Abstract
Background: The analysis of clinical free text from patient records for research has potential to contribute to the medical evidence base but access to clinical free text is frequently denied by data custodians who perceive that the privacy risks of data-sharing are too high. Engagement activities with patients and regulators, where views on the sharing of clinical free text data for research have been discussed, have identified that stakeholders would like to understand the potential clinical benefits that could be achieved if access to free text for clinical research were improved. We aimed to systematically review all UK research studies which used clinical free text and report direct or potential benefits to patients, synthesizing possible benefits into an easy to communicate taxonomy for public engagement and policy discussions.Methods: We conducted a systematic search for articles which reported primary research using clinical free text, drawn from UK health record databases, which reported a benefit or potential benefit for patients, actionable in a clinical environment or health service, and not solely methods development or data quality improvement. We screened eligible papers and thematically analyzed information about clinical benefits reported in the paper to create a taxonomy of benefits.Results: We identified 43 papers and derived five themes of benefits: health-care quality or services improvement, observational risk factor-outcome research, drug prescribing safety, case-finding for clinical trials, and development of clinical decision support. Five papers compared study quality with and without free text and found an improvement of accuracy when free text was included in analytical models.Conclusions: Findings will help stakeholders weigh the potential benefits of free text research against perceived risks to patient privacy. The taxonomy can be used to aid public and policy discussions, and identified studies could form a public-facing repository which will help the health-care text analysis research community better communicate the impact of their work.
Highlights
Electronic Health Records (EHRs) are revolutionizing health care at the point of delivery, and offer huge potential for discovery and research worldwide
This study provides the first evidence that services designed for people at high risk of psychosis may be associated with better outcomes in patients who are already psychotic, but were referred because they were thought to be at high risk
This study aimed to investigate socio-demographic, socioeconomic, clinical, and service-use predictors of long-term
Summary
Electronic Health Records (EHRs) are revolutionizing health care at the point of delivery, and offer huge potential for discovery and research worldwide. Data are entered into EHRs in free text natural language in the form of clinic notes, letters and reports This is true of UK-based mental health records, GP clinic notes and letters, and hospital communications such as pathology or scan reports and discharge letters. These free text natural language data are considered unstructured, in comparison to clinical data stored in preset fields in records or entered in the form of clinical codes, in which a numeric or alphanumeric string represents a unique clinical concept such as a diagnosis or process of care (9). We aimed to systematically review all UK research studies which used clinical free text and report direct or potential benefits to patients, synthesizing possible benefits into an easy to communicate taxonomy for public engagement and policy discussions
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