Tanatorn Tilkanont

I would like to discuss the point number 12 on page 342. This point mentioned the common misinterpretations of single P values that “P values are properly reported as inequalities (e.g., report “P < 0.02” when P = 0.015 or report “P > 0.05″ when P = 0.06 or P = 0.70)”.

The practice of reporting P-values as inequalities, such as ‘P < 0.02’ or ‘P >…[Read more]

Just notice that non-identifiable data in combination could identify someone particularly.
Myself, the non-identifiable data of the following combination could identify me.

Previous graduate : Faculty of Pharmaceutical Sciences, Khon Kaen University
Current education : MSc, BHI, Mahidol University
Current job and workplace : related to Data…[Read more]

To understand why respondents are not using bednets for malaria prevention, I suggest conducting a review of existing research as a first step. This can help identify common reasons for not using bednets to prevent malaria. Additionally, if the demographic data are collected, analyzing demographic data, such as age, gender, education level, and…[Read more]

When replacing an old technology with a new one that is easier to use, at least it should be as useful as the old technology, if not more useful, to ensure user acceptance. If users perceive the new technology as less useful than the old one, they may be resistant to adopting it, even if it is easier to use.

To encourage the adoption of the new…[Read more]

I agree with all colleagues’ comments. There are several external variables that can influence an individual’s perceived ease of use or perceived usefulness of a new technology, including:

First, Socioeconomic status and Accessibility;
People with higher socioeconomic status may have greater access to technology and may be more familiar with its…[Read more]

Hi, everyone.

I am Tanatorn from Thailand. I am currently working as a Clinical Data Associate in a private clinical research organization. My responsibilities briefly include clinical data management, development of CRF/eCRF design and annotation according to study protocol, and validation/edit checks for the Electronic Data Capture system to…[Read more]

Efficacy refers to the capability of an intervention to produce a desired outcome or effect in a controlled or ideal setting. For example, the efficacy of new flu vaccine has been shown in a randomized controlled trial to reduce the incidence of influenza in healthy individuals by a certain percentage.

Effectiveness is a measure of how well an…[Read more]

I agree with my friends’ previous answers, and I can think of another confounding factor: living area and location. Since we don’t know the demographic characteristics of the study subjects in Thailand, the location setting could affect the relationship between age and contact patterns, leading to incorrect conclusions.

For instance, young adults…[Read more]

As per the Centers for Disease Control and Prevention (CDC) website, the mortality rate is a measure of the frequency of death occurrences in a particular population during a designated time frame. The formula used to calculate the mortality rate of a given population over a specified period is as follows:

Calculation: Mortality rate = (Number of…[Read more]

The Universal Health Coverage (UHC) system aims to cover a wide range of health issues for the maximum number of people, while sustaining and adequately financing the system without incurring out-of-pocket expenses.

In addition to the information mentioned by my classmates, I had the opportunity to discuss dental health with a dentist in regard…[Read more]

During the COVID-19 pandemic, I worked at a clinical research organization and was not directly involved in the control policy for COVID-19. I used to work the same job as K.Kansiri and my practice under the organization is quite similar. As a Clinical Research Associate (CRA), I had the opportunity to be responsible for monitoring a COVID-19…[Read more]

Thank you for sharing. During the COVID-19 pandemic, my company has the similar policy as you mentioned.

Thank you for sharing. Data security (including privacy and confidentiality) is also my first concern when deciding of sharing the data because health data contains sensitive information and people should have their right to protect their personal information.

Yes I also agree, those locations have popular universities. Could this be implied that the health informatics is popular among researches in universities with high technology however, it is still unknown in rural areas?

Thank you for sharing. I like the point you share about the internship of health informatics field. I believe this can also increase the well-known of health informatician’s role in Thailand.

Health informatics is a field that includes a diverse range of professionals, including those who specialize in health information management, clinical informaticians, IT experts, data analysts and scientists, project managers, and educators. However, in my country, there is a general lack of awareness and understanding of the field among the…[Read more]

In my opinion, data sharing is a crucial aspect to consider for several reasons.

Firstly, it is important for data sharing to ensure the privacy and security of individuals whose health data is included in the dataset, through processes such as de-identifying the data or limiting access to authorized individuals.

Secondly, it is essential to…[Read more]

Since last 4-5 years ago, I have joined a private hospital as an IPD pharmacist. During that time, the hospital had recently implemented the electronic medical records (EMR) and encouraged healthcare workers to use it instead of paper-based medical records. It took a long period to fully utilize the EMR as it is a major change of workflow in the…[Read more]

The challenges are in every step of Big Health Data management, starting from the source of data collection to its application. In this articles, Silverio A, et al. had mentioned the challenges of big health data and how to deal with those challenges, including;

Missing Data: The missing data in big health data is uncontrollable. Thus, this…[Read more]