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OBJECTIVES: To develop a new model for patient recruitment that harnessed the full potential of Electronic Health Records (EHRs). Gaining access to potential participants' health records to assess their eligibility for studies and allow an approach about participation ('consent for contact') is ethically, legally and technically challenging, given that medical data are usually restricted to the patient's clinical team. The research objective was to design a model for identification and recruitment to overcome some of these challenges as well as reduce the burdensome (and/or time consuming) gatekeeper role of clinicians in determining who is appropriate or not to participate in clinical research. SETTING: Large secondary mental health services context, UK. PARTICIPANTS: 2106 patients approached for 'consent for contact'. All patients in different services within the mental health trust are gradually and systematically being approached by a member of the clinical care team using the 'consent for contact' model. There are no exclusion criteria. PRIMARY AND SECONDARY OUTCOME MEASURES: Provision of 'consent for contact'. RESULTS: A new model (the South London and Maudsley NHS Trust Consent for Contact model (SLaM C4C)) for gaining patients' consent to contact them about research possibilities, which is built around a de-identified EHR database. The model allows researchers to contact potential participants directly. Of 2106 patients approached by 25 October 2013, nearly 3 of every 4 gave consent for contact (1560 patients; 74.1%). CONCLUSIONS: The SLaM C4C model offers an effective way of expediting recruitment into health research through using EHRs. It reduces the gatekeeper function of clinicians; gives patients greater autonomy in decisions to participate in research; and accelerates the development of a culture of active research participation. More research is needed to assess how many of those giving consent for contact subsequently consent to participate in particular research studies.

Original publication

DOI

10.1136/bmjopen-2014-005654

Type

Journal article

Journal

BMJ Open

Publication Date

02/12/2014

Volume

4

Keywords

MENTAL HEALTH, PSYCHIATRY, Adolescent, Adult, Aged, Biomedical Research, Child, Child, Preschool, Cohort Studies, Electronic Health Records, Female, Humans, Infant, Infant, Newborn, Male, Mental Health Services, Middle Aged, Models, Organizational, Patient Selection, Retrospective Studies, United Kingdom, Young Adult