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1.
JMIR Diabetes ; 8: e42389, 2023 Mar 15.
Artículo en Inglés | MEDLINE | ID: mdl-36920464

RESUMEN

BACKGROUND: Type 2 diabetes has a growing prevalence and confers significant cost burden to the health care system, raising the urgent need for cost-effective and easily accessible solutions. The management of type 2 diabetes requires significant commitment from the patient, caregivers, and the treating team to optimize clinical outcomes and prevent complications. Technology and its implications for the management of type 2 diabetes is a nascent area of research. The impact of some of the more recent technological innovations in this space, such as continuous glucose monitoring, flash glucose monitoring, web-based applications, as well as smartphone- and smart watch-based interactive apps has received limited attention in the research literature. OBJECTIVE: This scoping review aims to explore the literature available on type 2 diabetes, flash glucose monitoring, and digital health technology to improve diabetic clinical outcomes and inform future research in this area. METHODS: A scoping review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to July 2021), EMBASE (January 1980 to July 2021), Cochrane Central Register of Controlled Trials (CENTRAL; the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. RESULTS: There were very few studies that have explored the use of mobile health and flash glucose monitoring in type 2 diabetes. These studies have explored somewhat disparate and limited areas of research, and there is a distinct lack of methodological rigor in this area of research. The 3 studies that met the inclusion criteria have addressed aspects of the proposed research question. CONCLUSIONS: This scoping review has highlighted the lack of research in this area, raising the opportunity for further research in this area, focusing on the clinical impact and feasibility of the use of multiple technologies, including flash glucose monitoring in the management of patients with type 2 diabetes.

2.
Fam Pract ; 37(3): 390-394, 2020 07 23.
Artículo en Inglés | MEDLINE | ID: mdl-31848589

RESUMEN

BACKGROUND: Potentially preventable hospitalizations (PPH) are defined as unplanned hospital admissions which could potentially have been prevented with the provision of effective, timely outpatient care. To better understand and ultimately reduce rates of PPH, a means of identifying those which are actually preventable is required. The Preventability Assessment Tool (PAT) was designed for use by hospital clinicians to assess the preventability of unplanned admissions for chronic conditions. OBJECTIVE: The present study examined the ability of the PAT to distinguish between those unplanned admissions which are preventable and those which are not, compared to the assessments of an Expert Panel. METHODS: Data were collected between November 2014 and June 2017 at three hospitals in NSW, Australia. Participants were community-dwelling patients with unplanned hospital admissions for congestive heart failure, chronic obstructive pulmonary disease, diabetes complications or angina pectoris. A nurse and a doctor caring for the patient made assessments of the preventability of the admission using the PAT. Expert Panels made assessments of the preventability of each admission based on a comprehensive case report and consensus process. RESULTS: There was little concordance between the hospital doctors and nurses regarding the preventability of admissions, nor between the assessments of the Expert Panel and the hospital nurse or the Expert Panel and the hospital doctor. CONCLUSIONS: The PAT demonstrated poor concurrent validity and is not a valid tool for assessing the preventability of unplanned hospital admissions. The use of Expert Panels provides a more rigorous approach to assessing the preventability of such admissions.


Asunto(s)
Enfermedad Crónica , Hospitalización/estadística & datos numéricos , Evaluación de Resultado en la Atención de Salud , Anciano , Anciano de 80 o más Años , Australia , Femenino , Humanos , Masculino , Persona de Mediana Edad
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