Anesthesia Information Management Systems

Anesthesia Information Management Systems

Toward Standardization of Terminology in Anesthesia Information Management Systems

Terri G. Monk, M.D.
Chairperson, Data Dictionary Task Force
International Organization for Terminology in Anesthesia
Anesthesia Patient Safety Foundation
Professor
Department of Anesthesiology
Duke University Hospital
Durham, NC

Martin Hurrell, Ph.D
Technical Director, Data Dictionary Task Force.
International Organization for Terminology in Anesthesia
Anesthesia Patient Safety Foundation
Chief Executive Officer
Informatics Clinical Information Systems Ltd.
Glasgow, Scotland, UK

Andrew Norton, MD
Content Director, Data Dictionary Task Force
International Organization for Terminology in Anesthesia
Consultant Anaesthetist
Pilgrim Hospital, Lincolnshire

Supported by the Anesthesia Patient Safety Foundation

Contact author information:

Terri Monk, M.D.
Department of Anesthesiology
Box 3094 DUMC
Duke University Medical Center
Durham, NC 27710
Email: Terri.Monk@duke.edu
Cell: (919)-636-0354

One of the first attempts to create a national database for anesthesia outcomes occurred in the late 1990s. The National Center for Clinical Outcomes Research (NCCOR) was organized for the purpose of developing a data warehouse to which participants would send their perioperative records. In return, NCCOR would deliver comparative derivatives of their data. This effort failed for a variety of reasons. One of the major obstacles to its success was the lack of a standardized medical terminology. Even if participating hospitals had an AIMS system, they faced the daunting task of reformatting and normalizing their data into a standard data file for submission. In addition, the lack of a standard data dictionary for anesthesiology meant that participating hospitals could not be sure that their data collection was comparable with that of other hospitals collecting data with different terms and semantic meanings.

Since 1984, the Anesthesia Patient Safety Foundation (APSF) has been an advocate for outcomes research in the specialty and has recognized the need for aggregate databases in outcomes research. The Institute of Medicine Report To Err is Human: Building a Safer Health System recognized that several groups in the United States were already working on methods to improve patient safety and named the Anesthesia Patient Safety Foundation (APSF) as a leader in this field.1 In 2001, the APSF endorsed the use of anesthesia information management systems (AIMS) as a means of collecting data for this purpose. AIMS are installed in less that 5% of US hospitals, yet the value of these systems is apparent in terms of legibility and accessibility of the patient's medical record as well as for research and practice analysis. According to the Institutes of Medicine report Crossing the Quality Chasm, "automated clinical and administrative data enable many types of health service research applications, such as assessment of clinical outcomes associated with alternative treatment options and care processes; identification of best practices; and evaluation of the effects of different methods of financing, organizing, and delivering services."2

One of the most significant barriers to adoption of information systems is the complexity and length of the product installation process. The installation of an AIMS system often includes the development of a customized set of terms and phrases to be created specific to each institution. There are few guidelines available and minimal standardization of the terms used. Complete product installations in excess of one year are not uncommon; this situation is unduly burdensome to vendor and customer alike. The result is a delay or barrier to the adoption of technology that at the least solves the problem of legibility and accessibility of the anesthesia record and necessary for meaningful outcomes research.

This lack of standardization for terms in AIMS inhibits the sharing of data between information systems from the same vendor, let alone across institutions with different vendor systems. This data interoperability issue did not arise with the advent of automated systems. It exists for paper-based anesthesia records and continues to stifle comparative research in the specialty. Attempts have been made to standardize subsets of terms pertinent to the specialty, such as the American Association of Clinical Director's (AACD) "Glossary of Times Used for Scheduling and Monitoring of Diagnostic and Therapeutic Procedures". However, these lexicons have not been widely adopted and, to date, no group has attempted a more complete terminology for the specialty.

The APSF approached the problem of developing meaningful outcomes research from a new perspective. This organization recognized that the primary problem preventing meaningful outcomes research was the lack of a standard anesthesia terminology. In 2001, the APSF executive committee commissioned the Data Dictionary Task Force to create a standardized terminology for AIMS. Dr. Terri Monk of the University of Florida was appointed chairperson and given the responsibility of organizing this task force and recruiting individuals in academic medicine, private practice, and industry to serve on this committee. She named Dr. Iain Sanderson of Duke University Medical Center as Technical Director for the DDTF. The original mission of this task force was to:

1. Establish a data dictionary for the collection of perioperative information
2. Identify the specific perioperative outcomes to be investigated.

Existing standard terminology were to be used wherever possible. A deliverable of this process would be a set of anesthesia terms that could be pre-loaded into an AIMS system during an initial installation, providing a considerable service to the vendors of these systems and institutions investing in them. This baseline set of terms would not preclude customization, but could reduce the need or desire for it.

In 2002, the DDTF learned of considerable expertise and experience in creating anesthesia terminologies in the United Kingdom (UK). Our anesthesia colleagues in the National Health Service (NHS) in the UK had been working independently on an anaesthesia terminology under the auspices of the Society for Computing and Technology in Anaesthesia (SCATA) for over 10 years. Members of SCATA were submitting their anesthesia terms to UK's Clinical Terms Version 3 initiative (CTV3), an extension of the well-respected Read Codes. In 2003, the DDTF joined forces with members of SCATA in the UK and evolved into the International Organization for Terminology in Anesthesia (IOTA) with the mission to create a standardized terminology for the global anesthesia community. IOTA also contains members from the Canadian Anesthesiologists Society and the Society for Technology in Anesthesia. The American Society of Anesthesiologists (ASA) has also appointed members of the Committee on Performance and Outcomes Measurement (CPOM) to represent them at all meetings and to lead the effort to establish meaningful outcomes research questions for the specialty of anesthesia. The Content Director for the DDTF/IOTA is Dr. Andrew Norton and the Technical Director is Dr. Martin Hurrell. Both of these individuals are members of SCATA and have been involved with terminology work in the UK for over a decade.

Concurrently, the DDTF became aware that the US government was considering the adoption of a major medical terminology called SNOMED (Systematized NOmenclature of MEDicine). SNOMED was originally developed by the College of American Pathologists (CAP). SNOMED International is a non-profit organization that oversees the strategic direction and scientific maintenance of SNOMED. Their goal is to develop a complete dictionary of medical terms. The latest SNOMED product, SNOMED CT, incorporates the CTV3 terms from the National Health Service (NHS) and is now licensed to be used throughout the NHS in the UK. SNOMED is extensively mapped to other lexicons, such as the ICD9-CM diagnosis coding system. In July 2003, the National Library for Medicine purchased a national license for SNOMED CT in the US, making it free for all US medical entities. In September 2003, the DDTF was formally adopted by SNOMED as an official extension group that would establish the terminology for anesthesia in the US and UK. The work of IOTA is now creating the "Anesthesia Subset" of terms for SNOMED CT.

The development of a standardized anesthesia terminology will greatly facilitate outcomes research in the future. However, we now recognized that future AIMS systems will need more than just a terminology to enable outcomes research and artificial intelligence applications for reasoning and decision support. The next generation of AIMS systems will need a schema to define the structure for well-formed anesthesia XML documents and a common model or ontology to develop an anesthesia-specific vocabulary. An ontology defines the terms used to describe and represent an area of knowledge. Ontologies are used by people, databases, and applications that need to share subject-specific (domain) information - like medicine, tool manufacturing, real estate, automobile repair, financial management, etc. Ontologies include computer-usable definitions of basic concepts in the domain and the relationships among them. They encode knowledge in a domain and also knowledge that spans domains. In this way, they make that knowledge reusable."

IOTA has chosen to develop the anesthesia ontology using Protg with the OWL plugin. (A 'clinician friendly' front end for the Protg-OWL plugin has been created for IOTA by the Information Management Group in the Computer Science Department at the University of Manchester, UK.). In February, 2004 the Web Ontology Language (OWL) was approved as a key standard to underpin the future development of the Semantic Web by the World Wide Web Consortium (W3C - http://www.w3.org). IOTA uses OWL DL (Description Logic) which allows the use of DIG compliant reasoners such as Racer to validate the ontology and also to support computer-based decision support.

Thus the IOTA project embraces three activities:

1. Ontology development
2. Schema definition (consistent with the HL7 Clinical Statement initiative)
3. Terminology development

Together these aim to deliver an international standard for the communication and understanding of anesthesia information which will enable a new era in research and clinical audit.

References:

1. Committee on Quality of Health Care in America, Institute of Medicine. To Err Is Human: Building a Safer Health System. Washington DC: National Academy Press; 1999.
2. Committee on Quality of Health Care in America, Institute of Medicine. Crossing the Quality Chasm. Washington DC: National Academy Press; 2001.