Usability and User Experience of an mHealth App for Therapy Support of Patients With Breast Cancer: Mixed Methods Study Using Eye Tracking.

BACKGROUND: Early identification of quality of life (QoL) loss and side effects is a key challenge in breast cancer therapy. Digital tools can be helpful components of therapeutic support. Enable, a smartphone app, was used in a multicenter, prospective randomized controlled trial in 3 breast cancer centers. The app simultaneously serves as a therapy companion (eg, by displaying appointments), a tool for documenting QoL (eg, by enabling data collection for QoL questionnaires), and documentation of patient-reported side effects. The need for digital tools is continually rising. However, evidence of the effects of long-term use of mobile health (mHealth) apps in aftercare for patients with breast cancer is limited. Therefore, evaluating the usability and understanding the user experience of this mHealth app could potentially contribute valuable insights in this field. OBJECTIVE: A usability study was conducted to explore how patients with breast cancer receiving neoadjuvant, adjuvant, or palliative outpatient treatment rated their engagement with the app , the user experience, and the benefits of using the app. METHODS: A mixed methods approach was chosen to combine subjective and objective measures, including an eye-tracking procedure, a standardized usability questionnaire (mHealth App Usability Questionnaire), and semistructured interviews. Participants were surveyed twice during the study period. Interviews were transcribed verbatim and analyzed using thematic analysis. Analysis of the eye-tracking data was carried out using the tracker-integrated software. Descriptive analysis was conducted for the quantitative data. RESULTS: The mHealth App Usability Questionnaire results (n=105) indicated good overall usability for 2 different time points (4 wk: mean 89.15, SD 9.65; 20 wk: mean 85.57, SD 12.88). The qualitative analysis of the eye-tracking recordings (n=10) and interviews (n=16) showed that users found the Enable app easy to use. The design of the app, information about therapies and side effects, and usefulness of the app as a therapy companion were rated positively. Additionally, participants contributed requests for additional app features and suggestions for improving the content and usability of the app. Relevant themes included optimization of the appointment feature, updating the app's content regularly, and self-administration. In contrast to the app's current passive method of operation, participants expressed a desire for more active engagement through messaging, alarms, or emails. CONCLUSIONS: The results of this study demonstrate the good usability of the Enable app as well as the potential for further development. We concluded from patients' feedback and requests that mHealth apps could benefit from giving patients a more active role (eg, being able to actively document side effects as they occur). Additionally, regular updates of app content could further contribute to encouraging continued use of mHealth apps. Our findings may also assist other researchers in tailoring their mHealth apps to the actual needs of patients undergoing breast cancer therapy.

Exploring Stakeholder Requirements to Enable Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Results of a Multistep Mixed Methods Study.

BACKGROUND: Legal, controlled, and regulated access to high-quality data from academic hospitals currently poses a barrier to the development and testing of new artificial intelligence (AI) algorithms. To overcome this barrier, the German Federal Ministry of Health supports the "pAItient" (Protected Artificial Intelligence Innovation Environment for Patient Oriented Digital Health Solutions for developing, testing and evidence-based evaluation of clinical value) project, with the goal to establish an AI Innovation Environment at the Heidelberg University Hospital, Germany. It is designed as a proof-of-concept extension to the preexisting Medical Data Integration Center. OBJECTIVE: The first part of the pAItient project aims to explore stakeholders' requirements for developing AI in partnership with an academic hospital and granting AI experts access to anonymized personal health data. METHODS: We designed a multistep mixed methods approach. First, researchers and employees from stakeholder organizations were invited to participate in semistructured interviews. In the following step, questionnaires were developed based on the participants' answers and distributed among the stakeholders' organizations. In addition, patients and physicians were interviewed. RESULTS: The identified requirements covered a wide range and were conflicting sometimes. Relevant patient requirements included adequate provision of necessary information for data use, clear medical objective of the research and development activities, trustworthiness of the organization collecting the patient data, and data should not be reidentifiable. Requirements of AI researchers and developers encompassed contact with clinical users, an acceptable user interface (UI) for shared data platforms, stable connection to the planned infrastructure, relevant use cases, and assistance in dealing with data privacy regulations. In a next step, a requirements model was developed, which depicts the identified requirements in different layers. This developed model will be used to communicate stakeholder requirements within the pAItient project consortium. CONCLUSIONS: The study led to the identification of necessary requirements for the development, testing, and validation of AI applications within a hospital-based generic infrastructure. A requirements model was developed, which will inform the next steps in the development of an AI innovation environment at our institution. Results from our study replicate previous findings from other contexts and will add to the emerging discussion on the use of routine medical data for the development of AI applications. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/42208.

Exploring Stakeholder Requirements to Enable the Research and Development of Artificial Intelligence Algorithms in a Hospital-Based Generic Infrastructure: Protocol for a Multistep Mixed Methods Study.

BACKGROUND: In recent years, research and developments in advancing artificial intelligence (AI) in health care and medicine have increased. High expectations surround the use of AI technologies, such as improvements for diagnosis and increases in the quality of care with reductions in health care costs. The successful development and testing of new AI algorithms require large amounts of high-quality data. Academic hospitals could provide the data needed for AI development, but granting legal, controlled, and regulated access to these data for developers and researchers is difficult. Therefore, the German Federal Ministry of Health supports the Protected Artificial Intelligence Innovation Environment for Patient-Oriented Digital Health Solutions for Developing, Testing, and Evidence-Based Evaluation of Clinical Value (pAItient) project, aiming to install the AI Innovation Environment at the Heidelberg University Hospital in Germany. The AI Innovation Environment was designed as a proof-of-concept extension of the already existing Medical Data Integration Center. It will establish a process to support every step of developing and testing AI-based technologies. OBJECTIVE: The first part of the pAItient project, as presented in this research protocol, aims to explore stakeholders' requirements for developing AI in partnership with an academic hospital and granting AI experts access to anonymized personal health data. METHODS: We planned a multistep mixed methods approach. In the first step, researchers and employees from stakeholder organizations were invited to participate in semistructured interviews. In the following step, questionnaires were developed based on the participants' answers and distributed among the stakeholders' organizations to quantify qualitative findings and discover important aspects that were not mentioned by the interviewees. The questionnaires will be analyzed descriptively. In addition, patients and physicians were interviewed as well. No survey questionnaires were developed for this second group of participants. The study was approved by the Ethics Committee of the Heidelberg University Hospital (approval number: S-241/2021). RESULTS: Data collection concluded in summer 2022. Data analysis is planned to start in fall 2022. We plan to publish the results in winter 2022 to 2023. CONCLUSIONS: The results of our study will help in shaping the AI Innovation Environment at our academic hospital according to stakeholder requirements. With this approach, in turn, we aim to shape an AI environment that is effective and is deemed acceptable by all parties. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/42208.

Engaging patients to develop a customized digital health companion for periodontitis: Study protocol.

Periodontitis is a chronic inflammatory disease resulting in the destruction of tooth-supporting tissues. It affects billions of people around the globe and substantiates an enormous economic burden to society. Digital tools such as mobile Health (mHealth) applications have the potential to increase patient engagement, knowledge about the disease, and adherence to treatment recommendations. Digital health companions represent a new kind of digital tool aiming to support patients throughout their course of periodontal care. This paper presents the study protocol of the Paro-ComPas project which aims to co-develop and evaluate a digital patient companion application ("app") to empower patients along their journey with periodontitis. As a first step, a qualitative study design encompassing semi-structured interviews with patients and experts as well as focus group discussions (FGD) will be used. Patients in different stages of periodontal care will be recruited from dental practices across Germany and are invited to share their experiences and opinions about their care and potential areas for support. Experts from relevant areas (e.g., mHealth, behavior change psychology, oral health, and dental hygiene) will be interviewed to map a holistic view on the current delivery of care and best practices of mHealth development. After setting up a minimal viable product (MVP) based on a requirements analysis, FGDs with patients will take place to incorporate user feedback and finalize the development of the prototypic app. The prototypic app will then be evaluated in a randomized, multi-center clinical trial in comparison with the current standard of care. Finally, a comprehensive implementation roadmap will be developed together with all relevant stakeholders. This comprehensive approach will allow us to map the patient journey and develop a digital health companion tailored to the needs of patients with periodontitis using an already existing indication independent medical companion toolbox. Novel insights into patients' knowledge and perception of periodontal disease as well as barriers in adherence to periodontal care pathways will be provided. This knowledge will be converted in a systematically tailored companion app to serve the needs and preferences of people to better address periodontitis. The results from the clinical trial will provide unique insights into the extent to which the patient companion app contributes to adherence to periodontal care. Although mHealth applications have become popular in recent years, only few apps focusing on promotion of oral health have been released so far. Our study presents a novel and comprehensive approach to both co-developing and evaluating a proof of concept for a digital health companion for patients with periodontitis.

Mobile Access to Medical Records in Heart Transplantation Aftercare: Mixed-Methods Study Assessing Usability, Feasibility and Effects of a Mobile Application.

BACKGROUND: Patient access to medical records can improve quality of care. The phellow application (app) was developed to provide patients access to selected content of their medical record. It was tested at a heart transplantation (HTx) outpatient clinic. The aims of this study were (1) to assess usability of phellow, (2) to determine feasibility of implementation in routine care, and (3) to study the effects app use had on patients' self-management. METHODS: Usability was measured quantitatively through the System Usability Scale (SUS). Furthermore, usability, feasibility, and effects on self-management were qualitatively assessed through interviews with users, non-users, and health care providers. RESULTS: The SUS rating (n = 31) was 79.9, indicating good usability. Twenty-three interviews were conducted. Although appreciation and willingness-to-use were high, usability problems such as incompleteness of record, technical issues, and complex registration procedures were reported. Improved technical support infrastructure, clearly defined responsibilities, and app-specific trainings were suggested for further implementation. Patients described positive effects on their self-management. CONCLUSIONS: To be feasible for implementation in routine care, usability problems should be addressed. Feedback on the effect of app use was encouraging. Accompanying research is crucial to monitor usability improvements and to further assess effects of app use on patients.

Estimation and Monitoring of Operating Room Utilization by a Distributed Streaming and Analytics Architecture Deployed at Heidelberg University Hospital's Medical Data Integration Center.

Operating rooms are a major cost factor in a hospital's budget. Therefore, there is a need for process optimization related to the operating rooms (OR). However, the collection of key figures for process optimization is often done manually by medical staff. This can be erroneous, inaccurate, time consuming, and incomplete. Automated, data-driven approaches are intended to address these problems and help to get the most precise picture possible of what is happening within the OR. At Heidelberg University Hospital (UKHD), a distributed AI based streaming analytics architecture was set up and integrated into the Medical Data Integration Center (MeDIC). This architecture can process, store, and visualize heterogeneous data from different sources. Data from medical devices and the video stream of the wall mounted cameras of four integrated operating rooms are ingested into our system. Aggregated and analyzed in real-time computed key figures including OR state and utilization numbers are visualized in a dashboard for monitoring and decision support. Because of high data protection hurdles the proposed system, especially the video analytics, was trained and tested with statists and did not run during real procedures. Studies to evaluate and test the system during live surgeries are planned.

Perspective of Information Technology Decision Makers on Factors Influencing Adoption and Implementation of Artificial Intelligence Technologies in 40 German Hospitals: Descriptive Analysis.

BACKGROUND: New artificial intelligence (AI) tools are being developed at a high speed. However, strategies and practical experiences surrounding the adoption and implementation of AI in health care are lacking. This is likely because of the high implementation complexity of AI, legacy IT infrastructure, and unclear business cases, thus complicating AI adoption. Research has recently started to identify the factors influencing AI readiness of organizations. OBJECTIVE: This study aimed to investigate the factors influencing AI readiness as well as possible barriers to AI adoption and implementation in German hospitals. We also assessed the status quo regarding the dissemination of AI tools in hospitals. We focused on IT decision makers, a seldom studied but highly relevant group. METHODS: We created a web-based survey based on recent AI readiness and implementation literature. Participants were identified through a publicly accessible database and contacted via email or invitational leaflets sent by mail, in some cases accompanied by a telephonic prenotification. The survey responses were analyzed using descriptive statistics. RESULTS: We contacted 609 possible participants, and our database recorded 40 completed surveys. Most participants agreed or rather agreed with the statement that AI would be relevant in the future, both in Germany (37/40, 93%) and in their own hospital (36/40, 90%). Participants were asked whether their hospitals used or planned to use AI technologies. Of the 40 participants, 26 (65%) answered "yes." Most AI technologies were used or planned for patient care, followed by biomedical research, administration, and logistics and central purchasing. The most important barriers to AI were lack of resources (staff, knowledge, and financial). Relevant possible opportunities for using AI were increase in efficiency owing to time-saving effects, competitive advantages, and increase in quality of care. Most AI tools in use or in planning have been developed with external partners. CONCLUSIONS: Few tools have been implemented in routine care, and many hospitals do not use or plan to use AI in the future. This can likely be explained by missing or unclear business cases or the need for a modern IT infrastructure to integrate AI tools in a usable manner. These shortcomings complicate decision-making and resource attribution. As most AI technologies already in use were developed in cooperation with external partners, these relationships should be fostered. IT decision makers should assess their hospitals' readiness for AI individually with a focus on resources. Further research should continue to monitor the dissemination of AI tools and readiness factors to determine whether improvements can be made over time. This monitoring is especially important with regard to government-supported investments in AI technologies that could alleviate financial burdens. Qualitative studies with hospital IT decision makers should be conducted to further explore the reasons for slow AI.

An Outpatient Management Strategy Using a Coronataxi Digital Early Warning System Reduces Coronavirus Disease 2019 Mortality.

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused sudden, severe strain to healthcare systems. Better outpatient management is required to save lives, manage resources effectively, and prepare for future pandemics. Methods: The Coronataxi digital early warning (CDEW) system deployed in Rhein-Neckar County and Heidelberg, Germany is an outpatient care system consisting of remote digital monitoring via a mobile application, a medical doctor dashboard, and medical care delivery to COVID-19 patients in home quarantine when indicated. Patients reported their symptoms, temperature, breathing rate, oxygen saturation, and pulse via the app. This single-center cohort study compared outcomes of the population with and without using the CDEW system. The primary outcome was mortality; the secondary outcomes were hospitalization, duration of hospitalization, intensive care therapy, and mechanical ventilation. Results: Mortality rate was 3- to 4-fold lower and hospitalization rate was higher in the CDEW cohort (459 patients) compared with the cohort without CDEW in the same test area and other regions (Mannheim, Karlsruhe town, Karlsruhe district, and Germany), (mortality rate: 0.65% [95% confidence interval {CI}, .13%-1.90%] versus 2.16%, 2.32%, 2.48%, 2.82% and 2.76%, respectively, P < .05 for all; hospitalization rate: 14.81% [95% CI, 11.69%-18.40%] versus 6.89%, 6.93%, 6.59%, 6.15%, and 7.22%, respectively, P < .001 for all). The median duration of hospitalization in the CDEW cohort was significantly lower compared with a national sentinel cohort (6 days [interquartile range {IQR}, 4-9.75 days] versus 10 days [IQR, 5-19 days]; Z = -3.156; P = .002). A total of 1.96% patients needed intensive care and 1.09% were mechanically ventilated. Conclusions: The CDEW system significantly reduced COVID-19 mortality and duration of hospitalization and can be applied to the management of future pandemics.

Integration of mobile sensors in a telemedicine hospital system: remote-monitoring in COVID-19 patients.

Aim: The goal is to design and, in a next step, establish a scalable, multi-center telemonitoring platform based on existing systems for monitoring COVID-19 patients in home quarantine. In particular, the focus will be on raw data acquisition, integration of sensor data into the hospital system, structured data storage, and interoperability. Subject and methods: Data necessary for monitoring, otherwise provided in various portals, will be continuously queried and integrated into the hospital system via a new interface in this proof-of-concept work. Results: Based on extensive preliminary work at Klinikum rechts der Isar with a structured clinical database, we extend our system's integration of raw data and visualization in dashboards, as well as scientific provision of data from mobile sensors for monitoring patients in home quarantine. Conclusion: Based on existing integrated telemonitoring systems supporting semantic and syntactic interoperability, short-term provision of scientific databases is possible. The integration of different mobile sensors into a clinical system for remote monitoring of patients around the clock is still new and to our knowledge unique.

Data Sharing in Distributed Architectures - Concept and Implementation in HiGHmed.

Medical routine data has the potential to benefit research. However, transferring this data into a research context is difficult. For this reason Medical Data Integration Centers are being established in German university hospitals to consolidate data from primary information systems in a single location. But, small data-sets from one organization can be insufficient to answer a research question adequately. In order to obtain larger data-sets, attempts to merge and provide data-sets across institutional boundaries are made. Therefore, this paper proposes a possible process that can extract, merge, pseudonymize and provide distributed data-sets from several organizations conforming to privacy regulations. This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4. The proposed solution is currently being deployed at eight university hospitals and one Trusted Third Party in the HiGHmed consortium.

Feasibility Queries in Distributed Architectures - Concept and Implementation in HiGHmed.

Medical routine data promises to add value for research. However, the transfer of this data into a research context is difficult. Therefore, Medical Data Integration Centers are being set up to merge data from primary information systems in a central repository. But, data from one organization is rarely sufficient to answer a research question. The data must be merged beyond institutional boundaries. In order to use this data in a specific research project, a researcher must have the possibility to query available cohort sizes across institutions. A possible solution for this requirement is presented in this paper, using a process for fully automated and distributed feasibility queries (i.e. cohort size estimations). This process is executed according to the open standard BPMN 2.0, the underlying process data model is based on HL7 FHIR R4 resources. The proposed solution is currently being deployed at eight university hospitals and one trusted third party across Germany.

Using openEHR in XDS.b Environments - Opportunities and Challenges.

The HiGHmed research project as part of Germany's Medical Informatics Initiative aims to establish Medical Data Integration Centers (MeDIC) at each participating institution to integrate data of multiple primary information systems in a single place. The MeDICs are based on an IHE XDS.b Affinity Domain in conjunction with an openEHR clinical data repository. This paper presents two ways of storing and retrieving structured and semantically annotated data from an openEHR repository whilst keeping data integrated in an existing IHE XDS.b infrastructure. Furthermore, the paper discusses multiple benefits of the presented approach as well as challenges and corresponding solutions.

Strengthening Interprofessional Requirements Engineering Through Action Sheets: A Pilot Study.

BACKGROUND: The importance of information and communication technology for healthcare is steadily growing. Newly developed tools are addressing different user groups: physicians, other health care professionals, social workers, patients, and family members. Since often many different actors with different expertise and perspectives are involved in the development process it can be a challenge to integrate the user-reported requirements of those heterogeneous user groups. Nevertheless, the understanding and consideration of user requirements is the prerequisite of building a feasible technical solution. In the course of the presented project it proved to be difficult to gain clear action steps and priorities for the development process out of the primary requirements compilation. Even if a regular exchange between involved teams took place there was a lack of a common language. OBJECTIVE: The objective of this paper is to show how the already existing requirements catalog was subdivided into specific, prioritized, and coherent working packages and the cooperation of multiple interprofessional teams within one development project was reorganized at the same time. In the case presented, the manner of cooperation was reorganized and a new instrument called an Action Sheet was implemented. This paper introduces the newly developed methodology which was meant to smooth the development of a user-centered software product and to restructure interprofessional cooperation. METHODS: There were 10 focus groups in which views of patients with colorectal cancer, physicians, and other health care professionals were collected in order to create a requirements catalog for developing a personal electronic health record. Data were audio- and videotaped, transcribed verbatim, and thematically analyzed. Afterwards, the requirements catalog was reorganized in the form of Action Sheets which supported the interprofessional cooperation referring to the development process of a personal electronic health record for the Rhine-Neckar region. RESULTS: In order to improve the interprofessional cooperation the idea arose to align the requirements arising from the implementation project with the method of software development applied by the technical development team. This was realized by restructuring the original requirements set in a standardized way and under continuous adjustment between both teams. As a result not only the way of displaying the user demands but also of interprofessional cooperation was steered in a new direction. CONCLUSIONS: User demands must be taken into account from the very beginning of the development process, but it is not always obvious how to bring them together with IT knowhow and knowledge of the contextual factors of the health care system. Action Sheets seem to be an effective tool for making the software development process more tangible and convertible for all connected disciplines. Furthermore, the working method turned out to support interprofessional ideas exchange.

Implementing the Patient Portal of the PEHR in the Metropolitan Region Rhine-Neckar - Experiences with Liferay.

A patient portal with access to a personal cross-enterprise electronic health record (PEHR) had to be developed for the project "INFormation technology for PATient-oriented healthcare in the Rhine-Neckar metropolitan region" (INFOPAT). Liferay was chosen as the platform technology in previous researches. Multiple portlets for patients, study members, security officers and administrators had been developed in Java. In this paper all portlets are presented. For three portlets the communication between them, Liferay and the PEHR are described in detail. To communicate with the PEHR a façade called IHE Connector had been implemented too. Despite the broad functionality of the Liferay Core some workarounds had to be implemented. The lack of information in the provided documentation of Liferay lead to delays in development. The Liferay IDE and Liferay itself showed an unstable state.

The Patient Portal of the Personal Cross-Enterprise Electronic Health Record (PEHR) in the Rhine-Neckar-Region.

Over the last years we stepwise implemented our vision of a personal cross-enterprise electronic health record (PEHR) in the Rhine-Neckar-Region in Germany. The patient portal is one part of the PEHR architecture with IHE connectivity. The patient is enabled to access and manage his medical record by use of the patient portal. Moreover, he can give his consent regarding which healthcare providers are allowed to send data into or read data from his medical record. Forthcoming studies will give evidence for improvements and further requirements to develop.

Patient Portal Integration - A Native IHE Connector Implementation for PEHR.

Providing patients with access to their medical data has recently evolved as a topic in several countries. Different approaches are possible. For example patient portals are used for patient access towards medical data. The University Hospital Heidelberg is engaged in a research project to develop a personal cross-enterprise electronic health record (PEHR). The objective of this work is to describe the architecture and implementation of a component called IHE Connector which represents the native IHE-based integration between the patient portal and the PEHR core components. The architecture of the PEHR is accepted based on international standards. The core components consist out of ready to use software products like a master patient index. The patient portal has been developed using Liferay framework. The IHE Connector is mainly based on the Open eHealth Integration Platform (IPF) Framework, which has been deeply integrated into the patient portal to support the needed IHE transactions. Several IHE profiles for sharing documents and patient information are supported by the IHE Connector. As IPF already provides interfaces for some IHE profiles others had to be developed from scratch. The IHE Connector can not only be used for connectivity between patient portal and PEHR core, but also provide connectivity for third party apps and healthcare providers' information systems.

Implementing PEHR: Design and Integration of a Consent Creator Service.

Giving the patient full control over his medical data electronically remains one of the most discussed topics in healthcare today. The INFOPAT project in the Rhine-Neckar region focuses on a personal cross-enterprise electronic health record (PEHR) in which the patient plays a major role. Thus, he should be provided with the possibility of granting access to his medical data which could be realized using a consent creator service. This paper presents a user interface concept for such a service as well as aspects for the technical implementation. In addition, a pattern for integrating the service into an existing IHE based infrastructure is shown. These concepts could be further adapted for improving patient empowerment in health care projects.

An Architecture for the Integration of Clinical Data from a PEHR in a Regional Research Platform.

Making clinical information available for research is not only relevant for healthcare institutions, but also for regional EHRs, as cross-sectorial information can be made accessible. In the INFOPAT (INFOrmation technology for PATient-oriented health care in the Rhine-Neckar metropolitan region) project we are thus implementing both, a regional personal cross-enterprise electronic health record (PEHR) and a regional research platform (RRP) based on information from the PEHR. IHE profiles are implemented to achieve interoperability between healthcare institutions electronic medical records (EMR) and PEHR on the one hand, as well as PEHR and RRP on the other hand. The use case for the RRP is cross-sectorial quality assessment and improvement for colorectal cancer based on a quality indicator (QI) approach including patients' perspectives. For semantic interoperability the responses are transferred in the form of HL7 CDA L2 documents. The resulting architecture for a RRP shows that implementing a PEHR in combination with a RRP based on international communication standards is possible. Also IHE XDS can be used for integration of patient care and biomedical research infrastructures.

Personal electronic health records: understanding user requirements and needs in chronic cancer care.

BACKGROUND: The integration of new information and communication technologies (ICTs) is becoming increasingly important in reorganizing health care. Adapting ICTs as supportive tools to users' needs and daily practices is vital for adoption and use. OBJECTIVE: In order to develop a Web-based personal electronic health record (PEPA), we explored user requirements and needs with regard to desired information and functions. METHODS: A qualitative study across health care sectors and health professions was conducted in a regional health care setting in Germany. Overall, 10 semistructured focus groups were performed, collecting views of 3 prospective user groups: patients with colorectal cancer (n=12) and representatives from patient support groups (n=2), physicians (n=17), and non-medical HCPs (n=16). Data were audio- and videotaped, transcribed verbatim, and thematically analyzed using qualitative content analysis. RESULTS: For both patients and HCPs, it was central to have a tool representing the chronology of illness and its care processes, for example, patients wanted to track their long-term laboratory findings (eg, tumor markers). Designing health information in a patient accessible way was highlighted as important. Users wanted to have general and tumor-specific health information available in a PEPA. Functions such as filtering information and adding information by patients (eg, on their well-being or electronic communication with HCPs via email) were discussed. CONCLUSIONS: In order to develop a patient/user centered tool that is tailored to user needs, it is essential to address their perspectives. A challenge for implementation will be how to design PEPA's health data in a patient accessible way. Adequate patient support and technical advice for users have to be addressed.

The patients' active role in managing a personal electronic health record: a qualitative analysis.

PURPOSE: The complexity of illness and cross-sectoral health care pose challenges for patients with colorectal cancer and their families. Within a patient-centered care paradigm, it is vital to give patients the opportunity to play an active role. Prospective users' attitudes regarding the patients' role in the context of a patient-controlled electronic health record (PEPA) were explored. METHODS: A qualitative study across regional health care settings and health professions was conducted. Overall, 10 focus groups were performed collecting views of 3 user groups: patients with colorectal cancer (n = 12) and representatives from patient support groups (n = 2), physicians (n = 17), and other health care professionals (HCPs) (n = 16). Data were audio- and videotaped, transcribed verbatim and thematically analyzed using qualitative content analysis. RESULTS: The patients' responsibility as a gatekeeper and access manager was at the center of the focus group discussions, although HCPs addressed aspects that would limit patients taking an active role (e.g., illness related issues). Despite expressed concerns, PEPAs possibility to enhance personal responsibility was seen in all user groups. CONCLUSIONS: Giving patients an active role in managing a personal electronic health record is an innovative patient-centered approach, although existing restraints have to be recognized. To enhance user adoption and advance PEPAs potential, key user needs have to be addressed.