Informatics Solutions Research Articles

A-195 Combination of Lean Mindset, Robotics and Digitalization allowed us to manage a 2.5 times increase in workload in our central reference lab

Abstract Background Our Agilus Diagnostics, Gurugram, India is a Central Reference Laboratory and part of the pan-India network over 400 lab in India. Our Gurugram lab delivers 3,200 tubes in the serum work area in 17 hour operations daily and is ISO 15189 and CAP accredited.In Jan 2023, our lab started to support Govt PHC Program samples and our workload increased to 8000 tubes. This was a clear operational and clinical challenge for us with a 2.5 x jump in workload. To achieve this goal, a lean mindset with process improvement steps were to be applied required across the total testing process. This lean approach was supported by cobas ® Lab Automation systems managed by navify ® Lab Operations informatics automation solution. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency when faced with this challenge. Methods We took 4 major steps We redesigned lab processes using lean process improvement operational dashboards. This poster will show the metric we track which help eliminate waste in the system. We optimized our total lab automation solution with smart load balancing across cobas ® Pro integrated analyzers and staff friendly recursive workflow. Clear and strict use of off peak hours for maintenance and QC procedures and standardized predictable schedule of operation. This poster will share our time table with key milestones across the 24 hours We built on the Informatics solution using 5 layered Auto verification rules based decision framework. IQC, Systems Flags check, Sample Quality checks, Biological Reference check, custom Auto verification Range, Critical ranges Delta check Criteria, Clinical Correlation Rule are all part of the auto verification logic framework. Results We were able to deliver the following results.Lean process design led to 53% simplification. Number of process steps reduced to 29 from 62 steps across the total testing process. Total Lab Automation has helped improve 90 percentile production TAT by 46% from 250 mins to 135 mins Our 90 % TAT CV has significantly reduced making our production predictable. Over 17,500 results / day reported are subject to auto verification with 87 % of all results auto-verified and auto-approved. Not a single additional employee was added in the analytical or post analytical areas of the lab operations Conclusions Lean Mindset complemented by Total Laboratory Automation along with Decision Automation on an Informatics solution has enhanced lab performance in terms of TAT, Efficiency, and Staff Motivation. This poster will also demonstrate using incremental effectiveness analysis comparative data of key performance indicators, such predictability in production, and efficiency of workforce, senior staff time saved, before and after technology deployment. The challenge of increase in sample workload is real in India and this approach allows for a sustainable way to ensure patient impact with minimum burden on our workforce.

B-128 Delivering Predictable Operational efficiency gains at our core central reference laboratory with strategic deployment of navify® Lab Operation informatics automation solution

Abstract Background Metropolis Healthcare Limited (‘MHL’) operates a network of 200 clinical labs in India, our Global Reference Lab (GRL) in Mumbai processes over 25000 tests in a 17 hour daily operation. We are an ISO15189 and CAP accredited laboratory. Our strategic goals have been to bring operational standardization across the network & Improve speed of service with a predictable 90 percentile production TAT. To achieve this goal, we chose digitalization of our laboratory operation with the deployment of navify ® Lab Operations informatics automation solution in. This poster explains our journey of planning, implementing, and delivering on our goal of predictable operational efficiency. The digital solution is at the forefront of all digitalization IQC processes, auto validation and auto approval of patient results passing through a framework of autoverification rules and complete traceability of processes. Methods The poster will explain the scope, planning and implementation approach of this digital automation project at Global reference Lab in 5 stepsHL7 order structure for communication between LIS and navify ® Lab Operations22 analyzers from 11 different manufacturers being connected to the Informatics solution. the corresponding testingTest & IQC (Internal Quality Control) Master with specific ranges and rules10 steps AV (Auto verification) Rules decision framework of concentric sieves across lab disciplines (155 AV Algorithms have been configured at GRL)Structured user acceptance testing framework before Go Live. Results This poster discusses the outcomes that we have seen on deployment of this digital solution.Over 25,000 test results are subject AV engine daily with AV rate of 75 % of all results in Biochemistry, Immunoassays.66 % of all Complete Blood Count (CBC) reports 95 % of all HbA1c results 93 % of all ESR resultsOver 1750 QC results are subject to QC rules dailyThere is an improvement of 4 hours observed in production TAT Conclusions Laboratory Informatics solution has enhanced lab performance in terms of TAT & efficiency of review. The staff satisfaction (both technical and medical) has increased and we see an impact on production outcome. The poster will also show an incremental effectiveness analysis by comparing key performance areas such as predictability in production, staff time saved, before and after technology deployment.

Multitasking during Medication Management in a Nursing Home: A Time Motion Study.

Multitasking, defined as performing two or more interventions simultaneously, increases the cognitive burden of clinicians. This may, in turn, lead to higher risk of medication and procedural errors. Time motion study (TMS) data for nurses in nursing homes revealed an extensive amount of multitasking while managing medications. Further investigation of multitasked nursing interventions will provide a foundation for optimizing medication management workflows. Using a continuous observational TMS method, this study aimed to describe pairs of multitasked nursing interventions associated with medication management interventions, including preparing and administering medications, assessing medication effects, instructing on medications, and documenting medication administration. An external nurse observer used 57 predefined Omaha System nursing interventions embedded within TimeCaT (version 3.9), TMS data recording software to collect observation data in a single nursing home. A total of 120 hours of time-stamped observation data from nine nurses were downloaded from TimeCaT and analyzed using descriptive and inferential statistics. The majority (74%) of medication management interventions were multitasked, resulting in 2,003 pairs of multitasked interventions. Of the 57 Omaha System nursing interventions, 35 were involved in these multitasking pairs. When nurses multitasked, the average duration of medication preparation was longer (non-multitasked: 81 seconds; multitasked: 162 seconds, p < 0.05), while the average duration of medication administration record documentation was shorter (non-multitasked: 93 seconds; multitasked: 66 seconds, p < 0.05). The findings reveal the complexity of medication management in nursing homes with numerous and diverse multitasking pairs. Findings provide a platform for in-depth study of medication management multitasking in the clinical context, and inform future efforts to create clinical and informatics solutions to optimize medication management workflow. This method may be also applied to examine medication management and multitasking in other clinical settings.

Occupational Electronic Health Records (OEHRs): Recommendations for the Design and Implementation of Information Systems in Occupational and Environmental Medicine Practice - ACOEM Guidance Statement.

Occupational and Environmental Medicine (OEM) clinicians require specialized Electronic Health Records (EHRs) to address the privacy, data governance, interoperability, and medical surveillance concerns that are specific to occupational health. The American College of Occupational and Environmental Medicine (ACOEM) Section of Health Informatics evaluated clinical workflow concerns, assessed health information requirements, and developed informatics recommendations through iterative consultation with ACOEM members. ACOEM presents ten recommendations that specialized Occupational EHR systems (OEHRs) should meet to serve the information needs and practice requirements of OEM clinicians. Common challenges in OEM practice and potential informatics solutions are used to illustrate each recommendation. The recommendations serve as a framework for occupational health clinicians to consider in their adoption of OEHRs and provide software engineers a set of requirements to facilitate the development and improvement of OEHRs.

Advancements in health informatics for monitoring perioperative patient data

Advancements in health informatics are revolutionizing perioperative care by enhancing patient monitoring, improving clinical decision-making, and promoting patient safety. The integration of electronic health records (EHR) facilitates seamless information flow across all perioperative stages, ensuring up-to-date patient data is accessible to the entire healthcare team. This accessibility reduces errors, improves coordination, and enhances overall patient outcomes. EHR systems also support standardized documentation, reducing variability in record-keeping and ensuring comprehensive patient information is consistently captured. Real-time data analytics and predictive modeling are powerful tools in perioperative settings, enabling clinicians to anticipate and manage potential complications proactively. By analyzing vast datasets, predictive models identify patterns and risk factors associated with adverse outcomes, allowing for targeted interventions and personalized care plans. Real-time analytics provide continuous monitoring of patient status during surgery, offering immediate feedback and enabling prompt adjustments to ensure patient stability. Wearable devices and remote monitoring systems further augment real-time data analytics by continuously tracking physiological parameters throughout the surgical process and into the postoperative period. This continuous data stream allows for ongoing assessment of patient status and early detection of complications, enhancing patient safety and outcomes. Health informatics solutions, including automated alerts and decision support tools, minimize human error and ensure adherence to clinical guidelines. Automated reminders for critical actions, such as timely antibiotic administration, significantly reduce the incidence of surgical site infections. Decision support tools provide real-time, evidence-based recommendations at the point of care, supporting clinicians in making informed decisions and improving patient outcomes. Additionally, health informatics facilitates continuous quality improvement by enabling the collection and analysis of performance data, informing targeted interventions and process improvements. Overall, advancements in health informatics are transforming perioperative care, offering numerous benefits in terms of efficiency, accuracy, and patient safety, ultimately leading to better patient outcomes and higher quality of care. Continued innovation in this field will be essential for maintaining and improving the standards of perioperative care.

Decoding Retinoblastoma: Unveiling Gene Networks and Potential Targets through In Silico Analysis

Background Retinoblastoma is an aggressive cancer whose majority of patients are infants and children below the age of five. Approximately 80% of the total patients of retinoblastoma reside in low-to-middle-income countries like India. Lack of public and medical awareness and the absence of significant and regular clinical trials to test and authenticate new potential treatments impede the process of treating retinoblastoma. Attempts have been made to establish an effective way to diagnose retinoblastoma early so that it can be controlled in time, but so far, no significant success has been documented on that front. Moreover, recent strategies include computational and informatics solutions to identify potential targets at a genetic level to alter the expression of defective proteins in human subjects. Aim The main aim of the current study is to unravel the potential targets of Retinoblastoma, an aggressive pediatric cancer, utilizing an in silico network biology approach. Methods In the present study, we have utilized the gene network analysis approach to identify hub genes that affect the expression in the human system. We developed the Protein – Protein Interaction network utilizing 158 genes extracted from the NCBI OMIM database and identified 15 key genes, which were then subjected to metascape analysis to identify pathways and processes that affect and prioritize genes based on their significance scores. We were able to identify the following target genes: RBBP4, TFDP1, and RBBP7. Result RBBP4, TFDP1, and RBBP7 were identified as the most novel target genes against retinoblastoma after gene network and enrichment analysis. Conclusion Our in-silico network analysis unveiled the intricate mechanisms behind the progression of retinoblastoma by dissecting 158 associated genes in humans. Thus, this work not only illuminates the underlying dynamics of the disease but also offers a promising avenue for intervention.

A review of the challenges and opportunities in implementing health informatics in rural healthcare settings

This paper reviews the challenges and opportunities associated with implementing health informatics in rural healthcare settings. It examines the unique barriers rural communities face, such as infrastructure limitations, workforce shortages, and financial constraints, which can impede the adoption and utilization of health informatics solutions. However, it also explores the promising opportunities afforded by health informatics, including telemedicine, electronic health records (EHRs), and mobile health technologies, to overcome these challenges and improve healthcare access, quality, and efficiency in rural areas. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Telemedicine, for instance, enables remote consultations and diagnostic services, breaking down geographic barriers and providing rural patients with access to specialists and healthcare expertise they may not have locally. Electronic Health Records (EHRs) streamline administrative processes, improve care coordination, and enhance patient safety by ensuring that vital health information is readily accessible to healthcare providers regardless of location. Mobile health technologies, including smartp hone apps and wearable devices, empower rural residents to monitor their health, track chronic conditions, and engage in self-management activities from the comfort of their homes.By embracing these innovations and overcoming infrastructure challenges, stakeholders in rural healthcare can significantly improve healthcare access, quality, and efficiency. Additionally, leveraging health informatics can help address workforce shortages by enabling healthcare providers to deliver more effective and integrated care, even in remote areas. Ultimately, by harnessing the opportunities presented by health informatics while addressing the unique challenges of rural healthcare, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. Keywords: Health Informatics, Rural Healthcare, Electronic Health Records (EHRS), Mobile Health, Challenges.

Abstract PO4-10-10: NAVYA-AI enabled intervention to increase real-world guideline compliant care: Improving NGS testing in breast cancer

Abstract BACKGROUND: Navya-AI is a validated online cancer informatics solution that combines artificial intelligence based analysis of the guidelines and evidence, along with asynchronous expert review. Navya-AI releases preliminary system-generated opinions for patients whose treatment plans fit high confidence based on NCCN Guidelines and prior expert reviews. Prior research (SABCS 2014-2018 and ASCO 2021 showed: 1) 97% concordance of Navya-AI predictions with an academic medical center in India and in the US 2) 80% of patients implement treatment concordant with Navya-AI recommendations on the ground 3) Navya’s NCCN and evidence-based treatment plans reduce the patient waiting times for an expert opinion by an average by 3.5 days. Next generation sequencing (NGS) is an expensive but necessary method for identifying patients for risk reduction and therapy selection in breast cancer (BC). NGS testing can be over-used or under-used, and compliance with NCCN guidelines on patient selection is especially important in resource-constrained settings and Low Middle Income Countries (LMIC) such as India. The aim of this study is to find the physician compliance to NCCN guidelines on NGS testing in India, and how Navya-AI can identify the opportunity for improved care, and improve compliance with guidelines for optimal care. METHODS: From January 2022 to May 2023, Breast Cancer patients receiving Navya-AI treatment plan (based on guidelines and live expert-review) were analyzed. Patients who could afford NGS testing and targeted therapies, and who met the Enhanced tier of NCCN resource stratified guidelines for their care centers were identified. Their records were screened by Navya-AI to assess if they met NCCN criteria for NGS testing for risk reduction or for treatment selection (young age, positive family history, triple negative breast cancer etc.). Treating physicians were then analyzed if they had ordered NGS appropriately, or had missed an opportunity for NGS (undertreatment), or had over-ordered NGS (overtreatment).RESULTS: 521 BC patients who could afford NGS tests received a Navya-AI plan during this period. Of these, 85% were Indian patients (415/521) and were analyzed. Patients were diverse with respect to age,cancer stage, family history of cancer and histology: Age &amp;lt; 35: 6.7%, 35-50: 33%, 51-65: 43.76%, &amp;gt;65: 16.51%; early stage: 21.5%, locally advanced stage: 29.56%,metastatic stage: 47.79% and benign disease: 1%; positive family history of cancer: 37.35%, triple negative BC: 21.9%. Of 415 indian breast cancer patients who could afford testing, NGS testing was indicated in 69.64% (289/415) as per NCCN guidelines. The treating physician was compliant with NCCN guidelines in only 47.95% (199/415) of the cases: 19.2% (80/415) of the time, NGS was indicated and the treating physician ordered the same; 28.67% (119/415) of the time, NGS was not indicated, and the treating physician did not order NGS. The remaining 52% were not compliant with NCCN. Under-treatment was present in 50.36% (209/415) of cases, and was the vast majority of fallouts. Over-treatment was only present in 1.69% (7/415). In all 50.63% (209/415) cases, where NGS was not ordered by the treating oncologist, but was indicated, and affordable to the patient, Navya requested the patient to discuss the risks/benefits of NGS testing with their treating oncologist. CONCLUSION: NGS testing in BC patients has significant impact on risk-reduction, genetic counseling, choice of surgery, and treatment options for adjuvant therapy. Missed opportunities for NGS testing in more than 50% of the patients who can afford the testing and resultant therapies, points to a signficant area where compliance with guidelines and expert opinions can impact outcomes. A 'Technological Earthshot" that significantly increases adoption of guideline-based care is the first and an easy step towards 'Cancer Moonshots'. Citation Format: RA Badwe, Premal Thaker, Farzana Begum, Mayukh Acherjee, Gitika Srivastava, Naresh Ramarajan, Shona Nag, Sudeep Gupta, Seema Gulia, Jaya Ghosh, Bhawna Sirohi. NAVYA-AI enabled intervention to increase real-world guideline compliant care: Improving NGS testing in breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-10-10.

Workflow analysis of breast cancer treatment decision-making: challenges and opportunities for informatics to support patient-centered cancer care.

Decision support can improve shared decision-making for breast cancer treatment, but workflow barriers have hindered widespread use of these tools. The goal of this study was to understand the workflow among breast cancer teams of clinicians, patients, and their family caregivers when making treatment decisions and identify design guidelines for informatics tools to better support treatment decision-making. We conducted observations of breast cancer clinicians during routine clinical care from February to August 2022. Guided by the work system model, a human factors engineering model that describes the elements of work, we recorded all aspects of clinician workflow using a tablet and smart pencil. Observation notes were transcribed and uploaded into Dedoose. Two researchers inductively coded the observations. We identified themes relevant to the design of decision support that we classified into the 4 components of workflow (ie, flow of information, tasks, tools and technologies, and people). We conducted 20 observations of breast cancer clinicians (total: 79 hours). We identified 10 themes related to workflow that present challenges and opportunities for decision support design. We identified approximately 48 different decisions discussed during breast cancer visits. These decisions were often interdependent and involved collaboration across the large cancer treatment team. Numerous patient-specific factors (eg, work, hobbies, family situation) were discussed when making treatment decisions as well as complex risk and clinical information. Patients were frequently asked to remember and relay information across the large cancer team. Based on these findings, we proposed design guidelines for informatics tools to support the complex workflows involved in breast cancer care. These guidelines should inform the design of informatics solutions to better support breast cancer decision-making and improve patient-centered cancer care.

Application of Artificial Intelligence or machine learning in risk sharing agreements for pharmacotherapy risk management.

Applications of Artificial Intelligence in medical informatics solutions risk sharing have social value. At a time of ever-increasing cost for the provision of medicines to citizens, there is a need to restrain the growth of health care costs. The search for computer technologies to stop or slow down the growth of costs acquires a new very important and significant meaning. We discussed the two information technologies in pharmacotherapy and the possibility of combining and sharing them, namely the combination of risk-sharing agreements and Machine Learning, which was made possible by the development of Artificial Intelligence (AI). Neural networks could be used to predict the outcome to reduce the risk factors for treatment. AI-based data processing automation technologies could be also used for risk-sharing agreements automation.

Lessons Learned in Change Management in Deploying Novel Informatics Solutions: Experience Implementing a Point-of-Care Patient Photography System with Radiography

We describe implementation of a point-of-care system for simultaneous acquisition of patient photographs along with portable radiographs at a large academic hospital. During the implementation process, we observed several technical challenges in the areas of (1) hardware—automatic triggering for photograph acquisition, camera hardware enclosure, networking, and system server hardware and (2) software—post-processing of photographs. Additionally, we also faced cultural challenges involving workflow issues, communication with technologists and users, and system maintenance. We describe our solutions to address these challenges. We anticipate that these experiences will provide useful insights into deploying and iterating new technologies in imaging informatics.

Training of Greek Public Administrators in Legal Knowledge Management by Using the Legislation Editing Open Software (LEOS)

The article describes the evolution of an innovative legal interoperability laboratory within the National School of Public Administration and Local Government in Athens, Greece. While critically analysing its general scope, objectives and structure, the knowledge management perspective of an interoperable legal informatics solution for handling big open legal data is brought into focus. In the context of the laboratory, the use of Legislation Editing Open Software (LEOS), a legal informatics tool that has been developed as a European Union ISA2 solution, is highlighted. Different aspects of and lessons learned from the training of public administrators are discussed while assessing this operations support system for potential use as a web-based authoring tool by the Hellenic public service. The evaluation of both the laboratory and the tool was conducted based on expert surveys, and possible upgrades are discussed to make the training of public administration more efficient.

Predicting the retention time of Synthetic Cannabinoids using a combinatorial QSAR approach

BackgroundAbuse of Synthetic Cannabinoids (SCs) has become a serious threat to public health. Due to the various structural and chemical group modified by criminals, their detection is a major challenge in forensic toxicological identification. Therefore, rapid and efficient identification of SCs is important for forensic toxicology and drug bans. The prediction of an analyte's retention time in liquid chromatography is an important index for the qualitative analysis of compounds and can provide informatics solutions for the interpretation of chromatographic data. MethodsIn this study, experimental data from high-resolution mass spectrometry (HRMS) are used to construct a regression model for predicting the retention time of SCs using machine learning methods. The prediction ability of the model is improved by adopting a strategy that combines different descriptors in different independent machine-learning methods. ResultsThe best model was obtained with a method that combined Substructure Fingerprint Count and Finger printer features and the support vector regression (SVR) method, as it exhibited an R2 value of 0.81 for the validation set and 0.83 for the test set. In addition, 4 new SCs were predicted by the optimized model, with a prediction error within 3%. ConclusionsOur study provides a model that can predict the retention time of compounds and it can be used as a filter to reduce false-positive candidates when used in combination with LC-HRMS, especially in the absence of reference standards. This can improve the confidence of identification in non-targeted analysis and the reliability of identifying unknown substances.

Comparison of SIREN social needs screening tools and Simplified Omaha System Terms: informing an informatics approach to social determinants of health assessments.

Numerous studies indicate that the social determinants of health (SDOH), conditions in which people work, play, and learn, account for 30%-55% of health outcomes. Many healthcare and social service organizations seek ways to collect, integrate, and address the SDOH. Informatics solutions such as standardized nursing terminologies may facilitate such goals. In this study, we compared one standardized nursing terminology, the Omaha System, in its consumer-facing form, Simplified Omaha System Terms (SOST), to social needs screening tools identified by the Social Interventions Research and Evaluation Network (SIREN). Using standard mapping techniques, we mapped 286 items from 15 SDOH screening tools to 335 SOST challenges. The SOST assessment includes 42 concepts across 4 domains. We analyzed the mapping using descriptive statistics and data visualization techniques. Of the 286 social needs screening tools items, 282 (98.7%) mapped 429 times to 102 (30.7%) of the 335 SOST challenges from 26 concepts in all domains, most frequently from Income, Home, and Abuse. No single SIREN tool assessed all SDOH items. The 4 items not mapped were related to financial abuse and perceived quality of life. SOST taxonomically and comprehensively collects SDOH data compared to SIREN tools. This demonstrates the importance of implementing standardized terminologies to reduce ambiguity and ensure the shared meaning of data. SOST could be used in clinical informatics solutions for interoperability and health information exchange, including SDOH. Further research is needed to examine consumer perspectives regarding SOST assessment compared to other social needs screening tools.

Exploring implementation outcomes in the clinical trial context: a qualitative study of physician trial stakeholders

IntroductionCancer clinical trials can be considered evidence-based interventions with substantial benefits, but suffer from poor implementation leading to low enrollment and frequent failure. Applying implementation science approaches such as outcomes frameworks to the trial context could aid in contextualizing and evaluating trial improvement strategies. However, the acceptability and appropriateness of these adapted outcomes to trial stakeholders are unclear. For these reasons, we interviewed cancer clinical trial physician stakeholders to explore how they perceive and address clinical trial implementation outcomes.MethodsWe purposively selected 15 cancer clinical trial physician stakeholders from our institution representing different specialties, trial roles, and trial sponsor types. We performed semi-structured interviews to explore a previous adaptation of Proctor’s Implementation Outcomes Framework to the clinical trial context. Emergent themes from each outcome were developed.ResultsThe implementation outcomes were well understood and applicable (i.e., appropriate and acceptable) to clinical trial stakeholders. We describe cancer clinical trial physician stakeholder understanding of these outcomes and current application of these concepts. Trial feasibility and implementation cost were felt to be most critical to trial design and implementation. Trial penetration was most difficult to measure, primarily due to eligible patient identification. In general, we found that formal methods for trial improvement and trial implementation evaluation were poorly developed. Cancer clinical trial physician stakeholders referred to some design and implementation techniques used to improve trials, but these were infrequently formally evaluated or theory-based.ConclusionImplementation outcomes adapted to the trial context were acceptable and appropriate to cancer clinical trial physician stakeholders. Use of these outcomes could facilitate the evaluation and design of clinical trial improvement interventions. Additionally, these outcomes highlight potential areas for the development of new tools, for example informatics solutions, to improve the evaluation and implementation of clinical trials.

Data integration and analysis for circadian medicine.

Data integration, data sharing, and standardized analyses are important enablers for data-driven medical research. Circadian medicine is an emerging field with a particularly high need for coordinated and systematic collaboration between researchers from different disciplines. Datasets in circadian medicine are multimodal, ranging from molecular circadian profiles and clinical parameters to physiological measurements and data obtained from (wearable) sensors or reported by patients. Uniquely, data spanning both the time dimension and the spatial dimension (across tissues) are needed to obtain a holistic view of the circadian system. The study of human rhythms in the context of circadian medicine has to confront the heterogeneity of clock properties within and across subjects and our inability to repeatedly obtain relevant biosamples from one subject. This requires informatics solutions for integrating and visualizing relevant data types at various temporal resolutions ranging from milliseconds and seconds to minutes and several hours. Associated challenges range from a lack of standards that can be used to represent all required data in a common interoperable form, to challenges related to data storage, to the need to perform transformations for integrated visualizations, and to privacy issues. The downstream analysis of circadian rhythms requires specialized approaches for the identification, characterization, and discrimination of rhythms. We conclude that circadian medicine research provides an ideal environment for developing innovative methods to address challenges related to the collection, integration, visualization, and analysis of multimodal multidimensional biomedical data.

MassChemSite for In-Depth Forced Degradation Analysis of PARP Inhibitors Olaparib, Rucaparib, and Niraparib.

Drugs must satisfy several protocols and tests before being approved for the market. Among them, forced degradation studies aim to evaluate drug stability under stressful conditions in order to predict the formation of harmful degradation products (DPs). Recent advances in LC-MS instrumentation have facilitated the structure elucidation of degradants, although a comprehensive data analysis still represents a bottle-neck due to the massive amount of data that can be easily generated. MassChemSite has been recently described as a promising informatics solution for LC-MS/MS and UV data analysis of forced degradation experiments and for the automated structural identification of DPs. Here, we applied MassChemSite to investigate the forced degradation of three poly(ADP-ribose) polymerase inhibitors (olaparib, rucaparib, and niraparib) under basic, acidic, neutral, and oxidative stress conditions. Samples were analyzed by UHPLC with online DAD coupled to high-resolution mass spectrometry. The kinetic evolution of the reactions and the influence of solvent on the degradation process were also assessed. Our investigation confirmed the formation of three DPs of olaparib and the wide degradation of the drug under the basic condition. Intriguingly, base-catalyzed hydrolysis of olaparib was greater when the content of aprotic-dipolar solvent in the mixture decreased. For the other two compounds, whose stability has been much less studied previously, six new degradants of rucaparib were identified under oxidative degradation, while niraparib emerged as stable under all stress conditions tested.

Analysis of user interactions with a digital health wallet for enabling care continuity in the context of an ongoing pandemic.

The onset of COVID-19 and related policy responses made it difficult to study interactive health informatics solutions in clinical study settings. Instrumented log and event data from interactive systems capture temporal details that can be used to generate insights about care continuity during ongoing pandemics. To investigate user interactions with a digital health wallet (DHW) system for addressing care continuity challenges in chronic disease management in the context of an ongoing pandemic. We analyzed user interaction log data generated by clinicians, nurses, and patients from the deployment of a DHW in a feasibility study conducted during the COVID-19 pandemic in Kenya. We used the Hamming distance from Information Theory to quantify deviations of usage patterns extracted from the events data from predetermined workflow sequences supported by the platform. Nurses interacted with all the user interface elements relevant to triage. Clinicians interacted with only 43% of elements relevant to consultation, while patients interacted with 67% of the relevant user interface elements. Nurses and clinicians deviated from the predetermined workflow sequences by 42% and 36%, respectively. Most deviations pertained to users going back to previous steps in their usage workflow. User interaction log analysis is a valuable alternative method for generating and quantifying user experiences in the context of ongoing pandemics. However, researchers should mitigate the potential disruptions of the actual use of the studied technologies as well as use multiple approaches to investigate user experiences of health technology during pandemics.

Integrating health disparities content into health informatics courses: a cross-sectional survey study and recommendations.

To assess the extent to which health disparities content is integrated in multidisciplinary health informatics training programs and examine instructor perspectives surrounding teaching strategies and challenges, including student engagement with course material. Data for this cross-sectional, descriptive study were collected between April and October 2019. Instructors of informatics courses taught in the United States were recruited via listservs and email. Eligibility was contingent on course inclusion of disparities content. Participants completed an online survey with open- and closed-ended questions to capture administrative- and teaching-related aspects of disparities education within informatics. Quantitative data were analyzed using descriptive statistics; qualitative data were analyzed using inductive coding. Invitations were sent to 141 individuals and 11 listservs. We obtained data from 23 instructors about 24 informatics courses containing health disparities content. Courses were taught primarily in graduate-level programs (n = 21, 87.5%) in informatics (n = 9, 33.3%), nursing (n = 7, 25.9%), and information science (n = 6, 22.2%). The average course covered 6.5 (range 2-13) social determinants of health; socioeconomic status and race/ethnicity (both n = 21, 87.5%) were most frequently addressed. Instructors described multiple obstacles, including lack of resources and time to cover disparities topics adequately, topic sensitivity, and student-related challenges (eg, lack of prior understanding about disparities). A foundational and translational knowledge in health disparities is critical to a student's ability to develop future equitable informatics solutions. Based on our findings, we provide recommendations for the intentional and required integration of health disparities-specific content in informatics curricula and competencies.

Using health information technology to support the needs of Children with Medical Complexity: Mapping review of consumer informatics applications.

Children with medical complexity (CMC) are fragile populations that require continuous care and supervision. CMC family caregivers experience many challenges trying to address CMC patients' needs which puts these caregivers in a stressful situation that may negatively impact the care of CMC patients. Consumer informatics might help these caregivers in coordinating care. However, few consumer informatics applications explicitly focus on supporting CMC caregivers' needs. This systematic mapping literature review aims to provide an overview and a structured understanding of the consumer informatics designed for CMC and their caregivers. We followed a systematic mapping literature review process to provide an overview of the existing Consumer Informatics literature for CMC, which is the scope of our study. We screened IEEE Xplore, Web of Science, and PubMed databases using a preset list of mesh terms that cover the use of medical informatics by children with medical complexities and their caregivers. The selected articles are peer-reviewed English publications that were empirically validated from January 2002 to January 2022. After selecting and filtering the articles, we analyzed them based on the preset mapping questions using the following criteria: publication year, publication source, research type, contribution type, empirical type, the need addressed, target audience, technology users, and consumer informatics' type. The initial search resulted in a number of (N = 2,275) articles, and 17 selected publications were included. The results showed an increasing interest in CMC consumer informatics publications over time. Most of the studies were published in 2021, and feasibility research is the dominant research type. The most used technology was telehealth and telemedicine, followed by mobile health. The technologies addressed various needs, including; coordination & follow-up, medical safety, education & social support, daily living activities, shared decision making, information seeking, and emotional support. Most of the efforts were focused on ensuring good coordination and follow-up. CMC consumer informatics is a promising research field to present novel initiatives and approaches to manage the caregivers' workload. Future research should be shifted toward providing more evidence-based studies to examine the effectiveness of CMC consumer informatics solutions and identify the related challenges and limitations.