Forum Replies Created
-
Posts
-
-
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.
-
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.
-
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.
-
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.
-
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.
-
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.
-
-
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.
-
-
-
-
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.
-
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.
-
I propose choosing the cloud server over the physical server based on the following reasons:
– Mobility: Users can work anywhere, as their tasks are mobile within the hospital.
– Scalability: It is easier to scale up and down. For example, during the outbreak with more patients, the cloud server can handle increased patients demand, and it can be scaled down when the demand declines, providing flexibility.
– Data security: Cloud providers professionally take care the security following established protocols and regulations, which our single IT officer cannot easily handle. They also provide backup and recovery.
– Cost saving: No need to buy servers or pay for the maintenance cost.
– Maintenance and support: With only one IT officer, the cloud server reduces their workload as the cloud provider already do these tasks.And I propose that the PaaS would be appropriate for our web-based patient appointment app for the following reasons:
– PaaS provides platform for app development including the servers, databases, and tools. Therefore, with our hospital setting, it offers fast development and less burden on our IT officer. We can build a customized system for our hospital without worrying about handing the infrastructure, security, or backup.
– IaaS may not be the most suitable type, because although it provides server, storage, and network, but we still require more IT work to manage and maintain them..
– SaaS also may not suitable for our hospital setting. While it offers the infrastructure and platform, but it also provides a ready-to-use software that limits our flexibility to customize the app to fit our hospital.
-
As health informatics combines people and IT, it can support the detection, response, and control of infectious diseases, such as in the following scenario: Influenza in school children in Bangkok.
Detection: School absence data collected through electronic or mobile systems show a rise in influenza-like illness. Hospital pediatric units also observe a spike of influenza cases and report to the local public health organization through electronic reporting system and share dashboard.
Response: Local public health teams identify the outbreak using real-time data dashboard. Therefore, they investigate the schools, and alert teachers, parents, and surrounding communities through digital communication platforms.
Control: Preventive measures such as health education, hygiene promotion, and temporary class closures are introduced to stop further spread. These can be supported by IT tools such as e-learning, mobile educational message, electronic tracking of prevention effectiveness.
In summary, health informatics helps bring the data sources (school absence, clinical and lab reports) into an early detection system that leads to public health action supporting by IT tools communicating among people.
-
I am a clinician with experience in health research, and am currently building up my knowledge in epidemiology and public health to gain a broader perspective on health. To improve my profession in public health/health informatics, I would need to gain knowledge and skills of the followings:
1. Computational and Mathematical Sciences: I have knowledge in medical statistics, but limited experiences with computer science and IT. I would need to develop skills in programming, database, data analysis and IT systems, so I can apply these tools in the public health settings.
2. Management and Social Sciences: Although I have experience leading research projects and working in teams, I would like to strengthen my skills in project management, business/organization administration, health policy, and regulations. These skills will help me apply clinical work with public health management on a broader scale.
3. Health Sciences: This is my area of expertise, given my background as a clinician and health researcher. I would like to learn health informatics to integrate it with my background in health science to solve more complexed health problems.
-
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.
-
-
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.
-
-
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.
-
-
-
-
-
-
