Advanced Temporal Language Aided Search for the OHDSI community

Juan M. Banda, Ph.D., Alison Callahan, Ph.D., David Kale, M.S. Vladimir Polony, M.S. Nigam H. Shah, MBBS, Ph.D.

Phenotyping in OHDSI

• Rule based, expert-consensus definitions• Exemplified by www.phekb.org• Implemented by ATLAS www.ohdsi.org/web/atlas/

• Probabilistic phenotyping• Relatively new• APHRODITE, ANCHOR learning• https://github.com/OHDSI/Aphrodite

Rule-based phenotypes: www.PheKB.org

• Created by community consensus• Shared as inclusion / exclusion rules

• Need to be implemented at each local site and can become quite complex

• This process is facilitate by OHDSI ATLAS

Introducing Advanced Temporal Language Aided Search

Instead of drop-down menus, we present a search interface to write phenotype definitions

Example phenotype: Type 2 diabetes mellitus

PheKB Vanderbilt definition – cases only

Available: https://phekb.org/phenotype/type-2-diabetes-demonstration-project

1) Select people over 18 years old and under 902) Define which diagnosis codes our selection can have

Example phenotype – Step 1

3) Define set of non-insulin medications the patient can have4) Define set of insulin-related medications the patient can have

Example phenotype – Step 2

5) Define abnormal glucose lab tests6) Define abnormal A1C lab results

Example phenotype – Step 3

7) Define case 1: Age over 18 AND a T2DM code AND non-insulin medication

Example phenotype – Step 4

8) Define case 2: Age over 18 AND T2DM code AND abnormal labs AND no history of non-insulin and insulin medications

Example phenotype – Step 5

9) Define case 3: Age over 18 AND abnormal lab values AND non-insulin medications

Example phenotype – Step 6

10) Finally, output the union of all different specified cases

Example phenotype – Step 7

Example phenotype search results: Type 2 diabetes mellitus

OMOP HOI - Acute Myocardial Infarction definition #4:

Available: http://omop.org/sites/default/files/OMOP%20HOI%20Acute%20Myocardial%20Infarction%204.xlsx

Example phenotype: Acute Myocardial Infarction

Occurrence of the lab test “blood troponin” LOINC codes 42757-5 or 10839-9, and lab test results ≥ the upper limit of normal in two sequential measurements, or ≥ 2 times the upper limit of normal in one measurement, and falling in a subsequent measurement. The ULN is defined as the 99th percentile of a non-MI control group, or 0.5 ng/mL if not availableOR

Occurrence of the lab test “creatinine phosphokinase MB isozyme (CK-MB)” LOINC codes 49551-5 or 13969-1, and lab test results ≥ the upper limit of normal in two sequential measurements, or ≥ 2 times the upper limit of normal in one measurement, and falling in a subsequent measurement. The ULN is defined as the 99th percentile of a non-MI control group, or 6 ng/mL if not available}AND

Occurrence of an EKG test with the LOINC codes 11524-6, 8601-7, 18843-3, 18844-1, 18810-2, 8625-6 or 8634-8 within 10 days prior or after the lab test result and any of the following readings{Any Q wave in leads V1 through V3, Q wave ≥ 5 to 30 ms in leads I, II, aVL, aVF, V4, V5, or V6OR

ST segment elevation: New or presumed new ST segment elevation at the J point in two or more contiguous leads with the cut-off points _0.2 mV in leads V1, V2, or V3 and ≥ 0.1mV in other leads (contiguity in the frontal plane is defined by the lead sequence aVL, I, inverted aVR, II, aVF, III)ORST segment depressionORT wave abnormalities

1) Find a sequence of high troponin without a low or normal finding separating them within one day

Example phenotype – Step 1

2) Find a sequence of high CKBM without a low or normal finding separating them within one day

Example phenotype – Step 2

3) Make sure we check that both lab measurements have the same trend

Example phenotype – Step 3

4) Define list of EKG CPT codes

Example phenotype – Step 4

5) Finally, output the patients with an EKG CPT code within 10 days of lab sequence in either direction

Example phenotype – Step 5

Example phenotype search results: Acute Myocardial Infarction

Built for speed

• We have implemented 55 definitions across 46 phenotypes

• Took us 2 hours, in a group of 15 people to define 38 of them

• With additional curation, about 53 hours of work

CDM extensions to support Advanced Temporal Language Aided Search

• Time in all tables (will be added in next CDM version)

• Clinical notes annotations (will be added in CDM next version)

• Consistent ICD/CPT mappings to SNOMED