AI Article Synopsis
- Identified anonymous potential participants for a depression trial using routine health data, assessing feasibility and ethical issues.
- Used Swansea University's SAIL database and SQL to develop an algorithm for participant eligibility, achieving high accuracy in identifying 867 candidates from a population of 37,263.
- Results showed strong agreement among clinicians on eligibility, indicating this method could effectively enhance future recruitment efforts for clinical trials.
Article Abstract
Background: Recruitment to clinical trials can be challenging. We identified anonymous potential participants to an existing pragmatic randomised controlled depression trial to assess the feasibility of using routinely collected data to identify potential trial participants. We discuss the strengths and limitations of this approach, assess its potential value, report challenges and ethical issues encountered.
Methods: Swansea University's Health Information Research Unit's Secure Anonymised Information Linkage (SAIL) database of routinely collected health records was interrogated, using Structured Query Language (SQL). Read codes were used to create an algorithm of inclusion/exclusion criteria with which to identify suitable anonymous participants. Two independent clinicians rated the eligibility of the potential participants' identified. Inter-rater reliability was assessed using the kappa statistic and inter-class correlation.
Results: The study population (N = 37263) comprised all adults registered at five general practices in Swansea UK. Using the algorithm 867 anonymous potential participants were identified. The sensitivity and specificity results > 0.9 suggested a high degree of accuracy from the algorithm. The inter-rater reliability results indicated strong agreement between the confirming raters. The Intra Class Correlation Coefficient (Cronbach's Alpha) > 0.9, suggested excellent agreement and Kappa coefficient > 0.8; almost perfect agreement.
Conclusions: This proof of concept study showed that routinely collected primary care data can be used to identify potential participants for a pragmatic randomised controlled trial of folate augmentation of antidepressant therapy for the treatment of depression. Further work will be needed to assess generalisability to other conditions and settings and the inclusion of this approach to support Electronic Enhanced Recruitment (EER).
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2864261 | PMC |
| http://dx.doi.org/10.1186/1745-6215-11-39 | DOI Listing |
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