Nursing Informatics' Contribution to One Health.

OBJECTIVES: To summarise contemporary knowledge in nursing informatics related to education, practice, governance and research in advancing One Health. METHODS: This descriptive study combined a theoretical and an empirical approach. Published literature on recent advancements and areas of interest in nursing informatics was explored. In addition, empirical data from International Medical Informatics Association (IMIA) Nursing Informatics (NI) society reports were extracted and categorised into key areas regarding needs, established activities, issues under development and items not current. RESULTS: A total of 1,772 references were identified through bibliographic database searches. After screening and assessment for eligibility, 146 articles were included in the review. Three topics were identified for each key area: 1) education: "building basic nursing informatics competence", "interdisciplinary and interprofessional competence" and "supporting educators competence"; 2) practice: "digital nursing and patient care", "evidence for timely issues in practice" and "patient-centred safe care"; 3) governance: "information systems in healthcare", "standardised documentation in clinical context" and "concepts and interoperability", and 4) research: "informatics literacy and competence", "leadership and management", and "electronic documentation of care". 17 reports from society members were included. The data showed overlap with the literature, but also highlighted needs for further work, including more strategies, methods and competence in nursing informatics to support One Health. CONCLUSIONS: Considering the results of this study, from the literature nursing informatics would appear to have a significant contribution to make to One Health across settings. Future work is needed for international guidelines on roles and policies as well as knowledge sharing.

Semantic Cross-Mapping Execution of Data in the Perinatal Registry of the Netherlands.

INTRODUCTION: The electronically submitted data from midwives and hospitals to the Netherlands perinatal registry vary significantly in their data definitions, and electronic message versions. The purpose of this article is to describe the semantic cross-mapping tool and execution procedure to prepare the data for statistical analysis. METHODS: requirements analysis, design, development and testing. RESULTS: The tool for governance of versions of datasets, CIMs, data, and value sets is designed, developed, and tested. The test is based on the data-mart of version PRN 1.3 based data from 2019. Data are semantically cross mapped to current version perinatology data 2.2. CONCLUSION: The cross-mapping of PRN 1.3 data to perinatology 2.2 data are defined in the tool, testing revealed this mapping is successful.

Architecture for Variable Data Entry into a National Registry.

INTRODUCTION: The Dutch perinatal registry required a new architecture due to the large variability of the submitted data from midwives and hospitals. The purpose of this article is to describe the healthcare information architecture for the Dutch perinatal registry. METHODS: requirements analysis, design, development and testing. RESULTS: The architecture is depicted for its components and preliminary test results. CONCLUSION: The data entry and storage work well, the Data Marts are under preparation.

Introduction: Forecasting Informatics Competencies for Nurses in the Future of Connected Health.

This introduction to the book discusses how the topic of competencies for nurses in a world of connected health needs to be addressed at the curriculum level to achieve the specific competencies for various roles, including practicing nurse, nurse teacher, nurse leader, and nursing informatics specialists. It looks back at milestone publications from the international Nursing Informatics post conferences that still serve a purpose for inspiring developments today and looks forward to the way nurses can use connected health to improve the health and health care for their patients. Specific emerging topics in health information technology are addressed as well, such as semantics, genetics, big data, eHealth and social media.

Informatics Competencies in Connected Health: Annotated Bibliography.

In this book it is of course impossible to be complete on all competencies publications, or all relevant subjects. For that reason the Post Conference Team decided to have some pages of the book reserved for annotations. An annotation is seen as a short reference to another topic or publication, not included in this book, and a brief motivation from one of us, why this might be of interest to the readers.

Information Architecture for Perinatal Registration in the Netherlands.

In the Netherlands, the perinatal registry has undergone significant changes in the past decades. The purpose of this article is to describe the current health care information architecture for the national perinatal registry, including how the national data set is arranged and how electronic messages are used to submit data. We provide implications for women's health care providers based on the creation and implementation of the Dutch perinatal registry system.

Checking the Quality of Detailed Clinical Models: Instrument Application.

BACKGROUND: The exchange of clinical data between electronic health records is a challenge and need flexible models that adapt to clinical needs. Detailed Clinical Models (DCM) are used for this purpose, however, what is their quality? This paper's objective is to report on the application of an existing instrument to determine DCM quality. METHODS: A selection of 9 DCMs about oncology care was tested using the 'Quality Metrics for DCM'. RESULTS: The instrument revealed scores per DCM varying from 16 to 26, rendering one DCM insufficient and five requiring upgrading. CONCLUSION: The instrument proved practical in its administration and revealed useful feedback for DCM improvement. A core part of a DCM, the actual specification of data elements, is not included in the instrument and is suggested to be added.

Strategic Deployment of Clinical Models.

The selection, implementation, and certification of electronic health records (EHR) could benefit from the required use of one of the established clinical model approaches. For the lifelong record of data about individuals, issues arise about the permanence and preservation of data during or even beyond a lifetime. Current EHR do not fully adhere to pertinent standards for clinical data, where it is known for some 20 plus years that standardization of health data is a cornerstone for patient safety, interoperability, data retrieval for various purposes and the lifelong preservation of such data. This paper briefly introduces the issues and gives a brief recommendation for future work in this area.

Strategies for Leveraging Interoperable Health Information Exchange Systems Among Healthcare Communities.

The panel will share international Health Information Exchange (HIE) projects to improve quality and lower costs in healthcare communities (i.e. hospitals, clinician practices, and aged care facilities). HIE allows healthcare professionals and patients to appropriately access and securely share a patient's vital medical information electronically within and across organizations. Intended audience: Researchers, consumers, practitioners, vendors, care providers, and policy makers with interests in technology design, development, implementation, and management, particularly focused on HIE.

Detailed clinical models: representing knowledge, data and semantics in healthcare information technology.

OBJECTIVES: This paper will present an overview of the developmental effort in harmonizing clinical knowledge modeling using the Detailed Clinical Models (DCMs), and will explain how it can contribute to the preservation of Electronic Health Records (EHR) data. METHODS: Clinical knowledge modeling is vital for the management and preservation of EHR and data. Such modeling provides common data elements and terminology binding with the intention of capturing and managing clinical information over time and location independent from technology. Any EHR data exchange without an agreed clinical knowledge modeling will potentially result in loss of information. RESULTS: Many attempts exist from the past to model clinical knowledge for the benefits of semantic interoperability using standardized data representation and common terminologies. The objective of each project is similar with respect to consistent representation of clinical data, using standardized terminologies, and an overall logical approach. However, the conceptual, logical, and the technical expressions are quite different in one clinical knowledge modeling approach versus another. There currently are synergies under the Clinical Information Modeling Initiative (CIMI) in order to create a harmonized reference model for clinical knowledge models. CONCLUSIONS: The goal for the CIMI is to create a reference model and formalisms based on for instance the DCM (ISO/TS 13972), among other work. A global repository of DCMs may potentially be established in the future.

Continuity of care with HL7 v3 care record for oncology nursing.

UNLABELLED: The Clinical Data Ware House needs to meet three functions: reporting quality indicators, clinical research, and continuity of care. This paper reports on one function, namely the development and testing of data exchange for continuity of nursing care for oncology patients. The proof of principle was carried out using system analysis, requirements setting, system design, system development and experiment with the application of Health Level 7 version 3 Care Record electronic message. A successful testing of the Care Record message was conducted, using a case based data-subset for oncology nursing care including personal data, pain, weight and vital signs, among others. CONCLUSION: The development illustrated that the system components facilitate electronic data exchange from hospital to home care, allowing home care nurses to use received clinical data in their local system. In an incremental approach this data exchange can be enhanced to meet all data and all systems requirements.

Representing the Glasgow Coma Scale in IT: Proper Specification is Required for Assessment Scales.

In healthcare a huge amount of assessment scales and score systems are in use to abbreviate and summarize the results of clinical observations to interpret a patient's condition in a valid and reliable manner. It is challenging to convey the information in a semantic interoperable form to other systems. A bad approach would be to invent individual models for each of them. Within this paper we would like to demonstrate that a generic model is sufficient by demonstrating the realization with the Glasgow Coma Scale.

Exchanging care records using HL7 V3 care provision messages.

OBJECTIVE: This paper describes Health Level 7 (HL7) V.3 Care Transfer, Care Record Query, and Care Record messages. This is the core of the Care Provision Domain in the HL7 standard which became normative at the end of 2012 and is an American National Standards Institute (ANSI)-approved HL7 standard. BACKGROUND AND SIGNIFICANCE: Using a message is somewhat different from the approach offered in the current HL7 Clinical Document Architecture (CDA). The overall advantage is human-to-human communication and system-to-system processing of structured data through electronic messages, supporting continuity of care and interactive structured data exchange through querying. MATERIALS AND METHODS: The Care Provision Domain Model in HL7 was developed based on use cases from several projects internationally. Use case and information analysis, model building, HL7 consensus methods (eg, working group meetings), conference calls, balloting, a draft standard for trial use, pilot implementations, and subsequent evaluation were applied. RESULTS: The membership and pilot implementers gave feedback to improve the draft standard. After the formal ballot process, HL7 membership accepted it as a normative standard and it is now ANSI approved. The Care Provision Domain Model defines the structure (data exchanged) and dynamics (workflow and communications) of the Care Record, Care Record Query, and Care Transfer. DISCUSSION AND CONCLUSIONS: The HL7 V3 Care Provision Domain differs from the HL7 CDA regarding support of the dynamics of care (eg, for continuity of care) as provided through a series of interactions and queries, but is similar with respect to the data and their organization.

Clinical modeling--a critical analysis.

BACKGROUND: Modeling clinical processes (and their informational representation) is a prerequisite for optimally enabling and supporting high quality and safe care through information and communication technology and meaningful use of gathered information. OBJECTIVES: The paper investigates existing approaches to clinical modeling, thereby systematically analyzing the underlying principles, the consistency with and the integration opportunity to other existing or emerging projects, as well as the correctness of representing the reality of health and health services. METHODS: The analysis is performed using an architectural framework for modeling real-world systems. In addition, fundamental work on the representation of facts, relations, and processes in the clinical domain by ontologies is applied, thereby including the integration of advanced methodologies such as translational and system medicine. RESULTS: The paper demonstrates fundamental weaknesses and different maturity as well as evolutionary potential in the approaches considered. It offers a development process starting with the business domain and its ontologies, continuing with the Reference Model-Open Distributed Processing (RM-ODP) related conceptual models in the ICT ontology space, the information and the computational view, and concluding with the implementation details represented as engineering and technology view, respectively. CONCLUSION: The existing approaches reflect at different levels the clinical domain, put the main focus on different phases of the development process instead of first establishing the real business process representation and therefore enable quite differently and partially limitedly the domain experts' involvement.

Clinical professional governance for detailed clinical models.

This chapter describes the need for Detailed Clinical Models for contemporary Electronic Health Systems, data exchange and data reuse. It starts with an explanation of the components related to Detailed Clinical Models with a brief summary of knowledge representation, including terminologies representing clinic relevant "things" in the real world, and information models that abstract these in order to let computers process data about these things. Next, Detailed Clinical Models are defined and their purpose is described. It builds on existing developments around the world and accumulates in current work to create a technical specification at the level of the International Standards Organization. The core components of properly expressed Detailed Clinical Models are illustrated, including clinical knowledge and context, data element specification, code bindings to terminologies and meta-information about authors, versioning among others. Detailed Clinical Models to date are heavily based on user requirements and specify the conceptual and logical levels of modelling. It is not precise enough for specific implementations, which requires an additional step. However, this allows Detailed Clinical Models to serve as specifications for many different kinds of implementations. Examples of Detailed Clinical Models are presented both in text and in Unified Modelling Language. Detailed Clinical Models can be positioned in health information architectures, where they serve at the most detailed granular level. The chapter ends with examples of projects that create and deploy Detailed Clinical Models. All have in common that they can often reuse materials from earlier projects, and that strict governance of these models is essential to use them safely in health care information and communication technology. Clinical validation is one point of such governance, and model testing another. The Plan Do Check Act cycle can be applied for governance of Detailed Clinical Models. Finally, collections of clinical models do require a repository in which they can be stored, searched, and maintained. Governance of Detailed Clinical Models is required at local, national, and international levels.

Towards a model based electronic nursing record.

The electronic nursing record (ENR) as part of the larger electronic health record has been discussed for years. Its implementation is not that widespread as often considered. E.g. in the Netherlands, a fraction of hospitals uses it. This paper describes a nurse led project in a Dutch hospital where an electronic nursing record system has been defined, based on requirements analysis, standardization through Detail Clinical Models (DCM), and implementation. Standardization of data with DCM is a method and a format to organize clinical knowledge, concepts, and data elements such that managing and exchanging semantics of data is independent from specific technology. 28 DCM are used in the specifications of the ENR. Using the DCM standards approach and the mapping of data elements to professional terminologies enable a vendor to develop what is needed for quality care, rather then sell a fixed set product.

Representing knowledge, data and concepts for EHRS using DCM.

With the move towards next generations of Electronic Health Record Systems (EHRS), the focus changes from administrative and data retrieval and data entry system capabilities towards clinical functions. The representation of the clinical knowledge and evidence base into EHRS becomes an important asset for health care, with its own challenges. Clinician's do want EHRS support but do not want to standardize care, they do want unified terminology and structured data entry but also free text. In addition, information modelers challenge each other for the best solution, and care pathways and other workflows seem to differ for each situation. Such diverging approaches add complexity to the already difficult situation around Information Technology in health care, the EHRS in particular. This paper argues that a change is necessary to adopt Detailed Clinical Modeling as a method to organize clinical knowledge, represent concepts and define data in such a manner that it allows for semantics to be exchanged without being trapped in a specific technology. DCM help to fulfill the requirements for the enter data once, reuse multiple times paradigm for EHRS.

Bridging the HL7 template - 13606 archetype gap with detailed clinical models.

The idea of two level modeling has been taken up in healthcare information systems development. There is ongoing debate which approach should be taken. From the premise that there is a lack of clinician's time available, and the need for semantic interoperability, harmonization efforts are important. The question this paper addresses is whether Detailed Clinical Models (DCM) can bridge the gap between existing approaches. As methodology, a bottom up approach in multilevel comparison of existing content and modeling is used. Results indicate that it is feasible to compare and reuse DCM with clinical content from one approach to the other, when specific limitations are taken into account and precise analysis of each data-item is carried out. In particular the HL7 templates, the ISO/CEN 13606 and OpenEHR archetypes reveal more commonalties than differences. The linkage of DCM to terminologies suggests that data-items can be linked to concepts present in multiple terminologies. This work concludes that it is feasible to model a multitude of precise items of clinical information in the format of DCM and that transformations between different approaches are possible without loss of meaning. However, a set of single or combined clinical items and assessment scales have been tested. Larger groupings of clinical information might bring up more challenges.

Detailed clinical models: a review.

OBJECTIVES: Due to the increasing use of electronic patient records and other health care information technology, we see an increase in requests to utilize these data. A highly level of standardization is required during the gathering of these data in the clinical context in order to use it for analyses. Detailed Clinical Models (DCM) have been created toward this purpose and several initiatives have been implemented in various parts of the world to create standardized models. This paper presents a review of DCM. METHODS: Two types of analyses are presented; one comparing DCM against health care information architectures and a second bottom up approach from concept analysis to representation. In addition core parts of the draft ISO standard 13972 on DCM are used such as clinician involvement, data element specification, modeling, meta information, and repository and governance. RESULTS: SIX INITIATIVES WERE SELECTED: Intermountain Healthcare, 13606/OpenEHR Archetypes, Clinical Templates, Clinical Contents Models, Health Level 7 templates, and Dutch Detailed Clinical Models. Each model selected was reviewed for their overall development, involvement of clinicians, use of data types, code bindings, expressing semantics, modeling, meta information, use of repository and governance. CONCLUSIONS: Using both a top down and bottom up approach to comparison reveals many commonalties and differences between initiatives. Important differences include the use of or lack of a reference model and expressiveness of models. Applying clinical data element standards facilitates the use of conceptual DCM models in different technical representations.