Search

BackgroundA population-level survey (PLS) is an essential and standard method used in public health research that supports the quantification of sociodemographic events, public health policy development, and intervention designs. Data collection mechanisms in PLS seem to be a significant determinant in avoiding mistakes. Using electronic devices such as smartphones and tablet computers improves the quality and cost-effectiveness of public health surveys. However, there is a lack of systematic evidence to show the potential impact of electronic data collection tools on data quality and cost reduction in interviewer-administered surveys compared with the standard paper-based data collection system. ObjectiveThis systematic review aims to evaluate the impact of the interviewer-administered electronic data collection methods on data quality and cost reduction in PLS compared with traditional methods. MethodsWe conducted a systematic search of MEDLINE, CINAHL, PsycINFO, the Web of Science, EconLit, Cochrane CENTRAL, and CDSR to identify relevant studies from 2008 to 2018. We included randomized and nonrandomized studies that examined data quality and cost reduction outcomes, as well as usability, user experience, and usage parameters. In total, 2 independent authors screened the title and abstract, and extracted data from selected papers. A third author mediated any disagreements. The review authors used EndNote for deduplication and Rayyan for screening. ResultsOur search produced 3817 papers. After deduplication, we screened 2533 papers, and 14 fulfilled the inclusion criteria. None of the studies were randomized controlled trials; most had a quasi-experimental design, for example, comparative experimental evaluation studies nested on other ongoing cross-sectional surveys. A total of 4 comparative evaluations, 2 pre-post intervention comparative evaluations, 2 retrospective comparative evaluations, and 4 one-arm noncomparative studies were included. Meta-analysis was not possible because of the heterogeneity in study designs, types, study settings, and level of outcome measurements. Individual paper synthesis showed that electronic data collection systems provided good quality data and delivered faster compared with paper-based data collection systems. Only 2 studies linked cost and data quality outcomes to describe the cost-effectiveness of electronic data collection systems. Field data collectors reported that an electronic data collection system was a feasible, acceptable, and preferable tool for their work. Onsite data error prevention, fast data submission, and easy-to-handle devices were the comparative advantages offered by electronic data collection systems. Challenges during implementation included technical difficulties, accidental data loss, device theft, security concerns, power surges, and internet connection problems. ConclusionsAlthough evidence exists of the comparative advantages of electronic data collection compared with paper-based methods, the included studies were not methodologically rigorous enough to combine. More rigorous studies are needed to compare paper and electronic data collection systems in public health surveys considering data quality, work efficiency, and cost reduction. International Registered Report Identifier (IRRID)RR2-10.2196/10678

The digital transformation has influenced medical pathways in clinical routine and research as never before. This transformation requires multiple competencies in digital health from health professionals. To address learning objectives for teaching, the national project group „Teaching Medical Informatics in Medicine“ of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) published a competency-based catalog in 2012. The project group has turned into working group with regular meetings to continuously plan, discuss, develop and harmonize teaching content in medical schools on a national level. After six years have passed, an updated catalog has been proposed, reviewed and consented by the working group. The new catalog specifically covers new aspects as patient empowerment, patient apps, precision medicine and further minor amendments. It is proposed as guidance for teaching contents of medical informatics at medical schools and will be subject to continuous developments and harmonization with ongoing digitization initiatives by the clinical disciplines.

BackgroundPeriodic demographic health surveillance and surveys are the main sources of health information in developing countries. Conducting a survey requires extensive use of paper-pen and manual work and lengthy processes to generate the required information. Despite the rise of popularity in using electronic data collection systems to alleviate the problems, sufficient evidence is not available to support the use of electronic data capture (EDC) tools in interviewer-administered data collection processes. ObjectiveThis study aimed to compare data quality parameters in the data collected using mobile electronic and standard paper-based data capture tools in one of the health and demographic surveillance sites in northwest Ethiopia. MethodsA randomized controlled crossover health care information technology evaluation was conducted from May 10, 2016, to June 3, 2016, in a demographic and surveillance site. A total of 12 interviewers, as 2 individuals (one of them with a tablet computer and the other with a paper-based questionnaire) in 6 groups were assigned in the 6 towns of the surveillance premises. Data collectors switched the data collection method based on computer-generated random order. Data were cleaned using a MySQL program and transferred to SPSS (IBM SPSS Statistics for Windows, Version 24.0) and R statistical software (R version 3.4.3, the R Foundation for Statistical Computing Platform) for analysis. Descriptive and mixed ordinal logistic analyses were employed. The qualitative interview audio record from the system users was transcribed, coded, categorized, and linked to the International Organization for Standardization 9241-part 10 dialogue principles for system usability. The usability of this open data kit–based system was assessed using quantitative System Usability Scale (SUS) and matching of qualitative data with the isometric dialogue principles. ResultsFrom the submitted 1246 complete records of questionnaires in each tool, 41.89% (522/1246) of the paper and pen data capture (PPDC) and 30.89% (385/1246) of the EDC tool questionnaires had one or more types of data quality errors. The overall error rates were 1.67% and 0.60% for PPDC and EDC, respectively. The chances of more errors on the PPDC tool were multiplied by 1.015 for each additional question in the interview compared with EDC. The SUS score of the data collectors was 85.6. In the qualitative data response mapping, EDC had more positive suitability of task responses with few error tolerance characteristics. ConclusionsEDC possessed significantly better data quality and efficiency compared with PPDC, explained with fewer errors, instant data submission, and easy handling. The EDC proved to be a usable data collection tool in the rural study setting. Implementation organization needs to consider consistent power source, decent internet connection, standby technical support, and security assurance for the mobile device users for planning full-fledged implementation and integration of the system in the surveillance site.

[english] IEC 80001-1 is an international standard and offers recommendations for a risk management process for medical information technology networks (MITs). MITs are defined as IT networks incorporating at least one medical device. The goal is to build and maintain reliable and secure MITs for hospitals of all kids. To achieve it, the standard suggests applying risk management and defines the roles involved as well as their responsibilities. A central role is the medical IT-network risk manager, assigned by the top management of organizations. He communicates with and mediates between clinical, medical device and IT divisions and compiles risk relevant facts usually distributed among them. All identified risks are analyzed, evaluated and documented in the risk management file along with counter measures and a final assessment of acceptability.We acknowledge that implementing the suggested process will create an overhead cost in documentation and – partly by extension – in personnel. However we believe that the investment at the start of projects is worthwhile, because it helps to prevent or solve problems in later stages. Especially consecutive projects can profit from the investment, reducing required effort and costs. Furthermore, a reliable and secure MIT forms the basis for frictionless routine operations and innovations for connected medical devices. Hence the investment is justified. Applying risk management to the whole cooperation all at once is unrealistic. Focusing on parts of the network, which are crucial to a new project is more recommendable. With a smaller scope, risk management remains feasible and can later be expanded to other parts of the network.IEC 80001-1 demands communication among involved employees from different specialties and divisions. This offers a chance for cooperation to find better decisions and solutions regarding an organization’s medical IT network.[german] Die IEC 80001-1 ist eine Norm, die Empfehlungen für einen Risikomanagementprozess für medizinische IT-Netzwerke (MIT) – also Netzwerke mit angeschlossenen Medizinprodukten – gibt. Das Ziel ist der Aufbau und Betrieb von stabilen und sicheren IT-Netzwerken in Kliniken. Die Empfehlungen richten sich vor allem an die Betreiber von Krankenhäusern, weisen Verantwortlichkeiten innerhalb einer verantwortlichen Organisation (meist einer Klinik) zu und geben deren Interaktion vor. Eine zentrale Rolle ist der MIT Risiko-Manager, der von der Geschäftsführung beauftragt wird und die Anstrengungen in Richtung Risikomanagement koordiniert. Dazu steht er in Kontakt mit Mitarbeitern von klinischen Abteilungen, der Medizintechnik, der IT-Abteilung und auch den Herstellern der beteiligten Medizinprodukte. Auf diese Art wird Wissen, das oft nur an diesen verschiedenen Stellen vorhanden ist, gesammelt und in der Risikomanagement-Akte dokumentiert. Jede gefundene Bedrohungs-Situation wird analysiert und nach ihrer Wahrscheinlichkeit und ihren (geschätzten) Folgen bewertet. Danach wird festgelegt, ob ein bestehendes Restrisiko tragbar ist und wie Gegenmaßnahmen umgesetzt werden. Der Dialog, der während des Informationsaustausches entsteht, nützt allen Parteien und trägt maßgeblich dazu bei, MITs stabiler und sicherer zu machen.Die Umsetzung der Norm erfordert einen Mehraufwand an Personal und Dokumentation. Nach Einschätzung der Autoren lohnt sich diese Investition am Anfang von Projekten, da sich dadurch Probleme im späteren Projektverlauf vermeiden oder zumindest reduzieren lassen. Spätestens bei Anschlussprojekten ist hier mit einer Aufwands- und damit Kostenersparnis zu rechnen. Ein stabiles und sicheres Netzwerk stellt die Basis für reibungslosen Routinebetrieb aber vor allem auch für Innovation im Bereich der vernetzten Medizingeräte dar. Eine sofortige unternehmensweite Einführung der IEC 80001-1 ist ein unrealistischer Ansatz. Vielmehr ist zu empfehlen, sich zunächst auf bestimmte Subnetze zu konzentrieren, die innerhalb eines Projektes oder eines bestimmten Prozesses wichtig sind. In einem solchen kleineren Rahmen bleibt der Aufwand für das Risikomanagement beherrschbar und lässt sich danach auf weitere Bereiche ausdehnen.Die IEC 80001-1 fordert alle Beteiligten zur Kommunikation auf und bietet so die Chance, aus einer Kooperation heraus die besten Entscheidungen im Sinne der verantwortlichen Organisation zu treffen.

[english] Competencies in Medical Informatics are important for all physicians, for instance regarding electronic health records or digital imaging systems. Physicians spend more than 25% of their working time with information management. The International Medical Informatics Association (IMIA) recommends 40 hours of curricular training dedicated to Medical Informatics for physicians. In this context, a national project group of the German Association for Medical Informatics, Biometry and Epidemiology developed a catalog of learning objectives for medical students regarding Medical Informatics. Seven areas of competencies were identified: Medical documentation and information processing, medical classifications and terminologies, information systems in healthcare, health telematics and telemedicine, data protection and security, access to medical knowledge and medical signal-/image processing. Overall, 42 learning objectives were identified and consented. For each objective a rationale why a physician needs this competence was provided. In addition, each objective was categorized according to competence context (A=covered by Medical Informatics, B=core subject of Medical Informatics, C=optional subject of Medical Informatics), competence level (1=referenced knowledge, 2=applied knowledge, 3=routine knowledge) and CanMEDS competence role (1=Medical Expert, 2=Communicator, 3=Collaborator, 4=Manager, 5=Health Advocate, 6=Professional, 7=Scholar). [german] Von der GMDS-Projektgruppe „MI-Lehre in der Medizin“ wurde unter Beteiligung aller Standorte, an denen derzeit Lehrveranstaltungen in diesem Fach durchgeführt werden, in einem mehrstufigen Verfahren ein national konsentierter Lernzielkatalog Medizinische Informatik (MI) für Studierende der Humanmedizin erarbeitet, der sich am Konzept des Nationalen Kompetenzbasierten Lernzielkatalogs Medizin (NKLM) orientiert.

Aim: This paper’s aim is to evaluate an e-learning-platform, which is meant to introduce medical students to medical informatics’ contents. Methods: The e-learning-platform MindMailer regularly sends e-mails, containing links to the lecture-related exercise forms to the students. It has been established as part of medical informatics training and was evaluated by means of an online survey. Results: The questionnaire has been accessed by 91 (60%) of 151 students and finished by 81 (54%). The leading motivations to use the MindMailer were the granted four extra points at the exam, and the training effect therefor. The students declared that they have been sensitized to medical informatics’ issues and that it has been an effective training-tool for the exam. Conclusion: The students gave a good rating to the MindMailer. We succeeded in introducing the medical students to medical informatics. However, the tool should not be established at all subjects in medical education in order not to jeopardize the beneficial effect of continuous learning by accepting an ‘alert-overflow’ with a consecutive alert-fatigue.

Introduction: The configuration of electronic data capture (EDC) systems has a relevant impact on data quality in studies and patient registries. The objective was to develop a method to visualise the configuration of an EDC system to check the completeness and correctness of the data definition and rules. Methods: Step 1: transformation of the EDC data model into a graphical model, step 2: Checking the completeness and consistency of the data model, step 3: correction of identified findings. This process model was evaluated on the patient registry EpiReg. Results: Using the graphical visualisation as a basis, 21 problems in the EDC configuration were identified, discussed with an interdisciplinary team, and corrected. Conclusion: The tested methodological approach enables an improvement in data quality by optimising the underlying EDC configuration. [ABSTRACT FROM AUTHOR]

Introduction: Process Mining (PM) has emerged as a transformative tool in healthcare, facilitating the enhancement of process models and predicting potential anomalies. However, the widespread application of PM in healthcare is hindered by the lack of structured event logs and specific data privacy regulations. Concept: This paper introduces a pipeline that converts routine healthcare data into PM-compatible event logs, leveraging the newly available permissions under the Health Data Utilization Act to use healthcare data. Implementation: Our system exploits the Core Data Sets (CDS) provided by Data Integration Centers (DICs). It involves converting routine data into Fast Healthcare Interoperable Resources (FHIR), storing it locally, and subsequently transforming it into standardized PM event logs through FHIR queries applicable on any DIC. This facilitates the extraction of detailed, actionable insights across various healthcare settings without altering existing DIC infrastructures. Lessons Learned: Challenges encountered include handling the variability and quality of data, and overcoming network and computational constraints. Our pipeline demonstrates how PM can be applied even in complex systems like healthcare, by allowing for a standardized yet flexible analysis pipeline which is widely applicable.The successful application emphasize the critical role of tailored event log generation and data querying capabilities in enabling effective PM applications, thus enabling evidence-based improvements in healthcare processes. [ABSTRACT FROM AUTHOR]