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Tanatorn’s Dashboard: COVID-19 Data (2020-2022)
This dashboard presents an analysis of COVID-19 Surveillance data for 6 countries: Thailand, Brazil, Germany, Egypt, Japan, and Mexico. The report contains three key metrics: Cumulative Confirmed Cases, Cumulative Recoveries, and Cumulative Deaths as metric cards. Color-filled map of COVID-19 cases with color intensity representing number of confirmed cases. A line chart of time series reporting cumulative confirmed cases, recovery, and death distinct by color legends. The dashboard provided selective filtering by countries and date range. Also, it provided reset, download, and get link buttons. The data spans from 2020 to 2022, providing a comprehensive overview of the pandemic’s impact on each country over this period.
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I would like to introduce the dashboard that was released by the University of Virginia’s Biocomplexity Institute. It used to provide a real-time county-level data for enabling people to understand how their communities are affected. However, this dashboard was stopped updating since March 2023. Nevertheless, I think this dashboard would be a good sample to be discussed.
I like the way it classified Est.Active, Confirmed, Deaths, and Est.Recovered in different color both in table and analytic line graph. Moreover, when we hovered the cursor in the graph area, it displayed the number of that exact point. This table is simple and easy to understand. In the geographic dashboard, they use the color intensity present the estimate active, confirmed, death, and recovered. The higher number of patients will have higher intensity of color. -
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Overview of CRF (Format and Appearance)
Your CRF looks clean and consistent in format. There is a good selection of font type and size helps the user to smoothly record the data. The header contains the protocol name and ID, and clearly separates the visit screening and enrollment. Most questions are close-ended question. The units and formats are provided as appropriate.
The vaccination information – I agree with the data collection of vaccine information (kit number, lot number and expired date), this helps to ensure that subject received the right product administration according to randomization
Room for Improvement: (Please be considered this is just from my opinion)
1. Flow of Study Procedure:
Informed Consent Sign: Your CRF design mainly follows the flow of study procedure. However from my understanding, the CRF would be better to start with informed consent form. As we need to ensure that the subject understand the study and willing to participate in the study before performing any study procedure.
2. Identifiable Information
Date of Birth – To ensure data is unidentifiable, it is recommend to collect only Year of Birth , ( not the full date of birth)
3. Redundancy
On Physical Examination Domain: There is the fix choices which I think it is for question of Pregnancy and lactating status, but I believe there might be an typo error. Please recheck.
4. Additional Questions
Eligibility Check: I can see that all questions in this part can cover all the things to be checked for inclusion and exclusion criteria. You may also list down the questions according to inclusion and exclusion criteria directly. One more thing that I would like to recommend is that as it may follow with the question “Is participant eligible to participate in the study?”, there might be an additional question which will collect the reason of “No”.
For example: If No, please provide the reason___”Fail to meet inclusion criteria #2”_____ , (let the user describe the reason).
By doing this, it could help the data reviewer to check the eligibility of subject easily and quickly.
Vaccination Administration: For the question “Injection site”, I think we can set the fix choice for the user such as “Right upper arm” or “Left upper arm”, to reduce inconsistency of the answer and easy for data cleaning.
Please feel free to correct me if I misunderstand anything. Thank you so much.
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The first things that I could think of is that the data standards allows for better interoperability and increase data quality when data sharing between different research studies, institution, and healthcare systems.
For example, if every clinical trial used a different format for collecting and storing patient data, it would be challenging to combine and compare results across various studies. By using a standardized format for data collection and storage, it would be simpler to combine data from different studies and gain a more comprehensive understanding of a particular disease or treatment.
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I have an experience to be in a part of clinical research studies. I can see those studies involved these process, however I did not have much details about data backup and recovery plan process. I think this supported by the software.
The software that I have experiences are electronic data capture system, including Viedoc, iMedidata and ClinicalOne (Oracle).
Audit trial/Time stamp: I got a chance to be a part of user as well (for iMedidata). I can see the audit trail in the system every time when the data entered or edited. The system will show which user was performed and the time that was entered/edited.
User authentication and access control level: All the softwares that I experienced are required one account for one user. Every user must be authorized and well-trained of EDC system. Different types of user may have different access permission and limited function in EDC depends on each role in the study.
Edit check and logical check: I have a little experience on this. But I have a chance to configure the system and design the edit checks using Viedoc EDC system. The software provides some build-in functions to generate the simple edit check such as preventing future dates or setting visibility of some fields/questions. The logical check is mostly designed by using simple JavaScript code to validate data consistency within the page and across the pages.
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To avoid the thing that could be calculated such as BMI, we may not need users to calculate BMI by themselves and record data in CRF. However, BMI can be auto-calculated by using value of weight and height. Moreover, there must be a unit and space with decimal number provided for weight and height as well, to ensure the same standard format.
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I recently started a new job as a clinical data associate. My main responsibility is to support the lead data manager in handling all data-related tasks of clinical research studies. While I have some experiences in the early stage/initiation process, I have yet to gain much experience during the conduct or study end. Instead of going back to improve previous projects, I will use all the steps to integrate standardized data coding and data management into my future work. To ensure that the data we work with is of the highest quality, one of the important process is the data quality assurance, which includes:
– Reviewing the trial protocol and ensuring that the trial is carried out according to plan (no PD/PV identification).
– Identifying trends in subject sampling and data.
– Reviewing measurements and staff compliance according to regulations to identify any areas of improvement.I believe that following these processes will help me perform my role effectively and efficiently and lead to better outcomes. Thank you very much.
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From my two years of work in the clinical research field, I gained experience in the data collection process when I was a study monitor. Please allow me to share one of the clinical research studies that I worked on, which was a vaccine study. The subject data was mainly recorded in electronic data capture (EDC), and one method used in data collection was the subject diary. This is considered primary data collection. The subjects would self-record their symptoms in the diary by rating the severity of each solicited symptom, such as fever (body temperature), myalgia, or injection site pain/redness, etc. (using a closed-ended question with a rating scale). The instructions for measuring each symptom were clearly written in the diary paper, and the instruments for measuring, such as an infrared thermometer and ruler, were provided.
Most subjects were able to record the data of their symptoms completely. However, when it came to other symptoms (unsolicited reaction), the subjects have difficulty to record the data properly since the instruction and the example are much details and quite unclear. At that time, as the subject could not write their symptoms directly in the diary, the site staff has retrained the subjects and consulted with them to ensure that all information was gathered completely. However, we also need to concern about the interviewer’s bias with this process.
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I would like to discuss the point number 12 on page 342. This point mentioned the common misinterpretations of single P values that “P values are properly reported as inequalities (e.g., report “P < 0.02” when P = 0.015 or report “P > 0.05″ when P = 0.06 or P = 0.70)”.
The practice of reporting P-values as inequalities, such as ‘P < 0.02’ or ‘P > 0.05’, can be misleading and may not accurately reflect the actual probability of obtaining the observed result.
Reporting P-values as inequalities may be acceptable when the P-value is very small (e.g., below 0.001), as the difference between P-values at this level is not vital. However, when the P-value is bigger than 0.001, it’s better to use the exact P-value to provide a more accurate and precise statistical results. We should also think about the assumptions and limitations of the statistical method used to get the P-value when we report statistical results. Sometimes, alternative measures such as confidence intervals or effect sizes may provide a more informative summary of the results.
In conclusion, while reporting P-values as inequalities may be acceptable in some situations, it is better to report the actual P-value to provide a more accurate and informative representation of the statistical result.
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Just notice that non-identifiable data in combination could identify someone particularly.
Myself, the non-identifiable data of the following combination could identify me.Previous graduate : Faculty of Pharmaceutical Sciences, Khon Kaen University
Current education : MSc, BHI, Mahidol University
Current job and workplace : related to Data Management, Clinical research organization, Clinixir, Thailand -
To understand why respondents are not using bednets for malaria prevention, I suggest conducting a review of existing research as a first step. This can help identify common reasons for not using bednets to prevent malaria. Additionally, if the demographic data are collected, analyzing demographic data, such as age, gender, education level, and socioeconomic status, if available, may reveal patterns in not using bednets. Another approach is to conduct follow-up interviews or surveys with respondents who reported not using bednets (focus group). These interviews, possibly via phone call or in-person interview, can provide deeper insights into the reasons why respondents are not using bednets to prevent malaria.
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When replacing an old technology with a new one that is easier to use, at least it should be as useful as the old technology, if not more useful, to ensure user acceptance. If users perceive the new technology as less useful than the old one, they may be resistant to adopting it, even if it is easier to use.
To encourage the adoption of the new technology, it is important to communicate its benefits to the users and demonstrate how it can improve their productivity or performance. Involving users or key influencers during the technology’s design phase can impact their perception of the technology’s usefulness and ease-of-use, potentially reducing its perceived complexity. Users are more likely to accept a new technology if they perceive it to be less complex, so simplifying the technology’s user interface, providing clear instructions and guidelines, and offering training and support to users are all essential steps to increase new technology adoption.
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I agree with all colleagues’ comments. There are several external variables that can influence an individual’s perceived ease of use or perceived usefulness of a new technology, including:
First, Socioeconomic status and Accessibility;
People with higher socioeconomic status may have greater access to technology and may be more familiar with its use, which can affect their perception of the usefulness and ease of use of new technologies. Moreover, the accessibility of different devices may affect an individual’s perception of its usefulness and ease of use.Second, the Age, Experience and Culture;
Different ages may have different cultures. Younger people may have different attitude towards new technology from older people. They may find it easier to use and understand new technologies than older people who did not have access to technology when they were younger.Lastly, with a technical support and training of new technology, it can affect the perceived usefulness or ease of use in any kind of people with different backgrounds mentioned above. For example, if a user receives a training and has access to good support resources, they may be more likely to perceive the technology as easy to use and useful.
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Efficacy refers to the capability of an intervention to produce a desired outcome or effect in a controlled or ideal setting. For example, the efficacy of new flu vaccine has been shown in a randomized controlled trial to reduce the incidence of influenza in healthy individuals by a certain percentage.
Effectiveness is a measure of how well an intervention performs in real-world settings, demonstrating its ability to produce meaningful effects. For instance, to identify the effectiveness of a new asthma medication with the reducing of frequency and severity of asthma attacks in patients who use it regularly.
Efficiency is the ability to provide interventions using minimal resources, time, or effort, while still having the desired outcome in an economical manner. For example, the hospital may use telemedicine to provide consultations for certain types of appointments, and communicate with healthcare providers remotely, which results in more efficient use of healthcare resources and better patient outcomes.
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I agree with my friends’ previous answers, and I can think of another confounding factor: living area and location. Since we don’t know the demographic characteristics of the study subjects in Thailand, the location setting could affect the relationship between age and contact patterns, leading to incorrect conclusions.
For instance, young adults may tend to live in urban areas with higher population densities. These areas typically house top colleges or universities, as well as workplaces that require frequent social interactions. Furthermore, urban areas often offer numerous social activities that are attractive to young adults, who tend to have more active social lives compared to other age groups. Due to the higher population density in urban areas, young adults may be more likely to use contact tracing applications and had the most active contact pattern than other age groups.
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As per the Centers for Disease Control and Prevention (CDC) website, the mortality rate is a measure of the frequency of death occurrences in a particular population during a designated time frame. The formula used to calculate the mortality rate of a given population over a specified period is as follows:
Calculation: Mortality rate = (Number of deaths occurring during the given period / Total size of the population at risk during the same period) x 10n (with n typically being 1,000 or 100,000).
Usefulness:
– Identifying health problems: Mortality rates can reveal health issues in a population, such as high death rates from certain illnesses. This can help government officials decide where to focus interventions to decrease mortality and enhance overall health.
– Monitoring progress: Mortality rates can track progress in reducing death rates from specific causes or overall mortality over time. This can help evaluate the success of interventions and support policy-making.
– International comparisons: Mortality rates can be compared across countries to identify variations in health outcomes and healthcare systems. This can highlight effective approaches and help shape global health policies.
– Informing research: Mortality rates can help in designing research questions and hypotheses by identifying specific risk factors or underlying causes of death. This can lead to the development of targeted interventions and policies. -
The Universal Health Coverage (UHC) system aims to cover a wide range of health issues for the maximum number of people, while sustaining and adequately financing the system without incurring out-of-pocket expenses.
In addition to the information mentioned by my classmates, I had the opportunity to discuss dental health with a dentist in regard to UHC. The strength of UHC is that it provides free benefits to patients for both dental health promotion and basic treatment. However, there are limitations in accessibility and availability, particularly in rural areas where only dental hygienists are available, even though the number of dentists has increased. Currently, any dental procedures performed by dental hygienists must be under the supervision of a professional dentist. The National Health Security Office (NHSO) is planning to deal with this policy, to accept the ability of dental hygienists to provide health promotion and basic treatment, thereby promoting early prevention of complicated dental health issues in rural areas.
Similarly, patients, in rural areas, lack knowledge about their rights to medical and dental benefits, and a telemedicine system could be implemented to allow patients in remote areas to receive consultations and treatment remotely. However, oral health evaluations may not only require a video phone call but may also require specialized devices, which presents another limitation for teledentistry.
Therefore, I can conclude that the UHC scheme in Thailand provides many benefits to patients but still has a gap in accessibility in rural areas for both medical and dental health. From my understanding, telemedicine could somehow solve this gap for basic treatment, however, not do much for a dental assessment. Higher technology, such as intraoral cameras, may require for teledentistry which finally could lead to early detection of dental problems and increase awareness of dental health prevention.
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During the COVID-19 pandemic, I worked at a clinical research organization and was not directly involved in the control policy for COVID-19. I used to work the same job as K.Kansiri and my practice under the organization is quite similar. As a Clinical Research Associate (CRA), I had the opportunity to be responsible for monitoring a COVID-19 vaccine study. I would like to share some ideas for practices that I believe can contribute to the COVID-19 policy.
First, policy should be based on evidence support. With the disease rapidly spreading, research must also respond quickly. The data collected during research should be accurate, reliable, and used ethically and responsibly, with patient safety and well-being are the primary concern. Data sharing and monitoring might be used to evaluate the effectiveness of COVID-19 policy in some aspects.
Additionally, multi-disciplinary collaboration is crucial. COVID-19 research should involve collaboration between experts from multiple disciplines, including public health, epidemiology, virology, and economics, to inform policy decisions.
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Health informatics is a field that includes a diverse range of professionals, including those who specialize in health information management, clinical informaticians, IT experts, data analysts and scientists, project managers, and educators. However, in my country, there is a general lack of awareness and understanding of the field among the general population, which has led to fewer individuals interest and go for education and training in health informatics.
Another challenge facing the health informatics workforce in my country is the limited availability of education and training programs in the field. This results in a shortage of professionals with the necessary skills and knowledge to work in health informatics.
As technology in the field of health informatics continues to advance, there is a growing need for healthcare plus IT professionals to stay update with new technologies, which can be costly and require ongoing professional development. Additionally, the interdisciplinary nature of health informatics requires collaboration and effective communication among healthcare professionals, IT specialists, project managers, and other experts, which can be challenging.
I honestly did not have a board knowledge on this situation, thus the above details are from my perspective. Please feel free to add comments or advise as appropriate. Thank you.
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In my opinion, data sharing is a crucial aspect to consider for several reasons.
Firstly, it is important for data sharing to ensure the privacy and security of individuals whose health data is included in the dataset, through processes such as de-identifying the data or limiting access to authorized individuals.
Secondly, it is essential to weigh the potential risks and benefits of sharing health data, and to ensure that any sharing of the data is aligned with ethical principles such as informed consent.
Thirdly, health data sharing can facilitate the discovery of new insights and knowledge that can improve patient care and lead to new treatments and therapies. The data sharing may increase the overall efficiency and effectiveness of research by allowing others to build on existing findings and data.
Furthermore, ensuring the quality of data sharing is also critical. The data should be accurate, reliable, and kept up-to-date. This can be achieved by implementing policies for data standardization and ensuring the data is shared securely.
Considering if the data should be paid for, there are different perspectives as follows.
Some may argue that data should be considered a valuable resource and those who generate or collect it should be compensated for it. This may include hospitals or medical institutions that conduct clinical trials and collect data from patients or participants.
Others may argue that it is a public good and should be freely available for the benefit of society as a whole. This may include government-collected data or data generated through publicly funded research. Additionally, there could be a point of view that health data is personal and sensitive information, and should not be paid or used for profit.In conclusion, sharing data can be a valuable tool for scientific and technological advancement, but it is important to ensure that the privacy and security of individuals are protected when data is shared. Whether the data should be paid or compensated for may depend on the type of data. To make a decision, it’s important to weigh the value of the data, the costs of collecting and maintaining it, and any ethical and social implications.
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Since last 4-5 years ago, I have joined a private hospital as an IPD pharmacist. During that time, the hospital had recently implemented the electronic medical records (EMR) and encouraged healthcare workers to use it instead of paper-based medical records. It took a long period to fully utilize the EMR as it is a major change of workflow in the department. Please let me share the pros and cons of using EMR as the following.
Pros:
– Considering patient safety, EMR could reduce risk of medication errors. For examples,
— Prevent prescribing error; EMR system included clinical decision supports such as suggested dosing regimens, aware of adverse events, drug allergy and interaction alertness. EMR provides better prescription with a complete regimen without abbreviation
— Prevent dispensing error from misreading of handwritten prescription
Therefore, improve process quality– Controlling accessibility level: EMR requires username and password to log-in and limited access for different types of users. Thus, better patient health data security and privacy
– Tracking on data changes over time
– Better communication interoperability
Cons :
During transition of EMR, the design of user interface may not be applicable to most senior staff users and moreover, time consuming for learning new systems and operation. Sometimes, electricity failure could affect the EMR system down time. If EMR has a low security process, it could be a risk of cyberattack.Training of staff/personnel and encouraging the benefits of using EMR are important keys during the initiation. Later on, the feedback and complaints from direct users are essential to system development.
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The challenges are in every step of Big Health Data management, starting from the source of data collection to its application. In this articles, Silverio A, et al. had mentioned the challenges of big health data and how to deal with those challenges, including;
Missing Data: The missing data in big health data is uncontrollable. Thus, this article suggested several methods for handling a large number of missing data, such as Imputation technique, Mixed effects regression model, Generalized estimating equation, and Inference. Several methods suggested to handle miss data that is less than 10% would remain the same distribution and prevent any outlier data.
Selection Bias: A large scale of health data from EHR would have many confounding factors as the data are from different sources, interventions, inconsistent, and independent. Big data is observational studies that reflect actual cases in the real world. I believe that the information from Big data analysis would be an important element that supports the randomized controlled trial design to confirm the hypothesis.
Data Analysis and Training: I personally believe that more clinicians and researchers are interested in training on big data analysis using appropriate statistical and methodological tools. However, only few researchers are able to interpret with more complex data. It would be great if clinical researchers themselves are trained with informatics, coding, data analysis, etc. The availability of well-trained researchers are required as advisory.
Data Privacy and Ethical Issue: Health data in Thailand are mostly centralized. The data confidentiality and privacy are primary concerns. The Personal Data Protection Act (PDPA) is implemented in Thailand to handle ethical issues. Patients provide their broad consent to allow using their health data on further research. However, we also need to ensure that our system security is good enough to protect data from cyberattackers.
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I agree with all recommendations provided in the articles. Fighting corruption would improve the health system and reduce health inequality.
For the first recommendation, I think convening key stakeholders would impact the change in policy-level. In this level, anti-corruption could be effectively executed. However, population power also matters. I think if the agreement is publicly open to be verified and partially accepted by the population, this may help anti-corruption become more decentralized and effective.
I also agree on the second step. Focus on the impact and vulnerable group would make the agreement and policy leading the big change to the health system and anti-corruption.
I partially agree with the third recommendation. I believe the earlier steps are impactful to draw attention. It is good to have research on corruption published in a healthcare database, however not many people will read that journal.
Finally, the research community is important. Once we develop the policy or agreement, we can know the feedback using the “big data” from social network analysis. The feedback could represent the room for improvement. Lastly, Thailand needs a good leader and a power of population that leads to an anti-corruption system.
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Recently, the new health system was announced by the National Health Security Office (NHSO) with regards to free drug dispensing in the drugstore setting. Patients who have common illnesses, such as fever, cough, sore throat, headache, dizziness, stomachache, diarrhea, constipation, etc., can receive treatment according to their rights (Universal Healthcare Coverage) for free of charge at the nearest registered drugstore. This system aims to improve both the hospital system and patients.
For hospital aspect, the system
– decreases the burden of healthcare providers in the hospital
– reduces crowded condition in hospital
– less risk of infection spreadingFor patient aspect, the system
– reduces time-consuming
– reduces traveling cost
– increases treatment accessibility
– increases the health awarenessIn case more patients decide to visit a drugstore, the barrier that could occur would be
1. insufficient pharmacy resources, including both approved drugstores and trained pharmacists
2. Possibility of missing claims data, causing difficulty in claims reimbursements
3. Increasing of drug store pharmacists workload per patient
4. If the drugstore doesn’t have standardized electronic medication records that can be interoperable to hospitals, it would be almost impossible to track medication history.Please feel free to share the idea on this topic.
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(Please accept my apologies for the delayed response.)
A disaster recovery plan is very important to the overall business continuity of the organization. It protects the organization from a negative event or other major disruption of information systems.
First, we are going to start with the identification and analysis of disaster risks or threats. While identifying, we categorized the risks into different classes. Then, we will assess and score the major risks in terms of likelihood and impact. This also includes identifying which systems and data are critical to the organization’s operations. It will help to prioritize the recovery efforts and ensure that we restored the most important systems and data first.
The risk for my organization could be power supply cuts and unexpected computer downtime that need to be addressed by a disaster recovery plan.
The disaster recovery plan will include a detailed backup and recovery strategy that shows how the organization will protect its critical systems and data in the event of a disaster as fast as possible since the organization/hospital works 24 hours a day. This may include using backup and replication technologies to create copies of data and systems that can be later restored quickly in the event of a disaster. I would consider using cloud-based disaster recovery solutions, which can provide off-site storage for backups and replication of critical systems and data.
Once we have a recovery plan, we will establish a procedure that should be simple and clear for recovering from a disaster. Communicating plans with stakeholders, such as healthcare providers, patients, or partners, will be included in the plan.
The plan will be tested periodically to ensure its effectiveness and that all stakeholders are familiar with their roles and responsibilities during the event of a disaster. During testing, we might identify a gap or weakness that should be updated in the plan.
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Apologize for the delay in response.
In the patient aspect, implementing “High Availability” technology in the hospital will reduce the patients’ waiting time when they visit the hospital because of the fast and good quality of hospital services. The hospital systems will run smoothly with no interruptions.
In the hospital aspect, implementing “High Availability” technology in the hospital will minimize the system downtime and ensure data availability and is always ready to access. Using RAID technology, could provide system redundancy and protects the data against loss. Load balancing technology would assist the hospital system distribution of workload across the servers. Therefore, reduce downtime and provide healthcare service to the patient faster. -
The STEEP analysis is used to identify the external factors that could significantly impact an organization. We can analyze the past and predict the future. The following STEEP listed the future factors which are uncertain and might affect health resources during the COVID-19 pandemic.
Social:
– Increasing awareness in the population to prevent infection -> fewer people get sick
– Increasing online education (as well as in healthcare) in the population -> increasing health knowledge
– Increasing demand for personalized care services -> Better healthcare service requires
– More healthcare workers interested in health technology -> Increasing future development of healthcare service (also Technology impact)Technology:
– Increasing research and development of new medicines and health innovation
– Due to travel restrictions and social distancing, there is a rising development of eHealth technology -> New implementation of eHealth standards may require.
– Low internet accessibility in Thailand: there would be an increasing consideration for Internet access in rural areas to get the most benefit from health technologyEconomic:
– Financial crisis due to more cost of healthcare resources required for pandemic infection management.
– Insufficient supply of quality vaccines and anti-viral medications for the populationEnvironmental:
– Strictly managing infectious waste and disposable medical devices
– Increasing waste of plastics, disposable gloves, masks, etc. affects an environment
– Traveling restriction during the pandemic helps to save the environment from pollution or carbon emissionPolitical:
– Creating an adoption of licensing rules to have electronic technology service
– Creating a policy for data confidentiality and privacy -
Firstly, I have never been involved in information system design and so I have no experience in not being able to preserve the CIA as well. But let me share one experience that may nearly impact information confidentiality. I was once experienced working as a clinical research monitor and needed to access the EMR system at the clinical site to monitor the subject’s clinical history. However, this site did not request access for external users. Therefore, I need to use the study coordinator’s access to the EMR system with an over-the-shoulder method. This should be prevented by requesting CRA’s access at least 1 month before the visit. It is good that this site has access control of different levels to ensure that the user can get the right information without accidental access to any sensitive information.
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Singapore President Lee Hsien Loong:
I quite appreciate PM Lee Hsien Loong on his public speaking. He utilized all CERC principles in his speech. (Be First) Within 2 weeks of COVID-19 spreading in the country, he quickly shared the situation first. (Be Right) He explained what is known, where we are, and what we line ahead. He informed what have been prepared to be ready for the situation such as the availability of equipment, healthcare staff, and ongoing study research. (Be Credible) He knew the situation and manage to respond promptly and make the public trust with experienced SARs management and scientific evidence knowledge. (Express Empathy) He showed his understanding that people facing this disease may fear, panic or do things that make matters worse, like circulating rumors online or blaming particular groups for the outbreak. He promoted people to be mentally prepared and self-protection with simple steps that would contain virus spreading (Promote Action). Overall, he showed respectful communication by understanding the different people’s concerns and putting inspiration to the population (Show Respect).US President Trump:
His speech is not quite early as the disease has already been announced for a global pandemic by WHO. (Be right) He informed the people about what is known or in-discussing and what has been done so far to manage with COVID-19 situation. As he talked about financial support and national health coverage, it seems that he tried to show empathy with people’s challenges (Express Empathy). However, he is quite providing too much self-confidence in his management but did not show many people respect. He tries to promote health protection with simple messages to stop COVID-19 from spreading (Promote Action).In my opinion, Singapore’s President provided better communication, by starting to make people trust and finally end up with people’s cooperation.
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Firstly, I would like to commend your efforts in creating a COVID-19 dashboard. It is evident that you have invested time and energy into developing this tool. However, to further enhance the user experience and maximize the dashboard’s effectiveness, I would like to offer some constructive feedback from my opinion:
1. Consider displaying the COVID-19 case numbers in a more concise format. Instead of showing the full numbers, employing a compact representation of the numbers on metric cards, for example: 330M.
2. Improve the user experience of country filtering by simplifying the design. Instead of overwhelming users with an extensive list of countries, consider implementing a user-friendly interface that allows for easy and intuitive selection, such as dropdown menus or search functionality.
3. Enhance the map chart by including clear legends and scales.
4. Adjust the time series chart to display data in the correct chronological order, from past to present. This adjustment will prevent potential misinterpretation that may arise when the chart is presented in reverse order.
Overall, I appreciate your dedication to creating a COVID-19 dashboard and the valuable insights it can provide. Implementing these suggestions will help refine the dashboard, making it more user-friendly, visually appealing, and effective in conveying critical information to the audience. Thank you.
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I agree this is quite challenge on how to make people comfortable to provide their data even though their oral health since they are concerning on the bad smell breath and food impaction. Thus, interpersonal skill to make people trust in interviewer/data collector is very importance as well as standardization and completeness of data. Thank you so much for sharing your experience.
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Thanks for introducing a new health system. I never experienced this kind of SIP. But I understand its advantage. This system is more formal than using LINE and all the evidence could be captured with SIP, unlike LINE.
I agree that the most important thing is the training and explain the importance of using SIP since Site Initiation Visit (SIV). While the new features updated, all the stakeholders should test and evaluate before it launch. -
Hi Zarni, Unfortunately, I could not find any paper written in English.
There’s only in Thai, which is a news/announce from Thailand NHSO website.
>> https://www.nhso.go.th/news/3809
If you are interested, you can visit the website and use translation tools. Sorry for inconvenience. -
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Good work creating the workflow for the staff to understand and follow.
However, I spend a little longer time making decisions for the questions including not/could not and answering yes/no. I would like to propose using simple questions in the decision node. (Ex. Nearly expired discount allowed?). This is just my personal view but overall your process is well-done ka. -
I deeply understand your situation as I had experienced a similar issue before, but I could not make it to discuss it with PI. I really respect your leadership to get out of your comfort zone and run through obstacles. This is such a big step for young CRA like us. 😂
Nice to know your story. Cheer up!
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