A collaborative platform for management of chronic diseases via guideline-driven individualized care plans

Older age is associated with an increased accumulation of multiple chronic conditions. The clinical management of patients suffering from multiple chronic conditions is very complex, disconnected and time-consuming with the traditional care settings. Integrated care is a means to address the growing demand for improved patient experience and health outcomes of multimorbid and long-term care patients. Care planning is a prevalent approach of integrated care, where the aim is to deliver more personalized and targeted care creating shared care plans by clearly articulating the role of each provider and patient in the care process. In this paper, we present a method and corresponding implementation of a semi-automatic care plan management tool, integrated with clinical decision support services which can seamlessly access and assess the electronic health records (EHRs) of the patient in comparison with evidence based clinical guidelines to suggest personalized recommendations for goals and interventions to be added to the individualized care plans. We also report the results of usability studies carried out in four pilot sites by patients and clinicians

Automated Injection of Curated Knowledge Into Real-Time Clinical Systems: CDS Architecture for the 21st Century

abstract: Clinical Decision Support (CDS) is primarily associated with alerts, reminders, order entry, rule-based invocation, diagnostic aids, and on-demand information retrieval. While valuable, these foci have been in production use for decades, and do not provide a broader, interoperable means of plugging structured clinical knowledge into live electronic health record (EHR) ecosystems for purposes of orchestrating the user experiences of patients and clinicians. To date, the gap between knowledge representation and user-facing EHR integration has been considered an “implementation concern” requiring unscalable manual human efforts and governance coordination. Drafting a questionnaire engineered to meet the specifications of the HL7 CDS Knowledge Artifact specification, for example, carries no reasonable expectation that it may be imported and deployed into a live system without significant burdens. Dramatic reduction of the time and effort gap in the research and application cycle could be revolutionary. Doing so, however, requires both a floor-to-ceiling precoordination of functional boundaries in the knowledge management lifecycle, as well as formalization of the human processes by which this occurs. This research introduces ARTAKA: Architecture for Real-Time Application of Knowledge Artifacts, as a concrete floor-to-ceiling technological blueprint for both provider heath IT (HIT) and vendor organizations to incrementally introduce value into existing systems dynamically. This is made possible by service-ization of curated knowledge artifacts, then injected into a highly scalable backend infrastructure by automated orchestration through public marketplaces. Supplementary examples of client app integration are also provided. Compilation of knowledge into platform-specific form has been left flexible, in so far as implementations comply with ARTAKA’s Context Event Service (CES) communication and Health Services Platform (HSP) Marketplace service packaging standards. Towards the goal of interoperable human processes, ARTAKA’s treatment of knowledge artifacts as a specialized form of software allows knowledge engineers to operate as a type of software engineering practice. Thus, nearly a century of software development processes, tools, policies, and lessons offer immediate benefit: in some cases, with remarkable parity. Analyses of experimentation is provided with guidelines in how choice aspects of software development life cycles (SDLCs) apply to knowledge artifact development in an ARTAKA environment. Portions of this culminating document have been further initiated with Standards Developing Organizations (SDOs) intended to ultimately produce normative standards, as have active relationships with other bodies.Dissertation/ThesisDoctoral Dissertation Biomedical Informatics 201

GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

Monitoring Integration Systems and Visualization

The amount of new software and data has grown significantly in our society. In addition, new software solutions often have been built over the old ones to extend their capabilities. Also architectural solutions for software systems include multiple smaller services that have been divided all over the system. This has lead to the situation where more communication happens between the different parts of the system. Monitoring abundant traffic manually, with human resources is really challenging or even an impossible task. That is the reason why monitoring is performed with automated systems. The objective of the thesis is to develop an extension for monitoring system, that will be in charge of monitoring the integration platform. Thesis is done for the SaaS -software company BCB Medical Oy. In the thesis solutions were sought for general monitoring challenges and integration platforms problems in monitoring. Retrieving integration platforms essential information and their visual presentation was one of these problems. In addition to these problems, the differences in monitoring between the integration part of the system and rest of the system, were evaluated. Also determining thresholds that help detecting any anomalies in the system, was considered an issue. The research for in thesis was performed with qualitative methods, by interviewing the employees of BCB Medical Oy. Interviews were constructed with semi structural interview model and they were used to discover solutions for monitoring issues. Implementation part of the thesis was made with the same tools that the company uses for monitoring, Prometheus and Grafana. Results of the work accomplished of determining values that are required from the integration platform. Transferring these values to the monitoring system was performed with using Prometheus exporter. Visualization of these values was done with Grafana to help discover important information and determining certain thresholds for alerts.Uusien ohjelmistojen ja datan määrä on kasvanut yhteiskunnassamme merkittävästi. Lisäksi vanhojen sovellusten toiminnallisuutta on yritetty laajentaa uusien ratkaisujen avulla. Myös sovellusten arkkitehtuuriset ratkaisut ovat usein toteuttettu niin, että järjestelmä on jaettu useisiin osiin. Tämä on myös johtanut lisääntyneeseen kommunikointiin komponenttien välillä. Runsaasta liikenteestä järjestelmässä johtuen sovellusten manuaalinen monitorointi on ihmisresurssein erittäin haastavaa ellei jopa mahdotonta. Tästä johtuen monitorointia suoritetaan automaattisella monitorointi järjestelmällä. Työn tavoitteena on kehittää monitorointi järjestelmän osa, joka vastaa integraatioalustan monitoiroinnista. Lopputyö toteutettiin SaaS -ohjelmistoyritys BCB Medical Oy:lle. Työssä etsittiin ratkaisuja monitoroinnin haasteisiin ja integraationalustan synnyttämiin ongelmiin monitoroinnissa. Erityisesti integraatioalustalta tarpeellisten tietojen hakemiseen ja niiden visuaaliseen esittämiseen etsittiin ratkaisua. Näiden ongelmien lisäksi koitettiin saada vastauksia integraatioalustan monitoroinnin eroavaisuuksiin tavalliseen monitorointiin verrattuna sekä miten määrittää integraatioalustan arvoille raja-arvo, jonka avulla havaitaan alustan ongelmat. Tutkimus suoritettiin kvalitatiivisellä menetelmällä, haastattelemalla BCB Medical:n työntekijöitä. Haastattelut on muodostettu käyttäen puolistrukturoitua rakennetta ja niillä selvitettiin monitorointiin liittyviä ratkaisuja. Työosuus toteutet-tiin yrityksen käyttämillä monitoroitityökaluilla, joita olivat Prometheus ja Grafana. Työn tuloksena saatiin määritettyä integraatioalustan monitoroinnissa välttämättömiä arvoja. Arvojen siirtäminen monitorointi alustalle tapahtui käyttämällä Prometheuksen exportteria. Sen lisäksi näiden arvojen esittäminen Grafana-ilmoitustaululla tärkeiden tietojen havaitsemisen sujuvoittamiseksi ja hälytysjärjestelmän arvojen määrittämiseksi

Usability analysis of contending electronic health record systems

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study. © 2019 American Psychological Association Inc. All rights reserved.Peer reviewe

Conceptual Framework for Semantic Interoperability in Sensor-enhanced Health Information Systems (SIOp4Se-HIS)

Transducer integration into different accessories such as eyeglasses, wristbands, vest, wristwatches, among others, has brought myriads of physiological data that could be of help in making patients health monitoring easier. However, this myriad of data are generated from different devices with different formats and uncoordinated data types which ultimately compromises the data integrity and renders it medically less importance. Furthermore, several wearables do operate as data island as they cannot incorporate their captured data into the Health Information Systems (HIS) for easy accessibility by the health-care professionals for further processing, interpretation and actions on the patients’ health. Therefore, to enable the flow of data that will be useful to both patient and health-care professional, the existing HIS should be transducer enhanced / enabled, and they should operate at the same semantic interoperability level to allow for exchange of meaningful data from transducers to HIS. In bid to achieve this, several attempts have been made using standards, and archetypes, which goes a long way in providing interoperability at the technical and syntactic level. However, repositories of heterogeneous transducer data as provided by health monitoring systems, requires actionable knowledge of context (environment) from which the data is collected for it to be medically useful and interoperate at the semantic level with the HIS. There are three approaches: the model-driven; standard based and archetype approach but only the ontology driven guarantees making the applications smarter, or make the data smarter. The study propose the latter option using a dual model approach to leverage semantic technologies in order to provide and apply more meaningful health monitoring data representation between transducers and HIS. We approached this study using the design science research methodology and developed a hybrid methodology by combining two methods to develop our ontologies that are based on standards in the domains, with this unique method we achieved a novel approach to solve the obstacle of semantic interoperability through our proposed framework for Semantic Interoperability for Sensor-enhanced Health Information Systems (se-HIS) and bridged the gaps in systems’ interoperability between monitoring units and HIS. The outcome is a robust, explicit conceptual framework for sensor-enhanced health information systems Interoperability (IOp) at the semantic level. This semantically enabled our HIS, to interoperate with Transducers that are compliant with the Institute of Electrical and Electronics Engineers (IEEE) 21451 family of standards, and it provides the ability to query high-level knowledge of the data context as well as low-level raw data accessibility in a multi-transducer enable HIS

Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation

Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother's and her unborn baby's health and well-being. Different studies have thus far proposed maternal health monitoring systems. However, they are designed for a specific health problem or are limited to questionnaires and short-term data collection methods. Moreover, the requirements and challenges have not been evaluated in long-term studies. Maternal health necessitates a comprehensive framework enabling continuous monitoring of pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system to provide ubiquitous maternal health monitoring during pregnancy and postpartum. The system consists of various data collectors to track the mother's condition, including stress, sleep, and physical activity. We carried out the full system implementation and conducted a real human subject study on pregnant women in Southwestern Finland. We then evaluated the system's feasibility, energy efficiency, and data reliability. Our results show that the implemented system is feasible in terms of system usage during nine months. We also indicate the smartwatch, used in our study, has acceptable energy efficiency in long-term monitoring and is able to collect reliable photoplethysmography data. Finally, we discuss the integration of the presented system with the current healthcare system