Table 2.
A subset of the 35 rules used by the system to detect relevant allergy information
| Rule | Description | Comments |
|---|---|---|
| 1. Document filtering | Documents must contain concept-related words, or else they are filtered out [7, 32] | E.g., for the clinical concept of “allergy”, documents must contain concept-related words associated with e.g. “allergy”, “allergen” “allergic reaction” or “symptom” |
| 2. Paragraph Boundary | Concept-related words must be located within the same paragraph [81, 82] | E.g., in case an “allergy”, “reaction” or “symptom” is identified in another sentence, a check for conformity with rule 2 and 3 is initiated again |
| 3. Window of context | Allergy concept-related words must be located within the same sentence, or if located in adjacent sentences must be in proximity (within a ± 6 word distance), of other identified allergy concept-related words [9, 69] | Distance tolerance can easily be adjusted in the system. We experimented with different scopes. As also reported by Afzal et al. [5], we found a six to ten word distance to be optimal |
| 4. Dependency |
Concept-related words can be of type [32] 1) Exist alone 2) Primary (exist when supported by 1 or 3) 3) Secondary (depend on 2 for existence) |
E.g., for the clinical concept of “allergy”: while words of type 1 (strong indicators like e.g. “Anaphylaxis”) are allowed to “exist alone” in a sentence, other types must conform to rules 2 and 3 |
| 5. Part of compound words | In case concept-related words are found as part of seldom-used compound words, they are also highlighted [69, 83, 84] | E.g., “Cave information” |
| 6. Header detection | Specific rules apply for relevant text detected below headers until the start of the next detected paragraph [9, 69] | E.g., in case of “Allergies” header, all allergy concept-related words (with certain limitations) should be highlighted |
| 7. Highlight color | The degree of word concept-relatedness determines (from low to high) text highlight color yellow, orange or red [81] | E.g., allergy concept-related words are highlighted in the text |
| 8. Disambiguation | Often repeated words where non-conceptual meaning (“word sense disambiguation”) is alluded are filtered out [9, 18] | E.g., «the patient reacts to light» in eye examination reports |
| 9. Negation | Detection of positive/negative contexts is handled by checking for the existence of negations in the text [6, 33] | E.g., “reacts to Penicillin” versus “does not react to Penicillin” |
| 10. Permutations | Use of the word permutations dictionary may be enabled or disabled [13, 69] | An algorithm detects and stores the most used misspellings not already covered by the clinical knowledge base |
| 11. Omitted documents | EHR documents of certain types or with certain headers or contents may be left out [28, 83] | Documents which, e.g., contain specific sensitive information may be left out of the results for some users |
| 12. Concept search access control | Performing search for specific clinical concepts may be assigned or restricted to a group of users |
Group of users may be defined in a flexible way E.g., a clinical department or individual users |