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Healthcare Quality Reporting Overview

Healthcare Quality Reporting with Semantic Technologies Christopher Pierce, Ph.D. Cleveland Clinic Medical Informatics Grand Rounds 20 August 2010. Healthcare Quality Reporting Overview.

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Healthcare Quality Reporting Overview

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  1. Healthcare Quality Reporting with Semantic TechnologiesChristopher Pierce, Ph.D.Cleveland ClinicMedical Informatics Grand Rounds20 August 2010

  2. 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

  3. 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

  4. Quality Reporting ComplexitiesSmoking/Tobacco Use History

  5. Typical Reporting Process

  6. 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

  7. The Semantic Reporting Process Utilize semantic technology to link concepts and translate core data into answers to reporting questions

  8. 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

  9. 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

  10. The Semantic Reporting ProcessCore 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

  11. The Semantic Reporting ProcessComputer 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

  12. Definition Pathway for Specific Variable Define Core Data Element (CDE) set for variable Expand CDE set to include all critical concepts Provide formal definition of all CDEs Map CDEs to standard taxonomies and ontologies (SNOMED-CT, FMA, LOINC, Cyc, etc.) Identify primary source systems where all data pertinent to CDEs are collected Produce formal logical methods for deducing variable values based on CDE definitions (ontologies and rules)

  13. The Semantic Reporting Process Mapping and Federation Reasoning Question A CDE 1 Source Term a CDE 2 Source Term b CDE 3 Source Term c CDE 4 Source Term d CDE 5 Source Term e CDE 6 Source Term f Answer to Question Core Data Elements In SemanticDB Source Data

  14. Example:ACC CathPCI National Registry (version 4.3)

  15. CathPCI v 4.3 Report Flow Clarity DB General demographic, prior history and billing datafor all Cleveland Clinic patients Acute MI DB ECG timing and result data for acute MI patients Sensis DB CathPCI v 4.3 Reports CathPCI Reports Point-of-care database for cath lab visits CathPCI Reports Common Data Model Infer Interventional DB Official registry for PCI procedure data (some of which is automatically pulled from Sensis) Diag. Cath DB Official registry for Diagnostic Cath data (some of which is automatically pulled from Sensis) Misys (Labs) DB Lab test data for all Cleveland Clinic patients

  16. 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 Clarity DB Acute MI DB Sensis DB Common Data Model Interventional DB 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) DxCath DB Misys (Labs) DB

  17. CathPCI v 4.3 Report Flow • Reasoning: • Access data in common data model store • Use rule encodings of CathPCI v4.3 variable definitions to deduce values Clarity DB Clarity DB Acute MI DB Acute MI DB Sensis DB CathPCI v 4.3 Reports Common Data Model Infer CathPCI Reports Sensis DB CathPCI Reports Interventional 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))) Interventional DB 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))) DxCath DB Misys (Labs) DB Misys (Labs) DB

  18. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Question to Answer Core Data Elements Source Data 18

  19. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Date/time Medication prescribed Medication taken Question to Answer Core Data Elements Source Data 19

  20. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Medication type: Anti-anginal medication Date/time Date/time Medication prescribed Medication prescribed or taken Medication taken Question to Answer Core Data Elements Source Data 20

  21. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Medication type: Anti-anginal medication Date/time Date/time Medication prescribed Medication prescribed or taken “Indicate the date of the patient’s most recent anti-anginal prescription.” Medication taken Question to Answer Core Data Elements Source Data 21

  22. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Medication type: Anti-anginal medication Date/time Date/time Medication prescribed Medication prescribed or taken “Indicate the date of the patient’s most recent anti-anginal prescription.” Medication taken Beta Blocker Ca Channel Blocker Long-acting Nitrate Ranolazine Question to Answer Core Data Elements Source Data 22

  23. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Medication type: Anti-anginal medication Date/time Date/time Medication prescribed Medication prescribed or taken “Indicate the date of the patient’s most recent anti-anginal prescription.” Medication taken Beta Blocker Beta Blocker Ca Channel Blocker Ca Channel Blocker Long-acting Nitrate Long-acting Nitrate Ranolazine Ranolazine Question to Answer Core Data Elements Source Data 23

  24. Example Variable: CathPCI v4.3 #5025 “Anti-Anginal Meds” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Anti-anginal medication Medication type: Anti-anginal medication Date/time Date/time Medication prescribed Medication prescribed or taken “Indicate the date of the patient’s most recent anti-anginal prescription.” Medication taken Beta Blocker Beta Blocker Ca Channel Blocker “Indicate if the patient has taken or has been prescribed ranolazine in the past six months.” Ca Channel Blocker Long-acting Nitrate Long-acting Nitrate Ranolazine Ranolazine Question to Answer Core Data Elements Source Data 24

  25. 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.”

  26. 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.”

  27. 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 branchesas 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 2 Diagonal 3 Lateral First Diagonal Lateral Second Diagonal Lateral Third Diagonal Left Anterior Descending Major Septal Perforator

  28. 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: Operation CABG procedure

  29. 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 catheterization Percutaneous coronary intervention Cardiac angiogram

  30. 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

  31. 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

  32. 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))

  33. 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”

  34. 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 a stenosis value for a particular artery. There is no CABG affecting that artery between the aforementioned dx cath and the current procedure.

  35. 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”

  36. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” Question to Answer Core Data Elements Source Data 36

  37. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” Hematoma Size in centimeters Question to Answer Core Data Elements Source Data 37

  38. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” Hematoma Hematoma Size in centimeters Size in centimeters Question to Answer Core Data Elements Source Data 38

  39. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” Hematoma Hematoma Size in centimeters Size in centimeters Small hematoma Medium hematoma Medium to large hematoma Large Hematoma Question to Answer Core Data Elements Source Data 39

  40. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” Hematoma Hematoma Size in centimeters Size in centimeters < 5 cm hematoma Small hematoma 5-7 cm hematoma Medium hematoma >7-10 cm hematoma Medium to large hematoma > 10 cm hematoma Large Hematoma Question to Answer Core Data Elements Source Data 40

  41. Qualitative/Quantitative Reasoning • Distinct qualitative source data can be brought into alignment quantitatively: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate the maximum dimension, in centimeters, of the hematoma: < 5 cm, 5-10 cm, >10 cm.” Hematoma Hematoma Size in centimeters Size in centimeters < 5 cm hematoma Small hematoma 5-7 cm hematoma Medium hematoma >7-10 cm hematoma Medium to large hematoma > 10 cm hematoma Large Hematoma < 3 cm hematoma Small hematoma Question to Answer Core Data Elements Source Data 41

  42. Qualitative/Quantitative Reasoning • Distinct quantitative source data can treated in a qualitatively uniform way: “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate whether the patient has an evaluation that indicates left atrial enlargement.” Question to Answer Core Data Elements Source Data 42

  43. Qualitative/Quantitative Reasoning • Distinct quantitative source data can treated in a qualitatively uniform way: Left atrium “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate whether the patient has an evaluation that indicates left atrial enlargement.” Diameter of object Rule indicating atrial enlargement Question to Answer Core Data Elements Source Data 43

  44. Qualitative/Quantitative Reasoning • Distinct quantitative source data can treated in a qualitatively uniform way: Left atrium Left atrium “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate whether the patient has an evaluation that indicates left atrial enlargement.” Diameter of object Diameter in centimeters Rule indicating atrial enlargement Evaluation Question to Answer Core Data Elements Source Data 44

  45. Qualitative/Quantitative Reasoning • Distinct quantitative source data can treated in a qualitatively uniform way: Left atrium Left atrium “Indicate if the patient has taken or has been prescribed anti-anginal medication within the past two weeks.” “Indicate whether the patient has an evaluation that indicates left atrial enlargement.” Diameter of object Diameter in centimeters Rule indicating atrial enlargement Evaluation Rule indicating male atrial enlargement Male patient Female patient Rule indicating female atrial enlargement Question to Answer Core Data Elements Source Data 45

  46. 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

  47. 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

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