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In the health sector, efficacy is the capacity for the therapeutic effect of an intervention under ideal conditions. Although effectiveness has the same meaning as efficacy, it measures under normal clinical conditions to have a meaningful effect. Efficiency is the ratio of the output to the inputs of any system.
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I think the nature of the young is one of the important confounders. They held social relationships with meaningful, it is not surprised me that why they had the most active contact pattern than other age groups. Most applications aim to allow people to make relationships and communicate, so young adults also use applications to maintain or make the new relationships.
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I think we can change to use the new technology for easier use of the old technology. The TAM uses two factors to determine whether a technology will be accepted by its potential users: perceived usefulness and perceived ease of use. This model emphasizes the perceptions of the potential user. So, if the users realize that using the new technology would be a more accessible effort, they may believe that it would enhance their performance.
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AGE-SPECIFIC DEATH RATE
1. Definition:
Age-specific mortality rates is the number of deaths in a particular age group per 1,000 population in the same age group2. Calculation:
= (Total Deaths in Specified Age Group/Total Population in the Same Specified Age Group)X 1,0003. Usefulness:
Age-specific mortality rates allow comparison between specified geographic area and over time for specific age groups. Because all-age mortality is not very useful for health planning or monitoring, so we need to know how many deaths occur in different age groups. -
No.1 page 340
The P-value is the probability that the test hypothesis is true; for example, if a test of the null hypothesis gave P=0.01, the null hypothesis has only a 1% chance of being true; if instead gave p=0.40, the null hypothesis has a 40% chance of being true.–> The P-value is the probability of obtaining our results if the null hypothesis is true. The null hypothesis either true or false and we cannot interpret the p-value as the probability that the null hypothesis is true.
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So sorry for replying late
I’m Penpitcha Thawong, now I work as a medical technologist at Genomics Medicine and innovation support, Department of medical science. All of my work is about statistic, after whole genome sequencing, I need to clean up the big data and then summarize them to many other purposes; research, diagnosis, prevention, and treatment, for example. Moreover, now I am responsible for reporting the number of covid-19 testing of all laboratories in Thailand. The visualizations have been presenting on DMSc website, so everyone can download them. -
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Please go to link https://app.powerbi.com/view?r=eyJrIjoiYWJiYTQ3YzItY2UyMS00Y2M2LWI2NjYtMjFiNDlkZmVhNzZjIiwidCI6ImE1NjYxYjU3LTQ3ZDItNDNlNC04MGFhLWYxNzcwMTZhNTJmYiIsImMiOjEwfQ%3D%3D&pageName=ReportSectionc6b61be1c357e904e5ca to explore my COVID-19 dashboard.
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1. Why was the author interested in investigating the suicide problem in Thailand during the time?
– The number of suicides in Thailand has been increasing with an average of around 6 per 100,000 people during the period under study.
– the researchers wanted to observe factors that may have a relationship with the suicide rates.
– There was a very limited number of empirical studies that can be applied to Thailand.2. Each of the students picks one potential risk factor mentioned in the paper and explains how the variable can contribute to the suicide rate?
– the percentage of individual above 60
In the study, a rural area in the north and northeast region had a relatively higher proportion of age over 60, and also in the north had the highest suicide rate. In my opinion, in rural areas, elderly people may have got depression/loneliness because young people who go to work in the urban area, leaving their parents/grandparents at home alone. Or they might be widowed and cannot live alone. In addition, healthcare access for the elderly was found inadequate in Thailand. As a consequence of this, the suicide rates seem to be high among people age over 60.3. How statistical modeling can contribute to investigate the epidemiology and spatial aspects of the Thai suicide problem?
– The statistical modeling makes us understand the relationship between the factors that may cause suicides. We can also test to find a suitable model that fits the situation, and then the coefficients of each factor will tell us how strong a relationship is between factors. Then I think, we can descript and analyze geographic variations in suicide with respect to the causative factors. -
1. What are the possible reasons locations in epidemiological research have not been incorporated as much as other components in epidemiological research? ; How can spatial epidemiology be considered as an interdisciplinary science?
Mostly, the epidemiology course emphasizes students a statistical concept for instance: incidence, prevalence, relative risk, odds ratio, and many others. There are a study design sequence pattern and hypothesis testing that induce students to forget to think about other factors like location. It would be good if the course has more detail about the place, location, mapping, or even spatial epidemiology. At least student could familiar with how to apply information about place in their study research.2. Explain why it is widely recognized that the place where individual lives or works should be considered as a potential disease determinant and give some examples?
A good example of this question is Covid-19 pandemic, Covid-19 is a viral infectious disease that can spread rapidly from human to human. To do a contact investigation, the place that people usually go or stay with other people at the same time should be considered. Because they may spend the most time there for doing activities, and they are suspected to see each other many times. -
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I would like to share my dashboard, please go to My Dashboard
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Please go to https://app.powerbi.com/view?r=eyJrIjoiMDZhZDRkOTEtMmVjNS00MDYwLTkyYjMtZmM0ZjYzNGY1ZWRiIiwidCI6ImE1NjYxYjU3LTQ3ZDItNDNlNC04MGFhLWYxNzcwMTZhNTJmYiIsImMiOjEwfQ%3D%3D to see my dashboard
The visualizations cover 4 pages:
1. The overview of Covid-19 situation and case forecast 20 days (Confirmed, Death, Recovered)
2. Total number of Covid-19 confirmed cases by continent.
3. Daily confirmed of TOP 5 countries
4. COVID-19 situation by country -
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PENPITCHA dashboard:
https://app.powerbi.com/view?r=eyJrIjoiYzIyZjZiZWUtM2MxNy00NzU4LThlZjYtODZkNjM4NzM2Y2VhIiwidCI6ImE1NjYxYjU3LTQ3ZDItNDNlNC04MGFhLWYxNzcwMTZhNTJmYiIsImMiOjEwfQ%3D%3DThere are 3 pages of the dashboard:
page 1. I show the cumulative number of confirmed, Deaths, and recovered cases. They are summarised in a matrix.
page 2. A table contains population numbers, confirmed, Deaths, and recovered cases.
page 3. A GDP data is presented in matrix.All visualizations have slicer(s) that are used for filtering date, continent, even country.
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I would like to share a COVID-19 data visualization website named ‘worldometer’ that all of you can go to https://www.worldometers.info/coronavirus/. This website different from the others is that it does not provide only the number of new cases, confirmed cases, or deaths but it shows the number of total tests implementing in each country. There are various kinds of visualizations presenting in this website: Case progression by country, Cases: Europe vs. USA, Countries Case Distribution, and even Case Timeline, for example. The data showing in the worldometer is also quite up-to-date. If you go to the worldometer website and try to find Thailand in the Report coronavirus cases table you can observe that the number of total cases is 468,175. This information is very fresh, that is because I’ve just collected, summarised, and sent it to my bose on Sunday last week.
However, this website used to shared a wrong total tests number of Thailand that is because the last 2 months Thailand showed only the number of Patient Under Investigation (PUI). Therefore, we should have critical thinking when we saw any information.
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Both of your selected journals are very interesting, the first one, researchers try to make some visualizations explain a relationship between explanatory variation and Covid-19 incidence rate from global models and local models. Maybe this would be difficult for some people who do not understand the statistics. For the second one, they present many type of maps explain ten challenges in using GIS with spatiotemporal bi data. I think we can learn more from each figures and we can applied them in our work.
I think both are good and I want to figure out both of them. LoL I can’t choose.
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I agree with Thanachol, the main purpose of the first one is to study risk patterns of lung cancer mortality in northern Thailand and researchers present in Polygon pattern. Lung cancer is one of the highest burden in Thailand so I think it would be proper to our background. The second one was published from Cell Reports journal that has a higher IF score, the content is very interesting but it has other contents. As a consequence of this, The first one would be OK for this situation.
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Two of your selected paper have the same concept, that is about to create some methods related to GIS and do user assessment. The first one is good in terms of the audience relevant, but I think the content about GIS is quite a few. The second one, the content is quite difficult for me, however, I go with it since MBJ Global Health has a better IF score and more content about GIS. Moreover, I hope I can learn more from your presentation and get some concepts of map usage for public health planning and management.
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I totally agree with Aj. Saranath that we do not have an official position, most of the staff who seem to be health informatics have learned some special skill by experience at work. There is no formal education program in the health informatics field, so the informatics staff may be able to work on a particular scale especially in their job. This is one reason why I want to join this excellent BHI program.
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Before thinking about sharing data, we should aware that why we need to share, and what the pros and cons of data sharing in this situation will have occurred. I want to give you an example of a data sharing plan, in my organization, we have got the pharmacogenetics profile of the patient who received an allopurinol drug. The data is about allele HLA-B*58:01 Genotype, if the patients have the mutation in that gene they will have an adverse drug reaction. Therefore, for protecting them to the risk when they change the hospital, the data should be shared between the hospital. Now we are at the beginning of the process and we should give a consent form back to previous patients and the prospective patients should consent before receiving the service. Moreover, we need to think about how to share data over the hospitals about security, deidentification, avoid stigmatized individual data, interoperability, for example. I think this project will be a good example and then we can share other important data later.
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If we compare healthcare prices between the US and Thailand, it can be said that they are completely different.
The United States is mostly capitalistic that is an economic system based on private ownership. Medical price regulation mostly also depends on private sectors. Therefore some people may think better health services reflect how much they able to pay. whoever cannot afford it, they do not deserve it. It is a fact in a capitalist society. In Thailand, because of different settings, most Thai people can’t afford to pay for healthcare prices. The government can set the price and develop policy allows people to have more chances to receive healthcare services. Thailand UHC covers around 99% of the whole population, and for the rest, the government always try finds the way to help them. As a consequence of this, we cannot determine which country has the best healthcare system (price/service) because I believe that each country has its proper system fit to their social, political and economics. -
what have been seen problems with Net Pracharat and do you agree? (10 marks)
1) unclear purpose: I agree with Kanathip Thongraweewong that the government should tell the full scope of each project both pros and cons. The government wants Thai people in the rural areas able to access the internet because they have poor opportunities, so they should aware that the people in that area also do not know much about the risks, dangers, and downsides of the use of the internet/online activities. A knowledge about privacy and cybersecurity law is also important that people should know for applying in their real-life when they have to use the government service.2) slow internet speed and limited access area: from the example and my experiences, the free internet sometimes difficult to connect. Moreover, the speed is very slow because of many users, so It doesn’t seem to work for them. In the future, Maybe no one wants to use it.
3) unauthorize user: Although Net Pracharat allows users to log in using CID and mobile number, someone who knows that data can it to access the internet. Unpredictable, they may use the internet in improper ways.
4) puts user data at risk: As I said in the beginning, the users should aware about some important detail of cybersecurity act because they should know how to use the public internet in the right way and what they should not do on the internet: access personal bank accounts or sensitive personal data, shop online, for example.
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Change is one of the most difficult things for humans. At the beginning of using EMR, we think about financial issues: installing hardware and software, converting paper charts to electronic ones, and training the users, for example. There was a loss of productivity because of changes in workflow, and there also had privacy and security concerns because the information would be shared between many other systems. However, there are a lot of benefits, for example, higher-quality documentation, quick patient transfer between departments, easier to improve results management, no more handwriting problem, reduce time-consuming, and reduce human error.
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As Dr.Piya said, there are more data from digitization of health care and health services, and the challanges are how to use the information for value creation of health services and improving health system performance. Moreover, missing data, selection bias, data analysis and training, interpretation and translational applicability of results, as well as privacy and rthical issue are should be concerned. For coping all of the challenges, we should have a plan cover every approach: collecting data, quality control, analysis, systemically storing, etc. Good plan and preparation lead to a good performances. In addition, there are few clinicians and researchers received a formal training in informatics coding, data analysis, or other increaingly relevant skills to handle very large information. Therefore, it is very important to plan to training more staffs. Furthermore, when we implement follow the plan we should do the risk assessment and always improve the plan and mornitor the situation. As a consequence of this, if we do follow the plan, I hope we will have a high quality results with “least impact”.
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An example of health system improvement that I want to share hasn’t yet implemented, but it is a very interesting project that is sharing patient data between hospitals (interoperability). I believe that this program will improve many aspects of the health system if it is successful: sometimes some patients travel to many hospitals for treating their disease and the data will be recorded redundantly or some patients have adverse drug reactions history, for example. As a consequence of this, if we can link some necessary data between hospital patient would gain better quality and safety life and many others. However, there are some possible barriers that should be considered – we need to understand the personal data protection act for protecting patient data from unauthorized people or hackers, the inability to match the patient with the records between hospitals, lack of professional staffs, lack of technical support and infrastructure, and many others.
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Almost all of my organization work is about research-based, so there are many kinds of data such as whole-exome sequencing data, whole-genome sequencing data, microarray results, for instance, that we need to keep, and we are planning to share some data or results back to the owner. So a disaster recovery plan is very important to control the risk. Firstly, we need to know what can be the cause of diaster, and then classify them with building the risk assessment (which one can be the highest risk). Secondly, we should know the effects of each diaster and plan which technology is suitable for our situation. For my situation, I think there should have replicate data in case many users are doing different roles. However, if we have enough budget we should back up data everd day by using a incremental backup system. And we should have firewall to monitor incoming and outgoing network traffic.
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All data in the HIS system: medical information, laboratory information, patient registration, staff information, etc, is very important and it should be available all the time that we want to use. HA solutions keep your data as accessible as possible, even in the case of a partial server failure. Under HA technology, if one server fails, data can be operated from an alternative server, and the system can be upgraded and unplanned outages can be dealt with during the normal situation. Moreover, HA allows server share retrieval and computing loads between them, and when there is a lot of client request (workload capacity) the workload balancing can be applied for this situation, for example. As a consequence of this, the data in the HIS system will be available all the time and the users can use them quickly under good security.
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Three years ago, my office designed a web-based program for patient registration. However, the program didn’t have data encryption, so when the users forgot their password they will ask us to give them the password. This situation can cause patient information leakage. Now we want to redesign the program with an awareness of the CIA triad model.
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A good presentation and easy to understanding, I agree with Thanachol that the surveillance system should have not only following the new case but also old cases. Moreover, the presentation should give more details, for example, what data you want to show and how the users get to benefit from the data.
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I agree with all of you. For me, I think the first important thing that makes people get panic in the situation is a lack of health information about plaque. Moreover, many wrong information is rapidly shared via the social media. The people did not trust the government because of the last outbreak.
For this situation, if we don’t have sufficient information to share with the people, we can tell them the fact of plaque, primary protection, prevention, and treatment. The government should communicate with the influencer, affected persons, community group or any social media to spread the news. Importantly, people should be updated on how the situation is going, and where people can access more information.
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Thailand should have an early warning system for the Dengue outbreak. Now, Dengue in Thailand, there is an epidemic spread throughout the country. The distribution of the disease has changed according to the area at all times. Therefore, some areas that never face with Dengue, the Dengue outbreak may happen. The preparation of Dengue infection treatment and control will be ready if we have the Dengue early warning system. Hope that can be help to reduce the number of dengue cases.
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The air pollution situation in Thai hardly differs from New Delhi, India. The first time that we faced this problem, many people concerned and so serious with it, but in a short time, they can adapt themselves act like it is very common: do not wear a mask, do not talk about it, etc. However, for me, the air pollution seems to be deleterious today, and public health emergency should be declared by the government. And I agree with Dr.Saranath that we need to have a piece of solid evidence on the health impact of air pollution, and the government should have the policy to mitigate the risk. I believe that the strength of Thai government officers is government advocacy, so if the government is aware of this issue, every part of Thailand will help each other to solve the problem.
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Many health informatics issues seem to be related to a vision for public health surveillance in the 21st Century: big data, ethics, and regulation, data security, interoperability, health information exchange, project management for user-friendly. When we want to exchange the overwhelming data, and most of them would be patient data. First of all, we need to think about the regulation, laws, or even ethics above them. What information we can share or should not share? How to share? Then, security is the one that should be concerned, who will be responsible if the data is hacked. Moreover, to exchange the data between different programs, systems are not easier, so to make the system is work with every user (user-friendly) will be a challenging issue too.
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@Tullaya Fig. 5 in my presentation illustrates the spatial pattern of the drug-resistant pattern of Isoniazid, Streptomycin, Ethambutol, and Fluoroquinolone resistance in DR-TB patients and also shows the XDR-TB patterns. The researchers summarised the drug sensitivity pattern of DR-TB patients in table 2 but I did not show it in the slide, so sorry about that.
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TB cases can transmit in a community, How’s about applying contact tracking to monitor & control epidemic?
>>> This could help to see the overview such as which areas have a high incidence rate, and we can also use it to help when we do the contact investigation. I think if we have MTB genotyping data, we can link the patient infected with the same lineage and observe the disease distribution in the area of interest. This should help a lot to control the epidemic.
For the method, Clinico-demographic details were extracted from treatment cards. There are TB patient data only, but Latent Tuberculosis data is not included. It is possible to design data collection to collect data extensively.
>>> This study assesses the spatiotemporal aggregation of DR-TB patients, so I think this is a good start. They can do the same study with improving any limitations with other types of TB patients: HIV/TB, latent TB, and so on.Form Pyae Phyo Aung’s question, although geocoding is the strengths of this study (no selection bias) but it’s a limitation too (some case may fail to geotag). To solve this problem, Is there any technique or technology to represent geocoding?
>> For the limited time, I couldn’t answer the question in a proper way. I guess we can use Bluetooth techniques as some organizations use to tracking COVID-19 patients as we used to discuss in TMHG 529 subject.
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In my opinion, this can affect some results, for example, the red rectangular grids in Fig. 4 that represents the number of DR-TB patients more than 1. So if the DR-TB patients have been moving a place to go to another city, the sum of the area of aggregation in the square kilometers should be changed (decrease). However, this shouldn’t change that much if many patients do not move from the city during the study period.
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