Pragmatic MDR: a metadata repository with bottom-up standardization of medical metadata through reuse.

BACKGROUND: The variety of medical documentation often leads to incompatible data elements that impede data integration between institutions. A common approach to standardize and distribute metadata definitions are ISO/IEC 11179 norm-compliant metadata repositories with top-down standardization. To the best of our knowledge, however, it is not yet common practice to reuse the content of publicly accessible metadata repositories for creation of case report forms or routine documentation. We suggest an alternative concept called pragmatic metadata repository, which enables a community-driven bottom-up approach for agreeing on data collection models. A pragmatic metadata repository collects real-world documentation and considers frequent metadata definitions as high quality with potential for reuse. METHODS: We implemented a pragmatic metadata repository proof of concept application and filled it with medical forms from the Portal of Medical Data Models. We applied this prototype in two use cases to demonstrate its capabilities for reusing metadata: first, integration into a study editor for the suggestion of data elements and, second, metadata synchronization between two institutions. Moreover, we evaluated the emergence of bottom-up standards in the prototype and two medical data managers assessed their quality for 24 medical concepts. RESULTS: The resulting prototype contained 466,569 unique metadata definitions. Integration into the study editor led to a reuse of 1836 items and item groups. During the metadata synchronization, semantic codes of 4608 data elements were transferred. Our evaluation revealed that for less complex medical concepts weak bottom-up standards could be established. However, more diverse disease-related concepts showed no convergence of data elements due to an enormous heterogeneity of metadata. The survey showed fair agreement (Kalpha = 0.50, 95% CI 0.43-0.56) for good item quality of bottom-up standards. CONCLUSIONS: We demonstrated the feasibility of the pragmatic metadata repository concept for medical documentation. Applications of the prototype in two use cases suggest that it facilitates the reuse of data elements. Our evaluation showed that bottom-up standardization based on a large collection of real-world metadata can yield useful results. The proposed concept shall not replace existing top-down approaches, rather it complements them by showing what is commonly used in the community to guide other researchers.

Criteria Suggestive of Psychological Components of Itch and Soma-toform Itch: Study of a Large Sample of Patients with Chronic Pruritus.

While psychological factors are relevant in many patients with chronic pruritus, not all patients can be offered psychologic, psychosomatic or psychiatric consultation. The aim of this exploratory study was to identify criteria suggestive of psychological factors relevant for the etiology of chronic pruritus and of somatoform pruritus. Routine data from the database of the Center for Chronic Pruritus of the University Hospital Münster were used, including the Neuroderm Questionnaire, Dermatology Life Quality Index and Hospital Anxiety and Depression Scale. Chronic pruritus patients (n = 3,391) without a psychiatric diagnosis in their medical history were compared to the 331 chronic pruritus patients with diagnoses of "psychological factors associated with etiology and course of chronic pruritus" (ICD-10:F54) or "somatoform pruritus" (F45.8) confirmed by an expert. The latter reported more pruritus triggers, especially "strain" and "emotional tension" and used more emotional adjectives to describe their pruritus. They reported more often scratching leading to excoriations, higher levels of pruritus, impairment of quality of life, anxiety and depression. These aspects suggest the presence of psychological factors in the etiology of chronic pruritus and somatoform pruritus. Prospective validation, however, needs to be carried out.

Scientific Challenge in eHealth: MAPPATHON, a Metadata Mapping Challenge.

Scientific challenges based on benchmark data enable the comparison and evaluation of different algorithms and take place regularly in scientific disciplines like medical image processing, text mining or genetics. The idea of a challenge is rarely applied within the eHealth community. Mappathon is a metadata mapping challenge that asks for methods to find corresponding data elements within similar datasets and to correlate data elements among each other.

Electronic Image Documentation of Patient Reported Outcomes Using Mobile Technologies.

Patient Reported Outcomes (PROs) provide essential clinical data for the diagnosis and treatment of patients. Mobile technologies enable rapid and structured collection of PROs with a high usability. MoPat is an electronic PRO system developed at the Münster University that enables patients to complete PROs in multiple languages. This research reports the further development of MoPat and the inclusion of features to document images electronically that will be evaluated in a multi-site clinical research.

Connecting healthcare and clinical research: Workflow optimizations through seamless integration of EHR, pseudonymization services and EDC systems.

OBJECTIVE: In the last years, several projects promote the secondary use of routine healthcare data based on electronic health record (EHR) data. In multicenter studies, dedicated pseudonymization services are applied for unified pseudonym handling. Healthcare, clinical research and pseudonymization systems are generally disconnected. Hence, the aim of this research work is to integrate these applications and to evaluate the workflow of clinical research. METHODS: We analyzed and identified technical solutions for legislation compliant automatic pseudonym generation and for the integration into EHR as well as electronic data capture (EDC) systems. The Mainzelliste was used as pseudonymization service, which is available as open source solution and compliant with the data privacy concept in Germany. Subject of the integration was the local EHR and an in-house developed EDC system. A time and motion study was conducted to evaluate the effects on the workflow. RESULTS: Integration of EHR, pseudonymization service and EDC systems is technically feasible and leads to a less fragmented usage of all applications. Generated pseudonyms are obtained from the service hosted at a trusted third party and can now be used in the EDC as well as in the EHR system for direct access and re-identification. The evaluation of 90 registration iterations shows that the time for documentation has been significantly reduced in average by 39.6 s (56.3%) from 71 ± 8 s to 31 ± 5 s per registered study patient. CONCLUSIONS: By incorporating EHR, EDC and pseudonymization systems, it is now feasible to support multicenter studies and registers out of an integrated system landscape within a hospital. Optimizing the workflow of patient registration for clinical research allows reduction of double data entry and transcription errors as well as a seamless transition from clinical routine to research data collection.

Humanistic burden of chronic pruritus in patients with inflammatory dermatoses: Results of the European Academy of Dermatology and Venereology Network on Assessment of Severity and Burden of Pruritus (PruNet) cross-sectional trial.

BACKGROUND: Chronic pruritus is a multifactorial, challenging symptom of global relevance. OBJECTIVE: The European Academy of Dermatology and Venereology Network on Assessment of Severity and Burden of Pruritus (PruNet) investigation aimed to analyze the severity and humanistic burden of chronic pruritus in patients suffering from inflammatory dermatoses across Europe. METHODS: Prospectively collected routine data on 552 patients (with atopic dermatitis, contact dermatitis, prurigo nodularis, psoriasis vulgaris, lichen planus, or mycosis fungoides [pruritus numeric rating scale score ≥3]) from 9 European centers (in Austria, France, Germany, Italy, Poland, Russia, Spain, Switzerland, and Turkey) were analyzed by univariate and multivariate variance analyses of various itch characteristics and quality of life (as measured by the Dermatology Life Quality Index and the ItchyQoL). RESULTS: Duration, frequency, and intensity of pruritus (according to a numeric rating scale and visual analog scale) and related impairment of quality of life differed between European centers and dermatologic diagnoses (P < .05). The country in which the center was located had a greater impact on how patients evaluated pruritus intensity and quality of life than diagnosis did (P < .001). LIMITATIONS: One center per country was included. CONCLUSION: The humanistic burden of chronic pruritus in patients with inflammatory dermatoses is high. European cross-cultural factors may have a stronger influence than a specific dermatologic diagnosis on how patients rate intensity of pruritus and quality of life.

Comparison and transformation between CDISC ODM and EN13606 EHR standards in connecting EHR data with clinical trial research data.

OBJECTIVES: Integrating Electronic Health Record (EHR) systems into the field of clinical trials still contains several challenges and obstacles. Heterogeneous standards and specifications are used to represent healthcare and clinical trial information. Therefore, this work investigates the mapping and data interoperability between healthcare and research standards: EN13606 used for the EHRs and the Clinical Data Interchange Standards Consortium Operational Data Model (CDISC ODM) used for clinical research. METHODS: Based on the specifications of CDISC ODM 1.3.2 and EN13606, a mapping between the structure and components of both standards has been performed. Archetype Definition Language (ADL) forms built with the EN13606 editor were transformed to ODM XML and reviewed. As a proof of concept, clinical sample data has been transformed into ODM and imported into an electronic data capture system. Reverse transformation from ODM to ADL has also been performed and finally reviewed concerning map-ability. RESULTS: The mapping between EN13606 and CDISC ODM shows the similarities and differences between the components and overall record structure of the two standards. An EN13606 archetype corresponds with a group of items within CDISC ODM. Transformations of element names, descriptions, different languages, datatypes, cardinality, optionality, units, value range and terminology codes are possible from EN13606 to CDISC ODM and vice versa. CONCLUSION: It is feasible to map data elements between EN13606 and CDISC ODM and transformation of forms between ADL and ODM XML format is possible with only minor limitations. EN13606 can accommodate clinical information in a more structured manner with more constraints, whereas CDISC ODM is more suitable and specific for clinical trials and studies. It is feasible to transform EHR data in the EN13606 form to ODM to transfer it into research database. The attempt to use EN13606 to build a study protocol (that was already built with CDISC ODM) also suggests the possibility of using EN13606 standard in place of CDISC ODM if needed to avoid transformations.

ODM Data Analysis-A tool for the automatic validation, monitoring and generation of generic descriptive statistics of patient data.

INTRODUCTION: A required step for presenting results of clinical studies is the declaration of participants demographic and baseline characteristics as claimed by the FDAAA 801. The common workflow to accomplish this task is to export the clinical data from the used electronic data capture system and import it into statistical software like SAS software or IBM SPSS. This software requires trained users, who have to implement the analysis individually for each item. These expenditures may become an obstacle for small studies. Objective of this work is to design, implement and evaluate an open source application, called ODM Data Analysis, for the semi-automatic analysis of clinical study data. METHODS: The system requires clinical data in the CDISC Operational Data Model format. After uploading the file, its syntax and data type conformity of the collected data is validated. The completeness of the study data is determined and basic statistics, including illustrative charts for each item, are generated. Datasets from four clinical studies have been used to evaluate the application's performance and functionality. RESULTS: The system is implemented as an open source web application (available at https://odmanalysis.uni-muenster.de) and also provided as Docker image which enables an easy distribution and installation on local systems. Study data is only stored in the application as long as the calculations are performed which is compliant with data protection endeavors. Analysis times are below half an hour, even for larger studies with over 6000 subjects. DISCUSSION: Medical experts have ensured the usefulness of this application to grant an overview of their collected study data for monitoring purposes and to generate descriptive statistics without further user interaction. The semi-automatic analysis has its limitations and cannot replace the complex analysis of statisticians, but it can be used as a starting point for their examination and reporting.

Compatibility Between Metadata Standards: Import Pipeline of CDISC ODM to the Samply.MDR.

The establishment of a digital healthcare system is a national and community task. The Federal Ministry of Education and Research in Germany is providing funding for consortia consisting of university hospitals among others participating in the "Medical Informatics Initiative". Exchange of medical data between research institutions necessitates a place where meta information for this data is made accessible. Within these consortia different metadata registry solutions were chosen. To promote interoperability between these solutions, we have examined whether the portal of Medical Data Models is eligible for managing and communicating metadata and relevant information across different data integration centres of the Medical Informatics Initiative and beyond. Apart from the MDM-portal, some ISO 11179-based systems such as Samply.MDR as well as openEHR-based solutions are going to be applyed. In this paper, we have focused on the creation of a mapping model between the CDISC ODM standard and the Samply.MDR import format. In summary, it can be stated that the mapping model is feasible and promote the exchangeability between different metadata registry approaches.

Standardising the Development of ODM Converters: The ODMToolBox.

CDISC's Operational Data Model (ODM) is a flexible standard for exchanging and archiving metadata and subject clinical data in clinical trials. The Portal of Medical Data Models (MDM-Portal) uses ODM to store more than 15000 medical forms. As not every electronic health system accepts ODM as input format, there is a need for conversion between ODM and other data standards and formats. This research proposes a standardised template-based process to develop ODM converters. So far, ten converters have been developed and integrated in the MDM-Portal following this process and new ones should be included soon. The template, programming utilities and an ODM test suite have been made online available and can be used to easily develop new converters.

S2O - A software tool for integrating research data from general purpose statistic software into electronic data capture systems.

BACKGROUND: Data capture for clinical registries or pilot studies is often performed in spreadsheet-based applications like Microsoft Excel or IBM SPSS. Usually, data is transferred into statistic software, such as SAS, R or IBM SPSS Statistics, for analyses afterwards. Spreadsheet-based solutions suffer from several drawbacks: It is generally not possible to ensure a sufficient right and role management; it is not traced who has changed data when and why. Therefore, such systems are not able to comply with regulatory requirements for electronic data capture in clinical trials. In contrast, Electronic Data Capture (EDC) software enables a reliable, secure and auditable collection of data. In this regard, most EDC vendors support the CDISC ODM standard to define, communicate and archive clinical trial meta- and patient data. Advantages of EDC systems are support for multi-user and multicenter clinical trials as well as auditable data. Migration from spreadsheet based data collection to EDC systems is labor-intensive and time-consuming at present. Hence, the objectives of this research work are to develop a mapping model and implement a converter between the IBM SPSS and CDISC ODM standard and to evaluate this approach regarding syntactic and semantic correctness. RESULTS: A mapping model between IBM SPSS and CDISC ODM data structures was developed. SPSS variables and patient values can be mapped and converted into ODM. Statistical and display attributes from SPSS are not corresponding to any ODM elements; study related ODM elements are not available in SPSS. The S2O converting tool was implemented as command-line-tool using the SPSS internal Java plugin. Syntactic and semantic correctness was validated with different ODM tools and reverse transformation from ODM into SPSS format. Clinical data values were also successfully transformed into the ODM structure. CONCLUSION: Transformation between the spreadsheet format IBM SPSS and the ODM standard for definition and exchange of trial data is feasible. S2O facilitates migration from Excel- or SPSS-based data collections towards reliable EDC systems. Thereby, advantages of EDC systems like reliable software architecture for secure and traceable data collection and particularly compliance with regulatory requirements are achievable.

Management of chronic pruritus: from the dermatological office to the specialized itch center: a review.

Patient care for those affected by chronic pruritus is remarkably complex due to its high prevalence and multifactorial nature. It requires a comprehensive assessment of the patient's medical history, extensive diagnostic procedures, and long treatment duration, including management of possible accompanying disorders such as sleep disturbances and mental distress. It is important to prioritize patient's needs when developing a therapeutic treatment plan. Standardized questionnaires and scales should be used to better analyze the patient history, quality of life, symptom intensity, and course of treatment. These can be distributed via digital platforms, allowing for more effective communication between the treating agents and gathering of large volumes of data in central databases. In today's health care system, it is essential for physicians with itch-related specializations and specialized itch centers to cooperate. It is thus crucial to focus efforts on the further development of specialized treatment centers and training courses for medical practitioners. There are, however, various regulatory and economic barriers to overcome in the modern health care system before patients with chronic pruritus can be offered the best possible care. Accordingly, health care authorities should be made aware of the difficulties associated with the management of chronic pruritus and of the high individual and societal burden it represents.

What Information Does Your EHR Contain? Automatic Generation of a Clinical Metadata Warehouse (CMDW) to Support Identification and Data Access Within Distributed Clinical Research Networks.

Data dictionaries provide structural meta-information about data definitions in health information technology (HIT) systems. In this regard, reusing healthcare data for secondary purposes offers several advantages (e.g. reduce documentation times or increased data quality). Prerequisites for data reuse are its quality, availability and identical meaning of data. In diverse projects, research data warehouses serve as core components between heterogeneous clinical databases and various research applications. Given the complexity (high number of data elements) and dynamics (regular updates) of electronic health record (EHR) data structures, we propose a clinical metadata warehouse (CMDW) based on a metadata registry standard. Metadata of two large hospitals were automatically inserted into two CMDWs containing 16,230 forms and 310,519 data elements. Automatic updates of metadata are possible as well as semantic annotations. A CMDW allows metadata discovery, data quality assessment and similarity analyses. Common data models for distributed research networks can be established based on similarity analyses.

The Portal of Medical Data Models: Where Have We Been and Where Are We Going?

To address current key problems of medical documentation: lack of transparency, overwhelming amount of medical contents to be documented and missing interoperability, the Portal of Medical Data Models (http://medical-data-models.org/) was established in 2012. Constantly evolving, four years later, the portal displays more than 8900 medical data models with more than 250000 items, of which 84 % have been semantically annotated with UMLS codes to support interoperability. Giving an update on new functions and contents of the portal, two additional export formats have been implemented, allowing the reuse of forms such as HL7's framework Fast Health Interoperability Resources (FHIR) Questionnaires, as well as the OpenDataKit format. Future projects include the implementation of an ODMtoOpenClinica converter, as well as supporting the reuse of forms with Apple's ResearchKit and Android's ResearchStack.

Integrating x4T-EDC into an Image-Portal to Establish an Ophthalmic Reading Center.

Reading centers provide centralized high-quality diagnostics in ophthalmic clinical trials. Since ophthalmic images are captured in electronic format at peripheral clinics, an integrated workflow for image transfer and creation of structured reports is needed, including quality assurance. The image portal and the study database are separate components. We assessed whether this integration is feasible with trial-related IT standards and built a prototype system as a proof-of-concept. CDISC ODM and OAuth authentication were used to integrate the image portal with x4T-EDC, facilitating automatic data transfer and single sign-on.

Common data elements for secondary use of electronic health record data for clinical trial execution and serious adverse event reporting.

BACKGROUND: Data capture is one of the most expensive phases during the conduct of a clinical trial and the increasing use of electronic health records (EHR) offers significant savings to clinical research. To facilitate these secondary uses of routinely collected patient data, it is beneficial to know what data elements are captured in clinical trials. Therefore our aim here is to determine the most commonly used data elements in clinical trials and their availability in hospital EHR systems. METHODS: Case report forms for 23 clinical trials in differing disease areas were analyzed. Through an iterative and consensus-based process of medical informatics professionals from academia and trial experts from the European pharmaceutical industry, data elements were compiled for all disease areas and with special focus on the reporting of adverse events. Afterwards, data elements were identified and statistics acquired from hospital sites providing data to the EHR4CR project. RESULTS: The analysis identified 133 unique data elements. Fifty elements were congruent with a published data inventory for patient recruitment and 83 new elements were identified for clinical trial execution, including adverse event reporting. Demographic and laboratory elements lead the list of available elements in hospitals EHR systems. For the reporting of serious adverse events only very few elements could be identified in the patient records. CONCLUSIONS: Common data elements in clinical trials have been identified and their availability in hospital systems elucidated. Several elements, often those related to reimbursement, are frequently available whereas more specialized elements are ranked at the bottom of the data inventory list. Hospitals that want to obtain the benefits of reusing data for research from their EHR are now able to prioritize their efforts based on this common data element list.

Baseline Characteristics and Prescription Patterns of Standard Drugs in Patients with Angiographically Determined Coronary Artery Disease and Renal Failure (CAD-REF Registry).

BACKGROUND: Chronic kidney disease (CKD) is strongly associated with coronary artery disease (CAD). We established a prospective observational nationwide multicenter registry to evaluate current treatment and outcomes in patients with both CKD and angiographically documented CAD. METHODS: In 32 cardiological centers 3,352 CAD patients with ≥50% stenosis in at least one coronary artery were enrolled and classified according to their estimated glomerular filtration rate and proteinuria into one of five stages of CKD or as a control group. RESULTS: 2,723 (81.2%) consecutively enrolled patients suffered from CKD. Compared to controls, CKD patients had a higher prevalence of diabetes, hypertension, peripheral artery diseases, heart failure, and valvular heart disease (each p<0.001). Myocardial infarctions (p = 0.02), coronary bypass grafting, valve replacements and pacemaker implantations had been recorded more frequently (each p<0.001). With advanced CKD, the number of diseased coronary vessels and the proportion of patients with reduced left ventricular ejection fraction (LVEF) increased significantly (both p<0.001). Percutaneous coronary interventions were performed less frequently (p<0.001) while coronary bypass grafting was recommended more often (p = 0.04) with advanced CKD. With regard to standard drugs in CAD treatment, prescriptions were higher in our registry than in previous reports, but beta-blockers (p = 0.008), and angiotensin-converting-enzyme inhibitors and/or angiotensin-receptor blockers (p<0.001) were given less often in higher CKD stages. In contrast, in the subgroup of patients with moderately to severely reduced LVEF the prescription rates did not differ between CKD stages. In-hospital mortality increased stepwise with each CKD stage (p = 0.02). CONCLUSIONS: In line with other studies comprising CKD cohorts, patients' morbidity and in-hospital mortality increased with the degree of renal impairment. Although cardiologists' drug prescription rates in CAD-REF were higher than in previous studies, they were still lower especially in advanced CKD stages compared to cohorts treated by nephrologists.

Portal of medical data models: information infrastructure for medical research and healthcare.

INTRODUCTION: Information systems are a key success factor for medical research and healthcare. Currently, most of these systems apply heterogeneous and proprietary data models, which impede data exchange and integrated data analysis for scientific purposes. Due to the complexity of medical terminology, the overall number of medical data models is very high. At present, the vast majority of these models are not available to the scientific community. The objective of the Portal of Medical Data Models (MDM, https://medical-data-models.org) is to foster sharing of medical data models. METHODS: MDM is a registered European information infrastructure. It provides a multilingual platform for exchange and discussion of data models in medicine, both for medical research and healthcare. The system is developed in collaboration with the University Library of Münster to ensure sustainability. A web front-end enables users to search, view, download and discuss data models. Eleven different export formats are available (ODM, PDF, CDA, CSV, MACRO-XML, REDCap, SQL, SPSS, ADL, R, XLSX). MDM contents were analysed with descriptive statistics. RESULTS: MDM contains 4387 current versions of data models (in total 10,963 versions). 2475 of these models belong to oncology trials. The most common keyword (n = 3826) is 'Clinical Trial'; most frequent diseases are breast cancer, leukemia, lung and colorectal neoplasms. Most common languages of data elements are English (n = 328,557) and German (n = 68,738). Semantic annotations (UMLS codes) are available for 108,412 data items, 2453 item groups and 35,361 code list items. Overall 335,087 UMLS codes are assigned with 21,847 unique codes. Few UMLS codes are used several thousand times, but there is a long tail of rarely used codes in the frequency distribution. DISCUSSION: Expected benefits of the MDM portal are improved and accelerated design of medical data models by sharing best practice, more standardised data models with semantic annotation and better information exchange between information systems, in particular Electronic Data Capture (EDC) and Electronic Health Records (EHR) systems. Contents of the MDM portal need to be further expanded to reach broad coverage of all relevant medical domains. Database URL: https://medical-data-models.org.

PIACS: A System for the Automatic Detection, Categorization and Comparison of Scratch-Related Skin Lesions in Dermatology.

OBJECTIVE: In the treatment of chronic pruritus-related, scratch-induced skin lesions the categorization, counting and temporal comparison are common methodologies. The observation requires a good memory and expertise in this field to gain comparable findings for this time-consuming process. Digital image processing aims at supporting such manual detections. The objective is to develop a software tool for automatic image detection and comparison. The new photographic setting implies the usage of markers to derive the brightness and size of lesions. MATLAB has been used for the software development. The newly defined setting allows taking standardized images of pruritus-associated cutaneous lesions for detection and comparison. The tool named PIACS (Prurigo Image Analyzing and Comparing System) allows automatically detecting, categorizing and comparing lesions based on digital images.

Health-Related Quality of Life in Chronic Pruritus: An Analysis Related to Disease Etiology, Clinical Skin Conditions and Itch Intensity.

BACKGROUND: It is unknown if health-related quality of life (HRQoL) differs between diseases associated with chronic pruritus (CP). OBJECTIVE: To analyze HRQoL in relation to age, gender, skin lesions (primary vs. scratch-induced secondary) and itch intensity. METHODS: Consecutive patients of our itch clinic were assessed with the Dermatology Life Quality Index (DLQI) and visual analogue scale (VAS). RESULTS: In 510 CP patients (282 females; median age, 61.4 years), DLQI scores and VAS values were highly correlated, irrespective of the type of skin lesion. Overall, women had a lower HRQoL compared to men (females: 10.7 ± 6.7, males: 8.9 ± 6.7), but female gender was only associated with worse quality of life in patients <65 years old. CONCLUSION: HRQoL impairment in CP is highly influenced by pruritus intensity but not to the visible skin lesion or underlying cause. With limitations to item bias, DLQI is a suitable instrument for estimating quality of life impairment by CP.