The Knowledge Grid: A Platform to Increase the Interoperability of Computable Knowledge and Produce Advice for Health

Here we demonstrate how more highly interoperable computable knowledge enables systems to generate large quantities of evidence-based advice for health. We first provide a thorough analysis of advice. Then, because advice derives from knowledge, we turn our focus to computable, i.e., machine-interpretable, forms for knowledge. We consider how computable knowledge plays dual roles as a resource conveying content and as an advice enabler. In this latter role, computable knowledge is combined with data about a decision situation to generate advice targeted at the pending decision. We distinguish between two types of automated services. When a computer system provides computable knowledge, we say that it provides a knowledge service. When computer system combines computable knowledge with instance data to provide advice that is specific to an unmade decision we say that it provides an advice-giving service. The work here aims to increase the interoperability of computable knowledge to bring about better knowledge services and advice-giving services for health. The primary motivation for this research is the problem of missing or inadequate advice about health topics. The global demand for well-informed health advice far exceeds the global supply. In part to overcome this scarcity, the design and development of Learning Health Systems is being pursued at various levels of scale: local, regional, state, national, and international. Learning Health Systems fuse capabilities to generate new computable biomedical knowledge with other capabilities to rapidly and widely use computable biomedical knowledge to inform health practices and behaviors with advice. To support Learning Health Systems, we believe that knowledge services and advice-giving services have to be more highly interoperable. I use examples of knowledge services and advice-giving services which exclusively support medication use. This is because I am a pharmacist and pharmacy is the biomedical domain that I know. The examples here address the serious problems of medication adherence and prescribing safety. Two empirical studies are shared that demonstrate the potential to address these problems and make improvements by using advice. But primarily we use these examples to demonstrate general and critical differences between stand-alone, unique approaches to handling computable biomedical knowledge, which make it useful for one system, and common, more highly interoperable approaches, which can make it useful for many heterogeneous systems. Three aspects of computable knowledge interoperability are addressed: modularity, identity, and updateability. We demonstrate that instances of computable knowledge, and related instances of knowledge services and advice-giving services, can be modularized. We also demonstrate the utility of uniquely identifying modular instances of computable knowledge. Finally, we build on the computing concept of pipelining to demonstrate how computable knowledge modules can automatically be updated and rapidly deployed. Our work is supported by a fledgling technical knowledge infrastructure platform called the Knowledge Grid. It includes formally specified compound digital objects called Knowledge Objects, a conventional digital Library that serves as a Knowledge Object repository, and an Activator that provides an application programming interface (API) for computable knowledge. The Library component provides knowledge services. The Activator component provides both knowledge services and advice-giving services. In conclusion, by increasing the interoperability of computable biomedical knowledge using the Knowledge Grid, we demonstrate new capabilities to generate well-informed health advice at a scale. These new capabilities may ultimately support Learning Health Systems and boost health for large populations of people who would otherwise not receive well-informed health advice.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/146073/1/ajflynn_1.pd

Improving Medication Adherence In Hypertensive Patients: A Scoping Review

Nos últimos anos, o interesse na área da adesão terapêutica tem aumentado de forma significativa. O panorama da adesão tem sido estudado particularmente na área do tratamento da hipertensão arterial; de facto, já foram desenvolvidas numerosas intervenções na tentativa de melhorar a adesão terapêutica em doentes hipertensos. No entanto, este tem sido um esforço frequentemente frustrante e desorganizado. O objetivo do presente estudo foi a realização de uma scoping review de intervenções destinadas a melhorar a adesão terapêutica em doentes hipertensos, de forma a fornecer uma visão mais clara e estruturada desta área. Além disso, desenvolveu-se um novo sistema de categorização de intervenções, baseado em evidência. A presente revisão foi realizada de acordo com o PRISMA-ScR statement. As bases de dados utilizadas foram a MEDLINE e a Web of Science, sendo que se incluíram estudos desde a criação das bases de dados até o dia 17 de agosto de 2020. De um número inicial de 2994 estudos não duplicados, 45 artigos foram incluídos após a realização das fases de screening e elegibility. Estes artigos foram analisados de acordo com o seu desenho, características dos participantes e estratégias de gestão de adesão aplicadas. De igual forma, avaliaram-se os seus outcomes relativos a indicadores de adesão terapêutica e pressão arterial, bem como os métodos utilizados para medir adesão. Posteriormente, cada intervenção descrita foi categorizada de acordo com um novo sistema de categorização, baseado em evidência e desenhado de acordo com o framework de conceptual clustering, amplamente utilizado em machine learning. Ao apresentar uma visão geral e organizada desta área de investigação, criando ainda uma nova ferramenta de categorização de intervenções, este trabalho revela-se um marco importante no desenvolvimento informado e eficiente de futuras intervenções em adesão terapêutica. Adicionalmente, para profissionais de saúde esta é uma fonte de informação valiosa sobre adesão terapêutica em doentes hipertensos.In recent years, interest in medication adherence has greatly increased. Adherence has been particularly well studied in the context of arterial hypertension treatment. Numerous interventions have addressed this issue, however, the effort to improve adherence has been often frustrating and frequently disorganized. The aim of present study was to perform a scoping review of medication adherence interventions in hypertensive patients, so that a clear overview was achieved. Moreover, an evidence-based categorization of interventions was developed. The review was performed according to the PRISMA-ScR statement. MEDLINE and Web of Science were searched, and studies published from database inception until August 17, 2020 were included. A total of 2994 non-duplicate studies were retrieved. After screening and eligibility phases, a total of 45 articles were included. Studies were analyzed regarding their design, participant characteristics and management of adherence strategies employed. Furthermore, medication adherence and blood pressure outcomes, as well as adherence measuring tools were evaluated. Each study's intervention was then categorized using a novel evidence-based system of categorization, derived from the conceptual clustering framework used in machine learning. This work is an important step in pushing for better informed and more efficient future research efforts, both by providing an overview of the research field and by creating a new, evidence-based intervention categorization tool. It also provides valuable information to clinicians about medication adherence to antihypertensive therapy

A case study in open source innovation: developing the Tidepool Platform for interoperability in type 1 diabetes management.

OBJECTIVE:Develop a device-agnostic cloud platform to host diabetes device data and catalyze an ecosystem of software innovation for type 1 diabetes (T1D) management. MATERIALS AND METHODS:An interdisciplinary team decided to establish a nonprofit company, Tidepool, and build open-source software. RESULTS:Through a user-centered design process, the authors created a software platform, the Tidepool Platform, to upload and host T1D device data in an integrated, device-agnostic fashion, as well as an application ("app"), Blip, to visualize the data. Tidepool's software utilizes the principles of modular components, modern web design including REST APIs and JavaScript, cloud computing, agile development methodology, and robust privacy and security. DISCUSSION:By consolidating the currently scattered and siloed T1D device data ecosystem into one open platform, Tidepool can improve access to the data and enable new possibilities and efficiencies in T1D clinical care and research. The Tidepool Platform decouples diabetes apps from diabetes devices, allowing software developers to build innovative apps without requiring them to design a unique back-end (e.g., database and security) or unique ways of ingesting device data. It allows people with T1D to choose to use any preferred app regardless of which device(s) they use. CONCLUSION:The authors believe that the Tidepool Platform can solve two current problems in the T1D device landscape: 1) limited access to T1D device data and 2) poor interoperability of data from different devices. If proven effective, Tidepool's open source, cloud model for health data interoperability is applicable to other healthcare use cases

Interventions to improve medication adherence in tuberculosis patients:A systematic review of randomized controlled studies

Non-adherence to anti-tuberculosis (anti-TB) medication is a major risk factor for poor treatment outcomes. We therefore assessed the effectiveness of medication adherence enhancing interventions in TB patients. We report a systematic review of randomized controlled trials that included either latent tuberculosis infection (LTBI) or active TB patients. Outcomes of interest included adherence rate, completed treatment, defaulted treatment and treatment outcomes. We identified four LTBI and ten active TB studies. In active TB patients, directly observed treatment (DOT) by trained community workers, short messaging service combined with education, counselling, monthly TB vouchers, drug box reminders and combinations of those were found effective. In LTBI patients, shorter regimens and DOT effectively improved treatment completion. Interestingly, DOT showed variable effectiveness, highlighting that implementation, population and setting may play important roles. Since non-adherence factors are patient-specific, personalized interventions are required to enhance the impact of a programme to improve medication adherence in TB patients

Reconciliation of Multiple Guidelines for Decision Support: A case study on the multidisciplinary management of breast cancer within the DESIREE project

Breast cancer is the most common cancer among women. DESIREE is a European project which aims at developing web-based services for the management of primary breast cancer by multidisciplinary breast units (BUs). We describe the guideline-based decision support system (GL-DSS) of the project. Various breast cancer clinical practice guidelines (CPGs) have been selected to be concurrently applied to provide state-of-the-art patient-specific recommendations. The aim is to reconcile CPG recommendations with the objective of complementarity to enlarge the number of clinical situations covered by the GL-DSS. Input and output data exchange with the GL-DSS is performed using FHIR. We used a knowledge model of the domain as an ontology on which relies the reasoning process performed by rules that encode the selected CPGs. Semantic web tools were used, notably the Euler/EYE inference engine, to implement the GL-DSS. "Rainbow boxes" are a synthetic tabular display used to visualize the inferred recommendations

Digital Pills to Measure Opioid Ingestion Patterns in Emergency Department Patients With Acute Fracture Pain: A Pilot Study

BACKGROUND: Nonadherence to prescribed regimens for opioid analgesic agents contributes to increasing opioid abuse and overdose death. Opioids are frequently prescribed on an as-needed basis, placing the responsibility to determine opioid dose and frequency with the patient. There is wide variability in physician prescribing patterns because of the lack of data describing how patients actually use as-needed opioid analgesics. Digital pill systems have a radiofrequency emitter that directly measures medication ingestion events, and they provide an opportunity to discover the dose, timing, and duration of opioid therapy. OBJECTIVE: The purpose of this study was to determine the feasibility of a novel digital pill system to measure as-needed opioid ingestion patterns in patients discharged from the emergency department (ED) after an acute bony fracture. METHODS: We used a digital pill with individuals who presented to a teaching hospital ED with an acute extremity fracture. The digital pill consisted of a digital radiofrequency emitter within a standard gelatin capsule that encapsulated an oxycodone tablet. When ingested, the gastric chloride ion gradient activated the digital pill, transmitting a radiofrequency signal that was received by a hip-worn receiver, which then transmitted the ingestion data to a cloud-based server. After a brief, hands-on training session in the ED, study participants were discharged home and used the digital pill system to ingest oxycodone prescribed as needed for pain for one week. We conducted pill counts to verify digital pill data and open-ended interviews with participants at their follow-up appointment with orthopedics or at one week after enrollment in the study to determine the knowledge, attitudes, beliefs, and practices regarding digital pills. We analyzed open-ended interviews using applied thematic analysis. RESULTS: We recruited 10 study participants and recorded 96 ingestion events (87.3%, 96/110 accuracy). Study participants reported being able to operate all aspects of the digital pill system after their training. Two participants stopped using the digital pill, reporting they were in too much pain to focus on the novel technology. The digital pill system detected multiple simultaneous ingestion events by the digital pill system. Participants ingested a mean 8 (SD 5) digital pills during the study period and four participants continued on opioids at the end of the study period. After interacting with the digital pill system in the real world, participants found the system highly acceptable (80%, 8/10) and reported a willingness to continue to use a digital pill to improve medication adherence monitoring (90%, 9/10). CONCLUSIONS: The digital pill is a feasible method to measure real-time opioid ingestion patterns in individuals with acute pain and to develop real-time interventions if opioid abuse is detected. Deploying digital pills is possible through the ED with a short instructional course. Patients who used the digital pill accepted the technology

Healthcare Robotics

Robots have the potential to be a game changer in healthcare: improving health and well-being, filling care gaps, supporting care givers, and aiding health care workers. However, before robots are able to be widely deployed, it is crucial that both the research and industrial communities work together to establish a strong evidence-base for healthcare robotics, and surmount likely adoption barriers. This article presents a broad contextualization of robots in healthcare by identifying key stakeholders, care settings, and tasks; reviewing recent advances in healthcare robotics; and outlining major challenges and opportunities to their adoption.Comment: 8 pages, Communications of the ACM, 201

Development of written information for antiretroviral therapy: comprehension in a Tanzanian population

Objective To design and develop a simple, easily readable patient information leaflet (PIL) for a commonly used antiretroviral (ARV) regimen and to evaluate its readability and acceptability in a Tanzanian population. Method A PIL incorporating simple text and pictograms was designed for the antiretroviral regimen of stavudine, lamivudine and efavirenz. The PIL was designed according to established good design guidelines, modified during a multi-stage iterative testing process and piloted in a South African Xhosa population. The PIL was made available in both English and Kiswahili. Sixty Tanzanian participants who were not taking ARVs were interviewed. They were asked to read the PIL in the language of their choice and were then asked a series of two-part questions; the first part required participants to locate the information in the PIL, after which they were asked to explain the information in their own words. Acceptability was assessed through close-ended questions and open-ended feedback. The influence of selected patient characteristics on comprehension of the PIL was investigated using one-way ANOVA and t-tests for independent samples with a significance level set at 0.05. Main outcome measure Comprehension of the written information in an overall percentage understanding. Results The overall average percentage comprehension of the PIL was 95%. The target set by the EC guideline that at least 80% of participants correctly locate and understand the information was achieved for 19 of the 20 questions. Five of the six instructions illustrated by pictograms were correctly understood by all participants. The only patient characteristics significantly associated with comprehension were educational level and self-reported ease of reading the PIL. Acceptability of the PIL was high and positive comments were associated with simplicity, good design, easy readability and user-friendliness, the latter enhanced by the inclusion of pictograms. Conclusion The PIL designed for this study was shown to be effective in communicating information about ARVs. Patient characteristics must be taken into account when developing written information, and the final document must be tested for comprehension in the target population