Development and pilot-testing of a colorectal cancer screening decision aid for individuals with varying health literacy levels.

OBJECTIVE: Making an informed decision about colorectal cancer screening requires health literacy. Our aim was to develop and pilot-test a computer-based decision aid to support informed decision making about whether or not to participate in colorectal cancer screening for individuals with varying health literacy levels in the Netherlands. METHODS: First, we designed and adapted the decision aid prototype among 25 individuals with low (n = 15) and adequate (n = 10) health literacy. Second, we used a before/after study to assess changes in knowledge, attitude, intention, decisional conflict, deliberation, anxiety and risk perception in an online survey among 81 individuals eligible for colorectal cancer screening with low (n = 35) and adequate (n = 46) health literacy. RESULTS: The decision aid was acceptable, comprehensible, reduced decisional conflict, increased deliberation and improved knowledge about colorectal cancer screening, but not about colorectal cancer, among individuals with adequate and low health literacy. Usability was slightly higher for participants with adequate health literacy compared to those with low health literacy. CONCLUSION: The decision aid is promising in supporting informed decision making about colorectal cancer screening, also among individuals with lower health literacy. PRACTICE IMPLICATIONS: Further refinement of interactive features, such as videos, animations and the values clarification exercise, is needed to increase the usability of the decision aid.

Assessment of a personalized and distributed patient guidance system.

OBJECTIVES: The MobiGuide project aimed to establish a ubiquitous, user-friendly, patient-centered mobile decision-support system for patients and for their care providers, based on the continuous application of clinical guidelines and on semantically integrated electronic health records. Patients would be empowered by the system, which would enable them to lead their normal daily lives in their regular environment, while feeling safe, because their health state would be continuously monitored using mobile sensors and self-reporting of symptoms. When conditions occur that require medical attention, patients would be notified as to what they need to do, based on evidence-based guidelines, while their medical team would be informed appropriately, in parallel. We wanted to assess the system's feasibility and potential effects on patients and care providers in two different clinical domains. MATERIALS AND METHODS: We describe MobiGuide's architecture, which embodies these objectives. Our novel methodologies include a ubiquitous architecture, encompassing a knowledge elicitation process for parallel coordinated workflows for patients and care providers; the customization of computer-interpretable guidelines (CIGs) by secondary contexts affecting remote management and distributed decision-making; a mechanism for episodic, on demand projection of the relevant portions of CIGs from a centralized, backend decision-support system (DSS), to a local, mobile DSS, which continuously delivers the actual recommendations to the patient; shared decision-making that embodies patient preferences; semantic data integration; and patient and care provider notification services. MobiGuide has been implemented and assessed in a preliminary fashion in two domains: atrial fibrillation (AF), and gestational diabetes Mellitus (GDM). Ten AF patients used the AF MobiGuide system in Italy and 19 GDM patients used the GDM MobiGuide system in Spain. The evaluation of the MobiGuide system focused on patient and care providers' compliance to CIG recommendations and their satisfaction and quality of life. RESULTS: Our evaluation has demonstrated the system's capability for supporting distributed decision-making and its use by patients and clinicians. The results show that compliance of GDM patients to the most important monitoring targets - blood glucose levels (performance of four measurements a day: 0.87±0.11; measurement according to the recommended frequency of every day or twice a week: 0.99±0.03), ketonuria (0.98±0.03), and blood pressure (0.82±0.24) - was high in most GDM patients, while compliance of AF patients to the most important targets was quite high, considering the required ECG measurements (0.65±0.28) and blood-pressure measurements (0.75±1.33). This outcome was viewed by the clinicians as a major potential benefit of the system, and the patients have demonstrated that they are capable of self-monitoring - something that they had not experienced before. In addition, the system caused the clinicians managing the AF patients to change their diagnosis and subsequent treatment for two of the ten AF patients, and caused the clinicians managing the GDM patients to start insulin therapy earlier in two of the 19 patients, based on system's recommendations. Based on the end-of-study questionnaires, the sense of safety that the system has provided to the patients was its greatest asset. Analysis of the patients' quality of life (QoL) questionnaires for the AF patients was inconclusive, because while most patients reported an improvement in their quality of life in the EuroQoL questionnaire, most AF patients reported a deterioration in the AFEQT questionnaire. DISCUSSION: Feasibility and some of the potential benefits of an evidence-based distributed patient-guidance system were demonstrated in both clinical domains. The potential application of MobiGuide to other medical domains is supported by its standards-based patient health record with multiple electronic medical record linking capabilities, generic data insertion methods, generic medical knowledge representation and application methods, and the ability to communicate with a wide range of sensors. Future larger scale evaluations can assess the impact of such a system on clinical outcomes. CONCLUSION: MobiGuide's feasibility was demonstrated by a working prototype for the AF and GDM domains, which is usable by patients and clinicians, achieving high compliance to self-measurement recommendations, while enhancing the satisfaction of patients and care providers.

Patient-oriented Computerized Clinical Guidelines for Mobile Decision Support in Gestational Diabetes.

The risks associated with gestational diabetes (GD) can be reduced with an active treatment able to improve glycemic control. Advances in mobile health can provide new patient-centric models for GD to create personalized health care services, increase patient independence and improve patients' self-management capabilities, and potentially improve their treatment compliance. In these models, decision-support functions play an essential role. The telemedicine system MobiGuide provides personalized medical decision support for GD patients that is based on computerized clinical guidelines and adapted to a mobile environment. The patient's access to the system is supported by a smartphone-based application that enhances the efficiency and ease of use of the system. We formalized the GD guideline into a computer-interpretable guideline (CIG). We identified several workflows that provide decision-support functionalities to patients and 4 types of personalized advice to be delivered through a mobile application at home, which is a preliminary step to providing decision-support tools in a telemedicine system: (1) therapy, to help patients to comply with medical prescriptions; (2) monitoring, to help patients to comply with monitoring instructions; (3) clinical assessment, to inform patients about their health conditions; and (4) upcoming events, to deal with patients' personal context or special events. The whole process to specify patient-oriented decision support functionalities ensures that it is based on the knowledge contained in the GD clinical guideline and thus follows evidence-based recommendations but at the same time is patient-oriented, which could enhance clinical outcomes and patients' acceptance of the whole system.

Determinants of successful telemedicine implementations: a literature study.

Telemedicine implementations often remain in the pilot phase and do not succeed in scaling-up to robust products that are used in daily practice. We conducted a qualitative literature review of 45 conference papers describing telemedicine interventions in order to identify determinants that had influenced their implementation. The identified determinants, which would influence the future implementation of telemedicine interventions, can be classified into five major categories: (1) Technology, (2) Acceptance, (3) Financing, (4) Organization and (5) Policy and Legislation. Each category contains determinants that are relevant to different stakeholders in different domains. We propose a layered implementation model in which the primary focus on individual determinants changes throughout the development life cycle of the telemedicine implementation. For success, a visionary approach is required from the multidisciplinary stakeholders, which goes beyond tackling specific issues in a particular development phase. Thus the right philosophy is: 'start small, think big'.