Selecting a winning team: Management of surgical team composition in robotic surgery

Name: Selecting a winning team: Management of surgical team composition in robotic surgery
Author: Bayram, A., Solak, S., Harmanli, O., Cesaret, Bahriye

İsim	Selecting a winning team: Management of surgical team composition in robotic surgery
Yazar	Bayram, A., Solak, S., Harmanli, O., Cesaret, Bahriye
Basım Tarihi:	2023-01
Basım Yeri	- Elsevier
Konu	OR in health services, Resource planning, Robotic surgery, Surgical team composition
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0360-8352
Kayıt Numarası	9cba4ae3-67f4-4c18-8bbd-4be5ee82a2db
Lokasyon	Business Administration
Tarih	2023-01
Örnek Metin	Surgical robots can offer higher precision, flexibility, and control during surgeries compared to conventional approaches. Robotic surgeries lead to a decrease in surgical error rates, lengths of hospital stays, and patient recovery times. The effectiveness of robotic surgeries depends on many factors, including the individual performance of team members. Although the experience of every team member makes a difference, the performance in the operating room depends as well on the cohesion among surgical team members. In this study, we address a team composition problem in robotic surgery in which we evaluate the efficiency of an operating room by assessing individual and dependent performances of surgical team members. We build a two-stage stochastic programming model, where the team members’ performance values are stochastic, to decide on team compositions. We propose two easy-to-implement algorithms based on implementations of data analyses and a stochastic programming model to identify surgical team compositions where the resulting computational difficulties are addressed through the Lagrangian decomposition procedure. We also describe computational results based on actual historical data, which indicate that the operating room time and surgical team performances can be improved if the proposed policies are implemented. With the model developed, surgical team composition decisions can be made more systematically and effectively. We also highlight the importance of considering individual and dependent performances of all surgical team members on operating room time and overall team performance.
DOI	10.1016/j.cie.2022.108819
Cilt	175

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Selecting a winning team: Management of surgical team composition in robotic surgery

Yazar Bayram, A., Solak, S., Harmanli, O., Cesaret, Bahriye

Basım Tarihi 2023-01

Basım Yeri - Elsevier

Konu OR in health services, Resource planning, Robotic surgery, Surgical team composition

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0360-8352

Kayıt Numarası 9cba4ae3-67f4-4c18-8bbd-4be5ee82a2db

Lokasyon Business Administration

Tarih 2023-01

Örnek Metin Surgical robots can offer higher precision, flexibility, and control during surgeries compared to conventional approaches. Robotic surgeries lead to a decrease in surgical error rates, lengths of hospital stays, and patient recovery times. The effectiveness of robotic surgeries depends on many factors, including the individual performance of team members. Although the experience of every team member makes a difference, the performance in the operating room depends as well on the cohesion among surgical team members. In this study, we address a team composition problem in robotic surgery in which we evaluate the efficiency of an operating room by assessing individual and dependent performances of surgical team members. We build a two-stage stochastic programming model, where the team members’ performance values are stochastic, to decide on team compositions. We propose two easy-to-implement algorithms based on implementations of data analyses and a stochastic programming model to identify surgical team compositions where the resulting computational difficulties are addressed through the Lagrangian decomposition procedure. We also describe computational results based on actual historical data, which indicate that the operating room time and surgical team performances can be improved if the proposed policies are implemented. With the model developed, surgical team composition decisions can be made more systematically and effectively. We also highlight the importance of considering individual and dependent performances of all surgical team members on operating room time and overall team performance.

DOI 10.1016/j.cie.2022.108819

Cilt 175