Ryan Y C Tan1, Marie Met-Domestici1, Ke Zhou1, Alexis B Guzman1, Soon Thye Lim1, Khee Chee Soo1, Thomas W Feeley1, Joanne Ngeow2. 1. National Cancer Centre Singapore; Duke-National University of Singapore Graduate Medical School, Singapore; The University of Texas MD Anderson Cancer Center, Houston, TX; and Harvard Business School, Boston, MA. 2. National Cancer Centre Singapore; Duke-National University of Singapore Graduate Medical School, Singapore; The University of Texas MD Anderson Cancer Center, Houston, TX; and Harvard Business School, Boston, MA joanne.ngeow.yuen.yie@singhealth.com.sg.
Abstract
PURPOSE: 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. We sought to improve access by increasing the clinic capacity of the Cancer Genetics Service by 100% within 1 year without increasing direct personnel costs. METHODS: Process mapping and plan-do-study-act (PDSA) cycles were used in a quality improvement project for the Cancer Genetics Service clinic. The impact of interventions was evaluated by tracking the weekly number of patient consultations and access times for appointments between April 2014 and May 2015. The cost impact of implemented process changes was calculated using the time-driven activity-based costing method. RESULTS: Our study completed two PDSA cycles. An important outcome was achieved after the first cycle: The inclusion of a genetic counselor increased clinic capacity by 350%. The number of patients seen per week increased from two in April 2014 (range, zero to four patients) to seven in November 2014 (range, four to 10 patients). Our second PDSA cycle showed that manual preappointment reminder calls reduced the variation in the nonattendance rate and contributed to a further increase in patients seen per week to 10 in May 2015 (range, seven to 13 patients). There was a concomitant decrease in costs of the patient care cycle by 18% after both PDSA cycles. CONCLUSION: This study shows how quality improvement methods can be combined with time-driven activity-based costing to increase value. In this paper, we demonstrate how we improved access while reducing costs of care delivery.
PURPOSE: 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. We sought to improve access by increasing the clinic capacity of the Cancer Genetics Service by 100% within 1 year without increasing direct personnel costs. METHODS: Process mapping and plan-do-study-act (PDSA) cycles were used in a quality improvement project for the Cancer Genetics Service clinic. The impact of interventions was evaluated by tracking the weekly number of patient consultations and access times for appointments between April 2014 and May 2015. The cost impact of implemented process changes was calculated using the time-driven activity-based costing method. RESULTS: Our study completed two PDSA cycles. An important outcome was achieved after the first cycle: The inclusion of a genetic counselor increased clinic capacity by 350%. The number of patients seen per week increased from two in April 2014 (range, zero to four patients) to seven in November 2014 (range, four to 10 patients). Our second PDSA cycle showed that manual preappointment reminder calls reduced the variation in the nonattendance rate and contributed to a further increase in patients seen per week to 10 in May 2015 (range, seven to 13 patients). There was a concomitant decrease in costs of the patient care cycle by 18% after both PDSA cycles. CONCLUSION: This study shows how quality improvement methods can be combined with time-driven activity-based costing to increase value. In this paper, we demonstrate how we improved access while reducing costs of care delivery.
Authors: Nick Dragojlovic; Kennedy Borle; Nicola Kopac; Ursula Ellis; Patricia Birch; Shelin Adam; Jan M Friedman; Amy Nisselle; Alison M Elliott; Larry D Lynd Journal: Genet Med Date: 2020-06-24 Impact factor: 8.822
Authors: Kate K Watabayashi; Ari Bell-Brown; Karma Kreizenbeck; Kathryn Egan; Gary H Lyman; Dawn L Hershman; Kathryn B Arnold; Aasthaa Bansal; William E Barlow; Sean D Sullivan; Scott D Ramsey Journal: BMC Health Serv Res Date: 2022-04-01 Impact factor: 2.655