Patient-reported outcomes (PRO) are questionnaire measures of patients’ symptoms, functioning, and health-related quality of life. They are designed to provide important clinical information that generally cannot be captured with objective medical testing. In 2004, the National Institutes of Health launched a research initiative to improve the clinical research enterprise by developing state-of-the-art PROs. The NIH Patient-Reported Outcomes Measurement System (PROMIS) and Assessment Center are the products of that initiative. Adult, pediatric, and parent-proxy item banks have been developed by using contemporary psychometric methods, yielding rapid, accurate measurements. PROMIS currently provides tools for assessing physical, mental, and social health using short-form and computer-adaptive testing methods. The PROMIS tools are being adopted for use in clinical trials and translational research. They are also being introduced in clinical medicine to assess a broad range of disease outcomes. Recent legislative developments in the United States support greater efforts to include patients’ reports of health experience in order to evaluate treatment outcomes, engage in shared decision-making, and prioritize the focus of treatment. PROs have garnered increased attention by the Food and Drug Administration (FDA) for evaluating drugs and medical devices. Recent calls for comparative effectiveness research favor inclusion of PROs. PROs could also potentially improve quality of care and disease outcomes, provide patient-centered assessment for comparative effectiveness research, and enable a common metric for tracking outcomes across providers and medical systems.

Advances in Patient-Reported Outcomes: The NIH PROMIS(®) Measures.

https://hal-univ-rennes1.archives-ouvertes.fr/hal-01147042/document

Using electronic health records for clinical research

Objective: To perform a review of recent research in clinical data reuse or secondary use, and envision future advances in this field. Methods: The review is based on a large literature search in MEDLINE (through PubMed), conference proceedings, and the ACM Digital Library, focusing only on research published between 2005 and early 2016. Each selected publication was reviewed by the authors, and a structured analysis and summarization of its content was developed. Results: The initial search produced 359 publications, reduced after a manual examination of abstracts and full publications. The following aspects of clinical data reuse are discussed: motivations and challenges, privacy and ethical concerns, data integration and interoperability, data models and terminologies, unstructured data reuse, structured data mining, clinical practice and research integration, and examples of clinical data reuse (quality measurement and learning healthcare systems). Conclusion: Reuse of clinical data is a fast-growing field recognized as essential to realize the potentials for high quality healthcare, improved healthcare management, reduced healthcare costs, population health management, and effective clinical research.

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Clinical Data Reuse or Secondary Use: Current Status and Potential Future Progress.

Trustworthy reuse of health data: A transnational perspective

Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were ‘age’ (89%), ‘gender’ (89%), ‘addictive behaviour’ (74%), ‘disease, symptom and sign’ (64%) and ‘organ or tissue status’ (61%). No data was available for 6 semantic groups. There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data.

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Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence

Integrating clinical research with the Healthcare Enterprise

Integrating biomedical research and patient care is a challenging issue requiring interoperability solutions. During a clinical trial, clinical data are captured twice, first in the Electronic Health Record (EHR) and then in the Clinical trials Data Management System (CDMS). The aim of REUSE (Retrieving EHR Useful data for Secondary Exploitation) project is to provide a single source solution for electronic data capture to the investigators of a university hospitals involved in a multi-centric clinical trial. We first investigated the differences between the workflows of patient care and biomedical research to specify the use of EHR for clinical trials. Then we defined a semantic interoperability framework in order to enable the reuse of EHR clinical data and implemented a mediator that transforms CDISC Operational Data Model (ODM) XML into proprietary XML document templates of different EHR solutions and vice-versa. Implementing electronic data capture for biomedical research within EHR eliminates redundant data entry, thus improving data quality and processing speed. Moreover, unlike other initiatives such as IHE integration profile "Retrieve Form for Data Capture" (RFD), the REUSE approach ensures that all clinical data is kept in the EHR whatever the context of data capture is.

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Abdennaji El Fadly

Papers

Integrating clinical research with the Healthcare Enterprise

The REUSE project: EHR as single datasource for biomedical research.