Coverage of patient safety terms in the UMLS metathesaurus.

Coverage of patient safety terms in the UMLS Metathesaurus Aziz A. Boxwala, MBBS, PhD1,2, Qing T. Zeng, PhD2 , Anthony Chamberas, MS1 , Luke Sato, MD1 , Meghan Dierks, MD3,4 1 Risk Management Foundation of the Harvard Medical Institutions, Cambridge, MA 2 Decision Systems Group, Brigham & Women’s Hospital, Harvard Medical School, Boston, MA 3 Center for Clinical Computing, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 4 Clinical Decision Making Group, MIT, Cambridge, MA The integration and large-scale analyses of medical error databases would be greatly facilitated by the use of a standard terminology. We investigated the availability in the UMLS metathesaurus of concepts that are required for coding patient safety data. Terms from three proprietary patient safety terminologies were mapped to the concepts in UMLS by an automated mapping program developed by us. From these candidate mappings, the concept that matched its corresponding term was selected manually. The reliability of the mapping procedure was verified by manually searching for terms in the UMLS Knowledge Source Server. Matching concepts in UMLS were identified for less than 27% of the terms in the study dataset. The matching rates of terms that describe the type of error and the causes of errors were even lower. The lack of such terms in the existing standard terminologies underscores the need for development of a standard patient safety terminology. INTRODUCTION According to a report published by the Institute of Medicine in 1999, more than one million preventable adverse events occur nationwide resulting in tens of thousands of deaths each year [1]. In order to better understand the frequency, types, and causes of medical errors that occur during the management of patients, healthcare institutions have deployed systems for reporting incidents [2, 3]. These systems enable staff to report incidents that caused or had the potential to cause harm to the patient. Other types of reports such as those from formal investigations of incidents [4] and malpractice claims [5] provide further information on the nature of medical errors. To avoid bias and assure the most faithful variable selection, data should be aggregated and analyzed from as many different medical disciplines and institutions as possible. To achieve this, researchers and policymakers have advocated the creation of statewide or nationwide databases of error and near miss reports [6]. A common terminology, which is required for encoding the reports in a shared, large-scale database, does not exist. Preliminary reports indicate that existing controlled clinical terminologies such as SNOMED, ICD-9 CM, or CPT [7-9] do not contain terms relat- ing to medical errors and their attributes [10]. Developers of incident reporting systems have created proprietary and application-specific terminologies for use in their systems, but there is tremendous heterogeneity across these sources, and a common refe rence model does not exist. As an initial step in developing a standard reference model for patient safety terminology, we performed a comprehensive audit of standard clinical terminologies contained within the Unified Medical Language System (UMLS) metathesaurus to determine the extent to which existing terms for patient safety applications (incident reporting systems, insurance industry risk codes, etc.) are covered. We selected three representative patient-safety-related terminologies, and mapped terms to concepts in the UMLS metathesaurus [11]. The mapping was performed using a software tool that generated candidate concepts that matched a term. An Informatician selected the correct concept for a term from the candidate concepts. METHODS AND MATERIALS Terminologies used For this study, we analyzed three different patient safety terminologies that were among the most comprehensive and representative of the patient safety issues. The sources and their general attributes are summarized in Table 1. DoctorQuality Inc.’s Risk Prevention and Management System (RPM) uses a broad but proprietary terminology for encoding incident reports from a variety of clinical do mains. The Risk Management Foundation (RMF), a malpractice insurer, has developed and uses a proprietary terminology for encoding medico-legal claims data. The NCC-MERP taxonomy is used for coding medication-related errors [12] and is representative of terminologies for a specific application domains. Terms in the latter group of terminologies are fine-gra ined and narrowly focused on their respective domains. All three terminologies organize terms into categories, and terms within a category are represented largely in is-a hierarchies. The terminologies have not been developed using formal knowledge representation approaches, however, so there is some inconsistency in the relationships between major and minor terms within a category. AMIA 2003 Symposium Proceedings − Page 110 Table 1. A partial listing of patient-safety-related terminologies with categories, sample terms, and the number of terms from the category used in the study dataset Selected categories Sample terms No. of terms NCC-MERP’s Taxonomy of Medication Errors 273 Setting Adult day health care 56 Product (Drug) information Tablet 20 Personnel involved Licensed Practical Nurse 23 Type (of error) Dose omission 29 Causes Written miscommunication 98 Contributing factors Lack of availability of health care professional 21 DoctorQuality Inc.’s Risk Prevention and Management System’s Terminology 518 Adverse clinical event Fall 213 Administrative incident Chart unavailable 100 Contributing factors Distractions in the environment 61 Level of impact Near death event 10 Medication type Antidepressant 54 Roles Respiratory therapist 37 Risk Management Foundation’s Malpractice Claims Codes 471 Allegations Inappropriate transfer 91 Location Radiation therapy 64 Services Radiology 61 Employee Chiropractor 53 Risk management issues Lack of any consent 149 For the purpose of this study, we considered the conterm hierarchy below, the term Community is in tent of the three terminologies (two broad and one tended to mean community pharmacy. domain-specific) as sufficient and representative. 24.13 Pharmacy Inspection of other broad terminologies indicated 24.13.1 Community significant overlap with the selected terminologies All terms in the dataset were inspected; for 244 (RMF and RPM). We chose the NCC-MERP taxo nterms, a composite term was constructed by concateomy as representative of domain-specific terminolnating a term with its ancestor terms in order to conogies. Inclusion of other domain-specific terminolvey its full meaning. For example, the composite ogies (e.g., MERS-TM [2] for transfusion-related term for the example above is Community Pharmacy. incidents) would have added more domain-specific Finally, related term categories were consolidated terms to the dataset but we believed would be into a smaller number of (...truncated)