The MADE Reference Information Model for Interoperable Pervasive Telemedicine Systems.

OBJECTIVES: The main objective is to develop and validate a reference information model (RIM) to support semantic interoperability of pervasive telemedicine systems. The RIM is one component within a larger, computer-interpretable "MADE language" developed by the authors in the context of the MobiGuide project. To validate our RIM, we applied it to a clinical guideline for patients with gestational diabetes mellitus (GDM). METHODS: The RIM is derived from a generic data flow model of disease management which comprises a network of four types of concurrent processes: Monitoring (M), Analysis (A), Decision (D) and Effectuation (E). This resulting MADE RIM, which was specified using the formal Vienna Development Method (VDM), includes six main, high-level data types representing measurements, observations, abstractions, action plans, action instructions and control instructions. RESULTS: The authors applied the MADE RIM to the complete GDM guideline and derived from it a domain information model (DIM) comprising 61 archetypes, specifically 1 measurement, 8 observation, 10 abstraction, 18 action plan, 3 action instruction and 21 control instruction archetypes. It was observed that there are six generic patterns for transforming different guideline elements into MADE archetypes, although a direct mapping does not exist in some cases. Most notable examples are notifications to the patient and/or clinician as well as decision conditions which pertain to specific stages in the therapy. CONCLUSIONS: The results provide evidence that the MADE RIM is suitable for modelling clinical data in the design of pervasive telemedicine systems. Together with the other components of the MADE language, the MADE RIM supports development of pervasive telemedicine systems that are interoperable and independent of particular clinical applications.

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.

Evaluation of a computer program for non-invasive determination of pulmonary shunt and ventilation-perfusion mismatch.

We describe a three-compartment model (shunt and two perfused compartments) to analyse the relationship between inspired oxygen (FIO2) and arterial oxygen saturation (SaO2) in terms of pulmonary shunt and ventilation-perfusion ratio (VA/Q). The program was tested using 24 exact datasets, each with six pairs of FIO2 and SaO2 data points with known VA/Q and shunt, generated by a complex calculator of gas exchange. Additional datasets were created by adding noise and rounding the exact sets, and by reducing the number of data points per dataset. The importance of the oxyhaemoglobin dissociation curve and the arterio-venous difference in oxygen content (avDO2) were also tested. Analysis using the three compartment model was more accurate than the two compartment model and less affected by data degradation. The absolute error in shunt estimation was never more than 2.2 % for the exact and rounded datasets, but the error in VA/Q estimation was -29 to 19 % of the true value (10th-90th centiles). The characteristics of the well-ventilated compartment were not determined accurately. At extremes of cardiac output, an assumed value of avDO2 resulted in significant errors. It is probably advantageous to correct for foetal haemoglobin in neonatal datasets. Analysis of FIO2 versus SaO2 datasets using a three compartment model provides accurate estimates of shunt and VA/Q when arterio-venous difference in oxygen content is known. The estimates may have value as objective measures of gas exchange, and as a visual guide for oxygen therapy.