ML-Enabled Informed Intervention for Crowdsourcing-Based Optimization of Medical Resources

2022 ◽  
pp. 291-315
Author(s):  
Irfan Siddavatam ◽  
Ashwini Dalvi ◽  
Abhishek Patel ◽  
Aditya Panchal ◽  
Aditya S. Vedpathak ◽  
...  
Keyword(s):  
Data Management ◽  
Patient Data ◽  
Hospital Data ◽  
Healthcare Resources ◽  
Medical Resources ◽  
Demand And Supply ◽  
Cooperative Approach ◽  
Open Mind ◽  
Medical Emergencies ◽  
Technology Assistance

It is said that every adversity presents the opportunity to grow. The current pandemic is a lesson to all healthcare infrastructure stakeholders to look at existing setups with an open mind. This chapter's proposed solution offers technology assistance to manage patient data effectively and extends the hospital data management system's capability to predict the upcoming need for healthcare resources. Further, the authors intend to supplement the proposed solution with crowdsourcing to meet hospital demand and supply for unprecedented medical emergencies. The proposed approach would demonstrate its need in the current pandemic scenario and prepare the healthcare infrastructure with a more streamlined and cooperative approach than before.

Database Considerations for an ICU Patient Data Management System

1991 ◽  
Author(s):  
N. Fumai ◽  
C. Collet ◽  
M. Petroni ◽  
K. Roger ◽  
E. Saab ◽  
...  
Keyword(s):  
Data Management ◽  
Real Time ◽  
Data Storage ◽  
Relational Database ◽  
Management System ◽  
Patient Data ◽  
Patient Data Management System ◽  
Data Management System ◽  
Data Types ◽  
Management Structure

Abstract A Patient Data Management System (PDMS) is being developed for use in the Intensive Care Unit (ICU) of the Montreal Children’s Hospital. The PDMS acquires real-time patient data from a network of physiological bedside monitors and facilitates the review and interpretation of this data by presenting it as graphical trends, charts and plots on a color video display. Due to the large amounts of data involved, the data storage and data management processes are an important task of the PDMS. The data management structure must integrate varied data types and provide database support for different applications, while preserving the real-time acquisition of network data. This paper outlines a new data management structure which is based primarily on OS/2’s Extended Edition relational database. The relational database design is expected to solve the query shortcomings of the previous data management structure, as well as offer support for security and concurrency. The discussion will also highlight future advantages available from a network implementation.

Personal Cloud System for Hospital Data Management to Store COVID-19 Patients Records

2021 ◽  
pp. 49-77
Author(s):  
Mousmi Ajay Chaurasia ◽  
Mohammed Usamah Moin ◽  
Syed Azeem Uddin ◽  
Mohammed Abdul Shoaib
Keyword(s):  
Data Management ◽  
Cloud System ◽  
Hospital Data

On Educating about Medical Data Management

2007 ◽  
Vol 46 (01) ◽  
pp. 74-79 ◽  
Author(s):  
P. Knaup ◽  
F. Leiner ◽  
R. Haux
Keyword(s):  
Data Management ◽  
Clinical Data ◽  
Medical Data ◽  
Patient Data ◽  
Management Systems ◽  
Multiple Use ◽  
Data Management Systems ◽  
Medical Coding ◽  
Medical Data Management ◽  
Coding Systems

Summary Objectives: To summarize background, challenges, objectives, and methods for the usability of patient data, in particular with respect to their multiple use, and to point out how to lecture medical data management. Methods: Analyzing the literature, providing an example based on Simpson’s paradox and summarizing research and education in the field of medical data management, respectively health information management (in German: Medizinische Dokumentation). Results: For the multiple use of patient data, three main categories of use can be identified: patientoriented (or casuistic) analysis, patient-group reporting, and analysis for clinical studies. A so-called documentation protocol, related to study plans in clinical trials, supports the multiple use of data from the electronic health record in order to obtain valid, interpretable results. Lectures on medical data management may contain modules on introduction, basic concepts of clinical data management and coding systems, important medical coding systems (e.g. ICD, SNOMED, TNM, UMLS), typical medical documentation systems (e.g. on patient records, clinical and epidemiological registers), utilization of clinical data management systems, planning of medical coding systems and of clinical data management systems, hospital information systems and the electronic patient record, and on data management in clinical studies. Conclusion: Usability, the ultimate goal of recording and managing patient data, requires, besides technical considerations, in addition appropriate methodology on medical data management, especially if data is intended to be used for multiple purposes, e.g. for patient care and quality management and clinical research. Medical data management should be taught in health and biomedical informatics programs.

An evaluation of patient data management systems in dutch intensive care

1998 ◽  
Vol 24 (2) ◽  
pp. 167-171 ◽  
Author(s):  
N. F. de Keizer ◽  
C. P. Stoutenbeek ◽  
L. A. J. B. W. Hanneman ◽  
E. de Jonge
Keyword(s):  
Intensive Care ◽  
Data Management ◽  
Patient Data ◽  
Management Systems ◽  
Data Management Systems ◽  
Patient Data Management Systems
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