Queuing Theory Analysis of Patient Waiting Times in University Hospitals: M/M/c and M/G/c Models

Alkan Durmuş

Makale detayları

Queuing Theory Analysis of Patient Waiting Times in University Hospitals: M/M/c and M/G/c Models

Yazarlar:

Alkan Durmuş

Yayıncı:

Dokuz Eylul University

Ana Başlıklar:

İşletme

Dergi:

İzmir İktisat Dergisi Vol.40 Issue 4, pp.1252-1286

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358680

pISSN:

1308-8505

Anahtar kelimeler:

Özet:

 This study was conducted to improve service processes and optimize resource utilization by analyzing patient waiting times in the orthopedics outpatient clinic of a university hospital. Using the queuing theory models MMc and MGc, the systems current performance was assessed, and scenarios simulating increased service demand were examined. The MMc model showed that the system operates efficiently under low-density conditions. Assuming exponential distribution of service times. The queue waiting time was calculated as 17.85 minutes, and total system waiting time as 34.02 minutes. The model revealed that patient demands were met with the number of doctors available. The MGc model provided more realistic results by taking into account variations in service times. Queue waiting time was calculated as 9.06 minutes and total waiting time as 25.22 minutes. However, service time variability during peak hours caused an increase in waiting times. In the scenario analyses, when the patient arrival rate was increased from 10 to 100, both models handled the increased load. However, while the MMc model maintained stable performance, the MGc model yielded more accurate and realistic results. Targeting a 70-80 density rate, it was determined that the number of available doctors was generally sufficient. However, it was emphasized that additional resource planning may be required in case of excessive demand. In conclusion, queuing theory models are a strategic tool for optimizing waiting times, increasing patient satisfaction and using resources efficiently. Especially under variable demand conditions, the MGc model offers a more appropriate solution.

 This study was conducted to improve service processes and optimize resource utilization by analyzing patient waiting times in the orthopedics outpatient clinic of a university hospital. Using the queuing theory models MMc and MGc, the systems current performance was assessed, and scenarios simulating increased service demand were examined. The MMc model showed that the system operates efficiently under low-density conditions. Assuming exponential distribution of service times. The queue waiting time was calculated as 17.85 minutes, and total system waiting time as 34.02 minutes. The model revealed that patient demands were met with the number of doctors available. The MGc model provided more realistic results by taking into account variations in service times. Queue waiting time was calculated as 9.06 minutes and total waiting time as 25.22 minutes. However, service time variability during peak hours caused an increase in waiting times. In the scenario analyses, when the patient arrival rate was increased from 10 to 100, both models handled the increased load. However, while the MMc model maintained stable performance, the MGc model yielded more accurate and realistic results. Targeting a 70-80 density rate, it was determined that the number of available doctors was generally sufficient. However, it was emphasized that additional resource planning may be required in case of excessive demand. In conclusion, queuing theory models are a strategic tool for optimizing waiting times, increasing patient satisfaction and using resources efficiently. Especially under variable demand conditions, the MGc model offers a more appropriate solution.

 This study was conducted to improve service processes and optimize resource utilization by analyzing patient waiting times in the orthopedics outpatient clinic of a university hospital. Using the queuing theory models MMc and MGc, the systems current performance was assessed, and scenarios simulating increased service demand were examined. The MMc model showed that the system operates efficiently under low-density conditions. Assuming exponential distribution of service times. The queue waiting time was calculated as 17.85 minutes, and total system waiting time as 34.02 minutes. The model revealed that patient demands were met with the number of doctors available. The MGc model provided more realistic results by taking into account variations in service times. Queue waiting time was calculated as 9.06 minutes and total waiting time as 25.22 minutes. However, service time variability during peak hours caused an increase in waiting times. In the scenario analyses, when the patient arrival rate was increased from 10 to 100, both models handled the increased load. However, while the MMc model maintained stable performance, the MGc model yielded more accurate and realistic results. Targeting a 70-80 density rate, it was determined that the number of available doctors was generally sufficient. However, it was emphasized that additional resource planning may be required in case of excessive demand. In conclusion, queuing theory models are a strategic tool for optimizing waiting times, increasing patient satisfaction and using resources efficiently. Especially under variable demand conditions, the MGc model offers a more appropriate solution.

 Bu çalışma, bir üniversite hastanesinin ortopedi polikliniğinde hasta bekleme sürelerini analiz ederek hizmet süreçlerini iyileştirme ve kaynak kullanımını optimize etme amacıyla gerçekleştirilmiştir. Kuyruk teorisi modelleri olan MMc ve MGc kullanılarak sistemin mevcut performansı değerlendirilmiş ve yoğunluk artışı senaryoları incelenmiştir. MMc modeli, hizmet sürelerinin üstel dağıldığını varsayarak sistemin düşük yoğunluk koşullarında verimli çalıştığını göstermiştir. Kuyruk bekleme süresi 17,85 dakika, toplam sistem bekleme süresi ise 34,02 dakika olarak hesaplanmıştır. Model, mevcut doktor sayısıyla hasta taleplerinin karşılandığını ortaya koymuştur. MGc modeli, hizmet sürelerindeki varyasyonları dikkate alarak daha gerçekçi sonuçlar sunmuştur. Kuyruk bekleme süresi 9,06 dakika, toplam bekleme süresi ise 25,22 dakika olarak hesaplanmıştır. Ancak yoğun saatlerde hizmet süresi değişkenliği bekleme sürelerinde artışa neden olmuştur. Senaryo analizlerinde, hasta giriş oranının 10dan 100e kadar artırılması durumunda, her iki model de artan yoğunluğu karşılamış, ancak MMc modeli stabil performans sergilerken, MGc modeli daha hassas ama gerçekçi sonuçlar sunmuştur. 70-80 yoğunluk oranı hedeflenerek mevcut doktor sayısının genellikle yeterli olduğu belirlenmiştir. Ancak aşırı talep durumunda ek kaynak planlaması gerekebileceği vurgulanmıştır. Sonuç olarak, kuyruk teorisi modelleri, bekleme sürelerini optimize etme, hasta memnuniyetini artırma ve kaynakları etkin kullanma açısından stratejik bir araçtır. Özellikle değişken talep koşullarında MGc modeli daha uygun bir çözüm sunmaktadır.

Makale detayları

Queuing Theory Analysis of Patient Waiting Times in University Hospitals: M/M/c and M/G/c Models

Yazarlar:

Alkan Durmuş

Yayıncı:

Dokuz Eylul University

Ana Başlıklar:

İşletme

Dergi:

İzmir İktisat Dergisi Vol.40 Issue 4, pp.1252-1286

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358680

pISSN:

1308-8505

Queuing Theory

M/M/c Model

M/G/c Model

Patient Waiting Times

Orthopedics Outpatient Clinic

Health Service EfficiencyKuyruk Teorisi

M/M/c Modeli

M/G/c Modeli

Hasta Bekleme Süreleri

Ortopedi Polikliniği

Sağlık Hizmeti Verimliliği

Sayı

Makale detayları

Yazarlar: Alkan Durmuş

Yayıncı: Dokuz Eylul University

Ana Başlıklar: İşletme

Dergi: İzmir İktisat Dergisi Vol.40 Issue 4, pp.1252-1286

Belge Tipi: Makale

Yayın Tarihi: 1/2025

Belge Dili: Türkçe

Document ID (Org No.): 2001358680

pISSN: 1308-8505

Sayı

Yazarlar:

Alkan Durmuş

Yayıncı:

Dokuz Eylul University

Ana Başlıklar:

İşletme

Dergi:

İzmir İktisat Dergisi Vol.40 Issue 4, pp.1252-1286

Belge Tipi:

Makale

Yayın Tarihi:

1/2025

Belge Dili:

Türkçe

Document ID (Org No.):

2001358680

pISSN:

1308-8505