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. 2022 Jun 25;19(13):7806.
doi: 10.3390/ijerph19137806.

From Survey Results to a Decision-Making Matrix for Strategic Planning in Healthcare: The Case of Clinical Pathways

Lavinia Bianco  1 , Salvatore Raffa  2   3 , Paolo Fornelli  4   5 , Rita Mancini  2   3 , Angela Gabriele  6 , Francesco Medici  7 , Claudia Battista  8 , Stefania Greco  7 , Giuseppe Croce  9 , Aldo Germani  2 , Simona Petrucci  2   3 , Paolo Anibaldi  3 , Valerio Bianco  10 , Mario Ronchetti  4   5 , Giorgio Banchieri  4   5 , Christian Napoli  3   10 , Maria Piane  2   3
Affiliations

From Survey Results to a Decision-Making Matrix for Strategic Planning in Healthcare: The Case of Clinical Pathways

Lavinia Bianco et al. Int J Environ Res Public Health. .

Abstract

Background: It is a well-known fact that the information obtained from a survey can be used in a healthcare organizational analysis; however, it is very difficult to compare the different results found in the literature to each other, even through the use of metanalysis, as the methodology is often not consistent.

Methods: Data from a survey analyzing the organizational and managerial responses adopted in pathology-specific clinical pathways (CPs) during the first two waves of the COVID-19 pandemic were used for constructing a decisional matrix, a tool called SPRIS system, consisting of four different sheets. The first sheet reports the results of the survey and, using a streetlight color system, identifies strengths and weaknesses; the second one, by assigning a priority score, establishes the priority of intervention on each of the strengths and weaknesses identified; the third sheet reports the subjective items of the questionnaire in order to identify threats and opportunities and their probability of happening; in the last sheet, a SWOT Analysis is used to calculate the performance index of the whole organization.

Results: The SPRIS system, applied to data concerning the adaptation of four CPs to the COVID-19 pandemic, showed that, whereas all the CPs had a good performance index, some concerns remained unsolved and need be addressed.

Conclusions: The SPRIS system showed to be an easily constructed tool that is able to give an overview of the organization analyzed by the survey and to produce an index that can be used in a direct quality comparison between different services or organizations.

Keywords: COVID-19; clinical pathways; comparison tool; healthcare system; strategic planning.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Workflow chart. The gray squares indicate the methodology of the first study published by the authors [14].
Figure 2
Figure 2
Graphic representation of the construction of the Excel sheets of SPRIS and the meaning of each one of them.
Figure 3
Figure 3
Example of SPRIS application. Photograph of the complete picture given by the Streetlight color system sheet, showing the first three Questionnaire Sections of the questionnaire for two CPs.
Figure 4
Figure 4
Example of Priority scores sheet of SPRIS; for each mean score, we report the correspondent classification scale, the priority score, and the category, following the conversion table. The construction of this second Excel sheet depends on the level of depth of the organizational analysis that is being applied. The analysis can be carried out at different levels: macro-dimensional, if one chooses to insert the data (mean scores) concerning the CP as a whole, with both horizontal and vertical reading; or micro-dimensional, if one choses to insert the mean scores for individual items, using only the horizontal or only the vertical.
Figure 5
Figure 5
Extraction of the last Excel sheet of SPRIS (NGSA). (A) Four tables used in the NGSWOT Analysis. (B) Sector of the sheet where the performance index is calculated.
Figure 5
Figure 5
Extraction of the last Excel sheet of SPRIS (NGSA). (A) Four tables used in the NGSWOT Analysis. (B) Sector of the sheet where the performance index is calculated.
Figure 6
Figure 6
Example of SPRIS (Streetlight PRIority Swot) application. (A) Photograph of the complete picture given by the Streetlight color system sheet, showing the first three Questionnaire Sections for two of the considered CPs. (B) Extraction of the first Questionnaire Section of the first CP. We can read the data about each item/ward (answer score in related cell; the gray circle shows as an example the score of item 1 reached by Ward 3) or about each item/CP (mean score of the answers of a single item for the CP as a whole, shown as an example for item 4 by the purple circle), or about each item/total CPs (mean score of the answers regarding a single item for all the CPs, shown as an example for item 2 by the light blue circle); for each Questionnaire Section of each CP a mean score is calculated (pink circle). (C) Extraction of the fourth Questionnaire Section of the second CP. Horizontally, we can find the data about the single question (neon green rectangle) and the fourth Questionnaire Section (blue rectangle); vertically, the data about one specific CP (dark green circle) and one of the first OU/wards (orange rectangle) are reported.
Figure 6
Figure 6
Example of SPRIS (Streetlight PRIority Swot) application. (A) Photograph of the complete picture given by the Streetlight color system sheet, showing the first three Questionnaire Sections for two of the considered CPs. (B) Extraction of the first Questionnaire Section of the first CP. We can read the data about each item/ward (answer score in related cell; the gray circle shows as an example the score of item 1 reached by Ward 3) or about each item/CP (mean score of the answers of a single item for the CP as a whole, shown as an example for item 4 by the purple circle), or about each item/total CPs (mean score of the answers regarding a single item for all the CPs, shown as an example for item 2 by the light blue circle); for each Questionnaire Section of each CP a mean score is calculated (pink circle). (C) Extraction of the fourth Questionnaire Section of the second CP. Horizontally, we can find the data about the single question (neon green rectangle) and the fourth Questionnaire Section (blue rectangle); vertically, the data about one specific CP (dark green circle) and one of the first OU/wards (orange rectangle) are reported.
Figure 7
Figure 7
(A) Photograph of the Priority scores sheet of SPRIS; for each mean score, we report the correspondent classification scale, the priority score, and the category, following the conversion table. (B) Extraction of the Priority scores sheet regarding the first Questionnaire Section of the survey referring to the first CP considered. (C) Extraction regarding the first ward considered (vertical reading of the streetlight color system). (D) Extraction regarding the items of the first Questionnaire Section (horizontal reading of the Streetlight color system). (E) Extraction regarding all eight Questionnaire Sections (horizontal reading of the streetlight color system).
Figure 8
Figure 8
Extraction of the last Excel sheet of SPRIS (NGSA). It shows the NGSWOT Analysis compiled by using the priority scores of each item, regardless of the CP or the OU/ward, and the performance index calculated with them.
Figure 9
Figure 9
Performance index calculated by using the scores of all four CPs but inserting either the single items (A) or only the Questionnaire Sections mean scores (B).
Figure 10
Figure 10
Performance indexes calculated for each CP, using the mean scores of every item of the questionnaire (A–D) and using the mean scores of every Questionnaire Section (E–H). For CP1, the deeper analysis is shown in (A), and the shallower one is in (E); for CP2, the deeper analysis is shown in (B), and the shallower one is in (F); for CP3, the deeper analysis is shown in (C), and the shallower one is in (G); lastly, for CP4, the deeper analysis is shown in (D), and the shallower one is in (H).
Figure 11
Figure 11
Performance indexes calculated for one randomly chosen OU/ward for each CP, using the mean scores of every item of the questionnaire (A,C,E,G) and using the mean scores of every Questionnaire Section (B,D,F,H). For Ward 1 of CP1, the deeper analysis is shown in (A) and the shallower one in (B); for Ward 2 of CP2, the deeper analysis is shown in (C) and the shallower one in (D); for Ward 3 of CP3, the deeper analysis is shown in (E) and the shallower one in (F); lastly, for Ward 4 of CP4, the deeper analysis is shown in (G) and the shallower one in (H).
Figure 11
Figure 11
Performance indexes calculated for one randomly chosen OU/ward for each CP, using the mean scores of every item of the questionnaire (A,C,E,G) and using the mean scores of every Questionnaire Section (B,D,F,H). For Ward 1 of CP1, the deeper analysis is shown in (A) and the shallower one in (B); for Ward 2 of CP2, the deeper analysis is shown in (C) and the shallower one in (D); for Ward 3 of CP3, the deeper analysis is shown in (E) and the shallower one in (F); lastly, for Ward 4 of CP4, the deeper analysis is shown in (G) and the shallower one in (H).
Figure 12
Figure 12
Summary of the results regarding all the Questionnaire Sections of all the CPs together.
Figure 13
Figure 13
Summary of the results regarding all the items of all the CPs together.
Figure 14
Figure 14
Summary of the results regarding all the Questionnaire Sections of the four analyzed CPs.
Figure 15
Figure 15
Summary of the results regarding all the items of the four analyzed CPs. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 15
Figure 15
Summary of the results regarding all the items of the four analyzed CPs. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 15
Figure 15
Summary of the results regarding all the items of the four analyzed CPs. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 15
Figure 15
Summary of the results regarding all the items of the four analyzed CPs. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 16
Figure 16
Summary of the results regarding all the Questionnaire Sections of the four wards analyzed, one for each CP.
Figure 17
Figure 17
Summary of the results regarding all the items of the four wards analyzed, one for each CP. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 17
Figure 17
Summary of the results regarding all the items of the four wards analyzed, one for each CP. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 17
Figure 17
Summary of the results regarding all the items of the four wards analyzed, one for each CP. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
Figure 17
Figure 17
Summary of the results regarding all the items of the four wards analyzed, one for each CP. (A) Results of CP1 and CP2. (B) Results of CP3 and CP4.
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