Formative evaluation of a patient-specific clinical knowledge summarization tool

To iteratively design a prototype of a computerized clinical knowledge summarization (CKS) tool aimed at helping clinicians finding answers to their clinical questions; and to conduct a formative assessment of the usability, usefulness, efficiency, and impact of the CKS prototype on physicians’ perceived decision quality compared with standard search of UpToDate and PubMed

Intelligent consumer-centric electronic medical record

Abstract: Web-based, consumer-centric electronic medical records (CEMRs) are currently undergoing widespread deployment. Existing CEMRs, however, have limited intelligence and cannot satisfy users ’ many needs. This paper proposes the concept of intelligent CEMR. We introduce and extend expert system and Web search technology into the CEMR domain. The resulting intelligent CEMRs can automatically provide users with personalized healthcare information to facilitate their daily activities. We use automatic home medical product recommendation as a concrete application to demonstrate the benefits offered by intelligent CEMRs

Master of Science

thesisLack of information is a serious concern for clinicians. Information resources can address this problem, leading to improvements in decision making and patient outcomes. Genomics is an information-rich domain where searching for information can be complex. For example, most physicians agree that pharmacogenomics can be used to improve the quality of care, and there is evidence that many patients harbor actionable pharmacogenomic variation. However, surveys have shown that physicians feel their knowledge of pharmacogenomics to be inadequate. This represents an information need. A natural approach to meet this need is to provide context-aware access to the precise information needed. The Health Level 7 Context-Aware Knowledge Retrieval Standard, a.k.a the Infobutton, offers a modality to deliver context-aware knowledge into electronic health record (EHR) systems. OpenInfobutton is a reference implementation of this standard that offers an open-source instantiation. In this thesis, we aimed to provide insight into pharmacogenomics information needs and an automated mechanism for addressing these needs. Such work can aid the design of tools that support clinical decisions in genomics

Providing better clinical reference sources at the point of care

Physicians frequently need clinical reference material at the time they are taking care of patients, but despite the widespread availability of seemingly appropriate resources, physicians do not consistently avail themselves. Previous research has shown that the main obstacle to resource use is lack of time to search, followed by inability to find the information even with extended searching. Using a randomly selected sample of previously published questions (Clinical Questions Collection at the National Library of Medicine), current online electronic clinical reference resources were searched. Search times, success rates, and result quality were compared. Retrieval of drug information was dominated by navigation time, whereas searches for other materials were dominated by search time. It was rare that actually reading the material required significant time. Based on the results, an improved interface for accessing clinical reference data is proposed. Key features include a "Fast" interface that minimizes navigation time to easily found resources and a "Flex" interface that minimizes search time for more arcane material.Master of Science in Information Scienc

Doctor of Philosophy

dissertationInadequate care coordination has been identified as a significant problem in patient care, resulting in diminished satisfaction, increased cost, and reduced quality of care. Comprising an estimated 15.6% (approximately 11 million) of the pediatric population, children and youth with special health care needs (CYSHCN) are "those who have or are at increased risk for a chronic physical, developmental, behavioral, or emotional condition and who also require health and related services of a type or amount beyond that required by children generally". Caring for CYSHCN is often highly complex, time-, effort-, and resource-intensive, due to complex healthcare conditions, comorbidities, and age of patients. Current electronic health record (EHR) and personal health record (PHR) systems do not adequately support the needs of care coordination. The reasons for this include lack of appropriate tools to support complex care coordination tasks, poor usability, and gaps in information essential for providing team-based patient care. The issues are further amplified while coordinating care for CYSHCN because their health records tend to be voluminous, involve a large care team, and are distributed over multiple systems typically with little to no interoperability. To develop tools that promote effective and efficient care coordination, designers must first understand what information is needed, who needs it, when they need it, and how it can be made available. Our first study focused on identifying and describing information needs and associated goals related to coordinating care for CYSHCN. We found that a critical information goal for care coordination is care networking, which includes building a patient's care team; knowing team member identities, roles, and contact information; and sharing pertinent information with the team to coordinate care. In our second study, we designed and developed two versions of a patient-, family-, and clinician-facing tool to support care networking. We then conducted a formative evaluation and compared the usability, usefulness, and efficiency of the two versions. To enable such tools to help with management of information critical to care coordination, information for care networking needs to be obtained from all information sources involved in the patient's care. In our third study, we identified and assessed prevalent and emerging national data standards to support electronic exchange and extraction of patient care team related data. The findings and innovations from this research are envisioned to help guide the design and development of next generation clinician- and patient-/family-facing applications to support care coordination of complex pediatric patients

Intention To Use A Personal Health Record (phr) A Cross Sectional View Of The Characteristics And Opinions Of Patients Of One Internal Medicine Practice

A personal health record (PHR) allows a patient to exert control over his/her healthcare by enhancing communication with healthcare providers. According to research, patients find value in having access to information contained in their medical records. Often a glossary is required to aid in interpreting the information and understanding the content. However, giving patients the ability to speak with providers about their medical conditions empowers them to participate as informed healthcare consumers. The majority of patients (75%) at Medical Specialists expressed their intention to adopt the PHR if it is made available to them. Although the perceived usefulness of a PHR was a significant determining factor, comfort level with technology, health literacy, and socioeconomic status were indirectly related to intention to adopt as well. Perceived health status was not found to be a significant factor in this population for determining intention to adopt a PHR. The majority of patients in each category of gender, age, marital status, and race/ethnicity (except American Indian/Alaska Native) expressed interest in adopting a PHR, with most categories being above 70%. Findings indicate a broad acceptance of this new technology by the patients of Medical Specialists. Improvement of adoption and use rates may depend on availability of office staff for hands-on training as well as assistance with interpretation of medical information. Hopefully, over time technology barriers will disappear, and usefulness of the information will promote increased demand

Audiobook player for older adults with vision impairement

Tato práce se zabývá designem přehrávače knih pro seniory se zrakovým postižením. Více než polovina zrakově postižených je starší sedmdesáti let. Hlavním účelem navrhovaného zařízení je zpřístupnit slabozrakým a nevidomým seniorům důležitou volnočasovou aktivitu -- čtení. Práce je zaměřena na interakci posluchače se zařízením. Design je založen na limitacích, znalostech a potřebách jedinců cílové skupiny získaných z provedené analýzy a výsledků předchozího výzkumu s~nevidomými seniory žijícími v domově s pečovatelskou službou. Realizovaný kvalitativní uživatelský výzkum s nevidomými uživateli (N = 9) byl zaměřený na čtení a trávení volného času. Vývoj designu probíhal iterativně, byly vytvořeny a formativně testovány dvě generace prototypů. Pro podporu pochopitelnosti rozhraní byly implementovány metafory propojující ovládací komponenty s obecně známými koncepty: přehrávač svým tvarem působí jako kniha; otevření spustí přehrávání, zavření zastaví; tvary tlačítek souvisí s jejich funkcí; rozložení položek k~poslouchání odpovídá hodinovému ciferníku. Průběžná evaluace zahrnovala 4 experimenty: neformální časnou zpětnou vazbu (N = 3), testování low-fidelity prototypu s nevidomými participanty (N = 7, věkový průměr = 45.6) a se seniory se zrakovou vadou (N = 7, věkový průměr = 73) a ověření high-fidelity prototypu seniory se zrakovým postižením (N = 2, věk = 81). Testování ukázalo, že preference nevidomých uživatelů jsou různé. Mladší a aktivnější uživatelé poslouchají různé žánry a vyžadují snadnou přenosnost a~pokročilé funkce. Starší a pasivnější uživatelé poslouchají převážně audioknihy a jejich hlavní požadavky jsou jednoduchost, pochopitelnost, vhodná velikost a rozložení komponent uživatelského rozhraní. Zhotovený design byl dotazovanými participanty označen jako jednoduchý a užitečný.This thesis focuses on supporting reading, an important activity of visually impaired older adults. More than half of people with severe vision impairment is older than 70 years. We present the design concept of a physical device for audio content playback tailored to specific needs and preferences of this user group. The design is based on analysis and the outcomes of fundamental research conducted with visually impaired older adults living in a residential care institution. A qualitative user study (N = 9) focused specifically on audio content consumption has been conducted. We employed iterative development and formative evaluation to develop two generations of the audiobook player prototype. Implemented metaphors links control components with generally known concepts to support understandability of user interface: the shape resembles a book, the opening of the device starts playback, the closing stops it; button shapes are related to their function; the layout of available items for listening matches to the clock reference system. Four qualitative evaluation experiments have been conducted: early informal study (N = 3), low-fidelity prototype evaluation with visually impaired (N = 7, age mean = 45.6) and visually impaired older adults (N = 7, age mean = 73), high-fidelity prototype evaluation (N = 2). We conclude that the preferences of visually impaired differ. Younger and more active users listen to different genres, require easy portability and advanced features. Older and more passive users listen mostly to audiobooks, their primary requirements are simplicity, understandability, appropriate dimensions and layout of controls. The final design was marked as simple and useful by representatives of the target user audience

Social analytics for health integration, intelligence, and monitoring

Nowadays, patient-generated social health data are abundant and Healthcare is changing from the authoritative provider-centric model to collaborative and patient-oriented care. The aim of this dissertation is to provide a Social Health Analytics framework to utilize social data to solve the interdisciplinary research challenges of Big Data Science and Health Informatics. Specific research issues and objectives are described below. The first objective is semantic integration of heterogeneous health data sources, which can vary from structured to unstructured and include patient-generated social data as well as authoritative data. An information seeker has to spend time selecting information from many websites and integrating it into a coherent mental model. An integrated health data model is designed to allow accommodating data features from different sources. The model utilizes semantic linked data for lightweight integration and allows a set of analytics and inferences over data sources. A prototype analytical and reasoning tool called “Social InfoButtons” that can be linked from existing EHR systems is developed to allow doctors to understand and take into consideration the behaviors, patterns or trends of patients’ healthcare practices during a patient’s care. The tool can also shed insights for public health officials to make better-informed policy decisions. The second objective is near-real time monitoring of disease outbreaks using social media. The research for epidemics detection based on search query terms entered by millions of users is limited by the fact that query terms are not easily accessible by non-affiliated researchers. Publically available Twitter data is exploited to develop the Epidemics Outbreak and Spread Detection System (EOSDS). EOSDS provides four visual analytics tools for monitoring epidemics, i.e., Instance Map, Distribution Map, Filter Map, and Sentiment Trend to investigate public health threats in space and time. The third objective is to capture, analyze and quantify public health concerns through sentiment classifications on Twitter data. For traditional public health surveillance systems, it is hard to detect and monitor health related concerns and changes in public attitudes to health-related issues, due to their expenses and significant time delays. A two-step sentiment classification model is built to measure the concern. In the first step, Personal tweets are distinguished from Non-Personal tweets. In the second step, Personal Negative tweets are further separated from Personal Non-Negative tweets. In the proposed classification, training data is labeled by an emotion-oriented, clue-based method, and three Machine Learning models are trained and tested. Measure of Concern (MOC) is computed based on the number of Personal Negative sentiment tweets. A timeline trend of the MOC is also generated to monitor public concern levels, which is important for health emergency resource allocations and policy making. The fourth objective is predicting medical condition incidence and progression trajectories by using patients’ self-reported data on PatientsLikeMe. Some medical conditions are correlated with each other to a measureable degree (“comorbidities”). A prediction model is provided to predict the comorbidities and rank future conditions by their likelihood and to predict the possible progression trajectories given an observed medical condition. The novel models for trajectory prediction of medical conditions are validated to cover the comorbidities reported in the medical literature