Soe Wai Yan

[Soe Wai Yan]

There are many major health challenges facing the world and in my country. Among them, I would like to choose the infectious diseases, non-communicable diseases and climate change that we are currently suffering.

1. Infectious diseases become a major concern because new viruses can appear quickly as well as other diseases like TB become more common while the communities do not aware or do not have full access to vaccines or early detection especially after political changes and instability.
To manage this, the MoH and partners are trying improve the vaccination programs, raising public awareness and working together to respond faster when outbreaks happen.

2. Non-communicable diseases like diabetes and hypertension are increasing as people live more sedentary lives and eat less healthy food.
Our health systems are now focusing on prevention (in collaboration with some non-profit organizations) by encouraging active lifestyles, offering regular check-ups and creating policies that reduce smoking and other risky habits.

3. Climate change is affecting people’s health through heatwaves, air pollution and the spread of diseases like dengue after heavy rain.
To protect communities, the MoH and other health organizations are trying to strengthen early warning systems, improving mosquito control and preparing healthcare services to respond better to climate-related emergencies.

[Soe Wai Yan]

For the patient, implementing high availability in a hospital information system ensures that the system is always accessible, even during technical issues or maintenance. This helps patients receive faster and safer care because doctors and nurses can consistently access medical records, lab results and treatment histories without delay. With fewer system interruptions, patients experience smoother services, shorter waiting times, and reduced risks of medical errors.
For the hospital, HA improves overall efficiency by minimizing downtime and ensuring continuous operations in all departments, especially critical areas like the ICU. It protects important data from loss, increases staff productivity and reduces financial losses caused by system outages. Overall, HA strengthens the hospital’s reliability, supports better decision-making and enhances the quality of healthcare services.

[Soe Wai Yan]

In my organization, I am working to transition from paper-based registers to the Community-Based Health Application (CBHA). This mobile application serves two key purposes: it replaces the manual records used by community volunteers, and it provides clinical guidance for diagnosing and treating patients through pre-identified algorithms, which is especially valuable in hard-to-reach areas. The current paper system often results in fragmented records and inconsistent reporting, limiting timely decision-making. To manage this change, I plan to use the ADKAR model. I will first build awareness by highlighting how CBHA improves accuracy and supports volunteers in making correct clinical decisions. Then I will strengthen desire by demonstrating how it simplifies their workload. Training sessions will build knowledge, and field support during early use will enhance ability. Finally, reinforcement will come from improved data quality and successful cases guided by the app’s algorithms.

[Soe Wai Yan]

Effective communication in a team starts with creating a safe environment where everyone feels comfortable sharing their ideas, supported by active listening and respect for different viewpoints. I focus on being transparent with information and decisions so that expectations are clear. I also encourage a culture of constructive feedback, where team members can openly give and receive comments in a supportive and solution orientated. Throughout all interactions, I use clear, positive and simple language to prevent misunderstandings and ensure that discussions remain open, honest and respectful for everyone on the team.

[Soe Wai Yan]

I would like to share a situation where the confidentiality of my information was affected.

What happened?
One time, I logged in to my colleague’s computer and I forgot to log out properly because I was in a hurry for another thing. My colleague found that computer accidentally opened my email inbox because my account was still signed in. He didn’t do anything bad, but they told me later that they saw some of my personal messages and files.
How did it affect the system or users?
It affected me because my private information was exposed to someone else without my permission. Even though it was not intentional, my personal data was no longer confidential. I felt embarrassed and worried that someone could have deleted or shared my files.
How to prevent it?
To protect confidentiality, I learned to:
Always log out properly when using shared or public computers.
Use strong passwords and avoid saving them on public devices.
Enable two-factor authentication on my email.
Be aware of where and how I access sensitive information.
After that, I became much more careful with my login information to maintain confidentiality.

[Soe Wai Yan]

I generally use the Affiliative and Democratic leadership styles in my workplace. As a project leader, I mostly use the Democratic style because I believe everyone has their own expertise and valuable insights. I always encourage team members to share their opinions and ideas, especially when developing new initiatives or solving complex problems, especially during the current unstable situation. By creating an open platform for discussion, I make sure their voices are heard and their contributions are recognized. This approach helps build trust, teamwork and a sense of ownership among the team.
At the same time, I use the Affiliative leadership style when I notice my team members feeling stressed or demotivated. I focus on maintaining harmony, showing empathy and supporting them both emotionally and professionally. By listening to their concerns and appreciating their efforts, I help strengthen the team’s morale and relationships. Using these 2 leadership styles together allows me to keep the team engaged, motivated, and connected while achieving our project goals.

[Soe Wai Yan]

Thank you for your very interesting presentation Ma Wah. Since I am also working in the malaria field, the content clearly shows how global malaria issues connect with Thailand’s efforts to eliminate the disease. I totally agree that the rise in P. vivax and P. falciparum cases and the challenges along the border, it gives a good understanding of the main factors affecting malaria control in the country. It also makes a strong case for why Thailand needs a well-organized, data-based surveillance system to reach and maintain its malaria elimination goal by 2026.

[Soe Wai Yan]

Hi Sirithep!
Thank you for your interesting presentation.
I agree with your sentinel and syndromic surveillance approach regarding the RSV infection particularly in hospitals and clinics for sentinel surveillance and community settings for syndromic surveillance. And I appreciate your discussion on seasonal trends and responses like resource allocation, vaccination and awareness campaigns ahead. Thanks.

[Soe Wai Yan]

Prime Minister Lee Hsien Loong (Singapore)
Lee Hsien Loong’s speech on 8 February 2020 demonstrated clear and compassionate leadership. He spoke early in the crisis, showing timeliness (be first) and reassuring the public that the government was prepared, drawing on Singapore’s experience with SARS. His message was accurate and fact-based, reflecting transparency about what was known and what was being done (be right).
His tone and manner brought credibility and empathy. He acknowledged public fears directly and urged Singaporeans to stay calm, united and rational. By using inclusive language such as “my fellow Singaporeans” and “we will get through this together,” he built trust and a sense of community.
His message was also actionable advising citizens to maintain hygiene, avoid panic buying and follow official updates. Importantly, his speech was relevant, tailored to Singapore’s culture of collective responsibility and discipline. He managed to fix both confidence and caution.

President Donald Trump (United States)
President Trump’s national address in March 2020 had a very different tone and structure. While it aimed to project authority and confidence, it fell short in several key areas of effective crisis communication. Although he spoke as the virus spread widely across the world, his message was not among the earliest official communications, so it was only moderately timely.
In terms of accuracy and credibility, Trump’s statements were sometimes inconsistent with information provided by health experts and agencies such as the CDC and WHO. Trump often made the virus seem less serious, saying it was “under control” and that the risk was “very low.” This made people trust him less (less credible). He did not show much care for people’s feelings, talking more about government actions and the economy than about public worries. His tone sounded defensive instead of kind, so people found it harder to connect with him. The speech also didn’t give clear advice on what people should do, like wearing masks or keeping distance. Finally, his message was broad and generic, making it less relevant to the diverse American population, where different regions faced varying levels of risk.

Comparison and Conclusion
Lee Hsien Loong’s speech was closed to all the main communication principles. He spoke early, gave facts, showed care and stayed calm. His clear and balanced tone helped people stay calm and work together.
Donald Trump, although confident and visible, did not fully follow these rules. His mixed messages and too optimistic tone made him seem less reliable and less caring.
Overall, I think Lee Hsien Loong was the better communicator. He built trust and unity, while Trump’s speech lacked the clear and caring tone needed during a health crisis.

[Soe Wai Yan]

Based on the 5 themes proposed in the article: team, transparency and trust, technology, techquity and transformation, Myanmar still faces major gaps, particularly in technology, techquity and transparency and trust.

Theme2 Transparency and Trust:
Public trust in data use and digital health initiatives remains low due to limited transparency, unclear data privacy regulations and misinformation on social media. Building trust through clear communication, public engagement and transparent data governance will help improve compliance and cooperation in future health emergencies.

Theme3 Technology:
Myanmar’s health information systems remain largely paper-based, with limited interoperability and data-sharing capacity between hospitals, ministries, and laboratories. During COVID-19, the lack of real-time data, weak digital surveillance and poor integration of electronic health records made it difficult to track cases or distribute vaccines efficiently. Strengthening technological infrastructure such as cloud-based systems, interoperable data platforms, and digital surveillance tools is essential for better preparedness.

Theme4 Techquity:
Digital health access is uneven across the country, especially in rural and conflict-affected areas where internet connectivity and digital literacy are limited. Many people still lack access to smartphones, affordable data plans, and online health information. This digital divide prevents equal participation in telemedicine and digital vaccination programs. Improving connectivity, affordability, and digital literacy is key to ensuring inclusive preparedness.

[Soe Wai Yan]

1. Could you list the disease outbreaks that have been declared as the Public Health Emergency of International Concern (PHEIC)?
a. H1N1 Influenza (2009): A global swine flu pandemic that spread rapidly, causing widespread concern.
b. Polio (2014): Declared due to outbreaks in countries where vaccination rates were low, risking further international spread.
c. Ebola (2014): A highly fatal disease with major outbreaks in Africa, raising fears of global transmission.
d. Zika Virus (2016): Caused birth defects like microcephaly and spread to many countries, particularly in the Americas.
e. Ebola (2019): Another Ebola outbreak in the Democratic Republic of the Congo, which was declared a PHEIC due to its risk of international spread.
f. COVID-19 (2020): A novel coronavirus that rapidly spread worldwide, causing a global pandemic.
g. Monkeypox (2022): An outbreak outside its typical regions, raising concerns about its international spread and potential for higher transmission.

2. Why do these outbreaks raise concerns?
_Global spread: Diseases can spread across borders quickly, especially with international travel, making containment difficult.
_High mortality and morbidity: Some diseases like Ebola have high fatality rates, while others like COVID-19 cause widespread illness.
_Burden on healthcare systems: Outbreaks can overwhelm hospitals and medical resources leading to shortages and higher mortality.
_Economic disruption: Outbreaks can close businesses, limit travel, and slow down economies, as seen with COVID-19.
_Emerging pathogens: New diseases, like COVID-19, may have no immediate treatments or vaccines, making them harder to manage.
_Potential for global impact: These diseases have the potential to turn into pandemics if not quickly controlled.

3. In your opinion, is there a disease or condition that may potentially lead to PHEIC in the future? Why?
In my opinion, the antimicrobial resistance may lead to PHEIC in the future. Due to the limited knowledge of the general population and lack of effective preventive measures such as some countries including Myanmar that lead the bacteria becoming resistant to antibiotics. This could lead to un-treatable infections, posing a serious global health threat.

[Soe Wai Yan]

1. Which single design limitation most threatens valid estimates of sensitivity and representativeness? How would you address it within six weeks?
The most critical design limitation is the system’s reliance on passive surveillance which threatens both sensitivity and representativeness. Health workers may lack training, motivation or time to report every AEFI and some communities may be completely missed.
To address this within six weeks, I would implement a short-term active surveillance pilot in a selection of underrepresented LGAs. This would involve:
a. Assigning trained health workers or community informants to actively seek and report AEFIs weekly,
b. Leveraging existing immunization outreach structures to minimize cost and delay,
c. Comparing reported cases from active sites to passive ones to estimate under-reporting.

2. Using the CDC surveillance attributes, propose one low-cost intervention to increase sensitivity. State the expected trade-offs, and list 2–3 indicators to detect impact from the intervention.
Intervention:
Distribute simple AEFI reporting job aids and provide short refresher training for frontline health workers during routine supervision visits targeting sensitivity.
Expected Trade-Offs:
May lead to an initial increase in reports of mild or unrelated events, reducing specificity that could temporarily burden health workers with additional tasks.
Indicators to Track Impact:
a. AEFI reporting rate per 10,000 vaccine doses that should increase if possible.
b. Proportion of health facilities submitting at least one AEFI report per month.
c. Completeness of AEFI report forms to ensure quality is maintained.

3. For a newly introduced vaccine, should the AEFI case definition be temporarily broadened to maximize early signal detection?
Yes, temporarily broadening the AEFI case definition is appropriate during the early phase of a new vaccine rollout. It increases the likelihood of detecting rare or unexpected adverse events which is critical for public trust and early risk management.

[Soe Wai Yan]

In my opinion, IT can help the following:

Verification and Preparation
1. Establish the existence of an outbreak: IT can help to detect outbreaks early by using mobile apps and real-time dashboards to track case trends that enables quick alerts to health authorities when unusual case surges occur.
2. Verify the diagnosis: IT can improve diagnosis verification by enabling faster data exchange between local hospitals and public health officials, reducing delays in response.
3. Prepare for field work: Digital tools like GIS mapping and mobile data collection apps can help health workers in remote areas efficiently to track and manage outbreak data.

Describe the Outbreak
1. Construct a working case definition: Digital collaboration tools can allow technical teams to draft and share case definitions quickly, ensuring consistent use without the need for in-person meetings.
2. Find cases and record information: Using mobile apps for case investigation, public health workers can quickly report cases in real time, syncing with a central database for faster decision-making.
3. Perform descriptive epidemiology: IT tools can create dashboards and GIS maps to identify patterns and clusters, allowing public health officials to focus resources on high-risk areas.

Hypothesis and Testing
1. Develop hypotheses and analytical studies: IT supports data analysis and the development of hypotheses by using statistical software and digital surveys to explore factors contributing to the outbreak.

Response and Action
1. Implementation of control measures: Automated SMS alerts and digital tools can be used to communicate control measures and follow-up actions to communities, especially in rural areas.
2. Communication including outbreak report: IT can generate automated reports and track social media to manage misinformation, ensuring accurate, timely updates to both stakeholders and the public.

By improving data exchange, minimizing errors and ensuring secure information sharing, IT can enhance the ability to respond quickly and effectively to health emergencies.

[Soe Wai Yan]

During COVID-19, some researchers and governments around the world used anonymized mobile phone location data to track how people moved and whether lockdowns or travel restrictions were effective. These data that were collected from telecom operators and apps can show the aggregated patterns of population mobility rather than individual identities.
In Myanmar, this type of technology was used during the pandemic. The UN Development Programme (UNDP) and Telenor Myanmar collaborated in 2020 to analyze anonymized mobile mobility data to support the government’s COVID-19 response. These data helped public health authorities and researchers understand how people were moving between regions, especially during lockdown periods or religious holidays when internal travel increased.
Because Myanmar has very high mobile ownership, this tool provided a realistic, data-driven picture of population movement even in the absence of widespread testing or digital contact tracing apps. It allowed policymakers to better target stay-at-home orders, border control and resource allocation to areas at higher risk of transmission.

Why it was important:
It helped to monitor compliance with lockdowns and travel restrictions.
It gave the real-time insight into urban/rural migration patterns during outbreaks.
It worked even in a context with limited internet access or low digital literacy, since it used existing telecom infrastructure.

[Soe Wai Yan]

1. How can surveillance help to detect and control the disease?
The surveillance can help:
_The early detection of outbreaks: Continuous monitoring can help to identify unusual case cluster or new geographic spread that allow the rapid containment and vaccination or isolation measures.
_For understanding epidemiology: It can provide data on incidence, risk groups, transmission routes and reservoir patterns that are essential for targeted interventions and public health messaging.
_The monitoring trend and impact: It can assess the effectiveness of control measures and detect the re-emergence.
_The detection of mutation and resistance: Laboratory-based surveillance can identify new viral strains or changes in virulence.

2. Should we conduct active or passive surveillance or both? Why?
We should conduct both. The passive surveillance can provide ongoing monitoring at low cost and can identify background incidence trend. The active surveillance is essential during outbreak to detect every case and interrupt transmission that is especially for an emerging or re-emerging disease.

3. Which method should be best to identify cases, why?
a. The medical facility vs community:
We should practice both but priority should depend on outbreak context. The severe cases often present to medical facilities and so hospital-based reporting can efficiently detect serious infections. However, mild cases may stay in the community especially in resource-limited or rural and hard to reach area.
b. The sentinel vs population-based surveillance
The sentinel surveillance is efficient for early outbreak detection and monitoring trend and population-based surveillance can give more generalize incidence data of the population although it is costly.
c. The case-based vs aggregated surveillance
The case-based surveillance should be prioritized while it can collect detailed information on each case. The aggregate system can only count the number of case and cannot support detailed outbreak investigation.
Monkeypox requires case-based surveillance to understand transmission, contact and vaccination status.
d. The syndromic vs laboratory-confirmed surveillance
The syndromic surveillance allows rapid alerts in the field. Laboratory confirmation can ensure diagnostic accuracy and monitoring of viral strains. The combined use of syndromic surveillance for early detection and lab confirmation for verification should be done for outbreak-prone disease.

4. What dissemination tools will you choose to disseminate monkeypox surveillance information? Why do you choose this/these tools?
a. The periodic tool: The weekly or monthly surveillance reports to inform health authority, partner and clinician.
b. The real-time tool: Event-based and online platform such as health map to share rapid alerts and outbreak locations. The mobile dashboard and map for real-time visualization and data sharing between local stakeholder enable faster dissemination, public awareness and coordinated response.

[Soe Wai Yan]

Hello Everyone,
I am Soe Wai Yan. I graduated from the University of Medicine 2, Yangon and I am working in an INGO since 2016. My passion is to craft and work with the system that integrate the advanced technology and healthcare in one platform specifically, for the ones who work in the hard-to-reach area.

[Soe Wai Yan]

Should you give the data out?
No, I should not give out the full individual-level data as requested because it would violate patient privacy and confidentiality, which are core principles of informatics ethics.

How do you not violate any of the General Principles of Informatics Ethics?
I must protect privacy, ensure confidentiality, obtain proper authorization and share only necessary, anonymized information.

If you want to provide the data to them , what and how will you do it?
You can provide de-identified or aggregated data after removing personal identifiers . Before sharing, I will get ethical approval, sign a data-sharing agreement and ensure the researchers agree to use the data responsibly and securely.

[Soe Wai Yan]

What should I do?
I cannot disclose the patient’s medical information to anyone including family members or friends. My duty is to maintain confidentiality and protect the integrity of the health record.

Can I tell my friend?
No, I cannot. Sharing that information would be a serious breach of confidentiality and a violation of both ethical standards and privacy laws. My responsibility is to the confidentiality of the patient’s data not to personal relationships.

Can I interfere with family issues?
No. As a health information professional, I have no right to interfere in personal or family matters.

Should my friend not know because she might be at risk?
Although I am worried about my friend’s health and potential risk, it is not my place to disclose confidential information. Instead, I can encourage proper medical and ethical channels—for example, ensuring that the patient receives counseling and is informed of his duty to notify his spouse.

How will you follow the fundamental principles about right to self-determination, doing good and doing no harm to others?
Autonomy: The patient has the right to decide who knows about his medical condition.
Doing Good: I can do good by protecting the patient’s confidentiality and ensuring the case is handled through proper procedures.
Non-Maleficence: The revealing the information to my friend could cause serious harm emotionally, socially and legally to both the patient and myself.

Is not it your obligation and the right of the subject to hold the information?
Yes. As a professional, I am obligated to hold patient information in confidence. It is the patient’s right to privacy and control over their own medical information.

[Soe Wai Yan]

In my organization, “The One Dashboard” was introduced in my previous discussion.
Awareness: The organization communicated the purpose of the new system early through emails and meetings. Most employees were aware of the change and its benefits.
Desire: This area was weaker. Many employees did not feel involved in the decision-making process and were hesitant to shift from familiar tools. There was limited effort to build motivation or address concerns.
Knowledge: Training was provided but it did not always meet the specific needs of different teams. Some users were unclear on how to apply the dashboard to their roles.
Ability: During implementation, many employees struggled to use the demo system effectively. There was not enough hands-on support or role-specific guidance to help users feel confident.
Reinforcement: While leadership continued to promote the dashboard, there was limited follow-up, recognition or feedback mechanisms to ensure long-term adoption.

The One Dashboard idea was a valuable initiative but the organization could have better managed the change by involving employees more and providing ongoing support.

[Soe Wai Yan]

Our organization is currently developing ‘The One Dashboard’ to integrate multiple data sources for better decision-making and performance monitoring. Although still in progress, I think this has key factors based on the 5 main areas:
People: We actively engaged staff and managers from the start to ensure the system meets their needs and gains their support.
Cost: Since we used open-source tools and internal expertise instead of purchasing new software, this does not share the costs.
Operation: The dashboard is designed to pull data automatically from existing systems minimizing manual work and avoiding disruptions to daily operations.
Design: We involved both technical and non-technical users in the design to ensure the interface is simple and easily understandable.
Data: Data quality is essential for reliable outputs. We standardized indicators and set up validation checks to ensure accuracy and consistency.

All factors are interdependent but people remain the most influential. Without staff and leadership support, even the best system may fail.

[Soe Wai Yan]

In our organization, we use a Community-Based Health App that guides volunteers in malaria diagnosis and treatment as well as replaces paper records. It works well because it even functions offline by pre-defined algorithm, improving accuracy in remote health settings in Myanmar. Factors like training, device availability and technical support can still influence its effectiveness.

[Soe Wai Yan]

If hospitals don’t use the ICD standard, diagnoses would be coded differently everywhere, making it hard to share patient data or compare information. This would cause problems in communication, research, insurance claims and even public health planning. Overall, it would reduce efficiency and quality in healthcare.

[Soe Wai Yan]

I partly agree with the findings from ‘Electronic Health Records and Physician Burnout’. Although electronic records and health information exchanges (HIEs) have many benefits such as improving coordination of care and reducing duplication of tests, these EMRs are also a major contributor to physician burnout.
The main causes include excessive documentation requirements, poor system design, high workload, working overtime to complete record and constant inbox alerts that lead to “alert fatigue.” These issues shift physicians’ focus from patient interaction to screen time which not only reduces job satisfaction but also negatively impacts patient care. Personally, I think some EMRs are time-consuming and sometimes difficult to navigate. The system requires a lot of times for simple tasks.
To reduce this problem, several measures are needed such as improving UI/UX, reducing unnecessary steps/documents, providing comprehensive training and optimizing the alert system.
Actually, I suppose EMRs are valuable tools but without proper design and support, they risk becoming a source of stress and burnout for health professionals. A balanced approach is needed to retain their benefits while minimizing negative impacts on physician well-being.

[Soe Wai Yan]

Hello Jenny,
Thank you for your great presentation about the RxBox.
I see how RxBox can save the lives in isolated and disadvantaged communities in your country and it is on the other hand cost effectiveness. It also reflects the usage in our country, Myanmar, with the under-served communities.

[Soe Wai Yan]

Hi Hteik Htar!
Thank you for your interesting presentation.
Your video helped me better understand how the KOBO is usable.
It enhances the visualization for the teams and supervisors with the real-time data that significantly improves the decision-making.

[Soe Wai Yan]

In my opinion, eHealth is the use of digital technologies to help people manage their health, improve communication with health professionals and use data to provide safer and more personalized care.

[Soe Wai Yan]

I think it is the national health records and disease surveillance data collected from public hospitals, PPM clinics and rural health centers across Myanmar. This includes patient records, diagnostic data, lab results, prescription data, COVID-19 tracking data and even mobile health data from remote areas.

Volume:
The healthcare system generates a large amount of data daily especially from hospitals in major cities like Yangon and Mandalay, but also increasingly from rural areas through digital health initiatives. This includes thousands of patient records, lab tests, and imaging data.

Velocity:
During disease outbreaks (e.g. COVID-19, dengue fever), data needs to be collected and processed quickly to inform public health decisions, resource allocation, and emergency responses.

Variety:
The data comes in different forms: structured (patient registration, lab results), unstructured (doctor’s notes) and semi-structured (health surveys, SMS-based symptom reporting from rural areas)

Veracity:
In Myanmar, data quality can be inconsistent due to manual record-keeping, lack of standardization and underreporting, especially in rural regions. This affects trust in the data.

Value:
When used effectively, this data can support disease prediction, health resource planning, and targeted health interventions especially in underdeveloped areas where resources are limited.

[Soe Wai Yan]

Brief Introduction about Health Informatics Project
_I have observed a health informatics project in our organization, where we implemented a Community-Based Health App (CBHA) in our project area. In this project, we provided mobile phone to each volunteer allowing them to collect health data directly through the application.The primary objective of this health informatics project is to improve decision-making in diagnosis and treatment by providing them the symptom-based algorithm and to reduce the burden of the paper works. This application also allows the volunteers to help the tracking of medical commodities so that the monthly manual stock checking is no longer needed.

How The Project Help to Improve Current Practices
_The app has significantly reduced the paper-based records, which were previously used by volunteers to track various diseases and projects. This digital transition has simplified the data collection process and significantly reduced the human errors in disease management. Furthermore, it also reduced the burden of manual stock management.

Challenges or Difficulties
_However, there are a few challenges in implementing the project. One of the main difficulties is the lack of digital literacy among some volunteers, particularly those of older age which makes it harder for them to fully utilize the app. Another challenge is the limited internet connectivity in some areas, which hinders real-time data transmission. To overcome this, the volunteers need to visit the nearest accessible points or the mobile teams visit these locations to collect data via Bluetooth or other offline methods, uploading it when they have access to better internet.

[Soe Wai Yan]

Dear Jenny,
Thanks for sharing an interesting story. This data breach highlights the critical importance of proper data security configuration and oversight, especially when handling sensitive personal and professional information. In addition, I think organizations should implement automated tools for vulnerability scanning, enforce role-based access management and conduct regular cybersecurity training for staff to minimize human error and strengthen overall data protection practices.

[Soe Wai Yan]

Dear Ma Yin,
Thank you for sharing such an interesting cyber attack. I think organizations should implement network segmentation to limit the spread of malware, conduct regular third-party security audits, and deploy advanced threat detection tools like AI-based monitoring to detect suspicious activity before it escalates into a full-blown breach.

[Soe Wai Yan]

Dear Nang,
This is a strong overview highlighting key lessons from the Blue Shield Data Breach, especially around misconfiguration and third-party risks. In addition to the suggested prevention measures, I would like to suggest to implement a data loss prevention (DLP) system to automatically detect and block unauthorized sharing of sensitive information, especially when integrated with third-party tools.

[Soe Wai Yan]

An attacker can use the following to conduct the security attack:
1. Using malware (viruses, ransomware, and spyware), an attacker can harm the system or steal the information.
2. Using social engineering, an attacker can manipulate people to gain access to systems or data. A common method is phishing, where fake emails or websites trick users into giving away passwords or personal details.
3. By targeting network communication like Man-in-the-Middle (MITM) attack, the attacker intercepts data between two parties.
4. Attackers can also take advantage of bugs in software using SQL injection.
5. Attackers can also conduct DDoS attack to overload the servers making them slow or unavailable. This disrupts services and can cause financial damage.

[Soe Wai Yan]

1. Why Choose a Cloud Server instead of a Physical Server?
Using a cloud server is more practical and cost-effective than investing in a physical server, especially considering our current limitations. Our hospital lacks a dedicated server and has only one IT officer who is mainly responsible for basic computer maintenance. Setting up a physical server would require significant investment, ongoing maintenance and specialized IT expertise that we currently do not have. In contrast, a cloud server can be deployed quickly with minimal initial cost, offers high reliability and availability, and includes built-in data backups and security managed by the provider. Cloud solutions are also highly scalable, allowing us to easily expand system resources as the hospital grows or as patient demand increases. This approach minimizes downtime, ensures secure access and reduces the technical burden on our small IT team.

2. Recommended Cloud Computing Service Model:
For this project, the most appropriate cloud computing model is Software as a Service (SaaS). SaaS allows us to use ready-to-deploy web-based software hosted and maintained by a third-party provider, eliminating the need for us to build, host or manage the application infrastructure ourselves. This model is suitable for our limited IT resources and the urgent need to get the appointment system running smoothly and quickly. A SaaS solution would include patient scheduling, data entry forms and even reporting tools that all accessible via a web browser with no need for installation or complex setup. It also ensures automatic updates, security compliance and technical support, helping our team stay focused on healthcare delivery rather than software maintenance. Overall, SaaS offers a fast, efficient, and reliable way to introduce digital appointment booking to our hospital with minimal operational complexity.

[Soe Wai Yan]

Due to increased population movement across borders and weakening of routine health services in conflict-affected areas, malaria continues to be a major public health concern in Myanmar. At the same time, information technology has rapidly developed and become vital in outbreak management, particularly in remote and hard-to-reach areas where health systems are fragile.
The systematic application of information technology in health has been increasingly used by health organizations in Myanmar to improve data collection, disease surveillance, early outbreak detection and timely response. In areas where routine services are disrupted, such as in parts of Kayin or Sagaing, malaria transmission often increases due to lack of preventive measures like insecticide-treated nets, health education and early diagnosis.
To address this, our organization and other partners are adopting mobile-based and digital systems to strengthen malaria surveillance and response. For example, the Community-Based Health Application, mobile application, is being used by field volunteers and community health workers to report malaria test results and case details in real time even from areas with poor internet connectivity. Once the phone connects to a network, data is sent to the central database. This allows the regional mobile medical teams to analyze trends and spot outbreaks much faster than before.
We recently received an alert from a mobile report in eastern Myanmar where a high number of Plasmodium falciparum cases were detected within one week. The mobile medical team immediately conducts the investigation. Through coordination between HIS, mobile medical teams and community health workers, we distributed bed nets and conducted the active case detection (ACD) together with health education within a few days. Within two weeks, no new cases were reported from that village. Without real-time data and digital systems, such a response would have taken much longer.
We also emphasize training and capacity building in digital reporting tools among our staff and community volunteers. Many of them now understand the value of real-time data and actively use these tools in their daily work. As a result, data quality has improved, errors have decreased, and the response time to outbreaks is much faster.
Although our current system is still developing, we see that applying health informatics in malaria outbreak response has already shown clear benefits. If we can further develop this with enterprise architecture and national-level integration, we will have a strong foundation for eliminating malaria in Myanmar.

[Soe Wai Yan]

Based on my background with clinical experience and public health, I recognize the need to strengthen my skills in the key areas:
1. Data Science and Analytics
I need to learn how to effectively collect, manage and analyze health data. This includes big data analysis using python or other programming to find key trends and insights that can support evidence-based decision-making.
2. Public Health Knowledge
While I have experience in public health, I need to deepen my knowledge of specific areas like epidemiology, disease surveillance and health policy that is strongly linked with my career.
3. Computer Science
As a medical professional, my technical skills in IT are limited. I have limitations in areas like database management, statistical analysis and programming languages that are commonly used in health informatics.

[Soe Wai Yan]

If I am a director of the hospital, I will surely plan to move the hospital’s information system to cloud computing. The main reasons include:
1. The cloud computing provides the data security and backup options, even though there are the privacy concerns, which is very important for protecting patient records and hospital data.
2. It allows for easier access to information for authorized personnel, even from remote locations, which can help improve patient care and coordination.
3. Using cloud systems can reduce the cost of maintaining physical servers and IT infrastructure, which is especially beneficial in the long term. Furthermore, it can reduce the cost of paper-based documentation and save the environment.
4. The cloud solutions are more scalable, allowing us to expand the system as the hospital grows.
Considering the global trend and the need for modernization in Myanmar’s healthcare sector, moving to cloud computing is a strategic decision for both efficiency and future readiness.

[Soe Wai Yan]

I had a really unfortunate experience with a cyber attack that taught me a valuable lesson. One day, I received an email from a co-worker containing a link. I did not realize that his computer had been infected and when I clicked the link on my phone, I unknowingly triggered malware. As soon as I did, all my contacts were wiped from my phone, and a message appeared demanding money in exchange for restoring them. At the time, I had all my contacts stored on my phone, so losing them was a big blow. Despite efforts from our IT team, they were unable to recover the contacts. As a result, I had to manually re-enter every single contact. This experience was a wake-up call and since then, our team has undergone training to better recognize cyber threats and to improve our overall security measures.

[Soe Wai Yan]

Based on my experience in non-profit sector, the healthcare supply chain system in Myanmar still faces significant challenges. Essential medicines and medical supplies often run short in remote station hospitals and rural health centers due to poor inventory management and delayed restocking. This results in treatment delays and negatively impacts patient outcomes.
1. Hardware:
Many healthcare facilities lack computerized inventory systems and rely on manual stock tracking.
Improvement: To equip facilities with affordable computers or tablets and reliable power sources to enable digital inventory management.
2. Software:
There is no centralized software to track medicine stocks, expiry dates, and order schedules.
Improvement: To develop or adopt simple, user-friendly inventory management software customized for Myanmar’s healthcare context.
3. Data:
Stock data is often inaccurate, incomplete, or outdated, leading to overstocking or shortages.
Improvement: To implement real-time data entry and monitoring systems to maintain accurate stock records.
4. Process:
Ordering and distribution processes are manual and slow, causing delays in replenishment.
Improvement: To automate procurement workflows and establish timely communication channels between facilities and suppliers.
5. People:
Healthcare workers and supply managers may lack training in digital tools and inventory best practices.
Improvement: To provide targeted training programs and continuous support to build capacity in supply chain management.

[Soe Wai Yan]

Hi Sayar Than Htike Aung,
Thank you for your information.

[Soe Wai Yan]

Hi Siriluk Dungdawadueng,
I really agree with your idea of combining a patient-facing mobile app with a hospital-facing web app. It is a smart way to streamline the entire care process from appointment scheduling to tele-medicine and medication delivery. I like your focus on data security, using end-to-end encryption. This approach will not only improve patient convenience but also reduce hospital crowding. I think it is a great solution for improving healthcare outcomes.

[Author]

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