FAIR data sharing: The roles of common data elements and harmonization.

The value of robust and responsible data sharing in clinical research and healthcare is recognized by patients, patient advocacy groups, researchers, journal editors, and the healthcare industry globally. Privacy and security concerns acknowledged, the act of exchanging data (interoperability) along with its meaning (semantic interoperability) across studies and between partners has been difficult, if not elusive. For shared data to retain its value, a recommendation has been made to follow the Findable, Accessible, Interoperable, Reusable (FAIR) principles. Without applying appropriate data exchange standards with domain-relevant content standards and accessible rich metadata that uses applicable terminologies, interoperability is burdened by the need for transformation and/or mapping. These obstacles to interoperability limit the findability, accessibility and reusability of data, thus diminishing its value and making it impossible to adhere to FAIR principles. One effort to standardize data collection has been through common data elements (CDEs). CDEs are data collection units comprising one or more questions together with a set of valid values. Some CDEs contain standardized terminology concepts that define the meaning of the data, and others include links to unique terminology concept identifiers and unique identifiers for each CDE; however, usually CDEs are defined for specific projects or collaborations and lack traceable or machine readable semantics. While the name implies that these are 'common', this has not necessarily been a requirement, and many CDEs have not been commonly used. The National Institutes of Health (NIH) CDEs are, in fact, a conglomerate of CDEs developed in silos by various NIH institutes. Therefore, CDEs have not brought the anticipated benefit to the industry through widescale interoperability, nor is there widespread reuse of CDEs. Certain institutes in the NIH recommend, albeit do not enforce, institute-specific preferred CDEs; however, at the NIH level a preponderance of choice and a lack of any overarching harmonization of CDEs or consistency in linking them to controlled terminology or common identifiers create confusion for researchers in their efforts to identify the best CDEs for their protocol. The problem of comparing data among studies is exacerbated when researchers select different CDEs for the same variable or data collection field. This manuscript explores reasons for the disappointingly low adoption of CDEs and the inability of CDEs or other clinical research standards to broadly solve the interoperability and data sharing problems. Recommendations are offered for rectifying this situation to enable responsible data sharing that will help in adherence to FAIR principles and the realization of Learning Health Systems for the sake of all of us as patients.

Harmonization of detailed clinical models with clinical study data standards.

INTRODUCTION: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". BACKGROUND: Data sharing and integration between the clinical research data management system and the electronic health record system remains a challenging issue. To approach the issue, there is emerging interest in utilizing the Detailed Clinical Model (DCM) approach across a variety of contexts. The Intermountain Healthcare Clinical Element Models (CEMs) have been adopted by the Office of the National Coordinator awarded Strategic Health IT Advanced Research Projects for normalization (SHARPn) project for normalizing patient data from the electronic health records (EHR). OBJECTIVE: The objective of the present study is to describe our preliminary efforts toward harmonization of the SHARPn CEMs with CDISC (Clinical Data Interchange Standards Consortium) clinical study data standards. METHODS: We were focused on three generic domains: demographics, lab tests, and medications. We performed a panel review on each data element extracted from the CDISC templates and SHARPn CEMs. RESULTS: We have identified a set of data elements that are common to the context of both clinical study and broad secondary use of EHR data and discussed outstanding harmonization issues. CONCLUSIONS: We consider that the outcomes would be useful for defining new requirements for the DCM modeling community and ultimately facilitating the semantic interoperability between systems for both clinical study and broad secondary use domains.

Long-term continuous ambulatory peritoneal dialysis. Mass transfer and nutritional and metabolic stability.

Long-term mass transfer and nutritional and metabolic stability of end-stage renal disease patients maintained on continuous ambulatory peritoneal dialysis (CAPD) continue to be of concern. This study longitudinally monitored 43 Japanese CAPD patients (29 males, 14 females) from three centres within the Tokyo Metropolitan Area for an average period of 15 +/- (SD) 8 months. The mean time for patients on CAPD at study initiation was 18 +/- 15 months. Monitored parameters included urea and creatinine mass transfer coefficients, clearances and blood levels, ultrafiltration, lipid levels, dietary protein intake, and weight. Lipid data were also gathered retrospectively from patient records from the time of CAPD initiation. The results were analyzed using regression growth curve analysis and analysis of variance. Statistically significant linear rises with time were apparent only for the creatinine mass transfer coefficients, although this was not considered clinically significant in terms of changes either in peritoneal creatinine clearances or ultrafiltration. Serum cholesterol levels were found to rise significantly above pre-dialysis levels 11 months after CAPD onset, thereafter returning to levels not significantly above baseline levels. In summary, CAPD provided stable, acceptable treatment over the study period.

Effect of diet on energy expenditure and plasma norepinephrine in lean and obese Pima Indians.

To assess whether thermogenesis or sympathetic nervous system (SNS) function might differ between lean and obese human subjects, studies of thermic and sympathetic responses to standard stimuli were undertaken in Pima Indians, an ethnic group with a high prevalence of obesity. Plasma levels of norepinephrine (NE) and energy expenditure at rest and in response to feeding, exercise, and graded infusions of NE were compared in five lean and five obese Indians during a period of weight maintenance (WM), after 3 weeks of overfeeding (OF) and, in the obese, also after 6 weeks of underfeeding (UF). Basal energy expenditure, when adjusted for fat free mass, was equivalent during WM and increased 3% with OF (P less than 0.01) in both groups. Thermic responses to exercise or a test meal did not differ in lean and obese and did not change with OF, while thermic responses to NE infusion fell during OF to a greater degree in obese than lean (P less than 0.05). A similar pattern (decreased effect in obese with OF) was also noted in the glycemic response to infused NE (P less than 0.05). Although not quantitatively different in lean and obese, the plasma NE concentration appeared to vary more in response to feeding or dietary alteration in the obese than lean, a finding that may reflect lower plasma clearance of NE in the obese. These studies, therefore, raise the possibility that overfeeding in obese Pima Indians may limit the contribution of sympathetically mediated thermogenesis to energy expenditure, though the implications of this for body weight regulation are speculative.