quasi-relational query language for persistent standardized ehrs using no-sql databases

7/25/2019 Quasi-relational query language for persistent standardized EHRs using no-SQL databases

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to Advance Knowledge for Humanity

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

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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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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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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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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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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S S f Q ( )


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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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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


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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S d C l i


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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)


References (3)
http://www.playframework.org/http://www.playframework.org/


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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)

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


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Questions

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quasi-relational query language for persistent standardized ehrs using no-sql databases

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