How to Retain Participants in User-Centered Design? Towards Recommendations for Minimizing Dropouts.

Dropout and fatigue is present in most research projects. The present project Chronic Pain includes Fibromyalgia patients and applies a user-centered design approach. Surprisingly to the research group, two years into the project there is zero dropout. As a step towards designing a survey to investigate the patient adherence to the project, the characteristics of the user-centered design process are described in this paper.

Use of e-Health by Healthcare Professionals vs. non-Healthcare Professionals.

The role of e-health is increasing worldwide. We surveyed the use of e-health in a large-scale population-based study, involving a representative sample of the Norwegian population aged above 40 years. Two-thirds of the health professionals had used search engines, apps, social media or video services for health purposes - while this was the case for approximately half of the non-health professionals.

Combining multivariate statistics and the think-aloud protocol to assess Human-Computer Interaction barriers in symptom checkers.

Symptom checkers are software tools that allow users to submit a set of symptoms and receive advice related to them in the form of a diagnosis list, health information or triage. The heterogeneity of their potential users and the number of different components in their user interfaces can make testing with end-users unaffordable. We designed and executed a two-phase method to test the respiratory diseases module of the symptom checker Erdusyk. Phase I consisted of an online test with a large sample of users (n=53). In Phase I, users evaluated the system remotely and completed a questionnaire based on the Technology Acceptance Model. Principal Component Analysis was used to correlate each section of the interface with the questionnaire responses, thus identifying which areas of the user interface presented significant contributions to the technology acceptance. In the second phase, the think-aloud procedure was executed with a small number of samples (n=15), focusing on the areas with significant contributions to analyze the reasons for such contributions. Our method was used effectively to optimize the testing of symptom checker user interfaces. The method allowed kept the cost of testing at reasonable levels by restricting the use of the think-aloud procedure while still assuring a high amount of coverage. The main barriers detected in Erdusyk were related to problems understanding time repetition patterns, the selection of levels in scales to record intensities, navigation, the quantification of some symptom attributes, and the characteristics of the symptoms.

Archetype-based data warehouse environment to enable the reuse of electronic health record data.

BACKGROUND: The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed. OBJECTIVE: To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse. MATERIALS AND METHODS: The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases. RESULTS: Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language. DISCUSSION: Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world of possibilities toward semantic or concept-based reuse, query and communication of clinical data.

Multidisciplinary Modelling of Symptoms and Signs with Archetypes and SNOMED-CT for Clinical Decision Support.

Clinical Decision Support Systems (CDSS) help to improve health care and reduce costs. However, the lack of knowledge management and modelling hampers their maintenance and reuse. Current EHR standards and terminologies can allow the semantic representation of the data and knowledge of CDSS systems boosting their interoperability, reuse and maintenance. This paper presents the modelling process of respiratory conditions' symptoms and signs by a multidisciplinary team of clinicians and information architects with the help of openEHR, SNOMED and clinical information modelling tools for a CDSS. The information model of the CDSS was defined by means of an archetype and the knowledge model was implemented by means of an SNOMED-CT based ontology.

Bridging the gap between patients' expectations and general practitioners' knowledge through disease surveillance.

In this paper we have investigated "to what degree patients trust their regular doctor to be fully informed about the prevalence of infectious diseases in their neighbourhood", and what general practitioners (GPs) actually know. A representative sample of one thousand Norwegians (potential patients) was interviewed by telephone, and 13 GPs were interviewed individually or in focus groups. Nearly half of the patients trusted their GP to be more or less "fully informed" about the prevalence of infectious diseases in their neighbourhoods, while the GPs in reality were not well informed. We conclude that new surveillance solutions are needed. One promising approach is electronic retrieval of symptom data directly from patients.

Threats to information security of real-time disease surveillance systems.

This paper presents the main results from a qualitative risk assessment of information security aspects for a new real-time disease surveillance approach in general, and for the Snow surveillance system in particular. All possible security threats and acceptable solutions, and the implications these solutions had to the design of the system, were discussed. Approximately 30 threats were identified. None of these got an unacceptable high risk level originally, but two got medium risk level, of which one was concluded to be unacceptable after further investigation. Of the remaining low risk threats, some have severe consequence, thus requiring particular assessment. Since it is very important to identify and solve all security threats before real-time solutions can be used in a wide scale, additional investigations are needed.

An exploratory study of disease surveillance systems in Norway.

We conducted a qualitative study of the system for contagious disease surveillance in Norway. Semi-structured interviews were held with five general practitioners (GPs), including one person responsible for informing GPs in their region about potentially serious disease outbreaks. The interviews suggested that the existing system had several limitations, making it of little relevance to local epidemics or daily medical practice. Specifically, it was difficult and time-consuming for physicians to locate relevant information, and there was a substantial delay between reported diagnoses and eventual feedback about outbreaks. This resulted in information that was too old to be of value. The interviews also investigated design matters related to future realtime disease surveillance systems. The GPs expressed interest in a distributed system for realtime extraction and presentation of data from electronic record systems. They required that any such system be customizable to the specific needs of the doctor in order to be relevant in day-to-day practice, and that correct interpretation of data would be possible in the minimum of time.

Using blood glucose data as an indicator for epidemic disease outbreaks.

In the future, transfer of vital sensor data from patients to the public health care system is likely to become commonplace. Systems for automatic transfer of sensor data are now at the prototype stage. As electronic health record (EHR) systems adapt such functionality, widespread use may become an actuality in the foreseeable future.To prevent spreading of diseases, an early detection of infection is important. At the time an outbreak is diagnosed, many people may already be infected due to the incubation period. This study suggests an approach for detecting an epidemic outbreak at an early stage by monitoring blood glucose data collected from people with diabetes. Continuous analysis of blood glucose data may have the potential to prevent large outbreaks of infectious diseases, such as different strains of Influenza, Cholera, Plague, Ebola, Anthrax and SARS.When a person gets infected, the blood glucose value increases. If the blood glucose data from a large number of patients with diabetes are collected in a central database, it may be possible to detect an epidemic disease outbreak at an early stage. Advanced data analysis on the data may detect predominant numbers of incidences, indicating a possible outbreak. This gives the health authorities the possibilities to take actions to limit the outbreak and its consequences for all the inhabitants in an affected area.At the Norwegian Centre for Telemedicine, a mobile system for automatic transfer of blood glucose values has been constructed. By using wireless communication standards such as Bluetooth and GSM, the system transfers blood glucose data to an electronic health record system. Combined with a system accessing and querying data from EHR systems for patient surveillance we are extending our work into an Epidemic Disease Detection using blood Glucose (EDDG) system.