Associative Analysis of Inefficiencies and Station Activity Levels in Emergency Response
2. Related Work
3. Research Methodology
3.1. Portuguese Emergency Response Dataset
3.2. Task Description
- a set of stations S from which response vehicles are dispatched, where each station has a fixed location;
- a set of vehicles V, where each vehicle belongs to a well-established category (e.g., vehicles with basic versus advanced life support), is assigned to a base station , and is uniquely identified;
- a set of medical emergency response records E. Each response in E contains information about the time and location of its occurrence, as well as the station that responded to it. The responding vehicle is one of the vehicles stationed in s.
- How correlated are potential inefficiencies with the activity levels of closer stations?
- Are there specific areas or days in which potential inefficiencies occurred often?
- Can stations be profiled according to their activity level to promote actionability?
3.3. Discovery and Analysis of Potential Inefficiencies
3.3.1. Identification of Potential Inefficiencies
|Algorithm 1 Potential inefficiencies identification algorithm|
Input: : emergencies, : stations, : threshold|
Output: list of potential inefficiencies
3.3.2. Estimation of Station Activity Level
|Algorithm 2 Activity level estimation algorithm|
| Input:: stations, : dates, : timestamps, : time span length, : window length|
Output: Activity level of each station
3.3.3. Validation and Analysis
4. Results and Discussion
4.1. RQ1: How Correlated Are Potential Inefficiencies with Activity Levels of Closer Stations?
4.2. RQ2: Are There Specific Areas or Days in Which Potential Inefficiencies Occurred Often?
4.3. RQ3: Can Stations Be Profiled According to Their Activity Level to Promote Actionability?
- We introduce a robust and efficient approach for the identification of potential inefficiencies in emergency response data that is sensitive to differences in the areas of coverage of stations. A tool, DAPI, is made available to this end.
- Furthermore, said approach is able to perform statistical analysis on response bottlenecks in relation to station activity levels with the aim of assessing potential causes. DAPI is able to perform this assessment in the presence of spatiotemporal dispatch information only, thus being applicable to EMS systems with minimal records of historical emergency data.
- We offer the possibility of visualizing potential inefficiencies in interactive maps under a parameterizable spatiotemporal footprint. DAPI integrates these graphical facilities with guarantees of statistical significance, serving as a valuable decision support tool for EMS stakeholders.
- The majority of potential inefficiencies are significantly correlated with high activity levels among closer stations for both ambulance and VMER data across different years.
- Potential inefficiencies appear to be geographically located according to dense clusters. Some clusters show evidence of a correlation between potential inefficiencies and high activity levels, while some clusters do not, suggesting that inefficiencies are associated with some unknown factors.
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
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|Mean Activity||p-Value of|
|No. of||No. of Potential||Level of||Wilcoxon Signed|
|Group||Responses||Inefficiencies||Closer Stations||Rank Test|
|No. of||Mean Activty||p-Value of|
|Potential||Level of||Wilcoxon Signed|
|Cluster||Inefficiencies||Closer Stations||Ranked Test|
|Porto area (red)||6611||+0.2150|
|Setúbal area (dark green)||3122||+0.1333|
|Northwest Lisbon (purple)||1739||+0.2448|
|South Braga (light green)||1546||+0.0463|
|Sintra area (brown)||1501||+0.2789|
|East Lisbon (pink)||1306||+0.1348|
|Seixal and Almada (blue)||779||+0.1053|
|Faro area (yellow)||774||+0.3171|
|Central Braga (orange)||695||+0.3204|
|No. of||Mean Activty||p-Value of|
|Cluster||Potential||Level of||Wilcoxon Signed|
|Area||Inefficiencies||Closer Stations||Ranked Test|
|No. of||Mean Activity||p-Value of|
|Potential||Level of||Wilcoxon Signed|
|Cluster||Inefficiencies||Closer Stations||Ranked Test|
|Oieras and Cascais, Lisbon||161||+0.2308|
|M: Sesimbra, Setúbal||154||+0.1046|
|Mean Activity||Median Activty||Ratio of|
|Station||Level||Level||+ Activity Level|
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Tiam-Lee, T.J.; Henriques, R.; Manquinho, V. Associative Analysis of Inefficiencies and Station Activity Levels in Emergency Response. ISPRS Int. J. Geo-Inf. 2022, 11, 356. https://doi.org/10.3390/ijgi11070356
Tiam-Lee TJ, Henriques R, Manquinho V. Associative Analysis of Inefficiencies and Station Activity Levels in Emergency Response. ISPRS International Journal of Geo-Information. 2022; 11(7):356. https://doi.org/10.3390/ijgi11070356Chicago/Turabian Style
Tiam-Lee, Thomas James, Rui Henriques, and Vasco Manquinho. 2022. "Associative Analysis of Inefficiencies and Station Activity Levels in Emergency Response" ISPRS International Journal of Geo-Information 11, no. 7: 356. https://doi.org/10.3390/ijgi11070356