Laboratory Panels &Tests Discussions (a.k.a. Observation Groups verses Atomic Observations)

Slides:



Advertisements
Similar presentations
Testing Relational Database
Advertisements

Dipak Kalra, David Lloyd Health Record Information The information in a health record is inherently hierarchical –Clinical observations, reasoning and.
CIMI Modelling Taskforce Example Instances Dr Linda Bird, IHTSDO Implementation Specialist.
Walks, Paths and Circuits Walks, Paths and Circuits Sanjay Jain, Lecturer, School of Computing.
New Semantic Elements (Part 2)
C-CDA Constraints FACA - Strategy Discussion June 23, 2014 Mark Roche, MD.
Working with Statisticians At some point, a statistician is likely to be asked to analyze your data. This can lead to much unhappiness.
Chapter 2 – Software Processes
Laboratory Panels &Tests Discussions (a.k.a. Observation Groups verses Atomic Observations)
CIMI Modelling Taskforce Progress Report
Spark: Cluster Computing with Working Sets
HSCIC Data Dictionary for Care Modelling Approach Dr. Rahil Qamar Siddiqui Health and Social Care Information Centre, NHS, England.
Multiversion Access Methods - Temporal Indexing. Basics A data structure is called : Ephemeral: updates create a new version and the old version cannot.
BehavioralCmpE196G1 Behavioral Patterns Chain of Responsibility (requests through a chain of candidates) Command (encapsulates a request) Interpreter (grammar.
C++ Programming: Program Design Including Data Structures, Third Edition Chapter 17: Linked Lists.
Demystifying Architectural Styles Nikunj Mehta 3/11/02Demystifying Architectural Styles2 Agenda Architectural Styles The Alfa Project Architectural framework.
Integrating disease and diagnosis semantics in clinical archetypes Leonardo Lezcano Miguel-Ángel Sicilia {leonardo.lezcano, University.
Demystifying Architectural Styles Nikunj Mehta 3/11/02Demystifying Architectural Styles2 Architectural Styles Characterize –Structure, i.e. external.
Chapter 10 Class and Method Design
Database Systems. What is a database? A database is an organised store of data items.
Pharmacy Administration Issues and thoughts Jürgen Brandstätter.
ICS-FORTH May 25, The Utility of XML Martin Doerr Foundation for Research and Technology - Hellas Institute of Computer Science Heraklion, May.
Use Case Diagrams – Functional Models Chapter 5. Objectives Understand the rules and style guidelines for activity diagrams. Understand the rules and.
JSP Standard Tag Library
RDF (Resource Description Framework) Why?. XML XML is a metalanguage that allows users to define markup XML separates content and structure from formatting.
LAYING OUT THE FOUNDATIONS. OUTLINE Analyze the project from a technical point of view Analyze and choose the architecture for your application Decide.
Lecture 22 Miscellaneous Topics 4 + Memory Allocation.
Design Patterns OOD. Course topics Design Principles UML –Class Diagrams –Sequence Diagrams Design Patterns C#,.NET (all the course examples) Design Principles.
CORE 2: Information systems and Databases COLLECTING AND DISPLAYING FOR DATABASE SYSTEMS.
July 20, 2007 Healthcare Information Technology Standards Panel Principles for Proper Use of HITSP Interoperability Specifications And Proposal for Proper.
MS Access Database Connection. Database? A database is a program that stores data and records in a structured and queryable format. The tools that are.
Microsoft Access Understanding Relationships Academic Health Center Training (352)
 Dr. Syed Noman Hasany.  Review of known methodologies  Analysis of software requirements  Real-time software  Software cost, quality, testing and.
Whole Number Arithmetic Recognising patterns. Oral Examples State the next three numbers 1)1, 3, 5, 7,,,
Writing the “Results” & “Discussion” sections Awatif Alam Professor Community Medicine Medical College/ KSU.
Clinical Document Architecture. Outline History Introduction Levels Level One Structures.
1 5 Normalization. 2 5 Database Design Give some body of data to be represented in a database, how do we decide on a suitable logical structure for that.
Metadata and Versioning VIF workshop 22 nd April
T Beale, Joey Coyle CIMI meeting Sep 2012 Copyright 2012 Ocean Informatics.
HSC IT Center Training University of Florida Microsoft Access Understanding Relationships Health Science Center IT Center – Training
Standards Analysis Summary vMR –Pros Designed for computability Compact Wire Format Aligned with HeD Efforts –Cons Limited Vendor Adoption thus far Represents.
Rules, Movement, Ambiguity
Work Place Based Assessment: A deeper understanding of competency assessment John Kedward, Associate Dean.
Sampling distributions rule of thumb…. Some important points about sample distributions… If we obtain a sample that meets the rules of thumb, then…
Behavioural Design Patterns Quote du jour: ECE450S – Software Engineering II I have not failed. I've just found 10,000 ways that won't work. - Thomas Edison.
Philosophy of ICT and Islam Lecture 3 Data, Information, Knowledge and Wisdom.
Principles of Database Design, Conclusions MBAA 609 R. Nakatsu.
Chapter 2 – Software Processes Lecture 1 Chapter 2 Software Processes1.
Why Standardize Metadata?. Why Have a Standard? Think for a moment how hard it would be to… … bake a cake without standard units of measurement. … put.
Behavioral Patterns1 Nour El Kadri SEG 3202 Software Design and Architecture Notes based on U of T Design Patterns class.
Microhematocrit Determination. Microhematocrit Hematocrit — Test that provides a health care worker with an estimate of the patient’s red cell volume.
A table is a set of data elements (values) that is organized using a model of vertical columns (which are identified by their name) and horizontal rows.
Fundamentals, Design, and Implementation, 9/e Appendix B The Semantic Object Model.
EMBL-EBI Dimitris Dimitropoulos MSD-mine. EMBL-EBI MSD-mine overview  Web application for online data analysis and mining  For the advanced MSDSD researcher.
O: You will be able to explain the difference between elements and compounds. Do Now: Everything in the world is made up of atoms, how many different types.
David M. Kroenke and David J. Auer Database Processing Fundamentals, Design, and Implementation Appendix H: The Semantic Object Model.
Mr H Kandjimi 2016/01/03Mr Kandjimi1 Week 3 –Modularity in C++
Understanding the Value and Importance of Proper Data Documentation 5-1 At the conclusion of this module the participant will be able to List the seven.
Normalization.
Healthcare Information Technology Standards Panel
Reconciling Issues re Performer & Assessor
Implementation of Clinical Guidelines Author: dr. Martin Rusnák
Chapter 19: Architecture, Implementation, and Testing
STRUCTURE OF PRESENTATION :
Reconciling Issues re Performer & Assessor
MS Access Database Connection
Statement-Level Control Structures
Chapter 2: The Accounting Information System
Word Choice Questions Skill being used: Identify the reason particular words are used by their connotations Marks come in PAIRS Method: Provide a quoted.
Presentation transcript:

Laboratory Panels &Tests Discussions (a.k.a. Observation Groups verses Atomic Observations)

Requirements 1.Recognise atomic information: –To recognise the smallest piece of information that you can sensibly say about a patient. 2.Consistent query paths: –Ensure query paths to these can be consistent 3.Same test in different panels: –A test should be able to appear in more than one type of panel 4.Simple navigation: –It should be as simple as possible for a query to navigate from a Panel to the Test Results

Principles 1.The reference model should be able to support new use cases 2.The reference model should have no healthcare semantics (e.g. Observation) 3.Healthcare semantics should be represented in reference archetypes above the reference model (patterns)

Options Option 1: Sections & Entries Option 2: Entries & Clusters/Elements Option 3: Templated ‘Uber Model’ Option 4: Entries with Links Option 5: Entries with External Panels Option 6: Compound & Indivisible Statements

Option 1 – Sections & Entries Panels defined using Sections Tests defined using Entries Panel-level information defined in a separate Entry Pros –No need to change existing reference model –Query path can be consistent (see below) Cons –Sections are not intended to represent semantics, and this approach does overload sections with semantics –Panel information entry will need to be distinguished from Test entries. –Need either copy the context into each test or ensure that we can execute a derivation rule to ensure that the query path can remain consistent

Option 1 – Sections & Entries ENTRY: Hematocrit Result Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name: |Hematocrit| ELEMENT: Result Value: 42% ELEMENT: Interpretation: |Normal| ELEMENT: SECTION: Complete Blood Count Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Hematocrit Result: ENTRY: ELEMENT: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Hemoglobin Result: ENTRY: ELEMENT: Test Name:|Hemoglobin| Result Value: 14.2 g/dL Interpretation: |Normal| Q: List the Date and Result of all Hematocrit Tests for Information Subject **: Derived using a rule Panel Information ENTRY: Info. Subj.** / Date ** ELEMENTS: Info. Subj.** / Date ** ELEMENTS: Panel Interpretation: … ELEMENT:

Option 2 – Entries & Clusters Panels defined using Entries Tests defined using Clusters Pros –No changes required to reference model –Allows arbitrary level of grouping Cons –Does not recognise atomic pieces of information –Query path not stable for a particular type of test

Option 2a – Entries & Clusters ENTRY: Hematocrit Result Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name: |Hematocrit| ELEMENT: Result Value: 42% ELEMENT: Interpretation: |Normal| ELEMENT: ENTRY: Complete Blood Count Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Hematocrit Result: CLUSTER: ELEMENT: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Hemoglobin Result: CLUSTER: ELEMENT: Test Name:|Hemoglobin| Result Value: 14.2 g/dL Interpretation: |Normal| Q: List the Date and Result of all Hematocrit Tests for Information Subject Panel Interpretation: … ELEMENT:

Option 2b – Entries & Clusters Lab Panel (name = HCT) ENTRY[panel] : Lab Panel (name = CBC) Information Subjct: 7549 ELEMENT[id2]: Date: 27 th June 2013 ELEMENT[id3]: Hematocrit Result: CLUSTER[HCT_res]: ELEMENT[id2]: ELEMENT[id3]: ELEMENT[id4]: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Hemoglobin Result: CLUSTER[HGB_res]: ELEMENT[id2]: ELEMENT[id3]: ELEMENT[id4]: Test Name:|Hemoglobin| Result Value: 14.2 g/dL Interpretation: |Normal| Panel Interpretation: … ELEMENT[id4]: Hematocrit Result: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Information Subjct: 7549 Date: 28 th June 2013 Panel Interpretation: … ENTRY[panel]: ELEMENT[id2]: ELEMENT[id3]: CLUSTER[HCT_res]: ELEMENT[id2]: ELEMENT[id3]: ELEMENT[id4]: item data Path to HCT value is always: [cimi-rm-ENTRY.panel] /data[cimi-rm-CLUSTER.HCT_result]/item[id3]/value/value

Option 2b – Using Lab Results Pattern ENTRY: Lab Results Pattern Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Result: CLUSTER: ELEMENT: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Panel Interpretation: … ELEMENT:

Option 3 – Templated ‘Uber Model’ Same as Option 2 (Entries & Clusters) – except: One Lab Results ‘Uber Model’ is defined, which contains every possible test Each Panel is defined as a template (or constraint) on the ‘Uber Model’) Pros –Query paths are stable Cons –Doesn’t identify smallest piece of queryable information

Option 3 – Templated ‘Uber Model’ ENTRY: ‘Uber’ Lab Results Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Hematocrit Result: CLUSTER: ELEMENT: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Hemoglobin Result: CLUSTER: ELEMENT: Test Name:|Hemoglobin| Result Value: 14.2 g/dL Interpretation: |Normal| Panel Interpretation: … ELEMENT: CLUSTER: LDL Result: ENTRY: Haematocrit Lab Results Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Hematocrit Result: CLUSTER: ELEMENT: Test Name: |Hematocrit| Result Value: 42% Interpretation: |Normal| Hemoglobin Result: Test Name:|Hemoglobin| Result Value: 14.2 g/dL Interpretation: |Normal| Panel Interpretation: … LDL Result:

Option 4 – Entries With Links Panels defined using Entries Tests defined using Entries Panel entry includes links to test entries Pros –No changes to the reference model –Query paths are consistent –Tests can stand independently with own context –Allows arbitrary levels of groupings Cons/Implications –Requires queries to navigate links and understand the semantics of the links –Need to repeat information in each test entry –Are reverse links also required?

Option 4 – Entries With Links ENTRY (A): Lab Test Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name: |Hematocrit| ELEMENT: Result Value: 42% ELEMENT: Interpretation: |Normal| ELEMENT: Q: List the Date and Result of all Hematocrit Tests for Information Subject ENTRY (C): Lab Panel Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Result: LINK: Result: LINK: ENTRY (A): Lab Test Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name:|Hemoglobin| ELEMENT: Result Value: 14.2 g/dL ELEMENT: Interpretation: |Normal| ELEMENT: Test Name: |CBC| ELEMENT: Panel Interpretation: … ELEMENT:

Option 5 – Entries With External Panels Same as Option 4 – except: Panels defined in an external database, as a set of references to test entries Pros –Recognises atomic information Cons –Knowledge is split between the model and the external resource. Knowledge framework is not consistent. –No place in model to put information that applies to the whole panel.

Option 5 – Entries With External Panels ENTRY (A): Lab Test Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name: |Hematocrit| ELEMENT: Result Value: 42% ELEMENT: Interpretation: |Normal| ELEMENT: GROUP: CBC Result: REFERENCE: Result: REFERENCE: ENTRY (A): Lab Test Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: Test Name:|Hemoglobin| ELEMENT: Result Value: 14.2 g/dL ELEMENT: Interpretation: |Normal| ELEMENT:

Option 6 – Compound & Indivis. Statements Specialise Entry into 2 new reference model classes: –Compound Entry Used for panels, and may contain data elements, compound statements or atomic statements; Contains shared context. –Indivisible Entry Used for individual tests, and represent indivisible unit of information about the patient; All context is self-contained or derivable. Pros –Consistent query paths –Identifies indivisible units of information –Allows arbitrary levels of nesting –Allows context derivation rules to be applied Cons / Implications –Requires reference model to be changed –Requires the implementation to ensure atomic statements are complete, and independently queryable

Option 6 – Compound & Indivis. Statements INDIVISIBLE ENTRY Hematocrit Result Information Subj:** 7549 ELEMENT: Date**: 27 th June 2013 ELEMENT: Test Name: |Hematocrit| ELEMENT: Result Value: 42% ELEMENT: Interpretation: |Normal| ELEMENT: COMPOUND ENTRY Complete Blood Count Information Subjct: 7549 ELEMENT: Date: 27 th June 2013 ELEMENT: INDIVISIBLE ENTRY Hemoglobin Result Information Subj**: 7549 ELEMENT: Date**: 27 th June 2013 ELEMENT: Test Name:|Hemoglobin| ELEMENT: Result Value: 14.2 g/dL ELEMENT: Interpretation: |Normal| ELEMENT: **: Derived Panel Interpretation: … ELEMENT: