Quality improvement at scale: evaluation of the drivers and barriers to adoption and sustainability of an intervention to reduce late referral in chronic kidney disease. Issue 4 (12th November 2020) - Thomas, Nicola; Nation, Michael; Woolnough, Lesley; Gallagher, Hugh
Abstract : This quality improvement project aimed to drive large scale and sustained change to reduce the burden of chronic kidney disease in the UK. The intervention is a software program that extracts relevant biochemical data from laboratory databases which then generate graphs of estimated kidney function (eGFR) over time. Graphs showing progressive kidney disease are sent directly back to general practitioners (GPs) to alert them to rereview patient care and if necessary, refer to renal services. The aim of this evaluation study was to explain the barriers and drivers to implementation and adoption of the eGFR graph intervention. This evaluation study involved 5 of the 20 participating renal units (sites) . A developmental evaluation approach was used. Methods included collection of descriptive data about graph reporting; GP surveys (n=68); focus groups (n=4) with practices; face-to-face interviews with secondary care clinicians (n=10). Results showed the mean number of graphs reviewed per week per site was 230, taking 1 hour per week per site. Only 18.2% graphs highlighted a concerning decline in kidney function. Important enablers to sustain the intervention were low cost, easy to understand, a sense of local ownership and perceived impact. Barriers included nephrologists' perceived increase in new referrals. We concluded that developmental evaluation can explain the barriers/drivers to implementation of a national quality improvement project that involves a variety of different stakeholders. The intervention has the potential to slow down progression of kidney disease due to the eGFR prompts alerting GPs to review the patient record and take action, such as reviewing medications and referring to renal teams if progressive kidney disease had not been identified previously.