Review on Master Patient Index

In today's health care establishments there is a great diversity of information systems. Each with different specificities and capacities, proprietary communication methods, and hardly allow scalability. This set of characteristics hinders the interoperability of all these systems, in the search for the good of the patient. It is vulgar that, when we look at all the databases of each of these information systems, we come across different registers that refer to the same person; records with insufficient data; records with erroneous data due to errors or misunderstandings when inserting patient data; and records with outdated data. These problems cause duplicity, incoherence, discontinuation and dispersion in patient data. With the intention of minimizing these problems that the concept of a Master Patient Index is necessary. A Master Patient Index proposes a centralized repository, which indexes all patient records of a given set of information systems. Which is composed of a set of demographic data sufficient to unambiguously identify a person and a list of identifiers that identify the various records that the patient has in the repositories of each information system. This solution allows for synchronization between all the actors, minimizing incoherence, out datedness, lack of data, and a decrease in duplicate registrations. The Master Patient Index is an asset to patients, the medical staff and health care providers

Addressing Childhood Adversity and Social Determinants inPediatric Primary Care:Recommendations for New Hampshire

Research has clearly demonstrated the significant short- and long-term impacts of adverse childhood experiences (ACEs) and the social determinants of health (SDOH) on child health and well-being.1 Identifying and addressing ACEs and SDOH will require a coordinated and systems-based approach. Pediatric primary care* plays a critical role in this system, and there is a growing emphasis on these issues that may be impacting a family. As awareness of ACEs and SDOH grows, so too does the response effort within the State of New Hampshire. Efforts to address ACEs and the SDOH have been initiated by a variety of stakeholders, including non-profit organizations, community-based providers, and school districts. In late 2017, the Endowment for Health and SPARK NH funded the NH Pediatric Improvement Partnership (NHPIP) to develop a set of recommendations to address identifying and responding to ACEs and SDOH in NH primary care settings caring for children. Methods included conducting a review of literature and Key Informant Interviews (KII). Themes from these were identified and the findings are summarized in this report

"There are too many, but never enough": qualitative case study investigating routine coding of clinical information in depression.

We sought to understand how clinical information relating to the management of depression is routinely coded in different clinical settings and the perspectives of and implications for different stakeholders with a view to understanding how these may be aligned

Patient safety competencies in undergraduate nursing students: a rapid evidence assessment

Aims To identify patient safety competencies, and determine the clinical learning environments that facilitate the development of patient safety competencies in nursing students. Background Patient safety in nursing education is of key importance for health professional environments, settings, and care systems. To be effective, safe nursing practice requires a good integration between increasing knowledge and the different clinical practice settings. Nurse educators have the responsibility to develop effective learning processes and ensure patient safety. Design Rapid Evidence Assessment. Data Sources MEDLINE, CINAHL, SCOPUS, and ERIC were searched, yielding 500 citations published between 1 January 2004 - 30 September 2014. Review Methods Following the Rapid Evidence Assessment process, 17 studies were included in this review. Hawker's (2002) quality assessment tool was used to assess the quality of the selected studies. Results Undergraduate nursing students need to develop competencies to ensure patient safety. The quality of the pedagogical atmosphere in the clinical setting has an important impact on the students’ overall level of competence. Active student engagement in clinical processes stimulates their critical reasoning, improves interpersonal communication, and facilitates adequate supervision and feedback. Conclusion Few studies describe the nursing students’ patient safety competencies and exactly what they need to learn. In addition, studies describe only briefly which clinical learning environments facilitate the development of patient safety competencies in nursing students. Further research is needed to identify additional pedagogical strategies and the specific characteristics of the clinical learning environments that encourage the development of nursing students’ patient safety competencies

Challenging Social Cognition Models of Adherence:Cycles of Discourse, Historical Bodies, and Interactional Order

Attempts to model individual beliefs as a means of predicting how people follow clinical advice have dominated adherence research, but with limited success. In this article, we challenge assumptions underlying this individualistic philosophy and propose an alternative formulation of context and its relationship with individual actions related to illness. Borrowing from Scollon and Scollon’s three elements of social action – “historical body,” “interaction order,” and “discourses in place” – we construct an alternative set of research methods and demonstrate their application with an example of a person talking about asthma management. We argue that talk- or illness-related behavior, both viewed as forms of social action, manifest themselves as an intersection of cycles of discourse, shifting as individuals move through these cycles across time and space. We finish by discussing how these dynamics of social action can be studied and how clinicians might use this understanding when negotiating treatment with patients

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Neonatal Diagnostics: Toward Dynamic Growth Charts of Neuromotor Control

© 2016 Torres, Smith, Mistry, Brincker and Whyatt. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).The current rise of neurodevelopmental disorders poses a critical need to detect risk early in order to rapidly intervene. One of the tools pediatricians use to track development is the standard growth chart. The growth charts are somewhat limited in predicting possible neurodevelopmental issues. They rely on linear models and assumptions of normality for physical growth data – obscuring key statistical information about possible neurodevelopmental risk in growth data that actually has accelerated, non-linear rates-of-change and variability encompassing skewed distributions. Here, we use new analytics to profile growth data from 36 newborn babies that were tracked longitudinally for 5 months. By switching to incremental (velocity-based) growth charts and combining these dynamic changes with underlying fluctuations in motor performance – as the transition from spontaneous random noise to a systematic signal – we demonstrate a method to detect very early stunting in the development of voluntary neuromotor control and to flag risk of neurodevelopmental derail.Peer reviewedFinal Published versio