A plain-language account of the Assistiv intelligence framework — what data we use, how we combine it, what our scores mean, and where we are honest about their limitations.
The NHS identifies frailty predominantly when people arrive at hospital. By that point, frailty has typically been developing for months or years — invisible to the health system, visible only to the person themselves and perhaps to family carers who may not know what they are seeing.
Systematic proactive identification of frailty in the community exists in policy — the NHS Long Term Plan, the Core20PLUS5 programme, the PCN Network Contract — but rarely in practice at scale. The challenge is not clinical knowledge of what frailty looks like. The challenge is geographic and demographic: where are the people who are frail but not yet presenting?
We call this population the Missing Middle: older adults who are beyond full independence but do not yet qualify for formal care. UK estimates suggest approximately 3.5 million people nationally sit in this space.1 In Kent and Medway, using our modelling, we estimate this at around 180,000 people.
The Assistiv framework is an attempt to answer that question using three complementary intelligence layers: the FEP score (district-level frailty risk), the RAVI (LSOA-level rural isolation), and the CBI (carer burden by district). Each layer illuminates a different aspect of the same underlying problem.
The FEP score is a composite index ranging from 0 to 100, calculated for each of the 13 Local Authority Districts in Kent and Medway. It is designed to estimate the relative concentration of frailty risk factors within a district's older adult population — not to provide an individual-level clinical assessment.
A score of 50 represents the England average. Districts above 50 have a higher concentration of risk factors than the national baseline; districts below 50 have a lower concentration. The index is relative, not absolute: a score of 65 means "substantially more risk factors than the national average", not "65% of older adults are frail."
For communication purposes, FEP scores are assigned to four bands:
The FEP score is calculated from 18 signals drawn from three data categories. Signal selection was guided by three criteria: clinical face validity (does this signal have a plausible causal relationship with frailty?), data quality and currency (is this from a reliable, regularly updated source?), and geographic availability (can we obtain this at district level for Kent?).
Demographic and socioeconomic signals (3 signals, 28% combined weight) — proxy measures where direct frailty data is unavailable at district level. Older adults living alone, deprivation index, and care home provision gaps. These are flagged as modelled estimates, not direct measurements.
NHS Fingertips outcomes indicators (10 signals, 47% combined weight) — published OHID data on falls admissions, hip fractures, winter mortality, dementia diagnosis rate, loneliness, and social isolation. All real data; all benchmarked against England averages with published confidence intervals.
NHSBSA prescribing signals (5 signals, 25% combined weight) — practice-level dispensing data from the NHS Business Services Authority, aggregated to district. Prescribing patterns are among the most sensitive indicators of frailty burden available in routine NHS data: hypnotics, anxiolytics, bisphosphonates, oral nutritional supplements, and anticholinergic medications all proxy specific clinical domains.
| Signal | Weight | Source | Type | |
|---|---|---|---|---|
| Over-75s living alone | 13% | ONS Census 2021 | Modelled | |
| Falls admissions 65+ | 12% | NHS Fingertips 22401 | Real | |
| Hip fracture rate 65+ | 9% | NHS Fingertips 41401 | Real | |
| Deprivation (IMD 2019) | 8% | MHCLG IMD 2019 | Modelled | |
| Winter mortality index | 8% | NHS Fingertips 90360 | Real | |
| Care home gap | 7% | CQC register | Modelled | |
| Loneliness rate | 6% | NHS Fingertips 94175 | Real | |
| Dementia diagnosis rate † | 6% | NHS Fingertips 92949 | Real | |
| Hip fractures 80+ | 5% | NHS Fingertips 41403 | Real | |
| Social isolation rate | 5% | NHS Fingertips 90280 | Real | |
| Hypnotics prescribing | 5% | NHSBSA EPD Mar 2026 | Real | |
| Antidepressant rate | 5% | NHSBSA EPD Mar 2026 | Real | |
| Bisphosphonate rate | 4% | NHSBSA EPD Mar 2026 | Real | |
| Anxiolytics prescribing | 3% | NHSBSA EPD Mar 2026 | Real | |
| Oral nutritional supplements | 3% | NHSBSA EPD Mar 2026 | Real | |
| Bladder antimuscarinics | 2% | NHSBSA EPD Mar 2026 | Real | |
| ACE/ARB prescribing | 1% | NHSBSA EPD Mar 2026 | Real | |
| Diuretics rate | 1% | NHSBSA EPD Mar 2026 | Real |
† Dementia diagnosis rate is inverted — a lower diagnosis rate than the England average indicates probable under-diagnosis, not better performance. Kent (62.3%) scores below the England average (66.3%), increasing the district's risk score for this signal.
Weights reflect a combination of clinical evidence strength and signal specificity. Falls admissions (12%) and hip fracture rate (9%) carry high weight because they are direct, high-consequence outcomes of frailty with strong published epidemiology. Dementia diagnosis (6%) is weighted less not because dementia matters less, but because the diagnosis rate is an imperfect proxy — it measures healthcare access and diagnostic practice as much as underlying prevalence.
Prescribing signals collectively carry 25% of the total weight. Individually they are modest proxies; together, a district that scores above England average on hypnotics, anxiolytics, bisphosphonates, and oral nutritional supplements simultaneously is displaying a coherent pattern of polypharmacy and frailty-associated clinical need. Oral nutritional supplements (BNF code 090402) were added in v5.0 because they are prescribed only when a patient is genuinely failing to maintain bodyweight — one of the five FRAIL Scale criteria.2
Each signal is normalised against the England average for that indicator, producing a score from 0 to 100. A score of 50 means the district is exactly at the England average for that signal. Higher scores indicate greater deviation above the England average — more risk.
Inverted signals (where a lower value means higher risk) are handled by subtracting from 100 before weighting. Scores are capped at 100 to prevent extreme outliers from distorting the index.
Because NHS Fingertips data is published at ICB or county level rather than district level for most indicators, we apply district-level multipliers derived from the relative demographic and prescribing profiles of each district. These multipliers are calculated from the NHSBSA EPD practice-level data, which is available at district level — practices are assigned to districts by postcode. The Fingertips signals at ICB level are then scaled by these multipliers.
This is the primary methodological limitation of the current model. The district-level FEP scores are not independently derived from district-level Fingertips data for all signals — they are scaled estimates. We are transparent about this in the tool interface.
When the UKHSA/Met Office issues a Heat-Health or Cold-Health Alert for South East England, FEP scores are uplifted for high-risk districts and specific prescribing signals (anticholinergics, diuretics, hypnotics) are flagged for elevated clinical sensitivity. This uplift is fetched at runtime and applied as a multiplicative factor, not permanently incorporated into the base score.
The FEP score operates at district level — 13 areas averaging 150,000 people each. This resolution is useful for commissioning decisions but hides profound within-district variation. Sevenoaks scores FEP 37 (Low), but contains 21 LSOAs at high or critical rural access vulnerability. The people in those LSOAs are not represented in the district average.
The RAVI addresses this by scoring all 1,065 Lower Super Output Areas (LSOAs) in Kent and Medway on five signals of geographic and social isolation. Each LSOA contains approximately 1,500 people.
| Signal | Weight | Source | |
|---|---|---|---|
| Geographic Barriers to Services | 30% | IMD 2019 File 7 — road distance to GP, pharmacy, food store, post office | |
| Rural Urban Classification | 25% | ONS/mySociety RUC 2021 — Urban, Rural town/village, Hamlet/Isolated | |
| Population aged 65+ | 20% | Census 2021 via Nomis TS008 | |
| No car or van in household | 15% | Census 2021 via Nomis TS045 | |
| Day-to-day activities limited a lot | 10% | Census 2021 via Nomis TS046 |
Geographic Barriers carries the highest weight (30%) because it directly measures the structural problem: road distance to services. In a rural area, having no car (15%) combined with a GP surgery 8 miles away (geographic barriers score) produces a qualitatively different kind of vulnerability than urban poverty. The RAVI is designed to capture this interaction.
The RAVI reveals a pattern that the FEP model obscures: the districts with the lowest FEP scores contain some of the most isolated LSOAs in Kent.
Sevenoaks has FEP 37 — the second lowest district score in Kent. Yet Sevenoaks 015A (Hever) scores RAVI 74.2 — critical. These are different populations requiring different interventions: Thanet's risk is driven by deprivation and prescribing burden; Hever's risk is driven by physical isolation from services.
53 of the 1,065 Kent LSOAs have no named settlement — they are open countryside with isolated dwellings. These are flagged as "Rural (no settlement)" in the tool. Canterbury 017C, the second highest-scoring LSOA in Kent, falls into this category.
Frailty does not occur in social isolation. Approximately 6.5 million people in England provide unpaid care, and the evidence consistently shows that carer exhaustion is both a consequence of frailty in the person cared for and an independent risk factor for crisis admissions — when carers reach breaking point, the person they support often presents at A&E within days.3
The CBI scores each district on five signals of carer strain, producing a score from 0 to 100 benchmarked against England averages. When plotted against the FEP score, districts fall into four quadrants. The most urgent quadrant — high FEP, high CBI — identifies places where frailty emergence and carer exhaustion are simultaneously elevated. Thanet and Folkestone & Hythe consistently occupy this quadrant.
| Signal | Weight | Geography | Source |
|---|---|---|---|
| 20+ hour/week unpaid carers | 30% | District | ONS Census 2021 TS039 |
| Carer social isolation | 25% | County | NHS Fingertips 90638 |
| Access to information and support | 15% | County | NHS Fingertips 90279 |
| Carer's assessment rate | 15% | County | NHS Fingertips 93014 |
| Carer wellbeing score | 15% | County | NHS Fingertips 90283 |
A geographic limitation applies: four of the five CBI signals are available only at county level (Kent as a whole) via NHS Fingertips, not at district level. These county-level values are applied uniformly across all 13 districts, with only the Census 2021 carer rate providing district-level discrimination. This is a known constraint of NHS administrative data. The CBI scores should therefore be read as an indicator of relative district concentration of intensive carers combined with a county-wide measure of carer system strain.
The map tool includes a cost-of-inaction estimate for each district — the estimated annual NHS expenditure attributable to preventable frailty-related falls admissions and hip fractures. This is not a financial model. It is a population-level triage estimate designed to contextualise the clinical risk in economic terms for commissioner conversations.
| Cost item | Figure | Source |
|---|---|---|
| Falls emergency admission | £3,068 | NHS Improvement (£2,600 CPI-uplifted to 2024/25) |
| Hip fracture — 12-month NHS cost | £14,642 | Lancet Healthy Longevity, July 2023 (n=178,757 patients) |
| Delayed discharge — bed day cost | £562 | NHS England 2025/26 (£527 × 6.65% uplift) |
| 111 call handling | £8.71 | NHSE IUC telephony published unit cost |
| Ambulance dispatch from 111 | £257 | NHSE Ambulance Cost Collection 2023/24 (Cat 2) |
| ED attendance from 111 referral | £212 | NHS Reference Costs 2023/24 — Type 1 ED |
The model applies preventability fractions from published clinical evidence: 30% of falls-related emergency admissions and 28% of hip fractures are considered preventable with proactive early intervention.4,5 These fractions are applied to the district's estimated population-level incidence, derived from Kent ICB Fingertips rates scaled by district FEP score and population of over-75s.
A ±30% uncertainty range is displayed on all estimates, reflecting the limitations of district-level population modelling. The figures are best interpreted as order-of-magnitude estimates — the kind that open a commissioning conversation rather than close one.
We believe transparency about limitations is not a weakness — it is the condition of being trusted. The following are the substantive limitations of the current model.
The majority of NHS Fingertips data is published at ICB level (Kent and Medway as a whole), not at Local Authority District level. District FEP scores are derived by applying district-level multipliers to the ICB baseline. These multipliers come from NHSBSA EPD data, which is genuinely available at practice level. The result is a defensible estimate, not a directly observed district measure.
Three of the five RAVI signals (age, car access, limiting long-term illness) are using England national averages as fallback values because LSOA-level Census 2021 data is not reliably returning from the Nomis API at query time. This reduces the discriminatory power of the RAVI — current scores are driven primarily by geographic barriers and rural classification. This will be corrected as Census data access stabilises.
No FEP score, RAVI score, or CBI score should be used to make decisions about individual patients. These are population-level instruments designed to direct resource allocation and outreach priorities. Individual frailty assessment requires clinical evaluation using validated instruments such as the Clinical Frailty Scale or the PRISMA-7.
The FEP model has not yet been validated against actual frailty prevalence data or clinical outcomes in Kent. We have clinical face validity — the signals make theoretical sense — but we do not yet have empirical evidence that higher FEP scores predict higher actual frailty rates, ED admissions, or care home placements. Outcome validation is the priority next step and is the subject of active stakeholder engagement with NHS Kent and Medway ICB.
NHS Fingertips indicators update on varying schedules — some annually, some quarterly. IMD data dates from 2019. The NHSBSA EPD data is the most current, at practice-dispensing month level (currently Mar 2026). Fingertips indicators are re-fetched daily via GitHub Actions. Any interpretation of the scores should account for the publication lag of the underlying data.
The current model represents a prototype — a working demonstration that the signals are accessible, that the pipeline is technically reliable, and that the outputs are plausible and clinically interpretable. It is not a validated predictive tool.
The pathway to validation has three stages:
Linking district-level FEP scores historically against actual NHS outcomes — falls-related A&E attendances, hip fracture admissions, emergency bed days attributed to frailty codes — using data sharing agreements with NHS Kent and Medway ICB. If FEP scores from six months ago predict subsequent admissions, that is the validation evidence. If they do not, the signal weights need revision.
The RESILIENCE community screening tool (Layer 4) is deployed in community settings. As screening outcomes are recorded, the distribution of Clinical Frailty Scale scores by district can be compared against FEP predictions. A district scoring FEP 65 should, if the model is working, yield a higher proportion of positive screens than a district scoring FEP 35.
The methodology has been reviewed informally by academic colleagues in health economics and geriatric medicine. Formal peer-reviewed publication of the composite index methodology is in preparation. Interested academics are invited to contact the team for collaborative engagement on the validation programme.