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      A model to prioritize access to elective surgery on the basis of clinical urgency and waiting time

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          Abstract

          Background

          Prioritization of waiting lists for elective surgery represents a major issue in public systems in view of the fact that patients often suffer from consequences of long waiting times. In addition, administrative and standardized data on waiting lists are generally lacking in Italy, where no detailed national reports are available. This is true although since 2002 the National Government has defined implicit Urgency-Related Groups (URGs) associated with Maximum Time Before Treatment (MTBT), similar to the Australian classification. The aim of this paper is to propose a model to manage waiting lists and prioritize admissions to elective surgery.

          Methods

          In 2001, the Italian Ministry of Health funded the Surgical Waiting List Info System (SWALIS) project, with the aim of experimenting solutions for managing elective surgery waiting lists. The project was split into two phases. In the first project phase, ten surgical units in the largest hospital of the Liguria Region were involved in the design of a pre-admission process model. The model was embedded in a Web based software, adopting Italian URGs with minor modifications. The SWALIS pre-admission process was based on the following steps: 1) urgency assessment into URGs; 2) correspondent assignment of a pre-set MTBT; 3) real time prioritization of every referral on the list, according to urgency and waiting time. In the second project phase a prospective descriptive study was performed, when a single general surgery unit was selected as the deployment and test bed, managing all registrations from March 2004 to March 2007 (1809 ordinary and 597 day cases). From August 2005, once the SWALIS model had been modified, waiting lists were monitored and analyzed, measuring the impact of the model by a set of performance indexes (average waiting time, length of the waiting list) and Appropriate Performance Index (API).

          Results

          The SWALIS pre-admission model was used for all registrations in the test period, fully covering the case mix of the patients referred to surgery. The software produced real time data and advanced parameters, providing patients and users useful tools to manage waiting lists and to schedule hospital admissions with ease and efficiency. The model protected patients from horizontal and vertical inequities, while positive changes in API were observed in the latest period, meaning that more patients were treated within their MTBT.

          Conclusion

          The SWALIS model achieves the purpose of providing useful data to monitor waiting lists appropriately. It allows homogeneous and standardized prioritization, enhancing transparency, efficiency and equity. Due to its applicability, it might represent a pragmatic approach towards surgical waiting lists, useful in both clinical practice and strategic resource management.

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          Most cited references28

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          R: a language and environment for statistic computing

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            Tackling excessive waiting times for elective surgery: a comparative analysis of policies in 12 OECD countries.

            This paper compares policies to tackle excessive waiting times for elective surgery in 12 OECD countries. It is found that waiting times may be reduced by acting on the supply of or on the demand for surgery (or both). On the supply side, evidence suggests that both capacity and financial incentives towards productivity can play an important role. On the demand side, inducing a raising of clinical thresholds may reduce waiting times but may also provoke tension between clinicians and policy makers. Preliminary evidence also suggests that an increase in private health insurance coverage may reduce waiting times.
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              Waiting for elective general surgery: impact on health related quality of life and psychosocial consequences

              Background Long waiting times for elective surgical treatment threaten timely care provision in several countries. The purpose of this study was to assess the impact of waiting for elective general surgery on the quality of life and psychosocial health of patients. Methods A cross-sectional questionnaire study with postoperative follow-up was performed among patients on waiting lists for surgical treatment of varicose veins (n = 176), inguinal hernia (n = 201), and gallstones (n = 128) in 27 hospitals. Results In each group the waiting period involved worse general health perceptions (GHPQ), more problems in quality of life (EuroQoL), and raised levels of anxiety (STAI) as compared to after surgery (all differences: p < 0.05). Quality of life was not affected in 19–36% of patients. Emotional reactions to waiting were most negative among patients with gallstones. Prior information about the duration of the wait reduced the negativity of these reactions (p < 0.05). Social activities were affected in 39% to 48% of the patients and 18%-23% of employed patients reported problems with work during the wait. Having waited a longer time was associated with worse quality of life among patients with inguinal hernia. Longer waited times also engendered more negative reactions to waiting among patients with inguinal hernia and gallstones (multilevel regression analysis, p < 0.01). Conclusion Waiting for general surgery mainly involves a prolonged period of decreased health and an affected psychological and social life of the patient in waiting. Variation in the severity of these consequences across patients indicates that the prioritisation of patients could reduce the overall burden of waiting. Early information about the duration of the delay could further promote a patient's acceptance of waiting.
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                Author and article information

                Journal
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central
                1472-6963
                2009
                1 January 2009
                : 9
                : 1
                Affiliations
                [1 ]Health Management Unit, S. Martino University Hospital, L.go R. Benzi 10, 16132 Genoa, Italy
                [2 ]Department of Economy and Quantitative Method, University of Genoa, Via Vivaldi 5, 16126 Genoa, Italy
                [3 ]Department of Communication, Computer and System Sciences, University of Genoa, Via all'Opera Pia 13, 16145 Genoa, Italy
                [4 ]Department of Transplantation, S. Martino University Hospital, L.go R. Benzi 10, 16132 Genoa, Italy
                [5 ]General Surgery Clinic, Department of Surgery, S. Martino University Hospital, L.go R. Benzi 10, 16132 Genoa, Italy
                Article
                1472-6963-9-1
                10.1186/1472-6963-9-1
                2651867
                19118494
                9450d535-d4fc-49ab-833e-6a1b9d365e8f
                Copyright © 2009 Valente et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 September 2008
                : 1 January 2009
                Categories
                Research Article

                Health & Social care
                Health & Social care

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