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What intervention(s) you are considering in your modelling and how it will be added to the model structure. What are the characteristics of the intervention(s) (e.g. coverage, efficacy etc.)
We can incorporate many interventions into the SEIR (Susceptible-Exposed-Infectious-Recovered) model for hepatitis C and adapt the model to evaluate their impact and simulate the transmission dynamics of hepatitis C in the population.
Screening Campaigns and Preventive Measures (e.g. Blood Safety and Needle Exchange Programs) can have an impact on the transition from the susceptible (S) to the exposed (E) compartment including the probability of being diagnosed as exposed based on screening.
Public Awareness and Education programs can have an impact on population behavior that reduces the risk of moving from exposed (E) to infected (I) compartment and can be added as a factor for σ (sigma).
Treatment Programs and Treatment Adherence Monitoring can impact treatment success and increase the rate at which infectious individuals move to the recovered compartment and can be added as a factor for γ (gamma).
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What model structure would the disease you are interested in, and please start adjusting the R code to that structure.
The SEIR (Susceptible Exposed Infectious Recovered/Removed) model is widely used in model studies on hepatitis and is effective in evaluating the transmissibility of HCV, predicting future morbidity, and evaluating the effectiveness of prevention and treatment.
SEIR Model structure:
Susceptible (S): Individuals at risk of acquiring hepatitis C.
Exposed (E): Individuals exposed to the virus but not yet infectious.
Acute Infectious (I1): Individuals with active acute hepatitis C infection.
Chronic Infectious (I2): Individuals with chronic hepatitis C infection.
Recovered (R): Individuals who have cleared the infection naturally or through treatment.Parameters (with suggested values from the literature):
β (beta): the transmission rate/coefficient.
σ (sigma): the rate at which exposed individuals become infectious
γ (gamma): the rate at which infectious individuals recover
ρ (delta): Disease-induced mortality rate
μ (mu): the Natural mortality rateN is the total system population.
𝑁(𝑡) = 𝑆(𝑡) + 𝐸(𝑡) + 𝐼(𝑡) + 𝑅(𝑡)############################ R Code ############################ # Load deSolve library library(deSolve) params <- c( beta = 0.21, # Transmission rate sigma = 0.1, # Rate of progression from exposed to infectious gamma = 0.064, # Recovery rate delta = 0.006, # Disease-induced mortality rate mu = 0.064 # Natural mortality rate ) initial <- c( S = 0.9, E = 0.01, I = 0.01, R = 0.0 ) times <- seq(0, 1000, by = 0.1) # Time span for simulation (years) # SEIR Model function seir_func <- function(time, var, par) { with(as.list(c(var, par)), { dS <- -beta * S * I dE <- beta * S * I - sigma * E dI <- sigma * E - (gamma + delta) * I dR <- gamma * I - mu * R return(list(c(dS, dE, dI, dR))) }) } result <- lsoda(initial, times, seir_func, params) TIME <- result[,1] S <- result[,2] E <- result[,3] I <- result[,4] R <- result[,5] N <- S + E + I + R plot(0, 0, type='n', xlim=c(0,200),ylim=c(0,1) , xlab = "Time (years)", ylab = "Population", main = "Hepatitis C Model") points(TIME,S,type='l',col='blue',lwd=3) points(TIME,E,type='l',col='red',lwd=3) points(TIME,I,type='l',col='orange',lwd=3) points(TIME,R,type='l',col='green',lwd=3) # Add a legend legend("topright", legend = c("Susceptible", "Exposed", "Infectious", "Recovered"), col=c('blue','red','orange','green'),lty=rep(1,4)) ######################### End of R Code #########################
Please state the key characteristics of the disease you are focusing on e.g. transmission, pathogenicity, symptoms, control measures, etc. You can write it as text or start using the parameter table in the template provided. Anything you want to let me know about the disease you are going to work on would be useful.
1- Transmission:
– Description: Hepatitis C in Egypt is primarily transmitted through medical procedures using improperly sterilized equipment, such as syringes and needles. Intravenous drug use, transfusions, and sexual transmission.
– Approximate Value: The transmission rate varies, but past unsafe medical practices significantly contributed to high prevalence.
– Source of Information: Research studies, including the WHO and Egyptian Ministry of Health.2. Pathogenicity:
– Description: Chronic HCV infection can lead to liver fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). Egypt has a high prevalence of genotype 4, which is associated with a higher risk of liver disease progression.
– Approximate Value: HCV-related liver disease is a leading cause of morbidity and mortality in Egypt.
– Source of Information: Scientific studies, healthcare reports, and publications from Egyptian health authorities.3. Symptoms of HCV:
– Description: Hepatitis C is often asymptomatic in its early stages. Symptoms may include fatigue, jaundice, abdominal pain, and complications like ascites.
– Approximate Value: Many HCV-infected individuals in Egypt are asymptomatic, making early detection and screening important.
– Source of Information: Clinical studies, healthcare data, and reports from Egyptian healthcare providers.4. Preventive Measures:
– Description: Prevention efforts in Egypt include safe injection practices, improved healthcare infection control, harm reduction programs, and public health campaigns promoting awareness and testing.
-Value: These measures have contributed to reducing new infections and improving care.
– Source of Information: Reports and initiatives by the Egyptian Ministry of Health and international health organizations.5. Treatment Cure Rates:
– Description: Egypt has implemented widespread access to direct-acting antiviral (DAA) treatments, resulting in high cure rates for chronic HCV infection.
-Value: Cure rates with DAAs often exceed 95%.
– Source of Information: Clinical trials, healthcare data, and WHO reports on HCV treatment in Egypt.6. Genotype Distribution:
– Description: Genotype 4 is the most prevalent in Egypt, accounting for a significant portion of HCV cases.
-Value: Genotype 4 is highly prevalent, with some regional variations.
– Source of Information: Genotype prevalence studies and genetic analyses in Egypt.7. Impact on Public Health:
– Description: Hepatitis C has been a major public health concern in Egypt, leading to extensive efforts to control the epidemic.
-Value: The disease has posed significant challenges, but recent interventions have improved outcomes.
– Source of Information: Public health reports, research studies, and WHO assessments of the HCV situation in Egypt. -
Choice of Disease and Scope:
Hepatitis C virus (HCV) in EgyptRationale/significance of the research:
Hepatitis C virus (HCV) is one of the leading known causes of liver disease in the world. Viral hepatitis has been estimated as the 7th leading cause of mortality globally. About half of this mortality is attributed to hepatitis C virus (HCV), a virus that causes acute hepatitis, fibrosis, cirrhosis, and liver cancer among other disease sequelae.Egypt has one of the highest prevalence rates of hepatitis C in the world, with 15% of the adult population infected. In 2018, 6% of individuals aged 1–59 years had a positive result on the hepatitis C antibody test, and 4% were found to have an active infection. HCV is one of the significant public health concerns in Egypt that needs more attention and funding from health policymakers. Indeed, Liver disease is the main cause of mortality in Egypt.
Hepatitis C has complex transmission patterns in Egypt and is characterized by unique patterns, including iatrogenic transmission through medical procedures and possible social and cultural factors. Mathematical modeling can help disentangle these complex transmission dynamics and inform targeted interventions.
Egypt faces resource constraints in its healthcare system. Mathematical modeling can assist policymakers in allocating limited resources more effectively by optimizing various intervention strategies.
State the research questions where modeling is likely to help answer:
What are the most effective strategies for reducing the burden of hepatitis C in a high-prevalence region, such as Egypt, and what are the key drivers of hepatitis C transmission and how can we optimize the allocation of healthcare resources in Egypt?Citations on other previous work that you may use to guide your study (if there are any):
– Current situation of viral hepatitis in Egypt
– Impact of treatment on hepatitis C virus transmission and incidence in Egypt: A case for treatment as prevention
– Estimation of hepatitis C virus infections resulting from vertical transmission in Egypt
– Effect of preventive and curative interventions on hepatitis C virus transmission in Egypt (ANRS 1211): a modelling study
– Estimation of hepatitis C virus infections resulting from vertical transmission in Egypt -
Well done, Sippapas.
I have a few comments to improve the CRF design (In my opinion)
1- Add a box for the site ID before the screen/subject ID.
2- Use only 3 boxes to screen/subject ID as we have only 150 patients per site.
3- Pregnancy test must be performed for female participants, we cannot have an “unknown” option for Sex.
4- We need to have a full date of birth. This will be helpful if the patient has exactly 18 or 60 years and a few months more or less.
5- In Weight, It is better to have an extra box for 1 decimal.
6- DRAWINGS, How we can enter it in eCRF or analyze it?Thank you.
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Based on your experience in data collection/management, which steps in the data management workflow that you have done and have not done?
In many projects, I was involved in Data Design & Acquisition, Data Collection/CRF development, Database access control, Data entry screen processing, CRF completion training, and Quality Assurance (QA), DBL.
If you have a chance to go back, which steps that you should have done it to improve your project?
If I got a chance to go back, to improve the project, we should have invested more time in data validation and Edit checks programming. During the study, we found many issues due to different data structures in each site and we had to amend the eCRF completion guide to add more clarification on the required data and additional notes to investigators.
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Could you share your experience on data collection?
A few years ago, I participate in the data collection for a research study on diabetes type 2 patients.1.Purpose of data collection: For research, for public health surveillance, or others
For research purposes to explore the safety and effectiveness of new insulin injections. Data collection included the most recent HbA1c and laboratory-measured fasting plasma glucose (FPG) value.2. Was it primary or secondary data collection?
It was a primary data collection. Data was collected from study participants at each visit during the study and recorded in eCRF.3. Methods used for data collection
Electronic Case Report Form was used in data collection. A paper diary was provided to each participant at the study entry; they were asked to return the diary at each site visit. Participants recorded blood glucose values, doses, any episodes of symptomatic hypoglycemia, and information on meal intake.Additional data collected included the physician-recommended dose and other antihyperglycemic medications (doses and timing of doses) and changes in lifestyle habits (e.g., working hours, sleeping duration, smoking, and physical activity).
4. Were there any problems that occurred regarding data collection?
There were a few challenges to encourage participants to complete the diaries and record hypoglycemia events. The site investigators had to transfer the data recorded in the paper diary to eCRF which took a long time and required verification of the data entry. -
If we don’t have data on why respondents don’t use bednets, we can use one or more of the following to gather more information to help us to understand the data:
Get a consultation from local experts: Experts in malaria prevention, such as public health officials and non-governmental organizations (NGOs) working in the field These experts may be able to offer advice on ways to increase bednet use and have valuable insights into the factors that influence its use.
Conduct interviews or follow-up surveys: We can conduct follow-up surveys or interviews with them. This may assist you in comprehending the reasons for their behavior.
Discussions in focus groups: With groups of people who do not use bednets, we can hold focus groups to learn more about their reasons for not using them. Using this strategy, you can learn about the most common reasons people don’t use bednets and find behavior patterns.
Literature review: We can conduct a literature review to gather information on factors that have been shown to affect bednet use. Bednet availability and accessibility, as well as other socioeconomic and cultural factors, are all examples of this.
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Efficacy: Efficacy refers to how well an intervention works and measures the ability of an intervention to produce a desired effect in a highly controlled environment. It is often assessed in randomized controlled trials. The goal of an efficacy study is to demonstrate that the intervention has a statistically significant effect on the outcome being measured
Effectiveness: Effectiveness refers to how well an intervention works under real-world conditions and it measures an intervention’s cost-effectiveness. effectiveness studies usually designed to evaluate whether an intervention is useful and practical when applied to real world situations, and they can provide valuable information on the feasibility of implementing interventions.
Efficiency: Efficiency refers to the cost-effectiveness of an intervention and measures the ratio of the resources required to achieve the desired outcome while using resources. Efficiency studies are to check if an intervention is worth the resources required to implement it
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Maternal mortality rate
Definition: The number of deaths of women due to pregnancy or childbirth-related complications per 100,000 live births.
How to Calculate: The number of maternal deaths / Number of live births * 100,000
Main usefulness: To measure the quality of maternal health care and to identify areas for improvement.Infant mortality rate
Definition: The number of deaths of infants under one year of age per 1,000 live births in a specified time period.
How to Calculate: The number of infant deaths under one year of age) / Number of live births * 1,000
Main usefulness: To measure the overall health and well-being of infants and to identify areas for improvement in prenatal, perinatal, and postnatal care.Neonatal mortality rate
Definition: The number of deaths of infants under 28 days of age per 1,000 live births in a specified time period.
How to Calculate: The number of neonatal deaths under the age of 28 / Number of live births * 1,000
Main usefulness: To measure the health and survival of newborns and to identify areas for improvement in prenatal and perinatal care -
It is crucial to promote ethical standards and best practices in clinical research in order to participate responsibly and effectively as a Clinical Research Associate (CRA) in the COVID-19 control policy. A CRA should adhere to the following significant ethical principles and best practices.
Knowledge and Adherence to Guidelines: CRA should has a good understanding of the relevant regulations, and laws related to clinical research conduction and make sure that the study is carried out in accordance with the pertinent guidelines, such as the World Health Organization (WHO) guidelines for clinical research during the pandemic.
Beneficence: A CRA has a responsibility to act responsibly to protect research participants from harm. In the case of COVID-19, it is the CRA’s duty to ensure that the study is planned and designed to maximize benefits and minimize risks to participants. This involves making sure that the research is conducted safely, and ethically, and that participants are treated fairly for any unfavorable incidents.
Non-maleficence: CRA must ensure that participants are not harmed during the research out of a sense of non-maleficence. This involves ensuring that the study is carried out in accordance with best clinical practices and that participants receive the appropriate medical care if any unfavorable outcomes occur.
Data security: CRA should ensure the security of participant data and respect their privacy. This involves removing any unnecessary data and putting in place suitable data security measures, such as password protection and encryption.
Justice: Justice requires that clinical research be carried out in a fair and equitable manner, making sure that the advantages and disadvantages of the research are distributed fairly among all participants. The CRA must guarantee that the research is conducted fairly and pays particular attention to those who are most impacted by COVID-19. This includes ensuring that individuals from underrepresented groups are not unjustly left out of the study.
Respect for Persons: It is one of the most crucial ethical principles in clinical research. The CRA should obtain informed consent from participants and respect their rights prior to conducting any study. This involves making sure that participants’ privacy is protected and that they are fully informed of the risks and advantages of the research.
Transparency: The CRA should promote transparency in data collection and reporting, ensure that study results are reported accurately and objectively and communicate with participants and other stakeholders in a transparent manner by giving clear and precise information about the research’s objective.
Continuous learning and improvement: CRA should continuously improve their knowledge and skills, and stay up-to-date with the latest developments in clinical research and ethical guidelines.
By adhering to these ethical considerations, a CRA can contribute to the development of a control policy for COVID-19 that promotes ethical and good practice in clinical research.
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In Egypt, the government has been working to provide citizens with Universal Health Coverage (UHC). In 2020, the government started the “Egypt Healthcare” initiative, which aims to make health services more accessible and better. The following are some of this initiative’s key points:
1. Health insurance coverage expansion: The government has been extending health insurance coverage to more people, notably those in rural areas and low-income families.
2- Investment in health infrastructure: The government has been funding improvements to existing hospitals and clinics as well as the building of new ones.
3. Focus on primary care: Egypt is emphasizing the development of primary healthcare services as the first point of contact for citizens with the healthcare system.However, there are additional challenges that must be faced for the UHC program to be successful. For instance, given the nation’s current economic state, maintaining the UHC scheme may be challenging without appropriate money. In addition, there are still differences between urban and rural locations as well as between public and private healthcare providers in terms of the quality of the services they offer.
Access to high-quality healthcare services may be hindered by a shortage of healthcare professionals, especially in rural areas. Stronger health information systems, including electronic health records, are required to track and monitor healthcare services in order to manage the UHC scheme effectively.
Overall, Egypt has made significant progress toward universal health coverage; however, the country still has a long way to go in terms of overcoming obstacles and enhancing the quality of healthcare services for all citizens.
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In my opinion, more skilled informatics skills are needed as the health informatics workforce in my country is not well established.
The lack of qualified professionals is one of the main challenges facing the health informatics workforce. This is especially true in countries where health informatics is still in its infancy and there are not enough seasoned professionals to teach and mentor the next generation of workers. The quality of healthcare delivery and the ability of healthcare organizations to keep up with the latest developments in the field can be affected by this shortfall, which can lead to a lack of investment in health informatics and slow adoption of new technologies and practices.
The need to keep up with rapidly changing technology is another obstacle that the health informatics workforce must overcome. To remain competitive and deliver high-quality care, healthcare organizations and staff must be able to rapidly adapt to new technologies and processes in the field of healthcare informatics. Health is changing rapidly. Ensure that the workforce is informed of the latest developments in the field and that education and training requirements are updated continuously.
In addition to these challenges, the growth of the health informatics workforce may be hindered by cultural and regulatory barriers. For example, cultural or political factors may hinder the adoption of new technologies and practices.
Health IT professionals may also find it difficult to collaborate and share information due to regulatory restrictions on sharing health information between organizations. In summary, cultural and regulatory barriers, a lack of skilled professionals, and the need to keep up with rapidly changing technology all pose significant barriers to the health informatics workforce. In my opinion, investments in health informatics workforce development, continuing education, and training, and supporting the adoption of new technologies and practices are critical to healthcare organizations, governments, and professional organizations.
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In my opinion, Data sharing, exchanging, and utilizing health data would be important for many reasons and has several key benefits that make it a crucial aspect of modern healthcare.
1- Improved public health outcomes
It is one of the most important benefits. Health data sharing enables healthcare organizations to access and utilize a larger pool of health information, which can lead to a better understanding of diseases, the development of new treatments, and the discovery of new cures. On a global level, countries and different research organizations can access information from a wider range of patients, allowing for more accurate diagnoses and treatments based on real-world data.2- Better research
Data sharing will enable researchers to work with data from multiple sources, leading to a more comprehensive understanding of diseases and accessing larger and more diverse sample sizes, researchers can conduct more robust and reliable studies.3- Transparency and trust
It is another key benefit of data sharing. By sharing data, healthcare organizations can demonstrate the steps they take to protect the privacy and security of sensitive information and build trust with the public and show the commitment of healthcare organizations to the responsible use of health information.4- Collaboration and information exchange
Data sharing enables collaboration and information exchange between healthcare organizations and researchers. This leads to more efficient use of resources and helps to avoid duplication of effort. leading to a more effective approach to healthcare delivery and research.However, we should consider many risks of data sharing. Data often contain sensitive and confidential information about individuals, including their medical history, personal information, and genetic data which leads to the risk of privacy and security breaches. Sharing this information with other organizations increases the risk of unauthorized access and potential misuse of this information. Also, data sharing is the potential for discrimination and unequal treatment. Health data can contain information that can be used to discriminate against individuals, including information about pre-existing conditions, genetic predispositions, and other sensitive health information.
In conclusion, while health data sharing has many benefits, there are also significant disadvantages that need to be carefully considered. It is important to minimize these risks, Healthcare organizations and researchers to develop and implement robust policies and procedures for the collection, storage, and sharing of health data, which balance the benefits of data sharing with the need to protect privacy and ensure ethical and equitable treatment of individuals.
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Electronic medical records (EMRs) have several advantages over traditional paper-based medical records in healthcare. Benefits of EMRs include:
Improve communication between hospital staff: EMRs can share patient information among healthcare providers, making it easier to coordinate care and avoid duplication of tests or treatments and help to reduce costs.
Improved efficiency and productivity: EMRs can be accessed quickly and easily by authorized hospital personnel, reducing the need to spend time searching for physical records.
Increased accuracy and completeness of patient information: EMRs can also alert healthcare providers to potential errors or omissions, and they can include more detailed information than paper records.
Improved patient outcomes: EMRs can assist healthcare providers in making decisions based on more information, which can improve patient outcomes.EMRs can also have some disadvantages, such as:
Setup fees & Initial costs: Implementing an EMR system can be expensive and may require significant investment in hardware and software.
Staff training: Staff may need to be trained on how to use the EMR system, which can be time-consuming and costly.
Interoperability: There are issues with data sharing and continuity of care because EMRs from different vendors don’t always talk to each other well.
Data security: EMRs store sensitive patient information and proper security measures must be in place to protect this information from unauthorized access or breaches.
Technology dependence: Because EMRs are based on technology, access to patient data may be lost if the system fails. -
In my opinion, We can implement several strategies to face these challenges including:
Disease definition: The quality and comparability of big health data can be enhanced by developing standardized and consistent disease definitions.
Data availability: Big health data can be made more accessible by forming alliances with a variety of data sources by developing partnerships to increase data availability with various data sources, such as hospitals, clinics, and research institutions. Also by involving cloud-based solutions and platforms to store and share large amounts of data, making it more accessible for remote teams and researchers.
Data quality and missing data: Data quality can be improved and missing data can be addressed using methods like data validation to check the data for any errors or inconsistencies, imputation by using statistical techniques to fill in missing data based on the observed data, and data cleaning to identify and remove errors, outliers, and inconsistencies in the data.
Data inconsistency and Data integrity: Data inconsistency can be addressed by developing methods for integrating and standardizing data from multiple sources. The integrity of large amounts of health data can be safeguarded by putting in place stringent data security and privacy measures.
Training: Developing specialized training programs for individuals working with big health data can help to ensure that they have the necessary skills and knowledge to work with this type of data.
Legal and ethical issues: Developing policies and guidelines to address legal and ethical issues related to big health data can help to mitigate risks and ensure compliance. And improve healthcare organizations’ transparency about how they collect, use, and share health data.
Data security: Implementing robust security measures such as encryption, firewalls, and network segmentation can help to protect big health data from unauthorized access and breaches. Data can be encrypted to protect it from unauthorized access or breaches.
Fairness and bias: Implementing fairness-aware machine learning methods and monitoring the data and models for any potential bias can help to mitigate any unfairness in the predictions.
Overall, it’s important to combine technical solutions such as encryption, access controls, network security, and data backup with policy, and governance, and collaborate with domain experts and stakeholders to ensure that the data and models are fair and align with ethical and social values.
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Convening key stakeholders in the health system to seek agreement on the scale and nature of corruption I agree that collaboration with all parties can aid in developing a common knowledge of the issue and a sense of shared accountability for finding solutions. This strategy can foster collaboration and the exchange of best practices while also facilitating the creation of focused and efficient anti-corruption tactics. Additionally, involving decision-makers can aid in ensuring that corruption-fighting measures are in line with the overall goals and objectives of the health system. Involving the public in the battle against corruption is another idea that might be successful in reducing corruption in the healthcare industry.
It is necessary to prioritize action I agree that prioritizing actions is necessary. The impact on the health system, particularly for vulnerable groups, as well as the viability of potential solutions should guide decisions regarding how to fight corruption. Healthcare professionals and policymakers can ensure that limited resources are utilized effectively by concentrating on the most severe and widespread forms of corruption as well as those that have the greatest impact on vulnerable groups. They can also increase the likelihood of successfully combating corruption by considering the viability of potential solutions.
It is essential to take a holistic view
I agree that taking a holistic view is essential to fight corruption in healthcare. Examining the issue from multiple perspectives, such as anthropology and political economy, can provide a more complete understanding of the root causes and potential solutions to corruption in the health sector.It is important that the research community sets out what it can offer I agree that research can play an important role in fighting corruption in healthcare. The four broad paths identified by Zyglidopoulos et al – individuals, organizations and industries, different countries, and different cultural contexts – provide a comprehensive framework for understanding the various factors that contribute to corruption in healthcare. Research on individuals can assist in determining the psychological and sociological factors that motivate individuals to engage in corrupt behavior. On the other hand, research on organizations and industries can shed light on the structural and cultural factors that enable corruption to flourish. Corruption in healthcare can be affected in a variety of ways by a country’s economic and political systems, which can be studied in depth.
In my opinion, it will be beneficial to collaborate with international organizations and other countries to share best practices and coordinate efforts to fight corruption. it is important to implement strict laws to prohibit corrupt practices in healthcare and promote transparency and accountability within healthcare organizations with different measures such as financial disclosure for healthcare workers and educating them and all stockholders about the negative impact of corruption on patients and communities to encourage a culture of integrity and ethical behavior.
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An example of a health system improvement is the implementation of a telehealth program in a rural area. By allowing people living in remote or underserved areas to consult with healthcare providers remotely, such as via video conferencing, can improve access to healthcare.
Implementing a telehealth program may be hindered by the following barriers:
cost and lack of funding, as well as a lack of infrastructure and technology in rural areas, concerns about the privacy and security of patient information, and a lack of reimbursement for telehealth consultations all contribute to patients’ resistance to the change. -
If High Availability (HA) is implemented in HIS, It will ensure the availability of life-critical clinical systems and EHRs especially in case of emergency without impacting clinical workflows. Clinicians will have continuous access to patient data, allowing them to treat and diagnose patients without interruption.
Also, HA can reduce the impact to patients and hospital staff whenever IT needs to take systems or data offline to perform necessary maintenance tasks and provide protection from unplanned outages caused by human error or hardware failures and reduce the time HIS services are unavailable during your backups.
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STEEP Factors
Social
– Increase in population awareness of infectious diseases, hygiene, and social distancing.
– Increase of elderly patients.
– Decrease social crowd gatherings.
– Change of working hours especially for hospital workers.
– Increase of population stress and fear levels.
Technological
– Increase of Telehealth usage by hospitals and governments including remote medical consultation for non-critical cases.
– Using social media platforms for awareness campaigns.
– Increase the need for interoperability for better COVID-19 management.
– Moving to virtual meetings.
Economic
– Shortages and increases in the prices of face masks and hand sanitizers.
– Change of insurance reimbursement policies.
– Increase in hospital admission rates.
– Increase of inflation rate in countries with a weak economy.
Environment
– Increase in biohazard wastes.
– Change in environmental regulations and travel restrictions.
– Increase in the unemployment rate.
Political
– Increase governmental Telehealth adoption for better control and monitoring of COVID-19 cases.
– New government policies and regulations.
– Travel restrictions and changes in immigration policy. -
Personally, I haven’t had any experience with CIA issues. However, I used many health information systems in hospitals that do not implement a secured connection (SSL). Also, preserving the data confidentiality the system availability was a challenge even in big institutions. A few systems failed to maintain proper confidentiality by using a weak password policy and 2FA was optional to make it easier for system users.
I think organizations should hire information security professionals to review their outdated systems and assess potential risks to anticipate malware attacks and train employees to maintain CIA Triad in the organization.
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By listening to the two leaders, Prime Minister Lee Hsien Loong and President Trump we can notice a difference in applying CERC principles recommended by CDC.
1. Be First: President Trump was late in announcing the outbreak after the situation got worsened. Singapore PM announced the COVID-19 situation after two weeks of the event.
2. Be Right: Both leaders share real credible information about the current situation. But, Singapore PM provided more information and compared SARS and COVID-19 preventive measures.
3. Be Credible: Both leaders gave credible scientific evidence of the disease. President Trump expressed strong confidence that the outbreak can be contained. Singapore PM was calm, had a more natural tone, and provided an informative and trustful message.
4. Express Empathy: President Trump was somehow aggressive while talking about other countries. Singapore PM expressed an empathic message to Singapore’s people
5. Promote Action: Both leaders showed the action being taken by the government and the necessary steps to overcome the pandemic.
6. Show Respect: Both leaders showed respect for the healthcare professionals President Trump has blamed other countries, especially China for the outbreak. Singapore PM expressed his respect to volunteers and healthcare workers. -
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Hello everyone,
I apologize for the delay.
I would like to share my story. As I am working in clinical research, In 2020 and due to the COVID-19 lockdown, I was appointed by my company as team leader and responsible for 5 team members and many studies where I have to try to keep the studies running without problems and ensure patients’ safety. We as a team faced many challenges during this year as most hospitals didn’t have a place for our patients, the hospital staff was very busy and we had to find new ways to deliver the medications to patients and use the home nursery to follow up with patients. It was a tough year for all of us but we were able to achieve success with good planning and collaboration as a team. -
In my opinion, We can provide the data after masking it. This includes masking the home address locations and the contact number as this may not be useful for the new study.
Also, we need to consider if the patients know about using their information in new studies and if this information was included in patients’ informed consent.
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As a health information professional, It is my duty to not disclose sensitive information including lab results to anyone without the patient’s explicit informed consent. I believe it is inappropriate to interfere with other people and family issues.
Professional regulatory bodies, legislatures, and courts have recognized that in some circumstances, patient confidentiality may give way to protect others who are thought to be at risk of harm. We should refer to standards and laws in the region for guidance.
In addition, under public health legislation in every province and territory, HIV (and/or AIDS) is a reportable illness. You might be required to report HIV diagnoses to public health authorities. The reportable details could include the patient’s name, risk factors, and demographic information. Reporting obligations vary, so we should check the applicable laws and regulations in the region.
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In my project example in topic 1, the Drug Stock Management System. According to ADKAR model, The awareness of the change to a better tracking system and benefits were clear for hospital staff but not for patients. Not all hospital staff had the desire to change the old paper-based system, especially those who didn’t want to use a computer and login into a system instead of adding data to a paper form. Many training and meeting were conducted for all staff to have the required knowledge to use the new system effectively. The ability to implement the change increased over time. Regarding the reinforcement, It took a long time to sustain the change than expected. Overall, the organization managed to implement the change but many improvements were needed.
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In my organization we developed a new Drug Stock Management System integrated with Interactive Web Response System (IWRS) to track Investigational drugs shipments, inventories, track doses taken by patients, collect drug related adverse events and other information on patient health status with a mobile application installed on patients devise and notify and send reports and alarms to all stackholders. The system still working and relatively successful but not this after overcoming many challenges after implementing it. The design of the system needed many improvements to make it easy especially for patients and improve the data entry workflow. Data storage and system architecture was completely changed to be scalable and connect bette considering unreliability of internet connection. The budget allocated to this project was exceeded by around 50% due to the new changes and time.
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Hospitals that use the ICD to categorize patient data can drive quality improvement and have an opportunity to make a training ground for the management of big data and can provide researchers with detailed information for population management purposes. Without ICD, exchanging health data would be difficult and will cause many problems with disease classification and make it impossible to analyze it for research purposes.
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In my opinion, Before implementing a new EHR system in the real workplace setting, Clinicians should evaluate EHR and provide feedback to Health IT to evaluate the feasibility of the changes and what could be improved or customized in the User Interface.
I believe this issue will be decreased over time because many EMR providers working on improving UI/UX interface. Also, It is easier for the new generation of clinicians to deal with computer software including EMR.
In the meantime, Health care providers should invest more in EHR training.
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In my opinion, eHealth should be defined as any solution using new technologies and data exchange to efficiently improve health services with lower costs and help healthcare providers to improve patients’ lives. This includes:
– Solutions that collect patient or disease data and analyze it.
– Solutions to enable remote interactions between HCPs and patients.
– Devices that self monitor patient data to enhance personal health management. -
An example of big data is online purchasing orders from websites like Amazon or online markets and collecting customer data and order history to predict products recommendation. characteristics that fit into 5Vs are:
Volume: There is a large amount of data collected from products viewed by the customer and complete/incomplete orders.
Velocity: Data processing, analysis, and recommendation should be fast and in real time.
Value: Customer data stored for a long period to be used in predicting customer behavior and increasing sales.
Variety: Customer data contains many types from categories, geo data for a customer location, product location, price range, etc.
Veracity: Products could be supplied by many companies to customers, and data from these companies should be accurate and reliable. -
Have you ever observed a health informatics project in your (other) organization? Please provide a brief introduction.
In my previous organization, we worked on a web-based and mobile drug safety reporting tool to facilitate adverse events reporting from hospitals, patients, and doctors to pharmaceutical companies and the Ministry of Health and perform signal detection on Individual Case Safety Reports (ICSR) to help observe safety signals on different market products and investigational drug in clinical trials.How can this health informatics project help to improve the current practices?
Using the drug safety database, we were able to perform signal detection on Individual Case Safety Reports (ICSR) to help observe safety signals on different market products and investigational drugs in clinical trials.Are there any challenges or difficulties in implementing the project?
It was difficult for all healthcare providers to move from a paper-based form to a web or mobile application and add additional data from patient medical history to fulfill the minimum required data in Individual Case Safety Reports (ICSR). -
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Thank you Kawin for sharing, I believe all companies should implement practical training on phishing. For example, I worked in a company where the security system team was sending phishing emails from time to time to all employees to test their awareness and give them a credit if they reported the suspicious email.
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Thank you Tanyawat for sharing and the excellent ideas. It is interesting how the hacker got access once the developer successfully authenticated using multi-factor authentication! I think the system should detect if one user accessed the system from two different locations, especially at the same time.
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I think, as we have one IT officer with no experience in servers networking and infrastructure, we have to choose a Cloud server. This will save the costs of hardware needed to establish the physical server(s) and hire new 2-3 IT officers to run and maintain the servers 24/7.
Also nowadays there are many cloud hosting providers that comply with General Data Protection Regulation (GDPR) and other data-related regulations which make them a preferred choice for military and governmental organizations.
I would choose SaaS as the cloud computing service model, If we compared the build vs buy costs, It is better to pay a monthly or annual subscription rather than hire someone to build the web application which will take a long time in addition to paying for the periodic maintenance.
In this model, we don’t need to pay extra costs for cloud servers or worry about data backup.
Also, we can find a SaaS solution that provides many features, maybe a mobile application and we can launch the appointment application in minutes to hours with no technical skills.
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Based on the hacker experience, there are many ways to get unauthorized access to confidential information by defining a gap in the system or the process.
– using Phishing, send a fake email with a link to steal users’ passwords and personal information.
– using brute force attacks to target user accounts with a weak common password.
– arrange a Denial of Service (DoS) attack on the system server to shut it down and make it inaccessible to the end-users. -
1- During COVID-19, Governments in many countries created a mobile application connected to national COVID-19 test centers to display individual status whether never been infected or time passed from the last infection, The application aims to monitor and control access to crowded places, especially closed stores.
Another example is an application using Bluetooth technology to notify you if get close to an infected person to keep an appropriate distance.
2- The problem was the lack of interoperability between governmental applications and private projects or even on a global level. As many countries were using these applications to allow air travel or moving among cities. Also, this would reduce restrictions and test certificates needed by different countries to enter their land.
3- Improving interoperability and maybe creating a global standard enterprise architecture for COVID-19 monitoring applications would make it easy for countries to exchange information and knowledge as well for maximum control and reduce error and workload.
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Based on my background in clinical research and IT, Developing a health informatics system requires strong project management skills besides the essential knowledge in many areas to work and achieve positive communication with multidisciplinary team members. I am looking to strengthen my skills in statistics and data analysis. Also to improve my knowledge about other professionals in healthcare and their roles as a party in any public health informatics. Also, understanding the legal issues and data privacy is important to be considered during the design and development of public health informatics.
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Hello everyone,
I choose to explore the spread and transmission of Measles at the global level between immunized, infected, and recovered populations with recent data to see if it was affected by COVID-19 immunization and new measures taken by individuals to mitigate COVID-19 (masking, handwashing, distancing).
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1- The number of suicides has been increasing since 2011. The factors change lead to this increase whether or not economic factors over time should be investigated especially in a country like Thailand which differs from other industrialized countries.
2- The suicide rates were significantly driven by alcohol. As mentioned in the paper, for every additional unit of population consuming alcohol we can expect suicide rates to increase by an average of 0.086. With the increase in alcohol consumption in provinces in the north and northeast regions and mainly Phayao, we can expect to have the highest suicide rate in this region compared with other regions in Thailand.
3- Using statistical models and methods for the analysis of geo-referenced data can effectively improve our understanding and help to determine the factors that contribute to the change in suicide rates of suicides and identify the area variation of suicide risk across provinces.
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Hello everyone,
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Applying Spatial Epidemiological faces many challenges over time to be incorporated in epidemiological research. One of the main challenges is data availability and quality since spatial epidemiology is almost entirely based on the analysis of data that must be accurate and collected with accurate health equipment. Furthermore, Data protection and confidentiality of personal health data and consent over its use in medical investigations is a challenge due to new legislation in different countries.Studies with a small population size at risk lead to small numbers of events and unstable risk estimates are more susceptible to errors or local variations in the quality of both the health and the population data than studies conducted over larger areas. Also, Socioeconomic effects can have an important influence on the rates of disease observed in small areas that are associated with the siting of sources of environmental pollution.
In addition, the digital boundaries identifying the geographic units, and the geographic linkages between the various data within a geographic information system (GIS) may contain errors, including errors in the assignment of geocodes (postcodes) and The extent to which disease excesses in any truly high-risk areas might be smoothed away leading to many false positive findings, whereas a specific but non-sensitive measure will miss areas with high risk.
Using GIS technology offers a cost-effective and more efficient solution to one of the most vexing problems for epidemiologists which occurs when both the disease and environmental exposure under investigation are rare.
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The socioeconomic and physical environment can have an important influence on the rates of disease among many of the determinants of health that make people healthy or not. For example:
– Natural environment, such as plants, weather, or climate change, and Exposure to toxic substances and other physical hazards have a high effect on people’s health.
– Higher-income and social status are directly linked to better health
– Low education levels are linked with poor health and more stress
– Employment, working conditions, safe water, clean air, and healthy workplaces are all physical environments that have control of people’s health.
– Availability of hospitals and access to Health services that prevent and treat disease leads to healthier people. -
Hi everyone,
Please follow the link for my Dashboard
Tab 1: A table chart includes country and capital name with Population, GDP, Confirmed cases, Recovered cases, and Death and a slicer to filter by country name.
Tab 2: A matrix chart by continent and slicers to filter by date, continent and country name. -
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