Weerapat Pipithruengkrai

[Weerapat Pipithruengkrai]

Question 1: How will you apply the results of this research article into different health care departments/settings or chronically ill patients, if this would be beneficial in your future practices e.g., Mental Health, Diabete, Oncology or others?

In my opinion, the results of this research on ePROs can significantly enhance the management of chronically ill patients such as allergic conditions. By providing continuous and detailed records of symptoms, triggers, and medication usage, ePROs allow for real-time monitoring and timely adjustments to treatment plans. This can help identify patterns and triggers that may not be evident during occasional clinic visits, leading to personalized and effective management strategies. Enhanced communication between patients and healthcare providers through ePROs ensures prompt attention to changes in the patient’s condition, which improves patient engagement and outcome. However, there’s a significant barrier in Thailand’s healthcare setting is the lack of awareness and availability of suitable software solutions, also by limited digital literacy among some patient groups. Addressing these barriers through targeted education and ensuring affordable, user-friendly ePRO platforms can eliminate any barriers and disadvantages, and finally improve the healthcare setting in handling allergy.

Question 2: What additional features or improvements would you suggest for ePRO systems to make them more effective and user-friendly for both patients and healthcare providers?

To make ePRO systems more effective and user-friendly, several enhancements could be considered. Firstly, integration with electronic health records (EHRs) can ensure seamless data transfer and accessibility for healthcare providers. Secondly, customizable interfaces that allow personalization according to specific health conditions or patient preferences can improve usability. Thirdly, multilingual support can cater to a diverse patient population. Additionally, implementing reminder notification systems for timely interventions. Finally, providing patient education resources within the ePRO system can enhance patient’s understanding and engagement in their own care. In my opinion, these improvements will make ePRO systems more accessible and beneficial for both patients and healthcare providers.

[Weerapat Pipithruengkrai]

1. How can integrating environmental data improve the accuracy and timeliness of malaria outbreak predictions compared to relying solely on epidemiological data?

In my opinion, integrating environmental data significantly improves the accuracy and timeliness of malaria outbreak predictions compared to relying solely on epidemiological data. Environmental factors, such as temperature, rainfall, and humidity, which influence the breeding and survival rates of mosquitoes. By integrating real-time environmental data, predictive models can anticipate changes in mosquito populations and potential outbreaks weeks or even months in advance. This approach allows for timely interventions, such as targeted spraying and distribution of bed nets, which reduce the incidence and impact of outbreaks.

2. What are the key benefits and challenges of involving public health stakeholders continuously throughout the development and implementation of a system like EPIDEMIA, and how can their feedback shape the system’s effectiveness?

In my view, involving public health stakeholders continuously in the development and implementation of systems like EPIDEMIA ensures the system meets practical needs and enhances its usability. Stakeholder feedback also leads to appropriate solutions, which improve data accuracy and report formats, as well as building trust for better adoption in routine operations. However, coordinating diverse input can be time-consuming and may lead to conflicting requirements and adjustments. Despite these challenges, continuous engagement is essential for refining the system and adapting it to changing circumstances, enhancing its overall effectiveness in malaria control efforts.

[Weerapat Pipithruengkrai]

1. Please discuss how you think the perceived ease of use and usefulness may differ among the different demographics.

In my opinion, based on Thai people’s digital literacy I experienced.
Age: Younger Thai people being more familiar with technology, typically find e-health applications easier to use and more beneficial, while older adults may struggle with these systems, perceiving them as challenging applications for use.
Gender: Thai women may prioritize user-friendly features and interfaces in technology that enhance their perception of ease and usefulness. In contrast, men might focus more on efficiency and technical aspects. However, I think that their gender is not the main factor in their adoption of the Personal Health Record System.
Education Level: Higher education correlates with greater digital literacy, making e-health systems appear more accessible and useful. Those with lower education levels might find these systems intimidating and less beneficial for them.

2. In your experience of using e-health applications or systems, what are some external factors or variables that should be considered to extend the proposed model for assessing the intention to use the system?

In my point of view, key technical factors on the intention to use the system include bugs and glitches, which can frustrate users and reduce trust in the system. System stability and reliability are crucial to prevent disruptions. Moreover, compatibility across devices is essential to ensure broad accessibility. Lastly, regular updates and maintenance are necessary to address technical issues and ensure data security, which is essential for protecting personal health information and maintaining user confidence.

[Weerapat Pipithruengkrai]

1. From the results, What would you recommend to Tak Hospital to improve the syphilis surveillance system?

In my opinion, Tak Hospital could significantly improve its syphilis surveillance system by focusing on a few key areas. Firstly, enhancing communication and cooperation between departments. This involves fostering better coordination between the blood bank, STI/HIV clinic, and antenatal care clinic to ensure comprehensive data collection and sharing. Secondly, ensuring accurate and complete diagnosis coding would improve the sensitivity of reporting, leading to more reliable surveillance data. By implementing data audits that involve all relevant units can help maintain data quality and identify areas for improvement. Lastly, investing in training for staff on the use of the surveillance system, which can help the system being used over time, ensure its sustainability.

2. Do you have experience with disease surveillance systems? What are the strengths and weaknesses of that system?

As I am currently in the team that currently developing new Event-based Surveillance (EBS) System, I have observed several strengths and weaknesses of the system. In my opinion, one of the primary strengths is its comprehensive data management capabilities, integrating multiple data points from various health organizations in Thailand like PHO, ODPC, and DDC, which helps centralize event data and reduce redundancy. Also, the system has a user-friendly interface, designed as a responsive web application compatible with mobile devices, making it accessible for users in different locations and roles. Additionally, the system’s real-time notification feature effectively informs relevant stakeholders, such as CEO, SME (Subject Matter Export), and JIT (Joint Investigation Team), about events, facilitating timely interventions and decision-making. The detailed event tracking provided through various modules, including event reporting and management, ensures thorough documentation and follow-up.
However, the system also has some weaknesses. Its extensive functionalities can be overwhelming for new users or those who are not proficient with IT, which requires thorough training to use the system effectively. Furthermore, effective use of the system requires seamless coordination between various departments, which can sometimes be hindered by bureaucratic delays or miscommunications. Overall, while the new EBS system that is currently being developed offers a robust framework for event surveillance, continuous improvements in user training and inter-departmental collaboration are essential to maximize its effectiveness.

[Weerapat Pipithruengkrai]

1. How can implementing artificial intelligence technologies in epidemic surveillance systems be enhanced to better detect and respond to disease outbreaks?

In my opinion, the implementation of AI in epidemic surveillance can be significantly enhanced by using advanced data analysis and applying Machine Learning (ML) techniques. As ML techniques can analyze vast amounts of information from various sources to detect early signs of disease outbreaks much faster than traditional methods. By using this diverse data, AI can make accurate predictions about how diseases will spread and how effective different interventions will be. This rapid identification and response capability, combined with overcoming issues such as trends and anomalies that could escape the attention of human healthcare professionals, makes AI a powerful tool to support and improve traditional epidemic surveillance systems.

2. What potential benefits do you see in utilizing AI for public preparedness, and what challenges might arise in implementing these technologies effectively?

In my opinion, utilizing AI for public preparedness offers numerous benefits, such as improving health security by generating early warnings and enabling rapid response, which can prevent outbreaks from becoming pandemics. As AI workload efficiency by automating data analysis, allowing public health officials to focus on critical interventions. Moreover, AI predictive capabilities can prioritize responses based on real-time data, and its tools can be made accessible to a wide range of users, and establish access to epidemic intelligence.
However, several challenges might arise in implementing AI effectively. As ensuring data quality and integration is crucial since AI systems depend on accurate and up-to-date information. Also, ethical concerns regarding the use of personal data must be addressed to comply with regulations. Furthermore, technical challenges, such as the need for substantial expertise and resources, can hinder the adoption of AI, especially in low-resource settings. Finally, there may be resistance to adopting AI technologies due to skepticism about their reliability compared to traditional methods. Addressing these challenges is essential for utilizing AI’s full potential in public health for epidemic early warning systems.

[Weerapat Pipithruengkrai]

1. What additional factors should be considered to identify barriers and unmet needs in health information seeking among youth for HIV/STI and RH than in the paper?

In my opinion, additional factors to consider include cultural and social norms that hinder open discussions about sexual health, gender dynamics that create different challenges for young men and women, and mental health issues like anxiety and depression that affect health-seeking behavior. Moreover, varieties in digital literacy and access can prevent the effective use of online health resources. Privacy concerns are also crucial, as fear of shame can prevent youth from seeking information. Addressing these factors through culturally sensitive, gender-specific, and privacy-assured approaches can improve health information access and utilization.

2. Which types of vulnerable people in your community are missing or left behind in receiving necessary health information, and why? How can we best reach these individuals and measure the real impact of health information on their health-seeking behaviors to ensure its effectiveness?

In my opinion, in Thailand, vulnerable groups often left behind in receiving necessary health information include youth from impoverished rural areas, migrant workers, and those living in slums. These individuals often face barriers such as poor educational backgrounds and unstable social environments, which limit their access to health information. To reach these groups, the government should leverage mobile health units and community outreach programs to provide education and services directly in their communities. Engaging locals and providing information in multiple languages can help overcome educational and cultural barriers. Additionally, utilizing social media by using advertisements can disseminate health information effectively. Measuring impact through community feedback and health outcome tracking ensures these strategies are effective and can be adjusted to better serve these populations.

[Weerapat Pipithruengkrai]

1. How can the decision tree model be integrated into clinical practice to assist surgeons in preoperative planning and decision-making?

In my opinion, integrating a decision tree model into clinical practice can significantly enhance preoperative planning for surgeons. By including the decision tree model into a clinical decision support system (CDSS) in electronic health records (EHR), as it can provide real-time risk assessments based on comprehensive preoperative data. This approach allows for personalized patient care, where patient’s conditions can be identified early, enabling surgeons and healthcare staffs to arrange for preoperative planning and preventive measures more conveniently and effectively. I believe that with the right implementation and training, this integration could lead to better patient outcomes and more efficient use of healthcare resources.

2. What are the potential benefits and limitations of using this model in a real-world clinical setting?

In my view, the decision tree model offers several potential benefits in clinical settings, such as improved prediction accuracy for massive intraoperative blood loss (IBL), which allows for better preparation and resource allocation. It enhances the decision-making process by providing evidence-based data. However, there are limitations to consider, as the model’s accuracy highly depends on high-quality input data, and integrating it with the current clinical setting can be challenging. Additionally, the risk of overfitting and the need for regular updates to the model are the things that need to be considered. I think that while the model can greatly aid surgeons and healthcare staff, its complexity requires proper training and continuous refinement to the model to ensure its practical utility in real-world settings.

[Weerapat Pipithruengkrai]

1. Is there any similar electronic-based clinical decision support system which has been developed or planned to be developed for NCD patients in remote area of your country? Please share your experience about advantages and disadvantages of the tool.

In Thailand, various electronic-based clinical decision support systems (CDSS) that support non-communicable diseases (NCD) have been developed and deployed. These systems typically involve features that mainly facilitate healthcare workers in managing patient data and basic data visualization. The primary advantage of these systems is the simplified healthcare work and data management process in remote areas where manpower and support are limited. However, these systems also face challenges, including technical issues such as internet connection, training for healthcare workers, and concerns about data security.

2. Do you think that nurse or community health worker facilitated NCD management tool is the best option to compensate the shortage of healthcare workers in managing NCDs in the remote area? Are there any alternative options to address insufficient healthcare workers and promote the quality of care to NCD patients?

In my opinion, clinical decision support systems (CDSS) are effective in addressing the shortage of healthcare workers in remote areas of Thailand. These tools enable nurses and healthcare staff to manage NCD cases, reducing the reliance on doctors and improving care access. However, training is required for healthcare staff to use these CDSS tools effectively. Additionally, alternatives like telemedicine for remote consultation can also help address manpower shortages and enhance care quality for NCD patients in remote areas.

[Weerapat Pipithruengkrai]

1. Besides medical algorithmic audits, are there some additional ways to improve the safety of medical AI systems?

In my opinion, applying human-in-the-loop concept in medical AI systems can significantly enhance patient safety, by ensuring AI outputs are continuously reviewed and verified by medical professionals. This approach can help in identifying errors and providing an additional layer of safety, making AI more reliable for facilitating healthcare work. Moreover, applying robust data collection and preprocessing can also ensure the quality and representativeness of the data used, reducing biases and inaccuracies that could lead to incorrect AI predictions and results.

2. Please name some key/ideal characteristics that medical AI systems can build trust and confidence in the medical community (for example; in terms of safety, quality, efficacy,…)

In order to build trust and confidence in the medical community, medical AI systems must prioritize accuracy and reliability, by demonstrating high accuracy in diagnosis and predictions consistently across different clinical settings and populations. Furthermore, explainability is also crucial, as clear and understandable clarification of AI decision-making processes helps healthcare providers trust and use these AI effectively. Lastly, ensuring ethical considerations by complying with healthcare regulations in the design and deployment process further enhances trust among the healthcare community.

[Weerapat Pipithruengkrai]

My dashboard contains 4 pages which are:

Main Dashboard
The main dashboard provides a comprehensive overview of COVID-19 data from January 2020 to April 2022 for six countries: Brazil, Egypt, Germany, Japan, Mexico, and Thailand. It includes scorecards displaying total confirmed cases, recoveries, and deaths, along with a filled map for visual geographic insights. Time-series charts effectively illustrate trends over the years. Users can easily filter data by year, month, and country using dropdown lists, enhancing the exploration of specific details. Action buttons such as reset, download, and share facilitate user interaction and accessibility. Additionally, navigation buttons lead users to detailed pages on confirmed cases, recoveries, and deaths, enabling deeper insights and comparisons of COVID-19 data across different years and countries. I also ensure that the color schemes are accessible to color-blind users, enhancing the overall user experience of the dashboard.

Confirmed Cases Details
This page focuses on confirmed COVID-19 cases, breaking down data by year and country. Users can view both total cases and maximum daily cases, presented through a comparative pivot table and time-series line chart. These visualizations allow users to quickly grasp trends and effectively compare data across various periods.

Recovered Details
The recovered details page highlights recovery rates, showcasing total recoveries and maximum daily recoveries by year and country by pivot table. Moreover, time-series charts make it easy to monitor recovery trends over time, helping users analyze the recovery rates in different regions.

Deaths Details
This page provides a detailed examination of total deaths and maximum daily deaths from COVID-19. Users can filter and compare data by country and year using the dropdown lists. Visualizations, including pivot table and time-series line chart, help users understand the pandemic’s impact over time.

Looker dashboard link: https://lookerstudio.google.com/s/mNWHK3u3dmc

Any comments and suggestions are welcome, thank you.

[Weerapat Pipithruengkrai]

1. Considering the model’s performance, what additional data or features do you think could further improve the accuracy of predicting PIH?

From my perspective, including a patient’s detailed medication history in the model can significantly improve the prediction of low blood pressure during anesthesia. Medications like antihypertensives, beta-blockers, and other drugs for heart conditions can affect how a patient’s blood pressure responds during surgery. This additional information helps create a more accurate prediction model, allowing for better preparation and management of anesthesia to prevent complications.

2. What future research directions would you suggest to address the limitations of this study and enhance the predictive model’s applicability across various surgical procedures?

In my opinion, to make the predictive model more reliable and applicable to a wider range of patients, it is necessary to include larger groups of patients in the study. Moreover, tracking patients for a longer period after surgery can provide insights into the long-term effects of low blood pressure during anesthesia. This extended follow-up can improve the model by identifying factors that impact recovery and other outcomes.

[Weerapat Pipithruengkrai]

1. What are the stakeholders that should be involved in applying Machine Learning in symptom prediction? What are their roles and responsibilities?

In my opinion, there are several key stakeholders who must be involved in using machine learning to predict symptoms in cancer patients.
– Data scientists and machine learning engineers are crucial for developing the models as well as analyzing large data sets to identify patterns and forecast symptoms.
– Healthcare professionals are necessary to provide necessary medical data, ensure clinical relevance, and validate the models.
– Patients are essential for providing data, experiences, and feedback on the model.
– Policymakers are the key to the integration process of these technologies into healthcare systems, enforcing regulatory compliance such as HIPAA.

2. What potential ethical considerations or challenges should researchers and clinicians keep in mind when developing and deploying machine learning models to predict cancer symptoms?

I think that patient privacy is a major concern, requiring data to be anonymized and securely stored to protect confidentiality. Moreover, informed consent must be addressed, ensuring patients understand how their data will be used and the potential benefits and risks. Additionally, clear communication about the model’s limitations is necessary to prevent over-reliance on the prediction result.

[Weerapat Pipithruengkrai]

Hi all, this is my visuals for this week topics.

My Looker studio link: https://lookerstudio.google.com/reporting/104341b2-1595-4b57-a37f-64858d8ada59/page/yKx3D

[Weerapat Pipithruengkrai]

I would like to introduce the COVID-19 Tableau Dashboard from Thailand’s Department of Disease Control (DDC). (https://ddc.moph.go.th/covid19-dashboard)

This dashboard provides comprehensive data on COVID-19 cases such as new cases, deaths by age or sex, pneumonia, and intubated patients. It features interactive elements that allow users to filter data by region, province, and timeframe. The dashboard presents information through various visualizations such as line charts, bar charts, and maps. Moreover, the color of the charts makes it easy to identify severity in each region and province. Overall, these features make the data more accessible and understandable.

However, the dashboard has some drawbacks. The navigation can be complex, with multiple sections and tabs that may confuse new users or those who are not proficient with web applications. Additionally, the line chart is difficult to understand as it doesn’t have any labels. Lastly, the language of the dashboard is Thai, which limits its accessibility to non-Thai.

In conclusion, the COVID-19 Interactive Dashboard by DDC is a detailed tool for tracking the COVID-19 pandemic in Thailand. While it can provide comprehensive and regularly updated data, improvements in user experience and accessibility could enhance its usability for a broader audience.

[Weerapat Pipithruengkrai]

This is my infographic for this week

[Weerapat Pipithruengkrai]

This is my infographic for this week.

[Weerapat Pipithruengkrai]

This is my summary of this week’s contents.

[Weerapat Pipithruengkrai]

Hi everyone, this is my infographic on summary of this week’s topic.

[Weerapat Pipithruengkrai]

The point that I will select for the discussion will be Point 3: “A significant test result (P value <= 0.05) means that the test hypothesis is false or should be rejected” from page 341.

This point clarifies that just because a study shows a significant result (small P value), it doesn’t mean that the test hypothesis is wrong and should be dismissed. Instead, it can be suggested that the observed data is unusual if all the assumptions used in the statistical test were correct.

While a result is significant and can indicate the potential effect, it doesn’t provide conclusive evidence. The P value is just a single aspect of data that must be analyzed alongside additional details before concluding the test hypothesis. The significant result could have been caused by a variety of factors such as random chance, errors in the study design, or biases that may cause discrepancies in the data.

Reference: Greenland S, Senn SJ, Rothman KJ, Carlin JB, Poole C, Goodman SN, Altman DG. Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. Eur J Epidemiol. 2016 Apr;31(4):337-50. doi: 10.1007/s10654-016-0149-3. Epub 2016 May 21. PMID: 27209009; PMCID: PMC4877414.

[Weerapat Pipithruengkrai]

Hello, my name is Weerapat Pipithruengkrai. You can call me “Poom”. I currently work as a research assistant and project coordinator at the Hospital for Tropical Diseases. I have some experience in statistics topics by collecting qualitative data from various surveys during my academic years and utilizing software such as Excel and Tableau.

I learned statistics for computing during my bachelor’s degree study at the Faculty of ICT, Mahidol University, and applied it to some of the IT projects that required basic statistical features such as finding the median and mean. However, my knowledge of statistics is on an elementary level. As a result, I would like to understand more about the statistics topic from this course.

[Weerapat Pipithruengkrai]

Age: 24
Sex: Male
Education: Bachelor’s in Computer Science
Occupation: Research Assistant
Workplace: BIOPHICS, Faculty of Tropical Medicine
Location: Bangkok

[Weerapat Pipithruengkrai]

In my opinion, I would like to suggest qualitative and experimental research approaches to identify why they did not prefer to use bednets for malaria prevention.

Qualitative research
Qualitative research would aim to understand the underlying reasons and motivations behind respondents’ refusal to use bednets. Researchers can gain insight into participant’s points of view, beliefs, and experiences with bednet use by engaging in open-ended discussions. This methodology allows an in-depth investigation of attitudes, cultural variables, and environmental factors that quantitative methods may fail to capture.
Researchers can conduct in-depth interviews or organize focus group discussions with people who didn’t use bednets. Participants would be encouraged to share their ideas, concerns, and experiences with bednet non-usage via open-ended questions and probes.

Experimental research
Researchers can use experimental research to find causal associations between factors. As controlled experiments let researchers adjust specific factors and assess their impact on participants’ behavior or attitudes toward bednet use. This approach enables the isolation of specific variables that may impact bednet non-usage, providing insights into underlying respondent’s opinions.
Researchers may organize randomized controlled trials (RCTs) or quasi-experimental studies. Which participants would be randomly assigned to various experimental scenarios involving treatments or manipulations targeted to increasing bednet usage.

[Weerapat Pipithruengkrai]

The Technology Acceptance Model (TAM) defines perceived usefulness as the degree to which a user believes the technology will enhance their productivity, which impacts their intention to use it. Therefore, if the new technology offers more benefits than the old one, users are more likely to adopt it.

Furthermore, TAM also emphasizes the role of perceived ease of use. If the new technology is more simpler and accessible than the old one, people might perceive it as more useful even if its objective functionality remains the same. This is because the reduced effort and learning curve results in a perceived increase in efficiency and output.

In conclusion, TAM emphasizes that both perceived ease of use and perceived usefulness are essential for technology adoption. While a newer, simpler technology may be seen as more beneficial despite having identical abilities, demonstrating clear and objective improvements in utility and practicality remains crucial for driving user acceptance and improving the adoption of the new technology.

[Weerapat Pipithruengkrai]

There are several external variables that influence an individual’s perceived ease of use or perceived usefulness of a new technology in my opinion.

Hype and Reputation: If everyone’s using a new technology, people might think it would be nice for them to try one, even if it’s not that great for their needs. However, if a tech has bad reviews, people might avoid it even if it’s been improved. It is similar to the case of judging a restaurant based on online reviews before even trying it.

Personal experiences: User’s past experiences with similar technologies can affect their perceptions of ease of use and usefulness. For example, if people had bad experiences with similar technologies in the past, they might be more hesitant to try something new, even if it’s different.

Accessibility and Design: If a technology isn’t designed to support every type of user it can be frustrating and difficult to use for people that not proficient in IT or those who have disabilities, which can impact perceived ease of use and usefulness.

Cost: The cost associated with using the technology can influence perceptions. As high cost may cause people to hesitate to utilize it, fearing wasted money. On the other hand, if a technology is affordable, people are more likely to invest time in understanding it on what it offers.

[Weerapat Pipithruengkrai]

Efficacy:
Definition: Efficacy is a measurement of how effectively a treatment performs in an ideal or controlled setting.
Context: Efficacy is frequently assessed via clinical trials or experimental studies in controlled environments, where researchers would closely monitor and adjust parameters to isolate the effects of the intervention. The purpose is to see if the intervention has the expected effect under ideal circumstances.
Design: Often uses randomized controlled trials (RCTs) with control groups and standardized procedures.

Effectiveness:
Definition: Effectiveness is a measurement of an intervention’s ability to achieve its desired effect in real-world or everyday situations. It evaluates the intervention’s effectiveness in the larger population, considering various factors such as patient diversity, real-world compliance, as well as innovations in healthcare service.
Context: Unlike efficacy, effectiveness is assessed in a broader and less controlled context, often reflecting the obstacles and differences experienced in typical healthcare settings. It provides insight into the intervention’s effectiveness when applied to a larger and more representative group of people.
Design: Often uses observational studies or pragmatic trials

Efficiency:
Definition: Efficiency is a measurement of an intervention’s capability to achieve the objectives with a limited amount of resources, time, or cost.
Context: Efficiency assesses not just the effectiveness of an intervention, but also its economic and resource aspects. An efficient intervention optimizes benefits while limiting resource use, making it cost-effective and practicable for broader utilization.
Design: Involve economic evaluations or cost-benefit analyses comparing resource use and outcomes

[Weerapat Pipithruengkrai]

As an IT developer working in a hospital, there are various ethical standards and practices that must be followed to contribute to COVID-19 control policies.

Firstly, patient data privacy and confidentiality must be protected. This includes complying with data protection rules such as HIPAA (Health Insurance Portability and Accountability Act) to protect sensitive medical information. Utilizing strong encryption techniques, access controls, and regular security audits can help minimize the risk of data breaches and create confidence between patients and healthcare providers.

Secondly, transparency and accuracy in the development and implementation of COVID-19 control technologies are essential. This includes providing clear documentation as well as communication channels to ensure that users understand the purpose, functionality, and potential risks of IT systems. Moreover, collaborating closely with healthcare professionals to understand their requirements and concerns ensures that technological interventions are consistent with clinical best practices and ethical norms, which improves the effectiveness and acceptability of control policies.

Finally, enhancing equity and accessibility in the use of IT systems for COVID-19 management is also crucial. Designing user-friendly interfaces and offering multilingual support promotes equal access to information and services for diverse patient populations.

[Weerapat Pipithruengkrai]

From my perspective, Thailand’s Universal Health Coverage (UHC) scheme has made notable successes in assuring citizens access to healthcare services, as seen during the COVID-19 epidemic. The country’s effort to UHC, which includes accessibility, availability, and service quality, has effectively prepared it for handling health issues such as COVID-19. The UHC scheme’s comprehensive coverage, robust public health infrastructure, and efficient supply chain have allowed Thailand to manage healthcare services during the pandemic effectively. However, like any system, it has strengths, weaknesses, and challenges to overcome.

Strengths
Accessibility: The UHC scheme provides a wide range of healthcare services, making them available to most of the population. This has resulted in a decrease in healthcare costs for many people in Thailand.
Equity: The scheme seeks to decrease inequality in healthcare access by providing equal benefits to all people, regardless of income or socioeconomic status.
Public participation: The development of the UHC benefit program requires public involvement, ensuring that people’s needs are fulfilled.
Innovation: The NHSO has implemented innovative solutions such as telemedicine and medication delivery to improve access to care.

Weaknesses
Financial sustainability: The scheme’s expenses are increasing due to an aging population, rising costs for pharmaceuticals, and the integration of healthcare personnel into the public service system.
Workforce challenges: The need to regularly upskill and create healthcare workers to adapt to emerging challenges and provide adequate services for all people.

Future challenges
Emerging diseases and global health threats: The COVID-19 pandemic highlighted the need for preparedness and adaptability to address future health challenges. The UHC scheme needs to be flexible enough to respond to emerging diseases and global health threats.
Aging population: Thailand’s aging population will increase the burden on the healthcare system. The UHC scheme must adapt to accommodate the particular requirements of older people, such as chronic disease management and long-term care.

Overall, Thailand’s UHC system has achieved tremendous progress toward the objective of universal healthcare access and equity. However, additional efforts are required to address financial sustainability, workforce development, and emerging challenges to ensure the scheme’s long-term viability.

[Weerapat Pipithruengkrai]

In my opinion, Thailand’s health informatics workforce is currently in the developing phase. While not yet that popular, it’s continuously developing. As initiatives such as universities have driven the need for skilled professionals, which offers health informatics programs and research centers for fostering knowledge and collaboration. However, the workforce remains relatively small compared to other healthcare professions, as many roles are filled by those with IT skills rather than specialized training.

As far as I am concerned, one major challenge in the workforce is a limited pool of individuals with relevant academic qualifications. Since there are diverse academic programs and varying levels of difficulties on health and IT topics it is challenging to create a specialized workforce such as health informaticians. Additionally, the rapid evolution of health technologies requires continuous upskilling, which the current education system struggles to provide. Furthermore, attractive salaries and career prospects in other IT sectors attract the workforce away from healthcare, impacting an already limited number.

Overcoming these challenges requires various approaches. Firstly, establishing standards for health informatics education and certification would ensure a level of competency and facilitate career development. Secondly, developing collaboration between universities, healthcare institutions, or even health IT companies. By creating courses and practical internship opportunities. Continuous Health IT skill development programs are also essential to keep pace with technological advancements. Finally, promoting the unique value proposition of a career in health informatics, highlighting its impact on patient care and public health as well as offering attractive salaries and career prospects, could attract and retain the workforce.

[Weerapat Pipithruengkrai]

If entrusted with a dataset such as healthcare data, my approach to data sharing will focus on potential benefits and safeguarding patient privacy.

Firstly, sharing healthcare data can bring various benefits to healthcare organizations. I think collaboration and sharing among healthcare organizations can facilitate medical processes such as inform event-based surveillance and advance public health initiatives. The insights from shared data can lead to a better understanding of diseases, more effective treatment strategies, and improved health outcomes.

Secondly, safeguarding patient privacy is essential in the data-sharing process. Ensuring that sensitive patient information remains confidential is crucial for maintaining trust and following ethical guidelines. Utilizing data anonymization techniques such as de-identification to strip the data of identifiable information while retaining its utility for research purposes. This approach not only mitigates the risk of privacy breaches but also addresses concerns related to data misuse.

In conclusion, a balanced approach to healthcare data sharing involves careful consideration of the potential benefits of collaboration and the necessity to ensure privacy. Integrating data sharing with anonymization techniques can promote a collaborative research environment while maintaining ethical and legal standards for patient trust and data protection. I think this approach can improve healthcare knowledge and services while respecting the privacy and confidentiality of individuals contributing to the data set.

[Weerapat Pipithruengkrai]

In this topic, I assume “Digital literacy and awareness” can be a confounder as it’s associated with both “Age” and “Contact pattern”, but it is not a direct step between them. Younger adults are more likely to adopt and actively use the app than older generations because of their access to technologies and societal trends. As a result, their “Digital literacy and awareness” could lead to higher participation rates of contacts among younger individuals.

[Weerapat Pipithruengkrai]

As I worked in a Thailand public hospital, they began to phase out traditional paper-based medical records in favor of EMR. These are the list overview of the pros and cons of EMR that I experienced.

Pros
-Enhanced efficiency: The EMR can save time and resources for healthcare staff by reducing the need for paperwork and administrative tasks. Moreover, EMR can facilitate on data collection process and improve data standardization.
-Improve patient care: EMR can speed up healthcare workflow and minimize medication errors. Furthermore, EMR can be used for sharing patient data across departments and hospitals to ensure effective care coordination and referral.
-Promote transparency: Improves accountability and allows the patient to access their medical records. This transparency is essential for building trust between public hospitals and patients.
-Benefits for public health: EMR data can be used for tracking outbreaks as well as improving public health intervention. The data collection and analysis of EMR can assist public health to respond to health challenges effectively.

Cons
-Cost: Implementing and maintaining an EMR system requires significant investment that needs to be considered, especially in public hospitals with limited budgets.
-Infrastructure: Adequate IT infrastructure such as secured databases and stable internet connection required to utilize EMR effectively as well as protect sensitive data from data breaches.
-User training: Training on EMR usage on healthcare staff and instructions for patients are required to ensure effective implementation, user adoption, and minimizing disruptions in daily healthcare operations.
-Technical issues: EMR systems can face technical issues or downtime, potentially disrupting healthcare operations and affecting patient care.

[Weerapat Pipithruengkrai]

Based on the challenges that are specified in big data in cardiovascular disease, here are my suggestions for coping with each challenge that can be applied to other healthcare topics as well.

Missing Data
-Improve data collection process: Implement clear guidelines for data collection to minimize missing data and ensure data consistency in the big data.
-Using data imputation method: Using imputation techniques such as mean/median or regression imputation to replace missing data with substitute values to retain most of the information in the big data.

Selection Bias
-Validation on Randomized Controlled Trials (RCT): Conduct additional studies on RCT to validate information from big data analysis.

Data Analysis and Training
-Improve collaboration between clinicians and data scientists: Enhance the knowledge by training and collaboration between multidisciplinary that can integrate healthcare expertise with IT technical skills for optimal analysis and data interpretation.
-User-friendly tools: Invest and create a user-friendly interface and visualization that can make complex data more accessible for those who are not proficient in technical topics.

Interpretation and Translational Applicability of Results
-Focus on outcome results: Prioritize analysis that focuses on patient care and treatment decisions on specific topics to ensure relevant results.
-Using decision support tools: Decision support tools can visualize results and insights from big data that can be integrated into healthcare workflow to support the patient care process.

Privacy and Ethical Issues
-Strong security measure: Utilize robust encryption methods, access control, and data audit to protect sensitive data from unauthorized access and data breaches.
-Informed consent: Obtained consent from the patient before using their data for research and analysis.
Data anonymization Using anonymization techniques to protect individual privacy by anonymizing their personal information.

[Weerapat Pipithruengkrai]

Case-Fatality Rate:
Definition: Percentage of people who die from the specific disease among those diagnosed with the disease.
Calculation: Case-Fatality Rate = (No. of deaths from the disease / No. of diagnosed cases) x 100%
Usefulness: Case-Fatality Rate are used for measuring the severity of a disease, evaluates the effectiveness of treatment, and identifies high-risk groups.

Mortality Rate:
Definition: No. of deaths in a population during a specific period such as per year.
Calculation: Mortality Rate = (No. of deaths / Total population) x 1,000 (or 100,000)
Usefulness: Tracks overall population health, identifies causes of death, and plans public health interventions.

Age-Specific Mortality Rate:
Definition: Age-Specific Mortality Rate is the mortality rate in a specified age group in the population.
Calculation: Age-Specific Mortality Rate = (No.deaths in age group / Total population in age group) x 1,000 (or 100,000)
Usefulness: Identifies age groups with the highest mortality risk, understands causes of death by age, and informs targeted interventions.

Maternal Mortality Rate:
Definition: No. of deaths from pregnancy-related causes per 100,000 live births.
Calculation: Maternal Mortality Rate = (No. of maternal deaths / No. of live births) x 100,000
Usefulness: Monitors maternal health, assesses healthcare quality for pregnant women, and identifies areas that need improvement.

Infant Mortality Rate:
Definition: No. of deaths in children under 1 year old per 1,000 live births.
Calculation: Infant Mortality Rate = (No. of infant deaths / No. of live births) x 1,000
Usefulness: Measures overall child health and well-being, identifies causes of infant mortality, and facilitates in improving child health outcomes.

Neonatal Mortality Rate:
Definition: No. of deaths in children under 28 days old per 1,000 live births.
Calculation: Neonatal Mortality Rate = (No. of neonatal deaths / No. of live births) x 1,000
Usefulness: Identifies specific risks and causes of early infant mortality, informs and plans interventions on targeting newborn care, and contributes to improving neonatal health outcomes.

[Weerapat Pipithruengkrai]

I would like to discuss how I agree with all of those four recommended points that public health professionals can do to fight corruption according to the article.

-Convene key stakeholders in the health system to seek agreement on the scale and nature of corruption:
I agree that this collaborative approach will be key to building a comprehensive understanding and finding solutions for addressing the issue. As everyone can share their perspectives and bridge the gap towards common ground.
-Prioritize action:
I agree that prioritizing actions is crucial, and decisions should based on their potential impact on the health system and vulnerable groups. Moreover, considering feasibility ensures successful interventions against corruption.
-Take a holistic view:
I agree that a holistic view is necessary to understand corruption in the health sector. Also, multidisciplinary responses can provide a more comprehensive understanding and effective solutions.
-Establishing research on “Why”:
I agree that developing a research program to identify causes is essential for a deeper understanding of corruption in the health sector. Leveraging diverse disciplines in research can ensure a comprehensive approach to studying corruption, allowing for more effective interventions.

Furthermore, aside from those four points, I would like to share some suggestions on fighting corruption.
-Transparency and accountability:
Implement mechanisms for public audit and access to information about healthcare budgets, procurement processes, and performance indicators. This can promote ethical behavior and empower the public to hold authorities accountable.
-Strengthen whistleblower protections:
Ensure legal and practical safeguards for individuals who report corruption. This would encourage more disclosures and discourage retaliation to those who reported.
-Invest in anti-corruption education:
Raise awareness among health professionals and the public about the forms, consequences, and methods to combat corruption in healthcare.

[Weerapat Pipithruengkrai]

I would like to discuss health system improvement, particularly IT topics by implementing an Agile methodology on a Health IT project. From my experience, sometimes Thailand’s health IT landscape is affected by a lack of a centralized and cohesive strategy for initiating and managing health IT projects. This can hinder resource allocation, knowledge sharing, and overall progress in developing projects for healthcare improvement.

Implementing an Agile methodology on a Health IT project can provide answers to five broad elements of health system:
-Improved Service Provision: Agile methods allow for rapid iteration and adaptation of health IT solutions based on real-world feedback, ensuring they effectively address evolving needs.
-Enhanced Financing: Prioritization of initiatives based on their value and feasibility within Agile sprints optimizes resource utilization and maximizes return on investment.
-Increased Resource Generation: Successful implementation of effective health IT solutions can lead to cost savings and improved healthcare outcomes, freeing up resources for further development.
-Effective Leadership/Governance: Agile governance structures foster transparency, accountability, and responsiveness to stakeholders, ensuring strong direction for the health system strategy.
-Reduced Risk Factors on Social: Agile approaches allow for rapid adaptation to address emerging public health challenges.

These are Agile solutions that can be applied to Health IT projects:
-Define goals and priorities: Establish a clear vision for the health IT strategy that can be aligned with the five broad elements of the healthcare system.
-Break down goals into smaller and achievable: Focus on specific projects with deliverables within defined timeframes, allowing for iterative progress and adaptation.
-Establish teams: Form teams comprising IT specialists, clinicians, policymakers, and public representatives to ensure diverse perspectives.
-Gather feedback: Regularly gather feedback from stakeholders and users, adapting projects and priorities based on real-world insights.
-Promote collaboration: Share progress, challenges, and adaptations openly with stakeholders to promote engagement.

Aside from the benefits of this methodology, there are possible barriers that can occur in the process.
-Change management: Shifting to Agile methodologies may require overcoming resistance from stakeholders that are familiar to traditional project management approaches.
-Lack of Agile expertise: Building capacity and training personnel on Agile principles and practices require dedicated resources and effort.
-Data integration challenges: Existing IT systems might not be readily compatible with new solutions, requiring integration efforts and standardization.
-Sustainability: Maintaining the iterative and adaptable nature of Agile over extended periods can be challenging if proper structures are not in place.
-Measuring success: Traditional health IT metrics may not be suitable for evaluating the success of Agile projects, requiring the development of new evaluation frameworks.

However, these barriers can be addressed as below:
-Comprehensive training: Invest in training for all stakeholders involved in the national health IT roadmap on Agile principles and practices.
-Standardization and interoperability: Promote data standards and modularity in health IT solutions to facilitate easier integration and adaptation.
-Developing Agile-specific metrics: Define metrics that capture the iterative nature of Agile projects and assess their impact on health outcomes, service delivery, and cost-effectiveness.

[Weerapat Pipithruengkrai]

These are my ideas on applying the 12 steps of Project Management to an Event-Based Surveillance Web Application project:

1. Define the project clearly:
Target audience: Medical staff and authorities.
-Goals: Enhance the event notification process, optimize resource allocation for facilities, and facilitate early detection of critical events.
-Integration: Connection with the existing authentication system and workflow.

2. List all tasks:
-User interface (UI) design and development: Design an intuitive and user-friendly interface.
-Backend development and API integration: Develop the backend infrastructure and APIs to connect with the map system.
-Data security and encryption: Implement robust data security measures and encryption protocols to protect patient privacy.
-Testing and quality assurance (QA): Conduct thorough testing of all functionalities and identify bugs or usability issues.
-System deployment and ongoing maintenance: Plan for deployment to the environment and establish a maintenance plan for continuous updates and support.

3. Get tasks into the right order:
-Prioritize core functionalities: Focus on inputting and notifying new event information.
-Phase deployment: Consider launching features in phases, starting with core functionalities and adding others later based on user feedback and adoption.
-Allocate time for user feedback: Dedicate time for gathering user feedback during development and improve the web application.

4. Add a safety margin:
-Buffer time for development: Account for potential delays in UI design iterations and system development.
-Plans for data security: Prepare for potential data breaches and have robust mitigation strategies in place.

5. Crash the project plan (if necessary):
-Phased deployment with limited features: Launch the web application with a limited set of core features initially and expand gradually based on user feedback and resource availability.

6. Create a Gantt chart:
-Visually map out all tasks, their dependencies, and estimated timelines.
-Track progress and adjust the plan as needed.

7. Look at resources:
-Assess IT staff: Evaluate the capabilities and availability of the IT team for web development.
-External partnerships: Consider collaborating with IT vendors for specific modules or expertise.
-Funding and approvals: Obtain necessary funding and approvals from hospital administration for project development and ongoing maintenance.

8. Think about what might go wrong:
-Data security breaches: Plan for potential data breaches and implement robust security protocols, data encryption, and backup systems.
-User adoption challenges: Address concerns about user technology proficiency, and provide adequate support mechanisms for user adoption.
-Technical issues: Anticipate potential technical problems and have plans for system downtime and data recovery.

9. Monitor progress:
-Track task completion, resource utilization, and user feedback regularly.
-Monitor system performance and address any technical issues promptly.

10. Monitor cost (time and resources):
-Track actual time spent on tasks and resource allocation against the plan.
-Identify areas where adjustments are needed to stay within budget and timeline.

11. Readjust plan:
-Be flexible and adapt the plan based on progress and user feedback.
-Prioritize tasks and adjust timelines to ensure core functionalities are delivered.

12. Project review:
-Evaluate the project’s success against its goals and objectives.
-Identify lessons learned and areas for improvement for future projects.
-Document the project experience and disseminate best practices.

[Weerapat Pipithruengkrai]

As sometimes I need to be a leader on an IT project, I motivate my team by discussing project requirements to encourage ideas about what we can do. I try to make team members comfortable with their work by assigning tasks based on their strengths as well as providing support if needed. In my opinion, considering teammates can create a positive work environment that improves productiveness, engagement, and commitment to achieving the project’s objectives. Additionally, I’d find new methods to facilitate the software development process and share with my teammates to improve productivity as well as morale while working on the project.

[Weerapat Pipithruengkrai]

In my opinion, developing a disaster recovery plan for a public hospital requires specific considerations due to the potential impact of disruptions on healthcare facilities. Here are several procedures and technologies that can support in development of a disaster recovery plan.

1. Risk assessment procedures
-Define possible disaster scenarios such as natural disasters, cyberattacks, power outages, and equipment failures.
-Establish a monitoring system to detect and report potential incidents in real-time.
-Conduct regular risk assessments to identify vulnerabilities and potential threats to the information system.
-Define acceptable downtime and data loss based on the criticality of data and processes (RTO and RPO)

2. Recovery Plan procedures
-Utilize a combination of backup and replication technologies to ensure rapid and reliable data recovery.
-Implement a failover system to minimize downtime for critical systems.
-Test and validate recovery procedures regularly to ensure their effectiveness.
-Using a communication plan to inform patients and staff about the incident and the expected recovery timeline.

3. Technology
-Cloud-based backup and replication: These services offer a cost-effective and scalable solution for hospitals of -all sizes, with minimal on-premise infrastructure requirements.
-Virtualization technology: Enables rapid server provisioning and failover to minimize downtime.

[Weerapat Pipithruengkrai]

The listening skill that I particularly like to improve upon is my ability to recall details, as I sometimes find myself struggling to recall specific information, especially if it’s not something that I’m particularly passionate about. This can be quite frustrating, as it hinders my ability to effectively communicate such as provide answers and advice for those in need.
As a result, I would like to address this issue by improving my conscious effort to actively engage with the details such as asking questions, seeking clarifications, and adapting the topic to my existing knowledge. This engagement will help me process and learn more about the information efficiently. Moreover, I will prioritize getting enough sleep, which may help me retain information more effectively and for longer periods.

[Weerapat Pipithruengkrai]

Implementing High Availability (HA) technology in a hospital information system (HIS) can bring numerous benefits to both patients and the hospital, especially in Thailand where the healthcare sector is rapidly growing and evolving. Below are benefits for patients and hospitals in Thailand when applied with HA technology.
Benefits for Patients:
-Uninterrupted access to medical records: HA ensures that patient medical records are always accessible, even in the event of hardware or software failures or disruptions.
-Improve decision-making process: With uninterrupted access to patient records, healthcare providers can make informed decisions quickly and effectively.
-Enhanced quality of care: HA enables consistent and reliable access to patient information, allowing healthcare providers to deliver diagnoses and effective treatments in a timely manner resulting in improving patient outcomes.
Benefits for Hospitals:
-Increased operational efficiency: HA minimizes downtime and ensures that the HIS is always available, which enhances hospital operations effectiveness and reduces the burden on IT staff.
-Improved resource allocation process: Reduced downtime and increased efficiency can lead to improved management operation for the hospital, as resources can be allocated more effectively.

[Weerapat Pipithruengkrai]

Your presentation effectively highlights the significance of MCBRS in tracking malaria trends and assessing malaria control interventions. You clearly outline the benefits for various stakeholders. Additionally, the presentation presents a structured approach for implementing MCBRS, including the development of a standardized case reporting method, a detailed data flow system, and dissemination of information to all stakeholders.

By the way, I would like to recommend utilizing cloud service on a central database and integrating with DHIS2 to facilitate system availability and security as well as reduce maintenance activities and resources required, which can further improve system quality and scalability.

[Weerapat Pipithruengkrai]

Thank you for highlighting the significance of wild mushroom poisoning as a public health concern, it is a new and interesting topic for me. In my opinion, your presentation effectively introduces the Mushroom Poisoning Surveillance System to promote public awareness and informed decision-making regarding wild mushrooms to help healthcare providers take action promptly.

By the way, I would like to add something that may facilitate the implementation process of the surveillance system. As you mentioned usage of web portals and cloud technology, I would recommend using low-code technology to implement these web portals as they have modules and cloud services that can facilitate system development as well as system uptime and security.

[Weerapat Pipithruengkrai]

My Strongest EQ Component: Social Skills
As a quite extroverted person, I find it not so difficult to connect with others. I enjoy learning about people’s opinions, experiences, and perspectives. My flexibility and easy-going nature help me get along with a wide range of personalities. These social skills have been allowing me to build relationships with new friends and colleagues.
Action Plan to Strengthen Social Skills:
-Actively seek out opportunities to meet new people.
-Focus on understanding the other person’s perspective and feelings, rather than simply waiting for my turn to speak.
-Try to use non-verbal actions to convey my interest and engagement in the conversation.
-Put myself in the other person’s shoes and try to understand their thoughts and feelings.

My Weakest EQ Component: Self-Awareness
My tendency to be too easy-going can sometimes hinder my self-awareness. I often find myself going with the flow and pleasing others without fully considering my own emotions and desires. This lack of self-awareness can lead to confusion and uncertainty about my own goals and passions.
Action Plan to Strengthen Self-Awareness:
-Dedicate time for self-reflection.
-Seek feedback from others about my strengths and weaknesses.
-Take personality tests or assessments to gain insights into my own preferences.
-Step outside my comfort zone and try new activities, hobbies, and experiences to uncover hidden passions and talents.

[Weerapat Pipithruengkrai]

Here are answers to the questions based on my experience as a computer technical officer while working in a hospital:

What happened?
When I was working as a computer technical officer at the hospital, our department experienced a cyberattack that disrupted access to the hospital’s website and information for almost a day. The attack was a denial-of-service (DoS) attack, a type of cyberattack that aims to overwhelm a website or server with traffic, making it unavailable to legitimate users.

How did it affect the system or users?
The DoS attack had a significant impact on the hospital’s operations. The hospital’s website was inaccessible to patients, staff, and the public, which caused users to be unable to access the hospital website and be informed about the services. Additionally, the attack disrupted the hospital’s internal systems, which made it difficult for staff to access and update hospital information.

And how to prevent it?
There are several things that can be done to prevent DoS attacks:
-Implementing intrusion detection systems: Using intrusion detection systems to identify and alert administrators to suspicious activity, IT can keep an eye on activity and take action in a timely manner.
-Using load balancing systems: Load balancing systems can distribute traffic across multiple servers, which can help prevent a single server from being overwhelmed.
-Educating about DoS attacks: Users should be aware of the signs of a DoS attack and know how to report it to the IT department.
-Ensure the web application is up to date: Keeping web application up to date can help to protect against DoS attacks that exploit known vulnerabilities.

[Weerapat Pipithruengkrai]

Hi, Nichcha. Your Looker dashboard on COVID-19 trends is detailed and visually appealing, showcasing data effectively across multiple countries. The use of interactive elements, such as filterable country and month and year selections is convenient for users to filter the data that they need. Moreover, the country icon that users can click access to specific details is useful and enhances user experiences.

To further improve the dashboard, consider adding comparative visuals between countries could also provide a clearer picture of differences in data. Overall, great job on a comprehensive and user-friendly presentation!

[Weerapat Pipithruengkrai]

Hi, Aung Thura Htoo. Your Looker dashboard for COVID-19 data is comprehensive and straight to the point, effectively displaying various key details such as total confirmed cases, recoveries, and deaths over time. Moreover, The simple design of filters and the option to select specific countries are convenient for users to use.

In my opinion, to further improve the dashboard, consider adding more detail on recovery and death, which could provide deeper insights into the impact of COVID-19 across different countries.
Overall, great work on a clear and informative dashboard!

[Weerapat Pipithruengkrai]

I appreciate your review of the CDC’s COVID-19 dashboard. You highlight several key strengths of the dashboard, such as bar charts for displaying trends over time, ongoing updates to real-time data, and color choices for accessibility. I agree that these elements contribute to a user-friendly and informative visualization.

By the way, I share your concern regarding the filter by date range (zoom feature). While it offers detailed data visualization capabilities, it can be challenging for the general audience to use as they need to take a good look to see how this feature works, Perhaps an alternative method for this feature, such as a button-based or date selection, could improve this aspect.

[Weerapat Pipithruengkrai]

Hi, K.Nichcha. I agree with your analysis and suggestions about the discussion on fighting corruption in the health system. By the way, I would like to add up on the accountability mechanisms that you talked about. I think if we can apply IT technology to those mechanisms such as online platforms for tracking resource allocation, real-time reporting of financial transactions, and public feedback, with these technologies we can create a more reliable and trustworthy healthcare system for everyone.

[Weerapat Pipithruengkrai]

I agree with your discussion for highlighting the potential of telemedicine in rural healthcare and the challenges that need to be addressed. I also think that your suggestions for overcoming these challenges are also insightful and applicable.
By the way, I would like to add one more area that can be explored and aligned with your solution, which is affordability. I think your solution regarding collaborating with IT companies can also benefit both healthcare organizations and consumers, as everyone can access the services and can enhance telemedicine service to be more effective.

[Weerapat Pipithruengkrai]

I agree that improving usability and acceptability to ensure it meets user needs and is accepted by more users can lead to more efficient data collection and productivity. As user is a key factor in completing the task and improving the outcome.

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