NoSQL Technologies for Real Time (Patient) Monitoring

Healthcare Ethics and Training ◽

10.4018/978-1-5225-2237-9.ch053 ◽

2017 ◽

pp. 1112-1140

Author(s):

Ciprian Dobre ◽

Fatos Xhafa

Keyword(s):

Data Storage ◽

Medical Data ◽

Evidence Based ◽

Health Administration ◽

Public Health Administration ◽

Medical Practitioners ◽

Pros And Cons ◽

Great Availability ◽

Storage Technologies ◽

Health Applications

Today we witness a growing change in how public health administration thinks about medical data. We have slowly moved from paper-based patient records to digitally storing medical data, in support for advanced evidence-based mining and decision support processes. With this change comes great responsibility, among which efficient storing and accessing the health status of the patient is particularly important. In this chapter, the authors analyze current storage technologies for storing medical data. We are witnessing a shift from traditional relational database support to NoSQL technologies capable of offering great availability and scalability options, and back to the mixture between the SQL and NoSQL worlds, and scalable SQL databases. All these alternatives come with their own pros and cons, which the authors carefully analyze. They believe that their survey will help medical practitioners and developers of health applications make a more informed decision when designing medical data storage support.

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NoSQL Technologies for Real Time (Patient) Monitoring

Medical Imaging ◽

10.4018/978-1-5225-0571-6.ch037 ◽

2017 ◽

pp. 932-961 ◽

Cited By ~ 1

Author(s):

Ciprian Dobre ◽

Fatos Xhafa

Keyword(s):

Data Storage ◽

Medical Data ◽

Evidence Based ◽

Health Administration ◽

Public Health Administration ◽

Medical Practitioners ◽

Pros And Cons ◽

Great Availability ◽

Storage Technologies ◽

Health Applications

Today we witness a growing change in how public health administration thinks about medical data. We have slowly moved from paper-based patient records to digitally storing medical data, in support for advanced evidence-based mining and decision support processes. With this change comes great responsibility, among which efficient storing and accessing the health status of the patient is particularly important. In this chapter, the authors analyze current storage technologies for storing medical data. We are witnessing a shift from traditional relational database support to NoSQL technologies capable of offering great availability and scalability options, and back to the mixture between the SQL and NoSQL worlds, and scalable SQL databases. All these alternatives come with their own pros and cons, which the authors carefully analyze. They believe that their survey will help medical practitioners and developers of health applications make a more informed decision when designing medical data storage support.

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WITHWomen: User Centered Approach to the Design and Development of a suite of Intimate Partner Violence Screening and Safety Planning Web-Applications (Preprint)

10.2196/preprints.24114 ◽

2020 ◽

Author(s):

Patricia O'Campo ◽

Alisa Velonis ◽

Pearl Buhariwala ◽

Janisha Kamalanathan ◽

Maha Awaiz Hassan

Keyword(s):

Partner Violence ◽

Web Applications ◽

Lessons Learned ◽

Evidence Based ◽

Safety Planning ◽

Future Design ◽

Mhealth Technology ◽

The Right ◽

Safe Access ◽

Health Applications

BACKGROUND The popularity of mHealth technology has resulted in the development of numerous applications for almost every type of self-improvement or disease management. M- and e-health solutions for increasing awareness about and safety around partner violence is no exception. OBJECTIVE These applications allow women to control access to these resources and provide unlimited, and with the right design features, safe access when these resources are needed. Few applications, however, have been designed in close collaboration with intended users to ensure relevance and effectiveness. METHODS We report here on the design of a pair of evidence-based m- and e-health applications to facilitate early identification of unsafe relationship behaviors and tailored safety planning to reduce harm from violence including the methods by which we collaborated with and sought input from population of intended users. RESULTS The demographic characteristics of those who participated in the various surveys and interviews to inform the development of our screening and safety-decision support app are presented in (Table 2). CONCLUSIONS Finally, we share challenges we faced and lessons learned that might inform future design efforts of m- and e-health evidence-based applications.

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A stochastic time-delayed model for the effectiveness of Moroccan COVID-19 deconfinement strategy

Mathematical Modelling of Natural Phenomena ◽

10.1051/mmnp/2020040 ◽

2020 ◽

Vol 15 ◽

pp. 50 ◽

Cited By ~ 1

Author(s):

Houssine Zine ◽

Adnane Boukhouima ◽

El Mehdi Lotfi ◽

Marouane Mahrouf ◽

Delfim F.M. Torres ◽

...

Keyword(s):

Public Health ◽

Health Administration ◽

Policy Makers ◽

Public Health Administration ◽

Additional Degree ◽

Epidemiological Trend ◽

The Impact ◽

Near Future ◽

Stochastic Time ◽

Delayed Model

Coronavirus disease 2019 (COVID-19) poses a great threat to public health and the economy worldwide. Currently, COVID-19 evolves in many countries to a second stage, characterized by the need for the liberation of the economy and relaxation of the human psychological effects. To this end, numerous countries decided to implement adequate deconfinement strategies. After the first prolongation of the established confinement, Morocco moves to the deconfinement stage on May 20, 2020. The relevant question concerns the impact on the COVID-19 propagation by considering an additional degree of realism related to stochastic noises due to the effectiveness level of the adapted measures. In this paper, we propose a delayed stochastic mathematical model to predict the epidemiological trend of COVID-19 in Morocco after the deconfinement. To ensure the well-posedness of the model, we prove the existence and uniqueness of a positive solution. Based on the large number theorem for martingales, we discuss the extinction of the disease under an appropriate threshold parameter. Moreover, numerical simulations are performed in order to test the efficiency of the deconfinement strategies chosen by the Moroccan authorities to help the policy makers and public health administration to make suitable decisions in the near future.

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