Peri-operative elective path optimization through algorithms in the Local Health Authority of Bologna

Background

High costs of healthcare and population ageing force the health system to constantly improve its efficiency in order to provide patients the best possible care with the available resources. In this perspective, the Local Health Authority and the University of Bologna started an experimentation to re-organize, manage and control the peri-operative elective path of general surgery, a discipline that works in a multiplatform environment according to a Hub & Spoke logic.

Methods

The experimentation is built on two mathematical programming models. The first one defines patient preparation appointments (i.e. diagnostic and anesthesiologic visits), harmonizing patient preparation with available resources, and planning migration from Hub to Spoke platforms, in order to optimize waiting time and facilities utilization. The second model defines weekly optimal admission plans. Both models consider the availability of resources in terms of surgical teams, operating room slots and number of beds for each operating unit. The proposed approach works on a four-week time horizon following a rolling horizon framework (weekly update) in order to effectively manage high priority patients.

Results

Both models have been tested on real-world instances over a six-month observation period. Overall, it was possible to increase the efficiency of surgical programming by reducing the waiting times for surgical interventions in over 20% of cases of high priority patiets in four local departments.

Conclusions

The proposed model represents one of the few cases in Italy of surgical programming developed through mathematical models. It will be necessary to evaluate the evolution of its effectiveness to optimize the system's ability to respond to the growing health needs of the population.

Key messages

Mathematical models are needed to optimize surgical planning. Efficiency of surgical planning may reduce waiting times for high priority procedures.