Biomedical subjects

Sookyung Hyun

Publications and source records attributed to Sookyung Hyun.

9 recordsLinked to original sources

PubMed2006

Is the Health Level 7/LOINC document ontology adequate for representing nursing documents?

The use of nursing documents from different electronic health record (EHR) systems is challenging due to inconsistency in document naming across systems and institutions. Mapping each local document name to standard document ontology may enable health care professionals to navigate and retrieve documents efficiently for multiple purposes such as quality assurance, outcomes research or public health reporting. The purpose of this study was to evaluate the sufficiency of the Health Level 7 (HL7)/Logical Observation Identifiers, Names, and Codes (LOINC) document ontology for representing nursing document names. We collected 94 nursing document types from the Eclipsys Clinical Information System (CIS) and the Columbia Medical Entities Dictionary (MED) and mapped them to the components of the HL7/LOINC document ontology. Seventy-five (79.8%) nursing document names were completely represented and 19 (20.2%) document names were partially represented. In order for the HL7/LOINC document ontology to be of more use in implementing EHRs that support nursing documentation, Subject Matter Domain and Type of Service axes require extension and clarification.

Humans↗

PubMed2006

Usefulness of a personal digital assistant-based advanced practice nursing student clinical log: Faculty stakeholder exemplars.

The number of health sciences educational programs that are integrating personal digital assistants (PDAs) into their curricula is on the rise. In this paper, we report an evaluation of the usefulness of a PDA-based advanced practice nursing (APN) student clinical log through faculty stakeholder exemplars in three areas: pediatric asthma care; procedures of Acute Care Nurse Practitioner (NP) students; and diagnostic and screening procedures of Women's Health NP students. We generated descriptive data through routine queries and through custom SQL queries at the request of a specific faculty member who wished to examine a particular aspect of an educational program. In addition, we discussed the potential implications of the data with the respective faculty members. The exemplars provide evidence that faculty stakeholders found the APN student clinical log to be useful for a variety of purposes including monitoring of student performance, benchmarking, and quality of care assessments.

Computers, Handheld↗

PubMed2006

Markup of temporal information in electronic health records.

Temporal information plays a critical role in the understanding of clinical narrative (i.e., free text). We developed a representation for marking up temporal information in a narrative, consisting of five elements: 1) reference point, 2) direction, 3) number, 4) time unit, and 5) pattern. We identified 254 temporal expressions from 50 discharge summaries and represented them using our scheme. The overall inter-rater reliability among raters applying the representation model was 75 percent agreement. The model can contribute to temporal reasoning in computer systems for decision support, data mining, and process and outcomes analyses by providing structured temporal information.

Hospitals, Religious↗

PubMed2005

ISO reference terminology models for nursing: applicability for natural language processing of nursing narratives.

Natural language processing (NLP) systems have demonstrated utility in parsing narrative texts for purposes such as surveillance and decision support. However, there has been little work related to NLP of nursing narratives. The purpose of this study was to compare the semantic categories of a NLP system (Medical Language Extraction and Encoding [MedLEE] system) with the semantic domains, categories, and attributes of the International Standards Organization (ISO) reference terminology models for nursing diagnoses and nursing actions. All but two MedLEE diagnosis and procedure-related semantic categories mapped to ISO models. In some instances, we found exact correspondence between the semantic structures of MedLEE and the ISO models. In other situations (e.g. aspects of Site or Location), the ISO model was not as granular as MedLEE. For clinical procedure and non-invasive examination, two ISO nursing action model components (Action and Target) mapped to a single MedLEE semantic category. The ISO models are applicable to NLP of nursing narratives. However, the ISO models require additional specification of selected semantic categories for the abstract semantic domains in order to achieve the objective of using NLP to parse and encode data from nursing narratives. Our analysis also suggests areas for extension of MedLEE particularly in regard to represent nursing actions.

Diagnosis, Computer-Assisted↗

PubMed2005

Document ontology: supporting narrative documents in electronic health records.

Electronic health records (EHRs) are beginning to manage an increasing volume of narrative data, such as clinical notes pertaining to admission, patient progress, shift change, follow-up, consultation, procedures, etc. These documents fall into a wide variety of classes, based on who is writing them, for what purpose, and in which location, suggesting the need for a document ontology (DO) to model our knowledge of health care documents and their properties. This paper focuses on one aspect of the Health Level 7 (HL7)/ Logical Observation Identifiers, Names, and Codes (LOINC) DO, the Subject Matter Domain (SMD). We created a new polyhierarchical structure for the SMD that combines the current value lists from the LOINC database with another value list from the American Board of Medical Specialties (ABMS). We refined and evaluated the new structure through expert review of the ontology, a survey of medical specialty boards, and specification of SMDs for a corpus of clinical notes.

Attitude of Health Personnel↗

PubMed2004

MobileNurse: hand-held information system for point of nursing care.

Healthcare information travels with patients and clinicians and therefore the need for information to be ubiquitously available is key to reliable patient care and reliable medical systems. We have implemented MobileNurse, a prototype point-of-care system using PDA. MobileNurse has four modules each of which performs: (1) patient information management; (2) medical order check; (3) nursing recording; and (4) nursing care plan. MobileNurse provides easy input interface and various outputs for nursing records. The system consists of PDAs and a mobile support system (MSS) which supports clinical data exchange between PDAs and hospital information system. Two synchronization modules have been developed to keep the patient data consistent between PDAs and MSS. Clinical trials were performed with six volunteered nurses. They tried MobileNurse for 1-day caring-simulated patients. According to the survey after the trials, most of volunteers agreed that MobileNurse is more helpful and convenient than other non-mobile care systems to check medical orders and retrieve the results of recent clinical tests at the bedside. Through the involvement, we found out that ease-to-use interface is the most critical successful factor for mobile patient care systems.

Computer Systems↗

PubMed2004

Promoting patient safety through informatics-based nursing education.

The Institute of Medicine (IOM) Committee on Quality of Health Care in America identified the critical role of information technology in designing safe and effective health care. In addition to technical aspects such as regional or national health information infrastructures, to achieve this goal, healthcare professionals must receive the requisite training during basic and advanced educational programs. In this article, we describe a two-pronged strategy to promote patient safety through an informatics-based approach to nursing education at the Columbia University School of Nursing: (1) use of a personal digital assistant (PDA) to document clinical encounters and to retrieve patient safety-related information at the point of care, and (2) enhancement of informatics competencies of students and faculty. These approaches may be useful to others wishing to promote patient safety through using informatics methods and technologies in healthcare curricula.

Curriculum↗

PubMed2004

A comparison of semantic categories of the ISO reference terminology models for nursing and the MedLEE natural language processing system.

Natural language processing (NLP) systems have demonstrated utility in parsing narrative texts for purposes such as surveillance and decision support. However, there has been little work related to NLP of nursing narratives. The purpose of this study was to compare the semantic categories of a NLP system (Medical Language Extraction and Encoding [MedLEE] system) with the semantic domains, categories, and attributes of the International Standards Organization(ISO) reference terminology models for nursing diagnoses and nursing actions. All but two MedLEE diagnosis and procedure-related semantic categories mapped to ISO models. In some instances, we found exact correspondence between the semantic structures of MedLEE and the ISO models. In other situations (e.g. aspects of site or location), the ISO model was not as granular as MedLEE. For clinical procedure and non-invasive examination, two ISO nursing action model components (action and target) were required to represent the MedLEE semantic category. The ISO model requires additional specification of selected semantic categories for the abstract semantic domains in order to achieve the objective of using NLP to parse and encode data from nursing narratives. Our analysis also suggests areas for extension of MedLEE.

Natural Language Processing↗

PubMed2003

Natural language processing challenges in HIV/AIDS clinic notes.

In recent years, significant progress has been achieved toward increased structured data entry using standardized health care terminologies. Concurrently, the value of narrative as the clinician's rich description of the encounter and source of vital information has been reaffirmed. Natural language processing (NLP) offers a strategy for integrating these approaches to provide structured reports for further computer processing. As part of a larger project aimed at using narrative data to enrich the online medical record, we analyzed a small sample of documents in a corpus of progress notes to identify potential challenges associated with using NLP for HIV/AIDS clinic notes. We provide illustrative examples of five types of challenges.

Acquired Immunodeficiency Syndrome↗