Domain | Target Criteria | Inclusion Criteria |
---|---|---|
Prevalence Purpose: to identify high prevalence conditions (that impact a greater number of people) | Estimated condition prevalence (UK 2017) | > = 1% |
Impact of LTC Purpose: to identify conditions that have a greater impact on people’s lives | Progressive natural course? (yes/no) | Yes |
Impact YLL Purpose: to identify conditions that are having a greater population-level impact in terms of years of life lost | Rank by volume of YLL (UK, 2017—Source: GBD) | Top 20 |
Impact YLD Purpose: to identify conditions that are having a greater population-level impact in terms of years lived in disability | Rank by volume of YLD (UK, 2017—Source: GBD) | Top 20 |
Prevention and Modifiability Purpose: to identify conditions that can be prevented, the onset delayed, or improved by modifying risk factors or intervention | Do risk factors play a role in preventing or delaying the onset of the condition? (yes/no) | Yes |
Can intervention result in complete resolution? (yes/no) | Yes | |
Treatment Burden: Utilisation Purpose: to identify conditions that account for a high-proportion of population-level admitted patient care | Rank by volume of hospital admissions (based on primary diagnosis) (England, 2017/18—Source: HES data, NHSD) | Top 20 |
Treatment Burden: Medication Purpose: to identify conditions that have a high treatment burden, particularly in relation to medication burden | Number of first-line, self-administered medications | > = 2 |
Progression to mLTCs Purpose: to identify conditions that are most likely to be involved in a mLTCs journey | Proportion of people with the condition who have 1 + comorbidities | > 50% |
Impact on younger people: Age at Onset Purpose: to identify conditions that can present in younger people, as these that are more likely to be the first condition in a multimorbidity pathway | Typical age of onset of the condition | < 50 years old |
Impact on younger people: YLD in younger people (aged 15–49) Purpose: to identify conditions that have a high population-level impact on years lived with disability, in younger people | Rank by volume of YLD, in people aged 15–49 (UK, 2017—Source: GBD) | Top 20 |
Data Quality Purpose: to identify conditions where data quality is of a sufficient level to allow for meaningful data analysis | Level of data quality: Low/Medium/High, based on three main criteria (whether a condition is included in QOF, whether regular/frequent prescriptions are required, whether hospitalisation for the condition is common), in combination with background knowledge on data quality | Medium and High |