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Information technology plays a crucial role in assisting the outbreak investigation process by enhancing data collection, analysis, communication, and decision-making at each stage. During the initial step of establishing the existence of an outbreak, electronic surveillance systems are used to monitor disease trends and detect abnormal increases in cases. These systems allow for real-time data collection and automated alerts, which help identify outbreaks quickly.
In the step of verifying the diagnosis, information technology supports laboratory confirmation through Laboratory Information Management Systems that record, track, and share laboratory test results efficiently. Electronic medical records (EMRs) also enable healthcare professionals to verify diagnoses remotely and ensure data accuracy.
When defining and identifying cases, electronic case reporting systems and mobile data collection tools such as KoBoToolbox assists field investigators in capturing standardized data directly from health facilities or communities. These tools improve the accuracy and timeliness of case finding, even in remote areas.
In descriptive epidemiology, IT applications such as Epi Info, Excel, and Geographic Information Systems (GIS) are used to analyze data according to time, place, and person. GIS helps to map cases geographically and visualize clusters, providing insights into the spatial distribution of diseases. Similarly, analytic and visualization software such as Tableau or Power BI helps to identify patterns and generate hypotheses about the possible sources and transmission routes.
During hypothesis testing and evaluation, statistical software support the analysis of relationships between exposures and disease outcomes.
When implementing control and prevention measures, information technology enables effective communication through mobile applications, SMS alerts, and social media platforms. Decision-support systems also provide real-time recommendations for interventions based on current data trends. Finally, during the step of communicating findings, digital dashboards, online reporting tools, and interactive data visualizations allow health authorities to present results clearly to policymakers, healthcare providers, and the public.
In conclusion, the application of information technology in outbreak investigations enhances the efficiency and accuracy of public health responses. It enables rapid data collection, real-time communication, and evidence-based decision-making, which are all essential for timely control of disease outbreaks. -
I have selected Digital Contact Tracing Apps as the technology that I find most compelling due to its direct role in interrupting community transmission at scale. Digital contact tracing automates the process of identifying individuals who have been in contact with a confirmed case, offering scale and speed that is difficult to replicate using traditional methods.
How it works:
1. These smartphone applications typically leverage low-power Bluetooth technology to operate.
2. When User A and User B come into contact, their phones exchange an anonymous identifier key via Bluetooth, recording this as a contact event. These detected keys, recording contact events, are usually saved on the device for a limited time.
3. If User A tests positive for COVID-19, they update their status in the app.
4. Depending on the architecture, either User A’s contact records are sent to a central server (centralized system) or only User A’s anonymous key is sent (decentralized system).
5. User B’s app receives this information and, if a match is found with their on-phone contact records, User B is alerted of contact with a confirmed case and advised to quarantine and/or get tested.
This digital approach helps to reduce reliance on human recall, which is particularly beneficial in densely populated areas with mobile populations.
The primary importance of digital contact tracing is its role in interrupting community transmission. Following the identification and isolation of a case, rapid tracing and quarantining of contacts is crucial to prevent the further spread of the virus.
However, the effectiveness of these apps is heavily dependent on widespread adoption by the population, requiring a large proportion of users to download and comply with the advice for the strategy to be effective in reducing the effective reproduction number (R) to less than 1. Furthermore, while offering significant benefits, digital tracing apps raise considerable challenges, especially regarding legal, ethical, and privacy barriers, and require careful implementation to build public trust. Several international frameworks have emerged to address privacy concerns, advocating for decentralized systems over centralized ones, for instance. -
Infectious disease surveillance serves three critical goals for managing public health threats like dengue, a disease listed as nationally notifiable in the United States. The surveillance system aims to describe the current burden and epidemiology (including seasonality and age distribution) to justify interventions, monitor disease trends (including the impact of control measures), and identify outbreaks and new pathogens. For an outbreak-prone disease like dengue, ongoing surveillance facilitates the early detection of an outbreak, enabling a rapid public health response. While passive surveillance, where medical professionals report cases, is commonly implemented because it requires fewer resources, it is prone to missing cases. Therefore, for a complete and responsive system, passive surveillance should be complemented by active surveillance during an outbreak, where public health staff actively engage in searching the community to find symptomatic patients and conduct contact tracing.
To achieve comprehensive case identification, various methods must be employed. Identifying cases in medical facilities captures severe cases requiring hospital treatment; however, community-based surveillance is essential to capture the full burden of disease, including milder cases or those who do not seek health care. Furthermore, population-based surveillance is preferred over sentinel surveillance if the goal is to produce generalizable rates of disease (incidence and mortality rates) across a defined geographic area. To ensure detailed information for investigation and targeted control efforts, case-based surveillance, which collects individual-level data on person, place, and time, is recommended over aggregated surveillance, although systems may temporarily transition to aggregated data if the case volume becomes overwhelming. Finally, an effective case definition strategy should use syndromic surveillance (monitoring clinical symptoms without laboratory confirmation) as a sensitive alert system for suspect cases, followed by laboratory-confirmed surveillance to provide the necessary specificity and definitive identification of the etiologic agent.
For diseases requiring rapid response, such as monkeypox (Mpox), surveillance information must be disseminated quickly as surveillance is an action-oriented public health tool. I would choose real-time and online tools to facilitate rapid intervention. The Health Alert Network (HAN) is vital for quickly disseminating confirmed disease reports and information (including required actions) to medical and public health professionals at a national level. Similarly, the Program for Monitoring Emerging Diseases (ProMED) acts as an important early warning of outbreaks by consolidating and verifying reports from media and observers, disseminating this free information rapidly via email and the Internet. These rapid tools are complemented by periodic dissemination tools (such as surveillance bulletins or the MMWR/ WER), which provide formal, regular summaries of disease trends and case counts to stakeholders. Additionally, online platforms like HealthMap provide an innovative way to display collected data geographically on an interactive interface, enhancing real-time situational awareness.
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• Should you give the data out?
No, I should not give out the individual-level malaria data that include personal identifiers such as home address, geolocation, and contact number.
• How do you not violate any of the General Principles of Informatics Ethics?
Sharing such identifiable information would violate data privacy, confidentiality, and the ethical principles of informatics, particularly autonomy, privacy, confidentiality, security, and justice. To avoid violating these principles, I would seek approval first and only after proper review and authorization could data sharing be considered.
If you want to provide the data to them , what and how will you do it?
If I decide to provide the data, I would ensure that it is properly anonymized or de-identified—removing all personal identifiers and replacing them with coded numbers so that individuals cannot be traced. I would also prepare a data-sharing agreement (DSA) outlining the scope of use, data security measures, and obligations of the research team to prevent misuse or re-identification. By following these steps, I can support valuable research that benefits public health while still protecting individual rights, ensuring confidentiality, and maintaining ethical and legal standards in data management. -
As a health information professional, I have an ethical and professional obligation to maintain patient confidentiality.
I am not allowed to disclose the information to anyone without the patient’s consent. Revealing it would be a serious breach of confidentiality, violating both professional ethics and legal standards such as patient privacy laws.
I also cannot interfere with family or personal matters related to the patient. My duty is to manage and protect health information—not to make personal judgments or decisions about how the patient handles their condition. While I may feel concerned for my friend’s health and safety, I must act within my professional boundaries.
In terms of ethical principles:
Right to self-determination: The patient has the right to control who knows about his medical condition.
Doing good (beneficence) and doing no harm (non-maleficence): My role is to protect the patient’s rights and trust in the health system. Breaching confidentiality could cause emotional and social harm to both the patient and my friend.
Justice and professional integrity: All patients deserve equal respect for their privacy, regardless of personal relationships.
Although the situation presents a moral dilemma, the correct action is to respect confidentiality. If I am deeply concerned about the possible risk to my friend, I could encourage the patient (through proper channels) to disclose his condition to his spouse or seek counseling services, but I must never disclose it myself. Upholding confidentiality protects the integrity of the health profession and ensures trust in the healthcare system. -
My organization implemented a Case Analysis System to track the therapy progress and goals of children with disabilities. The system aimed to improve documentation, rehabilitation goal-setting, and communication among therapists. However, it was partially unsuccessful due to challenges in user adaptation and system design.
According to the ADKAR model (Awareness, Desire, Knowledge, Ability, and Reinforcement), the organization did not fully manage the change process effectively. While there was Awareness about the importance of digital record-keeping, many staff members lacked strong Desire to change from paper-based methods. Training sessions were limited, which meant insufficient Knowledge and Ability to use the new system confidently. In addition, there was little Reinforcement after implementation—no continuous follow-up or recognition for those who used the system properly.
As a result, some therapists continued using manual reports, and data in the system remained incomplete. To improve future system adoption, the organization should strengthen staff engagement, provide regular hands-on training, and establish ongoing monitoring and feedback mechanisms.
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My organization implemented a Case Analysis System designed to track therapy progress and goals for children with disabilities. However, the system was partially unsuccessful due to several factors. In terms of data, records were not updated regularly and lacked consistency. The cost of the system was low, but limited budget meant fewer features and poor technical support. From an operational point of view, the system helped organize client information, but slow performance and occasional errors affected efficiency. The design was not user-friendly, and it was frequently changed by the organization, which discouraged some staff from using it. Finally, the people factor played a major role—some staff were not well trained or motivated to use the new system. Overall, the system showed potential to improve service delivery but failed to achieve full success because of design, data management, and user engagement issues.
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During my work experience at hospital, one example of a Decision Support System is the electronic medical record (EMR) system that helps collect and organize patient data such as assessment findings, progress notes, therapy schedules, and outcomes. It supports clinical decision-making.
Overall, the system works reasonably well, especially for maintaining accurate client records and ensuring continuity of care among multidisciplinary team members (physiotherapists, lab technologists, pharmacists, nurses, and doctors). But sometimes the internet connectivity and staff digital skills also affect how effectively the system is used.
Factors that might influence the Decision Support System implementation could be technical infrastructure: which is reliable internet, sufficient computers, and stable power supply are necessary for smooth operation. Another one is staff training and digital literacy because some staff may not be familiar with using electronic systems, so ongoing training is essential. Besides, management support is also important because implementation works better when leaders encourage and allocate time for proper data entry and use. Last one is data quality – The accuracy and completeness of patient data entered into the system directly affect the quality of decision-making. -
One of the key purposes of ICD is interoperability. Without it, exchanging EMR/EHR data between hospitals would become inconsistent so difficulty in health information exchange occurs. Another one is clinical communication problem such as a diagnosis written in free text or using local codes may cause misinterpretation, especially when patients move between hospitals which could lead to errors in treatment, duplication of tests, and poor continuity of care. Many insurance systems use ICD codes for claims, reimbursement, and fraud detection. Without it, billing would be inconsistent and inefficient for both hospitals and insurance providers.
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I agree with the study’s conclusion. EMRs were designed to improve efficiency, accuracy, and interoperability, but in practice, they often introduce heavy documentation tasks, complex interfaces, constant alerts, and increased administrative workload. These factors can overwhelm physicians and reduce the time they spend on actual patient care, which is a key source of professional satisfaction.
I have heard many concerns from healthcare professionals that they feel they spend more time typing, documenting things than interacting with patients. User friendly interface is important as this can make simpler and easier for users.
Some solutions could be:
1. Improve system usability: We can simplify EMR interfaces, reduce unnecessary clicks, and make workflows more intuitive and using speech-to-text and natural language processing to reduce manual typing.
2.Delegate non-clinical tasks: We can employ assistants to handle routine documentation as Sir. Zam suggests. Automate repetitive tasks like prescription refills and test result notifications.
3. Training and support: We can provide continuous training so staff can use EMRs more efficiently. Involve physicians in EMR design feedback loops to ensure real-world usability.
4. Policy and organizational support: Allow protected time for documentation within working hours instead of after hours. -
Hi Jenny! Thank you for sharing this interesting project. I believe patients in remote or disadvantaged areas who often struggle with limited access to doctors, diagnostic tools, and timely interventions can receive essential health services closer to home, reducing the need for long and costly travel.
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Hi Nang!
Thanks for the knowledge. I believe this project can significantly improve current health practices. When patients receive timely and well-coordinated interventions from providers who have a full picture of their medical history, they feel more confident and cared for. This transparency and continuity of care builds trust between patients and the healthcare system. -
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My opinion for an example of Big Data in healthcare is the Electronic Health Records (EHRs) combined with real-time patient monitoring data. For instance, hospitals now collect huge volumes of information such as laboratory test results, imaging files, medical reports, prescriptions, wearable device data (like heart rate, oxygen level, or physical activity), and patient histories. When combined, this creates a massive dataset that can be analyzed to improve diagnosis, predict disease outbreaks, and personalize treatments. This can be helpful in reducing patients’ unnecessary visit to the clinics.
Characteristics of this data according to 5Vs could be:
1)Volume: Healthcare systems generate large amount of data daily from EMRs, medical imaging, lab tests, wearable devices, and from billing systems. There is certainly large variety of data coming from different sources, in different formats.
2)Velocity: Data is generated rapidly in real-time—for example, continuous heart rate and oxygen saturation monitoring from ICU patients, and new wearable sensors helping track patient’s health trends that can be monitored by the doctors.
3)Variety: Data comes in multiple forms such as structured (lab results, demographics), semi-structured (sensor logs, prescriptions), and unstructured (doctor’s notes, CT scan images).
4)Veracity: Data quality can vary; some records may have errors, duplicates, or incomplete entries that require validation.
5)Value: When analyzed, the data can provide insights for better patient care, early diagnosis, and public health decisions. -
Brief Introduction
I have observed the implementation of an Electronic Medical Record (EMR) system in the hospital where I worked. This system was used to digitally store and manage patient health information, replacing most of the traditional paper-based documentation. The EMR allowed doctors, nurses, and other healthcare professionals to access patient records more efficiently and provide timely care.How it can help improve current practices
The use of EMRs helped improve healthcare practices in several ways:
Efficiency: Reduced the time spent on paperwork and allowed quick retrieval of patient history, lab results, and treatment plans.
Accuracy: Minimized errors caused by illegible handwriting or misplaced files.
Continuity of care: Enabled better coordination between different healthcare providers, as all relevant information was stored in one system.
Decision support: Some systems had built-in alerts for drug interactions or abnormal lab results, improving patient safety.
Patient satisfaction: Faster and more accurate services improved overall patient experience.Challenges or difficulties
Despite these benefits, there were several challenges in implementing and using the EMR:
Training requirements: Staff needed time and training to adapt to the new digital system.
Technical issues: Power outages or system downtime sometimes disrupted access to records.
Resistance to change: Some staff were reluctant to move away from familiar paper-based methods.
Data privacy and security: Ensuring that patient records remained confidential and secure from unauthorized access was also a major concern. -
I would consider moving the hospital’s information system to cloud computing using a hybrid cloud approach. This allows the hospital to store sensitive data on-premises while using the cloud for less critical data, which is suitable given Myanmar’s current infrastructure and connectivity. Cloud computing provides access to resources and improves mobility, allowing staff to access data from anywhere. It also offers scalability, ensures data security, provides cost savings, and includes maintenance and support handled by the cloud provider.
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Yes, my computer was once infected by a cyber threat. It happened when I inserted a USB stick into my computer without checking it for potential malware. The cause was a malware infection from the USB stick. After the infection, my computer started to slow down significantly, and some files were affected or became inaccessible. To prevent this from happening again, I will:
Always scan USB drives with antivirus software before opening any files.
Keep my antivirus and system software updated.
Avoid using unknown or untrusted USB drives.
Regularly back up important files to reduce the risk of data loss.
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I would like to build an app focused on patient care coordination and communication between doctors and patients. It would handle appointment scheduling, medical record access, telemedicine, and medication management. This ensures timely interventions, reduces miscommunication, and helps patients stay engaged in their health. The app would be a mobile app for patients with a web-based portal for doctors, supported by a cloud backend. Mobile access allows patients to receive reminders, track their health, and attend virtual consultations, while doctors can review detailed records and monitor multiple patients efficiently. By improving communication, adherence, and access to real-time data, the app helps prevent errors, enables early intervention, and keeps patients actively involved in their care. For example, abnormal lab results could trigger alerts to doctors, allowing quick adjustments to treatment and reducing the risk of complications.
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In my workplace, the patient management and therapy tracking system for people with disabilities still faces many challenges. Much of the patient information, including therapy plans, progress notes, and medical history, is recorded manually or across multiple unintegrated platforms. This leads to inefficiency, delayed access to information, time consuming, and difficulty monitoring the progress of each patient effectively.
Several components of the system contribute to these problems. Hardware is limited for real-time data entry. Software is fragmented, lacking an integrated system to track therapy, appointments, and outcomes. Data is often incomplete or inconsistent, and processes such as logging therapy sessions and generating reports are time-consuming and easy for errors. Additionally, people—including therapists and administrative staff—may be resistant to adopting digital systems or may lack proper training.
To improve the system, the clinic could implement an integrated rehabilitation information system. Providing portable devices or tablets would enable real-time data entry, while a unified software platform would streamline therapy tracking, scheduling, and reporting. Standardizing data entry, redesigning workflows, and offering staff training would further enhance efficiency. Overall, these improvements would reduce errors, save time, and enable better data-driven decisions for individualized patient care.
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Thanks for identifying the key issues, such as the incomplete implementation of multi-factor authentication (MFA) and the lack of a proactive security strategy. I would like to add The Zero Trust architecture could further enhance the system’s security posture. In this model, no user or device is trusted by default, and strict identity verification, authorization, and least-privilege access principles are enforced at every layer of the network. This would make it significantly more difficult for attackers to move laterally once they’ve gained access through a compromised account.
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Thanks for your comprehensive and and clear analysis of the SingHealth data breach. I would like to tell my opinion on some additional preventive measures that could help in mitigating similar attacks in the future. Beyond phishing awareness, it would be beneficial for organizations like SingHealth to implement Endpoint Detection and Response (EDR) tools. These tools provide real-time monitoring, automated threat detection, and the ability to respond to suspicious activity at the endpoint level. By detecting unusual activity on the front-end workstation early in the attack, the EDR system could have potentially stopped the malware from escalating further.
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Hi Nang!
The preventive measures you’ve outlined are also comprehensive, but I think there are a few more steps that could be emphasized or elaborated on to enhance data protection in similar situations. In this case, PHI was inadvertently shared with Google Ads. Anonymizing or pseudonymizing data before sharing with third parties (like Google Analytics or Ads) could reduce the risks of sensitive information exposure. Only data that is essential for the analysis or targeted ads should be shared, and all personally identifiable information (PII) should be anonymized wherever possible. Thanks for this case study. Data privacy and security measures should continuously evolve in response to new threats and vulnerabilities, especially when dealing with sensitive health information. -
Some possible means an attacker could use to conduct a security attack could be:
-Phishing mails are very popular and remain one of the most common methods of cyberattack worldwide. Attackers may send fake emails pretending to be someone or some organization or company name to trick the user into revealing login credentials or downloading malicious files.
-Exploiting weak passwords- weak or reused passwords can be targeted allowing attackers unauthorized access to electronic health records, for example.
-Network-based attacks- for example, Dos/DDoS by overwhelming systems with traffic to make them unavailable. Another one is MitM by intercepting communication between two parties.
-Malware-based attacks such as viruses, worms, trojans- attacker may use malicious software that damages systems or steal data, and ransomware which encrypts data and ask for payment. -
I would choose cloud server rather than physical server due to the following reasons:
1. Scalability and flexibility: The cloud server can easily scale up to handle more appointments or clinics if the patient demand increase, without needing new hardware.
2. Mobility: Patients and healthcare professionals can use the system from mobile devices or computers so it will be easier to schedule and check appointments without physically going to the hospital.
3. Data security: Cloud providers usually make regular updates to secure the sensitive patient data such as data encryption, secure authentication so that makes protecting patient information.
4. Maintenance and support: With limited IT staff, maintaining a physical server would be challenging. Cloud servers are managed and updated by the provider, reducing the burden on the hospital’s single IT officer.
5. Access to resources: As it is a cloud server, it allows authorized staffs and patients to access the appointment anytime and anywhere with internet connection.
6. Cost savings: Using a cloud server will be cost effective without needing to maintain as physical servers.
I suppose PaaS would be appropriate because it provides everything needed to build and run on the appointment system, while removing the burden of infrastructure management. It would be practical, secure, and cost-efficient for a hospital with limited IT resources. -
Health informatics play a vital role in outbreak management, especially in settings where vulnerable populations: such as children with disabilities need protection. During COVID-19 pandemic, many children with disabilities were at higher risk due to weak immunity and difficulties in accessing health services. I believe, through health informatics, early detection systems such as syndromic surveillance and real-time dashboards could be adopted to monitor infections also among these vulnerable groups. By developing skills in data analytics and interoperability, I could help design systems that ensure people with disabilities are not missed in the first stages of an outbreak, supporting both families and healthcare professionals, and community workers in real-time information.
In the response phase, digital tools like contact tracing apps and GIS can guide targeted interventions. To link with my current project, I have seen families struggle to reach health facilities due to mobility, financial, or communication barriers. Information skills would enable me to use GIS mapping to identify communities where children with disabilities live, so that vaccination for them or mobile clinics can reach out to their area. Mobile health applications could also be developed for parents. These technologies can make outbreak responses more inclusive and effective.
Long-term outbreak control and prevention can also benefit from health informatics. Immunization Information Systems (IIS) for example, can help track vaccination coverage and highlight children who might otherwise be overlooked in mass compaigns. -
According to my background, I already have clinical knowledge and experience working directly with patients, including working in the community for inclusion of children with disabilities. However, I would like to advance in the field of public health and health informatics, I would need to strengthen my skills in these following areas:
1. Data Science and analytics: I would like to learn the skills on how to collect, manage, and analyze health data to generate insights and support evidence-based decision making.
2. Public Health Knowledge: I need to gain knowledge about how population health, epidemiology, disease surveillance works to be able to connect the informatics skill with public health knowledge.
3. Information technology skill: As I came from the medical science background, I need to develop the technical skills in database management, statistical analysis, and programming languages that are commonly used in health informatics.
4. Ethics, policy, and management: Understanding data security, privacy, and health policy will make me able to ensure that health informatics solutions are ethical and align with the public health goals. -
Hello everyone!
My name is Yin Moe Khaing, you can call me Yin or Khaing. I am from Myanmar. I graduated from University of Medical Technology with a specialization in Physiotherapy in 2017. I am currently working as a physiotherapist at an INGO, working in the project related to Disability Inclusion for children with disabilities. Working at an organization and having to handle lots of data make me realize the importance of data management and healthcare analytics. My professional experience working with CwDs and in clinical setting have inspired me how health informatics can improve patient care, optimize healthcare system, and support evidence-based decision making. I see this program as a pathway to bridge clinical practice with technology. I am excited to join this program and aim to contribute my learning and skills in my community. -
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I completely agree that social media platforms have become powerful tools for disease surveillance and public health communication, especially during COVID-19. They allow rapid information sharing between health authorities and the public, helping people understand symptoms, prevention, and vaccination updates in real time.
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I agree that continuous data collection and monitoring are essential for early detection and timely response before the disease reaches epidemic levels. Using both passive and active surveillance is a smart approach—passive for routine monitoring of notifiable cases and active for rapid community-level intervention when there are outbreak signals. Thanks for your discussion, Ma Hteik Htar!
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Hi Ama,
Thanks for sharing your opinion about EPI data. Your mention of Variety and Veracity shows the complexity of EPI data, since it includes both structured (dosage, coverage rates) and unstructured information (adverse events following immunization), and is collected by trained staff using verified hospital records. This helps ensure reliability for disease monitoring. It is good to know this process. -
Hi Sayar!
Thank you for sharing your experience with the Community-Based Health App (CBHA) project. Digital literacy and limited internet connectivity are common barriers in community-based health informatics projects. It’s encouraging that practical solutions, such as offline data collection and uploading when connectivity is available, were implemented to overcome these issues. -
Thank you for sharing your experience with the EMR project in Yangon. It’s impressive to see how you implemented a comprehensive digital solution across three clinics, involving a multi-disciplinary team of developers. Technical issues, resistance to change, interdisciplinary communication gaps, and interoperability are common challenges in health informatics projects. It’s encouraging that you addressed these proactively through standby developer support, frequent training sessions, and regular check-ins between healthcare providers and developers. These strategies demonstrate thoughtful planning and collaboration, which are crucial for successful implementation.
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Your plan to implement a hybrid cloud model for the hospital’s information system is very well considered, especially given Myanmar’s challenges with electricity and internet connectivity. Storing sensitive patient data locally while using the cloud for less critical information strikes a good balance between security and accessibility. I also agree that cloud computing can significantly improve coordination among departments, streamline EMR access, and support faster decision-making during emergencies. Your emphasis on backup power systems, offline storage, and staff training is crucial to ensure continuity and smooth operations despite infrastructure challenges. I think this approach thoughtfully combines technology benefits with practical considerations for the local context. Thanks for sharing.
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That sounds like a very practical and patient-centered approach. A mobile app for scheduling and symptom tracking would empower patients to take an active role in their own care, improving both awareness and adherence to treatment plans. Including a self-evaluation tool or scoring system is an excellent idea. Thanks for sharing.
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I think your proposed improvements are practical and well-targeted. Implementing interoperable EHRs, streamlining workflows, and providing comprehensive training would go a long way toward addressing both technical and human challenges. I would also add that ongoing monitoring and feedback from staff using the system can help identify new issues early and ensure continuous improvement.
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