quasi-relational query language for persistent standardized ehrs using no-sql databases
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Aastha Madaan, W. Chu, Y. Daigo, S. Bhalla
University of Aizu
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Quasi-Relational Query Language
for Persistent Standardized EHRs:
Using No-SQL Databases
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EHRs Big data
Lifetime data temporal nature
Epidemic Query Needs (research on population) Big Data
Need Scalable and standardized ICT infrastructure
Data-standards EHRs HL7, CEN 13606, OpenEHR
Aim Knowledge-level interoperability
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Introduction
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Single-patient
Encounter
I ntroduction (2)
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OpenEHR Archetype
Maximal Defi ni tion : may be fur ther revised
Cur rentl y: 352 archetype def ini tions
Concept: Blood Pressure (Example)
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Universal Schema: Archetypal Ser ial ization
def in i t ion
OBSERVATION[at0000] match es { -- Bloo d Pressure
data matches {
HISTORY[at0001] match es { -- history
events cardinal i ty match es {1..*; unor dered} match es {
EVENT[at0006] occu rrences match es {0..*} match es { -- any event
data matches {
ITEM_TREE[at0003] matches { -- blood pressurei tems cardinal i ty match es {0..*; uno rdered} match es {
ELEMENT[at0004] occ urrences m atches {0..1} matches {-- Systol ic
value matches {
C_DV_QUANTITY = 140 ANDDiastolic >= 90).
AQL Equivalent:
SELECTobs/data[at0001]/events[at0006]/data[at0003]/items[at0004]/value/magnitude,
obs/data[at0001]/events[at0006]/data[at0003]/items[at0005]/value/magnitude
FROMEHR [ehr_id/value=$ehrUid]
CONTAINS COMPOSITIONc[openEHR-EHR-COMPOSITION.encounter.v1]CONTAINS OBSERVATION obs[openEHR-EHR-OBSERVATION.blood_pressure.v1]
WHERE
obs/data[at0001]/events[at0006]/data[at0003]/items[at0004]/value/magnitude>=140
ANDobs/data[at0001]/events[at0006]/data[at0003]/items[at0005]/value/magnitude>=90
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Data Management Model
CODASYL Data Model v/s OpenEHRData Management Model
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Former Database Solutions
Test prototype (Key-value store) Physical Layer
Cloud-based Database
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Archetypal EHRs: Database Options
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XML DB
Relational DB
Object DB
Object-Relational DB
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Conceptual View & New Query Language
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Problems
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Universal Schema Interoperable acrossdistributed healthcare systems
Research focus:
Scalable persistence mechanism
New Query Language
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Context of Study
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Healthcare
worker
Input: Patient id
Target:Patients EHR
Need: Precise I nformation
Modern View
Traditional View
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Standardized EHRs Database System
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The Proposal
1. Archetypal Definition Flattened Forms
2. QBE- style I/P & O/P Archetypal Definition
Possible to Query
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The Architecture
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Standardized EHRs Database Archi tecture (1)
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Main Components
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Local Archetype
Repository
Cloud-based
PersistenceUser-I nter face
t Ad K l d f H it
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Experimental Prototype
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t Ad K l d f H it
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Standardized EHRs Database Archi tecture(3)
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NoSQL-based Persistence
JSON document
Archetype
Cloud-based
Persistence
Unique id
Patient id
Version id
ADL
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Quasi-Relational Query Language
Archetypal QBE (AQBE)
Data I nsert
Query UI
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Query Language Options
1. Continue with AQL ADL Store
2.AQBE Relational Store (PostgreSQL)
3. AQBE JSON Store (Cloud-DB)
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Quasi-Relational Query Language: AQBE
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The AQBEData I nsert
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An Example
Store a patients blood pressure observation details
Insert the following details:
1. Patient Name: John_Barak
2. Composed By: Dr. Madaan3. Systolic BP: 95
4. Diastolic BP: 150
AQBE-Data I nsert UI
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http://halifax7.u-aizu.ac.jp:8080/aqbe/insert.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/insert.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/insert.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/insert.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/insert.html -
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g y
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Query-Requirements
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S. No. Query Requirement
1 Population-based Queries
2 Single-patient Queries
3 Epidemiological Queries
4 Single-concept Queries
5 Multi-concept Queries
6 Temporal Queries
6(a) Lifelong Queries
6(b) Instantaneous Queries
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Demo:The AQBE Query Language (3)
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Q3: [Single- patient, single-concept]
-Get a patients medication list
- Select Medication list concept
- Add patient name- Find data
AQBE-Query UI
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http://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.html -
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Demo:The AQBE Query Language (1)
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Q1: [Single-concept, mul tiple EHRs]
-Get all the patients recorded with abnormal (high) BP values
during patient care
- Select Blood pressure concept- Add Systolic > 140
- Add Diastolic > 90
- Find data
AQBE-Query UI
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http://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.html -
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Demo:The AQBE Query Language (2)
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Q2: [Single-concept , multiple patients]
-Find all the records with very high BMI value (>30) for patients
between the period of November 25, 2012 to January 21, 2013,
showing the sudden increase in obesity.
- Select BMI concept- Add context value >= November 25, 2012
- Add context value 30
- Find Data
AQBE-Query UI
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http://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.htmlhttp://halifax7.u-aizu.ac.jp:8080/aqbe/find.html -
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Sample Set of Queries (1)
Current set of Queries
1.Get a patient's current medication li st. [single-(concept/patient), projection]
2.Find high blood pressur e values (systolic >= 140 ordiastolic >= 90 ) within a
specified EHR.[single-(concept/patient), restrict & project]
3.Find high blood pressur e values (systolic >= 140 anddiastolic >= 90 ) within a
specified EHR. [single-(concept/patient), restrict & project]
4.Find blood pressur e values where systolic/diastolic value >0.2 within a specified EHR.
[single-(concept/patient), divide]
5.Get BM Ivalues > 30 kg/m2 for a specific patient. [single-(concept/patient), restrict &
project]
6.Get all HbA1cobservations that have been done in the last 12 months for a specific
patient. [single-(concept/patient), restrict & project]7.Find all blood pressur e (BP) values for a specific patient, showing their systolic and
diastolic blood pressure values; also change the tag-name of systolic BP as 'Sys' and
Diastolic BP as 'Dias'. [single-(concept/patient), rename]
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8. Return all blood pressur e (BP) elements having a position in which BP was record.
[single-(concept/patient), exists]
9. Get the blood pressure (BP)values where the position is not standing. [single-
(concept/patient), negation]
10. Find all the patients who have the same admitting doctor as 'A001'. [single-
concept, multi-patient,restrict & project]
11. Find all the patients who have diabetes but no record of hypertension
diagnosis.[XML definition not found]
12. Get the number of patients admitted on 9 October, 2012.[single-concept, multi-
patient, aggregate]
13. Get the number of all the patients with diabetes. .[XML definition not found]
14. Retrieve all patients who have not been discharged.[single-concept, multi-patient,
nested]15. Get all patients who are suffering from the same problem as a specific patient (e.g.,
diagnosis is Diabetes). [single-concept, multi-patient, nested]
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Sample Set of Queries (2)
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Test Query SetRecent L iterature Survey
16.The children of women which had medication XYZ during their first pregnancy
[complex query-multiple patients/concepts] (src: [11]).
17.Find the number of patients who were given medications during hospital course that
have caused an allergy in 1 or more patients[complex query- multiple patients/concepts,
aggregate, epidemiological] (src: [11]).
18.How many patients have had past medical history of anemia. patients[complexquery- multiple patients/concepts, aggregate, epidemiological] (src: [11]).
19.How many patients developed alopecia as a side effect of chemotherapy in the target
population[complex query- multiple patients/concepts, aggregate, epidemiological] (src:
[11]).
20.How many cases of small cell lung cancer are noted among smoking females in the
target population. [complex query- multiple patients/concepts, aggregate,
epidemiological] (src: [11]).
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Sample Set of Quer ies (3)
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22. To retrieve results containing 3 concepts (Fever, sore throat, and cough
with 1 concept having 2 sub-keys with numerical value (Temp > 38.2 deg and
duration > 1 day) [complex query- multiple patients/concepts](src: [36]).
23. To retrieve results containing 5 concepts (fever, sore throat, cough, no
vomiting and sputum);2 concepts having 1 sub-key with numerical value
(fever temp > 38.2 deg and duration > 1day) and 1 concept having 1 sub-key with
textual value (i.e. sputum of yellow color). [complex query- multiple
patients/concepts](src: [36]).24. To retrieve results containing 3 clinical concepts (cough, no sore-throat, and
had no sterol injection) with 1 concept having 1 sub-key with textual value (i.e.
non sterol injection at the left side). [complex query- multiple
patients/concepts](src: [36]).
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Sample Set of Queries (4)
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AQBE Q L (2)
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AQBE Query Language (2)
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S. No. Query Requirement AQBE Query Language Capability
1 Population-based Queries Yes
2 Single-patient Queries Yes
3 Epidemiological Queries Challenge
4 Single-concept Queries Yes
5 Multi-concept Queries Challenge
6 Temporal Queries Yes
6(a) Lifelong Queries Challenge
6(b) Instantaneous Queries Yes
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AQBE Q L (3)
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AQBE Query Language (3)
Query Function Support
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Query TypeAQL [5](Ocean
Informatics)
AQBE [30](Relational
DB)
AQBE(NoSQL DB)
Simple Query(Select)
Filtered Query(Where Clause)
Sorted Query(Order By) (Except Distinct
Grouping, Summary and Analysis(Group By,Having, grouping/ aggregation/ analyticalfunctions)
To be explored To be explored
Joins and Intersection(Outer/Inner/Natural/Range/Equi/Self) To be explored
Sub-query (In/Not In/Nested/Parallel/Multi(row/column)/single row) To be explored To be explored
Hierarchical Query To be explored To be explored To be exploredComposite Query(Union, Union All,Intersect, Minus)
Top-N Query To be explored To be explored To be explored
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Persistence Method Comparison
Feature PostgreSQL(Relational DB) [35]DB XML(Berkeley)
(XML DB) [28]
MongoDBDocument-Oriented
(No-SQL DB)
Scalability Single large relation
Versioning is expensive
Limited scalability
Nested structure archetypes andtemplates
Each concept stored JSONdocument (unique id andversion id)
Performance Relational queries slow [1] Limited query responseEach node traversed
Light application Fast query-response
Queryability SQL like AQL (limitedcapability)Epidemiological queries Low performance
Proposed AQBE languagepotential powerful querying
Indexing Automatic
Composite/secondaryindexing
Database pre-defined
May not be suitable
Automatic
Composite/secondaryindexing
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Fur ther Challenges
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1. Temporal Complexity
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C t T k
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Current Task
Upgrade existing Query Language
Implement More algebraic operations
Similar to SQL with simplified User-interface
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Summary and Conclusions
New Quasi-Relational Query Language
A. Possibility Cloud-based, scalable persistence for archetypal EHRs
B. Ease of query healthcare users
C. Facilitate Complex Queries for developers
D. Reduce Dependency on commercial query tools
E. Facilitate Creation of new SEHR database
Capable to exchange data with MS Health Vault and Google Health
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R f (1)
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References (1)
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1. Jacobs, A.: Pathologies of Big Data. Communications of ACM 52(8) (August 2009)
2. ADL for archetypes downloaded, http://www.openehr.org/svn/knowledge/archetypes/dev/html/
3. index_en.html
4. Any+time date picker downloaded form, http://www.ama3.com/anytime/
5. AQL query builder available at, http://www.oceaninformatics.com/
6. Solutions/openehr-solutions/ocean-products/Clinical-Modelling/Ocean-Query-Builder.html
7. Archetype Query Language, http://www.openehr.org/wiki/display/spec/~Archetype+Query+Language+Description
8. Beale, T., Heard, S., Kalra, D., Llyod, D.: The OpenEHR Reference Model: EHR Information Model, The
OpenEHR release 1.0.2., OpenEHR Foundation (2008)9. Beale, T.: The OpenEHR Archetype Model-Archetype Object Model, The OpenEHR release 1.0.2., OpenEHR
Foundation (2008)
10. Casbah plugin available at, https://github.com/mongodb/casbah
11. CEN 13606 standard, http://www.en13606.org/the-ceniso-en13606-standard
12. Clinical Knowledge Manager, http://www.openehr.org/knowledge/
13. Eclipse 4.2.0, http://www.eclipse.org/
14. Redmond, E., Wilson, J.R.: Book: Seven Databases in Seven Weeks (May 2012)
15. HTML 5, http://www.w3schools.com/html/html5_intro.asp
16. http://wako3.u-aizu.ac.jp:8080/aqbe/
17. ISO 13606-1: Health informatics - Electronic health record communication- Part 1: RM., 1st edn. (2008)
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18. JavaScript, http://www.w3schools.com/js/default.asp
19. jQuery downloaded from, http://jquery.com/
20. jQuery UI available at, http://jqueryui.com/
21. Lift JSON available at, https://github.com/lift/lift/tree/master/framework/lift-base/lift-json/
22. MongoDB available at, http://www.mongodb.org/
23. Zloof, M.M.: Query-By-Example: The invocation and definition of tables and forms (1975)
24. Opereffa Project available at, http://www.openehr.org/wiki/display/projects/Opereffa+Project
25. Play framework available at, http://www.playframework.org/26. PostgreSQL database downloadable from, http://www.postgresql.org/
27. Scala Plugin available at, http://www.scala-lang.org/
28. Freire, S.M., Sundvall, E., Karlsson, D., Lambrix, P.: Performance of XML Databases for Epidemiological Queries
in Archetype-Based EHRs. In: Scandinavian Conference on Health Informatics 2012, Linkping, Sweden, October
23 (2012)
29. Sachdeva, S., Madaan, A., Chu, W.: Information interchange services for electronic health record databases. IJCSE
7(1), 38
51 (2012)
30. Sachdeva, S., Yaginuma, D., Chu, W., Bhalla, S.: AQBE - QBE Style Queries for Archetyped Data. IEICE
Transactions 95-D(3), 861871 (2012)
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References (2)
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References (3)
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31. Sachdeva, S., Bhalla, S.: Semantic interoperability in standardized electronic health record databases. J. Data
and Information Quality 3(1), 1 (2012)
32. Beale, T.: OpenEHR: Node + Path Persistence (2008)
33. Twitter bootstrap framework downloaded from, http://twitter.github.com/bootstrap/
34. http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-
fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=%2Egmr_144276
35. http://www.openehr.org/wiki/display/projects/Opereffa+Project
36. Ken Ka-Yin Lee, Wai-Choi Tang, Kup-Sze Choi, Alternatives to relational database: Comparison of NoSQL
and XML approaches for clinical data storage, Computer Methods and Programs in Biomedicine, Volume110, Issue 1, April 2013, Pages 99109
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References (3)
to Advance Knowledge for Humanity
http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.openehr.org/wiki/display/projects/Opereffa+Projecthttp://www.openehr.org/wiki/display/projects/Opereffa+Projecthttp://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276http://www.linkedin.com/groups/Choice-OpenEHR-persistence-layer-144276.S.208531138?qid=208adbca-fc26-4ada-bf02-7efe5a9e5661&trk=group_most_recent_rich-0-b-ttl&goback=.gmr_144276 -
7/25/2019 Quasi-relational query language for persistent standardized EHRs using no-SQL databases
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Questions
513/25/2013 DNIS 2013