Improving Efficiency While Elevating the Ambulatory Experience for Cancer Patients

CHALLENGE

A nationally-ranked NCI-designated Comprehensive Cancer Center faced a unique challenge: their patients loved and raved about coming to the cancer center but, if you looked just under the surface, you discovered that many loved the organization because of how “patient centric” they were, but loathed many of the operational challenges encountered while actually engaging with the facility itself. The cancer center recorded over 100,000 clinic appointment cancellations every year. Some patients walked nearly a mile during the course of a visit due to the location of services scattered across a sprawling campus. Patients were enthusiastic about the care and the staff but dissatisfied with the overall experience.

  • 100+ stakeholder interviews

  • Operational analysis

  • Manual time-motion studies

  • Clinical functionality assessment

  • Patient consumer experiential analysis

  • Provider consumer experiential analysis

  • Co-creation sessions to explore the cancer patient, visitor and provider journey

  • Provider town halls

  • Customized demand projections

  • Site of service planning

  • Key room forecast

  • Space programming

  • Campus site of service planning

  • Computerized simulation modeling

APPROACH

Analysis of the current state centered on data analytics, stakeholder interviews, direct shadowing of patients and providers and ethnographic research. Operational data analysis was hampered by a lack of electronic patient tracking. In response, the team engaged in two weeks of manual timestamp analysis, following hundreds of patients through their campus visits, recording the time it took to move through the care delivery process while also learning so many stories about so many patient consumers. Service design approaches including patient and provider focus groups were used to co-create the ideal future state which was tested with computer simulation modeling prior to implementation.

As operational recommendations were advanced and considerations around reorganization service locations was debates, many providers were skeptical. To reassure providers, multiple simulation models were custom built to test the recommendations. The models were able to assess care time, travel distances, capacity management and queuing locations.

RESULTS

One of the most profound evolutions for the organization was a reorganized clinic environment shifting from specialty-based clinics (medical oncology, surgical oncology, radiation oncology) to interdisciplinary tumor-based clinics. An emerging model at the time, the tumor-based interdisciplinary clinics accelerated patient throughput while enhancing provider collaboration and casual collisions that added value to the patient care process.

In addition to shifting clinic models, the patient arrival and check-in process was reimagined. The new process focused on accelerating diagnostics in order to reduce infusion-related delays as well as clinic delays tied to waiting for diagnostic results.

80%

reduction in physician-attributed clinic cancellations

50%

reduction in patient travel distances

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