Affiliation:
1. İSTANBUL MEDİPOL ÜNİVERSİTESİ
2. ALANYA HAMDULLAH EMİN PAŞA ÜNİVERSİTESİ
3. ISTANBUL MEDIPOL UNIVERSITY
Abstract
The time spent waiting is an important problem regarding patient satisfaction and hospital efficiency, and increases the need for evidence-based information for management to make decisions towards a solution. This study aims to examine the process flows in hospitals based on actual data with the intent to design a better service delivery system and set a pattern in terms of determining the congestion in the process and planning the necessary improvements. For this purpose, the data sets for 2016 pertaining to secondary and tertiary level hospitals in Turkey, which are stored in the central physician appointment system (CPAS), are investigated. The data is analyzed through pre-processing, cleaning and transformation stages. Congestion patterns are determined by days and hours spent in hospitals. Monday is found to be the day with the highest patient density and the longest wait time in Turkish hospitals. Additionally, when analyzed by working hours, it is determined that the first 2 hours in the morning (9.00 a.m. to 11.00 a.m.) is the period when most patentse are examined. The lunchtime (between 12.00 p.m. - 1.00 p.m.) and the afternoon from 4.00 p.m. to 5.00 p.m. are the times when patient density is the lowest, but average wait time is the longest. Turkish hospitals are found to be particularly congested on some days and during some hours regarding patient wait times. Thus, policy recommendations can be developed specifically to the days and times when congestion patterns are identified rather than suggesting a general policy. This study is the most comprehensive study conducted in Turkey through process data. The working model is reproducible in different countries and regions.
Reference33 articles.
1. 1. Au, J, Horwood, C, Hakendorf, P. and Thompson, C. (2019). ‘‘Similar Outcomes for General Medicine Patients Discharged on any day of the week’’. Internal Medicine Journal, 49 (3), 380–384. https://doi.org/10.1111/imj.14083
2. 2. Brandenburg, L, Gabow, P. and Steele, G. (2015). ‘‘Innovation and Best Practices in Health Care Scheduling’’. NAM Perspectives.
3. 3. British Columbia Medical Association (2006). ‘‘Waiting Too Long: Reducing And Better Managing Wait Times. By The BCMA’s Council On Health Economics & Policy’’. British Columbia Medical Association.
4. 4. Budinoski, K., and Trajkovik, V. (2012). ‘‘Incorporate Social Network Services In E-Government Solutions: The Case Of Macedonia’’. International Journal of EBusiness and EGovernment Studies, 1 (4), 23–35. https://doi.org/10.17226/20220
5. 5. Cantwell, K., Morgans, A., Smith, K., Livingston, M., Spelman, T. and Dietze, P. (2015). ‘‘Time of Day and Day of Week Trends in EMS Demand’’. Prehospital Emergency Care, 19 (3), 425–431. https://doi.org/10.3109/10903127.2014.995843