Nuclear medicine in the United States has grown because of advances in technology, including hybrid imaging, the introduction of new radiopharmaceuticals for diagnosis and therapy, and the development of molecular imaging based on the tracer principle, which is not based on radioisotopes. Continued growth of the field will require cost-effectiveness data and evidence that nuclear medicine procedures affect patients' outcomes. Nuclear medicine physicians and radiologists will need more training in anatomic and molecular imaging. New educational models are being developed to ensure that future physicians will be adequately prepared.
"Further, machine restriction, startup time, radiopharmaceuticals logistics, and direct care and labor time have complicated the appointment scheduling and have introduced significant difficulty for pure manual processing [3, 5–7]. Imaging procedure management has become a major part of US government expenses and scheduling effectiveness thus depends on articulated management of various criteria and factors . Existing literature on nuclear medicine is limited and most of it emphasizes procedure management [4, 6–8]. "
[Show abstract][Hide abstract] ABSTRACT: Examination in nuclear medicine exhibits scheduling difficulties due to its intricate clinical issues, such as varied radiopharmaceuticals for different diseases, machine preparation and length of scan, patients’ and hospital’s criteria and/or limitations. Many scheduling methods exist, but limited for nuclear medicine. In this paper, we present a stateless two-stage scheduling to cope with multiple criteria decision making. The first stage mostly deals with patients’ conditions. The second stage concerns more on the clinical condition and its correlations with patients’ preference which presents more complicated intertwined configurations. A greedy algorithm is proposed in the second stage to determine the (time-slot, patient) pair in linear time. The result shows a practical and efficient scheduling for nuclear medicine.
[Show abstract][Hide abstract] ABSTRACT: The increased demand for medical diagnosis procedures has been recognized as one of the contributors to the rise of health care costs in the U.S. in the last few years. Nuclear medicine is a subspecialty of radiology that uses advanced technology and radiopharmaceuticals for the diagnosis and treatment of medical conditions. Procedures in nuclear medicine require the use of radiopharmaceuticals, are multi-step, and have to be performed under strict time window constraints. These characteristics make the scheduling of patients and resources in nuclear medicine challenging. In this work, we derive a stochastic online scheduling algorithm for patient and resource scheduling in nuclear medicine departments which take into account the time constraints imposed by the decay of the radiopharmaceuticals and the stochastic nature of the system when scheduling patients. We report on a computational study of the new methodology applied to a real clinic. We use both patient and clinic performance measures in our study. The results show that the new method schedules about 600 more patients per year on average than a scheduling policy that was used in practice by improving the way limited resources are managed at the clinic. The new methodology finds the best start time and resources to be used for each appointment. Furthermore, the new method decreases patient waiting time for an appointment by about two days on average.
Health Care Management Science 03/2013; DOI:10.1007/s10729-013-9224-4 · 1.05 Impact Factor
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