In this blog we delve into the bottlenecks revealed by our experience of nearly four years (as at 2024) of patient flow analytics. This bakers dozen of areas have all been discovered in real data from Trusts and National sources, and in each case the impact understood through the use of widely available process mining tools being applied to pre-existing anonymous patient data.
- Multiple Referrals for the Same Condition: There is now a widely accepted practice of referring the same patient for the same condition to multiple providers. It led to precise appointments being wasted either when the patient attends or do not attend the unnecessary appointment.
- Disparities in GP Referral Rates: There is a noticeable variance in referral rates among General Practitioners (GPs). GPs could be making unnecessary referrals.
- Under-utilised Advice and Guidance: There are missed opportunities to support patients that can be managed at home or in the community. Effective use of advice and guidance can ensure patients avoid long waits for treatment and that only those who need secondary care are referred.
- Inconsistent Triage Processes: The lack of uniformity in triage leads to more patients entering the system than intended. Shifting focus from measuring key performance indicators to monitoring processes will avoid unnecessary variations.
- Administrative Overhaul Needed: The elective recovery process is often hindered by administrative issues like late communications. Again, there is a need to shift focus from measuring key performance indicators to process monitoring to identify a range of avoidable administrative issues.
- Managing Non-Attendance (DNA): DNA, while predictable, can be driven by a range of underlying factors which may not be addressable within secondary care. Being precise on identifying the predictable and addressable patients will ensure the recovery effort is not wasted.
- Ensuring Correct Clinician Allocation: Patients are sometimes sent to the next available, rather than the most suitable, clinician. Booking rules need to be improved, updated and monitored to avoid wasting appointment slots.
- Rethinking Remote Follow-Ups: Remote follow-ups are used inappropriately. It's crucial to evaluate the necessity of face-to-face follow-ups versus remote consultations to ensure that patient treatment is being progressed rather than prolonged.
- Coordinated Scans and Tests: The necessary scans or tests required prior to appointments are not being monitored and led to appointments being wasted. Key process steps prior to appointment booking should be monitored.
- Addressing 'Lost' Patients: There are patients who not been contacted for more than 3 years and can be 'lost' in the system. A robust tracking system is needed to enhance current validation processes.
- Effective PIFU Implementation: Incorrect implementation of Patient Initiated Follow Up (PIFU) leads to an increased number of unnecessary appointments. Robust monitoring of this process can significantly reduce unnecessary appointments.
- Eliminating Deceased Appointments: Patient records are not updated and leads to appointments being made for deceased patients. This can be distressing for patients' families.
- Misallocation of Additional Resources: Inefficient resource allocation exacerbates elective care challenges. Extra resources often go to areas that are not the true bottlenecks e.g. undertaking waiting list initiatives instead of increasing diagnostic capacity. Relevant insights from process analytics ensures resources are effectively allocated to improve elective care.
Conclusion
Patient flow or process analytics helps the NHS understand the existing bottlenecks in elective care and the extent to which they impact patient flow and performance. Using patient flow analytics rather than traditional measurements of performance will enable the NHS to avoid unwanted activity maximising rather than output maximising behaviours.
NHS East of England findings
East of England Elective Care team, along with Logan Tod & Co and AnalystX, used process mining to identify elective recovery opportunities. Read the full discovery here.
To find out more, please contact Qian Huang at zhiqian.huang@logantod.net.