10 research outputs found

    Translation and National clinical validation of the Nursing Management Minimum Data Set (NMMDS) in hospitals in the country of Iceland

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    Rising health care costs place increased burden on patients, health care personnel, administrators and policymakers. Decisions in health care are influenced by data which can be transferred into valuable information and knowledge. Data sets that facilitate data collection, information management and knowledge building are needed by nurse managers to support administrative decision- making. The Nursing Management Minimum Data Set (NMMDS,,¦) offers a standardized method to capture core data that can be collected in information systems, shared and reused for multiple purposes to support safe and cost-effective care. The purpose of this descriptive study was to adapt to Iceland and clinically test the NMMDS-ICE in all adult inpatient care units in the country of Iceland (excluding psychiatry). The aims of the study were to 1) translate the NMMDS from source language (English) to target language (Icelandic); 2) to validate the translated instrument; and 3) to describe the environment, nursing care resources, and financial resources across acute adult inpatient care units in Iceland. Instrument development consisted of translation, expert validation, and psychometric testing. The target population was all adult acute care units in hospitals in Iceland, and the nurse managers (n=38) representing these units. Data collection included a mailed survey. The sample equaled the population. Furthermore, 134 staff nurses on these units (excluding staff nurses at Landspitali) completed a job satisfaction survey. Return rate was 74% for nurse managers and 71% for staff nurses. Semantic and content equivalence of the NMMDS-ICE was established. Five of seven subscales of the instrument received Cronbach¡¦s alpha score of 0.70 or higher. Results indicated that it was feasible to collect the NMMDS-ICE in hospitals in Iceland, albeit, there was an issue with time commitment to do so. The specialty services that best described the patient population were medical-, surgical services, birthing, and geriatrics. Furthermore, nurse managers seem to perceive good control on their units, and both nurse managers and staff nurses are satisfied with their job. A positive correlation was found between autonomy and satisfaction with nursing management, nursing administration, and own level of autonomy. Statistical differences were identified in environmental and staffing resources between hospitals.The Icelandic Nurses Association (Félag Íslenskra Hjúkrunarfræðinga) and Sigma Theta Tau Internationa

    Collaborative Efforts for Representing Nursing Concepts in Computer-based Systems: International Perspectives

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    Current nursing terminology efforts have converged toward meeting the demand for a reference terminology for nursing concepts by building on the foundation of existing interface and administrative terminologies and by collaborating with terminology efforts across the spectrum of health care. In this article, the authors illustrate how collaboration is promoting convergence toward a reference terminology for nursing by briefly summarizing a wide range of exemplary activities. These include: 1) the International Classification of Nursing Practice (ICNP) activities of the International Council of Nurses (ICN), 2) work in Brazil and Korea that has contributed to, and been stimulated by, ICNP developments, 3) efforts in the United States to improve understanding of the different types of terminologies needed in nursing and to promote harmonization and linking among them, and 4) current nursing participation in major multi-disciplinary standards initiatives. Although early nursing terminology work occurred primarily in isolation and resulted in some duplicative efforts, the activities summarized in this article demonstrate a tremendous level of collaboration and convergence not only in the discipline of nursing but in multi-disciplinary standards initiatives. These efforts are an important prerequisite for ensuring that nursing concepts are represented in computer-based systems in a manner that facilitates multi-purpose use at local, national, regional, and international level

    An exploratory study using the predicate-argument structure to develop methodology for measuring semantic similarity of radiology sentences

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    Indiana University-Purdue University Indianapolis (IUPUI)The amount of information produced in the form of electronic free text in healthcare is increasing to levels incapable of being processed by humans for advancement of his/her professional practice. Information extraction (IE) is a sub-field of natural language processing with the goal of data reduction of unstructured free text. Pertinent to IE is an annotated corpus that frames how IE methods should create a logical expression necessary for processing meaning of text. Most annotation approaches seek to maximize meaning and knowledge by chunking sentences into phrases and mapping these phrases to a knowledge source to create a logical expression. However, these studies consistently have problems addressing semantics and none have addressed the issue of semantic similarity (or synonymy) to achieve data reduction. To achieve data reduction, a successful methodology for data reduction is dependent on a framework that can represent currently popular phrasal methods of IE but also fully represent the sentence. This study explores and reports on the benefits, problems, and requirements to using the predicate-argument statement (PAS) as the framework. A convenient sample from a prior study with ten synsets of 100 unique sentences from radiology reports deemed by domain experts to mean the same thing will be the text from which PAS structures are formed

    Representing and Retrieving Patients\u27 Falls Risk Factors and Risk for Falls Among Adults in Acute Care Through the Electronic Health Record

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    Defining fall risk factors and predicting fall risk status among patients in acute care has been a topic of research for decades. With increasing pressure on hospitals to provide quality care and prevent hospital-acquired conditions, the search for effective fall prevention interventions continues. Hundreds of risk factors for falls in acute care have been described in the literature. However, due to variations in the terms utilized to represent each fall risk factor, an effort to compare findings across settings and replicate research is hampered. As the expectations for the effective use of electronic health records increase, an opportunity exists to create infrastructure within clinical information systems, constructed with evidence-based knowledge and standardized terms, that will support interoperability between systems and enable comparative research. The purpose of this study is to identify to what extent selected fall risk factors and the problem, `risk for falls\u27 are represented and retrievable, in patients\u27 electronic health record, in one acute care setting. Specifically, this study sought to answer three questions: 1) How can the selected fall risk factors and the problem, `risk for falls\u27 be represented through selected standardized terminologies? 2) How are the selected fall risk factors and problem, `risk for falls\u27 represented in a clinical information system? and 3) Which of the selected fall risk factors and problem, `risk for falls\u27 can be retrieved from the electronic health record? The study was guided by the Knowledge Based Nursing Initiative (KBNI) framework. The study was conducted at a local health system within the hospital division, utilizing electronic, patient clinical data. Five selected fall risk factors and the problem, `risk for falls,\u27 were mapped to five standardized terminologies utilizing lexical matching. The terms mapped from the five terminologies were compared to the terms, located in discrete fields within the study site\u27s clinical information system. In addition to SNOMED CT and ICD-9 CM terms, a mixture of vendor and site-specific terms that represented the problem, `risk for falls,\u27 and the five selected fall risk factors were located in the study site\u27s clinical information system. The mapped ICD-9 CM terms and fourteen of the twenty-two SNOMED CT terms were located in the `Problem List\u27 and `Medical History\u27 sections of the clinical information system, while the vendor and site-specific terms were located in `Orders,\u27 `Nursing Flow Sheet,\u27 and `Rehabilitation Flow Sheet\u27 sections. Although both the ICD-9 CM and SNOMED CT terminologies were visible to the clinicians, one of the two mapped SNOMED CT terms representing the problem, `risk for falls,\u27 and fourteen of the twenty-two mapped fall risk factors were not visible because they did not correspond to ICD-9 CM terms. Site-specific terms representing `cognitive impairment\u27 and `impaired gait\u27 were located in both the `Nursing Flow Sheet\u27 and `Rehabilitation Flow Sheet\u27 section. While the terms were lexically similar, the terms were not exact matches and the machine-readable codes differed.Data recorded in 995 episodes of care were retrieved from the electronic data warehouse for analysis. While the SNOMED CT terms were not available for retrieval from the electronic data warehouse, the ICD-9 CM, vendor, and site-specific terms were available. As there were not SNOMED CT terms available for retrieval from the electronic data warehouse, the representation of the problem, `risk for falls,\u27 was not retrievable as a standardized term; however, it was retrieved as a Morse Fall Scale score of 40 or greater among 64.7% of the sample. The percentage of the five fall risk factors represented with the ICD-9 CM terms was lower than the percentage of fall risk factors represented with vendor and site-specific terms. While it is promising that two standardized terminologies have been embedded in the study site\u27s system, limiting the SNOMED CT terms to those that have corresponding ICD-9 terms limits the representation of both the problem, `risk for falls,\u27 and the five selected fall risk factors. It is recommended that hospital administrators embed standardized terminologies in their entirety to allow for adequate representation of terms. Accepting terminologies in their entirety would allow for interoperability between health systems and enable comparative research. Additionally, if vendor and site-specific terms are embedded, clinical information analysts in partnership with clinicians should assure that terms representing the same clinical data (e.g., disorientation), match across different sections of the clinical information system or a cross-mapping of those terms exist in order to support interoperability within the system

    Importance of Measuring Sentential Semantic Knowledge Base of a "Free Text" Medical Corpus

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    At present, the healthcare industry uses codified data mainly for billing purpose. Codified data could be used to improve patient care through decision support and analytical systems. However to reduce medical errors, these systems need access to a wide range of medical data. Unfortunately, a great deal of data is only available in a narrative or free text form, requiring natural language processing (NLP) techniques for their codification. Structuring narrative data and analyzing their underlying meaning from a medical domain requires extensive knowledge acquired through studying the domain empirically. Existing NLP system like MedLEE has a limited ability to analyze free text medical observations and codify data against Unified Medical Language System (UMLS) codes. MedLEE was successful in extracting meaning from relatively simple sentences from radiological reports, but could not analyze more complicated sentences which appear frequently in medical reports. An important problem in medical NLP is, understanding how many codes or symbols are necessary to codify a medical domain completely. Another problem is determining whether existing medical lexicons like SNOMED-CT and ICD-9, etc. are suitable for representing the knowledge in medical reports unambiguously. This thesis investigates the problems behind current NLP systems and lexicons, and attempts to estimate the number of required symbols or codes to represent a large corpus of radiology reports. The knowledge will provide a greater understanding of how many symbols may be needed for the complete representation of concepts in other medical domains

    Haavanhoidon kirjaamismalli - innovaatio kliiniseen hoitotyöhön

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    Clinical foundations and information architecture for the implementation of a federated health record service

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    Clinical care increasingly requires healthcare professionals to access patient record information that may be distributed across multiple sites, held in a variety of paper and electronic formats, and represented as mixtures of narrative, structured, coded and multi-media entries. A longitudinal person-centred electronic health record (EHR) is a much-anticipated solution to this problem, but its realisation is proving to be a long and complex journey. This Thesis explores the history and evolution of clinical information systems, and establishes a set of clinical and ethico-legal requirements for a generic EHR server. A federation approach (FHR) to harmonising distributed heterogeneous electronic clinical databases is advocated as the basis for meeting these requirements. A set of information models and middleware services, needed to implement a Federated Health Record server, are then described, thereby supporting access by clinical applications to a distributed set of feeder systems holding patient record information. The overall information architecture thus defined provides a generic means of combining such feeder system data to create a virtual electronic health record. Active collaboration in a wide range of clinical contexts, across the whole of Europe, has been central to the evolution of the approach taken. A federated health record server based on this architecture has been implemented by the author and colleagues and deployed in a live clinical environment in the Department of Cardiovascular Medicine at the Whittington Hospital in North London. This implementation experience has fed back into the conceptual development of the approach and has provided "proof-of-concept" verification of its completeness and practical utility. This research has benefited from collaboration with a wide range of healthcare sites, informatics organisations and industry across Europe though several EU Health Telematics projects: GEHR, Synapses, EHCR-SupA, SynEx, Medicate and 6WINIT. The information models published here have been placed in the public domain and have substantially contributed to two generations of CEN health informatics standards, including CEN TC/251 ENV 13606
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