Heim Labs

Problem

Community and neighbourhood health services are central to the NHS shift of care from hospitals into people’s homes. However, many organisations lack reliable visibility of how community care is delivered in practice. Workforce activity, travel, demand patterns, and capacity are often inferred from incomplete documentation or retrospective reports, making accurate planning difficult.

This lack of operational insight creates several system-level challenges. Leaders struggle to understand baseline demand and capacity, assess productivity, or model the impact of service redesign. Variability in geography, population need, and skills mix is difficult to quantify. As a result, decisions about staffing, commissioning, and neighbourhood configuration are often made without consistent data.

For frontline teams, this can translate into uneven workload distribution, inefficiencies in travel, and limited transparency about how their time is spent supporting patients at home.

Solution

Heim Labs solves this problem by creating a structured, reliable, automated picture of how community and neighbourhood services operate in practice. It enables evidence-based operational and strategic decision-making, supporting safer, more efficient, and more equitable delivery of neighbourhood care.

Using a lightweight mobile app, Heim passively captures non-clinical workforce activity during the working day, including time spent delivering care, travel patterns, and service utilisation. This removes reliance on inconsistent manual documentation and avoids adding administrative burden to frontline staff.

Data is securely transmitted to Heim’s analytics platform, where it is aggregated and visualised through dashboards, geographic hotspot maps, and trend reports. Senior operational leaders, service managers, and system partners can use these insights to understand true demand and capacity, identify variation between neighbourhoods, and pinpoint where inefficiencies or pressure points exist.

Heim also supports scenario modelling, enabling organisations to test alternative service configurations such as flexing neighbourhood boundaries, adjusting skill mix, or redesigning routes. This helps teams move from assumption-led planning to evidence-based operational decision-making.

Heim is intended for non-clinical use. It does not replace electronic patient record systems and does not provide clinical decision support or inform individual patient care.

Impact

Heim Labs has been deployed across multiple NHS community providers, generating large-scale real-world workforce activity data across urban, suburban, and rural geographies.

Evidence and impact to date includes:

• Creation of the first reliable baseline of community workforce activity, including patient-facing time, travel, visit density, and variation across neighbourhoods
• Modelling of visit reallocation and route reordering demonstrated potential mileage reductions of approximately 25% in dense urban settings and over 50% in rural areas, reducing travel costs, supporting Green Plan objectives, and releasing staff time
• Identification of rapid operational interventions, including changes to coordination processes that could release approximately one senior nurse’s time per team, per day
• Implementation of practical service changes such as flexing neighbourhood boundaries, relocating clinics, introducing a deferral tracker for out-of-hours callouts, and reviewing skill mix allocation

Collectively, these changes support more efficient use of limited workforce capacity and enable more patients to be seen safely at home.