Analyzing the Impact of Digital Health Communication on Patient Engagement and Treatment Adherence DOI
Uma Bhardwaj,

H. Malathi,

Vinima Gambhir

и другие.

Deleted Journal, Год журнала: 2024, Номер 3, С. 492 - 492

Опубликована: Дек. 31, 2024

Modern healthcare systems now strongly rely on digital health communication to get patients more engaged in their treatment and assist them stay with prescriptions. Healthcare professionals may have tailored continuous interactions since so many individuals use mobile applications, telemedicine systems, data. With an eye how technology-based solutions can enable follow regimens for chronic illnesses preventative care, this paper investigates influences patient engagement commitment. This examines well various technologies text notes, video chats, real-time tracking help medical interact one another. The research also successfully treatments as behaviour, drive, overall pleasure regard care. uses a lot of current research, polls, case studies find the main things that make work healthcare. These are ease use, accessibility, perceived value, trust technology. results show makes interested by giving personalised material, letting connect at right time, chances learn. Digital platforms been shown people stick reminding them, progress, workers offer support when they used plans. Even though there benefits, still big problems need be fixed, like not knowing technology, worries about privacy, unequal access tools.

Язык: Английский

A Comprehensive Review of Patient Scheduling Techniques with Uncertainty DOI
Vaishali Choudhary, Apoorva Shastri,

Shivam Silswal

и другие.

Опубликована: Янв. 1, 2024

The advancement of patient scheduling techniques plays a crucial role in cost optimization and enhancing the flow patients. Efficient ensures timely allocation resources treatment, leading to improved resource utilization minimized waiting times. dynamic unpredictable nature healthcare system introduces uncertainty, making it essential address this factor when implementing processes for real-world problems. In recent years, there have been many new ways implement advance methods hospitals make sure are used with optimum utilization. Various isolated because they solve each problem independently. Combining two or more can be beneficial utilize their advantages collectively. This chapter provides an overview latest scheduling, specifically emphasizing on admission nurse operating room along recovery ICU while considering both scenarios without uncertainty. purpose is assist researchers by highlighting developments from previous literature understanding trends future directions.

Язык: Английский

Процитировано

1

A forecasting tool for a hospital to plan inbound transfers of COVID-19 patients from other regions DOI Creative Commons
Mehmet A. Begen, Felipe F. Rodrigues,

Tim Rice

и другие.

BMC Public Health, Год журнала: 2024, Номер 24(1)

Опубликована: Фев. 16, 2024

Abstract Background In April 2021, the province of Ontario, Canada, was at peak its third wave COVID-19 pandemic. Intensive Care Unit (ICU) capacity in Toronto metropolitan area insufficient to handle local COVID patients. As a result, some patients from were transferred other regions. Methods A spreadsheet-based Monte Carlo simulation tool built help large tertiary hospital plan and make informed decisions about number transfer it could accept hospitals. The model implemented Microsoft Excel enable be widely distributed easily used. estimates probability that each ward will overcapacity percentiles utilization daily for one-week planning horizon. Results used May 2021 February 2022 support ability transfers also ensure adequate inpatient bed human resources response various COVID-related scenarios, such as changes admission rates, managing impact intra-hospital outbreaks balancing with planned activity. Conclusions Coordination between hospitals necessary due high stress on health care system. simple can understand patient improve confidence leaders when making decisions. helpful investigating operational scenarios may preparing future or public emergencies.

Язык: Английский

Процитировано

1

Integrating discrete-event simulation and artificial intelligence for shortening bed waiting times in hospitalization departments during respiratory disease seasons DOI
Miguel Ortíz‐Barrios, Alessio Ishizaka, Maria Barbati

и другие.

Computers & Industrial Engineering, Год журнала: 2024, Номер 194, С. 110405 - 110405

Опубликована: Июль 25, 2024

Язык: Английский

Процитировано

1

A Comprehensive Review of Patient Scheduling Techniques with Uncertainty DOI
Vaishali Choudhary, Apoorva Shastri,

Shivam Silswal

и другие.

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

1

An explainable decision model based on extended belief-rule-based systems to predict admission to the intensive care unit during COVID-19 breakout DOI
Jing Zheng, Long-Hao Yang,

Ying‐Ming Wang

и другие.

Applied Soft Computing, Год журнала: 2023, Номер 149, С. 110961 - 110961

Опубликована: Окт. 19, 2023

Язык: Английский

Процитировано

3

A Hybrid Fuzzy MCDM Approach to Identify the Intervention Priority Level of Covid-19 Patients in the Emergency Department: A Case Study DOI

Armando Perez-Aguilar,

Miguel Ortíz‐Barrios, Pablo Pancardo

и другие.

Lecture notes in computer science, Год журнала: 2023, Номер unknown, С. 284 - 297

Опубликована: Янв. 1, 2023

Язык: Английский

Процитировано

1

A Machine Learning Model for Predicting the Risk of Perinatal Mortality in Low-and-Middle-Income Countries: A Case Study DOI
Sebastián Arias-Fonseca, Miguel Ortíz‐Barrios, Alexandros Konios

и другие.

Lecture notes in computer science, Год журнала: 2024, Номер unknown, С. 233 - 250

Опубликована: Янв. 1, 2024

Язык: Английский

Процитировано

0

A Hybrid Mathematical-Simulation Approach to Hospital Beds Capacity Optimization for COVID-19 Pandemic Conditions DOI Creative Commons
Reza Maleki, Mohammad R. Taghizadeh, Rohollah Ghasemi

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Июнь 20, 2024

Abstract The Covid-19 pandemic was an unforeseen threat to human survival, and the efficiency of health sector faced a severe challenge. lack hospital beds one most critical concerns, optimizing capacity considered key issues. Due ageing population occasional occurrence environmental crises, demand for services need improved planning administration are increasing daily. Therefore, optimal allocation resources, particularly number beds, essential criterion medical center’s capacity, can substantially reduce patient waiting time treatment costs improve services. An ideal multi-objective integer programming problem is presented in this study reducing length stay stay. also considers constraints relating circumstances, given Corona's prevalence. Moreover, answer obtained using simulation model, mathematical optimization, simulation-based optimization approach. For purpose, modelling used minimize patients' time, hospitalizations, maintenance existing purchasing new bed. Following that, real-world conditions were introduced into model information acquired from month hospitalization patients during Coronavirus outbreak at Imam Hussein Hospital Tehran. After comparing simulated models, OptQuest technique revealed beds.

Язык: Английский

Процитировано

0

A Case Study on AI to Automate Simulation Modelling DOI

Uchechukwu Obinwanne,

Wenying Feng

Communications in computer and information science, Год журнала: 2024, Номер unknown, С. 179 - 186

Опубликована: Окт. 18, 2024

Язык: Английский

Процитировано

0

A Hybrid Mathematical-Simulation Approach to Hospital Beds Capacity Optimization for COVID-19 Pandemic Conditions DOI
Reza Maleki, Mohammad R. Taghizadeh, Rohollah Ghasemi

и другие.

Operations Research Forum, Год журнала: 2024, Номер 5(4)

Опубликована: Ноя. 14, 2024

Язык: Английский

Процитировано

0