Diabetes is a common chronic health condition. Care for patients with diabetes accounts for almost 9% of the NHS budget: £8.8 billion a year. The number of cases of diabetes is rising, due an ageing population. Other risk factors, such as diet and physical activity, also contribute to increased demand for diabetes-related primary and secondary care.
Annual health checks, and effective treatments, are available to manage diabetes. Nevertheless, diabetes can be difficult to manage in practice. The 2016-17 National Diabetes Audit showed that a large proportion of patients do not achieve the NICE recommended treatment targets. This leaves them at increased risk of preventable diabetic complications. If diabetes is managed poorly, patients often experience worse health outcomes and they might need high-cost care interventions, such as emergency hospital admissions.
There is little evidence on the variation of health care utilisation by patients with diabetes. It is also unclear what effect this variation might have on health outcomes. In this study, we aim to describe health care utilisation of diabetes patients.
Hospital outpatient services are increasingly overstretched. There are plans to transform these services, so we will test strategic approaches that could be used to redesign and improve them.
We will also investigate whether patterns of outpatient care utilisation (e.g. number of visits and follow-up times) affect the risk of experiencing complications. These complications may lead to hospital admissions or death.
This research will help policymakers and health care leaders target aspects of diabetes care in a way that will improve outcomes for patients. We hope that our results will enable change so that patients will receive better care.
Objectives: The main objective of this research is to increase understanding of health care utilisation patterns by patients with diabetes, and understand the relationship between the frequency of diabetes monitoring in hospital outpatient settings and the risk for diabetes-related complications. We will then develop mathematical models to estimate changes in demand for diabetes outpatient care under different policy scenarios, and estimate the time to impact (i.e. attaining a predefined policy goal) for each scenario. This will allow us to translate our findings on health outcomes into actionable policy recommendations.
Methods and data analysis: A cross-sectional study of CPRD patients registered in 2015-2018 with prevalent diabetes. Data on utilisation (including GP and outpatient care) and health outcomes (all-cause and diabetes-related emergency admissions and mortality) will be derived from CPRD and linked Hospital Episode Statistics and ONS mortality records. Association between outpatient care utilisation and health outcomes will be tested for using use multi-level Cox's proportional hazards model, nesting patients within outpatient care providers. This model will control for patient-based, clinical and disease characteristics and other health care utilisation.
We will then develop an analytical model using Markov Chains, based on outpatient utilisation patterns in the data. This operational research technique that has been used successfully in strategic and capacity planning and to explore the effect of changes to ongoing operations. The model will replicate the flow of individual patients through different "states" (where state determined by the frequency of outpatient appointments for that patient). We will use the model to explore the impact of scenarios, such as changing the number of patients entering the outpatient system, or changing discharge rates and/or altering follow up intervals.
Types and level of health care utilisation by diabetes patients
Quality of diabetes care
Health care demand projections
Sarah Deeny - Chief Investigator - The Health Foundation
Richard Welpton - Corresponding Applicant - The Health Foundation
Fiona Grimm - Collaborator - The Health Foundation
Mai Stafford - Collaborator - The Health Foundation
Martin Utley - Collaborator - University College London ( UCL )
Meetali Kakad - Collaborator - The Health Foundation
2011 Rural-Urban Classification at LSOA level;HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;ONS Death Registration Data;Patient Level Index of Multiple Deprivation