Public Health Decision Support Systems

2020 ◽  
pp. 349-365
Author(s):  
Brian E. Dixon ◽  
Hadi Kharrazi ◽  
Sridhar R. Papagari Sangareddy
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Public Health Decision ◽  
Health Decision

scholarly journals Using participatory design to develop (public) health decision support systems through GIS

2007 ◽  
Vol 6 (1) ◽  
pp. 53 ◽  
Author(s):  
S. Michelle Driedger ◽  
Anita Kothari ◽  
Jason Morrison ◽  
Michael Sawada ◽  
Eric J Crighton ◽  
...  
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support Systems ◽  
Participatory Design ◽  
Support Systems ◽  
Public Health Decision ◽  
Health Decision

scholarly journals The Changing Nature of Clinical Decision Support Systems: a Focus on Consumers, Genomics, Public Health and Decision Safety

2009 ◽  
Vol 18 (01) ◽  
pp. 84-95 ◽  
Author(s):  
A. Y. S. Lau ◽  
G. Tsafnat ◽  
V. Sintchenko ◽  
F. Magrabi ◽  
E. Coiera
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Genetic Data ◽  
Clinical Decision ◽  
Translational Bioinformatics ◽  
The Impact

Summary Objectives To review the recent research literature in clinical decision support systems (CDSS). Methods A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. Results In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physicianorderentry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. Conclusions CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.

E-Health Decision Support Systems for the Diagnosis of Dementia Diseases

2013 ◽  
pp. 84-97
Author(s):  
Isabella Castiglioni ◽  
Maria Carla Gilardi ◽  
Francesca Gallivanone
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Diagnostic Tools ◽  
Diagnostic Process ◽  
Dementia Patients ◽  
Health Decision ◽  
Diagnosis Of Dementia ◽  
Dementia Diseases

The increase of incidence and prevalence of dementia diseases makes urgent the clinical community to be supported in the difficult diagnostic process of dementia patients. E-health decision support systems, based on innovative algorithms able to extract information from in vivo neuroimaging studies, can make a quite different way to perform neurological diagnosis and enlarge domains and actors involved in the diagnostic process. A number of image-processing methods that extract potential biomarkers from the in vivo neuroimaging studies have been proposed (e.g. volume segmentation, voxel-based statistical mapping). A number of new shape descriptors have also been developed (e.g. texture-based). Other approaches (e.g. machine learning, pattern recognition) have been proven effective, for both structural and functional data, in making automatic diagnoses. The integration of these sophisticated diagnostic tools into secure, efficient, and wide e-infrastructures is the prerequisite for the real implementation of e-health support services to the clinical and industrial communities managing dementia patients.

scholarly journals BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment

Appetite ◽  
2020 ◽  
pp. 104924
Author(s):  
Christos Diou ◽  
Ioannis Sarafis ◽  
Vasileios Papapanagiotou ◽  
Leonidas Alagialoglou ◽  
Irini Lekka ◽  
...  
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Local Environment ◽  
Public Health Decision ◽  
Obesogenic Behaviors ◽  
Health Decision

Data Standards for Mental Health Decision Support Systems: Mental Health Service Reports

1989 ◽  
Author(s):  
Walter A. Leginski ◽  
Colette Croze ◽  
John Driggers ◽  
Shirley Dumpman ◽  
Dennis Geertsen ◽  
...  
Keyword(s):  
Mental Health ◽  
Decision Support ◽  
Mental Health Service ◽  
Health Service ◽  
Decision Support Systems ◽  
Support Systems ◽  
Data Standards ◽  
Health Decision

Strengthening Implementation of Guidelines at Primary Health Care

2016 ◽  
pp. 133-151 ◽  
Author(s):  
V. Horner ◽  
A. Coleman
Keyword(s):  
Health Care ◽  
Primary Health Care ◽  
Decision Support ◽  
Decision Support Systems ◽  
Health Care Providers ◽  
Support Systems ◽  
Dissemination Strategy ◽  
Primary Health ◽  
Health Decision ◽  
Care Information

Implementation of guidelines in the health system is a complex and considerable undertaking. After the health administration has developed guidelines, a dissemination strategy needs to be put in place. Dissemination involves distribution of printed guidelines booklets, training of health care providers, provision of the equipment needed for implementing the guidelines, improvements to facilities, and supervision and monitoring by managers. This chapter reports on the Basic Antenatal Care Information System (Bacis) study in South Africa which pertains to an e-health decision support systems that is intended as an aid for nurses and managers at primary health care. The Bacis program study is important because there are few published studies from developing countries on implementation of e-health decision support systems at primary health care and their effectiveness in improving care.

Clinical Decision Support Systems

2021 ◽  
pp. 64-73
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Medical Informatics ◽  
Clinical Decision Support ◽  
Support System ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Health Decision ◽  
Software Development Methodologies

The BACIS program is an example of an e-health decision support system, and therefore a chapter focusing on the topic of decision support systems is needed as part of the background and context to the BACIS program study. The chapter begins with a discussion of the design of decision support systems. In this discussion, the software development methodologies used in their development is explained. Then various architectures for their design are considered. This is followed by a section on implementation of decision support systems in developing country contexts. The chapter closes with a discussion of the Clinical Decision Support (CDS) roadmap of the International Medical Informatics Association.

Sign in / Sign up

Export Citation Format

Share Document