Resilience Informatics for Public Health.

Resilience research is attracting increasing attention as stressors such as pandemics and climate change impact normal life worldwide. Informatics tools can play an important role in enhancing resilience of people, communities, and organizations. We present Resilience Informatics as a sub-discipline of resilience research and propose a conceptual framework for Resilience Informatics to aid in the development and effective deployment of informatics systems for resilience.

Chronic neuropsychiatric sequelae of SARS-CoV-2: Protocol and methods from the Alzheimer's Association Global Consortium.

Introduction: Coronavirus disease 2019 (COVID-19) has caused >3.5 million deaths worldwide and affected >160 million people. At least twice as many have been infected but remained asymptomatic or minimally symptomatic. COVID-19 includes central nervous system manifestations mediated by inflammation and cerebrovascular, anoxic, and/or viral neurotoxicity mechanisms. More than one third of patients with COVID-19 develop neurologic problems during the acute phase of the illness, including loss of sense of smell or taste, seizures, and stroke. Damage or functional changes to the brain may result in chronic sequelae. The risk of incident cognitive and neuropsychiatric complications appears independent from the severity of the original pulmonary illness. It behooves the scientific and medical community to attempt to understand the molecular and/or systemic factors linking COVID-19 to neurologic illness, both short and long term. Methods: This article describes what is known so far in terms of links among COVID-19, the brain, neurological symptoms, and Alzheimer's disease (AD) and related dementias. We focus on risk factors and possible molecular, inflammatory, and viral mechanisms underlying neurological injury. We also provide a comprehensive description of the Alzheimer's Association Consortium on Chronic Neuropsychiatric Sequelae of SARS-CoV-2 infection (CNS SC2) harmonized methodology to address these questions using a worldwide network of researchers and institutions. Results: Successful harmonization of designs and methods was achieved through a consensus process initially fragmented by specific interest groups (epidemiology, clinical assessments, cognitive evaluation, biomarkers, and neuroimaging). Conclusions from subcommittees were presented to the whole group and discussed extensively. Presently data collection is ongoing at 19 sites in 12 countries representing Asia, Africa, the Americas, and Europe. Discussion: The Alzheimer's Association Global Consortium harmonized methodology is proposed as a model to study long-term neurocognitive sequelae of SARS-CoV-2 infection. Key Points: The following review describes what is known so far in terms of molecular and epidemiological links among COVID-19, the brain, neurological symptoms, and AD and related dementias (ADRD)The primary objective of this large-scale collaboration is to clarify the pathogenesis of ADRD and to advance our understanding of the impact of a neurotropic virus on the long-term risk of cognitive decline and other CNS sequelae. No available evidence supports the notion that cognitive impairment after SARS-CoV-2 infection is a form of dementia (ADRD or otherwise). The longitudinal methodologies espoused by the consortium are intended to provide data to answer this question as clearly as possible controlling for possible confounders. Our specific hypothesis is that SARS-CoV-2 triggers ADRD-like pathology following the extended olfactory cortical network (EOCN) in older individuals with specific genetic susceptibility.The proposed harmonization strategies and flexible study designs offer the possibility to include large samples of under-represented racial and ethnic groups, creating a rich set of harmonized cohorts for future studies of the pathophysiology, determinants, long-term consequences, and trends in cognitive aging, ADRD, and vascular disease.We provide a framework for current and future studies to be carried out within the Consortium. and offers a "green paper" to the research community with a very broad, global base of support, on tools suitable for low- and middle-income countries aimed to compare and combine future longitudinal data on the topic.The Consortium proposes a combination of design and statistical methods as a means of approaching causal inference of the COVID-19 neuropsychiatric sequelae. We expect that deep phenotyping of neuropsychiatric sequelae may provide a series of candidate syndromes with phenomenological and biological characterization that can be further explored. By generating high-quality harmonized data across sites we aim to capture both descriptive and, where possible, causal associations.

Development and usability of a mobile tool for identification of depression and suicide risk in Fiji.

BACKGROUND: In Fiji and other South Pacific island countries, depression and suicide are of great concern. There is a pressing need to rapidly identify those at risk and provide treatment as soon as possible. OBJECTIVE: Design, develop and test a mobile health tool that enables CHNs to easily and rapidly identify individuals at risk for suicide and depression and provide guidelines for their treatment. METHODS: Using Android Studio, a native app called ASRaDA was developed that encoded two validated scales: Center for Epidemiological Studies-Depression (CES-D), and Suicide Behavior Questionnaire-Revised (SBQ-R). The usability of the app was measured using the System Usability Scale by community health nurses in Fiji. RESULTS: Out of a maximim possible of 100 on SUS, ASRaDA was scored at 86.79. CONCLUSION: Mobile tools with high usability can be designed to aid community health nurses in Fiji and Pacific island counties rapidly identify those at risk for depression and suicide.

Design and development of a mobile-based patient management and information system for infectious disease outbreaks in low resource environments.

BACKGROUND: The design of Patient Management and Information Systems during outbreaks of highly infectious diseases in low resource environments poses special challenges. Such systems necessitate special functional and design requirements to support patient care under austere conditions. A primary concern is to minimize spread of the disease to caregivers and non-infected individuals. Patient management in these conditions requires the design and development of systems customized for complex patient and caregiver workflows. OBJECTIVE: Design and develop a Patient Management and Information System for healthcare facilities on the frontlines of outbreaks of highly infectious diseases in low resource environments. METHODS: A team composed of clinicians with experience in Ebola care in affected areas of Africa and informaticians developed detailed hardware, software and functionality requirements. These were translated into hardware designs, software architectures, screen and interface designs and implemented using Common Off-The-Shelf hardware. An experimental app development system was used to develop mHealth software modules. RESULTS: The system was developed and implemented as a proof of concept. Acceptance testing showed that the system met functionality requirements. CONCLUSION: Useful Patient Management and Information systems can be developed and implemented for frontline use in low-resource environments during outbreaks of highly infectious diseases.

Mobile persuasive technology for the teaching and learning in surgical safety: Content validation.

BACKGROUND: Patient safety is a fundamental component of high-quality delivery of health care. However, despite scientific advances, surgical patients continue to face risks. Among the most common complications in surgery are operations on the wrong patient, performance of the wrong procedure or operation on the wrong surgical site, lack of adequate or required equipment, failure to prevent blood loss, and surgical items left inside patients. In this context, the planning and development of innovative educational strategies is important for prevention of adverse events and the improvement of surgical patient safety culture. OBJECTIVE: To describe the process of validating the content of mobile technology for education about surgical safety. METHODS: Content validation using the Delphi technique was carried out from December 2015 to January 2016 at a Federal University in South Brazil. Content development and animations were produced by the authors from a verification list for safety surgery and a safety surgery protocol. Twelve judges assessed five variables (Content, Language, Illustration, Layout and Motivation), for consensus on content validation. They evaluated quality of each item, using a rating scale consisting of five levels (1 to 5). RESULTS: Two assessment rounds were done, with a mean content validity index (CVI) of 0.95 and 1.0 and a kappa index of >0.83 and >0.92, respectively. The judges provided positive comments about each phase of the study, most of comments highlights were: choice of very relevant subject matter, excellent quality of the material and the motivation that the material can provide to the target audience. CONCLUSION: The study validated the content of learning technology by general consensus of judges with a high level of concordance among evaluated items. The application was considered adequate for educating students and health professionals about surgical safety.

Novel technology as platform for interventions for caregivers and individuals with severe mental health illnesses: A systematic review.

BACKGROUND: Severe mental illnesses (SMIs) have been found to be associated with both increases in morbidity-mortality, need for treatment care in patients themselves, and burden for relatives as caregivers. A growing number of web-based and mobile software applications have appeared that aim to address various barriers with respect to access to care. Our objective was to review and summarize recent advancements in such interventions for caregivers of individuals with a SMI. METHODS: We conducted a systematic search for papers evaluating interactive mobile or web-based software (using no or only minimal support from a professional) specifically aimed at supporting informal caregivers. We also searched for those supporting patients with SMI so as to not to miss any which might include relatives. RESULTS: Out of a total of 1673 initial hits, we identified 11 articles reporting on 9 different mobile or web-based software programs. The main result is that none of those studies focused on caregivers, and the ones we identified using mobile or web-based applications were just for patients and not their relatives. LIMITATIONS: Differentiating between online and offline available software might not always have been totally reliable, and we might have therefore missed some studies. CONCLUSIONS: In summary, the studies provided evidence that remotely accessible interventions for patients with SMI are feasible and acceptable to patients. No such empirically evaluated program was available for informal caregivers such as relatives. Keeping in mind the influential role of those informal caregivers in the process of treatment and self-management, this is highly relevant for public health. Supporting informal caregivers can improve well-being of both caregivers and patients.

Using Fault Trees to Advance Understanding of Diagnostic Errors.

PROBLEM DEFINITION: Diagnostic errors annually affect at least 5% of adults in the outpatient setting in the United States. Formal analytic techniques are only infrequently used to understand them, in part because of the complexity of diagnostic processes and clinical work flows involved. In this article, diagnostic errors were modeled using fault tree analysis (FTA), a form of root cause analysis that has been successfully used in other high-complexity, high-risk contexts. How factors contributing to diagnostic errors can be systematically modeled by FTA to inform error understanding and error prevention is demonstrated. INITIAL APPROACH: A team of three experts reviewed 10 published cases of diagnostic error and constructed fault trees. The fault trees were modeled according to currently available conceptual frameworks characterizing diagnostic error. The 10 trees were then synthesized into a single fault tree to identify common contributing factors and pathways leading to diagnostic error. KEY INSIGHTS: FTA is a visual, structured, deductive approach that depicts the temporal sequence of events and their interactions in a formal logical hierarchy. The visual FTA enables easier understanding of causative processes and cognitive and system factors, as well as rapid identification of common pathways and interactions in a unified fashion. In addition, it enables calculation of empirical estimates for causative pathways. Thus, fault trees might provide a useful framework for both quantitative and qualitative analysis of diagnostic errors. NEXT STEPS: Future directions include establishing validity and reliability by modeling a wider range of error cases, conducting quantitative evaluations, and undertaking deeper exploration of other FTA capabilities.

Persuasive technology in teaching acute pain assessment in nursing: Results in learning based on pre and post-testing.

BACKGROUND: Thousands of patients seek health services every day with complaints of pain. However, adequate pain assessment is still flawed, a fact that is partly related to gaps in professional learning on this topic. Innovative strategies such as the use of a virtual learning object mediated by persuasive technology in the learning of undergraduate nursing students can help to fill these gaps and to provide different ways of learning to learn. OBJECTIVE: To evaluate the results in learning among undergraduate nursing students about assessment of acute pain in adults and newborns, before and after an online educational intervention. DESIGN: This is a quasi-experimental, non-equivalent study using pre-and post-testing. SETTING: Federal University of Santa Catarina, Brazil. PARTICIPANTS: 75 undergraduate nursing students. METHODS: Our study was conducted in three steps (pre-test, education intervention, post-test). Data were collected from November 2013 to February 2014. The educational intervention was performed using online access to virtual learning object about acute pain assessment, which students accessed on their mobile devices. CONCLUSION: A significant difference was seen in student learning (p<0.001) in the post-test compared with the pre-test results. The students understood the importance of the topic, and were satisfied and motivated by the technology and method applied. The use of persuasive technology such as small mobile devices as mediators of online educational interventions broadens learning spaces in an innovative, flexible, motivational, and promising manner.

Measuring Workload Demand of Informatics Systems with the Clinical Case Demand Index.

Introduction: The increasing use of Health Information Technology (HIT) can add substantially to workload on clinical providers. Current methods for assessing workload do not take into account the nature of clinical cases and the use of HIT tools while solving them. Methods: The Clinical Case Demand Index (CCDI), consisting of a summary score and visual representation, was developed to meet this need. Consistency with current perceived workload measures was evaluated in a Randomized Control Trial of a mobile health system. Results: CCDI is significantly correlated with existing workload measures and inversely related to provider performance. Discussion: CCDI combines subjective and objective characteristics of clinical cases along with cognitive and clinical dimensions. Applications include evaluation of HIT tools, clinician scheduling, medical education. Conclusion: CCDI supports comparative effectiveness research of HIT tools. In addition, CCDI could have numerous applications including training, clinical trials, design of clinical workflows, and others.

Mobile phone-based clinical guidance for rural health providers in India.

There are few tried and tested mobile technology applications to enhance and standardize the quality of health care by frontline rural health providers in low-resource settings. We developed a media-rich, mobile phone-based clinical guidance system for management of fevers, diarrhoeas and respiratory problems by rural health providers. Using a randomized control design, we field tested this application with 16 rural health providers and 128 patients at two rural/tribal sites in Tamil Nadu, Southern India. Protocol compliance for both groups, phone usability, acceptability and patient feedback for the experimental group were evaluated. Linear mixed-model analyses showed statistically significant improvements in protocol compliance in the experimental group. Usability and acceptability among patients and rural health providers were very high. Our results indicate that mobile phone-based, media-rich procedural guidance applications have significant potential for achieving consistently standardized quality of care by diverse frontline rural health providers, with patient acceptance.

Representing second opinion requests from primary care within the Brazilian tele-health program: international classification of primary care, second edition.

Standardization of second opinion question-answer pairs with a classification system can be used to facilitate data sharing and reuse. The Brazilian telehealth program faces the problem of representing biomedical knowledge from the primary care second opinion demands generated by rural health care teams. The objective is to determine if one of the medical classification systems has a superior ability to standardize Portuguese-language second opinion question-answer pairs. Data from 2,638 second opinions from 2010 were randomly reduced to a 264 question-answer pair data set. The semantic meaning of the question-answer pairs was manually assigned to an International Classification of Primary Care, Second edition (ICPC2) code. Eight question-answer pairs did not contain sufficient medical semantic meaning to allow for mapping to an ICPC2 code; 53 question-answer pairs did contain sufficient medical semantic meaning for mapping, however an appropriate ICPC2 code did not exist; and 203 question-answer pairs did contain sufficient medical semantic meaning for mapping to an ICPC2 code. A review of the literature indicates that there is no baseline to compare the 77% success rate against.

Decreasing workload among community health workers using interactive, structured, rich-media guidelines on smartphones.

BACKGROUND: Currently, in developing countries, there is considerable interest in using mobile phones as job-aids for community health workers (CHWs) to improve the care they provide. However, acceptance of new technologies can be inhibited if the workload imposed is perceived as excessive compared to existing methods. OBJECTIVE: To compare perceived workload of CHWs using clinical care guidelines presented on mobile phones versus using conventional paper-based guidelines. METHODS: Validated clinical practice guidelines were developed as Interactive Structured Rich-Medical guidelines (ISRMGs) on Windows Mobile 6.5 mobile phones. A prospective randomized controlled study was performed in Colombia in which 50 CHWs used the ISRMGs, and paper-based materials with the same information, in a cross-over design to diagnose and treat 15 matched pairs of medical cases presented on Human Patient simulators. The NASA Task Load Index, a validated measure of perceived workload, was administered and results compared by means of a mixed model analysis. RESULTS: When using the ISRMGs on mobile phones the health workers reported statistically significant decreases in mental demand, frustration, and overall workload as compared to using paper-based job-aids. CONCLUSIONS: Use of ISRMGs on mobile phones by community health workers in developing countries has the potential to decrease their perceived workload, fatigue, and enhance their ability to provide better care for more patients.

The promise of the CCD: challenges and opportunity for quality improvement and population health.

Interoperability is a requirement of recent electronic health record (EHR) adoption incentive programs in the United States. One approved structure for clinical data exchange is the continuity of care document (CCD). While primarily designed to promote communication between providers during care transitions, coded data in the CCD can be re-used to aggregate data from different EHRs. This provides an opportunity for provider networks to measure quality and improve population health from a consolidated database. To evaluate such potential, this research collected CCDs from 14 organizations and developed a computer program to parse and aggregate them. In total, 139 CCDs were parsed yielding 680 data in the core content modules of problems, medications, allergies and results. Challenges to interoperability were catalogued and potential quality metrics evaluated based on available content. This research highlights the promise of CCDs for population health and recommends changes for future interoperability standards.

Optimizing medical resources for spaceflight using the integrated medical model.

INTRODUCTION: Efficient allocation of medical resources for spaceflight is important for crew health. The Integrated Medical Model (IMM) was developed to estimate medical event occurrences, mitigation, and resource requirements. An optimization module was created for IMM that uses a systematic process of elimination and preservation to maximize crew health outcomes subject to resource constraints. METHODS: A maximum medical kit is identified and resources are eliminated according to their relative impact on outcomes of interest. Additional steps allow opportunities for resources to be added back into the medical kit if possible. The effectiveness of the module is demonstrated under six alternative mission profiles by optimizing the medical kit to maximize the expected Crew Health Index (CHI), and comparisons are made with minimum and maximum kits. RESULTS: The optimum and maximum kits had similar expected CHI, but CHI was more variable for the optimum kit. The maximum kit resulted in the best outcomes, but required at least 13.7 times the mass of the optimum kit and 26.6 times the volume. The largest difference in mean CHI between the optimum and maximum kits occurred for four crewmembers on a 180-d mission (91.1% vs. 95.4%). CONCLUSIONS: The optimization module may be used as an objective tool to assist with the efficient allocation of medical resources for spaceflight. The module provides a flexible algorithm that may be used in conjunction with the IMM model to assist in medical kit requirements and design.

MEDRank: using graph-based concept ranking to index biomedical texts.

BACKGROUND: As the volume of biomedical text increases exponentially, automatic indexing becomes increasingly important. However, existing approaches do not distinguish central (or core) concepts from concepts that were mentioned in passing. We focus on the problem of indexing MEDLINE records, a process that is currently performed by highly trained humans at the National Library of Medicine (NLM). NLM indexers are assisted by a system called the Medical Text Indexer (MTI) that suggests candidate indexing terms. OBJECTIVE: To improve the ability of MTI to select the core terms in MEDLINE abstracts. These core concepts are deemed to be most important and are designated as "major headings" by MEDLINE indexers. We introduce and evaluate a graph-based indexing methodology called MEDRank that generates concept graphs from biomedical text and then ranks the concepts within these graphs to identify the most important ones. METHODS: We insert a MEDRank step into the MTI and compare MTI's output with and without MEDRank to the MEDLINE indexers' selected terms for a sample of 11,803 PubMed Central articles. We also tested whether human raters prefer terms generated by the MEDLINE indexers, MTI without MEDRank, and MTI with MEDRank for a sample of 36 PubMed Central articles. RESULTS: MEDRank improved recall of major headings designated by 30% over MTI without MEDRank (0.489 vs. 0.376). Overall recall was only slightly (6.5%) higher (0.490 vs. 0.460) as was F(2) (3%, 0.408 vs. 0.396). However, overall precision was 3.9% lower (0.268 vs. 0.279). Human raters preferred terms generated by MTI with MEDRank over terms generated by MTI without MEDRank (by an average of 1.00 more term per article), and preferred terms generated by MTI with MEDRank and the MEDLINE indexers at the same rate. CONCLUSIONS: The addition of MEDRank to MTI significantly improved the retrieval of core concepts in MEDLINE abstracts and more closely matched human expectations compared to MTI without MEDRank. In addition, MEDRank slightly improved overall recall and F(2).

Performance factors of mobile rich media job aids for community health workers.

OBJECTIVE: To study and analyze the possible benefits on performance of community health workers using point-of-care clinical guidelines implemented as interactive rich media job aids on small-format mobile platforms. DESIGN: A crossover study with one intervention (rich media job aids) and one control (traditional job aids), two periods, with 50 community health workers, each subject solving a total 15 standardized cases per period per period (30 cases in total per subject). MEASUREMENTS: Error rate per case and task, protocol compliance. RESULTS: A total of 1394 cases were evaluated. Intervention reduces errors by an average of 33.15% (p = 0.001) and increases protocol compliance 30.18% (p < 0.001). Limitations Medical cases were presented on human patient simulators in a laboratory setting, not on real patients. CONCLUSION: These results indicate encouraging prospects for mHealth technologies in general, and the use of rich media clinical guidelines on cell phones in particular, for the improvement of community health worker performance in developing countries.

Cytoview: development of a cell modelling framework.

The biological cell, a natural self-contained unit of prime biological importance, is an enormously complex machine that can be understood at many levels. A higher-level perspective of the entire cell requires integration of various features into coherent, biologically meaningful descriptions. There are some efforts to model cells based on their genome, proteome or metabolome descriptions. However, there are no established methods as yet to describe cell morphologies, capture similarities and differences between different cells or between healthy and disease states. Here we report a framework to model various aspects of a cell and integrate knowledge encoded at different levels of abstraction, with cell morphologies at one end to atomic structures at the other. The different issues that have been addressed are ontologies, feature description and model building. The framework describes dotted representations and tree data structures to integrate diverse pieces of data and parametric models enabling size, shape and location descriptions. The framework serves as a first step in integrating different levels of data available for a biological cell and has the potential to lead to development of computational models in our pursuit to model cell structure and function, from which several applications can flow out.

Using hit curves to compare search algorithm performance.

Databases continue to grow but the metrics available to evaluate information retrieval systems have not changed. Large collections such as MEDLINE and the World Wide Web contain many relevant documents for common queries. Ranking is therefore increasingly important and successful information retrieval systems, such as Google, have emphasized ranking. However, existing evaluation metrics such as precision and recall, do not directly account for ranking. This paper describes a novel way of measuring information retrieval performance using weighted hit curves adapted from the field of statistical detection to reflect multiple desirable characteristics such as relevance, importance, and methodologic quality. In statistical detection, hit curves have been proposed to represent occurrence of interesting events during a detection process. Similarly, hit curves can be used to study the position of relevant documents within large result sets. We describe hit curves in light of a formal model of information retrieval, show how hit curves represent system performance including ranking, and define ways to statistically compare performance of multiple systems using hit curves. We provide example scenarios where traditional measures are less suitable than hit curves and conclude that hit curves may be useful for evaluating retrieval from large collections where ranking performance is crucial.

Hypothesis generation in signaling networks.

Biological signaling networks comprise the chemical processes by which cells detect and respond to changes in their environment. Such networks have been implicated in the regulation of important cellular activities, including cellular reproduction, mobility, and death. Though technological and scientific advances have facilitated the rapid accumulation of information about signaling networks, utilizing these massive information resources has become infeasible except through computational methods and computer-based tools. To date, visualization and simulation tools have received significant emphasis. In this paper, we present a graph-theoretic formalization of biological signaling network models that are in wide but informal use, and formulate two problems on the graph: the Constrained Downstream and Minimum Knockout Problems. Solutions to these problems yield qualitative tools for generating hypotheses about the networks, which can then be experimentally tested in a laboratory setting. Using established graph algorithms, we provide a solution to the Constrained Downstream Problem. We also show that the Minimum Knockout Problem is NP-Hard, propose a heuristic, and assess its performance. In tests on the Epidermal Growth Factor Receptor (EGFR) network, we find that our heuristic reports the correct solution to the problem in seconds. Source code for the implementations of both solutions is available from the authors upon request.