| Title |
Personalized Decision Support in Type 2 Diabetes Mellitus: Current Evidence and Future Directions
|
|---|---|
| Published in |
Current Diabetes Reports, November 2012
|
| DOI | 10.1007/s11892-012-0348-6 |
| Pubmed ID | |
| Authors |
Michael J. Wilkinson, Aviva G. Nathan, Elbert S. Huang |
| Abstract |
The management of type 2 diabetes comprises a complex series of medical decisions regarding goals of care, self-care behaviors, and medical treatments. The quality of these medical decisions is critical to determining whether an individual diabetes patient is treated appropriately, overtreated, or undertreated. It is hypothesized that the quality of these medical decisions can be enhanced by personalized decision support tools that summarize patient clinical characteristics, treatment preferences, and ancillary data at the point of care. We describe the current state of personalized diabetes decision support on the basis of 13 recently described tools. Three tools provided support for personalized decisions based on preferences, while the remaining 10 provided support for treatment decisions designed to achieve standard diabetes goals. For the tools that supported personalized decisions, patient participation in medical decisions improved. Future decision support tools must be designed to account for both clinical characteristics and patient preferences. |
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 % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Mexico | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 58 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 23% |
| Researcher | 10 | 17% |
| Student > Ph. D. Student | 8 | 13% |
| Student > Bachelor | 5 | 8% |
| Student > Postgraduate | 4 | 7% |
| Other | 10 | 17% |
| Unknown | 9 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 27% |
| Computer Science | 7 | 12% |
| Nursing and Health Professions | 6 | 10% |
| Psychology | 6 | 10% |
| Engineering | 5 | 8% |
| Other | 8 | 13% |
| Unknown | 12 | 20% |
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 20 November 2012.
All research outputs
#18,320,524
of 22,685,926 outputs
Outputs from Current Diabetes Reports
#771
of 1,005 outputs
Outputs of similar age
#214,215
of 276,060 outputs
Outputs of similar age from Current Diabetes Reports
#20
of 25 outputs
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