| Title |
Open Issues in Intelligent Personal Health Record – An Updated Status Report for 2012
|
|---|---|
| Published in |
Journal of Medical Systems, April 2013
|
| DOI | 10.1007/s10916-013-9943-6 |
| Pubmed ID | |
| Authors |
Gang Luo |
| Abstract |
To improve the capability and usability of the personal health record (PHR) as a tool to empower consumers in the management of their own health, we have proposed the concept of an intelligent PHR (iPHR) and built a prototype iPHR system with four functions. These four functions use various health knowledge and computer science techniques to automatically provide users with personalized healthcare information to facilitate their well-being. This paper discusses several open issues in iPHR, including two enhancements to an existing function and two potential new functions. The two enhancements are for automatically compiling relevant self-care activities for each health issue and automatically identifying contraindicated self-care activities, respectively. One potential new function is personalized search for individual healthcare providers. Another potential new function is personalized local search for health-related services to help maintain patients in their homes. We include some preliminary thoughts on how to address these open issues with the hope to stimulate future research work on iPHR. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 73 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 3% |
| United States | 2 | 3% |
| Malaysia | 1 | 1% |
| Brazil | 1 | 1% |
| Unknown | 67 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 23% |
| Student > Master | 14 | 19% |
| Researcher | 10 | 14% |
| Other | 5 | 7% |
| Student > Doctoral Student | 4 | 5% |
| Other | 14 | 19% |
| Unknown | 9 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 22% |
| Computer Science | 15 | 21% |
| Nursing and Health Professions | 10 | 14% |
| Social Sciences | 7 | 10% |
| Engineering | 5 | 7% |
| Other | 7 | 10% |
| Unknown | 13 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 April 2013.
All research outputs
#18,336,865
of 22,707,247 outputs
Outputs from Journal of Medical Systems
#804
of 1,144 outputs
Outputs of similar age
#150,390
of 198,480 outputs
Outputs of similar age from Journal of Medical Systems
#5
of 8 outputs
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