Organisation and performance in renal anaemia management

Introduction

Performance in healthcare systems is under constant scrutiny, with particular focus on safety, quality and efficiency. The management of many long-term diseases involves complex patterns of care processes. However, the mechanisms by which this works are poorly understood, with care pathways reflecting pre-determined, linear processes.

Renal anaemia is a significant complication of chronic kidney disease that is expensive to treat and is associated with reduced quality of life and increased morbidity and mortality. There is wide variation between the clinical performance measures of centres for renal anaemia management, which researchers and practitioners have suggested is due to differences in organisation.

Aims and objectives

This research explores the features of high and low performing renal anaemia management services to build evidence for their improvement.

Methods

A multiple case studies approach examining anaemia management at eight renal centres with high and low performance was used. Data were collected using observation, interview and document sampling. The Unified Modelling Language was employed to define an abstract framework of the renal anaemia management service. A thematic analysis explored factors considered influential in the process and performance of renal anaemia management.

Results

System latency and reliability, regular communication and trust between decision makers all appear significant in producing high performance. The group of activities and coordination mechanisms used to manage renal anaemia in haemodialysis patients in high performing centres reflect these features. The current tax regime encourages practice that has neither quality nor efficiency at its core.

Discussion

The findings provide an important platform for performance improvement in renal anaemia management. In addition, the process modelling represents a departure from the major body of such work in healthcare, using a richer language to represent the complex and adaptive nature of healthcare systems. Therefore, the approach presented here may be a useful template for future work in this field.