The Value of Information Technology-Enabled Diabetes Management

Reviews different technologies used in diabetes disease management, as well as the costs, benefits, and quality implications of technology-enabled diabetes management programs in the United States

Patients without colonoscopic follow-up after abnormal fecal immunochemical tests are often unaware of the abnormal result and report several barriers to colonoscopy.

BackgroundThe fecal immunochemical test (FIT) is the second most commonly used colorectal cancer (CRC) screening modality in the United States; yet, follow-up of abnormal FIT results with diagnostic colonoscopy is underutilized. Our objective was to determine patient-reported barriers to diagnostic colonoscopy following abnormal FIT in an academic healthcare setting.MethodsWe included patients age 50-75 with an abnormal FIT result between 1/1/2015 and 10/31/2017 and no documented follow-up diagnostic colonoscopy. We abstracted demographic data from the electronic health record (EHR). Study personnel conducted telephone surveys with patients to confirm colonoscopy completion and elicit data on notification of FIT results and barriers to colonoscopy. We also provided brief verbal education about diagnostic colonoscopy. We calculated frequencies of demographic data and survey responses and compared survey responses by interest in colonoscopy after education.ResultsWe surveyed 67 patients. Fifty-one were aware of the abnormal FIT result, and a majority learned of the abnormal FIT result by direct communication with providers (19, 37.3%) or EHR messaging (11, 21.6%). Overall, fifty-three patients (79.1%) confirmed lack of colonoscopy, citing provider-related (19, 35.8%), patient-related (16, 30.2%), system-related (1, 1.9%), or multifactorial (17, 32.1%) reasons. Lack of knowledge of FIT result (14, 26.4%) was most common. After brief education, 20 (37.7%) patients requested colonoscopy.ConclusionPatients with an abnormal FIT reported various multi-level barriers to diagnostic colonoscopy after abnormal FIT, including knowledge of FIT results. When provided with brief education, participants expressed interest in diagnostic colonoscopy. Future efforts will evaluate interventions to improve colonoscopy follow-up

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

Although African patients use both conventional or modern and traditional healthcare simultaneously, it has been proven that 80% of people rely on African traditional medicine (ATM). ATM includes medical activities stemming from practices, customs and traditions which were integral to the distinctive African cultures. It is based mainly on the oral transfer of knowledge, with the risk of losing critical knowledge. Moreover, practices differ according to the regions and the availability of medicinal plants. Therefore, it is necessary to compile tacit, disseminated and complex knowledge from various Tradi-Practitioners (TP) in order to determine interesting patterns for treating a given disease. Knowledge engineering methods for traditional medicine are useful to model suitably complex information needs, formalize knowledge of domain experts and highlight the effective practices for their integration to conventional medicine. The work described in this paper presents an approach which addresses two issues. First it aims at proposing a formal representation model of ATM knowledge and practices to facilitate their sharing and reusing. Then, it aims at providing a visual reasoning mechanism for selecting best available procedures and medicinal plants to treat diseases. The approach is based on the use of the Delphi method for capturing knowledge from various experts which necessitate reaching a consensus. Conceptual graph formalism is used to model ATM knowledge with visual reasoning capabilities and processes. The nested conceptual graphs are used to visually express the semantic meaning of Computational Tree Logic (CTL) constructs that are useful for formal specification of temporal properties of ATM domain knowledge. Our approach presents the advantage of mitigating knowledge loss with conceptual development assistance to improve the quality of ATM care (medical diagnosis and therapeutics), but also patient safety (drug monitoring)

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

ESC core curriculum for the general cardiologist (2013)

[No abstract available

Health informatics domain knowledge analysis: An information technology perspective

Health Informatics is an intersection of information technology, several disciplines of medicine and health care. It sits at the common frontiers of health care services including patient centric, processes driven and procedural centric care. From the information technology perspective it can be viewed as computer application in medical and/or health processes for delivering better health care solutions. In spite of the exaggerated hype, this field is having a major impact in health care solutions, in particular health care deliveries, decision making, medical devices and allied health care industries. It also affords enormous research opportunities for new methodological development. Despite the obvious connections between Medical Informatics, Nursing Informatics and Health Informatics, most of the methodologies and approaches used in Health Informatics have so far originated from health system management, care aspects and medical diagnostic. This paper explores reasoning for domain knowledge analysis that would establish Health Informatics as a domain and recognised as an intellectual discipline in its own right

Social Worker Integrated Care Competencies Scale (SICCS): Assessing Social Worker Clinical Competencies for Health Care Settings

Integrating physical and behavioral health services has the potential to reduce health disparities and service inequities among persons most at risk. However, clinical social workers in integrated health settings must possess relevant knowledge and skills to provide quality care to diverse populations. The Social Worker Integrated Care Competency Scale (SWICCS), developed to complement the Integrated and Culturally Relevant Care (ICRC) field education curriculum, measures students’ self-perceptions of knowledge and skills associated with providing behavioral health care. Three student cohorts (n = 38) completed the SWICCS three times during an integrated care field practicum. Results indicated a statistically significant increase in student knowledge and skills at each time point, with a large effect size (r = −.87). The SWICCS demonstrated utility in measuring and tracking social work student acquisition of knowledge and skills required for practice in integrated care environments