Determination of the informational content of symptoms in the dynamic processes of assessing the patient’s condition in e-health
Open Access
- 30 September 2021
- journal article
- Published by OU Scientific Route in EUREKA: Health Sciences
- No. 5,p. 47-60
- https://doi.org/10.21303/2504-5679.2021.001976
Abstract
The study is devoted to substantiating the tactics of choosing the signs of the patient's condition for diagnostic decision-making on corrective medical intervention in mobile medicine. The aim of the research: to study a creation of a methodology for determining the integral informativeness of the patient's symptoms during remote monitoring of his condition. Materials and methods: this article is based on search results in PubMed, Scopus, MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA articles published between January 1991 and January 2021 and containing the search terms “information technology”, “Mobile medicine”, “digital pathology” and “deep learning”, as well as the results of the authors' own research. The authors independently extracted data on concealment of distribution, consistency of distribution, blindness, completeness of follow-up, and interventions. Results: concluded that to determine the Informativeness of symptoms in mobile monitoring of patients, it is possible to use risk indicators of predicted conditions as a universal method. Given that the Informativeness of the patient's condition changes constantly, for online diagnosis of conditions during remote monitoring of the patient it is recommended to use the function of informative symptoms from time to time and use a set of approaches to assess the Informativeness of patient symptoms. It is proposed to use the strategy of diagnosis and treatment using probabilistic algorithms based on the values of the risk of complications of the pathological process, as well as the formulas of Kulbach and Shannon to determine individual trends in the pathological patient process. Conclusion: there was proposed to use risk indicators of predicted conditions as a universal method for determining the informational content of symptoms in mobile monitoring of patients.Keywords
This publication has 48 references indexed in Scilit:
- The effectiveness of medical assistant health coaching for low-income patients with uncontrolled diabetes, hypertension, and hyperlipidemia: protocol for a randomized controlled trial and baseline characteristics of the study populationBMC Family Practice, 2013
- The Effectiveness of Mobile-Health Technologies to Improve Health Care Service Delivery Processes: A Systematic Review and Meta-AnalysisPLoS Medicine, 2013
- The effect of mobile phone text-message reminders on Kenyan health workers' adherence to malaria treatment guidelines: a cluster randomised trialThe Lancet, 2011
- An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational StudiesMultivariate Behavioral Research, 2011
- How smartphones are changing the face of mobile and participatory healthcare: an overview, with example from eCAALYXBioMedical Engineering OnLine, 2011
- An Overview on Wireless Sensor Networks Technology and EvolutionSensors, 2009
- The Use of the Personal Digital Assistant (PDA) Among Personnel and Students in Health Care: A ReviewJournal of Medical Internet Research, 2008
- SMART--An Integrated Wireless System for Monitoring Unattended PatientsJournal of the American Medical Informatics Association, 2008
- Self-Powered Wireless Sensor Networks for Remote Patient Monitoring in HospitalsSensors, 2006
- Use of handheld computers in medical educationJournal of General Internal Medicine, 2006