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

Valente R, Testi A, Tanfani E, Fato M, Porro I, Santo M, Santori G, Torre G, Ansaldo G - BMC Health Serv Res (2009)

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Health Management Unit, S. Martino University Hospital, L.go R. Benzi 10, 16132 Genoa, Italy. roberto.valente@gmail.com

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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Related in: MedlinePlus

Appropriate Performance Index (API). Lines show monthly values of Appropriate Performance Index (API) of admitted patients at index days, in the previous 30 days, within each URG (A1, A2, B, C and D). API is defined in Table 2. URGs classification is shown in Table 1.
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Figure 6: Appropriate Performance Index (API). Lines show monthly values of Appropriate Performance Index (API) of admitted patients at index days, in the previous 30 days, within each URG (A1, A2, B, C and D). API is defined in Table 2. URGs classification is shown in Table 1.

Mentions: The system prototype provided the rich set of waiting list data and detailed performance parameters described in table 2. Informative reports (days attended minimums, maximums, means) were automatically generated. As shown in figures 2 and 3 by cross-sectional view, the informative system allowed the generation of advanced datasets and runtime graphic displays. The frequency distribution of the waiting patients could be represented within each URG (Figure 2) or in an overall mosaic (Figure 3), bringing a comprehensible visualization of waiting list population. Similar views could be compared at different time-series end point (Figures 4 to 6): clinical users, managers and patients could be informed in real time about the trends of the waiting list and about the current expected waiting times.


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

Valente R, Testi A, Tanfani E, Fato M, Porro I, Santo M, Santori G, Torre G, Ansaldo G - BMC Health Serv Res (2009)

Appropriate Performance Index (API). Lines show monthly values of Appropriate Performance Index (API) of admitted patients at index days, in the previous 30 days, within each URG (A1, A2, B, C and D). API is defined in Table 2. URGs classification is shown in Table 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2651867&req=5

Figure 6: Appropriate Performance Index (API). Lines show monthly values of Appropriate Performance Index (API) of admitted patients at index days, in the previous 30 days, within each URG (A1, A2, B, C and D). API is defined in Table 2. URGs classification is shown in Table 1.
Mentions: The system prototype provided the rich set of waiting list data and detailed performance parameters described in table 2. Informative reports (days attended minimums, maximums, means) were automatically generated. As shown in figures 2 and 3 by cross-sectional view, the informative system allowed the generation of advanced datasets and runtime graphic displays. The frequency distribution of the waiting patients could be represented within each URG (Figure 2) or in an overall mosaic (Figure 3), bringing a comprehensible visualization of waiting list population. Similar views could be compared at different time-series end point (Figures 4 to 6): clinical users, managers and patients could be informed in real time about the trends of the waiting list and about the current expected waiting times.

Bottom Line: 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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: Health Management Unit, S. Martino University Hospital, L.go R. Benzi 10, 16132 Genoa, Italy. roberto.valente@gmail.com

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.

Show MeSH
Related in: MedlinePlus