Skip to main content

This blog post highlights the potential of patient flow analytics, using process mining, to improve elective recovery efforts in the National Health Service (NHS).

Key findings:

  • Multiple referrals for the same condition (“scatter gun” approach) by GPs leads to unwanted appointments, hindering overall efficiency.
  • Inappropriate referrals due to outdated training or guidelines can be identified and addressed.
  • Unnecessary rework in referral services can be reduced, freeing up clinical and non-clinical capacity.
  • High volume of “unwanted” activities like DNAs and cancellations can be minimized.
  • Inappropriate clinician allocation can waste appointment slots and require rework.
  • Uncoordinated scans and tests can lead to appointment cancellations.
  • Outdated validation methods using spreadsheets can delay prioritizing patients and risk patient deterioration while waiting.

Potential Impact:

  • Implementing these improvements could release significant clinical and non-clinical capacity across the National Health Service (NHS).
  • More efficient use of resources can lead to reduced waiting lists and improved patient care.


Patient flow analytics offers valuable insights into bottlenecks and inefficiencies within the referral process. By addressing the root causes identified, the NHS can move away from activity-focused metrics towards impact-maximizing behaviors, ultimately facilitating sustainable elective recovery.

For the full article

Elective Recovery Patient Flow Analytics

Getting involved

If you are already using process mining at your organisation, we would love to hear about your experience and your work, if you would like to learn more about process mining please join our community of practice (AnalystX Process Mining), to receive a live demo or have further questions, please get in touch with a member of the Logan Tod & Co team.