Marisa L. Wilson

Towards implementing a global competency-based nursing and clinical informatics curriculum: Applying the TIGER initiative

This workshop will review the history of the TIGER initiative in order to set the framework for an understanding of international informatics competencies. We will include a description of clinical nursing informatics programs in 37 countries as well as the results of a recent survey of nursing competencies in order to further discussions of internationally agreed-upon competency definitions. These two surveys will provide the basis for developing a consensus regarding the integration of core competencies into informatics curriculum developments. Expected outcomes include building consensus on core competencies and developing plans toward implementing intra- and inter-professional informatics competencies across disciplines globally.

Using dashboard technology and clinical decision support systems to improve heart team efficiency and accuracy: Review of the literature

AIM This review aimed to provide a comprehensive overview of the current state of evidence for the use of clinical dashboards and clinical decision support systems (CDSS) in multidisciplinary teams. METHODS A literature search was performed for the dates 2004-2014 on CINAHL, Medline, Embase, and Cochrane Library. A citation search and a hand search of relevant papers were also conducted. RESULTS (One hundred and twelve full text papers were retrieved of which 22 were included in the review.) There was considerable heterogeneity in setting, users, and indicators utilized. Information on usability and human-computer interaction was thoroughly reviewed. There was evidence that dashboards were associated with improved care processes when end-user input was incorporated and information was concurrent, pertinent and intuitive. CONCLUSION There is some evidence that implementing clinical dashboards and/or CDSS that provide immediate access to current patient information for clinicians can improve processes and patient outcomes.

Nursing, Professional Curiosity and Big Data CoCreating eHealth.

This paper describes work that has taken place over the past three years in the form of an annual deep dive study track within a national conference setting. The work explores the changing influence that big data, and in particular population and social determinants of health data, makes upon the generation of co-created eHealth within a nursing domain. Working with delegates, many of whom returned year after year, the paper reports the discussion themes and ideas that evolved over time. The paper is presented as an example of connected reasoning and personal development by all those involved and is offered as a distributed think tank for further discussion and debate.

Population health: a nursing action plan

Abstract The passage of the Affordable Care Act shifted the focus of health care from individual, patient specific, episodic care, towards health management of groups of people with an emphasis on primary and preventive care. Population health management assists to attain and maintain health while improving quality and lowering costs. The recent Catalyst for Change report creates an urgent call for harnessing the power of nurses—in our communities, schools, businesses, homes and hospitals—to build capacity for population health. Informatics Nurse Specialists are prepared to bridge roles across practice, research, education, and policy to support this call. Each year, the AMIA Nursing Informatics Working Group convenes an expert panel to reflect on the “hot topics” of interest to nursing. Not surprisingly, the 2017 topic was on the current state and challenges of population health. The following summary reflects the panel’s perspectives and recommendations for action.

Big Data in Healthcare: A Wide Look at a Broad Subject

Healthcare, as an industry, is being held accountable for outcomes that were never before considered. No longer is it a fee for service industry but one in which providers are accountable for quality, performance, and satisfaction. How can healthcare utilize the sea of data collected to optimize care for quality, performance, and satisfaction? One answer is to harness the power of that data and to manage the ability to perform meaningful analyses. Clinicians and ancillary providers collect data as they interact with patients each and every day. Data is brought into patient records from laboratories, radiology readings, pathology reports, transfers, and consults where it is integrated and reviewed in order to make informed decisions related to care. Patient and consumer generated data is being gathered and stored on millions of mobile applications or in personal health records. Some patients are passing this data to their care providers for inclusion in care decision-making. Data is coming from external care providers in disparate systems and is passed from one provider to another as patients traverse a trajectory of care that may or may not be seamless. At each juncture, the data is reviewed, updated, and then transferred onto the next provider or caregiver. At some point in the not too distant future, data describing our homes, schools, workplaces, and communities will be considered as these social determinants of health contribute greatly to the overall health of persons and communities. This will encompass data and information describing poverty, employment, food security, housing, education, incarceration and institutionalization, access to care, environment, and literacy. All of this data will need to be extracted from dissimilar storage points, cleaned and transformed for use, and loaded into a storage repository so that clinicians will all be able to gain a fuller picture of how to care better and to delivery that quality.

Exploring Community Planning Thinking as a Model for Use Case Development.

There are many vetted technical and semantic standards promulgated within the United States and the United Kingdom to operationalize eHealth interoperability in order to improve care outcomes, manage population health, and provide efficient information exchange between providers, services, patients and consumers. However, consideration must be given to the complex real world use cases in which the data and information will be exchanged between a wide variety of interested parties, including the consumer or patient. In many instances, community based use cases need development in order to serve as the model. These use cases can only be accurately described and created by using a wide lens viewpoint such as community-planning engages, which requires that all interested parties be actively involved. This poster will introduce models of community planning that can be developed and led by the Nurse Informatician.

Using clinical decision support and dashboard technology to improve heart team efficiency and accuracy in a transcatheter aortic valve implantation (TAVI) program

Heart Team meetings are becoming the model of care for patients undergoing transcatheter aortic valve implantations (TAVI) worldwide. While Heart Teams have potential to improve the quality of patient care, the volume of patient data processed during the meeting is large, variable, and comes from different sources. Thus, consolidation is difficult. Also, meetings impose substantial time constraints on the members and financial pressure on the institution. We describe a clinical decision support system (CDSS) designed to assist the experts in treatment selection decisions in the Heart Team. Development of the algorithms and visualization strategy required a multifaceted approach and end-user involvement. An innovative feature is its ability to utilize algorithms to consolidate data and provide clinically useful information to inform the treatment decision. The data are integrated using algorithms and rule-based alert systems to improve efficiency, accuracy, and usability. Future research should focus on determining if this CDSS improves patient selection and patient outcomes.