Applicability of the nursing interventions classification in the psychiatric outpatient care setting

Standardized nursing terminologies (SNT) have been developed to describe the nursing process systematically. The aim of this research was to study the applicability of the Nursing Interventions Classification (NIC) in the psychiatric outpatient care setting in Finland. The research includes three phases. In the first phase using an integrative literature review we identified nursing interventions in research publications (n=60) and used the NIC to analyze the identified interventions. In the second phase, we used an ethnographically oriented work-place study to identify interventions in the clinical setting. This included observations and interviews and the findings were analyzed together with nurses (n=17). The core interventions were identified using the Delphi method. The panelists consisted of nurses and nurse managers (round one n=54, round two n=26). In the third phase we identified nursing interventions in nursing progress notes (n=1150) and in nursing care summaries (n=17) and mapped these into the NIC. In all we identified 105 different nursing interventions, of which 95% could be mapped into the NIC. The emphasis was in interventions aiming at behavioral change and more specifically interventions that support coping by building on patients’ strengths. In nursing documentation, the most frequent interventions were Surveillance and Care Coordination. The group delivery method was common in all phases. The findings of this study emphasize the need for a systematic terminology to describe nursing interventions for nurses to conceptualize their work, to make the work visible and to ensure the quality of nursing documentation. The broad coverage, descriptiveness of the interventions and the taxonomical structure of the NIC support its applicability. However, the interventions in the classification were found to be overlapping which limits the systematic transfer of information and the possibilities for secondary use of data. Additional limitations are the lack of semantic coherence with the concepts used in research and the difficulty of describing interventions delivered using the group method. This research generated recommendations for the development of the classification. The most central ones include the need to include multiple methods in the research and development and the integration of concepts used in research literature.Hoitotyön interventioiden luokituksen soveltuvuus aikuispsykiatrian avohoitoon Hoitotyön systemaattinen kuvaaminen edellyttää yhteisen kielen ja käsitteistöjen käyttöä. Tässä tutkimuksessa selvitetään hoitotyön interventioiden luokituksen (Nursing Interventions Classification, NIC) soveltuvuutta aikuispsykiatrian avohoitoon. Tutkimus koostuu kolmesta osavaiheesta. Ensimmäisessä vaiheessa integratiivisen kirjallisuuskatsauksen avulla tutkimuksista (n=60) tunnistettiin hoitotyön interventioita ja nämä analysoitiin NIC-luokituksen avulla. Toisessa vaiheessa hyödynnettiin etnografista työntutkimusta. Hoitotyön interventioita tunnistettiin hoitajien työtä havainnoimalla ja hoitajia haastattelemalla. Analysointi tapahtui yhdessä hoitajien (n=17) kanssa. Ydininterventioiden tutkimus tapahtui sähköistä Delfoi-menetelmää hyödyntäen. Panelisteina toimivat sairaanhoitajat ja hoitotyön lähijohtajat (ensimmäisellä kierroksella n=54, toisella kierroksella n=26). Kolmannessa vaiheessa tutkittiin hoitotyön päivittäiskirjauksia (n=1150) ja hoitotyön yhteenvetoja (n=17), joista tunnistetut interventiot yhdistettiin NICluokitukseen. Tutkimuksessa tunnistettiin yhteensä 105 interventioita, joista 95 %:lle löytyi vastine luokituksesta. Keskeisiä interventioita kirjallisuuskatsauksessa, etnografisessa työntutkimuksessa ja ydininterventioiden tutkimuksessa olivat käyttäytymisen muutokseen tähtäävät psykososiaaliset interventiot ja erityisesti voimavaralähtöinen selviytymiskyvyn tukeminen. Hoitotyön kirjauksissa korostuivat seuranta ja hoidon koordinointi. Interventioiden ryhmämuotoinen toteutustapa oli yleinen kaikissa tutkimusvaiheissa. Tutkimuksen tulokset korostavat yhteisten käsitteiden tarvetta hoitotyön interventioille työn käsitteellistämisen, näkyväksi tekemisen ja kirjaamisen laadun näkökulmista. Tutkitun luokituksen soveltuvuutta tukevat sen kattavuus, käsitteiden hyvä tunnistettavuus ja hierarkkinen rakenne. Luokituksen interventiokäsitteet ovat osittain päällekkäisiä heikentäen sen systemaattista käytettävyyttä ja tiedon toisiokäytön mahdollisuuksia. Soveltuvuutta rajoittavat myös luokituksen vähäinen yhteys tutkimuskirjallisuudessa käytettyihin käsitteisiin ja vaikeus kuvata ryhmämuotoisia interventioita. Tutkimus antaa suosituksia luokituksen jatkokehittämiselle. Keskeisimpänä ovat monimenetelmäisyys tutkimuksessa ja kehittämisessä sekä tutkimuskirjallisuuden käsitteistöjen vahvempi integroiminen luokitukseen

Extensions of SNOMED taxonomy abstraction networks supporting auditing and complexity analysis

The Systematized Nomenclature of Medicine – Clinical Terms (SNOMED CT) has been widely used as a standard terminology in various biomedical domains. The enhancement of the quality of SNOMED contributes to the improvement of the medical systems that it supports. In previous work, the Structural Analysis of Biomedical Ontologies Center (SABOC) team has defined the partial-area taxonomy, a hierarchical abstraction network consisting of units called partial-areas. Each partial-area comprises a set of SNOMED concepts exhibiting a particular relationship structure and being distinguished by a unique root concept. In this dissertation, some extensions and applications of the taxonomy framework are considered. Some concepts appearing in multiple partial-areas have been designated as complex due to the fact that they constitute a tangled portion of a hierarchy and can be obstacles to users trying to gain an understanding of the hierarchy’s content. A methodology for partitioning the entire collection of these so-called overlapping complex concepts into singly-rooted groups was presented. A novel auditing methodology based on an enhanced abstraction network is described. In addition, the existing abstraction network relies heavily on the structure of the outgoing relationships of the concepts. But some of SNOMED hierarchies (or subhierarchies) serve only as targets of relationships, with few or no outgoing relationships of their own. This situation impedes the applicability of the abstraction network. To deal with this problem, a variation of the above abstraction network, called the converse abstraction network (CAN) is defined and derived automatically from a given SNOMED hierarchy. An auditing methodology based on the CAN is formulated. Furthermore, a preliminary study of the complementary use of the abstraction network in description logic (DL) for quality assurance purposes pertaining to SNOMED is presented. Two complexity measures, a structural complexity measure and a hierarchical complexity measure, based on the abstraction network are introduced to quantify the complexity of a SNOMED hierarchy. An extension of the two measures is also utilized specifically to track the complexity of the versions of the SNOMED hierarchies before and after a sequence of auditing processes

A modular, open-source information extraction framework for identifying clinical concepts and processes of care in clinical narratives

In this thesis, a synthesis is presented of the knowledge models required by clinical informa- tion systems that provide decision support for longitudinal processes of care. Qualitative research techniques and thematic analysis are novelly applied to a systematic review of the literature on the challenges in implementing such systems, leading to the development of an original conceptual framework. The thesis demonstrates how these process-oriented systems make use of a knowledge base derived from workflow models and clinical guidelines, and argues that one of the major barriers to implementation is the need to extract explicit and implicit information from diverse resources in order to construct the knowledge base. Moreover, concepts in both the knowledge base and in the electronic health record (EHR) must be mapped to a common ontological model. However, the majority of clinical guideline information remains in text form, and much of the useful clinical information residing in the EHR resides in the free text fields of progress notes and laboratory reports. In this thesis, it is shown how natural language processing and information extraction techniques provide a means to identify and formalise the knowledge components required by the knowledge base. Original contributions are made in the development of lexico-syntactic patterns and the use of external domain knowledge resources to tackle a variety of information extraction tasks in the clinical domain, such as recognition of clinical concepts, events, temporal relations, term disambiguation and abbreviation expansion. Methods are developed for adapting existing tools and resources in the biomedical domain to the processing of clinical texts, and approaches to improving the scalability of these tools are proposed and evalu- ated. These tools and techniques are then combined in the creation of a novel approach to identifying processes of care in the clinical narrative. It is demonstrated that resolution of coreferential and anaphoric relations as narratively and temporally ordered chains provides a means to extract linked narrative events and processes of care from clinical notes. Coreference performance in discharge summaries and progress notes is largely dependent on correct identification of protagonist chains (patient, clinician, family relation), pronominal resolution, and string matching that takes account of experiencer, temporal, spatial, and anatomical context; whereas for laboratory reports additional, external domain knowledge is required. The types of external knowledge and their effects on system performance are identified and evaluated. Results are compared against existing systems for solving these tasks and are found to improve on them, or to approach the performance of recently reported, state-of-the- art systems. Software artefacts developed in this research have been made available as open-source components within the General Architecture for Text Engineering framework

Computing Healthcare Quality Indicators Automatically: Secondary Use of Patient Data and Semantic Interoperability

Harmelen, F.A.H. van [Promotor]Keizer, N.F. de [Copromotor]Cornet, R. [Copromotor]Teije, A.C.M. [Copromotor