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Published in Marilyn Sue Bogner, Human Error in Medicine, 2018
An anesthetist is anyone who administers anesthesia. Anesthesiology is a medical specialty, and an anesthesiologist is a physician who has specialized in anesthesiology. In the United States (and in a few other places), there are nurse anesthetists who are registered nurses with several years of training in anesthesia. There is a mandatory certification process for nurse anesthetists, such that they are often known as “Certified Nurse Anesthetists” or CRNAs. They can administer general anesthesia and monitor patients under the supervision of a physician, who may or may not be an anesthesiologist. Fifty percent of anesthetics in the United States are conducted with nurse anesthetists. In this chapter, the term anesthetist refers generically to whoever is the anesthesia provider.
Blood transfusion prediction using restricted Boltzmann machines
Published in Computer Methods in Biomechanics and Biomedical Engineering, 2020
Jenny Cifuentes, Yuanyuan Yao, Min Yan, Bin Zheng
The data-set includes 5000 surgical cases collected from 9 hospitals in Zhejiang of China between 2007 and 2011. The primary objective for setting up this data-set was assessing the rate of inappropriate blood transfusion during the perioperative phase in Zhejiang. The study protocol was reviewed and approved by the Ethics Review Committee at the Second Affiliated Hospital of Zhejiang University. Initial report for this work was published in 2018 (Yao et al. 2018). In order to collect the information, a structured survey form was planned by an expert committee (conformed by anesthesiologists and hospital quality control officers) to gather the characteristic patient information used during the evaluation of the quality of blood management (Yao et al. 2018). The reported cases included adult hospitalized patients. For each registration, the patient’s demographic information, including age, type of admission (i.e., scheduled or emergency), and American Society of Anesthesiology (ASA) grade prior to surgery were collected. Likewise, information about the surgical procedure was recorded as well. As such, the type of surgical procedure, duration of operation, perioperative complications, and volume of blood loss during the surgery were taken into account. To assess the quality of blood management, the results of the blood laboratory tests involved the last Hb measurement before the patient was sent to the ward.
Medical specialty choice and well-being at work: Physician's personality as a moderator
Published in Archives of Environmental & Occupational Health, 2019
Sari Mullola, Christian Hakulinen, David Gimeno Ruiz de Porras, Justin Presseau, Markus Jokela, Jukka Vänskä, Tiina Paunio, Marko Elovainio
Medical specialty was self-reported in 2006, 2010, and 2015. In Finland, a medical specialist degree requires five to six years of medical practice, including at least nine months of service in public health centers, theoretical and administrative courses, and a passing grade on a national written exam. If they had more than one specialty, they were advised to report the most recent one. Specialties were categorized into 12 different specialties according to the classification used by FMA57: (1) Anesthesiology and Intensive Care Medicine; (2) Surgery (including all surgeon sub-specialties); (3) Pediatrics (including Child neurology and Children's disease); (4) Obstetrics and Gynecology; (5) Psychiatry (including Child Psychiatry, Adolescent Psychiatry, and Forensic Psychiatry); (6) Radiology; (7) Internal Medicine and Oncology; (8) Ophthalmology and Otorhinolaryngology; (9) Other specialties of Internal Medicine (e.g., Endocrinology, Gastroenterology, Dermatology and Allergology); (10) Occupational Health; (11) General Practice; (12) Hospital Service Specialties (e.g., Clinical Microbiology, Forensic Medicine, Clinical genetics). The most recent specialty between study intervals was chosen for analyses purposes.
Health analytics in business research: a literature review
Published in Journal of Management Analytics, 2023
Quanchen Liu, Mengli Yu, Bingqing Xiong, Zhao Cai, Pengzhu Zhang, Chee-Wee Tan
Fifth, surgical scheduling has also been a hot topic, which can further affect healthcare quality and patient satisfaction. For example, Ko et al. (2019) analysed over one million physician reviews across 17 medical specialties to examine the relationship between operational efficiency and patient satisfaction. They found that operational inefficiency negatively influences patient satisfaction. Aiming at balancing benefit against patient waiting time and clinic overtime costs, Wang et al. (2018) developed a coordinated pre-operative scheduling approach between Anesthesiology and Internal Medicine to optimize patients’ medical conditions prior to surgery. Considering surgical scheduling with constrained patient waiting times, Zhou et al. (2021) proposed an algorithm that sorts surgical cases according to their surgical duration variability. Bavafa et al. (2019) examined the allocation of daily hospital service capacity for elective surgical procedures amidst arbitrary finite support distributions. An innovative, multidimensional model of the inverse news vendor problem was proposed, in which multiple types of demand compete for multiple types of service capacity, aimed at addressing the allocation of two constraining hospital resources: operating room (OR) and recovery bed capacity. To consider integrated scheduling decisions that simultaneously consider capacity usage at all locations in a hospital, Liu et al. (2019) have developed a Markov decision process model for scheduling surgery patients on a daily basis, explicitly considering the length of stay in the hospital following surgery and the number of inpatients. In addition, under the context of performing robot-assisted surgery, Mukherjee and Sinha (2020) addressed the twin objectives of a hospital performing robot-assisted surgery: maximizing clinical outcome benefits and minimizing total costs of the procedure.