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Suzanne Bakken

Publications and source records attributed to Suzanne Bakken.

At least 55 records · Page 3Linked to original sources

Practical considerations for exploiting the World Wide Web to create infobuttons.

BACKGROUND: We are studying ways to provide automated, context-specific links (called "infobuttons") between clinical information systems (CIS) and other information resources available on the World Wide Web. As part of this work, we observed the information needs that arose when clinicians used a CIS and we classified those needs into generic questions. We then sought general methods for accessing information resources to answer the questions. METHODS: For each generic question, we identified a satisfactory resource and then developed a method for retrieving from it the information relevant to the question. We then studied these methods to characterize them into general approaches. RESULTS: We identified six general approaches and describe them in detail. These approaches range in complexity from simple, hard-coded links to intelligent agents and calculators. CONCLUSION: Web-based information resources can be exploited using a relatively small number of methods, although the specific methods require custom solutions. Standard methods for accessing Web-based resources would simplify the task of linking to CISs.

Decision Support Systems, Clinical↗

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↗

Representing public health nursing intervention concepts with HHCC and NIC.

PURPOSE: It is imperative that public health nurses define their services and provide evidence supporting the effectiveness of interventions. The purpose of this paper is to examine the ex-tent to which two standardized nursing terminologies--Home Health Care Classification (HHCC) and Nursing Interventions Classification (NIC)--represent public health nursing practice according to core public health function in Public Health Nursing Intervention model. METHODS: First, we divided all HHCC and NIC interventions into intervention focus levels: individual/family-focused, community-focused, and system-focused. Second, we categorized HHCC and NIC interventions according to core public health functions: assessment, policy development, and assurance and the categories of interventions in the PHI Model. RESULTS: We identified HHCC and NIC Nursing interventions that represented public health nursing concepts across core public health functions and categories of the PHI model. Analysis of the findings demonstrated that HHCC and NIC have terms for the concepts in the PHI model. CONCLUSION: Although HHCC and NIC cover many concepts in public health nursing practice, additional research is needed to extend these terminologies and to evaluate other standardized terminologies that can reflect more comprehensively public health nursing interventions.

Home Care Services↗

Requirements of tools and techniques to support the entry of structured nursing data.

The benefits of structured data are widely accepted within the nursing informatics community. However, despite the existence of structured data in the form of well-established nursing terminologies, computer-based nursing record systems are yet to achieve widespread adoption and few of the potential benefits have yet to be realized. In this paper we argue the need for tools and techniques to support the entry of structured nursing data into computer-based systems. In the absence of a generally accepted solution, we build on preliminary work carried out at the 2002 Nursing Terminology Summit and analyze the results of other studies in order to identify a preliminary set of requirements or desiderata for such tools and techniques. These requirements are centered on: how structured data is presented to users for selection; how to mediate between a variety of conceptual structures--terminologies, information models, user interface models and models of the clinical process; and how to reduce the considerable modeling burden through reuse of modeling constructs. Further applied research is needed with the ultimate goal of developing a general solution that will benefit nurses, other professionals and ultimately their patients.

Data Collection↗

Development and representation of a fall-injury risk assessment instrument in a clinical information system.

The potential for informatics solutions to address inpatient safety issues is significant; however, several challenges are associated with the development of patient safety related informatics applications. These challenges include: 1) the identification and/or development of valid and reliable instruments; 2) adequate representation of key safety concepts, constructs, and associated concepts in the clinical information system; and 3) identification of data sources for instrument pre-population. As part of a larger project aimed at identifying and addressing the information needs of clinicians while using a clinical information system, an electronic fall and injury risk assessment instrument is in development to address a hospital-based fall and injury prevention initiative. The concepts contained in the instrument are well represented by Clinical LOINC and the UMLS. Associated concepts have been identified in the existing clinical information system data dictionary for pre-population of the instrument.

Accidental Falls↗

National and regional health information infrastructures: making use of information technology to promote access to evidence.

The vision for national and regional health information infrastructures (HII) includes provision of a framework that is supportive of access and integration of health information with the goal of improving the health and safety of individuals, public health systems, and nations. Internationally, prominent examples of national and regional HIIs exist that provide a means for achievement of this goal. However, to fully realize benefits, an explicit mechanism is needed for linking national and regional HIIs with existing knowledge, automated processes and evaluation of the ability of HIIs to meet the information needs of primary recipients. Using the United States' Na-tion Health Information Infrastructure (NHII) as an example, the authors describe expansion of the conceptual framework to explicitly acknowledge the role of access to evidence at the overlap between the three dimensions of the NHII to create an "evidence-based" link between interrelated components. The role of national measures in setting e-communication goals and evaluating the evolving infrastructure in meeting informational needs of users is discussed. Additionally, automated knowledge management tools such as practice guidelines are presented as a means by which access to critical information is delivered to users, in a format that is appropriate for their health literacy level and that provides adequate support for informed decision making.

Decision Support Techniques↗

Patient Education and Recovery Learning System (PEARLS) pathway: a tool to drive patient centered evidence-based practice.

Myocardial infarction is a significant problem for Americans and individuals in developed countries. According to the American Heart Association, coronary heart disease is the single largest killer of Americans. Variation in practice is recognized as a key barrier to promoting positive outcomes in patients with cardiac illness. Implementation of clinical practice guidelines has been identified as one way to promote evidence-based practice, reduce practice variation, and ultimately improve the quality of care and outcomes of cardiac patients. Improving patient knowledge and understanding of guideline recommendations and the ways in which evidence-based recommendations are linked to recovery is recognized as one means of facilitating guideline adherence. Automated patient pathways are proposed as a means to improve patient access to guideline-based information at the point of care. Within this context, the prototype development of a Patient Education And Recovery Learning System, or PEARLS, is discussed along with the potential benefits of the use of automated patient pathways as one means for overcoming challenges associated with acute care patient education and facilitating patient adherence to clinical practice guideline recommendations.

Evidence-Based Medicine↗

Integrating nursing diagnostic concepts into the medical entities dictionary using the ISO Reference Terminology Model for Nursing Diagnosis.

OBJECTIVE: The purposes of the study were (1) to evaluate the usefulness of the International Standards Organization (ISO) Reference Terminology Model for Nursing Diagnoses as a terminology model for defining nursing diagnostic concepts in the Medical Entities Dictionary (MED) and (2) to create the additional hierarchical structures required for integration of nursing diagnostic concepts into the MED. DESIGN AND MEASUREMENTS: The authors dissected nursing diagnostic terms from two source terminologies (Home Health Care Classification and the Omaha System) into the semantic categories of the ISO model. Consistent with the ISO model, they selected Focus and Judgment as required semantic categories for creating intensional definitions of nursing diagnostic concepts in the MED. Because the MED does not include Focus and Judgment hierarchies, the authors developed them to define the nursing diagnostic concepts. RESULTS: The ISO model was sufficient for dissecting the source terminologies into atomic terms. The authors identified 162 unique focus concepts from the 266 nursing diagnosis terms for inclusion in the Focus hierarchy. For the Judgment hierarchy, the authors precoordinated Judgment and Potentiality instead of using Potentiality as a qualifier of Judgment as in the ISO model. Impairment and Alteration were the most frequently occurring judgments. CONCLUSIONS: Nursing care represents a large proportion of health care activities; thus, it is vital that terms used by nurses are integrated into concept-oriented terminologies that provide broad coverage for the domain of health care. This study supports the utility of the ISO Reference Terminology Model for Nursing Diagnoses as a facilitator for the integration process.

Dictionaries, Medical as Topic↗

The classification of clinicians' information needs while using a clinical information system.

INTRODUCTION: Information needs are prevalent in clinical practice. They represent a potential source of medical errors. This study seeks to empirically determine the information needs of clinicians while using a clinical information system (CIS), and characterize those needs. In addition this paper will provide the framework necessary for the development of the solutions to these information needs. METHODS: Clinicians were observed while using a CIS. They were recorded on audiotape and the computer screen recorded on videotape. The types of question during these interactions were recorded. A classification of the questions provided the conceptual and architectural basis for the development of context-sensitive links to information resources, called infobuttons. RESULTS: There were 154 information needs. The questions were grouped into seven categories. Within these categories we were able to identify eleven specific repeated question patterns, accounting for 72 or 47% of users' questions. DISCUSSION: These findings are applicable to a number of settings and can be generalized to other institutions. The proposed infobuttons based on six categories, will be navigational ('how-to.' links), cross-reference ('what is the em leader ' links), domain knowledge buttons in the areas of laboratory, pharmacy, diagnosis, and definitions/general information. Using these groups we were able to identity eleven patterns of questions.

Clinical Medicine↗

Informatics competencies pre-and post-implementation of a Palm-based student clinical log and informatics for evidence-based practice curriculum.

The purpose of this paper is to describe the implementation and evaluation of a two-part approach to achieving informatics competencies: 1) Palm-based student clinical log for documentation of patient encounters; and 2) informatics for evidence-based practice curriculum. Using a repeated-measures, non-equivalent control group design, self-reported informatics competencies were rated using a survey instrument based upon published informatics competencies for beginning nurses. For the class of 2002, scores increased significantly in all competencies from admission to graduation. Using a minimum score of 3 on a scale of 1=not competent and 5=expert to indicate competence, the only area in which it was not achieved was Computer Skills: Education. For 2001 graduates, Computer Skills: Decision Support was also below 3. There were no significant differences in competency scores between 2001 and 2002 graduates. Computer Skills: Decision Support neared significance. Subsequently, the approaches were refined for implementation in the class of 2003.

Computer Literacy↗

Use of online resources while using a clinical information system.

BACKGROUND: Clinical information system (CIS) use is likely to evoke information needs, yet information resources use during CIS use has not been studied. METHODS: We used CIS log files and a survey to characterize clinicians' use of resources and infobuttons (context-sensitive links from a CIS to specific resources) while using a CIS. RESULTS: We examined 38,763 uses of resources and infobuttons by 2,607 users to identify specific sources and contexts (CIS functions) in which they used them. Laboratory results review was the most frequent context and Micromedex was the most popular resource. Differences in resource use were related to context and user type. The survey confirmed that resources and infobuttons were perceived as useful for patient-specific questions while using a CIS. CONCLUSIONS: Understanding context- and user-type-specific information needs can guide the development of infobuttons for use in a CIS.

Clinical Laboratory Techniques↗

Clinical information needs in context: an observational study of clinicians while using a clinical information system.

INTRODUCTION: The development of tools to meet the information needs of clinicians requires an understanding of the clinician and the context in which clinical decisions are being made. METHODS: We conducted an observational study of clinicians' information needs via think-aloud protocols during which we observed physicians and nurses as they used the clinical information system. Protocol analysis was then used to identify the information needs events, the types of questions that were asked, the method of meeting that need, the success or failure of meeting the specific information need, and the context in which it arose. RESULTS: Results indicated that a) unmet information needs occur frequently and that b) the predominant feature of these unmet needs is that they are patient-related or domain-specific. Two categories of context: laboratory and medical communication accounted for more than half of the events.

Hospital Information Systems↗

Characterizing information needs and cognitive processes during CIS use.

Medical errors are often associated with inadequate cognitive processing that is based upon impaired access to information.1 Understanding the information needs of nurses and physicians' when using a clinical information system (CIS) is difficult largely because there are few systematic attempts made to do so. We collected 15.5 hours of data of nurses and physicians' CIS interactions in three clinical environments (cardiac ICU, a general medical/surgical nursing, and an ambulatory clinic). We accomplished this through observational, cognitive-based methods (e.g., thinking aloud during interaction) and the video capturing of events with a portable usability laboratory.2 We developed a systematic approach to identify and define in-context clinical information needs while using a CIS, and determine how to categorize and code such events. 3

Cognition↗

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↗

Tailored health communication: crafting the patient message for HIV TIPS.

The HIV TIPS project will pilot and evaluate the use of web-based information technology on prescription errors and quality of care by providing tailored practice guidelines and patient education in ambulatory practice settings of the National AIDS Education and Training Centers (NAETC) network. In the first phase of the project, we tailored messages to guide patient adherence and self-care, using DHHS guidelines. We developed a method based on communication theory to ensure complete and effective messages.

Anti-Retroviral Agents↗

Impact of a physician's order entry (POE) system on physicians' ordering patterns and patient length of stay.

OBJECTIVE: To investigate the impact of a physician's order entry (POE) system on physicians' ordering patterns and patient length of stay. DESIGN: Prospective time series study at pre-POE, 3 months and 6 months after POE at a tertiary teaching hospital in Korea. The study period was from June 1999 to May 2000. MEASUREMENTS: The number of orders (doctor's, PRN, medication, changed, canceled orders), number of tests (complete blood count, chemistry, chest X-ray, stat laboratory, serum electrolytes tests), appropriateness and length of patient stay were measured through chart review of 171 in-patients (liver disease, renal disease, gastrectomy, simple mastectomy). RESULTS: The number of doctors' orders, PRN, and medication orders significantly increased after POE. The numbers of changed and canceled orders were not significantly different between pre- and post-POE. The number of stat lab tests significantly decreased after POE. There was no change in appropriateness of patients' hospital stay between pre- and post-POE. Length of stay significantly decreased (P=0.049). CONCLUSION: POE contributed to improving the quality of care in two ways: improvement of auditability by recording the medical services for patients in more precise and transparent manner, and more appropriate utilization of resources by decreasing the number of stat diagnostic tests and length of stay.

Analysis of Variance↗