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Efficacy is usually used in scientific setting under very specific and controlled conditions. It indicates whether the intervention can achieve the desired result or not.
Effectiveness is the measure of how well the intervention is in the real-world settings. It might be sometimes difficult to achieve high effectiveness even the interventions have good efficacy because there are many unpredictable and uncontrollable factors in real life.
Efficiency is different from the prior two points above since it is not only about performance. But it also considers the input. Efficiency measures outputs and inputs. Some interventions might have good efficacy and effectiveness but very undesired efficiency. For instance, some intervention that can provide good effectiveness but consume a lot of budget and workforce.
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I think that awareness of project’s importance might be considered as confounders in this case.
– Young adults are the group understanding how beneficial is technology. Thus, it might lead to higher number of young adults intending to use the application constantly because they know that technology can finally provide benefits.
– Young adults are mostly affected from the disease since they have to socialize for the purpose of works and social importance. They might aware that the project can be helpful. -
I am interested in Case-Fatality rate (range 0-100%) or sometimes called case-fatality ratio (0-1).
The definition of case-fatality rate (CRF) is the measure of number of confirmed deaths among number of confirmed diagnosed cases for particular disease during a given time.
To calculate CRF we can use the formula CFR in % = (Number of deaths from disease/Number of confirmed cases of disease) x 100. And if we want to calculate in ratio, we can use the same equation without multiplying with 100.
CRF can be very useful to indicate severity of particular diseases that can indirectly tell us about prognosis of the disease. Consequently, we can manage the resources needed for treatments and controlling the diseases.
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I strongly agree that the new technology replacing the old one should be at least as useful as before. There will be many resources, such as workforce, investment, and time, needed in the process of technology implementation. So, it is nothing to implement the new technology without any improvement.
Other than the usefulness of the technology itself, awareness of all stakeholders on the usefulness of the technology is a vital factor to be considered. Thus, responders should communicate to all stakeholders to let them realize the usefulness.
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I agree with all comments above. Factors including personal factor (Age, Experience, Digital literacy) and others are vital for technology adoption.
However, from my experience, Support is the most important factor. Many struggles can be solved with a decent support from executives and IT team. For instance, some people with bad experience using IT and low digital literacy can be assisted with good support system that can help them to be able to use the IT system easier and more effective.
Another factor not yet mentioned but, in my opinion. is very effective is incentive. I read some articles about incentive and HIS adoption in the USA and I found that incentive can be a big positive factor in IT adoption.
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I would start figuring this problem by
1. Research more articles and research papers relating to this problem.
2. Perform interview with specialists especially local experts.
3. Conduct interview. I would go for semi-structured interviews that can provide me both expected answer and might provide unexpected views from the respondents. -
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I would go for the point No. 11 that said P=0.05 and p < 0.05 are the same.
The point was described using analogy that said have the height less than 2m and equal to 2m are not the same. When we talk about less than some certain values, it means we don’t include the value. In stats, p = 0.05 and p < 0.05 are completely different. Thus, we, as readers or researchers, should carefully take this into consideration.
As a physician, I’ve experienced many physicians always look at P-value to make decisions if they intend to accept research outcomes. This is the good point that reminds us to interpret the outcomes more precisely.
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I also curious the same issue as Kansiri.
As I know from searching in the internet.
I found the formula to calculate lift as this picture
Formula of Lift (ref: https://bigdata.go.th/big-data-101/data-science/what-is-association-rule/)From the formula, in my own understanding.
If lift of A -> B is high, it means that we won’t see A or B frequently among all data. but we see A and B frequently. That makes high lift value when we calculate it. That’s why higher lift value, more interesting the rule is.For interpretation.
If lift > 1: positive correlation.
If lift = 1: A and B might be independent.
And if lift < 1: Negative Correlation.I hope this can help. And please correct me if I understand incorrectly.
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This is my Final Dashboard.
My Dashboard is quite informative but not to deep in-detail and I want all information to be in just 1 page.
I want people to understand big picture comprehensively about Covid-19 Situation.The dashboard include.
1. 3 Card to give number of Total cases, Total Deaths, Total Recovered cases.
2. Matrix that provide deeper information, exact number for each continent and countries (notice that total row is not equal to the number on the cards above because I exclude some data such as Summer/Winter Olympics)
3. Line chart that provide total cases from starting to current dat with trendline and prediction. You can select time period by sliding the gauge below the chart.
4. Donut chart to give information about proportion of cases in each continent.
5. Map, that I decide to start with continent because it’s cleaner and easier to look than starting with country. but you can drilldown to see each countries’ bubbles.
6. 100% stack column to give information about changes of proportion between continent. I want people to know how covid-19 pandemics changes over time in term of affected area.
7. Daily cases chart to let people know how severe is Covid-19 pandemics compare to past.
8. Slicer to filter by area and by date.in term of human perception.
1. I try to use as less colors as possible.
2. I use line chart without area to make it looks clean.
3. I use donut chart to represent proportion because it contains both angle and length.
4. 100% stack column chart is also easy to look at a certain time because it contains both area and length( if we look at a single time point)
5. For the map. I think showing bubbles as a country is a bit difficult to read. So I decided to show the continent bubble first to make it looks cleaner and people can drilldown deeper if they want. Continent bubble is also easier to interpret than countries’ bubble in term of bubble size. -
Here is my My Dashboard
1. The First Page is overall page
– Use Card and Multi-Row Card to display big-sized number of Total Cases, Total deaths, and Total Recovered.
– I decided to use donut chart to demonstrate Proportion of Total case by Continent to let you see big picture of covid19
– I used line chart with trends line and prediction to represent Total confirmed cases by time.
– Slicer to filter by location to be able to see in detail.2. The Second page provide more dynamic detail.
– First, I used map to give geographical information about total cases in each area. Bubbles’ size represent number of cases.
– I put 100% stack column to represent proportion of cases by time and put color for each continent. This will help you to see changes of Covid19 situation dynamically during the last 3 year.
– I also put bar chart for daily cases that use legend to identify continent that help you to see more detail other than just proportion in each continent.3. The third page
– Stack column and line chart demonstrate Total cases and daily cases along with Sparkline chart for top 5 cumulative cases countries. This chart can help to understand in-depth detail about relationship between Daily cases, Total cases, and severity in each area.4. This page can help you understand more about total cases and time.
– I used stack column to demonstrate total cases over time in each continents and used clustered column to separately demonstrate cases in each year.5.Treemap and Funnel chart.
– Treemap help us to understand proportion of cases in each continent and countries. and the funnel chart helped us to understand changes of 2-weeks cases (I use 14days as bins size)
– I also provide you matrix containing exact number of cases in each countries6. The last page is Scatter chart to understand relationship of confirmed cases and deaths
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This is my dashboard for Week2. I use table, matrix, slicers, and also try to add a few additional other charts to make it more useful for decision making.
It consists of 5 pages.
1. The first page demonstrates Overall Covid-19 situation including Total cases, total deaths, and the line chart of total confirmed cases by date sliced by continents and country. The first dashboard provide overall situation and trend of cumulative cases to make us understand a big picture.
2. The second page is daily stats. There are 2 charts, Daily Confirmed cases by date and Daily Deaths by date, with slicer that can filter by Year/Month/Date and Area(Continents, Countries, Province). The chart provide us deeper detail of daily situation each day and each specific area. With these information, we can see trend of covid-19 severity situation in any specific date and area.
3. The third page is table containing very informative detail about each country. This table also provide information of Capital and GDP. And I also create new measurement that I use Sum of Deaths divided by Sum of Confirm to the DeathConfirmRatio. I imply that this ratio can tell us about effectiveness of Covid-19 patient care. And it might be related with GDP or GDP per Capita. There are 2 filters, Date and Area.
4. The fourth chart is Treemap. I decide to illustrate number of confirmed cases in percentage. So you can see the percentage along with proportion of the area to see proportion of confirmed cases proportion among continents. You can also click on each continents’ area to drilldown to see deeper detail in each continent. There is also a matrix showing number of Confirmed cases, Deaths, and Recovered cases categorized by Continent and Country that make you to see exact number along with Treemap. Date filter is also provided. This chart make you to be able to compare cases in each area.
5. The last one is map. Bubbles’ size represent number of cases in each area. You can click on the bubble to drilldown. This map provide geographical data related with Covid19 cases.
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In my point of view, other than abilities to communicate that Teletherapy can do as good as In-Person, It might be depend on individual’s personality. Some might feel more comfortable to do Telemedicine as they don’t have to drive to the hospital and also don’t have to talk face-to-face, that can be awkward, with therapist.
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The dashboard created by Khon Kaen University demonstrated proportion of vaccinated students in different faculties.
The dashboard included 3 charts.
1. Bar chart demonstrating overall proportion of vaccinated students
2. Doughnut chart showing proportion of vaccinated student categorized into 0 – 5 doses
3. Bar chart demonstrating proportion of vaccinated students in each facultyWhat I like
– The main color is orange in different intensity that make it’s easy to watch. Although the doughnut chart contains color shading with gradient from orange to green, it’s still easy to read.
– They use bar chart and doughnut chart containing length element make it easier for us to estimate the proportion.
– They use dash line as a grid line. It’s very clean.
– They provide exact number on each proportion.What I don’t like
– there are too many bar charts on the right. It could be grouped or categorized and applied collapse function.
– X axis label for bar charts should not be “Number (จำนวน)”. But it should be “Percentage” or “Proportion”.
– No English version. -
– Height and weight – should provided Unit such as CM, Kg.
– Pregnancy test – should be in Lab section and should have “not done” choice
– variable number should be align between Physical Exam and Pregnancy Test. If for Physical Exam 0 = Normal, 1 = Abnormal it should be applied for pregnancy test. We should change it from Negative =1, Positive =2 to Negative = 0, Positive =1, and Not done =3. -
the most important benefits of having data standard is it can be further utilized by everyone.
That can lead accumulation of data to happen.Consequently, we can utilized those standardized data to create further benefits such as research, innovation, and understandable for other organization to use without confusion (eg. FDA). -
I don’t have experience in conducting or doing clinical trial or any research.
But I would like to share my experience when I conducted database for Covid-19 Vaccination while I was working for a private hospital.At that time we used an electronic form as a main data collection method but the data was entered directly by patient and some was also entered by our officer. We design our system by using all of those steps including Audit trial/Time stamp, User authentication and access control level, Edit check and logical check, Data backup and recovery plan. The system worked well with some non-critical problems.
Unfortunately,we didn’t use ready to use software. We build our own software and data was managed by using SQL.
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From my experience, I haven’t done any project initiation from scratch especially Clinical research.
I just have experience to analyse and manage data it after it was collected.But If I had a chance to improve some steps of data collection, I would pay the most attention to the early phase such as protocol discussion and data design because many project that I involved with usually wasn’t designed well enough to be utilized to reach the goal of research.
Many data just was collected for non specific purposes and in different standard of recording. Hence, in my opinion, the early stage is the most important stage to be focused on.
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1.I collected the data of pathology reports and have to do a primary analysis and cleaning the data for the purpose of building the AI to analyse further pathology slide.
2. It was a secondary data from a information system used in the pathology department.
3. It was in electronics form and I tried to transform it into table and also tried to structurize it.
4. The most challenging problem is about missing data and unstructured data. Since the data was collected during 10 years ago and came from many pathologists without standard form. -
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As a CIO, I took responsibility to manage all IT systems related to COVID19, including vaccine reservation application, vaccination application, self-monitoring application for patient in Hospitel (Isolation ward located in hotel), and also bed management application.
I have to be align with all ethical principles mentioned in the article, ‘independence’ and ‘transparency’ are in particular. I worked with abundant of patients’ data, so I had to work without any conflict of interest. I have to make sure that all data is full of integrity and nobody can change it in bad way. I also have to make the system transparent and can be audited by auditor. Moreover, I use best practice to secure our application to protect any IT threats.
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I agree with Auswin and Napisa about UHC scheme in Thailand.
The most obvious benefit is ease of access to healthcare services for all Thai without any financial discrimination. With ’30-Baht treat all’, all Thai doesn’t need to worry about healthcare services’ fee and as a physician I experienced many goods aspect about the scheme.However,in my opinion, there are some aspects that needs improvements.
– To use pay-per-head policy might not fair for some hospital that has responsibility to take care of significantly more patient than others. Moreover,DRG might not cover costs that happen in reality. These can push some hospital to face with financial struggle and push hospital to deal with the problem itself.
– Similar to Auswin said, there are some inequality of treatment choices among different areas and also among different health insurance funding.
– The last one is controversial. I heard some providers said that UC might cause access to healthcare services too easy. Consequently, Thai people might care about their health less. Personally, I don’t agree with this statement. -
Similar to other Thai students opinion, I think that Thailand lacks of health informatics workforce.
These should be some challenges.– There is always a gap between healthcare professionals and IT professionals. Although there are a lot of people talented in both field, to communicate between them is quite difficult to clearly understand. We need people who have knowledge in both field to fill the gap.
– Health informatics is very new in Thailand. Technical knowledge, such as health data standard, health information exchange, and reference information model, is not well-known yet in Thailand. This could be a big challenge to have more professionals who expertise in the knowledge.
– Other than people who expertise in health informatics, every healthcare people should has some basic knowledge about health informatics to raise awareness about importance of health informatics. -
I would say that I will do data sharing.
There are a lot of advantages from data sharing. Data sharing can bring abundant knowledge that could help millions of people around the world as we can see from data sharing about COVID19 situation.
However, we have to do it carefully. Data sharing should be managed properly. We should inform data owners about how data will be managed if they allow us to collect and share their data. De-identification should be done properly. Additionally, I think that to agree with data sharing should be opt-in decision for patient, unless the data is very vital for human-being like COVID19. -
My setting is a Chief Information Officer for a private hospital and I am now working on implementation of EHR. I would like to share my view briefly.
Good things
– Data Utilization : EHR can enhance how we utilize data. It is essential to adopt EHR to turn the organization to data driven organization. Abundant priceless information collected in EHR can be utilized to generate many insight in aspect of health services and business insight.
– Data Accessing regulation : Using decent EHR can prevent us from unauthorized accessing to patients’ data. EHR usually has function to authorize and can track when and who access data.
– Health Information Exchange : Adoption of HIE is now increasing. EHR can help us to do HIE between hospitals including between small network of hospital, nation-wide, and world-wide.And I agree with other good and bad, such as prevent data loss, cost of implementation, needs of training were already by other classmates.
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– Missing Data : As mentioned in the article that “Since informations in EHR are non-systematically collected”. I think that to to cope with missing data, we might have improve method of data collection in both system and human. EHR should store as much structured data as possible, and minimize unstructured data collection. Applying terminology standard and reference information model such as SNOMED-CT or HL7 FHIR along with decent application design might help to improve the problem. Moreover, healthcare provider should record data in the same standard to lower missing data. That means organization should have policy and regulation about recording data.
– Selection bias and Data Analysis : I think that the biggest challenge in the problem is lacking of knowledge. We have to work as a multidisciplinary team, including data analyst specialist, to integrate variety of knowledge to solve the problem. Providing knowledge or training about data analyst for healthcare provider will be a good option too.
– Privacy and Ethical issue : Privacy and ethical are now considered in every aspect. Regulation, such as PDPA in Thailand and GDPR in Europe, must be followed to keep good privacy and good ethical acts.
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The four recommendations written in the article looks theoretical reasonable. There are many issues such as talking with stakeholders, prioritizing actions, creating pragmatic solution, doing and improving about researches, that could be good to deal with general corruption issues.
However, there are many more factors and social context that could influence and affect the happening of corruption in each society. For example, hierarchy is involved in most organization in Thailand and that’s similar to difficulty mentioned in the first recommendation. I think that we should apply the recommendations above combining with consideration of specific social context and factors in each society to decrease corruptions.
Another thing that might help to decrease corruption is to do something like a decent “Internal Audit” but in national level. But we also have to trust that the organization ,having responsibility to do an internal audit, won’t corrupt.
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HIS (Hospital information system) implementation or upgrading might be an example of health system improvement. Decent HIS can improve many aspects of health system, including increasing cost-effective of taking care of patient, improve quality of delivering health services, providing information for further improvement.
There are many factors that could affect the process of implementation. I try to consider the factors in aspect of framework of health system.
– Leadership/Governance : Leadership is vital to make the process of implementing HIS success. Organization’s leader will be the one deciding how the process should be done. Leader who doesn’t realize the importance of IT might be the biggest barrier in the process.
– Human resources : It takes many officers to implement the HIS. Another possible barrier is some healthcare provider might resist to change their way of work.
– Financing : Implementation of HIS is usually expensive. Although there are a few way to decrease cost of implementation, such as develop our own local made HIS and buying a bundle of license for many hospitals, it still tooks much financial resources.
– Information : To maximize the benefits of using and implementing HIS, the information should be structured and standardized.
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Basically, Disaster Recovery Plan should start from identifying and classifying threats based on its impacts and chances of events occurings.
In my opinion, Disaster Recovery Plan should includes.
– Backup – Full Backup should be done periodically, I prefer to store my backup data separately on Cloud Storage or any remote storage devices to reduce risk of physical threats such as flooding and fire.
– Replication – My company always do a replication in DR Server. It would be great if we can do realtime replication. Or we should reduce RTO as short as possible. -
Hospital and patients will gain many benefits from implementing High Availability Technique.
– Hospital and patients will get benefits from availability of accessing to health data that can provide seamless healthcare services. There will be more accurate data and shorter waiting time that will lead to better quality and satisfaction. Furthermore, High Availability is very vital for emergency situation that cannot be missed just a second of time.
– Hospital will receive benefits in aspect of business. With high availability, hospital can store, access, and use data properly, including clinical data and non-clinical data.
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I would like to share my experience in roles of user and IT guy.
User – I had experience with lack of confidentiality when I work as a physician. In my former hospital, doctors could access to every patients’ information even the information was not belong to the patient taken care by specific doctors. The events affected in less confidential of patients’ information that might cause data leakage. In my opinion, the system should be designed to restrict accessible to only specific doctors who involved in taking care of specific patient.
IT guy – I had experience in availability and integrity problem. There were a few time that HIS system taken care by my team was down and had issue in showing wrong lab result. It affected quality of care a lot. To solve the problem, we had to stick to our plan, such as Business Continuity Plan, written to prevent and recovery this kind of problems.
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I am now working for a private sector for a while, so there might be some differences from public sector. But I think it would be good to share my view about effects to healthcare resources in my setting.
Social – During COVID-19 pandemic, The outbreak affected resources in term of number of beds and ward. We have to spare a few floor of our hospital to be ready for COVID-19 infected patients. Moreover, we have to spare shared resources such as medical devices, elevator, entrance, and parking for COVID19 infected patients. The outbreak also significantly affected on human resources. For instance, some staffs had to quarantine themself in COVID19 ward after accidentally contact with patients. We also had to hire more healthcare providers to be able to deliver proper services during the peak period that cost a lot to hospital. Furthermore, some business collaboration was more difficult to be completed because of the lock down.
Technologies – My hospital decided to change every physical meetings to online meeting. Therefore there are some struggles at the beginning. Surprisingly, after a few sessions, our staffs got familiar with online meeting and found it more convenience to join and share their resources than traditional physical meeting. We had to implemented new information system to maintain quality of services while reducing risk of getting infection. Thus, IT team had more workload to deliver many systems.
Environment – Environment itself, such as climate and weather, didn’t affect much to my hospital.
Economic – During the outbreak, people had less purchasing power to access to private hospital that resulted in decreasing our revenue. This affected on other projects that should be done to improve quality of services. It also affected on individuals, such as decreasing in OT and other extras wage.
Political – Policy about Covid-19 frequently changed during the outbreak. Our staff had to spend much time trying to work along the policies. Policy about vaccine also affect us in management of all resources, including human resources, financial, medical device, and places, to be always ready to deliver vaccination services.
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Thank you for sharing your interesting project.
Cholera outbreak can be very harmful to humanity, so I totally agree to have the Cholera post outbreak.
I really like the stakeholders flow that contain international level organization. I-EMT and N-EMT would be very useful to prevent further Cholera outbreak. -
Thank you for sharing interesting project.
CKD, from my experience of taking care of patients, is very burden disease than can significantly worsen quality of life.
The surveillance will be very useful in early detection and management for patient who have early stage of CKD that will be very benefits in slower progression of the disease.
To apply health data standard, such as HL7 and SNOMED-CT, will be very helpful in transferring data from EMR to the system according to the data flow presented. -
I think that awareness of project’s importance might be considered as confounders in this case.
– Young adults are the group understanding how beneficial is technology. Thus, it might lead to higher number of young adults intending to use the application constantly because they know that technology can finally provide benefits.
– Young adults are mostly affected from the disease since they have to socialize for the purpose of works and social importance. They might aware that the project can help. -
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Prevent data loss is very good point. With EHR, we can back up data to remote site and also to cloud storage that is very helpful in preventing data loss.
And I think that about Confidentiality, it might be better if we apply a decent policy about data accessibility, such as leveling data in to a few different confidential levels and assign each level to different authorized users, thus the more sensitive data can be accessed only by the higher level officer or officer who assigned to take responsibility.
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Thank you for comment.
Misdiagnosing with other systemic infection will be the most challenging issue for this surveillance program. I think that the surveillance will be helpful in early detection, but at the end of the day doctors might have to do laboratory investigation before treating pateints.
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