From: Analytical methods for identifying sequences of utilization in health data: a scoping review
Stated aim in article | N | Publications | |
Proposal of method | 27 | [6, 8,9,10, 20, 21, 24, 29, 31, 34, 36,37,38, 40, 41, 43,44,45,46,47, 49, 51, 55, 57, 59, 62, 66] | |
Trajectory | 28 | [5,6,7,8,9,10, 20, 21, 23, 25, 27, 35, 36, 38,39,40, 42, 44,45,46,47, 54,55,56, 58, 61, 62, 66] | |
Patterns | 20 | [19, 24, 26, 28,29,30,31,32,33, 37, 41, 43, 48,49,50, 52, 53, 57, 59, 60] | |
Phenotyping | 9 | ||
Prediction | 11 | ||
Stated method in article | N (%) | Publications | |
Clustering | 16 (31Â %) | ||
   Hierarchical | 7 | ||
   Partitioning | 5 | ||
   Other Clustering | 4 | ||
Pattern Mining (PM) | 16 (31Â %) | [10, 26, 28, 30,31,32, 34, 37, 38, 41, 43, 48,49,50, 57, 60] | |
   PM + Clustering | 3 | ||
Markov Model | 10 (20Â %) | ||
   MM + Clustering | 7 | ||
Other | 9 (18Â %) | ||
Presentation of results | N | Publications | |
Visualization | 36 | Â | Â |
   Trajectory | 28 | [5,6,7,8,9,10, 21, 23, 25, 27, 28, 30, 33, 35,36,37,38,39,40, 42, 44, 45, 54,55,56, 58, 61, 66] | |
   Patterns | 8 | ||
      Weighted | 8 / 4 | ||
      Sankey | 5 / 1 | Patterns: [49] | |
      Timeline | 10 / 1 | Patterns: [24] | |
Tabular | 22 | Â | Â |
   Trajectory | 5 | ||
   Patterns | 17 | [10, 22, 26, 29, 32, 37, 38, 43, 44, 46, 48,49,50, 52, 53, 57, 60] | |
      Weighted | 2/14 | Patterns: [10, 22, 29, 32, 37, 38, 43, 44, 46, 48, 50, 52, 53, 60] |