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1.
Health Syst (Basingstoke) ; 8(1): 52-73, 2019.
Article in English | MEDLINE | ID: mdl-31214354

ABSTRACT

Cancer is a disease affecting increasing numbers of people. In the UK, the proportion of people affected by cancer is projected to increase from 1 in 3 in 1992, to nearly 1 in 2 by 2020. Health services to tackle cancer can be grouped broadly into prevention, diagnosis, staging, and treatment. We review examples of Operational Research (OR) papers addressing decisions encountered in each of these areas. In conclusion, we find many examples of OR research on screening strategies, as well as on treatment planning and scheduling. On the other hand, our search strategy uncovered comparatively few examples of OR models applied to reducing cancer risks, optimising diagnostic procedures, and staging. Improvements to cancer care services have been made as a result of successful OR modelling. There is potential for closer working with clinicians to enable the impact of other OR studies to be of greater benefit to cancer sufferers.

2.
Int J Nurs Stud ; 97: 7-13, 2019 Sep.
Article in English | MEDLINE | ID: mdl-31129446

ABSTRACT

Despite a long history of health services research that indicates that having sufficient nursing staff on hospital wards is critical for patient safety, and sustained interest in nurse staffing methods, there is a lack of agreement on how to determine safe staffing levels. For an alternative viewpoint, we look to a separate body of literature that makes use of operational research techniques for planning nurse staffing. Our goal is to provide examples of the use of operational research approaches applied to nurse staffing, and to discuss what they might add to traditional methods. The paper begins with a summary of traditional approaches to nurse staffing and their limitations. We explain some key operational research techniques and how they are relevant to different nurse staffing problems, based on examples from the operational research literature. We identify three key contributions of operational research techniques to these problems: "problem structuring", handling complexity and numerical experimentation. We conclude that decision-making about nurse staffing could be enhanced if operational research techniques were brought in to mainstream nurse staffing research. There are also opportunities for further research on a range of nurse staff planning aspects: skill mix, nursing work other than direct patient care, quantifying risks and benefits of staffing below or above a target level, and validating staffing methods in a range of hospitals.


Subject(s)
Health Workforce , Nursing Research , Nursing Staff , Personnel Staffing and Scheduling , Models, Organizational
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