Feasibility and cost of obtaining informed consent for essential review of medical records in large-scale health services research.
ABSTRACT To evaluate the effectiveness and cost of obtaining consent for review of medical records within the passively observed non-intervention arm of a cluster randomized controlled trial, 'Comparison Arm for ProtecT'.
Two hundred and thirty men, who had been notified to the trial by cancer registries as having prostate cancer, were sent a consent form from their general practitioner or secondary care clinician. The consent rate of participants to the review of their medical records and the estimated costs of the process were evaluated.
One hundred and seventy-nine men (84%: 95% CI = 78%, 89%) consented to have their medical notes reviewed at an estimated cost of pound123 (euro172, $248) per person.
A high consent rate for review of medical notes is achievable but at a cost. There needs to be renewed debate about the automatic need for consent to review medical records where the chance of personal harm is negligible and the purpose of the review is to provide robust evidence to save lives, prevent needless suffering, and improve the effectiveness and efficiency of health care delivery.
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ABSTRACT: If genomic studies are to be a clinically relevant and timely reflection of the relationship between genetics and health status--whether for common or rare variants--cost-effective ways must be found to measure both the genetic variation and the phenotypic characteristics of large populations, including the comprehensive and up-to-date record of their medical treatment. The adoption of electronic health records, used by clinicians to document clinical care, is becoming widespread and recent studies demonstrate that they can be effectively employed for genetic studies using the informational and biological 'by-products' of health-care delivery while maintaining patient privacy.Nature Reviews Genetics 06/2011; 12(6):417-28. · 41.06 Impact Factor
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ABSTRACT: Clinical data describing the phenotypes and treatment of patients represents an underused data source that has much greater research potential than is currently realized. Mining of electronic health records (EHRs) has the potential for establishing new patient-stratification principles and for revealing unknown disease correlations. Integrating EHR data with genetic data will also give a finer understanding of genotype-phenotype relationships. However, a broad range of ethical, legal and technical reasons currently hinder the systematic deposition of these data in EHRs and their mining. Here, we consider the potential for furthering medical research and clinical care using EHR data and the challenges that must be overcome before this is a reality.Nature Reviews Genetics 05/2012; 13(6):395-405. · 41.06 Impact Factor