Rachel Wilf-Miron1, Ilya Novikov2, Arnona Ziv3, Avishai Mandelbaum4, Yaacov Ritov5, Osnat Luxenburg6. 1. Health Technology Assessment Unit, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel; Dept. of Health Promotion, School of Public Health, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel. Electronic address: r.w.miron@gmail.com. 2. Biostatistics & Biomathematics Unit, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel. Electronic address: IliaN@gertner.health.gov.il. 3. Information & Computerization Unit, Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621, Israel. Electronic address: arnonaz@gertner.health.gov.il. 4. Faculty of Industrial Engineering & Management, Technion, Haifa, Israel. Electronic address: avishaimandelbaum51@gmail.com. 5. Department of Statistics, University of Michigan, USA. Electronic address: yaacov.ritov@gmail.com. 6. Medical Technology, Health Information and Research Directorate, Ministry of Health, Jerusalem, Israel. Electronic address: osnat.luxenburg@moh.gov.il.
Abstract
BACKGROUND: Monitoring waiting time (WT) in healthcare systems is essential, since long WT are associated with adverse health outcomes, reduced patient satisfaction and increased private financing. OBJECTIVE: To describe a methodology developed for routine national monitoring of WT for community-based non-urgent specialist appointments, in a public healthcare system. METHODS: The methodology is based on data from computerized appointment scheduling systems of all Health Maintenance Organizations (HMOs) in Israel. Data included first 50 available appointments for community-based specialists and actual number of visits. Five most frequent specialties: orthopedics, ophthalmology, gynecology, dermatology and otolaryngology, were included. WT offered to HMO members for non-urgent care was calculated for two scenarios: "specific" physician and "any" physician in the region. Distribution of offered WT was calculated separately for each specialty and geographical region, combined to create the nationwide distribution. RESULTS: The methodology was tested on data extracted between December 2018-June 2019. Estimated national median WT for "specific" physician, ranged from 9 days (ophthalmology/gynecology) to 20 days (dermatology), with large variation between geographic regions. WT were 26-56 % shorter for "any" than for "specific" physician. CONCLUSIONS: This novel method offers a solution for ongoing national WT measurement, using computerized scheduling systems. It integrates two scenarios for appointment scheduling and allows identification of differences between specialties and regions, setting the ground for interventions to strengthen public healthcare systems.
BACKGROUND: Monitoring waiting time (WT) in healthcare systems is essential, since long WT are associated with adverse health outcomes, reduced patient satisfaction and increased private financing. OBJECTIVE: To describe a methodology developed for routine national monitoring of WT for community-based non-urgent specialist appointments, in a public healthcare system. METHODS: The methodology is based on data from computerized appointment scheduling systems of all Health Maintenance Organizations (HMOs) in Israel. Data included first 50 available appointments for community-based specialists and actual number of visits. Five most frequent specialties: orthopedics, ophthalmology, gynecology, dermatology and otolaryngology, were included. WT offered to HMO members for non-urgent care was calculated for two scenarios: "specific" physician and "any" physician in the region. Distribution of offered WT was calculated separately for each specialty and geographical region, combined to create the nationwide distribution. RESULTS: The methodology was tested on data extracted between December 2018-June 2019. Estimated national median WT for "specific" physician, ranged from 9 days (ophthalmology/gynecology) to 20 days (dermatology), with large variation between geographic regions. WT were 26-56 % shorter for "any" than for "specific" physician. CONCLUSIONS: This novel method offers a solution for ongoing national WT measurement, using computerized scheduling systems. It integrates two scenarios for appointment scheduling and allows identification of differences between specialties and regions, setting the ground for interventions to strengthen public healthcare systems.