| Title |
Using Administrative Data to Examine Health Disparities and Outcomes in Neurological Diseases of the Elderly
|
|---|---|
| Published in |
Current Neurology and Neuroscience Reports, October 2015
|
| DOI | 10.1007/s11910-015-0595-4 |
| Pubmed ID | |
| Authors |
Allison W. Willis |
| Abstract |
The fields of neurodegenerative disease and dementia research have grown considerably in the last several decades. Due to tremendous efforts of basic and clinical research scientists, we know a great deal about dementia risk factors and have multiple treatment options. Clinician recognition of cognitive impairment has increased considerably, national policies which support screening for and documenting cognitive dysfunction now exist, and public awareness of neurodegenerative disease has never been greater. These conditions promote (and demand) the growth of translational epidemiology and health services research, which focuses on examining outcomes in groups of individuals as a function of health care experiences. This review discusses the use of administrative data to answer health care outcomes and disparities questions in dementia. Of particular interest are publically available datasets that contain varying amounts of diagnostic, clinical, pharmacy, and patient information. Methodological challenges that are frequently encountered and must be understood to minimize biased inference are also discussed. |
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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 57 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 14% |
| Student > Master | 8 | 14% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Bachelor | 6 | 11% |
| Other | 5 | 9% |
| Other | 8 | 14% |
| Unknown | 16 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 25% |
| Psychology | 7 | 12% |
| Nursing and Health Professions | 7 | 12% |
| Neuroscience | 2 | 4% |
| Social Sciences | 2 | 4% |
| Other | 7 | 12% |
| Unknown | 18 | 32% |
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 07 October 2015.
All research outputs
#18,428,159
of 22,829,683 outputs
Outputs from Current Neurology and Neuroscience Reports
#762
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Outputs of similar age
#197,664
of 274,923 outputs
Outputs of similar age from Current Neurology and Neuroscience Reports
#11
of 13 outputs
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