Health and social care services across England are facing increasing demand pressure, through a growing and aging population and, due to improving medical services, people are living longer with non-communicable diseases (NCDs) such as diabetes, heart disease or cancer: these illnesses are persistent, non-infectious, often incurable and require long-term management through health and care. It is crucial to understand how demand for the health system is growing, and how it is likely to change in the future.
The aim of this work is to develop projections for NHS demand and cost pressures, including the future prevalence and patterns of ill health and NCDs. To estimate future healthcare costs and activity, we will analyse how people have used the health service over time, depending on their age, sex, where they live and whether they have no, one or multiple NCDs. This will be done initially using a random sample of people. Using population projections from the Office for National Statistics (ONS), we will estimate the total future cost of the NHS and the activity required to treat a growing population who are living longer with multiple NCDs.
We will combine the results of the above and feed these into a more complex model to develop projections of the expected demand pressures facing the NHS in the next 15 years.
Exploiting linked Clinical Practice Research Datalink (CPRD), Hospital Episode Statistics, ONS mortality, patient deprivation and cancer registry data allows a more complete understanding of NCDs and their impact on healthcare use.
We will use a cohort of 2 million participants randomly sampled from the Clinical Practice Research Datalink(CPRD) and linked Hospital Episode Statistics(HES), Office for National Statistics (ONS) mortality data, Patient-Level Index of Multiple Deprivation(IMD), National Cancer Registration and Analysis Service(NCRAS) data from 2008/09 to 2020/21 to inform the parameters of a microsimulation model, based on the widely published IMPACTNCD modelling framework.
Our overarching aims are to:
1. create mid-term (15-year) projections for all NHS funding and health care activity, assuming that the observed recent trends will continue in the future; and
2. create projections for all NHS funding and health care activity using different assumptions about disease incidence, case fatality, and healthcare activity trends.
Thus, we will produce a holistic estimation of NCDs' prevalence and NCDs' impact on NHS costs and activity. Moreover, we will better understand how changes in the patterns of NCDs affect the health resources used.
Our objective is to interrogate the data and extract:
1. incidence, prevalence, case fatality, and mortality rates for common non-communicable diseases, stratified by year, age, sex, region, socioeconomics and ethnicity.
2. Primary and secondary (inpatient, outpatient, Accident and Emergency) healthcare activity, stratified by the same factors as #1, and by disease duration, number of comorbidities, and whether on last year of life.
3. Prescription costs stratified by the same factors as #2.
We will use generalised additive models for location scale and shape (GAMLSS) for all statistical modelling and the Personal Social Services Research Unit (PSSRU) costs per appointment minute, CPRD prescribing activity and costs – checked against OpenPrescribing and NHS reference costs for costings.
We will use the GAMLSS models in a discrete-time stochastic dynamic microsimulation that simulates the life course of a close-to-reality English synthetic population and tracks the development and accumulation of NCDs and healthcare utilisation.
Incidence, prevalence, case fatality, and mortality rates for common non-communicable diseases, stratified by year, age, sex, region, patients' quintile group index of multiple deprivation (QIMD), and if data allow ethnicity. We will focus our efforts on diseases with a high burden on the population according to the Global Burden of Disease project (6), namely; coronary heart disease (CHD), stroke, chronic obstructive pulmonary disease (COPD), diabetes mellitus type 2 (T2DM), dementia, asthma, chronic liver disease, breast cancer, prostate cancer, lung cancer, colorectal cancer, skin melanoma, depression, and hypertension. We will expand this list if resources allow us to include more diseases based on the magnitude of their health and economic burden.
Disease accumulation over time, from a list of 211 conditions, allows us to model the incidence and prevalence of basic (two or more chronic conditions) and complex (three or more chronic conditions affecting three or more different body systems) multimorbidity. We will stratify this by year, age, sex, region, QIMD, and if data allow ethnicity (Note that our team is already working towards this using a more limited CPRD dataset).
Number of attendances at outpatient appointments by treatment speciality per year; Number of attendances in A&E by type and treatment outcome (e.g. treated and sent home/admitted) per year; Number of hospitalisations (elective (long-stay/day case) and non-elective) by HRG code per year; Number of attendances at primary care consultations per year; Number and type of primary care prescriptions per year; Costs of health care activity per year. We will stratify these by year, age, sex, region, QIMD, disease duration (from the list of the disease above and for patients without any disease from this list), the number of comorbidities, whether on last year of life and if data allow ethnicity.
Toby Watt - Chief Investigator - The Health Foundation
Andrew Campbell - Corresponding Applicant - The Health Foundation
Andrew Mooney - Collaborator - The Health Foundation
Ann Raymond - Collaborator - The Health Foundation
Anna Head - Collaborator - University of Liverpool
Anne Alarilla - Collaborator - The Health Foundation
Chris Kypridemos - Collaborator - University of Liverpool
Geraldine Clarke - Collaborator - The Health Foundation
Jay Hughes - Collaborator - The Health Foundation
Kate Fleming - Collaborator - University of Liverpool
Laurie Rachet-Jacquet - Collaborator - The Health Foundation
Martin O'Flaherty - Collaborator - University of Liverpool
Miqdad Asaria - Collaborator - The Health Foundation
Nuha Bazeer - Collaborator - The Health Foundation
Stephen Rocks - Collaborator - The Health Foundation
Zeyad Issa - Collaborator - The Health Foundation
Emma Vestesson - Collaborator - The Health Foundation
Sahan Jayawardana - Collaborator - The Health Foundation
HES Accident and Emergency;HES Admitted Patient Care;HES Outpatient;NCRAS Cancer Registration Data;No additional NCRAS data required;ONS Death Registration Data;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation