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WHO Drug
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The WHO Drug dictionary for medical product information was created by the WHO Programme for International Drug Monitoring and is managed by the Uppsala Monitoring Centre. WHO Drug allows biopharmaceutical companies and regulatory agencies to consistently identify drug names, active ingredients, and therapeutic uses for drugs or compounds typically reported under concomitant or suspect medica- tions. The most recent versions are referred to as WHO Drug Dictionary Enhanced or WHO-DDE. The hierarchical structure of the dictionary includes trade or proprietary names and a preferred or nonproprietary (generic) name. Additional information associated with the drug name includes the manufacturer’s name and whether the drug has a single or multiple ingredients.
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USING AUTOCODERS
|
Basic versions of autocoder programs take a reported term and look for an exact match in the lower-level terms column of a dictionary table. These work well with drug and disease dictionaries where the reported terms tend to have little variation. Coding Dictionaries and Systems 221 They do not have as high of a match rate for adverse event terms where the variation in the wording of reported terms is high. More sophisticated autocoders do simple text transformations on the reported term in an attempt to improve the likelihood of a match to the dictionary. The transformations may include removal of punctuation or removal of extraneous words (such as “patient complains of”). Even the most simple text transformations improve the match rate for adverse event terms. To understand how autocoders work at a specific company, we have to understand the details of the following: • How the term is collected (as this can impact the coding success) • The results the autocoder returns when it finds a match • The support, if any, the autocoder provides when no match is found
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Collecting the Term
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The first part of the coding process involves collecting and storing the reported term (which may be an adverse event term, a drug name, or a medical history diagnosis). The term is reported on a case report form (CRF) and entered into the database or through an electronic CRF (eCRF) form and is immediately in a database. When entered into an eCRF form, the term is typically “cleaner” than that found on a paper form because on paper, sites tend toward abbreviations and symbols. Misspellings, however, will be common in whatever way the term is reported. In paper studies, data management may find some terms that are hard to read, that contain abbreviations or symbols, and terms that are longer than the database fields. Company-specific guidelines specify how to handle these events in general, and data management should be aware how those guidelines specifically affect the ability of autocoders to code these terms. All variations in the reported term will make coding, especially autocoding, more difficult. Therefore, there is great temptation to make modifications to the term that will make it more standard. Those changes that can be clearly specified by entry guidelines may be allowed. For example, symbols may be left out or replaced with standard text (e.g., ↑ with increased). Some companies permit correction of obvious misspellings based on a study-specific, predefined list. Other companies feel that “obvious” is unclear to begin with and that staff without medical training may make incorrect assumptions. As a compromise, a few companies have a secondary internal field, which does not appear on the CRF, to collect a version of the reported term that is more standard and more likely to code. For both paper and EDC, the autocoder is not run immediately after a user sub- mits the data. Autocoders are typically run once a day for EDC systems, and once a day but only after second entry (or quality review) for paper studies. Some companies may batch coding work or out-source it to specialized coding firms or contractors, but in all cases, data management or coders should run coding regularly throughout the course of a study rather than at a few milestones or infrequent time points along the way. Coding problems need to be identified on an ongoing basis, just as other discrepancies are, in order to improve the quality and timeliness of resolutions from the site. 222 Practical Guide to Clinical Data Management, Third Edition
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Storing the Results
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When autocoders successfully find a match, they store the resulting code or pre- ferred term and other information found in the dictionary hierarchy in the database along with the rest of the subject’s data. At some smaller companies, the matches will be left in a coding dataset and joined to the subject data dynamically at the time of analysis. The result of the “match” may be nothing more than a code or text associated with the reported term since the additional dictionary information can always be found via the unique code or term. But, as previously noted, dictionaries have auxiliary information associated with a code and this information is typically stored in additional columns or tables linked by code or preferred term. Some com- panies find it convenient to add in that information to the subject or coded record itself. Examples of auxiliary information include body system for adverse events or generic name for drugs. Sophisticated autocoders that support a complex process and more sophisticated algorithms often support information called something like coding status. This sta- tus is associated with the reported term and code to identify how the term was coded. The status values might indicate that the code for a reported term falls into one of these categories: • Provided automatically by the autocoder from the main dictionary • Provided automatically by the autocoder from a synonyms table • Found via lexical transformation • Assigned by the autocoder but manually overridden • Manually coded All of these states are used by the autocoder itself to determine future process- ing (e.g., never recode a term that was manually coded or overridden) and by data management reports to identify what coding assignments may require review. For example, many data management groups require review by the medical monitor of all codes assigned manually and review by a specialist of all codes assigned via a lexical transformation.
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EFFECTIVE CODING
|
The coding process is most effective when it integrates data management systems, practices, autocoders, data managers, and coding experts into one workflow. Good data management systems and practices will collect adverse event terms accurately and will identify many problem terms early. Autocoders run routinely as part of the data handling will also identify problems and discrepancies early. By giving coding experts access to the output of autocoder runs throughout the study (rather than only at critical points or near the end), they will have more time to devote to resolving problems and reviewing difficult coding decisions. A basic autocoder should be considered a requirement by every company. The more steps of the coding process the autocoder can support, the more effective the process will be. One of the most important features to improve effectiveness is the ability to store the association of new, nonmatching terms to the appropriate codes as synonyms. This both increases match rates over time and also helps ensure coding consistency. For highly varied adverse event terms, an autocoder may have to sup- port text modification algorithms to increase the match rate or to make the manual assignment process more effective. 229 27 Migrating and
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Migration by Hand
|
The more complex the migration and the more complex the data problems, the more complex the tools needed to migrate that data. Complex programs require time for development and validation by sophisticated and experienced programmers. When the job to migrate through tools and programs becomes too big or too expensive, companies should consider migrating by hand—that is, by reentering the data. Even with large volumes of data, experienced data entry staff may be able to reenter the data more efficiently than software tools can. Double entry in particular has a low error rate and even 100% verification can be reasonably cost efficient when carried out by administrative staff. This migration by hand should be an approach of last resort because information about the origin of the records (who originally entered them and when) is lost, as is any original audit trail. (For records submitted to the Food and Drug Administration [FDA], 21 CFR Part 11 requires that the audit trail be retained for at least as long as the electronic record itself.) Migrating Audit Trails For systems that have audit trails, the question arises as to whether the audit trail should be migrated along with the data. The FDA rule on electronic signatures and electronic records requires that the audit trail be accessible for the life of the data. However, this can prove difficult, if not impossible, because audit trails of some older systems are not in a structured form that would allow access and migration. Even accessible audit trail structures may contain less (or more) information than the new system requires. The migration team should review the audit trail structure and migrate it if the systems are compatible. If they are not, companies should consider putting the audit trail in some other archive format that is perhaps not as accessible as the data in the main application but could be reviewed if necessary during an audit of the data. This may mean putting it on the same platform or moving only key pieces of data. It is better, even, to move the audit trail to a different but accessible platform or applica- tion (even PDF files) than to lose the information entirely.
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What to Archive
|
Just archiving the data is usually not enough; if that were the case, saving the SAS extract of the data would satisfy everyone. As we saw in the previous migration discussion, the audit trail should be retained for as long as the records are (see 21 CFR Part 11, Section, 11.10). So the audit trail, at a minimum, must be brought along into the archive. General industry consensus seems to be that as much information 234 Practical Guide to Clinical Data Management, Third Edition about the design and conduct of the study should be brought along as well. This would include database design, coding dictionaries, coding algorithms, derived and calculated values, and cleaning rules. For some systems, this information will be in a proprietary design and cannot be moved electronically. In this case, paper or PDF versions of the information should be obtained before the old system is retired. In other cases, this study information will be available electronically (in Oracle, for example) and can be archived along with or parallel to the data, if care is taken. MIGRATION AND ARCHIVE PLANS Like every other major undertaking we have looked at so far in this book, every migration or archive effort needs a plan. The plan should clearly document the approach being taken for all data and list all of the risks involved. In particular, the plan should specify all points at which verification that the data is a true copy will be provided and what methods will be used to provide that verification. For archiving data, the plan should explicitly list all the components of the original system that will be included in the archive and the formats being used for their storage.
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FUTURE DIRECTIONS
|
The whole area of archiving is bound to mature over the next couple of years as companies try out various methods and improve upon standard format models. The FDA issued a guidance document in July of 2002 on the maintenance of electronic records. This guidance was withdrawn when the scope and application 21 CFR Part 11 was reevaluated. Presumably, the agency will issue new guidance on this topic eventually. In the meantime, every company will have to make its best effort, archiving as much as possible in as simple a format as possible, and documenting all decisions and approaches for future reference. 235 Appendix A: Data Management Plan Outline The outline for a data management plan shown in this appendix is just one example of the structure such a plan might take. The section headings that appear here come from the recommendations of the Society for Clinical Data Management (SCDM) combined with actual plans used by a wide variety of data management groups. The main headings identify the task to be described or the information to be provided. The subpoints provide a bit more detail on the kinds of information that might be included if appropriate. The subsections also list some of the documents that might be created or collected to fulfill requirements with the designation of Associated Documents. This basic outline can be easily adapted to studies carried out by a contract research organization (CRO) and studies that use electronic data capture (EDC) rather than paper case report forms (CRFs). As noted in Chapter 1, “The Data Management Plan,” the level of detail provided by a given group for a given study in such a data management plan could legitimately vary from little to lengthy. In particular, only a reference is needed when a task is fully described by standard operating procedures or guidelines. So, for example, if the process for reconciling serious adverse events (SAEs) is fully described in the company standard operating procedure (SOP) numbered DM-114, then the text under that bullet point would be something as simple as “As per DM-114. No study- specific instructions.”
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DESCRIPTION
|
1. Protocol title and study number 2. Reference to protocol document RESPONSIBILITIES/SCOPE OF WORK 1. Lead data manager 2. CRO contact information 3. Other relevant responsibilities (e.g., coding) CRF/ECRF DESIGN 1. Who is responsible for design 2. Who needs to sign off and when 3. How revisions are made, approved, and filed Associated document(s): Approved design document 236 Appendix A: Data Management Plan Outline
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CRF FLOW AND TRACKING
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1. For paper studies: the CRF workflow 2. For EDC studies: any paper elements being used (e.g., worksheets, backup SAE forms)
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Data Entry
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Perform Discrepancy Management and Query Resolution
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loads
|
LAB DATA ADMINISTRATION 1. Normal range handling 2. Other lab administration tasks
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SAE RECONCILIATION
|
1. Process for reconciliation, including discrepancy handling 2. Frequency Associated document(s): Final approved SAE reconciliation records
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CODING REPORTED TERMS
|
1. All dictionaries and specific versions being used for all items to be coded 2. Autocoding process, algorithms if relevant, software used 3. Workflow for uncoded terms and review/approval requirements 4. Coding conventions specific to this protocol or project Associated document(s): Final approved coding
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REPORTS
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1. List of standard reports (e.g., missing pages, outstanding discrepancies) 2. Frequency of reports TRANSFERS OR EXTRACTIONS 1. List of transfers expected or frequency of transfers, if any 2. Process for transfers Associated document(s): Transfer specifications for outgoing transfers INTERIM ANALYSES/LOCKS 1. If any, when in the course of the trial do they take place 2. Process that will be followed at that time; signature requirements if any Associated document(s): Any documents required by the process
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DATABASE CHANGES
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1. Process that is followed for database changes Associated document(s): Database change log; any output from testing and
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releasing updates
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238 Appendix A: Data Management Plan Outline
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Management SOPs
|
The list of standard operating procedures (SOPs) in this appendix is derived from good clinical practices (GCP) and 21 CFR Part 11 requirements, Food and Drug Administration (FDA) guidance documents, the Society for Data Management’s “Good Clinical Data Management Practices” document, and a broad selection of SOPs from companies both large and small. The list is a superset of the topics from those references and sources and is meant to be a comprehensive list of topics to be covered by a standard procedure. Note that: • Not all of these SOPs are of the same priority. • Some of the topics could be combined into a single procedure document. • Some of the topics might be addressed by corporate SOPs or policies. Refer to the relevant chapters of this book for additional details on best practices and documentation. 240 Appendix B: Clinical Data Management SOPs TABLE B.1
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Both
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FDA guidance documents recommend SOPs on system backups and archiving. For larger companies, this is usually an IT or validation group SOP. 243 Appendix C: CRO-Sponsor
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Paper
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For paper-based studies there should be a database audit SOP, study-specific audit plan, or the DMP. Requirements may be included in the Study Lock SOP.
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Comments
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Query Management: Issuing, Tracking, and
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EDC
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For EDC studies, describes what kinds of queries and query responses must be reviewed by in-house staff and covers the responsibilities for review and closing queries. Receiving Electronic Data
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Continued
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242 Appendix B: Clinical Data Management SOPs TABLE B.1 (Continued )
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Responsibility Matrix
|
Figure C.1 is an example of a responsibility matrix to be used in setting up a contract with a contract research organization (CRO) for a paper trial. Most of the key data management tasks are listed; some of them are broken down in detail. Note that this matrix should indicate not only who performs the work but also who is responsible for review (as shown in the first lines for the data management plan [DMP] and case report form [CRF] development.) It is also possible that the sponsor and CRO both do some of the work. The matrix should be customized for each study and sponsor– CRO combination as needed to clearly identify the work that is to be done. Figure C.2 is a similar matrix that might apply to an electronic data capture (EDC) study. Particular attention there should be paid to defining involvement during the testing phase of the study build. 244 Appendix C: CRO-Sponsor Responsibility Matrix
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CRO
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Write and Maintain Data Management Plan
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Review
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Develop Help Text and Completion Guidelines Define Database Characteristics Specify Edit Checks (manual and automatic) Build the EDC Application (includes unit test)
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Build the Database
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• Write specifications • Design • Testing Program and Validate Edit Checks Image CRF Pages and Query Forms
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Track CRFs
|
Generate Weekly Reports • Missing/expected pages • Discrepancy counts including time outstanding Perform Clinical Data Reviews Administer Central Lab Data • Define lab transfer agreement • Receive lab data • Manage lab normals • Check lab data (specify specific checks) • Contact lab to resolve data issues Receive and Manage Assay Data • Define transfer agreement • Receive data transfers • Check electronic data (specify specific checks) • Contact provider to resolve data issues Conduct Database QC (quality control) Audit • Frequency • Special milestones • Final audit Transfer Data to Sponsor Transfer Specification
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Code Reported Terms
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• AEs • Medications Perform SAE reconciliation
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Approve Study Lock
|
FIGURE C.1 Data management responsibility: Paper-based study. Appendix C: CRO-Sponsor Responsibility Matrix 245
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Approve Online eCRF
|
Create Validation/UAT (user acceptance testing) Plan Perform System Testing Perform Query Management • Review queries closed without data updates • Create manual queries as needed Generate Weekly Reports • Missing/expected pages • Discrepancy counts including time outstanding Perform Clinical Data Reviews Administer Central Lab Data • Define lab transfer agreement • Receive lab data • Manage lab normals • Check lab data (specify specific checks) • Contact lab to resolve data issues Receive and Manage Assay Data • Define transfer agreement • Receive data transfers • Check electronic data (specify specific checks) • Contact provider to resolve data issues Transfer Data to Sponsor Transfer Specification
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Create Site PDFs
|
Create PDFs for Sponsor FIGURE C.2 Data Management Responsibilities: EDC study. 247 Appendix D: Implementation
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Plan Outline
|
This example outline for a validation plan applies to a vendor-supplied software application. It includes elements common to most validation plans but the actual names, organization, and grouping of the various requirements would vary from company to company. This outline shows mostly high-level headings; the description of what might be included under each heading can be found in detail in Chapter 23. 1. Introduction and Scope 1.1
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Hardware
|
1.2 Options 1.3 Project Plan/Timeline 2. Assumptions and Risk Assessment 3. Business Requirements 4. Functional Specification 5. Installation/Implementation 5.1 Installation Procedure 5.2 Installation/Implementation Notes 5.3 Installation Qualification 6. Testing Overview 7. Vendor Audit Summary 8. Security Plan 9. SOPs and Guidelines 10. Completion Criteria 11. Revision History 251 Appendix F: CDISC and HIPAA New data managers and others concerned about proper data management often ask about the CDISC and HIPAA and how they impact data collection. CDISC is a standards format and HIPAA is a privacy rule. This appendix provides a very brief explanation of each as well as links for more detailed information.
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CDISC
|
CDISC stands for the Clinical Data Interchange Standards Consortium. The mission of this independent group is to develop and support global, platform-independent data standards that enable information system interoperability or interchange in medical research. Their goal is to develop standard models that still permit flex- ibility in research. The group has done most of its work in the study data tabulation model (SDTM), which is the standard for regulatory submission of case report form data tabulations from clinical trials. The Food and Drug Administration (FDA) already accepts data in SDTM and most companies are moving in this direction. There is a proposed rule being considered that will require data being submitted in electronic format conform to standardized data structures, terminology, and codes. Many sponsors also request that data sent to them from contract research organizations (CROs) or other vendors be consistent with this model. CDISC also has other standard models including an Operational Data Model (ODM) for the interchange and archive of data collected in clinical trials through a variety of sources. This would include not only the data but also the audit trail and metadata (structural and/or administrative data). The important point at this time is that the model is for writing and reading of files for interchange—it is not meant to replace standard clinical data management systems. However, electronic data cap- ture (EDC) systems could write ODM-compatible files and those files could be read into the clinical data management (CDM) system through an ODM reader utility. An initial version of a Clinical Data Acquisitions Standards Harmonization (CDASH) standard has also been released that connects to ODM. Data management groups have begun exploring these standards to see how they can facilitate building of stud- ies and transformation of the database to STDM for submission. More companies will begin to work with CDISC as more tools are available from vendors, but at this writing, it appears that it will be several years yet before the impact on data management will be clear. Data management groups would be wise to stay current with CDISC. The group has speakers that present sessions at many conferences and also has workshops on the standards. More information can be found at http://www.cdisc.org. 252 Appendix F: CDISC and HIPAA
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HIPAA
|
HIPAA is the Health Insurance Portability and Accountability Act of 1996. It is a federal law, and like 21 CFR (Code of Federal Regulations), it covers quite a range of topics. The sections that most apply to data management are those on privacy. (See 45 CFR Parts 160 and 164 for the actual rule.) The rules apply to covered entities, which are generally people (such as your private physician) or organizations (such as medical centers or research hospitals). Those entities may not transfer identifiable data to another organization without explicit permission from the patient for each transfer. Sponsors of clinical trials are able to receive datasets that identify each patient (albeit without an actual name) because the rule has provisions for research. Those provisions require the consent of the patient for the purpose of a single study. The informed consent document that patients in clinical trials sign, or a separate HIPAA waiver, serves this purpose. Data management groups that work with research institutions occasionally get calls from those sites asking that some data fields be removed from the CRF. Most often the field in question is the birth date. Some sites request that only the year be provided. Should the sponsor not be able to convince the institution that the data is permitted, the database design must handle partial birth dates. Patient initials are another kind of identifying field that may be called into question. Data managers can attend short introductions to HIPAA offered by a wide range of groups and private instructors. The National Institutes of Health (NIH) publishes use- ful material to explain the rule and its impact on clinical research. In particular, refer to its web publication “Clinical Research and the HIPAA Privacy Rule” and other useful materials found at http://privacyruleandresearch.nih.gov/clin_research.asp. 253
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Bibliography
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FDA, 21 CFR Part 11, Electronic Records; Electronic Signatures; Final Rule. Federal Register Vol. 62, No. 54, 13429, March 20, 1997. FDA, Guidance for Industry E6 Good Clinical Practice: Consolidated Guidance. FDA, Part 11, Electronic Records; Electronic Signatures—Scope and Application, 2003. FDA, General Principles of Software Validation; Guidance for Industry and FDA Staff, 2002. FDA, Guidance for Industry; Computerized Systems Used in Clinical Investigations, 2007. MedDRA MSSO 2011, MedDRA Term Selection: Points to Consider, Version 4.1. http://www. meddramsso.com/files_acrobat/ptc/9491-1400_TermSelPTC_R4_1_mar2011.pdf. Society for Clinical Data Management, Good Clinical Data Management Practices. http:// www.scdm.org/gcdmp/ (accessed July 2011). w w w . c r c p r e s s . c o m
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Prac t ical Guide to
|
CLINICAL DATA MANAGEMENT T h i r d E d i t i o n PHARMACEUTICAL TECHNOLOGY w w w. c rc p r e s s . c o m
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an informa business
|
6000 Broken Sound Parkway, NW Suite 300, Boca Raton, FL 33487 711 Third Avenue New York, NY 10017 2 Park Square, Milton Park Abingdon, Oxon OX14 4RN, UK The management of clinical data, from its collection during a trial to its extraction for analysis, has become a critical element in the steps to prepare a regulatory submission and to obtain approval to market a treatment. Groundbreaking on its initial publication nearly fourteen years ago, and evolving with the field in each iteration since then, the third edition of P actical Guide to Clinical Data Management includes important updates to all chapters to reflect the current industry approach to using electronic data capture (EDC) for most studies. See what’s new in the Third Edition: • A chapter on the clinical trial process that explains the high level flow of a clinical trial from creation of the protocol through the study lock and provides the context for the clinical data management activities that follow • Reorganized content reflects an industry trend that divides training and standard operating procedures for clinical data management into the categories of study startup, study conduct, and study closeout • Coverage of current industry and Food and Drug Administration (FDA) approaches and concerns The book provides a comprehensive overview of the tasks involved in clinical data management and the computer systems used to perform those tasks. It also details the context of regulations that guide how those systems are used and how those regulations are applied to their installation and maintenance. Keeping the coverage practical rather than academic, the author hones in on the most critical information that impacts clinical trial conduct, providing a full end-to-end overview or introduction for clinical data managers.
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AAB
|
American Association of BioAnalysts A national professional association whose members are clinical laboratory directors, owners, supervisors, managers, medical technologists, medical laboratory technicians, physician office laboratory technicians and phlebotomists. AAB is committed to the pursuit of excellence in clinical laboratory services by enhancing the professional skills of each of its members; promoting more efficient and productive operations; offering external quality control programs; collaborating with other professional associations and government agencies; promoting safe laboratory practices; and educating legislators, regulators, and the general public about clinical laboratory tests and procedures. http://www.aab.org/aab/default.asp
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AABB
|
(formerly American Association of Blood Banks), now just known as AABB International non-profit association representing individuals and institutions involved in the field of transfusion medicine and cellular therapies, specifically ones based on hematopoietic stem cells . Virtually all major blood banks in the United States are voluntarily accredited by the AABB with more than 80 percent of hospital transfusion services and similar facilities in the US being members. In 2005 the organization changed its name to AABB to reflect the changes in scope and operations. http://www.aabb.org/Pages/default.
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Chemistry
|
An international society comprised of medical professionals with an interest in clinical chemistry, clinical laboratory science, and laboratory medicine. http://www.aacc.org/Pages/default.
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AAFS
|
American Academy of Forensic Sciences A multi-disciplinary professional organization that provides leadership to advance science and its application to the legal system with the objectives to promote professionalism, integrity, competency, education, foster research, improve practice, and encourage collaboration in the forensic sciences. http://www.aafs.org/
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ABP
|
American Board of Pathology The American Board of Pathology is the certifying board for physicans seeking or maintaining a specialty certificate as a Pathologist. http://www.abpath.org/
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Affordable Care Act
|
The Patient Protection and Affordable Care Act (PPACA), also known as the federal health care law, is a 2010 US federal statute to decrease the number of uninsured Americans and reduce the overall cost of health care. https://www.healthcare.gov/law/feat ures/index.html
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ACLA
|
American Clinical Laboratory Association A not-for-profit organization created in 1971 which offers members the benefits of representation, education, information and research, in order to facilitate advocacy for laws and regulations recognizing the essential role that laboratory services play in delivering cost-effective health care; encourage the highest standards of quality, service and ethical conduct among its members; and promote public awareness about the value of laboratory services in preventing illness, diagnosing disease, and monitoring medical treatment. http://www.acla.com/
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ACLPS
|
Academy of Clinical Laboratory Physicians and Scientists An organization dedicated to the advancement of teaching and scholarship in laboratory medicine. http://www.aclps.org/
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ACO
|
Accountable Care Organization Coordinated care systems in which providers are incentivized on the basis of outcomes rather than the number of services. http://www.gpo.gov/fdsys/pkg/FR- 2011-11-02/pdf/2011-27461.pdf
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ADASP
|
Association of Directors of Anatomic and
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Surgical Pathology
|
An organization comprised of directors of anatomic and/or surgical pathology from academic institutions, that promotes expertise and education of pathologists and other healthcare professionals in the field of anatomic pathology and related disciplines. http://www.adasp.org/
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AFIP
|
Armed Forces Institute of Pathology Founded in 1862 as the Army Medical Museum in Washington, D.C., AFIPs primary purpose was to provide a second opinion diagnostic consultation on pathologic specimens such as biopsies from military, veteran, and civilian medical, dental, and veterinary sources. AFIP was closed in September, 2011. http://www.nlm.nih.gov/hmd/medto ur/afip.html
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AJCC
|
American Joint Committee on Cancer An organization that provides leadership in the development, promotion and maintenance of evidence-based systems for the classification and management of cancer. https://cancerstaging.org/Pages/def ault.aspx CAP Glossary of Clinical Informatics Terms 1 of 14
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Link
|
CAP Glossary of Clinical Informatics Terms
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Association
|
An international association of over 1,800 clinical laboratory professionals that provides support, resources and advocacy in the clinical laboratory industry to enhance the image and increase the visibility of the laboratory management profession. http://www.clma.org/
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Immunologists
|
A society of medical and scientific professionals, including veterinary and dental, enjoined to improve the practice and study of medical laboratory immunology. http://www.amli.org/
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AMP
|
Association for Molecular Pathology An organization comprised of molecular pathologists, clinical laboratorians, clinical or basic research scientists, reagent/ instrument manufacturers, bioinformaticists, teachers, mentors, students and public servants, who promote the highest quality of molecular diagnostics to improve patient care. AMP is a community that fosters and advances excellence in innovation, translational research, education, training, and clinical practice. http://www.amp.org/
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ANSI
|
American National Standards Institute A private non-profit organization that oversees the development of voluntary consensus standards for products, services, processes, systems, and personnel in the United States for consumer and environmental safety, while strenghtening the U.S. marketplace position globally by coordinating U.S. standards with international standards so that American products can be used worldwide. http://www.ansi.org/
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APHA
|
American Public Health Association A public healthcare professional organization aimed at protecting all Americans and their communities from preventable, serious health threats and ensuring that preventative health services are universally accessible
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APHL
|
Association of Public Health Laboratories A U.S. membership organization comprised of public health laboratories for the promotion of policies that support healthy communities. http://www.aphl.org/Pages/default.a
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API
|
Association for Pathology Informatics A non-profit organization whose mission is to promote the field of pathology informatics as an academic and a clinical subspecialty of pathology by supporting advances in the field of Pathology Informatics through research, education, scientific meetings, and through electronic and printed communications. http://www.amp.org/
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Reporting
|
A profile within IHE AP that provides templates for building surgical pathology reports (cancers, benign neoplasms as well as non-neoplastic conditions). http://www.ihe.net/Technical_Fram eworks/#anatomic
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Act of 2009
|
An economic stimulus package enacted by the 111th United States Congress in February 2009 and signed into law on February 17, 2009, by President Barack Obama. The ARRA created the HITECH Act for healthcare meaningful use. Also referred to referred to as the Stimulus or The Recovery Act http://en.wikipedia.org/wiki/America n_Recovery_and_Reinvestment_A ct_of_2009
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ASC
|
American Society of Cytopathology A national professional society of physicians, cytotechnologists and scientists dedicated to improving patient care in regards to the cytologic method of diagnostic pathology. http://www.cytopathology.org/ ASCLD/LAB PRC American Society of Crime Laboratory Directors/Laboratory Accreditation Board Proficiency Review Committee Proficiency Review Committees (PRC) are established for each forensic discipline accredited by ASCLD/LAB. The PRCs are tasked with reviewing the proficiency test results of accredited laboratories in the corresponding discipline. http://www.ascld-lab.org/proficiency- review-committees/
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ASCLS
|
American Society for Clinical Laboratory
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Science
|
Canada's national certifying body for medical laboratory technologists and medical laboratory assistants. http://www.csmls.org/
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ASCP
|
American Society for Clinical Pathology ASCP is a professional membership organization for pathologists and laboratory professionals, whose mission is to provide excellence in education, certification and advocacy on behalf of patients, pathologists and laboratory professionals across the globe. http://www.ascp.org/
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and Immunogenetics
|
An international non-profit association of professionals dedicated to advancing the science, education, and application of immunogenetics and transplant immunology. http://www.ashi-hla.org/
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ASIP Sante
|
French Agency of Shared Healthcare
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Information Systems
|
An agency of the French government and one of three sponsors of IHE Lab, whose mission is to strengthen public ownership of the information systems being developed in the healthcare. http://esante.gouv.fr/en 2 of 14
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ATA
|
American Telemedicine Association A non-profit organization whose goal is to promote access to medical care for consumers and health professionals via telecommunications technology. http://www.americantelemed.org/
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Bioinformatics
|
An interdisciplinary scientific field combining computer science, statistics, mathematics and engineering, for the purpose of developing methods and software tools that are used for storing, retrieving, organizing and analyzing biological data, especially as applied in molecular genetics and genomics. http://en.wikipedia.org/wiki/Bioinfor
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CAH
|
Critical Access Hospital Small, rural hospitals that are structured differently than acute care hospitals. Some of the requirements for CAH certification include having no more than 25 inpatient beds; maintaining an annual average length of stay of no more than 96 hours for acute inpatient care; offering 24-hour, 7-day-a-week emergency care; and being located in a rural area, at least 35 miles drive away from any other hospital or CAH (fewer in some circumstances). http://www.cms.gov/Outreach-and- Education/Medicare-Learning-
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CCD
|
Continuity of Care Document XML based document standard developed by the HL7 organization and specifies the encoding, structure, and semantics of a patient summary clinical document for exchange. It is a constraint on CDA and contains US specific requirements. http://en.wikipedia.org/wiki/Continuit y_of_Care_Document
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CDA
|
Clinical Document Architecture An HL7 document markup standard that specifies the structure and semantics of "clinical documents" for the purpose of exchange between healthcare providers and patients. It can contain any type of clinical content – eg, Discharge Summary, Imaging Report, Admission & Physical, Pathology Report and more. The most popular use is for inter-enterprise information exchange, such as is envisioned for a US Health Information Exchange (HIE). http://www.hl7.org/implement/stand ards/product_brief.cfm?product_id= 7
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CDC
|
Center for Disease Control and
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Prevention
|
The national public health institute of the United States that is a federal agency under the Department of Health and Human Services, headquartered in Georgia. Its main goal is to protect America from health, safety and security threats, both foreign and in the U.S., through the control and prevention of disease, injury, and disability. http://www.cdc.gov/
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Consortium
|
A multidisciplinary, neutral, non-profit standards developing organization that develops and supports global, platform-independent data standards that enable information system interoperability to improve medical research and related areas of healthcare. http://www.cdisc.org/
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Technology
|
Founded in 1901 and prior to 1989 was known as the National Bureau of Standards (NBS), NIST is one of the nation's oldest physical science laboratories, providing measurement standards in the U.S. NIST measurements support the smallest of technologies to the largest and most complex of human-made creations. http://www.nist.gov/
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CFR
|
Code of Federal Regulations The codification of the general and permanent rules published in the Federal Register by the departments and agencies of the Federal Government. It is divided into 50 titles that represent broad areas subject to Federal regulation. http://www.gpo.gov/fdsys/browse/c ollectionCfr.action?collectionCode=
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Product List
|
The authoritative, comprehensive listing of certified Complete Electronic Health Records (EHRs) and EHR modules, published by the ONC. http://www.healthit.gov/policy- researchers-implementers/certified- health-it-product-list-chpl
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CISC
|
Clinical Informatics Steering Committee CAP committee that reports to the Council on Scientific Affairs (CSA) and presides over the Informatics Committee and PERT committee. http://capnet/
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CISH
|
Chromogenic in situ hybridization A practical, cost-effective, and valid alternative to fluorescent in situ hybridization (FISH) testing for gene alteration, in that it does not need expensive fluorescence microscopy instrumentation / expertise, and the chromogenic agents used in most CISH methods are chemically stable and do not fade over time, allowing easy storage and repeated re-examination of samples. http://www.cytotest.com/cish.asp
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CLC
|
Clinical Laboratory Coalition An organization committed to ensuring access to high quality laboratory services. http://www.aab.org/NewsBot.asp?M ODE=VIEW&ID=209 3 of 14
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Amendments
|
Federal regulatory standards that apply to all clinical laboratory testing performed on humans in the United States, except clinical trials and basic research. Clinical laboratories must be certificated by their state as well as the Center for Medicare and Medicaid Services (CMS) before they can accept human samples for diagnostic testing. Laboratories can obtain multiple types of CLIA certificates, based on the kinds of diagnostic tests they conduct. http://wwwn.cdc.gov/CLIA/Default.a
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Advisory Committee
|
A diverse committee managed by the Centers for Disease Control and Prevention (CDC), that provides scientific and technical advice and guidance to the Department of Health and Human Services (HHS), pertaining to general issues related to improvement in clinical laboratory quality and laboratory medicine practice, as well as possible revision of the CLIA standards. http://wwwn.cdc.gov/CLIAC/default.
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Clinical Informatics
|
The application of information management in healthcare to promote safe, efficient, effective, personalized, and responsive care. Clinical informatics benefits individuals, institutions, populations, and communities. (from CAP Clinical Informatics Strategy, 2013) http://www.amia.org/applications- informatics/clinical-informatics
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Program
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Created by an agreement between the Department of Health and Human Services and the Department of Defense (DOD), the DOD Clinical Laboratory Improvement Program (CLIP) authorized the Assistant Secretary of Defense for Health Affairs to develop CLIA'88-comparable regulations for governing DOD laboratories. In implementing the DOD program, the CLIA'88 regulations were adopted to the maximum extent possible and modified only as required to meet those unique DOD missions that precluded
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"clinical-informatics-acronym-glossary.pdf"
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CLSI
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Clinical and Laboratory Standards Institute (formerly NCCLS) A volunteer-driven, membership-supported, not-for-profit, standards development organizationthat promotes the development and use of voluntary laboratory consensus standards and guidelines within the health care community. http://clsi.org/
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"clinical-informatics-acronym-glossary.pdf"
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CMS
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Centers for Medicare and Medicaid Services (formerly HCFA) A federal agency within the United States Department of Health and Human Services (DHHS) that administers the Medicare program and works in partnership with state governments to administer Medicaid, the State Children's Health Insurance Program (SCHIP), and health insurance portability standards. Additionally, CMS administers standards from the Health Insurance Portability and Accountability Act of 1996 (HIPAA), ensures quality in long-term care facilities by survey and certification processes, oversees clinical laboratory quality standards under CLIA, and maintains HealthCare.gov. http://cms.hhs.gov/
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COLA
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Commission on Laboratory Accreditation Formerly known as the Commission on Office Laboratory Accreditation, COLA is a clinical laboratory education, consultation, and accreditation organization. http://www.cola.org/ 4 of 14
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"clinical-informatics-acronym-glossary.pdf"
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Change Proposal
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Method employed by IHE by which stable, published technical documents can be proposed to be modified by knoweldgeable suggestion by users, vendors or Technical Committee members. These proposals are reviewed by the Technical Committee on a regular bases and then either approved or rejected. http://wiki.ihe.net/index.php?title=C ategory:CPs
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"clinical-informatics-acronym-glossary.pdf"
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CPOE
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Computerized Physician Order Entry (Computerized Provider Order Entry) The electronic entry of medical practitioner instructions for the treatment of patients which are communicated over a computer network to the medical staff or to the departments (pharmacy, laboratory, or radiology) responsible for fulfilling the order. CPOE has many benefits including reducing delays in order completion, reduceing transcription errors, and provideing error-checking for duplicate or incorrect doses or tests. http://searchhealthit.techtarget.com /definition/computerized-physician-
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CQM
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Clinical Quality Measure Tools that utilize date in order to measure and track the quality of health care services provided by eligible professionals, eligible hospitals and critical access hospitals, such as treatment, experience, and patient outcomes. CQMs are required as part of meaningful use requirements for the Medicare and Medicaid Electronic Health Record (EHR) Incentive Programs. http://www.cms.gov/Regulations-
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"clinical-informatics-acronym-glossary.pdf"
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CRC
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Chemistry Resource Committee A CAP committee working to improve patient care by promoting the overall quality of laboratory results, evaluating emerging trends, and advising the Laboratory Accreditation Program on issues related to clinical chemistry. http://www.cap.org/apps//cap.portal ?_nfpb=true&cntvwrPtlt_actionOver ride=%2Fportlets%2FcontentViewe r%2Fshow&_windowLabel=cntvwrP tlt&cntvwrPtlt%7BactionForm.conte ntReference%7D=committees%2F chemistry_description.html&_state= maximized&_pageLabel=cntvwr
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CSMLS
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Canadian Society for Medical Laboratory
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"clinical-informatics-acronym-glossary.pdf"
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DICOM
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Digital Imaging and Communications in
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Medicine
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A special interest group of IHTSDO focused on Pathology and Laboratory Medicine as it relates to SNOMED CT. http://www.ihtsdo.org/search/
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DIHIT
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Diagnostic Intelligence and Health Information Technology See Informatics Committee (ICE) www.cap.org
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Direct Project
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The Direct Project specifies a simple, secure, scalable, and standards-based way for participants to send authenticated, encrypted health information directly to known, trusted recipients over the Internet. http://wiki.directproject.org/
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"clinical-informatics-acronym-glossary.pdf"
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DPA
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Digital Pathology Association A not-for-profit organization comprised of pathologists, scientists, technologists and industry representatives that are focused on facilitating education and awareness of digital pathology applications in healthcare and life sciences. https://digitalpathologyassociation.o rg/
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