Objective: This study explored healthcare quality issues affecting the reporting and investigation levels of digital incident reporting systems. Methods: A total of 38 health information technology-related incident reports (free-text narratives) were collected from one of Sweden's national incident reporting repositories. The incidents were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the types of issues and consequences. The framework was applied in two fields, ‘event description’ by the reporters and ‘manufacturer's measures’, to assess the quality of reporting incidents by the reporters. Additionally, the contributing factors, i.e., either human or technical factors for both fields, were identified to evaluate the quality of the reported incidents. Results: Five types of issues were identified and changes made between before-and-after investigations: Machine to software-related issues ( n = 8), machine to use-related issues ( n = 5), software to software-related issues ( n = 5), use to software-related issues ( n = 4) and use to use-related issues ( n = 1). Over two-thirds ( n = 15) of the incidents demonstrated a change in the contributing factors after the investigation. Only four incidents were identified as altering the consequences after the investigation. Conclusion: This study shed some light on the issues of incident reporting and the gap between the reporting and investigation levels. Facilitating sufficient staff training sessions, agreeing on common terms for health information technology systems, refining the existing classifications systems, enforcing mini-root cause analysis, and ensuring unit-based local reporting and standard national reporting may help bridge the gap between reporting and investigation levels in digital incident reporting.

Objective: To identify a subset of software issues occurring in daily Swedish healthcare practice and devise a set of local solutions to overcome the challenges. Methods: A sample of 46 incident reports was collected from one of Sweden's national incident reporting repositories, ranging from June 2019 to December 2021. The reports were first subjected to an algorithm to identify if they were health information technology-related incidents and were analysed using an existing framework, i.e., the Health Information Technology Classification System, to identify the software-related incidents. The incidents associated with software issues were then subjected to thematic analysis, in which themes were extracted and presented under the category assigned by the existing framework used. Results: Of 46 reports, 45 (with one exception) were included using the algorithm. Of 45 incidents, 31 software-related incidents were identified using the classification system. Six types of software issues were identified, including software functionality ( n = 10), interface with other software systems or components ( n = 10), system configuration ( n = 7), interface with devices ( n = 2), record migration ( n = 1) and increased volume of transactions ( n = 1). Each issue was further categorised into different themes; for example, software interface-related problems were grouped into ‘two patients being active in the system simultaneously’ ( n = 6) and ‘transfer of patient information’ ( n = 4). Conclusions: The study provided some insights into software issues and relevant consequences. A set of local solutions were devised to overcome the present challenges encountered in Swedish healthcare in their daily clinical practice. Systematic identification and characterisation of such software challenges should be a routine part of clinical practice for all major health information technology implementations.

Despite many benefits, the extensive deployment of Health Information Technology (HIT) systems by healthcare organizations has encountered many challenges, particularly in the field of telemetry concerning patient monitoring and its operational workflow. These challenges can add more layers of complexity when an unplanned software security patching is performed, affecting patient monitoring and causing disruption in daily clinical operations. This study is a reflection on what happened associated with software security patching and why it happened through the lens of an incident report to develop potential preventive and corrective strategies using qualitative analyses—inductive and deductive approaches. There is a need for such analyses to identify the underlying mechanism behind such issues since very limited research has been conducted on the study of software patching. The incident was classified as a “software functionality” issue, and the consequence was an “incident with a noticeable consequence but no patient harm”, and the contributing factor was a software update, i.e., software security patching. This report describes how insufficient planning of software patching, lack of training for healthcare professionals, contingency planning on unplanned system disruption, and HIT system configuration can compromise healthcare quality and cause risks to patient safety. We propose 15 preventive and corrective strategies grouped under four key areas based on the system approach and social-technical aspects of the patching process. The key areas are (i) preparing, developing, and deploying patches; (ii) training the frontline operators; (iii) ensuring contingency planning; and (iv) establishing configuration and communication between systems. These strategies are expected to minimize the risk of HIT-related incidents, enhance software security patch management in healthcare organizations, and improve patient safety. However, further discussion should be continued about general HIT problems connected to software security patching.

Objective: This study explored the Swedish digital health testbeds through the lens of complexity science. Methods: The purposive sampling was used to identify 38 digital health testbed organizations to conduct interviews in written or audio-conferencing. The interview responses were aggregated and analyzed using thematic analysis. The themes were mainly generated through complexity theory and the principles of complex adaptive systems. Results: Fifteen testbed organizations responded, comprising 13 written responses and two audio-conferencing. Five main theoretical themes were generated: agents and diversity, connections and communication, adaptation and learning, perturbations, and path dependence. Agents and diversity depicted different types of testbeds, stakeholders and innovation, and the primary function and purpose of the testbeds. Various factors enhancing connections and communications among multiple stakeholders were identified, such as the quality of e-health solutions and the 2030 Agenda for Sustainable Development. Some adaptation and learning factors, such as internal reorganization, sharing and creating learning opportunities, and additional funding, guaranteed the sustainability of testbeds. Perturbations were characterized by two factors: non-linear interactions – lack of commitment and transparency in stakeholders' engagement, and uncertainty about testbed definitions and concepts. Path dependence highlighted the importance of history, such as previous positive and negative experiences. Conclusion: This study provided insights into testbeds' organization, their functions, how various aspects were challenged, and how they adapted to overcome and improve the system issues. Identifying the stakeholders and relevant factors, commissioning an evaluation, backing up with a contingency plan, securing adequate funding, and disseminating the findings can improve the testbeds' design and implementation.

This study aimed to examine health information technology-related incidents and identify risks associated with multiple patients’ management. Sources of information comprised interviews with healthcare professionals and three small sets of local voluntary incident reports using two sampling strategies, purposive and snowball sampling. Incident reports, in the form of free-text narratives, were aggregated for analysis using the Health Information Technology Classification System and thematic analysis. Of 95 incidents, 176 issues were identified, comprising 77% ( n = 136) technical issues, and 23% ( n = 40) use or human-related issues. Human issues were over two times more likely to harm patients (OR 2.25, 95% CI 1.01 - 4.98) than technical issues. Incidents that affected multiple patients’ care accounted for 70% ( n = 66) of the total sample, and large-scale events comprised 39% ( n = 26) of the incidents that affected multiple patients' care. Systematically identifying and characterizing such incidents should be prioritized for health information technology implementations.

Introduction: Despite many benefits offered by Health Information Technology (HIT) systems, new technology brings new and unforeseen risks to healthcare quality and patient safety if they're not properly planned, designed, implemented, and managed. This study examined health information technology-related (HIT) incidents to identify patient details-related issues, their association with contributing factors, and outcomes.Methods: Sources of information comprised retrospectively collected incident reports (n = 95) using two sampling methods, i.e., purposive and snowball sampling. The incident reports were analyzed using both the inductive method (thematic analysis) and the deductive approach using an existing framework, i.e., the International Classification for Patient Safety.Results: The studies identified 90 incidents with 120 patient details-related issues—categorized as either information-related (48%) or documentation-related (52%) problems; around two-thirds of the 120 issues were characterized by human factors. Of the total sample, 87 contributing factors were identified, of which “medical device/system” (45%) and “documentation” (20%) were the most common contributing factors. Of 90 incidents, more than half (59%) comprised patient-related outcomes—patient inconvenience (47%) and patient harm (12%) and the remaining 41% (n = 37) included staff or organization-related outcomes.Discussion: More than half of the incidents resulted in patient-related outcomes, namely patient inconvenience and patient harm, including disease risks, severe health deterioration, injury, and even patient death. Incidents associated with patient details can cause deleterious effects; therefore, characterizing them should be a routine part of clinical practice to improve the constantly changing healthcare system.