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proposes an Information Technology infrastructure model that provides drug providers IT organization with a strategic perspective for how to computerize their Safety Drug reporting activity. It introduces software development concepts, methods, techniques and tools for collecting data from multiple platforms and generates reports from them by scripting queries.
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Standardization of “Standardization of “Drug safetyDrug safety” Reporting Applications” Reporting Applications
The State University of New York collage at Brockport
Department of Computational Science
by: Halley M. ZandWinter, 2005
Thesis advisor: Dr. Robbert Tuzun
““Drug SafetyDrug Safety” Reporting” Reporting
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Standardization Standardization
CostTime
Quality
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CharacteristicsCharacteristicsofof
Computer-based Computer-based ““Drug SafetyDrug Safety” Reporting ” Reporting ApplicationsApplications
Consistent with FDA Standards.Consistent with FDA Standards. Use of different data resources.Use of different data resources. Accuracy of results is critical.Accuracy of results is critical. Efficiency, reliability, Efficiency, reliability,
maintainability, maintainability, usabilityusability and and dependability are required.dependability are required.
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Hire qualified developersHire qualified developers Provide a standardized IT Provide a standardized IT infrastructureinfrastructure
How to provide a standard computer-based How to provide a standard computer-based method for Drug Safety Evaluationmethod for Drug Safety Evaluation
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Technical SpecificationsTechnical Specifications
Data Access Data Access Data Management Data Management Statistical Analysis Statistical Analysis Representations Representations
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System Architecture ModelingSystem Architecture Modeling
Post marketing DATA Ware House
Data DictionaryArchive
(MedDRA/PubMed)
(Oracle)
ModificationClinical Studies Data,
Individual clinical trials
Reporting data by investigators.
Data Analyses
(SAS)
Adverse Event Reporting
Clinical Trials Hospital Labs.
Verifications
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TerminologiesTerminologies (technical terms)(technical terms)
Data ClassificationsData Classifications Control CodeControl Code FormattingFormatting Quality ControlQuality Control Data MiningData Mining Gathering information and documenting system specificationsGathering information and documenting system specifications Accessing and manipulating dataAccessing and manipulating data ScriptingScripting
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MedDRAMedDRA
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MedDRAMedDRA
AdvantagesAdvantages::
On-line and well supported.On-line and well supported.
Informatics terminologies such as encoding are already included in Informatics terminologies such as encoding are already included in MedDRA for its own data sets. MedDRA for its own data sets.
Maintains high standards that can be updated and used in queries Maintains high standards that can be updated and used in queries or importing dataor importing data
Has a control code utility that is able to analyze the coding sets. Has a control code utility that is able to analyze the coding sets.
DisadvantagesDisadvantages:: Quality control may be required for the data mining codes. Quality control may be required for the data mining codes.
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Control CodeControl Code
MedMinerMedMiner(MedDRA)(MedDRA)
SCM(SAS)(SAS)
DebuggingDebugging AnalysisAnalysis
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SAS->Solutions->Desktop->Development and Programming-> Source Code Manager
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Formatting Formatting
type-checking type-checking readability readability Us l tyabi i
user defined formattinguser defined formattingDefault formattingDefault formatting
standardized formattingstandardized formatting
• Save these formats in SAS catalogs Save these formats in SAS catalogs reusablereusable
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Quality Control Quality Control
Check for:Check for:
syntax errorssyntax errors
execution errorsexecution errors
assure that statements appear in correct orderassure that statements appear in correct order
input statements and datainput statements and data
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Data miningData mining
Looking for hidden patterns in a group of Looking for hidden patterns in a group of data.data.
By applying statistical options, we can By applying statistical options, we can optimize our guess about a frequently optimize our guess about a frequently occurring best match. occurring best match.
SAS supports data mining for large volumes SAS supports data mining for large volumes of statistical proceduresof statistical procedures. .
Provides a safe marketing strategy rather Provides a safe marketing strategy rather than risk-taking as it can protect drug than risk-taking as it can protect drug providers against lawsuitproviders against lawsuit
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Gathering Information and Documenting Gathering Information and Documenting System SpecificationsSystem Specifications
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SPSSSPSS
DBASE, DB2, DB4DBASE, DB2, DB4
MedDRAMedDRA
SYMBASSYMBAS
ACCESS, EXCELACCESS, EXCELOracle, MySQLOracle, MySQL
Raw dataRaw data
remoteremote
MainframeMainframe
System specifications:System specifications:
Source DataSource Data Data StagingData Staging MetadataMetadata The The
Entity-Relationship ModelEntity-Relationship Model
Source DataSource Data
Clinical and postmarketing trialsClinical and postmarketing trials
Homegrown applications used by clinics and hospitalsHomegrown applications used by clinics and hospitals
EMREMR
Adverse Event Reporting (Med Watch)Adverse Event Reporting (Med Watch)
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Data StagingData Staging
The storage and processing of extracted data from internal and The storage and processing of extracted data from internal and external systems prior to loading in a SAS data bank.external systems prior to loading in a SAS data bank.
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MetadataMetadataMetadata for MedDRA informationMetadata for MedDRA information
SOCSOC MedDRA CODE NumericMedDRA CODE Numeric MedDRA Term StringMedDRA Term String HLGTHLGT MedDRA CODE NumericMedDRA CODE Numeric MedDRA Term StringMedDRA Term String PT PT MedDRA CODE NumericMedDRA CODE Numeric MedDRA Term StringMedDRA Term String COSTART Symbol, AlphaNumericCOSTART Symbol, AlphaNumeric WHO_ART Code, WHO_ART Code, Numeric Numeric ICDS Code, ICDS Code, Numeric Numeric PT ICD-10 CodePT ICD-10 Code Numeric Numeric HARTS Code, NumericHARTS Code, Numeric ICDS_CM Code, ICDS_CM Code, Numeric Numeric JART CodeJART Code Numeric Numeric * SOC Code * SOC Code Numeric Numeric * SOC Name * SOC Name Numeric Numeric
LLT – Lowest Level TermLLT – Lowest Level Term MedDRA CodeMedDRA Code NumericNumeric MedDRA TermMedDRA Term StringString WHO_ART CodeWHO_ART Code NumericNumeric COSTART SymbolCOSTART Symbol AlphaNumericAlphaNumeric ICDS_CM CodeICDS_CM Code NumericNumeric CURRENCYCURRENCY
Character/BooleanCharacter/Boolean HARTS CodeHARTS Code NumericNumeric ICDS CodeICDS Code NumericNumeric JART CodeJART Code NumericNumeric * Multi valued attribute* Multi valued attribute
List of other information that need Metadata:List of other information that need Metadata:
Patient information such as Patient identifier, Age at time of Patient information such as Patient identifier, Age at time of event or date of birth, sex, weight; event or date of birth, sex, weight;
Outcomes attributed to adverse event such as death: Outcomes attributed to adverse event such as death: mo/day/yr, life-threatening, hospitalization, initial or mo/day/yr, life-threatening, hospitalization, initial or prolonged, disability, congenital anomaly, required prolonged, disability, congenital anomaly, required intervention to prevent impairment/damage, other; intervention to prevent impairment/damage, other;
Date of event and report in mo/day/yr format; Date of event and report in mo/day/yr format; Description of problem; Description of problem; Relevant tests/laboratory data including dates; Relevant tests/laboratory data including dates; Other relevant history including preexisting medical condition Other relevant history including preexisting medical condition
(e.g. allergies, race, pregnancy, smoking or alcohol use, (e.g. allergies, race, pregnancy, smoking or alcohol use, hepatic/renal dysfunction, etc.)hepatic/renal dysfunction, etc.)
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Patient primary reason for medical visitPatient primary reason for medical visit History of onset of clinical signs and symptoms,History of onset of clinical signs and symptoms, Current list of medications the patient is usingCurrent list of medications the patient is using Relevant past medical history, including hospital admission, Relevant past medical history, including hospital admission,
surgeries, and diagnosissurgeries, and diagnosis History of family disease, such as diabetes, cancer, heart History of family disease, such as diabetes, cancer, heart
disease, and medical illnessdisease, and medical illness Social history: use of drugs, smoking, job stability, and Social history: use of drugs, smoking, job stability, and
housing, living condition, incarceration.housing, living condition, incarceration. Review of systems: patient relocation of systems and current Review of systems: patient relocation of systems and current
medical problems, such as trouble sleeping at night or panic medical problems, such as trouble sleeping at night or panic episodes, and result or tests.episodes, and result or tests.
Physical examination: the clinician’s hands-on examination Physical examination: the clinician’s hands-on examination of patient, including head, eyes, ears, nose, throat, chest, of patient, including head, eyes, ears, nose, throat, chest, and extremitiesand extremities
Labs includes blood glucose, cholesterol, and drug levelsLabs includes blood glucose, cholesterol, and drug levels Studies such as X-ray, MRI, CT, and EKG.Studies such as X-ray, MRI, CT, and EKG. Progress notes such as record of temporal progression of Progress notes such as record of temporal progression of
signs and symptoms, labs and studies for the length of the signs and symptoms, labs and studies for the length of the study or admissionstudy or admission
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entity-relationship modelentity-relationship model
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Accessing and Manipulating DataAccessing and Manipulating Data
Processing Examples:Processing Examples:
Retrieving dataRetrieving data Using external files Using external files LibrariesLibraries
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Special focus should be placed on the management of SAS data Special focus should be placed on the management of SAS data set input and output, working with different data types, and the set input and output, working with different data types, and the
manipulation of data. It may also be necessary to control the SAS manipulation of data. It may also be necessary to control the SAS data set input and output, combine, summarize, and then process data set input and output, combine, summarize, and then process
iteratively with programming to perform data manipulations and iteratively with programming to perform data manipulations and transformations. transformations.
Example1:
Example:Example:
filename fromrcr ftp 'main.data' cd='halley/thesis‘ user='cpsuser' host='cps.brockport.edu' recfm=v /* logical record length is long*/ prompt;
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data PatientInfo; data PatientInfo; infile 'c:\thesis\data1.txt' ;infile 'c:\thesis\data1.txt' ; input PatientId $ 1-13 age 14-17 sex $ 18-23 weight 24-30 +2 country input PatientId $ 1-13 age 14-17 sex $ 18-23 weight 24-30 +2 country run;run;
proc print data=PatientInfo;proc print data=PatientInfo;
run;run;------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------The SAS System 05:25 Thursday, December 15, 2005 5The SAS System 05:25 Thursday, December 15, 2005 5 PatientId age sex weight countryPatientId age sex weight country Hzan0616341 30 1 200 11 Hzan0616341 30 1 200 11 Amir5666892 40 2 180 12 Amir5666892 40 2 180 12 J675bhgfdql 56 2 . 45 ->J675bhgfdql 56 2 . 45 ->Nmjhg567908 12 1 100 23 Nmjhg567908 12 1 100 23 Iu6-567-567 99 1 170 01 Iu6-567-567 99 1 170 01 ***A missing value for a numeric variable is presented by a period (.) ***A missing value for a numeric variable is presented by a period (.)
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Retrieving DataRetrieving Data
Accomplishing typical data processing such as the reading of raw data Accomplishing typical data processing such as the reading of raw data
files and SAS data sets and then files and SAS data sets and then writing writing these results to SAS data sets.these results to SAS data sets.
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Reading Terminology:
• Tables• DBMS • Queries• Views• Null Values
tablestables
SQL TermsSQL Terms SAS Terms SAS Terms Data Processing Data Processing Terms Terms
tabletable SAS data fileSAS data file filefile
rowrow observationobservation recordrecord
columncolumn variablevariable fieldfield
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Database Management Systems Database Management Systems
Connect to, update, and modify tables that were created in other Connect to, update, and modify tables that were created in other environments with other applications.environments with other applications.
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QueriesQueries
By Proc SQL, use a SELECT statement and its subordinate clauses to By Proc SQL, use a SELECT statement and its subordinate clauses to form a query. form a query.
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ViewsViews
Do not actually contain data in the same way as tables.Do not actually contain data in the same way as tables.
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Null ValuesNull Values
Are not the same as a blank or zero value. However, to be compatible Are not the same as a blank or zero value. However, to be compatible with the rest of SAS, PROC SQL treats missing values as blanks or with the rest of SAS, PROC SQL treats missing values as blanks or
zero values, and considers all three to be null values. zero values, and considers all three to be null values.
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Using External FilesUsing External Files
Where is the file?Where is the file?
Identify the file directly in the INFILE, FILE, or other SAS statement that uses it.Identify the file directly in the INFILE, FILE, or other SAS statement that uses it.
Set up a fileref for the file by using the FILENAME statement, and then use the Set up a fileref for the file by using the FILENAME statement, and then use the fileref in the INFILE, FILE, or other SAS statement.fileref in the INFILE, FILE, or other SAS statement.
Use operating environment commands to set up a fileref, and then use the fileref Use operating environment commands to set up a fileref, and then use the fileref in the INFILE, FILE, or other SAS statement.in the INFILE, FILE, or other SAS statement.
To use several files or members from the same directory, partitioned data sets To use several files or members from the same directory, partitioned data sets (PDS), or MACLIB, use the FILENAME statement to create a fileref that will (PDS), or MACLIB, use the FILENAME statement to create a fileref that will identify the name. The fileref can then be used in the INFILE statement and identify the name. The fileref can then be used in the INFILE statement and enclose the name of the file, PDS member, or MACLIB member in parentheses enclose the name of the file, PDS member, or MACLIB member in parentheses immediately after the fileref. immediately after the fileref.
example example
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Example:Example:
/* filename data 'directory-or-PDS-or-MACLIB' */;/* filename data 'directory-or-PDS-or-MACLIB' */;/* data1.txt and data2.txt located in directory c:\thesis *//* data1.txt and data2.txt located in directory c:\thesis */
filename data 'c:\thesis\';filename data 'c:\thesis\';
data paitientdata1;data paitientdata1; infile data('data1.txt');infile data('data1.txt'); input PatientId $11. +2 age 2. +1 weight 3. +2 sex 1. +2 date1 input PatientId $11. +2 age 2. +1 weight 3. +2 sex 1. +2 date1
mmddyy10. +2 date2 mmddyy10. + 2 country 12. ;mmddyy10. +2 date2 mmddyy10. + 2 country 12. ;run;run;data paitientdata2;data paitientdata2; infile data('data2.txt');infile data('data2.txt'); input PatientId $11. +2 age 2. +1 weight 3. +2 sex 1. +2 date1 input PatientId $11. +2 age 2. +1 weight 3. +2 sex 1. +2 date1
mmddyy10. +2 date2 mmddyy10. + 2 country 12. ;mmddyy10. +2 date2 mmddyy10. + 2 country 12. ;run;run;
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LibrariesLibraries
Access data sources by defining ’libref’ and assign accesses without copying
them inside the SAS environment.
**** SAS Library includes Metadata objects that are defined by libref. These objects define the engines that are used to process the data. This library has URI (Uniform Resource Identifier) architecture. To get access to a SAS Metadata Server, define the host address. If working in a TCP network, define the port number. If the protocol is not a com but a bridge, define a user-id and password otherwise it will not be possible to log into a SAS Metadata Server. In addition, any repository Metadata may be used by a repository-id or name.
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ScriptingScripting
Examples:Examples:
Accessing or importingAccessing or importing Creating tablesCreating tables and and entering dataentering data Statistical ProcessStatistical Process Extracting parts of dataExtracting parts of data FormattingFormatting
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According to Guidance Documents for Drug Evaluations and Research from the U.S. Food and Drug Administration all prescription drugs, both new and generic need to be approved by the FDA. To obtain these approvals, drug providers are required to generate annual reports on product safety and attach them to their application letter. Also, any person can report to the FDA a reaction or problem with a drug. The FDA reviews applications and all reported clinical outcomes to see if the reported events happened because of other reasons or use the suspected drug.
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ConclusionsConclusions
The quality of a drug safety reporting application The quality of a drug safety reporting application depends on the system architecture and the depends on the system architecture and the
programming skill. programming skill.