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Gaps between rural and urban health in Thailand
– Workforce imbalance: Major cities and urban areas have a higher concentration of doctors, including subspecialists, for which the ratio can be up to 10x different.– Accessibility: Rural people rely on a three-level healthcare system where traveling to district hospitals for specialized treatment remains difficult due to distance and poor resources, while in urban areas, there are more options, such as private hospitals and clinics, highlighting more gaps in seeking treatment.
– Burnout: Rural doctors frequently work 80-100 hours per week, leading to burnout and high turnover, which decrease the quality of care.
Innovative action plan in Thailand
– Rural workforce scheme: There has been an effort to recruit the students from rural backgrounds to train them specifically for service in their own communities.– Telehealth medicine: Digital platforms (esp. during COVID-19, apps like Mor Prompt) allow rural people to consult specialists via telemedicine and access personal digital health records. This includes linking referral networks as well.
– Mobile medical service: Using mobile clinics to bring specialized screenings and care directly to remote areas.
– Empowered community networks: We have established and strengthened village health volunteers as a bridge to screen and treat patients locally, including using mobile technology, reducing the workload in big hospitals.
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Thailand is currently facing a crisis regarding its health workforce. For example:
The Problems
Poor distribution: We produce enough doctors on paper, but they are in the wrong places. While cities are fine, some are oversaturated, but the rural border areas face low doctor vs population ratio. Other professionals, especially nurses, are even scarcer.
Burnout issue: Staff are leaving the public hospitals to private practice and it is not just for money, but due to poor management, heavy workloads, and high expectations from patients and families.
Lack of Value: Many workers feel undervalued, unprotected, and financially under-paid.
Unnecessary tasks: Paperwork such as for accreditation and unplanned policies from the central goverment (like the sudden Dialysis Choice policy) cause hugh overload without extra support or pay.
Rigid government system: Strict government rules prevent hospital directors from easily hiring help or firing underperforming staff.The Solutions
I feel that health system in Thailand is very complexed, so to tackle the problems is quite challenging. However, the suggestions could be:
Cut the paperwork: Reduce documentation and pause new non-essential projects.
Informatics: Use it to decrease workload, though we must face the initial implementation barriers.
Empower the workforce: Allow health workers to form unions to negotiate fair working hours, payment and safety standards.
Strengthen primary care: Use our existing community health network to manage care locally, preventing big hospitals from unnessessary workload. -
The good side of using EHR and why I prefer it is that, unlike the paper-based system where retrieving record cards for old patients is time-consuming and difficult, EMR allows faster access and review of complete medical histories. Digital systems allow more consistent and detailed information, improving the coordination between health workers, lab technicians, and administrative staff.
However, the downside is that there are still barriers to reaching its full potential. With the confusion during early transition, staff often have to handle both paper and electronic records, leading to an increased workload. Moreover, many healthcare workers have low computer usage levels or only basic training. Successful implementation of EMR requires much training. Additionally, some users fear that the time spent on EMR might reduce the quality of face-to-face interaction and the relationship with the patient.
And I believe that in order for the EMR system to operate smoothly, we need at least 1) capacity building, where IT training should be practical and role-specific to make sure that staff are comfortable enough to be familiar with it, and 2) centralized regulation and a unified standard of the system so it can allow streamlined data sharing across institutions within the country.
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I would like to add some thoughts about the communication gap between the frontline collectors and the analysts regarding the main challenges in the article.
Missing Data: Data is often missing because workers are busy and sometimes don’t see the point of completing it. They should be shown how their data turns into better patient care or improves their workflow. If they see positive results, they would be less likely to skip the info. Automated error-checking can also be included in the process of checking for missing data and errors.
Selection Bias: Big data, for example, the national registries, should be checked for quality and coverage so they do not miss the full picture of representatives. Also, analysts can later use statistical techniques to adjust for bias in this observational data.
Training and applications: We can start by training the data lead in each department and then branch out. The key is making it practical by the collectors need to know how to keep data clean, while analysts need to master the stats/AI/tech tools to handle these big datasets.
Privacy and Ethics: The current system feels like every institution has its own rules and ethical committees, making data sharing difficult. We need more centralized regulation to streamline the process.
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I agree with all 4 main recommendations in the article. To solve any problem, the first step is acknowledging that the problem exists. In order to reach a consensus among different stakeholders, we must clearly define the specific issues we are trying to solve, which in this context is corruption.
However, I believe one reason it is so difficult to acknowledge corruption is that healthcare professionals often hold themselves to high standards of ethics and morality. This can lead to a misconception where they believe they are acting in the best interest of the patient or the system while ignoring or defending practices that are actually part of a corrupt cycle. Therefore, I strongly agree that to effectively tackle corruption, we must move beyond individual morality or victim blaming and focus instead on strengthening the larger system, which I believe can create a larger impact and be more sustainable than focusing on individuals’ cheating. We must create an environment where all stakeholders can talk openly about these issues without feeling defensive about their professional ethics or personal morality. And solving this effectively requires more than just clinical health practices. It must include a multidisciplinary approach to address the root causes of the problem.
In addition, the role of research is also important, especially, as I gathered from our peer discussions, when combined with digitalization and the transparency of open data, it can make an impact to help fight corruption in the system.
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Changing of dialysis policy in Thailand
In 2022, Thailand changed its national dialysis policy from a Peritoneal Dialysis (PD) First model to Patient-Led Dialysis. This improvement aimed to allow patients to choose their preferred dialysis modality (HD or PD) based on individual clinical needs and lifestyle preferences without additional financial burdens. The goal was to move away from a “one-size-fits-all” approach and increase patient safety by reducing the morbidity and mortality risks sometimes associated with forced PD in unsuitable candidates.
However, recent reports have shown that this policy has significant barriers, leading to unintended consequences for both patients (e.g. worse clinical outcomes from poorly planned initiation) and the health system (e.g. over-dialysis and the neglect of home-based PD). The barriers include:
– Informatics Barrier: A lack of interoperability between hospitals, private HD providers, and the budget payer’s database (NHSO-National Health Security Service). This makes it difficult to monitor real-time efficiency or track patient outcomes across different stakeholders
– Workforce Constraints: The increase in demand for HD has led to a shortage of specialized healthcare professionals, which affected the quality of treatment
– Financial Sustainability: This affected the Universal Coverage Scheme budget, as HD is significantly more expensive for the health system to maintain than home-based PD
– Incentive Bias: Private clinics may prioritize HD sessions for revenue generation, which could lead to over-dialysis for unsuitable candidates
Ref: https://www.nature.com/articles/s41591-025-04084-w
https://www.hitap.net/en/document/policy-brief-191-sustainable-kidney-replacement-thailand-2022-reform/ -
If I were developing a DR plan for a 250-bed hospital, I’d include the following steps and tools:
## Phase:
1. Activation: Identify potential risks and staffs (including committee) who will be responsible for activating the processes and assessing when there is a pre-defined disaster.
2. Execution: Power, network, and EMR will be restored first. Clinical teams can switch to paper workflow if required.
3. Reconstitution: Once the issue is stable, the flows are moved back to the electronic-based in a controlled way.Regular mock drills are mandatory after we implement the plan.
## Technology (with limited budget and human resources):
– Critical systems: such as EMR, Lab, Radiology, can use replication of data to a secondary site to decrease downtime and prevent data loss. In case of limited budget, any tools with near real-time replication may be used as well.
– Back-up storage: cloud available such as google/one drive
– Administration: backups that don’t require heavy management can be used. Daily incremental backups should be set with full backups scheduled regularly and kept them at a secondary site -
Benefits for patients: For example, it improves the quality of care. In case the system goes down, HA will keep clinical data flowing seamlessly. Medical information won’t get lost or delayed. Moreover, it will impact how quickly health workers can get the patient information they need. No waiting time when a patient needs immediate attention.
Benefits for hospitals: For example, HA helps save costs (even if it might cost money upfront). It will cost less for the emergency situation needed when a critical system fails. And since HA makes hospital operation more available and reliable, it ensures patient data delivery is timely and continuous, resulting in better efficiency.
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I’d like to share an example of an incident in Thailand in 2020, when a tertiary hospital in central Thailand was attacked by ransomware (Ref: https://www.bangkokpost.com/thailand/general/1982423/ransomware-attack-on-saraburi-hospital).
In summary, Saraburi Hospital’s computer system was hit by ransomware, causing the entire system to crash. This represented a failure of confidentiality, due to the unauthorized disclosure of hospital information, and a failure of availability, as the shutdown made health information inaccessible.
Effects: Patients visiting the hospital were advised to bring their own medical records and old medications with them. This also affected healthcare workers, making patient management more difficult.
Prevention: To prevent such incidents, the organization should at least have had an emergency plan or backup system in place. For example, procedures for operating when ePHI becomes inaccessible, regular hardware/software maintenance and updates, and strengthened security awareness through staff training.
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Hi Sirithep! Thank you for the presentation. I appreciate that you chose RSV, as it’s increasingly relevant not only in children but also in adults and the elderly. I agree with the use of sentinel and syndromic surveillance across schools and daycare centers, though it would be helpful to clarify how active surveillance will be implemented.
I also agree that the extended SARI definition works well for hospital-based severe cases, though including apnea and sepsis in infants might be less suitable for surveillance purposes. The ARI definition for community-based surveillance is reasonable and could be integrated with other respiratory virus outbreaks like influenza or COVID-19 to strengthen detection capacity.
And just a minor point for me, the sound was a bit off at times, but your slides were clear and informative, so it wasn’t difficult to follow.
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Hi New! Thank you for your presentation. I like that you clearly explained the case definition, although the COVID-consistent symptoms might be too broad and could benefit from further clarification. I would suggest visualizing the data flow and showing how each stakeholder connects to make it easier to understand how the system works. I also like that you specified the intervals for data utilization, dissemination, and indicator measurement. It would be even better if a brief detail on how each indicator is collected were included.
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Based on CERC, PM Lee was a more effective communicator. His statement was delivered at the initial phase of the outbreak and stated what was already known by bringing up the scientific evidence, such as the infectivity and mortality comparison, which built the strong credibility. He also expressed empathy and showed respect for public reaction by addressing the public fear, reassuring them that anxiety is a natural human reaction. He provided simple, clear, and actionable steps, suggesting basic preventive measures that people can follow.
Meanwhile, President Trump also made an early statement. Although he shared some facts about the risks, some of them were more like claims rather than measurable evidence, such as trying to reassure that the U.S. was more prepared than other nations. Empathy and respect were not clearly demonstrated, although the actionable preventive measures were mentioned.
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Thailand needs to improve in:
– Techquity: Many people still have limited capacity to use digital tools, and this gap seems to be wider. It results in unequal participation in digital health programs.
– Transparency and trust: Fragmented data sharing and unclear data governance cause low confidence and trust among people. They are unsure how their personal data are collected and used, have no clear understanding of the protocols, and generally lack trust in the government.
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PHEIC outbreaks were: H1N1 (2009), Polio (2014), Ebola (2014, 2018), Zika (2016), COVID-19 (2020).
These outbreaks raise such concerns because they were threat to public health by causing severe morbidity and high mortality. Some also posed rapid global spread.
The possible PHEIC in the future could be the emergence of a zoonotic influenza strain such as H5N1 that could potentially adapt to mammalian host and spread between humans.
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1.) Which single design limitation most threatens valid estimates of sensitivity and representativeness? How would you address it within six weeks?
– It was the lack of involvement of private healthcare providers, resulting in under-reporting and incomplete documentation. When this data was missed, it means the community awareness of AEFI report would be low. Therefore, I would suggest including them by implementing a fast-track training for staff in these centers. For example, scheduling the workshop for the key staff responsible for detecting and reporting AEFI. Then, providing them the necessary tools for detection and documentation. Direct consultation should also be offered to support the fast track process.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.
– Since the lack of participation and low awareness was mentioned, a feedback loop could be implemented. It can be a regular monthly requirement for health center leaders to submit their reports to the central database. A simple summary from the central system should be produced and distributed so that the stakeholders can see their contribution, and also can help monitor vaccine safety data. The trade-off is this practice can add more workload to the local staff as well.
The key indicators could be: the proportion of complete reporting, and the timeliness of reporting.3.) For a newly introduced vaccine, should the AEFI case definition be temporarily broadened to maximize early signal detection?
– Yes, which means that more inclusive case definition will increase sensitivity, which is important for a new vaccine. The trigger could be for example the standardized reporting rate is achieved, and the decision would be made baked on the judgement of the National Committee. -
1. Verification and preparation
– IT can be used for verification of case numbers by comparing them to the normal baseline on IT-based surveillance systems
– It can send timely alerts when there’s an excess number, which also helps in identifying the Place.
– IT helps to deliver rapid information to the authorities responsible for verifying the diagnosis and communication for fieldwork.2. Describe the outbreak
– Fieldwork team can use IT devices and systems in the field for case finding and investigation
– IT tools create the digital line listing and deliver it online, allowing the whole team prompt access to the information.
– IT tools can generate the visualization, such as Epi curves, to see the pattern of outbreak (Time).
– It can also create a digital map to demonstrate the Place by showing case distribution, which benefits hypothesis generation and further investigation.3. Hypothesis and testing
– IT tools are used to test the hypothesis and obtain results useful for creating control measures.4. Response and action
– IT is used to deliver rapid and effective messages of the control measures to the stakeholders and the affected communities. -
I choose social media platforms as a tool that I found having a strong impact on COVID-19 surveillance and response. Through social media, people can quickly become aware of an emerging disease and its characteristics by accessing information shared by public health authorities and their communities. For example, these platforms help spread awareness of symptoms and signs of COVID-19, when to seek testing, how to access vaccines, and updates on preventive measures. They also support real-time communication faster than traditional systems, although some people may still be left behind due to digital inequalities.
However, because of their huge impact, if not carefully managed, social media can also become a source of misinformation, such as from antivax people, or false treatment information. I think this is a big challenge today, and health authorities need to be more aware and proactive in monitoring and correcting such information.
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For dengue scenario:
1. How can surveillance help to detect and control the disease?
– Surveillance helps detect dengue by monitoring trends and signals of dengue cases in the target area, resulting in an appropriate response when any change is found, e.g. increasing acute febrile illness suggesting dengue infection. It not only helps in early detection and outbreak response, but also helps evaluate the interventions after they are implemented to control the spread of dengue.2. Should we conduct active or passive surveillance or both for the disease, why?
– We should conduct both for dengue where appropriate. Passive surveillance should be used for routine monitoring in health centers since it requires fewer resources. Active surveillance should be added during the outbreak or peak season or clusters to help collect more detailed information for further intervention and control.3. Which method should be best to identify cases, why?
Cases in medical facilities VS community
Sentinel VS population-based surveillance
Case-based VS aggregated surveillance
Syndromic VS laboratory-confirmed surveillance
– While it should depend on context, objectives, and available resources. I am not sure about this objective of best identifying CASES (which can be done with case-based medical centers, sentinel coverage, and a lab-confirmed approach).However, if based on dengue surveillance in limited-resource settings but still aiming for effective disease control, the most appropriate approach could be medical facility-based, population-aggregated, and syndromic-confirmed surveillance.
Medical facility-based method is practical since most clinically significant dengue cases will eventually present at health centers, while the community-based method costs more. For public health control, identifying asymptomatic cases is less critical since the preventive measures can be applied when a signal of the outbreak is detected.
In terms of scope and coverage, population-based surveillance can be used to identify the high-risk area. Aggregated method are suitable for continuous routine surveillance since it is cheaper, while case-based methods can be used during outbreak clusters for detailed investigation.
Lastly, syndromic approach is fast and appropriate for early warning and timely response, with laboratory confirmation that can be added on a subset of cases to verify and provide more detail.4. What dissemination tools will you choose to disseminate monkeypox surveillance information? Why do you choose this/these tools?
– For dissemination of Mpox surveillance information, I would prioritize real-time dissemination tools because the disease requires rapid alert and awareness among health professionals and public health authorities. Periodic dissemination tools can be used later for formal documentation, trend monitoring, and reporting and evaluating the interventions -
Should you give the data out?
– No, I should not give out individual data with personal identifiers. That would break privacy and confidentiality, even if the research has potential public health benefits.How do you not violate any of the General Principles of Informatics Ethics?
– I will follow the individual privacy and security, least Intrusive, and ensure transparency of all processes.If you want to provide the data to them, what and how will you do it?
– I should provide data at village or sub-district level, instead of identifiable individual records. If individual-level data is absolutely required, I will seek approval from the ethics committee and/or responsible authority. A data-sharing agreement is also required to define how the data will be used, stored, and protected. After that, I would share only the data relevant to their research, after de-identifying any personal identifiers. -
As a health information professional – can you tell your friend?
– As a health information professional, I cannot tell my friend about her husband’s HIV status because it would break confidentiality and professional ethics.Can you interfere with other people or family issue?
– I cannot interfere with family issues either. Disclosure should come through the patient or the doctor in charge.But, should your friend not know about this because she might be at risk?
– I believe that she should know for her safety. But the responsibility lies with the patient and the healthcare team to inform her.How will you follow the fundamental principles about right to self-determination, doing good and doing no harm to others?
– I respect the patient’s right to self-determination. I do good by ensuring that patient data is protected, and I do no harm by making sure no one is put at unnecessary risk.Isn’t it your obligation and the right of the subject to hold the information?
– It is the patient’s right to decide whether to share his health information with whom. My role is to protect that right and confidentiality. -
In my hospital, the EMR system is still used alongside paper records, and a newer inpatient digital system is currently being piloted. I think the change management has not been fully effective. Referring to the ADKAR model:
– Awareness: I believe that staff are frustrated, and some concerns may have been raised to the hospital board. However, the problems are not fully acknowledged, as staff keep pushing through daily work to prioritize patient care.
– Desire: Even though frontline staff are frustrated with the current system, many are not motivated to learn a completely new one from scratch. They feel the system only adds more work without clear benefits.
– Knowledge: Training was inadequate and delivered randomly. By the time the system launched, many users had already forgotten what they learned.
– Ability: The system itself is not user-friendly, and IT support is limited. Users often had to rely on each other for help instead of receiving timely support.
– Reinforcement: No ongoing reinforcement or encouragement to adopt the system. Without incentives or follow-up, many staff reverted to using paper records.
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In my hospital, we use an EMR system, but it still runs alongside paper records. The EMR mainly stores scanned copies of doctors’ handwritten notes, laboratory results, and uses a separate program for imaging studies.
From my experience, the main problems are design and operation. The system is not user-friendly. For example, to review imaging exams I need to switch between different program windows. Recently, a newer system was introduced in the inpatient unit to move toward fully digital records, but its implementation seems slower than expected. More training sessions will be needed for staff, including myself, to use it effectively.
In addition, I believe that cost is another critical barrier. The limited budget restricts improvement not only in my hospital but also in many government health centers across Thailand.
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Based on the hospitals I work with, the CDSS examples include pop-up alerts during drug prescriptions, such as dosage adjustments for body weight, and allergy warnings. These help reduce prescription errors and reviews.
Factors that could influence the implementation of CDSS are:
– Users: Their trust in the system. Alert fatigue
– Technical: Challenges of integration into existing HIS/EMR
– Resources: IT support within the organization including budget -
Apart from interoperability, data analysis and sharing, health surveillance, and billing that were already mentioned, without ICD (or other standardized tools), it would be difficult to develop EMR or decision-support systems. Hospitals may also struggle to adopt IT tools that are meant to reduce the workload of health professionals. This can lead to hidden costs from duplicated tasks and inefficient processes. It also could increase inequity in the health system, as hospitals that remain non-ICD–based would face challenges with traditional systems, resulting in poor data quality and affecting patient care in those regions.
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Thank you for your presentation on eHealth Africa. From the VDO, I understood that they have shifted from paper-based to electronic systems for health data records, vaccination tracking, surveillance, and eLearning. Mobile devices are also used for contact tracing and health campaigns. These implementations clearly cover the three main domains you mentioned. I’d like to add that it also highlights the interaction between global stakeholders, both governments and NGOs, enabling communication on a large scale across the Africa continent, where health challenges is significant. I am really impressed by their work and journey.
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Hi Hteik! Thank you for your presentation about KOBO. The VDO helped me better understand how the KOBO works, after previously reading peers’ mentions of it. I agree that this project improves field staff’s monitoring and response efficiency. It also enables faster communication between field staffs and regional teams or other stakeholders, supporting timely interventions and data-driven decisions that can enhance public health outcomes in your covered area.
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I agree with the review that EMRs can cause physician burnout. It aligns with my experience from working with different EMRs in different hospitals, where it clearly shows that design and user-friendliness are very important. Some hospital EMRs cause me frustration when they require too many windows, run too slowly, or force me to go back and forth among various clinical data.
However, I think physician burnout originates more from the heavy nature and environment of clinical work itself. For example, long hours, high patient loads, and pressure to avoid mistakes. EMRs don’t directly create this stress, but they amplify it. When physicians are already overloaded, poorly designed EMRs can add more frustration and lead to heavier burnout.
So, apart from tackling the workload itself, EMRs can still be valuable tools. They should reduce duplication and provide a fast, smooth workflow. Involving health professionals directly in the design process would make EMRs more practical and user-friendly. I also strongly agree that using scribes, voice-over/voice-to-text technology can help with physician routines. In addition, supporting staff who are efficient with EMRs can also help reduce the workload.
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I’ll give the example of big data in chronic kidney disease. Big data in the nephrology field can involve not only national databases such as the renal registries in the U.S., UK, Europe (ERA), etc, but also data collected through EHR/administrative claims, clinical trial registries, mobile health devices, and molecular databases. These big datasets fit the 5V framework as follows:
1. Volume: Data are collected from multiple large-scale sources as mentioned above.
2. Variety: Includes structured data such as laboratory values and diagnosis codes in registries, and unstructured data such as radiographs and pathology images.
3. Velocity: Refers to the speed of data generation and collection, which is accelerated by digital technologies. Wearable devices also contribute to real-time data generation.
4. Veracity: Data may be inconsistent and not fully standardized, but its trustworthiness still depends on the accuracy of diagnoses and laboratory values generated by professionals.
5.Value: This data has the potential to significantly improve the management and outcomes of chronic kidney disease.
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My background is a kidney doctor taking care of dialysis patients. In Thailand, we have the Thailand Renal Replacement Therapy (TRT) Registry, a nationwide database that covers around 98% of dialysis services across the country. It integrates data from hospitals and dialysis centers using standardized forms and electronic submission. The TRT collects data on patients with end-stage kidney disease (ESRD) undergoing dialysis, including both hemodialysis (HD) and peritoneal dialysis (PD). The registry includes patient demographics, clinical parameters, treatment details, and outcomes, with data primarily submitted by dialysis nurses through electronic systems.
The TRT helps improve chronic kidney disease (CKD) practice. For example, it highlights key trends and challenges in CKD on dialysis management since 2000, providing epidemiological data and insights for policymakers to plan strategies that benefit public health. Recent data analysis in 2023 revealed that the number of HD patients has increased dramatically since 2022, while the number of PD patients has remained stable. Stakeholders can use these findings to enhance early CKD detection and prevention strategies, as well as to investigate how the choice of dialysis modality impacts public health management. Moreover, the data is available for researchers to gain insights that can guide CKD practice and improve the quality of patient care.
However, the TRT still faces challenges. For example, there is a need for clear clinical definitions of various comorbidities associated with ESRD outcomes. Some data domains are still not standardized, making them difficult to use directly for analysis. Some diagnoses are based on treating physicians’ assessments and are not implemented using standardized criteria across centers. Additionally, many types of data that would benefit public health analysis are still not captured. Implementing an ideal registry practice would faces challenges from health workers, as the registry requires them to manually enter hundreds of data points into the system, rather than capturing data directly, posing interoperability challenges.
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I have just noticed that someone was trying to attack one of my social media accounts last week. So I’d identify some possible means as followings:
– Reuse passwords: I am too lazy sometimes to change and remember different passwords across many accounts. If one of passwords has leaked somewhere online, attackers could try to use it to guess my other accounts.
– Weak 2FA: I also noticed that I haven’t set the 2FA for this account, so that could be another weak point where someone could trick to be the owner.
– Tied email account: Since I use the same email address to many accounts, attacker s could use it to reset my password.
– Phishing: While scrolling the social media, I might sometimes get hooked by advertisements (that know my personal interests based on my online activities). I might make a mistake clicking on a fake login or even get tricked by a warning message with a fake link.
– Mobile malware: If my device has malware getting from my online activities, it could steal my passwords, or other linked information that attackers could use to log into my account.
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Thank you for sharing your real case. It helped me understand the issue clearly, and your lessons learned are practical. I think your example shows the common pitfall where test systems are treated as low-risk, but attackers don’t see the difference. This is why consistent security plans and routine audits are necessary for every system, not just production.
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Thank you for your insightful comment as always! I totally agree that linking evaluation results to long-term impact is also important. Especially in the CKDSS, the evaluation indicators such as data accuracy and user feedback can inform policymakers about areas needing improvement, helping early detection programs and overall CKD care.
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Hi Kevin! So although the CKDSS is based on laboratory and clinical data, it can still be used for the general public, especially during the dissemination stage. After data analysis, the results provide important information on the burden of CKD in Thailand, which can be used to increase public awareness and engagement. Recently, public health authorities have hosted campaigns addressing the NCD burden in Thailand, using information from the surveillance system to raise awareness and promote preventive strategies.
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Thank you for your comment, Hteik đŸ™‚
Since CKD is a slowly progressive disease, data collection will be continuous through the EHR system once abnormal values meet the pre-defined criteria, with automatic extraction from laboratory records. Additionally, data will be aggregated and reviewed monthly at the hospital level, and analyzed quarterly at the regional and national levels to monitor trends and ensure data quality.
Both physicians and laboratory technicians are involved. Physicians verify CKD diagnoses and follow-up status, while lab technicians ensure the accuracy of test results before they are transferred into the CKDSS.
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I agree with the point that text messaging and chatbots can be hugely useful nowadays, given the way of our communication in this era. Public health authorities can use these tools to deliver messages to people instantly. Also, IT devices can be useful in the reverse direction in that they aren’t only for communication but also for monitoring the effectiveness of the measures implemented.
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I still find that some platforms continue to spread misinformation about COVID-19 even today, especially in open chat groups that started during the pandemic and have now turned into anti-vaccine communities. I have seen efforts from both the government and health influencers trying to tackle this news by sharing correct information online to counter false claims. I think what we can do is to keep spreading reliable information on the same platforms and make people stronger in digital and media literacy, which will help tackling this problem in the long run.
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Thank you for the comment ka. I saw physicians in the U.S. using it in their OPDs. In Thailand, tech start-ups are now developing AI software that can record conversations between doctors and patients and automatically summarize them into HIS/EMR systems, such as Prescribe AI. I think further development is still needed to improve transcription accuracy and ensure it aligns with real-time clinical contexts.
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Thank you for your comments :). I agree with your point about making the app accessible to all communities. In reality, some people are not aware that these options are available on the app. In my opinion, this tool is especially useful in big cities like Bangkok, where there are multiple health benefit schemes and various health centers, and people are generally efficient at incorporating technology into daily life. However, in some areas, people may struggle with both physical access to health services and technological accessibility.
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Hi Hteik! Thanks for bringing up the EPI data. I agree with your explanation of the 7V characteristics of EPI data. I also would like to add that EPI data can provide more values, such as being used for epidemiology research, economic studies in the cost-effectiveness of vaccination programs, and social sciences e.g. to understand the barriers of vaccine uptake. Therefore, it is valuable not only for clinical use but also for guiding broader health policy.
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