[Nationally standardized broad consent in practice: initial experiences, current developments, and critical assessment]. / National standardisierter Broad Consent in der Praxis: erste Erfahrungen, aktuelle Entwicklungen und kritische Betrachtungen.

BACKGROUND: The digitalization in the healthcare sector promises a secondary use of patient data in the sense of a learning healthcare system. For this, the Medical Informatics Initiative's (MII) Consent Working Group has created an ethical and legal basis with standardized consent documents. This paper describes the systematically monitored introduction of these documents at the MII sites. METHODS: The monitoring of the introduction included regular online surveys, an in-depth analysis of the introduction processes at selected sites, and an assessment of the documents in use. In addition, inquiries and feedback from a large number of stakeholders were evaluated. RESULTS: The online surveys showed that 27 of the 32 sites have gradually introduced the consent documents productively, with a current total of 173,289 consents. The analysis of the implementation procedures revealed heterogeneous organizational conditions at the sites. The requirements of various stakeholders were met by developing and providing supplementary versions of the consent documents and additional information materials. DISCUSSION: The introduction of the MII consent documents at the university hospitals creates a uniform legal basis for the secondary use of patient data. However, the comprehensive implementation within the sites remains challenging. Therefore, minimum requirements for patient information and supplementary recommendations for best practice must be developed. The further development of the national legal framework for research will not render the participation and transparency mechanisms developed here obsolete.

Herding Cats in Pandemic Times - Towards Technological and Organizational Convergence of Heterogeneous Solutions for Investigating and Mastering the Pandemic in University Medical Centers.

To understand and handle the COVID-19 pandemic, digital tools and infrastructures were built in very short timeframes, resulting in stand-alone and non-interoperable solutions. To shape an interoperable, sustainable, and extensible ecosystem to advance biomedical research and healthcare during the pandemic and beyond, a short-term project called "Collaborative Data Exchange and Usage" (CODEX+) was initiated to integrate and connect multiple COVID-19 projects into a common organizational and technical framework. In this paper, we present the conceptual design, provide an overview of the results, and discuss the impact of such a project for the trade-off between innovation and sustainable infrastructures.

Enhancing Data Protection via Auditable Informational Separation of Powers Between Workflow Engine Based Agents: Conceptualization, Implementation, and First Cross-Institutional Experiences.

German best practice standards for secondary use of patient data require pseudonymization and informational separation of powers assuring that identifying data (IDAT), pseudonyms (PSN), and medical data (MDAT) are never simultaneously knowable by any party involved in data provisioning and use. We describe a solution meeting these requirements based on the dynamic interaction of three software agents: the clinical domain agent (CDA), which processes IDAT and MDAT, the trusted third party agent (TTA), which processes IDAT and PSN, and the research domain agent (RDA), which processes PSN and MDAT and delivers pseudonymized datasets. CDA and RDA implement a distributed workflow by employing an off-the-shelf workflow engine. TTA wraps the gPAS framework for pseudonym generation and persistence. All agent interactions are implemented via secured REST-APIs. Rollout to three university hospitals was seamless. The workflow engine allowed meeting various overarching requirements, including auditability of data transfer and pseudonymization, with minimal additional implementation effort. Using a distributed agent architecture based on workflow engine technology thus proved to be an efficient way to meet technical and organizational requirements for provisioning patient data for research purposes in a data protection compliant way.

Implementation of 2D Barcode Medication Labels and Smart Pumps in Pediatric Acute Care: Lessons Learned.

BACKGROUND: In pediatric intensive care, prescription, administration, and interpretation of drug doses are weight dependent. The use of standardized concentrations simplifies the preparation of drugs and increases safety. For safe administration as well as easy interpretation of intravenous drug dosing regimens with standardized concentrations, the display of weight-related dose rates on the infusion device is of pivotal significance. OBJECTIVES: We report on challenges in the implementation of a new information technology-supported medication workflow. The workflow was introduced on eight beds in the pediatric heart surgery intensive care unit as well as in the pediatric anesthesia at the University of Bonn Medical Center. The proposed workflow utilizes medication labels generated from prescription data from the electronic health record. The generated labels include a two-dimensional barcode to transfer data to the infusion devices. METHODS: Clinical and technical processes were agilely developed. The reliability of the system under real-life conditions was monitored. User satisfaction and potential for improvement were assessed. In addition, a structured survey among the nursing staff was performed. The questionnaire addressed usability as well as the end-users' perception of the effects on patient safety. RESULTS: The workflow has been applied 44,111 times during the pilot phase. A total of 114 known failures in the technical infrastructure were observed. The survey showed good ratings for usability and safety (median "school grade" 2 or B for patient safety, intelligibility, patient identification, and handling). The medical management of the involved acute care facilities rated the process as clearly beneficial regarding patient safety, suggesting a rollout to all pediatric intensive care areas. CONCLUSION: A medical information technology-supported medication workflow can increase user satisfaction and patient safety as perceived by the clinical end-users in pediatric acute care. The successful implementation benefits from an interdisciplinary team, active investigation of possible associated risks, and technical redundancy.

Data protection-compliant broad consent for secondary use of health care data and human biosamples for (bio)medical research: Towards a new German national standard.

BACKGROUND: The secondary use of deidentified but not anonymized patient data is a promising approach for enabling precision medicine and learning health care systems. In most national jurisdictions (e.g., in Europe), this type of secondary use requires patient consent. While various ethical, legal, and technical analyses have stressed the opportunities and challenges for different types of consent over the past decade, no country has yet established a national consent standard accepted by the relevant authorities. METHODS: A working group of the national Medical Informatics Initiative in Germany conducted a requirements analysis and developed a GDPR-compliant broad consent standard. The development included consensus procedures within the Medical Informatics Initiative, a documented consultation process with all relevant stakeholder groups and authorities, and the ultimate submission for approval via the national data protection authorities. RESULTS: This paper presents the broad consent text together with a guidance document on mandatory safeguards for broad consent implementation. The mandatory safeguards comprise i) independent review of individual research projects, ii) organizational measures to protect patients from involuntary disclosure of protected information, and iii) comprehensive information for patients and public transparency. This paper further describes the key issues discussed with the relevant authorities, especially the position on additional or alternative consent approaches such as dynamic consent. DISCUSSION: Both the resulting broad consent text and the national consensus process are relevant for similar activities internationally. A key challenge of aligning consent documents with the various stakeholders was explaining and justifying the decision to use broad consent and the decision against using alternative models such as dynamic consent. Public transparency for all secondary use projects and their results emerged as a key factor in this justification. While currently largely limited to academic medicine in Germany, the first steps for extending this broad consent approach to wider areas of application, including smaller institutions and medical practices, are currently under consideration.

The COVID-19 Data Exchange Platform of the German University Medicine.

COVID-19 has challenged the healthcare systems worldwide. To quickly identify successful diagnostic and therapeutic approaches large data sharing approaches are inevitable. Though organizational clinical data are abundant, many of them are available only in isolated silos and largely inaccessible to external researchers. To overcome and tackle this challenge the university medicine network (comprising all 36 German university hospitals) has been founded in April 2020 to coordinate COVID-19 action plans, diagnostic and therapeutic strategies and collaborative research activities. 13 projects were initiated from which the CODEX project, aiming at the development of a Germany-wide Covid-19 Data Exchange Platform, is presented in this publication. We illustrate the conceptual design, the stepwise development and deployment, first results and the current status.

Evaluation of a Paper-Based Checklist versus an Electronic Handover Tool Based on the Situation Background Assessment Recommendation (SBAR) Concept in Patients after Surgery for Congenital Heart Disease.

(1) Background: we compare a new SBAR based electronic handover tool versus a paper-based checklist for handover in a pediatric intensive care unit (PICU). (2) Methods: this is a randomized, observational study of 40 electronic vs. 40 paper checklist handovers after pediatric cardiac surgery, with a 48 items checklist for comparison of reporting frequencies and notification of disturbances and noise. PICU staff satisfaction was evaluated by a 12-item questionnaire. (3) Results: in 14 out of 40 cases, there were problems with data processing (incomplete or no data processing). Some item groups (e.g., hemodynamics) were consistently reported at higher frequencies than other groups. Items not specifically asked for did not get reported. Some items, automatically processed in the SBAR handover page, did not get reported. Many handovers suffered a noisy and distracting atmosphere. There was no difference in staff satisfaction between the two handover approaches. Nurses were highly unsatisfied with the general approach by which the handover was performed. (4) Conclusions: human error appears to be a main factor for unreliable data processing. Software is still too complicated, and multitasking is a stressful and error prone event. Handover is a complex task with many factors required for a successful completion.

Algorithmic surveillance of ICU patients with acute respiratory distress syndrome (ASIC): protocol for a multicentre stepped-wedge cluster randomised quality improvement strategy.

INTRODUCTION: The acute respiratory distress syndrome (ARDS) is a highly relevant entity in critical care with mortality rates of 40%. Despite extensive scientific efforts, outcome-relevant therapeutic measures are still insufficiently practised at the bedside. Thus, there is a clear need to adhere to early diagnosis and sufficient therapy in ARDS, assuring lower mortality and multiple organ failure. METHODS AND ANALYSIS: In this quality improvement strategy (QIS), a decision support system as a mobile application (ASIC app), which uses available clinical real-time data, is implemented to support physicians in timely diagnosis and improvement of adherence to established guidelines in the treatment of ARDS. ASIC is conducted on 31 intensive care units (ICUs) at 8 German university hospitals. It is designed as a multicentre stepped-wedge cluster randomised QIS. ICUs are combined into 12 clusters which are randomised in 12 steps. After preparation (18 months) and a control phase of 8 months for all clusters, the first cluster enters a roll-in phase (3 months) that is followed by the actual QIS phase. The remaining clusters follow in month wise steps. The coprimary key performance indicators (KPIs) consist of the ARDS diagnostic rate and guideline adherence regarding lung-protective ventilation. Secondary KPIs include the prevalence of organ dysfunction within 28 days after diagnosis or ICU discharge, the treatment duration on ICU and the hospital mortality. Furthermore, the user acceptance and usability of new technologies in medicine are examined. To show improvements in healthcare of patients with ARDS, differences in primary and secondary KPIs between control phase and QIS will be tested. ETHICS AND DISSEMINATION: Ethical approval was obtained from the independent Ethics Committee (EC) at the RWTH Aachen Faculty of Medicine (local EC reference number: EK 102/19) and the respective data protection officer in March 2019. The results of the ASIC QIS will be presented at conferences and published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: DRKS00014330.

Towards a comprehensive and interoperable representation of consent-based data usage permissions in the German medical informatics initiative.

BACKGROUND: The aim of the German Medical Informatics Initiative is to establish a national infrastructure for integrating and sharing health data. To this, Data Integration Centers are set up at university medical centers, which address data harmonization, information security and data protection. To capture patient consent, a common informed consent template has been developed. It consists of different modules addressing permissions for using data and biosamples. On the technical level, a common digital representation of information from signed consent templates is needed. As the partners in the initiative are free to adopt different solutions for managing consent information (e.g. IHE BPPC or HL7 FHIR Consent Resources), we had to develop an interoperability layer. METHODS: First, we compiled an overview of data items required to reflect the information from the MII consent template as well as patient preferences and derived permissions. Next, we created entity-relationship diagrams to formally describe the conceptual data model underlying relevant items. We then compared this data model to conceptual models describing representations of consent information using different interoperability standards. We used the result of this comparison to derive an interoperable representation that can be mapped to common standards. RESULTS: The digital representation needs to capture the following information: (1) version of the consent, (2) consent status for each module, and (3) period of validity of the status. We found that there is no generally accepted solution to represent status information in a manner interoperable with all relevant standards. Hence, we developed a pragmatic solution, comprising codes which describe combinations of modules with a basic set of status labels. We propose to maintain these codes in a public registry called ART-DECOR. We present concrete technical implementations of our approach using HL7 FHIR and IHE BPPC which are also compatible with the open-source consent management software gICS. CONCLUSIONS: The proposed digital representation is (1) generic enough to capture relevant information from a wide range of consent documents and data use regulations and (2) interoperable with common technical standards. We plan to extend our model to include more fine-grained status codes and rules for automated access control.

Accuracy of the non-invasive Tcore™ temperature monitoring system to measure body core temperature in abdominal surgery.

An accurate determination of body core temperature is crucial during surgery in order to avoid and treat hypothermia, which is associated with poor outcome. In a prospective observational study, we evaluated the suitability of the Tcore™ device (Drägerwerk AG & Co. KGaA, Lübeck, Germany)-a non-invasive thermometer-to accurately determine core body temperature. In patients undergoing surgery for ovarian cancer, core body temperature (CBT) was determined with the Tcore™ sensor attached to the forehead and compared with blood temperature (Tblood) as measured within the femoro-iliacal artery. Both temperatures were recorded every 10 s and the measurement error was calculated. 57,302 data pairs of CBT and Tblood were obtained in 22 patients. In a repeated-measurements version of the Bland and Altman test, a bias of - 0.02 °C and 95% limits of agreement of - 0.48 to 0.44 °C were calculated. In a population analysis, a median absolute error of 0 [- 0.1; + 0.1] °C, a bias of 0 [- 0.276; 0.271] % and an inaccuracy of 0.276 [0.274; 0.354] % was determined. Although the Tcore™ sensor was attached to the frontal skin, it provided an accurate measurement of core body temperature in the investigated intraoperative setting.

Integrating Heterogeneous Data Sources for Cross-Institutional Data Sharing: Requirements Elicitation and Management in SMITH.

The digitization of health records and cross-institutional data sharing is a necessary precondition to improve clinical research and patient care. The SMITH project unites several university hospitals and medical faculties in order to provide medical informatics solutions for health data integration and cross-institutional communication. In this paper, we focus on requirements elicitation and management for extracting clinical data from heterogeneous subsystems and data integration based on eHealth standards such as HL7 FHIR and IHE profiles.

Model-Based Quantification of Left Ventricular Diastolic Function in Critically Ill Patients with Atrial Fibrillation from Routine Data: A Feasibility Study.

INTRODUCTION: Left ventricular diastolic dysfunction (LVDD) and atrial fibrillation (AF) are connected by pathophysiology and prevalence. LVDD remains underdiagnosed in critically ill patients despite potentially significant therapeutic implications since direct measurement cannot be performed in routine care at the bedside, and echocardiographic assessment of LVDD in AF is impaired. We propose a novel approach that allows us to infer the diastolic stiffness, ß, a key quantitative parameter of diastolic function, from standard monitoring data by solving the nonlinear, ill-posed inverse problem of parameter estimation for a previously described mechanistic, physiological model of diastolic filling. The beat-to-beat variability in AF offers an advantageous setting for this. METHODS: By employing a global optimization algorithm, ß is inferred from a simple six parameter and an expanded seven parameter model of left ventricular filling. Optimization of all parameters was limited to the interval ]0, 400[ and initialized randomly on large intervals encompassing the support of the likelihood function. Routine ECG and arterial pressure recordings of 17 AF and 3 sinus rhythm (SR) patients from the PhysioNet MGH/MF Database were used as inputs. RESULTS: Estimation was successful in 15 of 17 AF patients, while in the 3 SR patients, no reliable estimation was possible. For both models, the inferred ß (0.065 ± 0.044 ml-1 vs. 0.038 ± 0.033 ml-1 (p=0.02) simple vs. expanded) was compatible with the previously described (patho) physiological range. Aortic compliance, α, inferred from the expanded model (1.46 ± 1.50 ml/mmHg) also compared well with literature values. CONCLUSION: The proposed approach successfully inferred ß within the physiological range. This is the first report of an approach quantifying LVDF from routine monitoring data in critically ill AF patients. Provided future successful external validation, this approach may offer a tool for minimally invasive online monitoring of this crucial parameter.

Correction: From Inverse Problems in Mathematical Physiology to Quantitative Differential Diagnoses.

[This corrects the article DOI: 10.1371/journal.pcbi.0030204.].

Smart Medical Information Technology for Healthcare (SMITH).

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH's goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. OBJECTIVES: To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. GOVERNANCE AND POLICIES: SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals' Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. METHODOLOGY AND ARCHITECTURAL FRAMEWORK: To share medical and research data, SMITH's information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM2 for enterprise architecture modeling supports a consistent development process.The DIC reference architecture determines the services, applications and the standardsbased communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. USE CASES: The methodological use case "Phenotype Pipeline" (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case "Algorithmic Surveillance of ICU Patients" (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a "hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections" (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. DISCUSSION: SMITH's strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals' information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period.

Dynamic prediction of the need for renal replacement therapy in intensive care unit patients using a simple and robust model.

We aimed at identifying a model that dynamically predicts future need for renal replacement therapy (RRT) in intensive care unit (ICU) patients and can easily be implemented for online monitoring at the bedside. 7290 interdisciplinary ICU admissions were investigated. Patients with <3 days of stay or RRT in the first 2 days were excluded. 1624 of the remaining 2625 patients had a normal serum creatinine at admission. Every second of these 1624 patients was used for model calibration whereas the other half and, in addition, the 1001 patients with elevated serum creatinine were exclusively used for validation. Discriminant analysis was used to determine and validate a combination of clinical parameters that predicts the need for RRT 72 h ahead. Based on the calibration sample, stepwise discriminant analysis selected the serum values of (1) current urea, (2) current lactate, (3) the ratio of current and admission serum creatinine, and (4) the mean urine output of the previous 24 h. In the validation datasets, the model reached areas under the receiver operating characteristic curve of 0.866 and 0.833 in patients with normal and elevated serum creatinine at admission, respectively. Moreover, the model's predictive value extended to at least 5 days prior to initiation of RRT and exceeded that of the RIFLE classification at all investigated prediction intervals. We identified a robust model that dynamically predicts the future need for RRT successfully. This tool may help improve timing of therapy and prognosis in ICU patients.

Differential Effects of Left Ventricular Pacing Sites on Regional Contraction Patterns and Global Performance.

OBJECTIVE: To define the differential effect of site-specific ventricular counterpacing efficacy during cardiac resynchronization therapy (CRT) to identify the most informative imaging views to quantify it. Cross-sectional and long-axis views commonly are used to assess left ventricular (LV) contractility. DESIGN: The effects of LV apical (LVa) and free-wall (LVfw) pacing during CRT on long- and short-axis contraction, cardiac output, and stroke work were assessed in an open-chested acute canine model to determine whether LVa and LVfw would induce earlier apical than basilar LV radial contraction and earlier free-wall than septal contraction, respectively. Apical (CRTa) and free-wall (CRTfw) using right ventricular (RV) pacing-induced dyssynchrony also were examined. SETTING: University large animal research laboratory. PARTICIPANTS: Ten acutely anesthetized and instrumented open-chested purpose-bred dogs. INTERVENTIONS: RV pacing served as the model of cardiac dyssynchrony. Selective LVfw and LVa pacing alone or with RV (CRTfw and CRTa, respectively) were studied relative to right atrial pacing (RA) as the control. MEASUREMENTS AND MAIN RESULTS: Two pairs of 3 ultrasonic crystals were place along the LV longitudinal axis-apex and mid-to-base pairs along septal and free wall lines. Conductance catheter-defined longitudinal LV segmental volumes and pressure-volume data were collected. RV decreased cardiac output and stroke work compared with RA (2.0±0.3 v 1.4±0.1 L/min; 137±22 v 60±14 mJ; p<0.05, respectively). LVfw but not LVa decreased stroke work (130±35 mJ), and CRTa but not CRTfw improved both (2.1±0.2 L/min; 113±13 mJ; p<0.01 v RV pacing). No difference in time to minimal length free wall-to-septal crystal was seen with pacing. Both LVa and CRTa displayed increased apical-to-basilar shortening delay compared with RA, RV, and LVfw (42±47, 9±105, and 1±46 msec, respectively; p<0.05). No matching regional LV volume changes were seen during LVa. CONCLUSIONS: LV functional analysis from only a cross-sectional plane may be insufficient to characterize improved LV contraction synchrony during multisite CRT.

The inverse problem in mathematical biology.

Biological systems present particular challengers to model for the purposes of formulating predictions of generating biological insight. These systems are typically multi-scale, complex, and empirical observations are often sparse and subject to variability and uncertainty. This manuscript will review some of these specific challenges and introduce current methods used by modelers to construct meaningful solutions, in the context of preserving biological relevance. Opportunities to expand these methods are also discussed.

Robust model-based quantification of global ventricular torsion from spatially sparse three-dimensional time series data by orthogonal distance regression: evaluation in a canine animal model under different pacing regimes.

BACKGROUND: Quantification of global ventricular rotational deformation, expressed as twist or torsion, and its dynamic changes is important in understanding the pathophysiology of heart disease and its therapy. Various techniques, such as sonomicrometry, allow tracking of specific sites within the myocardium. Quantification of twist from such data requires a longitudinal reference axis of rotation. Current methods require specific positioning and numbers of myocardial markers and assumptions about temporal positional evolution that may be violated during dyssynchronous contraction. METHODS: We present a new method to assess myocardial twist that makes minimal fully explicit assumptions while removing extraneous assumptions, by performing a least squares orthogonal distance regression of all position data on an ellipsoidal ventricular model. Rotational deformation is quantified in terms of the ellipsoid's internal coordinate system, allowing intuitive visualization. RESULTS: We tested this method on a set of sparse, noisy sonomicrometric crystal data in dogs under different pacing regimes to model dyssynchrony and cardiac resynchronization. We found that this method yielded robust and plausible data. This technique is also fully automated while identifying when data may be insufficient for reliable quantification of rotational deformation. CONCLUSION: This approach may allow future analysis of myocardial contraction with less tracking sites and relaxed positioning requirements while identifying situations where data are insufficient for reliable quantification of rotational deformation.