Risk Information Management Resource (RIMR): modeling an approach to defending against military medical information assurance brain drain

Author(s):  
Willie E. Wright
1995 ◽  
Vol 28 (6) ◽  
pp. 361-376 ◽  
Author(s):  
Ken Chee Keung Law ◽  
Horace Ho Shing Ip ◽  
Siu Lok Chan

2018 ◽  
Vol 23 (2) ◽  
pp. 467-480 ◽  
Author(s):  
Yang Zou ◽  
Arto Kiviniemi ◽  
Stephen W. Jones ◽  
James Walsh

2014 ◽  
Vol 644-650 ◽  
pp. 3166-3169
Author(s):  
Ming Li ◽  
Shu Yuan Yang

The existing hospital information management system generally does not support remote access and the information sharing is low. In order to adapt to the needs of the development of medical information management, the hospital information management system should be developed based on B/S structure. The system should store staff basic information, outpatient and hospitalization reimbursement detail in the database; can timely reflect the patient fee in arrears; draw graphical statistics of the use of funds, the incidence of disease, drug usage information; can set reimbursement policy according to the conditions and can automatically submit an expense account settlement, fund collection, decomposition of annual and carry forward; show the real-time dynamic tracking information for ins and outs of supplies, equipment, and drugs, reduce the backlog and shortages.AFS.NET technology.


Author(s):  
Walid A. Afifi

The turn of the 21st century has seen an explosion of frameworks that account for individuals’ decisions to seek or avoid information related to health risks. The four dominant frameworks are Risk Perception Attitude Framework, the Risk Information Seeking and Process model, the Planned Risk Information Seeking Model, and the Theory of Motivated Information Management. A comparison of the constructs within each and an examination of the related empirical tests reveal important insights into (a) factors that have consistently been shown to shape these decisions across these approaches and (b) constructs in need of additional theorizing and empirical testing. Specifically, the analysis suggests that uncertainty, efficacy, affect, risk perceptions, and subjective norms all play crucial roles in accounting for decisions to seek or avoid risk-related information. However, inconsistencies in the direction of influence for uncertainty or information discrepancy, risk perceptions, and negative affect argue for the need for considerably more theoretical clarity and empirical rigor in investigations of the ways in which these experiences shape decision making in these contexts.


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