with introduction of feedback of temperature data. Discussion This study contributes important learning for both the intervention context and improvement science methods. For clinicians, data feedback that is timely, relevant, credible and acceptable to end users can be used to monitor variations in patient care and support improvement at both the personal and system levels. Findings suggest that the type of data which is often used in hospital governance is too high level for quality improvement purposes and can mask useful information concerning local variation. This project demonstrates the importance of using mixed methods and multiple outcome designs in evaluation of complex improvement interventions, in order to account for context and describe the implementation process alongside intervention outcomes. Declaration of competing interests None.