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Methodologies and AutomatedMethodologies and Automated Applications for Post-Marketing Applications for Post-Marketing
Outcomes Surveillance of Medical Outcomes Surveillance of Medical Devices and MedicationsDevices and Medications
Michael E. Matheny, MD, MSMichael E. Matheny, MD, MS
NLM Biomedical Informatics FellowNLM Biomedical Informatics Fellow
Decision Systems Group, Department of Radiology Decision Systems Group, Department of Radiology Brigham & Women’s Hospital, Boston, MABrigham & Women’s Hospital, Boston, MA
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OutlineOutline
Post-Marketing Surveillance BackgroundPost-Marketing Surveillance Background Statistical Methodology DevelopmentStatistical Methodology Development Computer Application DevelopmentComputer Application Development Clinical ExamplesClinical Examples Future Directions Future Directions
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BackgroundBackgroundSurveillance RationaleSurveillance Rationale
Phase 3 Trials insufficient to ensure Phase 3 Trials insufficient to ensure adequate safety of medications and devicesadequate safety of medications and devices
– Low frequency events are not detectedLow frequency events are not detected
– Protected populations (pregnant women, Protected populations (pregnant women, children) and more ill populations not children) and more ill populations not representedrepresented
– Complications delayed by a number of years Complications delayed by a number of years cannot be detectedcannot be detected
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BackgroundBackgroundFDA Medical DevicesFDA Medical Devices
1,700 types of devices1,700 types of devices
500,000 device models500,000 device models
23,000 manufacturers23,000 manufacturers
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BackgroundBackgroundFDA New Drug Applications (NDA)FDA New Drug Applications (NDA)
0
20
40
60
80
100
120
140
Applications
Approvals
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BackgroundBackgroundCurrent Post-Marketing SurveillanceCurrent Post-Marketing Surveillance
Combination of mandatory and voluntary Combination of mandatory and voluntary adverse event reportingadverse event reporting
– Mandatory reporting by manufacturers and health Mandatory reporting by manufacturers and health facilitiesfacilities
– Voluntary MedWatch / MAUDE reports by providers and Voluntary MedWatch / MAUDE reports by providers and patientspatients
2004 Drug-Related Adverse Event Reports2004 Drug-Related Adverse Event ReportsTotalTotal 422,889422,889 Manufacturer & Facility ReportsManufacturer & Facility Reports 401,396401,396 MedWatchMedWatch 21,49321,493
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0.173%
0.131%
0.102%
0.045%
0.234%
0.198%
0.116%
0.00%
0.05%
0.10%
0.15%
0.20%
0.25%
0.30%
Q2 Q3 Q4 Q1 Q2 Q3 Q4
0.0%
BackgroundBackgroundMAUDE Cypher Reporting RateMAUDE Cypher Reporting Rate
2003 2004
FDA Warning FDA Warning Cancelled
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BackgroundBackgroundCurrent Post-Marketing SurveillanceCurrent Post-Marketing Surveillance
‘‘Phase 4’ TrialsPhase 4’ Trials
– Poor CompliancePoor Compliance
• As of March 2006 report, 797 of 1231 (65%) agreed-As of March 2006 report, 797 of 1231 (65%) agreed-upon trials had yet to be startedupon trials had yet to be started
– BarriersBarriers
• Lack of manufacturer incentivesLack of manufacturer incentives– ExpensiveExpensive– Drug already on the marketDrug already on the market
• Lack of regulatory enforcementLack of regulatory enforcement
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BackgroundBackgroundMedical Device RecallsMedical Device Recalls
Boston Scientific cardiac stent (1998)Boston Scientific cardiac stent (1998)– Balloon rupture at low pressuresBalloon rupture at low pressures
Guidant cardio-defibrillator (2005)Guidant cardio-defibrillator (2005)– Malfunction due to electrical shortMalfunction due to electrical short
Vioxx (2004)Vioxx (2004)– cardiovascular complicationscardiovascular complications
Tequin (2006)Tequin (2006)– Hypoglycemia and hyperglycemiaHypoglycemia and hyperglycemia
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BackgroundBackgroundFDA ResponseFDA Response
Increasing demands for Phase 4 trialsIncreasing demands for Phase 4 trials
Legislation to increase quality of adverse Legislation to increase quality of adverse event reportingevent reporting
Emphasizing trial registries (clinicaltrials.gov) Emphasizing trial registries (clinicaltrials.gov) as way to prevent omission of resultsas way to prevent omission of results
Commissioned IOM report “The Future of Commissioned IOM report “The Future of Drug Safety”Drug Safety”
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BackgroundBackgroundAdverse Event Data ContinuumAdverse Event Data Continuum
Phase 3Trials
MAUDE /MedWatch
VoluntaryRegistry
MandatoryRegistry
Internal Validity +++ -- ++ +++
Generalizibility +/- +/- ++ +++
Breadth ++ +++ ++ ++
Immediacy --- +++ ++ ++
Lack of Bias +++ --- --- ++
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Statistical MethodsStatistical MethodsMedical Outcomes MonitoringMedical Outcomes Monitoring
Using registry data that tracks all patients Using registry data that tracks all patients allows different types of analysis than used in allows different types of analysis than used in the FDA’s adverse event reporting systemsthe FDA’s adverse event reporting systems
No generally accepted methods for No generally accepted methods for monitoring registry data for adverse eventsmonitoring registry data for adverse events
– Lack of sufficient discrete electronic data Lack of sufficient discrete electronic data sources to construct registriessources to construct registries
– Some outcomes are challenging or expensive to Some outcomes are challenging or expensive to track for an entire populationtrack for an entire population
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ObjectiveObjective
Develop methodologies and implement an Develop methodologies and implement an automated computer monitoring system to automated computer monitoring system to perform outcomes surveillance of registry perform outcomes surveillance of registry data for new medical devices and data for new medical devices and medicationsmedications
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Statistical MethodsStatistical MethodsStatistical Process ControlStatistical Process Control
Period
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Statistical MethodsStatistical MethodsBayesian Updating StatisticsBayesian Updating Statistics
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Statistical MethodsStatistical MethodsEstablishing Baseline DataEstablishing Baseline Data
Primary Data SourcesPrimary Data Sources
– Phase 3 trial dataPhase 3 trial data
– Post-Marketing data from a closely related Post-Marketing data from a closely related medication/devicemedication/device
Alternative Data SourcesAlternative Data Sources
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Statistical MethodsStatistical MethodsEstablishing Alerting ThresholdsEstablishing Alerting Thresholds
Use number of events and sample size to calculate Use number of events and sample size to calculate proportion with confidence intervalsproportion with confidence intervals
Typically, medical domains use 95% CI or 1.96 Typically, medical domains use 95% CI or 1.96 sigma from the point estimatesigma from the point estimate
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Statistical MethodsStatistical Methods Establishing Alerting ThresholdsEstablishing Alerting Thresholds
SPCSPC
BUSBUS
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Statistical MethodsStatistical Methods Establishing Alerting ThresholdsEstablishing Alerting Thresholds
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Statistical MethodsStatistical Methods Establishing Alerting ThresholdsEstablishing Alerting Thresholds
Wilson’s method of comparison between two Wilson’s method of comparison between two proportionsproportions
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Statistical MethodsStatistical MethodsRisk StratificationRisk Stratification
Allows creating subgroups for separate Allows creating subgroups for separate analysesanalyses
Single variableSingle variable
Logistic regression model with scoring Logistic regression model with scoring thresholdsthresholds
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Application DevelopmentApplication DevelopmentDELTADELTA
Data Extraction and Longitudinal Time Data Extraction and Longitudinal Time Analysis (DELTA)Analysis (DELTA)
Design GoalsDesign Goals– Generic data import formatGeneric data import format– Allow both prospective and retrospective Allow both prospective and retrospective
analysesanalyses– Modular framework to allow sequential addition Modular framework to allow sequential addition
of statistical methodologiesof statistical methodologies– Multiple alerting methodsMultiple alerting methods– Any number of concurrent ongoing analysesAny number of concurrent ongoing analyses
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Application DevelopmentApplication DevelopmentDELTADELTA
Data Dictionary Statistical Modules
DELTA Database
Clinical Data Entry
Source Database
Source IT Manager
SPC
BUSVP
NIn
tra
ne
t
DELTA Users
WebServer
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Application Test DataApplication Test DataCypher Drug-Eluting Stent (DES)Cypher Drug-Eluting Stent (DES)
Setting:Setting:– Brigham & Women’s Hospital Brigham & Women’s Hospital (07/2003 – 12/2004)(07/2003 – 12/2004)
Population:Population:– All patients receiving a drug-eluting stent (2270)All patients receiving a drug-eluting stent (2270)
Outcome:Outcome:– Post-procedural in-hospital mortality (27)Post-procedural in-hospital mortality (27)
Baseline:Baseline:– University of Michigan Data (1997-1999)University of Michigan Data (1997-1999)
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Application DevelopmentApplication DevelopmentDELTADELTA
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Risk StratificationRisk StratificationPotential SolutionPotential Solution
Incorporate individual risk prediction models Incorporate individual risk prediction models in order to adjust for case mix and illness in order to adjust for case mix and illness severityseverity
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Possible Risk Prediction MethodsPossible Risk Prediction Methods
Linear / Logistic RegressionLinear / Logistic Regression
Artificial Neural NetworksArtificial Neural Networks
Bayesian NetworksBayesian Networks
Support Vector MachinesSupport Vector Machines
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LR External Validation LR External Validation ModelsModels
Model Dates Location Sample
NY 1992 1991 NY 5827
NY 1997 1991 – 1994 NY 62670
CC 1997 1993 – 1994 Cleveland, OH 12985
NNE 1999 1994 – 1996 NH, ME, MA, VT 15331
MI 2001 1999 – 2000 Detroit, MI 10796
BWH 2001 1997 – 1999 Boston, MA 2804
ACC 2002 1998 – 2000 National 100253
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LR External ValidationLR External Validation
Setting:Setting:– Brigham & Women’s Hospital Brigham & Women’s Hospital (01/2002 – 09/2004)(01/2002 – 09/2004)
Population:Population:– All patients undergoing percutaneous coronary All patients undergoing percutaneous coronary
intervention (5216)intervention (5216)
Outcome:Outcome:– Post-procedural in-hospital mortality (71)Post-procedural in-hospital mortality (71)
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LR External Validation LR External Validation ResultsResults
Curve Deaths AUC HL χ2 HL (p)
NY 1992 96.7 0.82 31.1 <0.001
NY 1997 61.6 0.88 32.2 <0.001
CC 1997 78.8 0.88 27.8 <0.001
NNE 1999 56.2 0.89 45.9 <0.001
MI 2001 61.8 0.86 30.4 <0.001
BWH 2001 136.1 0.89 39.7 <0.001
ACC 2002 49.9 0.90 42.0 <0.001
BWH 2004 70.5 0.93 7.61 0.473
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LR External Validation LR External Validation ConclusionsConclusions
Excellent discrimination across all modelsExcellent discrimination across all models
Calibration (Hosmer-Lemeshow) poor for all Calibration (Hosmer-Lemeshow) poor for all models but recent local onemodels but recent local one
Addressed categorical risk stratification by Addressed categorical risk stratification by keeping all records in one stratumkeeping all records in one stratum
Calibration problems over time limit Calibration problems over time limit application, and require exploration of application, and require exploration of recalibration methodsrecalibration methods
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OPUS (TIMI-16)OPUS (TIMI-16)
Setting:Setting:– 888 Hospitals in 27 Countries888 Hospitals in 27 Countries
Intervention:Intervention:– Oral IIb-IIIa Inhibitor vs PlaceboOral IIb-IIIa Inhibitor vs Placebo
Population:Population:– Intervention Arm [Both arms identical at 30 days] (6867)Intervention Arm [Both arms identical at 30 days] (6867)
Outcome:Outcome:– 30 day mortality30 day mortality– Trial stopped early due to elevation in intervention armTrial stopped early due to elevation in intervention arm
Baseline:Baseline:– Control Arm (3421)Control Arm (3421)
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OPUS (TIMI-16)OPUS (TIMI-16)30 Day Mortality30 Day Mortality
Control Intervention
Period Events Patients Event Rate (%) Events Patients Event Rate (%) p
1 0 0 0.0 0 5 0.0 *
2 0 17 0.0 0 30 0.0 *
3 0 48 0.0 1 95 1.1 1.000
4 0 135 0.0 7 249 2.8 0.102
5 1 268 0.4 11 529 2.1 0.070
6 4 463 0.9 18 951 1.9 0.173
7 5 764 0.7 33 1,528 2.2 0.008
8 8 1,089 0.7 46 2,161 2.1 0.003
9 11 1,412 0.8 54 2,815 1.9 0.004
10 16 1,805 0.9 78 3,610 2.2 <0.001
11 21 2,173 1.0 92 4,410 2.1 <0.001
12 33 2,701 1.2 109 5,447 2.0 0.011
13 46 3,360 1.4 134 6,756 2.0 0.031
14 46 3,421 1.3 134 6,867 2.0 0.031
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OPUS (TIMI-16) OPUS (TIMI-16) Alert SummaryAlert Summary
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Month
Prospective
SPC
LR Stratified SPC
BUS
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CLARITY (TIMI-28) CLARITY (TIMI-28)
Setting:Setting:– 313 Hospitals in 23 Countries313 Hospitals in 23 Countries
Intervention:Intervention:– Oral Anti-Platelet Agent vs PlaceboOral Anti-Platelet Agent vs Placebo
PopulationPopulation– Intervention Arm (1751)Intervention Arm (1751)
Outcome:Outcome:– Major BleedingMajor Bleeding– DSMB concerned, but trial did not stop earlyDSMB concerned, but trial did not stop early
BaselineBaseline– Control Arm (1739)Control Arm (1739)
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CLARITY (TIMI-28)CLARITY (TIMI-28)Major BleedingMajor Bleeding
Control Intervention
Period Events Patients Event Rate (%) Events Patients Event Rate (%) p
1 0 4 0.0 0 1 0.0 *
2 0 13 0.0 0 12 0.0 *
3 1 27 3.7 0 23 0.0 1.000
4 2 40 5.0 1 49 2.0 0.586
5 2 73 2.7 2 83 2.4 1.000
6 3 116 2.6 5 126 4.0 0.724
7 4 168 2.4 7 173 4.0 0.548
8 4 214 1.9 9 226 4.0 0.262
9 7 276 2.5 10 284 3.5 0.624
10 8 337 2.4 12 361 3.3 0.502
11 10 424 2.4 15 450 3.3 0.423
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CLARITY (TIMI-28)CLARITY (TIMI-28)Major BleedingMajor Bleeding
Control Intervention
Period Events Patients Event Rate (%) Events Patients Event Rate (%) p
12 11 536 2.1 16 554 2.9 0.438
13 13 639 2.0 18 649 2.8 0.468
14 17 776 2.2 22 780 2.8 0.517
15 17 892 1.9 23 926 2.5 0.427
16 18 1,041 1.7 28 1,058 2.6 0.180
17 20 1,192 1.7 31 1,195 2.6 0.156
18 24 1,314 1.8 31 1,327 2.3 0.414
19 25 1,457 1.7 31 1,459 2.1 0.500
20 26 1,584 1.6 32 1,606 2.0 0.509
21 30 1,739 1.7 34 1,751 1.9 0.706
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CLARITY (TIMI-28)CLARITY (TIMI-28)Alert SummaryAlert Summary
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
Month
Prospective
SPC
LR Stratified SPC
BUS
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OPUS /CLARITYOPUS /CLARITYConclusionsConclusions
SPC performed well in the positive study, but SPC performed well in the positive study, but did have some false positive alerts in the did have some false positive alerts in the negative studynegative study
LR stratified SPC failed to alert early in the LR stratified SPC failed to alert early in the positive study, but performed well in the positive study, but performed well in the negative studynegative study
BUS was more specific than SPC in both BUS was more specific than SPC in both studiesstudies
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Sensitivity AnalysisSensitivity Analysis
Setting:Setting:– Brigham & Women’s Hospital Brigham & Women’s Hospital (01/2002 – 12/2004)(01/2002 – 12/2004)
Population:Population:– All patients undergoing percutaneous coronary All patients undergoing percutaneous coronary
intervention (6175)intervention (6175)
Outcome:Outcome:– Post-procedural major adverse cardiac events (403)Post-procedural major adverse cardiac events (403)
• DeathDeath• Post-Procedural Myocardial InfarctionPost-Procedural Myocardial Infarction• Repeat VascularizationRepeat Vascularization
Baseline:Baseline:– Arbitrarily set event rates and sample sizesArbitrarily set event rates and sample sizes
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Sensitivity AnalysisSensitivity AnalysisResultsResults
6158
5552
5047
4441
42 4
2 92 92
19
3
19
3
40
5
40
5
85
1
85
1
17
87
17
87
0
5
10
15
20
# Alerts
Observed Rate (% )
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Clinical AlertClinical Alert
Setting:Setting:– Brigham & Women’s Hospital Brigham & Women’s Hospital (01/2002 – 12/2004)(01/2002 – 12/2004)
Population:Population:– All patients receiving a vascular closure device All patients receiving a vascular closure device
after percutaneous coronary intervention (3947)after percutaneous coronary intervention (3947)
Outcome:Outcome:– Retroperitoneal Hemorrhage (25)Retroperitoneal Hemorrhage (25)
Baseline:Baseline:– Stanford University Data (2000 – 2004)Stanford University Data (2000 – 2004)
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Event Rate ElevationEvent Rate Elevation
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Manual ReviewManual Review
Triggered root cause analysisTriggered root cause analysis
Manual chart review and multivariable Manual chart review and multivariable analsysisanalsysis
Final Result: Not related, confounded by Final Result: Not related, confounded by indicationindication
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Future WorkFuture WorkMethodologyMethodology
Address Calibration ConcernsAddress Calibration Concerns
– Recalibration of Logistic Regression modelsRecalibration of Logistic Regression models
– Development of Machine Learning Risk Development of Machine Learning Risk Prediction ModelsPrediction Models
Address BUS InsensitivityAddress BUS Insensitivity
– Incorporate data weight decay over timeIncorporate data weight decay over time
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Future Work Future Work ApplicationApplication
Outcomes DB
DELTAAgent
Brigham and Women’s Hospital
DELTA reports
DELTA Server
Massachusetts Data Analysis Center (Mass-DAC)
SMTP E-mail Server
E-mail alert
Outcomes DB
DELTAAgent
Massachusetts General Hospital
Outcomes DB
DELTAAgent
St. Elizabeth’s Medical Center
MA Claims DB
MA Death Index
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Future WorkFuture Work
New Medication Outcomes SurveillanceNew Medication Outcomes Surveillance
Inpatient (versus Outpatient)Inpatient (versus Outpatient)
– More frequent monitoringMore frequent monitoring
– Higher quality source dataHigher quality source data
– Outcomes easier to captureOutcomes easier to capture
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Future WorkFuture WorkDevelop Data RepositoryDevelop Data Repository
PatientDemographics
Local Institution
DELTA Server
CentralizedData
Repository
ComputerizedOrder Entry
Laboratory
Progress Notes(NLP)
HospitalBilling
MedicationAdministration
RadiologyIS
State DeathIndex
OtherOutcomes
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Future WorkFuture WorkInitial FrameworkInitial Framework
New medication laboratory monitoring New medication laboratory monitoring protocolprotocol
Standard measures that are most commonly Standard measures that are most commonly affected in new medicationsaffected in new medications– AST, ALT, Creatinine, WBC, PlateletsAST, ALT, Creatinine, WBC, Platelets
Establish reasonable baselinesEstablish reasonable baselines– Closely Related medication lab resultsClosely Related medication lab results– Unrelated medication lab resultsUnrelated medication lab results– Expert Panel EstimationExpert Panel Estimation
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AcknowledgementsAcknowledgements
MentorsMentors– Lucila Ohno-Machado, MD, PhDLucila Ohno-Machado, MD, PhD– Frederic S. Resnic, MD, MSFrederic S. Resnic, MD, MS
CollaboratorsCollaborators– Nipun Arora, MDNipun Arora, MD– Sharon Lise-Normand, PhDSharon Lise-Normand, PhD– Ewout Steyerberg, PhDEwout Steyerberg, PhD
Programming TeamProgramming Team– Richard CopeRichard Cope– Barry CoflanBarry Coflan– Atul TatkeAtul Tatke
FundingFunding– NLM R01-LM-08142NLM R01-LM-08142– NLM T15-LM-07092NLM T15-LM-07092
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Michael Matheny, MD MS Michael Matheny, MD MS
mmatheny@dsg.harvard.edummatheny@dsg.harvard.edu Brigham & Women’s HospitalBrigham & Women’s Hospital
Thorn 309Thorn 30975 Francis Street75 Francis Street
Boston, MA 02115Boston, MA 02115
The EndThe End