513P - Using Quality Improvement Methods and Time-Driven Activity Based Costing to Improve Value-Based Cancer Care Delivery at a Cancer Genetics Clinic

Date 20 December 2015
Event ESMO Asia 2015 Congress
Session Poster presentation 2
Topics Bioethics, Legal, and Economic Issues
Presenter Ryan Tan
Citation Annals of Oncology (2015) 26 (suppl_9): 156-160. 10.1093/annonc/mdv535
Authors R. Tan1, M. Met-Domestici1, K. Zhou2, A. Guzman3, S.T. Lim2, K.C. Soo2, T. Feeley3, J. Ngeow4
  • 1Medical Oncology, Cancer Genetics Service, National Cancer Centre Singapore, 169610 - Singapore/SG
  • 2Oncology Academic Clinical Program, Duke-NUS Graduate Medical School, Singapore/SG
  • 3Institute For Cancer Center Innovation, University of Texas MD Anderson Cancer Center, Houston/US
  • 4Medical Oncology, Cancer Genetics Service, National Cancer Centre Singapore, Singapore/SG

Abstract

Aim/Background

To meet increasing demand for cancer genetic testing and improve value-based cancer care delivery, National Cancer Centre Singapore restructured the Cancer Genetics Service in 2014. Care delivery processes were redesigned to improve access by increasing the Cancer Genetics Service's clinic capacity by 100% within a year while measuring direct personnel costs.

Methods

Process mapping and Plan-Do-Study-Act (PDSA) cycles were used in a Quality Improvement (QI) project for the Cancer Genetics Service clinic. The impact of interventions was evaluated by tracking the weekly number of patient consultations from April 2014 to May 2015. The cost impact of implemented process changes was calculated via the Time-Driven Activity Based Costing (TDABC) method.

Results

Our study completed 2 PDSA cycles. An important outcome was achieved after the first cycle: the inclusion of a genetic counsellor increased clinic capacity by 350%. The number of patients seen per week increased from 2 in April 2014 (range 0-4) to 7 in November 2014 (range 4-10). Our second PDSA cycle showed that pre-appointment call reminders reduced the variation in the no-show rate and contributed to a further increase in patients seen per week to 10 in May 2015 (range 7-13). There was a concomitant decrease in costs of the patient care cycle by 18% after both PDSA cycles.

Conclusions

This study shows how QI methods can be combined with TDABC to demonstrate improved value. In this example, we improved access while reducing care delivery costs.

Clinical trial identification

Disclosure

All authors have declared no conflicts of interest.