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Mendeley readers
| Title |
Empirical aspects of record linkage across multiple data sets using statistical linkage keys: the experience of the PIAC cohort study
|
|---|---|
| Published in |
BMC Health Services Research, February 2010
|
| DOI | 10.1186/1472-6963-10-41 |
| Pubmed ID | |
| Authors |
Rosemary Karmel, Phil Anderson, Diane Gibson, Ann Peut, Stephen Duckett, Yvonne Wells |
| Abstract |
In Australia, many community service program data collections developed over the last decade, including several for aged care programs, contain a statistical linkage key (SLK) to enable derivation of client-level data. In addition, a common SLK is now used in many collections to facilitate the statistical examination of cross-program use. In 2005, the Pathways in Aged Care (PIAC) cohort study was funded to create a linked aged care database using the common SLK to enable analysis of pathways through aged care services. Linkage using an SLK is commonly deterministic. The purpose of this paper is to describe an extended deterministic record linkage strategy for situations where there is a general person identifier (e.g. an SLK) and several additional variables suitable for data linkage. This approach can allow for variation in client information recorded on different databases. |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 7% |
| Netherlands | 1 | 3% |
| Brazil | 1 | 3% |
| Unknown | 26 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 11 | 37% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Master | 4 | 13% |
| Professor > Associate Professor | 3 | 10% |
| Other | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 2 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 30% |
| Computer Science | 8 | 27% |
| Nursing and Health Professions | 2 | 7% |
| Social Sciences | 2 | 7% |
| Mathematics | 1 | 3% |
| Other | 4 | 13% |
| Unknown | 4 | 13% |