A model for managing the variability of care processes – A quality improvement method for introducing Enhanced Recovery after Surgery (ERAS) within an orthopaedic elective care clinical microsystem
Authors: Wainwright, T.
Conference: Bournemouth University Faculty of Health and Social Sciences
Abstract:Background and purpose – The National Health Service (NHS) continues to face economic and capacity challenges. Quality improvement (QI) interventions such as Enhanced Recovery after Surgery (ERAS) that can improve clinical and economic outcomes are needed. However, implementation remains a challenge and the widespread adoption of ERAS across the NHS for total hip replacement and total knee replacement is not complete. A novel QI method (the model to manage variability) was developed and is evaluated when utilised to inform improvements to ERAS care processes within clinical microsystems performing hip and knee replacement.
Methods – The model to manage variability was adapted for use as a QI method and then deployed within two orthopaedic elective care clinical microsystems. An improvement replication programme was adopted. In the pilot site (Study 1) a retrospective observational study design was used. In Study 2, the validation site, a prospective observational study design, with a mixed-methods sequential explanatory design (QUAN emphasised) that consisted of two distinct phases was used.
Results – The model for managing variability was successfully deployed and evaluated as a QI method to help implement ERAS within both sites. Length of Stay was reduced by 45% in Study 1, and by 18% in Study 2. The interventions to improve care process highlighted by the QI method were implemented fully in Study 1 but were not able to be fully implemented in Study 2. In Study 2, qualitative data revealed that staff thought the model to manage variability was simple, effective, and had highlighted the correct changes to make. However, they felt that contextual factors around leadership, staffing, and organizational issues had prevented changes being implemented.
Discussion – The model to manage variability was successfully adapted and utilised to improve ERAS care processes within two settings. Users within the validation site felt it had advantages over other QI methods but found improvement efforts were still affected by crucial contextual factors known to influence both QI efforts and ERAS implementation.
https://eprints.bournemouth.ac.uk/36904/
Source: Manual
A model for managing the variability of care processes – A quality improvement method for introducing Enhanced Recovery after Surgery (ERAS) within an orthopaedic elective care clinical microsystem
Authors: Wainwright, T.
Conference: Bournemouth University
Abstract:Background and purpose – The National Health Service (NHS) continues to face economic and capacity challenges. Quality improvement (QI) interventions such as Enhanced Recovery after Surgery (ERAS) that can improve clinical and economic outcomes are needed. However, implementation remains a challenge and the widespread adoption of ERAS across the NHS for total hip replacement and total knee replacement is not complete. A novel QI method (the model to manage variability) was developed and is evaluated when utilised to inform improvements to ERAS care processes within clinical microsystems performing hip and knee replacement.
Methods – The model to manage variability was adapted for use as a QI method and then deployed within two orthopaedic elective care clinical microsystems. An improvement replication programme was adopted. In the pilot site (Study 1) a retrospective observational study design was used. In Study 2, the validation site, a prospective observational study design, with a mixed-methods sequential explanatory design (QUAN emphasised) that consisted of two distinct phases was used.
Results – The model for managing variability was successfully deployed and evaluated as a QI method to help implement ERAS within both sites. Length of Stay was reduced by 45% in Study 1, and by 18% in Study 2. The interventions to improve care process highlighted by the QI method were implemented fully in Study 1 but were not able to be fully implemented in Study 2. In Study 2, qualitative data revealed that staff thought the model to manage variability was simple, effective, and had highlighted the correct changes to make. However, they felt that contextual factors around leadership, staffing, and organizational issues had prevented changes being implemented.
Discussion – The model to manage variability was successfully adapted and utilised to improve ERAS care processes within two settings. Users within the validation site felt it had advantages over other QI methods but found improvement efforts were still affected by crucial contextual factors known to influence both QI efforts and ERAS implementation.
https://eprints.bournemouth.ac.uk/36904/
Source: BURO EPrints