Healthcare Quality Reporting Overview
description
Transcript of Healthcare Quality Reporting Overview
Healthcare Quality Reporting with Semantic Technologies
Christopher Pierce, Ph.D.
Cleveland ClinicMedical Informatics Grand Rounds
20 August 2010
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Healthcare Quality ReportingOverview
• Demand for quality reporting is growing rapidly and requirements are increasing in complexity and institutional impact
• Traditional process of reporting is labor intensive, scales poorly and yields inconsistent results
• To address these deficiencies the Cleveland Clinic has developed a semantic approach for producing quality reports
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Health Care Quality Reporting Agencies and Databases
• Government and Industry Groups– CMS– Leapfrog– National Quality Forum (NQF)
• National Databases– ACC National Cardiovascular Data
Registries– ACS National Surgical Quality
Improvement Program
• 3rd Party Payors– Blue Cross Blue Shield– United Health– Anthem
• Private Quality Tracking Groups– US News and World Report– Health Grades
National Cardiovascular Reporting Databases
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Quality Reporting ComplexitiesSmoking/Tobacco Use History
STS Adult Cardiac Surgery Database
2002 - 2007 2008 - Present
Any tobacco use history Used < 1 mo. of surgery
Current or recent cigarette smoker < 1 year of surgery
STS General Thoracic Surgery Database
2004 - 2009 2009 - present
Chew user Cigarette user Pipe user Other tobacco user Days quit before surgery
History of cigarette smoking Never Quit > 1 mo. of surgery Smoked < 1 mo. of surgery
ACC NCDR CathPCI Registry
2004 - 2009 2009 - present
History of tobacco use Never Quit > 1 mo. of surgery Used < 1 mo. of surgery
Current or recent cigarette smoker < 1 year of surgery
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Typical Reporting Process
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Typical Reporting Process
• Redundant and costly– Same data collected multiple times– Managing multiple databases with overlapping
content plus separate databases for research
• Inconsistent– Same measures may be collected differently in
separate databases– Potential for reporting different results for same
measures
• Low data reusability for research– Changing definitions– Different definitions
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The Semantic Reporting Process
Utilize semantic technology to link concepts and translate core data Utilize semantic technology to link concepts and translate core data into answers to reporting questionsinto answers to reporting questions
Utilize semantic technology to link concepts and translate core data Utilize semantic technology to link concepts and translate core data into answers to reporting questionsinto answers to reporting questions
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The Semantic Reporting Process
• Data Federation– Relevant data obtained from multiple source systems
as electronic feeds whenever possible
• Core Data Elements– Source data mapped to core data elements in
federated repository
• Computer Reasoning– Use inference to deduce answers to questions in
specific reports from core data elements
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The Semantic Reporting ProcessFederation with SemanticDB
• Virtual or actual aggregation of source system data into semantic repository through feeds and manual abstraction
• Data mapped to common RDF model with well-documented meanings that supports computer reasoning
• RDF model linked to expressive ontologies of medical terms to contextualize term meanings
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The Semantic Reporting Process Core Data Elements
• Critical concepts mentioned in queries or variable definitions
e.g. “Indicate if the patient developed a hematoma at the percutaneous entry site.”
• Support unified data meanings for multiple purposes
Internal and external reporting, research, and ad hoc queries
• Provide targets for aligning with standard medical terminologies and taxonomies
• Critical concepts mentioned in queries or variable definitions
e.g. “Indicate if the patient developed a hematoma at the percutaneous entry site.”
• Support unified data meanings for multiple purposes
Internal and external reporting, research, and ad hoc queries
• Provide targets for aligning with standard medical terminologies and taxonomies
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The Semantic Reporting Process Computer Reasoning
• Reasoning: Use of ontologies and rules to derive logical entailments from existing data– Kind of, part of, temporal sequence (pre-
procedure, post-procedure), etc.
• Forward Reasoning: derive entailments before query to create targets for simplified queries
• Backward Reasoning: derive specific entailments at query time
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Definition Pathway for Specific Variable1. Define Core Data Element (CDE) set for variable
2. Expand CDE set to include all critical concepts
3. Provide formal definition of all CDEs
4. Map CDEs to standard taxonomies and ontologies (SNOMED-CT, FMA, LOINC, Cyc, etc.)
5. Identify primary source systems where all data pertinent to CDEs are collected
6. Produce formal logical methods for deducing variable values based on CDE definitions (ontologies and rules)
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Source DataCore Data ElementsIn SemanticDB
Source Term a
Source Term b
Source Term c
Source Term d
Source Term e
Source Term f
Question A
CDE 1
CDE 2
CDE 3
CDE 4
CDE 5
CDE 6
Answer toQuestion
The Semantic Reporting Process
ReasoningReasoningMapping andFederation
Mapping andFederation
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Example:ACC CathPCI National Registry (version 4.3)
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CathPCI v 4.3 Report Flow
Common Data Model
Common Data Model InferInfer CathPCI
ReportsCathPCIReports
CathPCIReportsCathPCIReports
CathPCIv 4.3
Reports
CathPCIv 4.3
Reports
Acute MI DBAcute MI DB
Clarity DBClarity DB
Misys (Labs) DBMisys (Labs) DB
Interventional DBInterventional DB
Sensis DBSensis DB
Diag. Cath DBDiag. Cath DB
General demographic, prior history and billing datafor all Cleveland Clinic patients
ECG timing and result data for acute MI patients
Point-of-care database for cath lab visits
Official registry for PCI procedure data (some of which is automatically pulled from Sensis)
Lab test data for all Cleveland Clinic patients
Official registry for Diagnostic Cath data (some of which is automatically pulled from Sensis)
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CathPCI v 4.3 Report Flow• Specify mappings from 405 distinct DB fields to structures in common data model
• Use integration software to import
raw data values from source databases into store that accommodates common data model, for each patient record in cohort
Acute MI DBAcute MI DB
Clarity DBClarity DB
Misys (Labs) DBMisys (Labs) DB
Interventional DBInterventional DB
Sensis DBSensis DB
Dx Cath DBDx Cath DB
Common Data Model
Common Data Model
Example 1:
CATHUSER.SPECTSTRESSTEST = 1=>(?TEST a Event_evaluation_cardiac_stress_test)(?TEST hasCardiacStressTestType CardiacStressTestType_SPECT_MPI)(?TEST contains ?DATE)(?DATE a EventStartDate)(?DATE hasDateTimeMax ?MAX)
Example 2:
PROCEDURE_MASTER.SUPPORT_DEVICE_CD = 1=>(?INDEX a Event_management_percutaneous_intervention)(INDEX startsNoEarlierThan ?ESTART)(INDEX startsNoLaterThan ?LSTART)(?INDEX contains ?DATA)(?DEV a CardiacAssistDevice) (?DEV hasCardiacAssistDeviceType CardiacAssistDeviceType_intra-aortic_balloon_pump)
Example 3:
CATHPCI_V4_LAB_VISIT.ANGINALCLASS_5020 = 1=>(?EVT a Event_evaluation_history_and_physical)(?EVT startsNoEarlierThan ?ESTART)(?EVT startsNoLaterThan ?LSTART)(?EVT hasCanadianHeartClass CanadianHeartClass_0)
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CathPCI v 4.3 Report Flow
Acute MI DBAcute MI DB
Clarity DBClarity DB
Misys (Labs) DBMisys (Labs) DB
Common Data Model
Common Data Model InferInfer
Interventional DBInterventional DB
Sensis DBSensis DB
Reasoning:• Access data in common data model store• Use rule encodings of CathPCI v4.3 variable definitions to deduce values
CathPCIReportsCathPCIReports
CathPCIReportsCathPCIReports
CathPCIv 4.3
Reports
CathPCIv 4.3
Reports
Acute MI DBAcute MI DB
Clarity DBClarity DB
Misys (Labs) DBMisys (Labs) DB
Interventional DBInterventional DB
Sensis DBSensis DB
Dx Cath DBDx Cath DB
Example 1:
“Indicate if stress testing with SPECT imaging was performed within 6 months prior to current procedure.”
(eventOfTypePriorToWithinIntervalWithValueForOf ?TEST ?INDEX CardiacStressTest (MonthsDuration 6) hasCardiacStressTestType StressTestWithSPECTMPI)))
Example 2:
“Indicate if the patient required the use of an Intra-Aortic Balloon Pump between start of procedure and end of procedure.”
(and (hasDetail ?INDEX ?DEV) (isa ?DEV CardiacAssistDeviceData) (hasCardiacAssistDeviceType ?DEV IntraAorticBalloonPump)))
Example 3:
“Indicate if the patient required the use of an Intra-Aortic Balloon Pump between start of procedure and end of procedure.”
((eventOfTypePriorToWithinIntervalWithValueForOf ?TEST ?INDEX ClinicalExam-HAndP (MonthsDuration 6) hasCanadianHeartClass ?CLASS-VALUE)))
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Source DataCore Data ElementsQuestion to Answer
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medication
Date/time
Medication prescribed
Medication taken
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medicationMedication type:
Anti-anginal medication
Date/time Date/time
Medication prescribed
Medication taken
Medication prescribed or taken
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medicationMedication type:
Anti-anginal medication
Date/time Date/time
Medication prescribed
Medication taken
Medication prescribed or taken
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
“Indicate the date of the patient’s most recent anti-anginal
prescription.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medicationMedication type:
Anti-anginal medication
Date/time Date/time
Medication prescribed
Medication taken
Medication prescribed or taken
Beta Blocker
Ca Channel Blocker
Long-acting Nitrate
Ranolazine
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
“Indicate the date of the patient’s most recent anti-anginal
prescription.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medicationMedication type:
Anti-anginal medication
Date/time Date/time
Medication prescribed
Medication taken
Medication prescribed or taken
Beta Blocker
Ca Channel Blocker
Long-acting Nitrate
Ranolazine
Beta Blocker
Ca Channel Blocker
Long-acting Nitrate
Ranolazine
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
“Indicate the date of the patient’s most recent anti-anginal
prescription.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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Source DataCore Data ElementsQuestion to Answer
Anti-anginal medicationMedication type:
Anti-anginal medication
Date/time Date/time
Medication prescribed
Medication taken
Medication prescribed or taken
Beta Blocker
Ca Channel Blocker
Long-acting Nitrate
Ranolazine
Beta Blocker
Ca Channel Blocker
Long-acting Nitrate
Ranolazine
“Indicate if the patient has taken or has been prescribed ranolazine
in the past six months.”
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
“Indicate the date of the patient’s most recent anti-anginal
prescription.”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
Example Variable:
CathPCI v4.3 #5025 “Anti-Anginal Meds”
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
CathPCI v4.3 Data Dictionary Coding Instructions:
“Indicate the best estimate of most severe percent stenosis in mid/distal left anterior descending (LAD), including all diagonal coronary artery branches as determined by angiography.
Note: It is acceptable to use prior cath lab visit information as long as there have been no changes in coronary anatomy.
Target value: The highest value between one month prior to current procedure and current procedure.”
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Isolate Core Data Elements:
“Indicate the best estimate of most severe percent stenosis in mid/distal left anterior descending (LAD), including all
diagonal coronary artery branches as determined by angiography.
Note: It is acceptable to use prior cath lab visit information as long as there have been no changes in coronary anatomy.
Target value: The highest value between one month prior to current procedure and current procedure.”
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Expand relevant CDE set to all critical concepts:
“Indicate the best estimate of most severe percent stenosis in mid/distal left anterior descending (LAD), including all
diagonal coronary artery branches as determined by angiography.
Note: It is acceptable to use prior cath lab visit information as long as there have been no changes in coronary anatomy.
Target value: The highest value between one month prior to current procedure and current procedure.”
Expands into additional critical concepts:
Diagonal 1 Diagonal 2Diagonal 3Lateral First DiagonalLateral Second DiagonalLateral Third DiagonalLeft Anterior Descending Major Septal Perforator
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Expand relevant CDE set to all critical concepts:
“Indicate the best estimate of most severe percent stenosis in mid/distal left anterior descending (LAD), including all
diagonal coronary artery branches as determined by angiography.
Note: It is acceptable to use prior cath lab visit information as long as there have been no changes in coronary anatomy.
Target value: The highest value between one month prior to current procedure and current procedure.”
Expands into additional critical concepts:
OperationCABG procedure
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Expand relevant CDE set to all critical concepts:
“Indicate the best estimate of most severe percent stenosis in mid/distal left anterior descending (LAD), including all
diagonal coronary artery branches as determined by angiography.
Note: It is acceptable to use prior cath lab visit information as long as there have been no changes in coronary anatomy.
Target value: The highest value between one month prior to current procedure and current procedure.”
Expands into additional critical concepts:
Diagnostic catheterizationPercutaneous coronary interventionCardiac angiogram
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Indentify pertinent source data:
From Interventional DB:• Cohort who had PCI performed in relevant timeframe• Dates of those PCIs• Dates of the cath lab visits that subsume those PCIs• Coronary artery stenosis values for LAD and relevant diagonals as
determined during PCI
From Diagnostic Cath DB:• Dx Cath procedures, with stenoses determined by angiography• Dates of the cath lab visits that subsume those PCIs
From SemanticDB:• CABG operations, with affected coronary regions
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Store as Common Data Model:
Import the following relevant types of structure:
1. PCIs and associated cath lab visits
2. Diagnostic caths and associate cath lab visits
3. Stenosis findings from all PCIs and Diagnostic caths
4. CABG procedures and associated operations
5. Coronary artery graft data
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CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
Example Semantic Query:
(ist CCF-CAE-QueryMt (and (elementOf ?ARTERY-TYPE (TheSet MiddleLeftAnteriorDescendingArtery-Coronary LeftAnteriorDescendingDistalArtery-Coronary CoronaryArtery-Diagonal1 LateralFirstDiagonalCoronaryArtery CoronaryArtery-Diagonal2 LateralSecondDiagonalCoronaryArtery CoronaryArtery-Diagonal3 LateralThirdDiagonalCoronaryArtery LeftAnteriorDescendingMajorSeptalPerforator)) (cathOrPCIHasStenosisForCoronaryRegion ?INDEX ?ARTERY-TYPE ?DEGREE))
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Example Reasoning Rule:
(implies (and (isa ?INDEX InterventionalCatheterization) (hasFinding ?INDEX ?STENOSIS) (isa ?STENOSIS CoronaryArteryStenosis-Finding) (hasCoronaryArtery ?STENOSIS ?REGION-TYPE) (hasVesselStenosisDegree ?STENOSIS ?DEGREE)) (cathOrPCIHasStenosisForCoronaryRegion ?INDEX ?REGION-TYPE ?DEGREE))
“If the current procedure records a stenosis value for a particular artery, then that stenosis value is a stenosis value for that region for the current procedure.”
CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
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Example Rule:(implies (and (isa ?INDEX InterventionalCatheterization) (startsNoEarlierThan ?INDEX ?INDEX-MIN) (contains ?PTREC ?INDEX) (isa ?STENOSIS CoronaryArteryStenosis-Finding) (hasCoronaryArtery ?STENOSIS ?REGION-TYPE) (hasVesselStenosisDegree ?STENOSIS ?DEGREE) (hasFinding ?EARLIER-DIAG ?STENOSIS) (closestEventOfTypeAtOrPriorToWithValueFor ?EARLIER-DIAG ?INDEX CardiacCatheterization-Diagnostic hasFinding) (startsNoEarlierThan ?EARLIER-DIAG ?DIAG-MIN) (greaterThanOrEqualTo (MonthsDuration 1) ?DURATION) (timeElapsedBetween-MinMin-CCF ?INDEX ?EARLIER-DIAG ?DURATION) (unknownSentence (thereExists ?OP (thereExists ?OP-MIN (thereExists ?CABG (thereExists ?CAG (thereExists ?CAGS (thereExists ?CAGDA (and (isa ?CABG CoronaryArteryBypassGraft-SurgicalProcedure) (isa ?OP Operation) (contains ?PTREC ?OP) (sksiLaterThan ?INDEX-MIN ?OP-MIN) (sksiLaterThan ?OP-MIN ?DIAG-MIN) (hsaCoronaryArtery ?CABG ?REGION-TYPE) (startsNoEarlierThan ?OP ?OP-MIN) (time:intervalContains ?OP ?CABG)))))))))) (cathOrPCIHasStenosisForCoronaryRegion ?INDEX ?REGION-TYPE ?DEGREE))
CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
There is a dx cath within 1 month prior to the current procedure that records astenosis value for a particular artery.
There is no CABG affecting that artery between the aforementioned dx cath and the current procedure.
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Query could find multiple stenosis values for a single region:
Diagonal 1 Stenosis = 50%
Diagonal 2 Stenosis = 60%
Query post-processing (backward reasoning) selects the highest stenosis value returned by the query:
(FirstInListFn (SortSetViaBinPredFn (SetOfValuesOfFn ?RESULT) greaterThan))))
CathPCI v4.3 seq. #6130:“Mid/Distal LAD, Diag Branches Stenosis”
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Distinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
Question to Answer
“Indicate the maximum dimension, in
centimeters, of the hematoma:
< 5 cm,5-10 cm,>10 cm.”
Qualitative/Quantitative Reasoning
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
Hematoma
Size in centimeters“Indicate the maximum
dimension, in centimeters, of the
hematoma: < 5 cm,
5-10 cm,>10 cm.”
Qualitative/Quantitative ReasoningDistinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
Hematoma
Size in centimeters“Indicate the maximum
dimension, in centimeters, of the
hematoma: < 5 cm,
5-10 cm,>10 cm.”
Qualitative/Quantitative Reasoning
Hematoma
Size in centimeters
Distinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
Hematoma
Size in centimeters“Indicate the maximum
dimension, in centimeters, of the
hematoma: < 5 cm,
5-10 cm,>10 cm.”
Qualitative/Quantitative Reasoning
Hematoma
Size in centimeters
Small hematoma
Medium hematoma
Medium to largehematoma
Large Hematoma
Distinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
Hematoma
Size in centimeters“Indicate the maximum
dimension, in centimeters, of the
hematoma: < 5 cm,
5-10 cm,>10 cm.”
Qualitative/Quantitative Reasoning
Hematoma
Size in centimeters
Small hematoma
Medium hematoma
Medium to largehematoma
Large Hematoma
< 5 cm hematoma
5-7 cm hematoma
>7-10 cm hematoma
> 10 cm hematoma
Distinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
Hematoma
Size in centimeters“Indicate the maximum
dimension, in centimeters, of the
hematoma: < 5 cm,
5-10 cm,>10 cm.”
Qualitative/Quantitative Reasoning
Hematoma
Size in centimeters
< 5 cm hematoma
5-7 cm hematoma
>7-10 cm hematoma
> 10 cm hematoma
Small hematoma
< 3 cm hematoma
Small hematoma
Medium hematoma
Medium to largehematoma
Large Hematoma
Distinct qualitative source data can be brought into alignment quantitatively:Distinct qualitative source data can be brought into alignment quantitatively:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Distinct quantitative source data can treated in a qualitatively uniform way:Distinct quantitative source data can treated in a qualitatively uniform way:
Question to Answer
“Indicate whether the patient has an evaluation that
indicates left atrial enlargement.”
Qualitative/Quantitative Reasoning
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
“Indicate whether the patient has an evaluation that
indicates left atrial enlargement.”
Qualitative/Quantitative Reasoning
Left atrium
Diameter of object
Rule indicating atrial enlargement
Distinct quantitative source data can treated in a qualitatively uniform way:Distinct quantitative source data can treated in a qualitatively uniform way:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
“Indicate whether the patient has an evaluation that
indicates left atrial enlargement.”
Qualitative/Quantitative Reasoning
Left atrium
Diameter of object
Rule indicating atrial enlargement
Left atrium
Diameter in centimeters
Evaluation
Distinct quantitative source data can treated in a qualitatively uniform way:Distinct quantitative source data can treated in a qualitatively uniform way:
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Source DataCore Data Elements
“Indicate if the patient has taken or has been prescribed anti-anginal medication within the
past two weeks.”
Question to Answer
“Indicate whether the patient has an evaluation that
indicates left atrial enlargement.”
Qualitative/Quantitative Reasoning
Left atrium
Diameter of object
Rule indicating atrial enlargement
Left atrium
Diameter in centimeters
Evaluation
Male patient
Female patient
Rule indicating male atrial enlargement
Rule indicating female atrial enlargement
Distinct quantitative source data can treated in a qualitatively uniform way:Distinct quantitative source data can treated in a qualitatively uniform way:
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Benefits of Semantic Reporting• Consistent
– Guarantees reporting of same values for same measures across different reports
– Data corrections can be made in one location, the source database
– Guides clinical documentation towards well-defined core data elements
• Reusable– Same core data and reasoning usable for reporting,
research, marketing, etc.• Responsive
– Able to rapidly change core data elements and reasoning logic to respond to new requirements
• Cheaper– Eliminates redundant data collection and reduces
data management costs
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Challenges of Semantic Approach
• Source Data– Fields in sources systems often poorly defined– Much medical information is still narrative requiring
later abstraction– Access to many source systems remains difficult
• Core Data Elements– No universal set of core medical data– Pragmatic definitions based on existing requirements
• Reasoning– Few good medical ontologies– Need to create ontologies and rules as needed