Increasingly, patients are engaged in managing their health via patient-facing interfaces such as smartphone apps.This increased use of digital health tools heralds a fundamental change in the patient experience.
Digitally supported self-management with the healthcare team getting involved only when needed improves outcomes at a lower healthcare cost, enabling the next generation of value-based arrangements (VBAs). This accelerated adoption by health policymakers and patients' willingness to try this treatment avenue of telehealth demonstrates the opportunity for using remote health tools and methods that facilitate patient engagement outside the clinic to improve patient outcomes. More
While there are limits to what can be done from a distance, the hope is that telehealth can address the social determinants of health, promote access to care for vulnerable and hard-to-reach populations, and boost caregivers' skills on the ground. For example, for doctors and volunteer organizations in Ukraine, telemedicine can be a bridge to ensure a secure and safe environment for the people they serve. Remote services reduce the risks posed by the physical barriers designed to delay access or prevent movement for both healthcare providers and patients. Telehealth also provides a mechanism to triage patients and relieve the strain on an already overburdened humanitarian response system where disasters emerge out of a context of chronic vulnerability. The evaluation suggests that as health services are expanded, protracted conflict highlights how telehealth, partly out of necessity to maintain continuity of care, ensures that refugees and internally displaced people in the acute phase of humanitarian emergencies are still able to access it matter their situation or location. Wartime conditions may also necessitate particular attention to government regulation, industry self-regulation, and technological solutions to avoid safety risks to providers and patients. Other challenges are multidomain environments in which each domain can use extra security, privacy, and trust requirements and potentially employ various mechanisms, interfaces, and semantic interoperability in the face of ontology development and maintenance, as well as on storage and automated reasoning and secondary trauma; exposure to the stigma, and physical and psychological violence of a society that is also afraid healthcare providers face, even if they provide care from a safer, remote location. Beyond the immediate response, the psychosocial aspects of these professionals in their workplaces will often face prolonged insurgencies, wars, border conflicts, or deepened human suffering in caring for people in and fleeing from war-torn Ukraine. They may need to make sustainable commitments. For example, the timely delivery of appropriate treatment is imperative following the acute crisis phase, should providers be prepared to continue offering services for free or risk an exploitative dependency arising when the relationship embodies an asymmetrical balance of power? Even if an agency has the technical, financial, and other resources to deliver specific components of care, is there a question of whether it is appropriate to do so? This study is an illustration of the broader ability to use remote health when health emergency preparedness, resilience, and response collide with healthcare capacity shortages, both created by the conflict, to predict disease progression in patients faster and engage patients earlier, improving the experience at an individual level and reducing medical cost at the population level. Taken together, it allows all stakeholders to capture value in VBAs. |
White Paper: Rapid Adoption of Telehealth Technologies Can Leave Patients and Data at Risk
High-quality results depend on integrating the different components constituting the blueprint for data collection, measurement, and analysis. Statistics cannot correct for a poor initial design, nor can they compensate for inadequate reporting of methods. Results from analyses can only provide valid inference on the level of intervention.
According to Jamieson & Bader (2016, p.172), in forensic science, “DNA testing requires analysts to use subjective judgments to resolve crucial ambiguities,” potentially influencing observer effects. Data analysis is often seen as the poltergeists of completing research (Emerging Research in Electronics, Computer Science and Technology, 2019), but it doesn’t have to be that way. Load More
While you’ll need to understand what to do with the data and how to interpret the results (Rhodes, 2018), software designed for statistical analysis can create variation-aware timing models that account for both systemic and random process variations which were not possible previously due to fixed parameters for the near-threshold regime (National Academies of Sciences, Engineering, and Medicine, 2019). R is a free statistical software package for statistical computing and graphics that can articulate the conceptualization of behavior and the complicated relationships among the sciences, culture, and policy (Holland, 2019). Recognized as one of the most powerful and flexible statistical software packages (Skiena, 2017), it enables the user to apply simple regression, perform data wrangling, hypothesis testing, or multivariate analysis of variance concentrating on graphical inspection. While it can simplify various aspects of data processing, it also has a steep learning curve, requiring a certain degree of coding. However, as it is an open-source programming language, it comes with advocates within larger technology organizations engaged in building and improving R and the associated plugins, ensuring accessibility support is never too far away As often happens, we are seduced by technique at the expense of content (Hemanth et al., 2019), and data comes to have the same value. This study delves into the intricacies of algorithm analysis, correlation coefficients, data structures, statistical probabilities, and data mining of programming in R that can suit various purposes and sectors as varied as health, education, tech, construction, healthcare, banking, finance, defense, agriculture, etc. References
Emerging Research in Electronics, Computer Science and Technology: Proceedings of International Conference, ICERECT 2018. (2019). Singapore: Springer Singapore. Hemanth, D. J., Shakya, S., & Baig, Z. (Eds.). (2019). Intelligent Data Communication Technologies and Internet of Things: ICICI 2019 (Vol. 38). Springer Nature. Holland, M. (2019). Understanding & Applying Basic Statistical Methods Using R. Scientific e-Resources. Jamieson, A., & Bader, S. (2016). A guide to forensic DNA profiling. National Academies of Sciences, Engineering, and Medicine. (2019). Reproducibility and replicability in science. Rhodes, R. A. (Ed.). (2018). Narrative policy analysis: cases in decentred policy. Springer. Skiena, S. S. (2017). The data science design manual. |
Computational Environment
Failure Mode and Effects AnalysisSince 1980 (Hoorelbeke, 2021), military standards (MIL-STD-1629) have recommended Failure Mode and Effects Analysis (FMEA) to mitigate product risks during the conceptual design phase by identifying design variables affecting product failures.
FMEA can be used in assessing and analyzing risk associated with implementing Enterprise Resource Planning (ERP), including design configuration. In parallel to the concept and process variances to shape tolerance analysis, content validity, according to Singh et al. (2020), is a prerequisite for selecting or applying an instrument. The strength and direction of that relationship depend on association measures, including correlation and regression analysis. Load More
In practice, FMEA is a methodological approach that relies on the subjective judgment of experts. In many cases, it isn't easy to replicate the analysis, making it a static model in cognitive science (Kiritsis et al., 2021).
Performing a distributed exploration and evidence gathering allows the elicitation of scientific and technical judgments from a team of expert analysts to capture the subjective and qualitative aspects of decision-making. The quality of the outcome depends on the analysts' ability to deduce the dependencies between components (Montgomery, 2020), which can reflect the system transiting into a failing state and how applications behave in the presence of faults. By proposing a framework for the use of systematic review, this article embodies the extent to which it helps infer the questions. Can the test under realistic conditions and sometimes involving competing products or systems meet the design specification and requirements, and, by extension, do the results accurately calculate the concrete outcome they are designed to measure? Reference
Hoorelbeke, P. (2021). Process Safety: An Engineering Discipline. Walter de Gruyter GmbH & Co KG. Kiritsis, D., Lazaro, O., Hodkiewicz, M., Lee, J., & Ni, J. (2021). Data-Driven Cognitive Manufacturing—Applications in Predictive Maintenance and Zero Defect Manufacturing. Frontiers in Computer Science, 2, 633850. Montgomery, D. C. (2020). Introduction to statistical quality control. John Wiley & Sons. Singh, J., Singh, H., & Singh, B. (2020). Prioritization of Failure Modes in Manufacturing Processes: A Fuzzy Logic-based Approach. Emerald Group Publishing. |
Failure Mode & Effects Analysis (FMEA) Guide
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