DIABETEX — a decision support system for therapy of type I diabetic patients

Zahlmann, Gudrun; Franczykova, Maria; Henning, G.; Strube, Michael; Hüttl, Irmtraud; Hummel, Ingrid; Bruns, W

doi:10.1016/0169-2607(90)90112-m

Cited by 12 publications

(3 citation statements)

References 3 publications

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“…Zahlmann et al [ 38 ] found a significant decrease in HbA 1c values with a decision support system ('DIABETEX') and Horan et al [ 39 ] reported a significant improvement in the level of blood glucose with the use of a computer-assisted system designed to promote self-management of insulin.…”

Section: Resultsmentioning

confidence: 99%

Application of biomedical informatics to chronic pediatric diseases: a systematic review

Moeinedin

Moineddin

Jadad

et al. 2009

BMC Med Inform Decis Mak

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BackgroundChronic diseases affect millions of children worldwide leading to substantial disease burden to the children and their families as well as escalating health care costs. The increasing trend in the prevalence of complex pediatric chronic diseases requires innovative and optimal delivery of care. Biomedical informatics applications play an important role in improving health outcomes while being cost-effective. However, their utility in pediatric chronic diseases has not been studied in a comprehensive and systematic way. The objective of this study was to conduct a systematic review of the effects of biomedical informatics applications in pediatric chronic diseases.MethodsA comprehensive literature search was conducted using MEDLINE, the Cochrane Library and EMBASE databases from inception of each database to September 2008. We included studies of any methodological type and any language that applied biomedical informatics to chronic conditions in children and adolescents 18 years of age or younger. Two independent reviewers carried out study selection and data extraction. Quality assessment was performed using a study design evaluation instrument to appraise the strength of the studies and their methodological adequacy. Because of heterogeneity in the conditions and outcomes we studied, a formal meta-analysis was not performed.ResultsBased on our search strategy, 655 titles and abstracts were reviewed. From this set we identified 27 relevant articles that met our inclusion criteria. The results from these studies indicated that biomedical informatics applications have favourable clinical and patient outcomes including, but not limited to, reduced number of emergency room visits, improved knowledge on disease management, and enhanced satisfaction. Seventy percent of reviewed papers were published after year 2000, 89% of users were patients and 11% were either providers or caregivers. The majority (96%) of the selected studies reported improved outcomes.ConclusionPublished studies suggested positive impacts of informatics predominantly in pediatric asthma. As electronic tools become more widely adopted, there will be opportunities to improve patient care in a wide range of chronic illnesses through informatics solutions.

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Section: Resultsmentioning

confidence: 99%

Application of biomedical informatics to chronic pediatric diseases: a systematic review

Moeinedin

Moineddin

Jadad

et al. 2009

BMC Med Inform Decis Mak

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“…The DIABETEX system was tested on data from 12 adults with T1D and demonstrated a 66% full agreement with endocrinologist-recommended adjustments for meal-related doses, and a 42% full agreement for basal-related doses [53]. The DIABETEX program was later evaluated in children and was reported to improve HbA1c from 5.85% to 5.0%, and reduced the number of measured hypoglycemic events in children from 143 to 58 during a 12-month evaluation period [54].…”

Section: Early Approaches At Decision Support System Designmentioning

confidence: 99%

Artificial Intelligence in Decision Support Systems for Type 1 Diabetes

Tyler

Jacobs

2020

Sensors

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Type 1 diabetes (T1D) is a chronic health condition resulting from pancreatic beta cell dysfunction and insulin depletion. While automated insulin delivery systems are now available, many people choose to manage insulin delivery manually through insulin pumps or through multiple daily injections. Frequent insulin titrations are needed to adequately manage glucose, however, provider adjustments are typically made every several months. Recent automated decision support systems incorporate artificial intelligence algorithms to deliver personalized recommendations regarding insulin doses and daily behaviors. This paper presents a comprehensive review of computational and artificial intelligence-based decision support systems to manage T1D. Articles were obtained from PubMed, IEEE Xplore, and ScienceDirect databases. No time period restrictions were imposed on the search. After removing off-topic articles and duplicates, 562 articles were left to review. Of those articles, we identified 61 articles for comprehensive review based on algorithm evaluation using real-world human data, in silico trials, or clinical studies. We grouped decision support systems into general categories of (1) those which recommend adjustments to insulin and (2) those which predict and help avoid hypoglycemia. We review the artificial intelligence methods used for each type of decision support system, and discuss the performance and potential applications of these systems.

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“…Sie setzen ein hartes Regime täglicher Messungen voraus, nur dann können die Algorithmen sinnvolle Werte liefern.Die Ergebnisse der ersten beiden Testphasen sind in[7] ausgeführt. Diese sehr positiven Ergebnisse konnten auch für dieTabelle 1: HbA lc -Werte in % für die Patientengruppe Kinder über den langen Zeitraum sank die Akzeptanz der EntscheidungsvorschlMge durch den medizinischen Experten.…”

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Komplexes Therapieführungssystem Für Typ-I-Diabetiker - Diabetex

Zahimann¹,

Abdin²,

Kaeding³

et al. 1991

Biomedizinische Technik/Biomedical Engineering

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DIABETEX ist ein wissensbasiertes, rechnergestütztes System zur Entscheidungsunterstützung für die ambulante Behandlung von Typ-I-Diabetikern. Vier Wissensbasen enthalten das medizinische und technische Wissen zur Therapieführung von Kindern/Jugendlichen, Schwangeren Erwachsenen mit konventioneller Therapie und Pumpenpatienten. DIABETEX beinhaltet einen komplexen Teil für die Entscheidungsunterstützung des Arztes und einen individuellen Teil in Form eines Patientenrechners. Das System wurde in 3 Phasen über mehr als 3 Jahre erfolgreich getestet. EINLEITUNG

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DIABETEX — a decision support system for therapy of type I diabetic patients

Cited by 12 publications

References 3 publications

Application of biomedical informatics to chronic pediatric diseases: a systematic review

Application of biomedical informatics to chronic pediatric diseases: a systematic review

Artificial Intelligence in Decision Support Systems for Type 1 Diabetes

Komplexes Therapieführungssystem Für Typ-I-Diabetiker - Diabetex

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