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I would like to select Neonatal mortality rate
Definition
NEONATAL MORTALITY RATE is the number of resident newborns in a specified geographic area (country, state, county, etc.) dying at less than 28 days of age divided by the number of resident live births for the same geographic area (for a specified time period, usually a calendar year) and multiplied by 1,000.Calculation
(Number of resident neonatal deaths/Number of resident live births) x 1,000Usefulness
The main purpose of this vital statistic is to determine rate of survival of fetal. In under-development countries, the rate is high since access to medical service is scarce. By improving to maternal care can help reduce fetal motility rates. -
I would like to suggest High School Student Stress Monitoring System.
Background: Currently, we’re amidst a pandemic COVID-19 outbreak, which change our current socio-economic status quo to the new normal. Our traditional education system did not construct to support the newer methods of learning, the government has embarked on fully distance learning such as studying from home, lecturing by video conference, or giving assignments through the social networks. While these measures might be our best strategy, it still has an inevitable mental side effect toward children especially high-school students who are undergoing rigorous study for higher education admission. Create mental monitoring system for students might be beneficial to screening and prevent stress that can lead to mental illness.
Coverage: The high school students aged range from 14 to 18 years old, studying in education institutes.
Method: Using a set of survey questionnaire screening periodically. The results will be analyzed and reports, the potential high-stress students will be referred to the school guidance teacher and psychologist for consultation.
Cost: Direct cost – Computers, Servers, and Internet Service. Indirect cost – Productivity loss (as students , psychologists and teachers have to spent some time using the system)
Outcome: DALYs averted
Reference:
Pieh, C., et al. (2021). “Assessment of Mental Health of High School Students During Social Distancing and Remote Schooling During the COVID-19 Pandemic in Austria.” JAMA Netw Open 4(6): e2114866.
Williams, M. L., et al. (2021). “Addressing Stress in High School Students During the COVID-19 Pandemic.” NASN Sch Nurse 36(4): 226-232. -
Mycobacterium tuberculosis is the bacteria that cause Tuberculosis or TB which is easily infected, widely spreading from cough aerosol, and causes pathological disease in the susceptible population especially immunocompromised people. TB is also a concerning disease at a multi-national level as such WHO has planned to eradicated TB in 2030. TB spreading in Thailand varies from geographical settings and the highest endemic area usually consists of borders with neighboring countries such as the northeast and northern region.
Creating a model for TB SIR could help medical professionals determine health control policy to cope with the TB problem.
Variables:
S = 0-100, I = 0-100, R = 0-100, N = S+I+R (Total 100)
t = 100 (because TB has long spreading period)Defind equation
beta = 0.326666
gamma = 0.123111Coding in R
library(deSolve) SIR.dyn <- function(t,var,par) { # Rename the variables and parameters S <- var[1] I <- var[2] R <- var[3] N <- S+I+R beta <- par[1] gamma <- par[2] # Derivatives dS <- -beta*S*I/N dI <- beta*S*I/N - gamma*I dR <- gamma*I # Return the 3 values list(c(dS,dI,dR)) } beta <- 0.326666 gamma <- 0.123111 SIR.par <- c(beta,gamma) SIR.init <- c(100,1,0) SIR.t <- seq(0,100,by=1) SIR.sol <- lsoda(SIR.init,SIR.t,SIR.dyn,SIR.par) TIME <- SIR.sol[,1] S <- SIR.sol[,2] I <- SIR.sol[,3] R <- SIR.sol[,4] N <- S + I + R plot(SIR.sol[,2],type='l',main='TB SIR Model',xlab='Time',ylab='Number',col='blue',ylim=c(0,100)) lines(SIR.sol[,3],type='l',col='red') lines(SIR.sol[,4],type='l',col='green') legend(60,60,c("Susceptible","Infected","Recovered"),fill=c("blue","red","green"))Here is the result
Reference: Side, Syafruddin. (2015). A Susceptible-Infected-Recovered Model and Simulation for Transmission of Tuberculosis. Advanced Science Letters. 21. 10.1166/asl.2015.5840. Link
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Analysis of Dengue Fever pattern from seasonal climate setting in Mae Hong Son
Rationale: Dengue Fever or DF is an important high-mortality disease caused by the Dengue virus which can transmit between mosquitoes of the genus Aedes and humans. Aedes mosquito has a distinct life cycle as it required a specific temperature, humidity, and rainfall range to develop from egg to adult. The climate of Mae Hong Son is drastically different in each season where temperature can vary from 8.2 Celcius in winter to 41.5 in summer and the Aedes mosquitoes depend on these factors for their development which results in the seasonal pattern of Dengue Fever endemic. Mae Hong Son is also the highest DF patient per capita in Thailand.
Research question: Can climate patterns predict Dengue Fever endemic in Mae Hong Son?
References:
1. Bartley LM, Donnelly CA, Garnett GP. The seasonal pattern of dengue in endemic areas: mathematical models of mechanisms. Trans R Soc Trop Med Hyg. 2002 Jul-Aug;96(4):387-97. doi: 10.1016/s0035-9203(02)90371-8. PMID: 12497975.
2. Chanprasopchai P, Pongsumpun P, Tang IM. Effect of Rainfall for the Dynamical Transmission Model of the Dengue Disease in Thailand. Comput Math Methods Med. 2017;2017:2541862. doi: 10.1155/2017/2541862. Epub 2017 Aug 8. PMID: 28928793; PMCID: PMC5591907.
3. Chanprasopchai P, Pongsumpun P, Tang IM. Effect of Rainfall for the Dynamical Transmission Model of the Dengue Disease in Thailand. Comput Math Methods Med. 2017;2017:2541862. doi: 10.1155/2017/2541862. Epub 2017 Aug 8. PMID: 28928793; PMCID: PMC5591907. -
1. Why was the author interested in investigating the suicide problem in Thailand during the time?
I think the author would like to investigate becuase suicide rate has been increased.2. Each of students picks one potential risk factor mentioned in the paper and explains how the variable can contribute to the suicide rate?
Debt can be count as a risk factor which contributes to suicide. Higher debt ratio to income can cause stress and economical difficulties and potentially led to depression and suicide.3. How statistical modeling can contribute to investigate the epidemiology and spatial aspects of Thai suicide problem?
This model uses multiple factors including health, socio-economic, and demographic that can be study using spatial analysis. -
In my opinion, when we talk about location in epidemiological, we often thinking of them as static maps of sick people instead of locations that people actually living in. Incorporating social study in spatial epidermiology enables us to understand how disease occurred and spread, for example, in the heavily populated urban area in which people commute from rural to the center for work and study, we can implement disease control and prevention based on social settings.
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I’ve got some tutorial on this website: LINK
They’ve said
“Spatial Indexing
When you ran your model, you may have noticed a warning message No spatial index exists for the input layer, performance will be severely degraded. This is because certain spatial queries make use of a spatial index and QGIS warns you when having a spatial index can speed up your operations. PostGIS documentation has a good overview of spatial indexes and why they are important.
You can compare a spatial index to a book index. When you want to search for a particular term, rather than scanning each page sequentially, you can speed up your search by looking up the index and directly going to the pages where the word appears. Spatial indexes work in similarly. You spent the effort once to create the index and all subsequent operations can make use of it. When you create a spatial index, each feature’s bounding box is used to establish its relationship with other features. This is stored alongside the dataset and can be used by algorithms. When trying to determine spatial relationships, the algorithms speed-up the look-up using the following two-pass method:
Step 1: Use the spatial index to determine which target features’ bounding boxes intersect with the source feature’s bounding box. Since the spatial index already has computed this – this is very fast. The result is a list of candidate features.
Step 2: Now that there is a small subset of candidate features, iterate over them and use their full geometry to evaluate exact intersections.”More info on PostGIS website: LINK
Here are some excerpt
“Recall that spatial index is one of the three key features of a spatial database. Indexes make using a spatial database for large data sets possible. Without indexing, any search for a feature would require a “sequential scan” of every record in the database. Indexing speeds up searching by organizing the data into a search tree which can be quickly traversed to find a particular record.
Spatial indices are one of the greatest assets of PostGIS. In the previous example building spatial joins requires comparing whole tables with each other. This can get very costly: joining two tables of 10,000 records each without indexes would require 100,000,000 comparisons; with indexes the cost could be as low as 20,000 comparisons.”
In short – We didn’t create a spatial index so the program will run a sequential scan all data, this might have a problem with large amount of data but because we have relatively small data so we won’t probably notice any diffence.
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I used MacOS with Apple M1 chip to study. The app currently not support CPU architecture, instead, the app will be translated using Rosetta simultaneously. If there’s a bug that deter program function, I will switch to cloud based OS visualisation such as Microsoft Azure which I used in the last course (because PowerBI is not supported in Mac).
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I have created dashboard about COVID-19 vaccination in Thailand.
Link: https://bit.ly/3gvJZk4
The dashboard include vaccination at National and Provincial level. You’ll see the amount of first and second dose administration, registered, type of vaccine (Sinovac or AstraZeneca) and more. I think the dashboard can summarize a lot of data in a meaningful and attractive way by using various visualization.
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Here is my dashboard https://bit.ly/3x9glGD
I add another variable that important to consider: In Treatment which comes from Confirmed case = Recovered – Death
I think the dashboard let us see the overview of large data at a glance. All data has been summarized so the working group can determine strategies effectively.
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I would like to present the dashboard from CDC. Link: https://covid.cdc.gov/covid-data-tracker
What I like
– Comprehensive and reliable information
– Real-time update from the government
– Ability subscribe to weekly review e-mailWhat I don’t like
– Require medical knowledge to use
– Navigation is not intuitive
– Experience can be overwhelm when we need quick information -
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I would like to share my thought on Telemedicine on topics of benefit, disadvantage, and concern.
Benefit
– Faster access to healthcare
– 24/7 access
– Emergency care screening
– Broader coverage
– Lower non-essential cost
– Easy access to medical consultation
– Access to specialistDisadvantage
– Require technological infrastructure setup
– Need system specialist
– Higher cost for the instrument
– Require end-user devices (mobile phone or tablet)
– Require physicians training
– Difficult to differentiate diseases
– Difficult to perform continuous care
– Unable to perform physical and laboratory examinationConcern
– Privacy because the service providers or physician can obtain certain patient information
– Monetary as many insurance companies did not have a plan about telemedicine such as drug order and doctor fee -
From the article, I would like to summarise into pros and cons of implementing AI in healthcare.
Pros:
1. Faster testing and report
2. Higher throughput
3. More accuracy (depend on data and methods)
4. Increase patient service coverage
5. Remote diagnosis (from telemedicine)
6. Reduce cost (from professional hiring)Cons:
1. Require technological knowledge
2. Privacy concern
3. Proprietary matter (the data from the subject belong to who?)
4. AI BlackBox (what is the formula?)
5. Selection bias, data from some group of people might not work well with another group
6. Increase cost in computational and storage instrument
7. Require professional personnel to approve the resultIn conclusion, I think using healthcare AI is in development and it could be the future method of diagnosis but we need to be aware of potential privacy concerns.
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Your CRF is very concise and throughout. By providing a coding number in each box, the data manager and researcher can fill in eCRF in the system intuitively. Also, you divided each section for easier reading.
I would like to give some suggestions in the following aspect.
1. If the study is conducted in Thailand, we should clarify the year’s format since we use both BE (Buddhist Era) and CE (Common Era in gregorian calendar)
2. In the eligibility check, when the participant is not eligible for the study, there should be a comment section after No box.
3. The vaccination arms should write in the full name and in bold type to reduce clerical error: QIV -> Quadrivalent inactivated Influenza vaccine (QIV), TIV -> Trivalent inactivated Influenza vaccine (TIV)
4. For laboratory results, the titer always begins with 1 such as A/H1N1 Antibody titer 1: _______ etc.
5. There should be personnel initial fields in each session to explain who performs a physical exam, laboratory test, or fill in the form. And the initial must correlate with the study delegation log.Overall, your CRF is impressive. Keep Up the Good work!
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There’re multiple fields that need units:
Age: years or years with months
Weight: kilograms (kg), pounds (lbs)
Height: centimeters (cm), meters (m), feet, and inches (ft, in)
BMI: kg/m^2Also, the Date, Date of informed consent can be design into boxes for easier writing
for example, Date could be written as ⬜️⬜️/⬜️⬜️⬜️/⬜️⬜️⬜️⬜️ (DD,MMM,YYYY; 05/APR/2021) -
In my opinion, using the standard for the clinical study will provide interoperability between multiple study sites around the world including the same dataset, unit, procedure, and reports. All of which, provides the researcher with a better tool to conduct a study and improve quality of the results.
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I have experienced data quality control very frequently during work. My work involved as input data into the database. I would like to describe my routine activity that can correlate with the concept.
– Audit trail and Timestamp, the research database record when the value has been entered and who use the application at that time.
– User authentication and access control level, we have both physical and logical control. As entering the facility required authorization, currently, we use biometrics such as facial recognition at the entrance. By logical means, we restricted access to the computer with username and password. We also utilize “Windows Users Control” (UAC) that restrict users from accessing some file or modified computer system.
– Edit check and logical check. The application used edit check by control type of value, for example, the specimen number can only be number, if we entered character into the field, it refuses to save into the database. We also use double entry for verifying each other.
– Data backup and recovery plan. We have a physical backup at the remote locations that can be retrieved easily such as CDC server at Atlanta. -
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As I have worked in a research clinic setting that involved many data collection procedures. I would like to share some comments on the forum.
1. For a purpose of the data, we collected data for clinical trials such as drug investigation or disease surveillance.
2. We collected both primary and secondary data because it was required by Study Specific Protocol. Some secondary data may be received from external parties as participants have visited another hospital and we need to record in an adverse event form.
3. Our clinic used Electronic Data Capture that connected to the internet. The researcher can record all data into the browser. However, some data still need paper-based such as informed consent, laboratory report.
4. We have experienced some issues in the system such as internet network downtime result in workflow deterioration.
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I think we have a small number of health informaticians in Thailand and need to produce more people in the field. As I have observed both in the clinical and hospital areas, it turned out that many potential jobs have been fulfilled by non-medical personnel such as IT technician whom may lack medical knowledge or medical personnel who don’t understand IT system, these kinds of discrepancies resulted in miscommunication and might led to operational difficulties or even patients loss.
For example, in the emergency department, medical personnel tend to prioritize patient safety so they required an application interface that simple and has lowest amount of input to reduce time while technician tends to prioritize data input in the system as it needs to connect to another department such as finance, pharmacy, laboratory. In this case, both are not wrong if we have a cluttered user interface, personnel will waste time on the screen instead of taking care of patients, or if we don’t have data, we cannot bill the expense, order drugs, or find necessary lab results. In the end, both applications they pictured are drastically different. This type of scenario already happens in organizations that don’t have health information and I think it is our job to mediate between the two which would build the successful health IT implementation.
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I think sharing health data in Thailand could provide many benefits to the healthcare system as it provides a better solution for a medical practitioner to collect and analyze patient data set which will lead to better care for people. Data set such as demographics, symptoms, and laboratory results can be used for the research in future studies. However, we need to apply strict policies regarding sensitive data for privacy and security concerns.
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The reason that medical cost is so high in the United State of America is that they have not using single-payer system like another developed nation mean that the people have to relied on the private insurance to get medical expense covered. Many typical hospitals in the USA used Master price list or Chargemaster that tell how much each procedure cost, and the insurance company usually negotiate for the lowest price possible that led to hospital overcharge. If the uninsured patient go to hospital, they still have to pay for high amounts as same as insured patient.
The US government tried to solved the problem such as Affordable Care Act or Obamacare that targeted low income population, Medicare or Medicaid from Federal government for low income and elderly people.
Here are some simplified video that describe the problem of healthcare in USA:
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I agree with the article about Net Pracharat concerns because using internet that provided by the government mean that they can access many sensitive data from the user and coupling with new digital criminal law that required internet service provider keep usage record for a period of time. Certainly, these records can be used to prevent and condone illegal activity, on the another hand, the government can also use data to convict criminal allegation on political opposition.
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I would like to suggest some solutions for the challenges.
1. Missing data can be corrected by established strict rules or policies whether data can be obtained or not and those data that cannot be collected must provide cause in the the incident report for further prevention.
2. Selection bias, because of large amount of information, the researchers are able to select the best data that suited their research purposes, this led to bias result and abuse fundamental concept of big data that more amount of data could provide more accurate results. To prevent this type of problem, the researcher should conduct a study based on real representation of data.
3. Data analysis and training, if the dataset is too large or complex to be analyze by standard set of statistic and the study required more advance statistical analysis, the researcher should consult the statistician. Moreover, many modern packaged softwares provide comprehensive list of statistic to use and intuitive graphic user interface.
4. Interpretation and translational application of result, in my opinion, the researchers should conduct big data studies on real problem in healthcare or result from the studies can benefits current health practices.
5. Privacy and ethical issue, using technologies to assist study always have privacy and cybersecurity issues but implementing right policy and punctual practice can reduce risk of these problem.
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In the clinical trial setting, using EMR provides many benefits for the researchers such as data utilization, data storage, and data dissemination. For example, we have an appointment application to manage participant schedule, a web application to record case report and adverse effect, a laboratory app which record all detailed about testing etc.
After using these applications for a while, I can summarized pros and cons of EMR into following aspects:
Pros
– Working collaboratively which users can access and edit data in the same time.
– Transfer data more efficiently where users can send and receive data through the computer network.
– Better Back-up procedure when all data has been digitalise, we can back-up them with multiple solution.
– More environmental friendly because tradiontal EMR producing a lot more waste from paper and office supplies.Cons
– High cost upfront because digital EMR required setup of hardware, software and technician.
– Required consistence network infrastructure such as power and internet.
– Required safeguard policy and personnel training to prevent data breakage and malicious attack.In my opinion, the benefits from digital EMR is far outweighed and many disadvantage can be prevent by good management.
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I agree with the authors in a recommendation to fight against corruption in healthcare and I would like to point out some aspect about bribery in the healthcare system. As the authors have provide some cultural influence in the system, in many asian culture, it is a very common for the patients to give the presence or gift to the healthcare worker because we thought it’s good custom that nobody could harm while this cultural phenomenon didn’t appear in the western society.
However, this could let to exploitation of the system, for example, in Thailand, there’s a annenatal care system and government has grant basic access to every pregnant mother but some obstetrician exploited this system by established antenatal clinic where wealthy pregnant mother can chose to receive “special care”. The problem existed when obstetrician received money from the patients disguised as “gift” while using public resources to perform check up on their personal patients. Some of this special requirements from mothers even led to infant harmness such as perform Cesarean section without indication because the parents want their baby to be born in a specific time and date according to their belief. Since the hospital delivery room is a limited resources, the obstetrician tend to using their influence to book a room according to their schedule while others has to waited just because they didn’t give “gift” to their doctor.
In my opinion, we need to established law that restrict healthcare employee received any gift from patients to cut down their influence on the healthcare system.
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In Thailand, the national health coverage system has been deemed to be a successful project and it is recommended by World Health Organization. However, the financial aspect is still the main problem in which many hospitals suffered from an operational deficit and in debt due to government policy.
Currently, the government hospitals received monetary reimbursement from National Health Security Office (NHSO) or สำนักงานหลักประกันสุขภาพแห่งชาติ (สปสช) in Thai. The policy is to distribute yearly government health budgets to each hospital per capita, for example, in 2020, each Thai people has 3,719.23 THB maximum spending per year that means a hospital with 10,000 coverage will get only 37,192,300 THB per year. Normally, this method might work if most people are not using healthcare services and the rest of the budget will go to more required patients as in private health insurance.
But the problem occurred as Thailand has gradually become an aging society, where most of the patients are elderly and suffering from non-communicable diseases such as diabetes, hypertension, and chronic kidney disease. The hospital has to manage its budget to fit all required costs including healthcare workers, medicine, laboratory, instrument maintenance, etc. According to the news, many hospitals are already in debt and at risk of bankruptcy.
In my opinion, we can resolve this issue by implementing health IT reimbursement which provides both direct (medicine, doctor’s fee, disposable instrument) and indirect cost (hospital fee, lab test, instrument maintenance) reports, by this way, both NHSO and the hospital can determine the real cost of each treatment which will help to allocate health budget proportionally.
The main barrier of this project is the difficulty to implement at the national level as all government hospitals in Thailand will be subject to the same system.
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My organization is clinical trial and IT system used by small quantities of people. It is required by our trial International Review Board and sponsors that information in the database must be correct, confidential and available at all time. So, in my opinion, deploying the system required many security implementation.
To protect confidentiality of information, I would like to use encryption for the data communicating between network, and user access control that authorized only responsible personnel on specific date and time of their shifts. For data integrity, test result that recorded on the database should has hashing when transferring data between applications for verify whether that data is corrected. And because we generate a lot of data during clinical trial period, Data back up is essential so I preferred backing up to the cloud because our internet is quiet good and we have no estate to install back up server.
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I’ve encountered difficulty in CIA triad in term of availability, because my workplace used servers that established in remote location and required internet connection to transfer data so when the internet down, we cannot access information nor upload data to the server. In order to continue our work, we have to use manual system such as Record in Excel and print out in paper. However, I still don’t know the solution that our IT personnel would do apply to.
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Your presentation is creative with detailed information, I’d like to add that you could implement a Geographic Information System in the project as it could narrow down the potentially infected area which local health authority can focus into. Also in the stakeholder, there should be a patient or participant as the project will require their consent and cooperation.
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