Say Goodbye to the 'Paper on Screen', Rethinking Presentation of and Interaction with Medical Information

Traditionally, Electronic Medical Records (EMR) have been designed to mimic paper records. Organizing and presenting medical information along the lines that evolved for non-digital records over the decades, reduced change management for medical users, but failed to make use of the potential of organizing digital data. We proposed a method to create clinical dashboards to increase the usability of information in the medical records. Official clinical guidelines were studied by a working group, including dashboard target users. Necessary clinical concepts contained in the medical records were identified according to the clinical context and finally, dedicated technical tools with standard terminologies were used to represent categories of information. We used this method to generate and implement a dashboard for sepsis. The dashboard was found to be appropriate and easy to use by the target users.

PharmoCo: a graph-based visualization of pharmacogenomic plausibility check reports for clinical decision support systems

The first approaches in recent years for the integration of pharmacogenomic plausibility checks into clinical practice show both a promising improvement in the drug therapy safety, but also difficulties in application. One of the difficulties is the meaningful interpretation of the text-based results by the medical practitioner. We propose here as an appropriate and sensible solution to avoid misunderstandings and to include evidence-based, pharmacogenomic recommendations in prescriptions, which should be the graph-based visualization of the reports. This allows for a plausible interpretation and relate complex, even contradictory guidelines. The improved overview over the pharmacogenomics (PGx) guidelines using the graphical visualization makes the medical practitioner's choice of dose and medication more patient-specific, improves the treatment outcome and thus, increases the drug therapy safety.

Dashboard of Short-Term Postoperative Patient Outcomes for Anesthesiologists: Development and Preliminary Evaluation

BACKGROUND

Anesthesiologists require an understanding of their patients' outcomes to evaluate their performance and improve their practice. Traditionally, anesthesiologists had limited information about their surgical outpatients' outcomes due to minimal contact post discharge. Leveraging digital health innovations for analyzing personal and population outcomes may improve perioperative care. BC Children's Hospital's postoperative follow-up registry for outpatient surgeries collects short-term outcomes such as pain, nausea, and vomiting. Yet, these data were previously not available to anesthesiologists.

OBJECTIVE

This quality improvement study aimed to visualize postoperative outcome data to allow anesthesiologists to reflect on their care and compare their performance with their peers.

METHODS

The postoperative follow-up registry contains nurse-reported postoperative outcomes, including opioid and antiemetic administration in the postanesthetic care unit (PACU), and family-reported outcomes, including pain, nausea, and vomiting, within 24 hours post discharge. Dashboards were iteratively co-designed with 5 anesthesiologists, and a department-wide usability survey gathered anesthesiologists' feedback on the dashboards, allowing further design improvements. A final dashboard version has been deployed, with data updated weekly.

RESULTS

The dashboard contains three sections: (1) 24-hour outcomes, (2) PACU outcomes, and (3) a practice profile containing individual anesthesiologist's case mix, grouped by age groups, sex, and surgical service. At the time of evaluation, the dashboard included 24-hour data from 7877 cases collected from September 2020 to February 2023 and PACU data from 8716 cases collected from April 2021 to February 2023. The co-design process and usability evaluation indicated that anesthesiologists preferred simpler designs for data summaries but also required the ability to explore details of specific outcomes and cases if needed. Anesthesiologists considered security and confidentiality to be key features of the design and most deemed the dashboard information useful and potentially beneficial for their practice.

CONCLUSIONS

We designed and deployed a dynamic, personalized dashboard for anesthesiologists to review their outpatients' short-term postoperative outcomes. This dashboard facilitates personal reflection on individual practice in the context of peer and departmental performance and, hence, the opportunity to evaluate iterative practice changes. Further work is required to establish their effect on improving individual and department performance and patient outcomes.

Joint Display of Integrated Data Collection for Mixed Methods Research: An Illustration From a Pediatric Oncology Quality Improvement Study

PURPOSE

Researchers often struggle to integrate quantitative and qualitative data. Joint displays of data collected using mixed methods provide a framework for supporting integration, yet the literature lacks methodologic articles illustrating in detail the iterative nature of constructing such displays. We demonstrate the process for creating a joint display for integrating the collection of data obtained by qualitative and quantitative methods.

METHODS

Within a convergent mixed methods cohort study, the Early Discharge of Febrile Neutropenic Children with Cancer Study, we constructed a joint display to inform integrated collection of 2 forms of data (quantitative and qualitative) from 2 sources (a patient-caregiver mixed methods survey and a manual abstraction of medical records).

RESULTS

In a first step, we used a data sources table to align related quantitative and qualitative data. The resulting table consisted of 2 side-by-side columns based on the mixed survey data. After several additional iterative steps, we constructed a final 6-column joint display. This final display delineated the separate data sources, linked constructs to the quantitative and qualitative variables within each source, and integrated the constructs across the separate data sources.

CONCLUSIONS

Challenges of integration, though not unique to prospective mixed methods cohort studies, stem from the sheer volume of qualitative and quantitative information and the need to logically organize the data in preparation for integrated data analysis. Tailoring joint displays to specific studies is challenging, but mixed methods researchers who embrace the methodologic malleability can produce effective joint displays to illustrate the mixed data collection linkages and create a preliminary structure ultimately for organizing mixed data findings.

Impact of clinical note format on diagnostic accuracy and efficiency

BACKGROUND

Clinician notes are structured in a variety of ways. This research pilot tested an innovative study design and explored the impact of note formats on diagnostic accuracy and documentation review time.

OBJECTIVE

To compare two formats for clinical documentation (narrative format vs. list of findings) on clinician diagnostic accuracy and documentation review time.

METHOD

Participants diagnosed written clinical cases, half in narrative format, and half in list format. Diagnostic accuracy (defined as including correct case diagnosis among top three diagnoses) and time spent processing the case scenario were measured for each format. Generalised linear mixed regression models and bias-corrected bootstrap percentile confidence intervals for mean paired differences were used to analyse the primary research questions.

RESULTS

Odds of correctly diagnosing list format notes were 26% greater than with narrative notes. However, there is insufficient evidence that this difference is significant (75% CI 0.8-1.99). On average the list format notes required 85.6 more seconds to process and arrive at a diagnosis compared to narrative notes (95% CI -162.3, -2.77). Of cases where participants included the correct diagnosis, on average the list format notes required 94.17 more seconds compared to narrative notes (75% CI -195.9, -8.83).

CONCLUSION

This study offers note format considerations for those interested in improving clinical documentation and suggests directions for future research. Balancing the priority of clinician preference with value of structured data may be necessary.

IMPLICATIONS

This study provides a method and suggestive results for further investigation in usability of electronic documentation formats.

Establishing a global quality of care benchmark report

BACKGROUND

The Movember funded TrueNTH Global Registry (TNGR) aims to improve care by collecting and analysing a consistent dataset to identify variation in disease management, benchmark care delivery in accordance with best practice guidelines and provide this information to those in a position to enact change. We discuss considerations of designing and implementing a quality of care report for TNGR.

METHODS

Eleven working group sessions were held prior to and as reports were being built with representation from clinicians, data managers and investigators contributing to TNGR. The aim of the meetings was to understand current data display approaches, share literature review findings and ideas for innovative approaches. Preferred displays were evaluated with two surveys (survey 1: 5 clinicians and 5 non-clinicians, 83% response rate; survey 2: 17 clinicians and 18 non-clinicians, 93% response rate).

RESULTS

Consensus on dashboard design and three data-display preferences were achieved. The dashboard comprised two performance summary charts; one summarising site's relative quality indicator (QI) performance and another to summarise data quality. Binary outcome QIs were presented as funnel plots. Patient-reported outcome measures of function score and the extent to which men were bothered by their symptoms were presented in bubble plots. Time series graphs were seen as providing important information to supplement funnel and bubble plots. R Markdown was selected as the software program principally because of its excellent analytic and graph display capacity, open source licensing model and the large global community sharing program code enhancements.

CONCLUSIONS

International collaboration in creating and maintaining clinical quality registries has allowed benchmarking of process and outcome measures on a large scale. A registry report system was developed with stakeholder engagement to produce dynamic reports that provide user-specific feedback to 132 participating sites across 13 countries.

Impact of a problem-oriented view on clinical data retrieval

OBJECTIVE

The electronic health record (EHR) data deluge makes data retrieval more difficult, escalating cognitive load and exacerbating clinician burnout. New auto-summarization techniques are needed. The study goal was to determine if problem-oriented view (POV) auto-summaries improve data retrieval workflows. We hypothesized that POV users would perform tasks faster, make fewer errors, be more satisfied with EHR use, and experience less cognitive load as compared with users of the standard view (SV).

METHODS

Simple data retrieval tasks were performed in an EHR simulation environment. A randomized block design was used. In the control group (SV), subjects retrieved lab results and medications by navigating to corresponding sections of the electronic record. In the intervention group (POV), subjects clicked on the name of the problem and immediately saw lab results and medications relevant to that problem.

RESULTS

With POV, mean completion time was faster (173 seconds for POV vs 205 seconds for SV; P < .0001), the error rate was lower (3.4% for POV vs 7.7% for SV; P = .0010), user satisfaction was greater (System Usability Scale score 58.5 for POV vs 41.3 for SV; P < .0001), and cognitive task load was less (NASA Task Load Index score 0.72 for POV vs 0.99 for SV; P < .0001).

DISCUSSION

The study demonstrates that using a problem-based auto-summary has a positive impact on 4 aspects of EHR data retrieval, including cognitive load.

CONCLUSION

EHRs have brought on a data deluge, with increased cognitive load and physician burnout. To mitigate these increases, further development and implementation of auto-summarization functionality and the requisite knowledge base are needed.

Need for Interactive Data Visualization in Public Health Practice: Examples from India

The world is full of data which is increasing by leaps and bounds. In health care, big data is becoming common with increased electronic health data accumulation and/or accessibility to public data previously held under lock and key. At the same time, health data visualization applications have become popular over recent years. Against this background, a review was done to summarize the application of data visualization in public health & the challenges faced. Peer-reviewed original research articles and review articles searched in Google Scholar and Pubmed databases that were indexed in the last ten years period, using the keywords “Big data” or “data visualization” or “Interactive visualization techniques.” Other related information in books, blogs, and published documents were searched in Google search engine using the same keywords. Contents from the downloaded documents were presented and discussed under three headings viz. (a) the visualizations that are still current and how they have evolved further, (b) tools or methods that can be used by end-users to make their own modifications, (c) the platforms to disseminate them. Usage of different plots in public health is explained with suitable examples using the data from public health datasets. From the discussion it can be understood that when big data is visualized well, it can identify implementation gaps and disparities and accelerate implementation strategies to reach the population groups in most need for interventions. As health administrator may come from diverse specialties, robust training and career development for big data in public health is the need of the hour.

Impact of Age on Patients' Communication and Technology Preferences in the Era of Meaningful Use: Mixed Methods Study

BACKGROUND

Identifying effective means of communication between patients and their health care providers has a positive impact on patients' satisfaction, adherence, and health-related outcomes.

OBJECTIVE

This study aimed to identify the impact of patients' age on their communication and technology preferences when managing their health. We hypothesize that a patient's age affects their communication and technology preferences when interacting with clinicians and managing their health.

METHODS

A mixed methods study was conducted to identify the preferences of patients with cardiovascular diseases. Results were analyzed based on the patients' age. Grounded theory was used to analyze the qualitative data. Patients were recruited based on age, gender, ethnicity, and zip code.

RESULTS

A total of 104 patients were recruited: 34 young adults (19-39 years), 33 middle aged (40-64), and 37 senior citizens (>65). Young adults (mean 8.29, SD 1.66) reported higher computer self-efficacy than middle-aged participants (mean 5.56, SD 3.43; P<.05) and senior citizens (mean 47.55, SD 31.23; P<.05). Qualitative analysis identified the following three themes: (1) patient engagement (young adults favored mobile technologies and text messaging, middle-aged patients preferred phone calls, and senior citizens preferred direct interactions with the health care provider); (2) patient safety (young adults preferred electronic after-visit summaries [AVS] and medication reconciliation over the internet; middle-aged patients preferred paper-based or emailed AVS and medication reconciliation in person; senior citizens preferred paper-based summaries and in-person medication reconciliation); (3) technology (young adults preferred smartphones and middle-aged patients and senior citizens preferred tablets or PCs). Middle-aged patients were more concerned about computer security than any other group. A unique finding among senior citizens was the desire for caregivers to have access to their personal health record (PHR).

CONCLUSIONS

Patients of different ages have different communication and technology preferences and different preferences with respect to how they would like information presented to them and how they wish to interact with their provider. The PHR is one approach to improving patient engagement, but nontechnological options need to be sustained to support all patients.

Novel displays of patient information in critical care settings: a systematic review

OBJECTIVE

Clinician information overload is prevalent in critical care settings. Improved visualization of patient information may help clinicians cope with information overload, increase efficiency, and improve quality. We compared the effect of information display interventions with usual care on patient care outcomes.

MATERIALS AND METHODS

We conducted a systematic review including experimental and quasi-experimental studies of information display interventions conducted in critical care and anesthesiology settings. Citations from January 1990 to June 2018 were searched in PubMed and IEEE Xplore. Reviewers worked independently to screen articles, evaluate quality, and abstract primary outcomes and display features.

RESULTS

Of 6742 studies identified, 22 studies evaluating 17 information displays met the study inclusion criteria. Information display categories included comprehensive integrated displays (3 displays), multipatient dashboards (7 displays), physiologic and laboratory monitoring (5 displays), and expert systems (2 displays). Significant improvement on primary outcomes over usual care was reported in 12 studies for 9 unique displays. Improvement was found mostly with comprehensive integrated displays (4 of 6 studies) and multipatient dashboards (5 of 7 studies). Only 1 of 5 randomized controlled trials had a positive effect in the primary outcome.

CONCLUSION

We found weak evidence suggesting comprehensive integrated displays improve provider efficiency and process outcomes, and multipatient dashboards improve compliance with care protocols and patient outcomes. Randomized controlled trials of physiologic and laboratory monitoring displays did not show improvement in primary outcomes, despite positive results in simulated settings. Important research translation gaps from laboratory to actual critical care settings exist.

Improving Team-Based Decision Making Using Data Analytics and Informatics: Protocol for a Collaborative Decision Support Design

Background

According to the September 2015 Institute of Medicine report, Improving Diagnosis in Health Care, each of us is likely to experience one diagnostic error in our lifetime, often with devastating consequences. Traditionally, diagnostic decision making has been the sole responsibility of an individual clinician. However, diagnosis involves an interaction among interprofessional team members with different training, skills, cultures, knowledge, and backgrounds. Moreover, diagnostic error is prevalent in the interruption-prone environment, such as the emergency department, where the loss of information may hinder a correct diagnosis.

Objective

The overall purpose of this protocol is to improve team-based diagnostic decision making by focusing on data analytics and informatics tools that improve collective information management.

Methods

To achieve this goal, we will identify the factors contributing to failures in team-based diagnostic decision making (aim 1), understand the barriers of using current health information technology tools for team collaboration (aim 2), and develop and evaluate a collaborative decision-making prototype that can improve team-based diagnostic decision making (aim 3).

Results

Between 2019 to 2020, we are collecting data for this study. The results are anticipated to be published between 2020 and 2021.

Conclusions

The results from this study can shed light on improving diagnostic decision making by incorporating diagnostics rationale from team members. We believe a positive direction to move forward in solving diagnostic errors is by incorporating all team members, and using informatics.

International Registered Report Identifier (IRRID)

DERR1-10.2196/16047

Ramf: An Open-Source R Package for Statistical Analysis and Display of Quantitative Root Colonization by Arbuscular Mycorrhiza Fungi

Data analysis and graphical representation form an essential part of scientific research dissemination. The life-science community is moving towards a more transparent presentation of single data points or data distributions and away from mean values displayed as bar charts. To facilitate transparent data display to the mycorrhiza community, we present "Ramf" an open-source R package for statistical analysis and preparation of a variety of publication-ready plots, custom-made for analyzing and displaying quantitative root colonization by arbuscular mycorrhiza fungi or any kind of data to be displayed in the same format. Ramf replaces the scripting needed for data analysis and can be readily used by researchers not acquainted with R. In addition, the package is open to improvements by the community. Ramf is available at https://github.com/mchiapello/Ramf.

Task-Data Taxonomy for Health Data Visualizations: Web-Based Survey With Experts and Older Adults

Background

Increasingly, eHealth involves health data visualizations to enable users to better understand their health situation. Selecting efficient and ergonomic visualizations requires knowledge about the task that the user wants to carry out and the type of data to be displayed. Taxonomies of abstract tasks and data types bundle this knowledge in a general manner. Task-data taxonomies exist for visualization tasks and data. They also exist for eHealth tasks. However, there is currently no joint task taxonomy available for health data visualizations incorporating the perspective of the prospective users. One of the most prominent prospective user groups of eHealth are older adults, but their perspective is rarely considered when constructing tasks lists.

Objective

The aim of this study was to construct a task-data taxonomy for health data visualizations based on the opinion of older adults as prospective users of eHealth systems. eHealth experts served as a control group against the bias of lacking background knowledge. The resulting taxonomy would then be used as an orientation in system requirement analysis and empirical evaluation and to facilitate a common understanding and language in eHealth data visualization.

Methods

Answers from 98 participants (51 older adults and 47 eHealth experts) given in an online survey were quantitatively analyzed, compared between groups, and synthesized into a task-data taxonomy for health data visualizations.

Results

Consultation, diagnosis, mentoring, and monitoring were confirmed as relevant abstract tasks in eHealth. Experts and older adults disagreed on the importance of mentoring (χ²₄=14.1, P=.002) and monitoring (χ²₄=22.1, P<.001). The answers to the open questions validated the findings from the closed questions and added therapy, communication, cooperation, and quality management to the aforementioned tasks. Here, group differences in normalized code counts were identified for “monitoring” between the expert group (mean 0.18, SD 0.23) and the group of older adults (mean 0.08, SD 0.15; t₉₆=2431, P=.02). Time-dependent data was most relevant across all eHealth tasks. Finally, visualization tasks and data types were assigned to eHealth tasks by both experimental groups.

Conclusions

We empirically developed a task-data taxonomy for health data visualizations with prospective users. This provides a general framework for theoretical concession and for the prioritization of user-centered system design and evaluation. At the same time, the functionality dimension of the taxonomy for telemedicine—chosen as the basis for the construction of present taxonomy—was confirmed.

The assessment of diagnostic medical images using 10-bit grayscale - fact or myth?

PURPOSE

The aim of the study was to find tests for verification of 10-bit grayscale support for radiological workstation hardware/operating system and for DICOM viewer. Also, we wanted to perform the tests on available workstations.

MATERIAL AND METHODS

The following tests were selected to verify 10-bit grayscale support: workstation hardware and operating system tests using DirectX SDK 10BitScanout10.exe and NEC 10bitdemo.exe programs, DICOM viewer tests using TG18-MP and TG18-QC patterns. The tests were performed on 14 radiological workstations in a local department of radiology and on 4 radiological workstations during the technical exhibition at the ECR (European Congress of Radiology) in 2017.

RESULTS

Only 3 out of 14 local workstations passed the hardware and operating system 10-bit grayscale support test. Only one workstation passed the DICOM viewer 10-bit grayscale support test.

CONCLUSIONS

Hardware/operating system and DICOM viewer 10-bit grayscale support should be tested on every radiological workstation even if compatibility is stated by the manufacturer. Existing medical diagnostic display quality requirements should be adjusted so that 10-bit support for DICOM viewers is only a desirable option.

[Infoxication in health. Health information overload on the Internet and the risk of important information becoming invisible]

OBJECTIVE

The objectives of this study were to: 1) raise awareness of the volume of quality health information on the Internet; 2) explore perceptions of information professionals with regard to the use of qualified sources for health decision-making; and 3) make recommendations that facilitate strengthening health worker capacities and institutional competencies related to digital literacy.

METHODS

A non-experimental, descriptive cross-sectional study was conducted with a non-probability sample of 32 information professionals from nine countries. Internet information was compiled on the volume of content in Internet tools, social networks, and health information sources. Searches in English and Spanish were carried out using the keywords Ebola, Zika, dengue, chikungunya, safe food, health equity, safe sex, and obesity. Finally, information was obtained on opportunities for formal education on the subjects of digital literacy, information management, and other related topics.

RESULTS

Selecting only four diseases with a high impact on public health in May 2016 and averaging minimum review time for each information product, it would take more than 50 years without sleeping to consult everything that is published online about dengue, Zika, Ebola, and chikungunya.

CONCLUSION

We conclude that public health would benefit from: health institutions implementing formal knowledge management strategies; academic health sciences institutions incorporating formal digital literacy programs; and having health workers who are professionally responsible and functional in the information society.

Technology and tuberculosis control: the OUT-TB Web experience

Objective

Develop a tool to disseminate integrated laboratory, clinical, and demographic case data necessary for improved contact tracing and outbreak detection of tuberculosis (TB).

Methods

In 2007, the Public Health Ontario Laboratories implemented a universal genotyping program to monitor the spread of TB strains within Ontario. Ontario Universal Typing of TB (OUT-TB) Web utilizes geographic information system (GIS) technology with a relational database platform, allowing TB control staff to visualize genotyping matches and microbiological data within the context of relevant epidemiological and demographic data.

Results

OUT-TB Web is currently available to the 8 health units responsible for >85% of Ontario's TB cases and is a valuable tool for TB case investigation. Users identified key features to implement for application enhancements, including an e-mail alert function, customizable heat maps for visualizing TB and drug-resistant cases, socioeconomic map layers, a dashboard providing TB surveillance metrics, and a feature for animating the geographic spread of strains over time.

Conclusion

OUT-TB Web has proven to be an award-winning application and a useful tool. Developed and enhanced using regular user feedback, future versions will include additional data sources, enhanced map and line-list filter capabilities, and development of a mobile app.

New Unintended Adverse Consequences of Electronic Health Records

Although the health information technology industry has made considerable progress in the design, development, implementation, and use of electronic health records (EHRs), the lofty expectations of the early pioneers have not been met. In 2006, the Provider Order Entry Team at Oregon Health & Science University described a set of unintended adverse consequences (UACs), or unpredictable, emergent problems associated with computer-based provider order entry implementation, use, and maintenance. Many of these originally identified UACs have not been completely addressed or alleviated, some have evolved over time, and some new ones have emerged as EHRs became more widely available. The rapid increase in the adoption of EHRs, coupled with the changes in the types and attitudes of clinical users, has led to several new UACs, specifically: complete clinical information unavailable at the point of care; lack of innovations to improve system usability leading to frustrating user experiences; inadvertent disclosure of large amounts of patient-specific information; increased focus on computer-based quality measurement negatively affecting clinical workflows and patient-provider interactions; information overload from marginally useful computer-generated data; and a decline in the development and use of internally-developed EHRs. While each of these new UACs poses significant challenges to EHR developers and users alike, they also offer many opportunities. The challenge for clinical informatics researchers is to continue to refine our current systems while exploring new methods of overcoming these challenges and developing innovations to improve EHR interoperability, usability, security, functionality, clinical quality measurement, and information summarization and display.

Visualization approaches to support healthy aging: A systematic review

Background

Informatics tools have the potential to support the growing number of older adults who are aging in place. Many tools include visualizations (data visualizations and visualizations of physical representations). However, the role of visualizations in supporting aging in place remains largely unexplored.

Objective

To synthesize and identify gaps in the literature evaluating visualizations (data visualizations and visualizations of physical representations) for informatics tools to support healthy aging.

Methods

We conducted a search in CINAHL, Embase, Engineering Village, PsycINFO, PubMed, and Web of Science using a priori defined terms for publications in English describing community-based studies evaluating visualizations used by adults aged ≥ 65 years.

Results

Six out of the identified 251 publications were eligible. Most studies described in the publications were user studies and all varied methodological quality. Three publications described visualizations of virtual representations supported performing at-home exercises. Participants found visual representations either (1) helpful, motivational, and supported their understanding of their health behaviours or (2) not an improvement over alternatives. Three publications described data visualizations that aimed to support understanding of one’s health. Participants were able to interpret data visualizations that used precise data and encodings that were more concrete better than those that did not provide precision or were abstract. Participants found data visualizations helpful in understanding their overall health and granular data.

Conclusions

Few studies were identified that used and evaluated visualizations for older adults to promote engagement in exercises or understanding of their health. While visualizations demonstrated some promise to support older adult users in these activities, the studies had various methodological limitations. More research is needed, including research that overcomes methodological limitations of studies we identified, to develop visualizations that older adults could use with ease and accuracy to support their health behaviours and decision making.

Understanding Older Adult Use of Data Visualizations as a Resource for Maintaining Health and Wellness

To better understand how older adults use health visualizations and the potential barriers that impact utility, we conducted semistructured interviews with 21 older adults. Within these sessions, we presented participants with two interactive visualizations for exploration. Through an affinity mapping exercise, we extracted five key themes associated with how older adults utilize health visualizations and provide corresponding recommendations as points of consideration for designers developing older adult focused health visualizations. By examining how older adults perceive the utility of health visualizations, we lay the groundwork for design choices that impact eventual use and adoption of systems that generate data for such visualizations.

Leveraging cues from person-generated health data for peer matching in online communities

OBJECTIVE

Online health communities offer a diverse peer support base, yet users can struggle to identify suitable peer mentors as these communities grow. To facilitate mentoring connections, we designed a peer-matching system that automatically profiles and recommends peer mentors to mentees based on person-generated health data (PGHD). This study examined the profile characteristics that mentees value when choosing a peer mentor.

MATERIALS AND METHODS

Through a mixed-methods user study, in which cancer patients and caregivers evaluated peer mentor recommendations, we examined the relative importance of four possible profile elements: health interests, language style, demographics, and sample posts. Playing the role of mentees, the study participants ranked mentors, then rated both the likelihood that they would hypothetically contact each mentor and the helpfulness of each profile element in helping the make that decision. We analyzed the participants' ratings with linear regression and qualitatively analyzed participants' feedback for emerging themes about choosing mentors and improving profile design.

RESULTS

Of the four profile elements, only sample posts were a significant predictor for the likelihood of a mentee contacting a mentor. Communication cues embedded in posts were critical for helping the participants choose a compatible mentor. Qualitative themes offer insight into the interpersonal characteristics that mentees sought in peer mentors, including being knowledgeable, sociable, and articulate. Additionally, the participants emphasized the need for streamlined profiles that minimize the time required to choose a mentor.

CONCLUSION

Peer-matching systems in online health communities offer a promising approach for leveraging PGHD to connect patients. Our findings point to interpersonal communication cues embedded in PGHD that could prove critical for building mentoring relationships among the growing membership of online health communities.

Interactive tools for inpatient medication tracking: a multi-phase study with cardiothoracic surgery patients

OBJECTIVE

Prior studies of computing applications that support patients' medication knowledge and self-management offer valuable insights into effective application design, but do not address inpatient settings. This study is the first to explore the design and usefulness of patient-facing tools supporting inpatient medication management and tracking.

MATERIALS AND METHODS

We designed myNYP Inpatient, a custom personal health record application, through an iterative, user-centered approach. Medication-tracking tools in myNYP Inpatient include interactive views of home and hospital medication data and features for commenting on these data. In a two-phase pilot study, patients used the tools during cardiothoracic postoperative care at Columbia University Medical Center. In Phase One, we provided 20 patients with the application for 24-48 h and conducted a closing interview after this period. In Phase Two, we conducted semi-structured interviews with 12 patients and 5 clinical pharmacists who evaluated refinements to the tools based on the feedback received during Phase One.

RESULTS

Patients reported that the medication-tracking tools were useful. During Phase One, 14 of the 20 participants used the tools actively, to review medication lists and log comments and questions about their medications. Patients' interview responses and audit logs revealed that they made frequent use of the hospital medications feature and found electronic reporting of questions and comments useful. We also uncovered important considerations for subsequent design of such tools. In Phase Two, the patients and pharmacists participating in the study confirmed the usability and usefulness of the refined tools.

CONCLUSIONS

Inpatient medication-tracking tools, when designed to meet patients' needs, can play an important role in fostering patient participation in their own care and patient-provider communication during a hospital stay.

An aid to generating figures for the American Journal of Epidemiology using SAS/GRAPH

Data visualization is an important tool that epidemiologists use to communicate with others in the field. The American Journal of Epidemiology recently acknowledged the importance of data visualization by inaugurating an award for the "Figure of the Year." Yet, creating figures that adhere to the standards of the Journal is a challenge. The purpose of the present article was to provide helpful hints for creating figures in SAS/GRAPH that meet the requirements of the Journal. It stresses 3 techniques: properly sizing figures overall, sizing text within a figure, and creating acceptable file formats. This information will prove useful to authors who create data-driven figures intended to be published in the Journal.

Integrating Quantitative and Qualitative Results in Health Science Mixed Methods Research Through Joint Displays

PURPOSE

Mixed methods research is becoming an important methodology to investigate complex health-related topics, yet the meaningful integration of qualitative and quantitative data remains elusive and needs further development. A promising innovation to facilitate integration is the use of visual joint displays that bring data together visually to draw out new insights. The purpose of this study was to identify exemplar joint displays by analyzing the various types of joint displays being used in published articles.

METHODS

We searched for empirical articles that included joint displays in 3 journals that publish state-of-the-art mixed methods research. We analyzed each of 19 identified joint displays to extract the type of display, mixed methods design, purpose, rationale, qualitative and quantitative data sources, integration approaches, and analytic strategies. Our analysis focused on what each display communicated and its representation of mixed methods analysis.

RESULTS

The most prevalent types of joint displays were statistics-by-themes and side-by-side comparisons. Innovative joint displays connected findings to theoretical frameworks or recommendations. Researchers used joint displays for convergent, explanatory sequential, exploratory sequential, and intervention designs. We identified exemplars for each of these designs by analyzing the inferences gained through using the joint display. Exemplars represented mixed methods integration, presented integrated results, and yielded new insights.

CONCLUSIONS

Joint displays appear to provide a structure to discuss the integrated analysis and assist both researchers and readers in understanding how mixed methods provides new insights. We encourage researchers to use joint displays to integrate and represent mixed methods analysis and discuss their value.

Design and feasibility of integrating personalized PRO dashboards into prostate cancer care

OBJECTIVE

Patient-reported outcomes (PROs) are a valued source of health information, but prior work focuses largely on data capture without guidance on visual displays that promote effective PRO use in patient-centered care. We engaged patients, providers, and design experts in human-centered design of "PRO dashboards" that illustrate trends in health-related quality of life (HRQOL) reported by patients following prostate cancer treatment.

MATERIALS AND METHODS

We designed and assessed the feasibility of integrating dashboards into care in 3 steps: (1) capture PRO needs of patients and providers through focus groups and interviews; (2) iteratively build and refine a prototype dashboard; and (3) pilot test dashboards with patients and their provider during follow-up care.

RESULTS

Focus groups (n = 60 patients) prioritized needs for dashboards that compared longitudinal trends in patients' HRQOL with "men like me." Of the candidate dashboard designs, 50 patients and 50 providers rated pictographs less helpful than bar charts, line graphs, or tables (P < .001) and preferred bar charts and line graphs most. Given these needs and the design recommendations from our Patient Advisory Board (n = 7) and design experts (n = 7), we built and refined a prototype that charts patients' HRQOL compared with age- and treatment-matched patients in personalized dashboards. Pilot testing dashboard use (n = 12 patients) improved compliance with quality indicators for prostate cancer care (P < .01).

CONCLUSION

PRO dashboards are a promising approach for integrating patient-generated data into prostate cancer care. Informed by human-centered design principles, this work establishes guidance on dashboard content, tailoring, and clinical use that patients and providers find meaningful.

An evaluation of wellness assessment visualizations for older adults

BACKGROUND

Smart home technologies provide a valuable resource to unobtrusively monitor health and wellness within an older adult population. However, the breadth and density of data available along with aging associated decreases in working memory, prospective memory, spatial cognition, and processing speed can make it challenging to comprehend for older adults. We developed visualizations of smart home health data integrated into a framework of wellness. We evaluated the visualizations through focus groups with older adults and identified recommendations to guide the future development of visualizations.

MATERIALS AND METHODS

We conducted four focus groups with older adult participants (n=31) at an independent retirement community. Participants were presented with three different visualizations from a wellness pilot study. A qualitative descriptive analysis was conducted to identify thematic content.

RESULTS

We identified three themes related to processing and application of visualizations: (1) values of visualizations for wellness assessment, (2) cognitive processing approaches to visualizations, and (3) integration of health data for visualization. In addition, the focus groups highlighted key design considerations of visualizations important towards supporting decision-making and evaluation assessments within integrated health displays.

CONCLUSIONS

Participants found inherent value in having visualizations available to proactively engage with their healthcare provider. Integrating the visualizations into a wellness framework helped reduce the complexity of raw smart home data. There has been limited work on health visualizations from a consumer perspective, in particular for an older adult population. Creating appropriately designed visualizations is valuable towards promoting consumer involvement within the shared decision-making process of care.

Technical and radiological image quality comparison of different liquid crystal displays for radiology

BACKGROUND

To inform cost-effective decisions in purchasing new medical liquid crystal displays, we compared the image quality in displays made by three manufacturers.

METHODS

We recruited 19 radiologists and residents to compare the image quality of four liquid crystal displays, including 3-megapixel Barco(®), Eizo(®), and NEC(®) displays and a 6-megapixel Barco display. The evaluators were blinded to the manufacturers' names. Technical assessments were based on acceptance criteria and test patterns proposed by the American Association of Physicists in Medicine. Radiological assessments were performed on images from the American Association of Physicists in Medicine Task Group 18. They included X-ray images of the thorax, knee, and breast, a computed tomographic image of the thorax, and a magnetic resonance image of the brain. Image quality was scored on an analog scale (range 0-10). Statistical analysis was performed with repeated-measures analysis of variance.

RESULTS

The Barco 3-megapixel display passed all acceptance criteria. The Eizo and NEC displays passed the acceptance criteria, except for the darkest pixel value in the grayscale display function. The Barco 6-megapixel display failed criteria for the maximum luminance response and the veiling glare. Mean radiological assessment scores were 7.8±1.1 (Barco 3-megapixel), 7.8±1.2 (Eizo), 8.1±1.0 (NEC), and 8.1±1.0 (Barco 6-megapixel). No significant differences were found between displays.

CONCLUSION

According to the tested criteria, all the displays had comparable image quality; however, there was a three-fold difference in price between the most and least expensive displays.

Instructive head-mounted display system: pointing device using a vision-based finger tracking technique applied to surgical education

Introduction

The head-mounted display (HMD) system is a novel personalized imaging monitoring system for use in a medical setting.

Aim

To support interactive intraoperative communication among HMD wearers, we integrated vision-based finger tracking into our system as a pointing device.

Material and methods

Our vision-based finger tracking system is composed of a commercially available real-time video camera, which is mounted on the modern HMD, and computer software that enables tracking of the tip of the operator's index finger and superimposing the marker on the endoscopic view.

Results

We used this system in an experimental demonstration. The operator used the finger-tracking pointer to explain the intraoperative findings of transurethral resection for bladder cancer to medical students.

Conclusions

This finger tracking system-based pointing device can function as a supportive tool for the HMD system, enabling interactive instruction and communication between the operator and other attending physicians or medical students.

A head-mounted display-based personal integrated-image monitoring system for transurethral resection of the prostate

The head-mounted display (HMD) is a new image monitoring system. We developed the Personal Integrated-image Monitoring System (PIM System) using the HMD (HMZ-T2, Sony Corporation, Tokyo, Japan) in combination with video splitters and multiplexers as a surgical guide system for transurethral resection of the prostate (TURP). The imaging information obtained from the cystoscope, the transurethral ultrasonography (TRUS), the video camera attached to the HMD, and the patient's vital signs monitor were split and integrated by the PIM System and a composite image was displayed by the HMD using a four-split screen technique. Wearing the HMD, the lead surgeon and the assistant could simultaneously and continuously monitor the same information displayed by the HMD in an ergonomically efficient posture. Each participant could independently rearrange the images comprising the composite image depending on the engaging step. Two benign prostatic hyperplasia (BPH) patients underwent TURP performed by surgeons guided with this system. In both cases, the TURP procedure was successfully performed, and their postoperative clinical courses had no remarkable unfavorable events. During the procedure, none of the participants experienced any HMD-wear related adverse effects or reported any discomfort.

Interactive Visualization for Patient-to-Patient Comparison

A visual analysis approach and the developed supporting technology provide a comprehensive solution for analyzing large and complex integrated genomic and biomedical data. This paper presents a methodology that is implemented as an interactive visual analysis technology for extracting knowledge from complex genetic and clinical data and then visualizing it in a meaningful and interpretable way. By synergizing the domain knowledge into development and analysis processes, we have developed a comprehensive tool that supports a seamless patient-to-patient analysis, from an overview of the patient population in the similarity space to the detailed views of genes. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, and gene comparison. We demonstrate our approach with medical scientists on a case study of childhood cancer patients on how they use the tool to confirm existing hypotheses and to discover new scientific insights.

The effect of ambient illumination on handheld display image quality

Handheld devices such as smartphones and tablets are becoming useful in the medical field, as they allow physicians, radiologists, and researchers to analyze images with the benefit of mobile accessibility. However, for handheld devices to be effective, the display must be able to perform well in a wide range of ambient illumination conditions. We conducted visual experiments to quantify user performance for testing the image quality of two current-generation devices in different ambient illumination conditions while measuring ambient light levels with a real-time illuminance meter. We found and quantified that due to the high reflectivity of handheld devices, performance deteriorates as the user moves from dark areas into environments of greater ambient illumination. The quantitative analysis suggests that differences in display reflection coefficients do not affect the low illumination performance of the device but rather the performance at higher levels of illumination.

Advancing user experience research to facilitate and enable patient-centered research: current state and future directions

Human-computer interaction and related areas of user experience (UX) research, such as human factors, workflow evaluation, and data visualization, are thus essential to presenting data in ways that can further the analysis of complex data sets such as those used in patient-centered research. However, a review of available data on the state of UX research as it relates to patient-centered research demonstrates a significant underinvestment and consequently a large gap in knowledge generation. In response, this report explores trends in funding and research productivity focused on UX and patient-centered research and then presents a set of recommendations to advance innovation at this important intersection point. Ultimately, the aim is to catalyze a community-wide dialogue concerning future directions for research and innovation in UX as it applies to patient-centered research.

Health care transformation through collaboration on open-source informatics projects: integrating a medical applications platform, research data repository, and patient summarization

Background

The Strategic Health IT Advanced Research Projects (SHARP) program seeks to conquer well-understood challenges in medical informatics through breakthrough research. Two SHARP centers have found alignment in their methodological needs: (1) members of the National Center for Cognitive Informatics and Decision-making (NCCD) have developed knowledge bases to support problem-oriented summarizations of patient data, and (2) Substitutable Medical Apps, Reusable Technologies (SMART), which is a platform for reusable medical apps that can run on participating platforms connected to various electronic health records (EHR). Combining the work of these two centers will ensure wide dissemination of new methods for synthesized views of patient data. Informatics for Integrating Biology and the Bedside (i2b2) is an NIH-funded clinical research data repository platform in use at over 100 sites worldwide. By also working with a co-occurring initiative to SMART-enabling i2b2, we can confidently write one app that can be used extremely broadly.

Objective

Our goal was to facilitate development of intuitive, problem-oriented views of the patient record using NCCD knowledge bases that would run in any EHR. To do this, we developed a collaboration between the two SHARPs and an NIH center, i2b2.

Methods

First, we implemented collaborative tools to connect researchers at three institutions. Next, we developed a patient summarization app using the SMART platform and a previously validated NCCD problem-medication linkage knowledge base derived from the National Drug File-Reference Terminology (NDF-RT). Finally, to SMART-enable i2b2, we implemented two new Web service “cells” that expose the SMART application programming interface (API), and we made changes to the Web interface of i2b2 to host a “carousel” of SMART apps.

Results

We deployed our SMART-based, NDF-RT-derived patient summarization app in this SMART-i2b2 container. It displays a problem-oriented view of medications and presents a line-graph display of laboratory results.

Conclusions

This summarization app can be run in any EHR environment that either supports SMART or runs SMART-enabled i2b2. This i2b2 “clinical bridge” demonstrates a pathway for reusable app development that does not require EHR vendors to immediately adopt the SMART API. Apps can be developed in SMART and run by clinicians in the i2b2 repository, reusing clinical data extracted from EHRs. This may encourage the adoption of SMART by supporting SMART app development until EHRs adopt the platform. It also allows a new variety of clinical SMART apps, fueled by the broad aggregation of data types available in research repositories. The app (including its knowledge base) and SMART-i2b2 are open-source and freely available for download.

Health providers' perceptions of novel approaches to visualizing integrated health information

OBJECTIVES

We evaluated the design of three novel visualization techniques for integrated health information with health care providers in older adult care. Through focus groups, we identified generalizable themes related to the visualization and interpretation of health information. Using these themes we address challenges with visualizing integrated health information and provide recommendations for designers.

METHODS

We recruited ten health care providers to participate in three focus groups. We applied a qualitative descriptive approach to code and extract themes related to the visualization of graphical displays.

RESULTS

We identified a set of four common themes across focus groups related to: 1) Trust in data for decision-making; 2) Perceived level of detail for visualization (subthemes: holistic, individual components); 3) Cognitive issues (subthemes: training and experience; cognitive overload; contrast); and 4) Application of visual displays. Furthermore, recommendations are provided as part of the iterative design process for the visualizations.

CONCLUSIONS

Data visualization of health information is an important component of care, impacting both the accuracy and speed of decision making. There are both functional and cognitive elements to consider during the development of appropriate visualizations that integrate different components of health.

Creating a magnetic resonance imaging ontology

The goal of this work is to build an ontology of Magnetic Resonance Imaging. The MRI domain has been analysed regarding MRI simulators and the DICOM standard. Tow MRI simulators have been analysed: JEMRIS, which is developed in XML and C++, has a hierarchical organisation and SIMRI, which is developed in C, has a good representation of MRI physical processes. To build the ontology we have used Protégé 4, owl2 that allows quantitative representations. The ontology has been validated by a reasoner (Fact++) and by a good representation of DICOM headers and of MRI processes. The MRI ontology would improved MRI simulators and eased semantic interoperability.

The design and evaluation of a graphical display for laboratory data

OBJECTIVE

Advances in healthcare information technology have provided opportunities to present data in new, more effective ways. In this study, we designed a laboratory display that features small, data-dense graphics called sparklines, which have recently been promoted as effective representations of medical data but have not been well studied. The effect of this novel display on physicians' interpretation of data was investigated.

DESIGN

Twelve physicians talked aloud as they assessed laboratory data from four patients in a pediatric intensive care unit with the graph display and with a conventional table display.

MEASUREMENTS

Verbalizations were coded based on the abnormal values and trends identified for each lab variable. The correspondence of interpretations of variables in each display was evaluated, and patterns were investigated across participants. Assessment time was also analyzed.

RESULTS

Physicians completed assessments significantly faster with the graphical display (3.6 min vs 4.4 min, p=0.042). When compared across displays, 37% of interpretations did not match. Graphs were more useful when the visual cues in tables did not provide trend information, while slightly abnormal values were easier to identify with tables.

CONCLUSIONS

Data presentation format can affect how physicians interpret laboratory data. Graphic displays have several advantages over numeric displays but are not always optimal. User, task and data characteristics should be considered when designing information displays.

Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments

An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.