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Can mental health diagnoses in administrative data be used for research? A systematic review of the accuracy of routinely collected diagnoses

Overview of attention for article published in BMC Psychiatry, July 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Title
Can mental health diagnoses in administrative data be used for research? A systematic review of the accuracy of routinely collected diagnoses
Published in
BMC Psychiatry, July 2016
DOI 10.1186/s12888-016-0963-x
Pubmed ID
Authors

Katrina A. S. Davis, Cathie L. M. Sudlow, Matthew Hotopf

Abstract

There is increasing availability of data derived from diagnoses made routinely in mental health care, and interest in using these for research. Such data will be subject to both diagnostic (clinical) error and administrative error, and so it is necessary to evaluate its accuracy against a reference-standard. Our aim was to review studies where this had been done to guide the use of other available data. We searched PubMed and EMBASE for studies comparing routinely collected mental health diagnosis data to a reference standard. We produced diagnostic category-specific positive predictive values (PPV) and Cohen's kappa for each study. We found 39 eligible studies. Studies were heterogeneous in design, with a wide range of outcomes. Administrative error was small compared to diagnostic error. PPV was related to base rate of the respective condition, with overall median of 76 %. Kappa results on average showed a moderate agreement between source data and reference standard for most diagnostic categories (median kappa = 0.45-0.55); anxiety disorders and schizoaffective disorder showed poorer agreement. There was no significant benefit in accuracy for diagnoses made in inpatients. The current evidence partly answered our questions. There was wide variation in the quality of source data, with a risk of publication bias. For some diagnoses, especially psychotic categories, administrative data were generally predictive of true diagnosis. For others, such as anxiety disorders, the data were less satisfactory. We discuss the implications of our findings, and the need for researchers to validate routine diagnostic data.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 1%
United States 1 <1%
Unknown 135 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 35 25%
Student > Ph. D. Student 23 17%
Student > Master 13 9%
Other 10 7%
Student > Postgraduate 8 6%
Other 20 14%
Unknown 29 21%
Readers by discipline Count As %
Medicine and Dentistry 33 24%
Psychology 15 11%
Social Sciences 13 9%
Nursing and Health Professions 10 7%
Neuroscience 7 5%
Other 20 14%
Unknown 40 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 01 June 2018.
All research outputs
#5,036,497
of 24,072,790 outputs
Outputs from BMC Psychiatry
#1,937
of 5,042 outputs
Outputs of similar age
#88,607
of 372,070 outputs
Outputs of similar age from BMC Psychiatry
#39
of 105 outputs
Altmetric has tracked 24,072,790 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,042 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one has gotten more attention than average, scoring higher than 61% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 372,070 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 105 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.