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I tried watching VR videos on YouTube and VR apps such as VR Moon and VR Space. Honestly, I found it very hard to enjoy the experience. The stereoscopic vision was uncomfortable. Immediately after putting it on, I got motion sickness. I also noticed that my right and left eyes were trying to calibrate and not working together for some time. I worried that it might lead to cross-eyedness. After adjusting, aligning, and adapting the vision, I watched VR videos for a minute, and then I got pain or an ache around or inside my eyes.
A standout feature, I feel, is that it replicates the maximum experience of realism. Watching YouTube VR videos on “Indigenous people in the Amazon forest” and “New York street walk” feels like I was there walking and going for an adventure, and makes me realize what it’s like to be there. However, my phone does not have a very high pixel density, which makes me feel like watching pixelated videos or a pixelated experience.
I could only find the head gaze combined with the screen tap interaction method in Google Cardboard and YouTube. The VR cardboard seems purposely made to be smaller than the average size of the phone. My phone, for instance, is bigger and has extra screen space. Later, I found that it aims for screen tap interaction with head gaze.
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Visualization & Experimentation
While the aircon is on, the temperature and humidity remain the same.
After turning it off and opening all windows, the humidity climbed up while the temperature increased gradually.
Then, I tried to test it with all windows closed while the aircon was still off. The result shows that the temperature and humidity stay in balance.
After the aircon is turned on, I noticed that as the temperature decreases, the humidity also decreases.
During this experiment, the circuit board and sensor are stationary.
Challenges & Solutions
After uploading code to the circuit board, I could not see any output in the console. I noticed that it is suggested to use 9600 baud written on the board. After changing the code to
9600 baudand the console to 9600 baud, it becomes visible.Ideas for Improvement & Application
If I had more time, one modification I would make would be to cache failed records and push them if the internet connection is restored. Because while I was testing this experiment, I was using my neighbor’s Wifi (a very, very poor connection).
In this case, the complexity is not as simple as we think. Because, as far as I’ve researched, the ESP 8266 microcontroller does not have an internal clock. So, we have to manage time programmatically again.The trick is to retrieve the current time from the Network Time Protocol (NTP) via Wi-Fi (internet). Once we get the current time, we compute the current time as time goes by in the loop. However, this can drift over time. So, re-adjusting the clock with NTP will be needed once the connection is restored. While the connection is offline, take the current time from the internally running computed time and cache it with temperature and humidity data.
A real-world public health scenario where this system could be useful is monitoring vaccine cold chain temperature. So, if a circuit board is integrated / integrable with a telecom network/telecom module, it could trigger an automatic SMS alert. If we continue to use the ESP 8266 microcontroller, we could use a cloud communication platform such as Twilio to trigger an SMS message via API.
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I chose an old article, “A Review on Architectures and Communications Technologies for Wearable Health-Monitoring Systems” by VÃctor Custodio, Francisco J. Herrera, Gregorio López, and José Ignacio Moreno (2012) to see what an IoT looked like previously.
Summary
What it does—The article details the LOBIN platform, an IoT platform based on e-textiles and Wireless Sensor Networks (WSN) for healthcare monitoring.
Where it was implemented – It was implemented as a pilot scheme in the Cardiology Unit of La Paz Hospital in Madrid, Spain, to monitor psychological parameters and track patient location.
How it generally works– The system utilizes smart shirts (e-textiles) integrated with sensors that transmit data wirelessly through a network infrastructure.
Key points
Objective – The primary goal is to enable non-invasive and pervasive monitoring of patients with cardiac issues, but within hospital settings. It also aims to measure physiological data (ECG, Heart rate, SpO2, etc) and the indoor location of patients in real-time.
Sensors used –
(1) e-textiles electrodes to measure ECG
(2) 3-axis accelerometer to detect body movement and position
(3) thermometer to measure body temperatureChallenges –
(1) ECG signal loss during patient movement
(2) Data packet loss in their Wireless Communications Infrastructure Subsystems (WCIS)
(3) Patient discomfort requiring modifications like adjusting the smart shirt’s tightnessReference:
Custodio, V., Herrera, F. J., López, G., & Moreno, J. I. (2012). A Review on Architectures and Communications Technologies for Wearable Health-Monitoring Systems. *Sensors*, *12*(10), 13907-13946. https://doi.org/10.3390/s121013907
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If the dashboard’s target audience is policymakers, it will be a bit scientific and filled with non-layman terms and indicators. In my dashboard, I’ll focus on simplicity.
For the dashboard, I chose Covid-19 dummy data and specified locations with states and regions in Myanmar. The disclaimer here is that the data will not make sense.
As for the policy makers viewing the dashboard, I assume that the following indicators will be important
_ incidence rate: the rate at which new cases are positive in a population per 100,000 people
_ mortality rate: the rate of deaths in a population per 100,000 people
_ case fatality rate: the rate of deaths among positive cases in a population per 100,000 people
_ confirmed / positive cases: the number of positive cases
_ deaths: the number of deaths
_ recovered cases: the number of cases being recovered
_ active cases: the number of positive cases right nowTherefore, I put those essential indicators as a scorecard in the dashboard.
Additionally, the map and detailed table are included. The map helps in identifying patterns of disease distribution geographically. The table describes a detailed report of surveillance information by regions across the country.
The Weekly Trend page is aimed at viewing the trend every week, which allows policymakers to view the trend as smoothing out daily fluctuations and providing a clear picture of the epidemic’s direction, trend, and patterns, which inform their decisions on public health measures, resource allocation, policy adjustment, and so on.
Here is my Looker Studio Project: https://lookerstudio.google.com/s/jVsxj2nfPqk
Please feel free to comment.
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Looker Studio -> https://lookerstudio.google.com/s/vSbz9jI5P2k
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1. Overview: Includes Score Card, Bar Chart, Running Sum and comparison
2. Cases / Deaths / Recovered: Includes Pivot Table, Running Sum and comparison
3. The last 28 Days Report: Includes Time Series
4. Cases Table by Date: Includes Table, Running Delta, Drill Down and Date, Running Sum and comparison
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I would like to share COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU).
What I like:
– At a glance, all important information is displayed and the site is responsive to any screen/device sizes.
– Color grading is strong but maintains the importance of information from RED for cases/deaths, GREEN for vaccination, creating intuitive associations
– Prominent key metrics at the top catch the eye (enhance iconic memory)
– Information metrics groups are chunked well for better working memory.
– The dark and minimal background avoids distraction patterns.What needs improvement
– Following chunking principles, large numbers are difficult to process such as 676,609,955 and it would be better displayed as 676.6M to reduce cognitive load.
– Red-green color scheme can be problematic for color-blind users
– Crowded country metrics in the left sidebar are unnecessary and do not allow easy comparison. This could be improved by an approach with a shorter list for better visual hierarchy. -
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Very neat and practically clear design which is very friendly with data collector, especially in wide tick box.
In my opinion, I would remove weight in collecting demographic data, which I assume that it cannot be associated with the study.
Physical examination is well categorized including a detail section to provide its abnormal codes.
I am not sure what collected sample type means. If there is ID in the specimen or lab result, we can also add it.
More detail information about administrated vaccine can be added such as site of administration, route of administration, lot no, which would help in tracing back in finding out in manufacturing fault and adverse events.
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This week, we were introduced to the principles of ethics (general principles as well as principles for health informatics). Then, we were provided a case study of ethical and legal issues if an external person is outsourced for research. We also learned the 4-factor assessment for breach. Individuals have duties and obligations to be followed with ethical guidelines such as AMIA’s code of Professional and ethical conduct 2018. Entities have EU regulation in EU and Thailand regulation in Thailand respectively for personal data protection.
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I would simplify the normal way of encoding presence or absence as binary digits for pregnancy tests: 0 for negative, 1 for positive like in a physical examination where 0 is normal, and 1 is abnormal.
This could help in data analysis consistently with 0 as false, absent, or negative and 1 as true, present, or positive. -
The obvious benefit of having data standards regardless of any purpose is that they make data communication easier. Otherwise, data must be re-aligned for interpretation in multiple formats for different partners.
One simple example is the date format. Let’s suppose we are going to collect blood pressure including these indicators: systolic blood pressure, diastole blood pressure, and the date and time being measured. In this example, the date could be written in different ways: 2025-03-21, 21-Mar-25, 21/03/2025, 21/03/25, 21-Mar-2025, etc…
If a researcher has to combine all data from different sources that are unstructured/non-standard, he has to spend much time re-aligning the date format.
Therefore, data standards facilitate data communication faster and easier than non-standards for all parties.
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My team and I conducted the best way to manage computer systems to provide access systems and data internally and externally. The requirements include more than data quality and integrity with audit trial, user authentication, access control level, checks, data backup, and recovery support.
In scoping down for data management, we can think about it in two ways: database-only or system-wide database management.
For database only, enterprise-grade relational database management systems provide robust support for these features. The selected choices are Oracle Database, PostgreSQL, MySQL, and IBM Db2.
For the system-wide database management, it should be handled by a domain network system (with such Domain Controller, Active Directory). This can safeguard not only the database but also a wider scope from services running inside a computer to the whole network.
In my experience, normally spreadsheet programs can meet the requirements of study projects when it comes to data, however, they lack auditing standards, the ability to provide different levels of access, strong type checking, and data backup and recovery support.
But if we are looking for a specific field such as clinical trials, public health, and hospitals, we will have to look for specialized data management systems in adherence to standards and guidelines.
Ideally, study projects should be considered based on the nature of the study such as type of study (observational studies or interventional studies), study size and complexity (small pilot or large, or trials), collaboration needs (access control), the need for standards and compliance, project budget and so on. Examples are REDCap (Research Electronic Data Capture), OpenClinica (Community Edition), Castor EDC, etc…
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In my experience, the data collection and management process is very simple, involving setting up data type and validation, data collection, and data visualization. When it comes to data entry, there was neither double data entry nor single data entry with manual review. The given workflow also seems unrealistic for underserved communities with human resource shortages, where clinics and health centers are funded by donors or NGOs.
Nevertheless, based on the provided data management workflow, I would add protocol discussion to ensure everyone is on the same page with the agreed protocol. Second, I would implement database security and locking to prevent information leaks. Another significant consideration is a document sharing policy and to share the data in a public data repository during the project closure if its donors or owners allow so that it can support researchers to conduct future studies. However, if the project or program is executed in the enterprise or private hospital, I would follow the given comprehensive data management workflow.
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In Oct 2021, I conducted mental health pilot research on whether playing mobile games is one of their mental reliever, targeting young adults between 15 and 30 years old, experiencing the political unrest and civil war following the coup.
The primary data were collected quantitatively via an online form. There were not any problems regarding the data collection since it was digitally validated and provided with a lucky draw program, which does not influence or skew the results.
The finding concluded that mobile games offered a temporary distraction from the grim political situation in Myanmar rather than actual mental relief.
The challenge in this pilot research was in formulating research questions that deviated from the objectives of the research.
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I have learned case studies of whether AI assistance can hurt or improve their performance, balancing innovation and ethics, generative AI and medical ethics, and, more importantly, how to be ethically responsible in research and innovation. I have also learned what to consider in research with AI, including the regulatory aspect.
I re-organized this knowledge into three topics: Precaution, AI & The future of Healthcare, and AI Governance.
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Primary Health Care (PHC) is a whole-of-society approach to health that aims at ensuring the highest possible level of health and well-being and their equitable distribution by focusing on people’s needs and as early as possible along the continuum from health promotion and disease prevention to treatment, rehabilitation and palliative care, and as close as feasible to people’s everyday environment (World Health Organization: WHO, 2023). The primary care system assesses how early and convenient a sick person can get treatment. It is the first level of contact between individuals and the health system.
The availability of the primary healthcare system has been widened from centralized, urban-focused to decentralized, community-driven healthcare services in Myanmar. According to Grundy & et., al. (2014), the development of primary health care began after the post-independence period extending up to the 1988 uprising political event; the second period from 1988 to 2005 is when the country launched a free market economic model, but experiencing very low levels of national health investment; the third period (2005-2012) was the first attempts at health reform and recovery including national political reform and international politics; the fourth period was during the democratic transition period (2012-2020) which increased levels of development assistance for the health sector.
Before the 2021 military coup, the primary healthcare system (PHC) of Myanmar was handled by multiple stakeholders: private (for-profit), public (non-profit), ethnic health organizations (EHOs), and international development assistance. In the areas governed by ethnic armed organizations (EAOs), PHC services are provided by EHOs.
During the COVID-19 pandemic, the people-elected democratic government formed the National-level Central Committee on Prevention, Control, and Treatment of Coronavirus Disease 2019 to strengthen governance, scale up testing capacities, and coordinate emergency responses while maintaining essential services such as maternal and child healthcare (Lin et. al., 2023). Several health interventions were implemented at the primary level during the pandemic.
According to the case study by Lin et. al. (2023),_ Scaling up COVID-19 tests: With international support, Myanmar expanded its testing capacities from around 400 tests per day in April 2020 to around 12,000 tests per day by mid-September 2020
_ Expanding public awareness: The Ministry of Health and Sports (MoHS) utilized various media platforms to disseminate information about COVID-19. Celebrities and community leaders were also engaged in public awareness.
_ Telemedicine services: Teleconsultation services were provided by private hospitals and non-profit organizations.One month before the first case was detected, the government began active surveillance, trained health providers and professionals, and pre-allocated essential medical supplies. Nevertheless, Myanmar faced a shortage of human resources. The MoHS invited volunteers with medical backgrounds and community health workers. Volunteer support was critical in ensuring families received medical assistance. Intensive care unit beds and ventilators could not be provided. Generally, challenges included a lack of human resources when needed, limited testing capacities, weak infrastructure, and insufficient medical facilities. Additionally, there was no information and health services in conflict-affected areas.
While the democratic government was trying to control the COVID wave, the military seized power on 1 February 2021. From that point on, Myanmar’s healthcare system collapsed and corrupted. The consequences in the medical sector I encountered firsthand were brutal, for example, (1) a surgeon in Yangon refused to perform a medical procedure because a 2-week-old baby and his parents came from an affected state * * without even offering a COVID-19 test * *, (2) blocking the entry of life-threatening patient to a hospital * * denying them a COVID-19 test first * *, and (3) the military forcefully seizing oxygen cylinders meant for patients from private and public hospitals through armed threats. In the face of such adversity, people managed to struggle for their lives and built support mechanisms through community empowerment and coordination.
In my opinion, just as people were able to struggle through COVID-19 with community empowerment, and just as the people continue to resist the dictatorship system and fight for freedom with their own capabilities until now, Myanmar’s collapsed healthcare sector also has many opportunities to strive to achieve basic healthcare services for the public in rural or urban, or conflict areas or wherever they live, no matter what difficulties exist.
In conclusion, Myanmar’s primary healthcare system demonstrated resilience and innovation by government and non-government organizations including community empowerment during the COVID-19 pandemic despite political unrest. Continued support in community-based healthcare infrastructure from overseas development assistance is essential for maintaining primary healthcare access and ensuring health equity in Myanmar.
References:
World Health Organization: WHO. (2023, November 15). Primary health care. https://www. who.int/news-room/fact-sheets/detail/primary-health-care
Grundy, J., Annear, P., Ahmed, S., & Biggs, B. A. (2014). Adapting to social and political transitions – the influence of history on health policy formation in the Republic of the Union of Myanmar (Burma). Social science & medicine (1982), 107, 179–188. https://doi.or g/10.1016/j.socscimed.2014.01.015
Lin, A. M. H., Tin, N., & World Health Organization. (2023). Myanmar: a primary health care case study in the context of the COVID-19 pandemic. World Health Organization. http s://iris.who.int/bitstream/handle/10665/372726/9789240058811-eng.pdf -
Please share about the work towards the UHC scheme in your country, what works and what needs to be done to make it work, and its strengths and weaknesses, for example.
Universal Health Coverage is about ensuring all people get the quality health services they need, without experiencing financial hardship (World Health Organization: WHO, 2019). Universal Health Coverage (UHC) is not a realistic statement; however, it is a powerful concept that drives responsive governments to accomplish it.Having said that, public health services are not provided for free by governments. Instead, they manage to secure the required budget through various mechanisms including national health insurance plans, tax-funded systems, and employer-based contributions. In the absence of other funding options, philanthropic health NGOs become the exclusive providers of primary healthcare.
#_ The work towards the UHC scheme
Myanmar relies on an out-of-pocket scheme. Myanmar National Plan 2017-2021, based on the UHC concept, was introduced before 2017. The plan focuses on extending access to a Basic Essential Package of Health Service (EPHS) to the entire population by 2020 while increasing financial protection (Ministry of Health and Sports, 2016). In terms of the UHC dimension, it focuses on the population with basic healthcare services while reducing out-of-pocket spending on health.
#_ What works
As a result of this plan, according to the report by The Lancet. Global health (Han et. al., 2018), coverage of health services ranged from 18.4% to 96.2% nationally, however, most indicators such as skilled birth attendance, and the institutional delivery rate fall below the 80% UHC target. In terms of quality of care and services, the progress is limited to success due to underfunded township health facilities and a lack of standardized training for ethnic health workers (Community Partners International, 2024). Regarding cost reduction, 2% were impoverished by healthcare costs while 14.6% of households faced catastrophic health payments (Han et. al., 2018).
#_ What needs to be done
As a solution, increasing funding for township-level health facilities and expanding community-based health workers (CBHWs) to rural areas could strengthen community health systems. According to the World Bank report (2017), one suggestion includes governance reform to increase accountability and eliminate inefficiencies. The Ministry of Health and Sport underspent 15.26% of its budget allocation in 2016–2017(The Ananda, 2018)._ Strength and Weakness
While this plan possesses strengths, it also exhibits weaknesses. Some of the positive impacts are (1) covering more area and more population and (2) reducing out-of-pocket expenses and eliminating financial hardship. Some of the challenges in executing the plan are: (1) lack of human resources and increased medical staff turnover rate, and (2) underfunding leading to health disparities.
However, the military coup in 2021 exacerbated weaknesses. It has devasted healthcare infrastructure leaving the population with severely limited access to basic essential healthcare. Myanmar’s UHC index declined from 52 in 2015 to 52 in 2021 (ASEANstat, 2024). The score is now anticipated to decrease significantly more than in 2021.
In conclusion, the National Health Plan (2017-2021) delivered primary healthcare services more or less than 80% UHC target. The military coup in 2021 jeopardized Myanmar’s healthcare system, undoing years of progress.References
World Health Organization: WHO. (2019, October 3). Universal health coverage. https://ww w.who.int/southeastasia/health-topics/universal-health-coverage
Ministry of Health and Sports. (2016, December 15). Myanmar National Health Plan 2017 – 2021. https://www.mohs.gov.mm/page/5832
Han, S. M., Rahman, M. M., Rahman, M. S., Swe, K. T., Palmer, M., Sakamoto, H., Nomura, S., & Shibuya, K. (2018). Progress towards universal health coverage in Myanmar: a national and subnational assessment. The Lancet. Global health, 6(9), e989–e997. https://d oi.org/10.1016/S2214-109X(18)30318-8
Community Partners International (2024, September 13). Universal health coverage in Myanmar: The way forward – Community Partners International. Community Partners International. https://cpintl.org/type/impact-story/universal-health-coverage-in-myanm ar-the-way-forward
Moving toward UHC : Myanmar – national initiatives, key challenges, and the role of collaborative activities. (2017). World Bank. https://documents.worldbank.org/en/publicati on/documents-reports/documentdetail/991991513148339321/moving-toward-uhc-myan mar-national-initiatives-key-challenges-and-the-role-of-collaborative-activities
The Ānanda. (2018). Giving but not receiving it. https://www.theananda.org/en/blog/vie w/underspent
ASEAN Secretariat & UN Global Database. (2024). ASEAN Health Worker Density (per 10,000 population), 2022. In ASEAN Health Worker Density: Vol. VI. https://www.aseanstat s.org/wp-content/uploads/2024/03/ASEAN-Statistical-Brief-March-2024-FINAL.pdf -
About 84% of Myanmar’s population with lower socioeconomic status resides in rural areas. Most rural areas lack electricity, safe drinking water, and poor sanitation. This contributes to poor health outcomes. For basic health services, there are NGO-established village health centers. However, more serious conditions require travel to the nearest city hospitals.
The political unrest since the military coup has further caused health disparities. Healthcare has become a battleground nationwide except for the urban centers particularly, Yangon and Mandalay.
In rural areas, the quality of care cannot be expected while struggling for basic care. Essential healthcare is facilitated by internally displaced health professionals within the affected communities. Access to medicine and required equipment is obtained through neighboring countries with external support from various countries. In the military-controlled areas, of Yangon and Mandalay, primary, secondary, and tertiary healthcare services are easily accessible.
Addressing these gaps is a complex undertaking. Political considerations matter in this context. Peace is the only medicine that heals wars. However, practically saying, conflict is a transition phase to eternal peace or hell depending on the conqueror.
Within the context of healthcare, continuous external support from people around the world through the neighboring countries and the presence of available human resources would stabilize the current phase of health service (basic service). Sadly, it would not be feasible to advance to a higher level of healthcare in conflict-affected areas since hospitals are easily vulnerable to military airstrikes.
In conclusion, access and quality of care continue to widen between rural conflict areas and military-controlled urban centers. Although there is no way to fill the gaps, maintaining basic health services in rural areas requires external aid.
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Your discussion makes me wonder how sensors can get actual values instead of dependent values. In your case, temperature values are not immediately responsive to the environment but are being settled with heat affected on board (itself).
Your observation about the interval is very insightful. I didn’t realize that because the time value comes from App Script, and there’s a significant delay in data transmission, the sensor’s timestamps end up being incorrect. -
When my phone is also not fit with the cardboard, I utilize the extra screen space for touch/click interaction, where a pointer moves with my head on the VR screen (phone screen). So, to select an item, you can tap anywhere on the extra screen space. To navigate back, I rotate 90 degrees as described in the help tutorial on the Google Cardboard app.
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Thank you for sharing a very insightful article. It is a comprehensive framework for IoT from all dimensions. Although the article does not explicitly mention the details of specific technical, logistical, or ethical challenges, it emphasizes the importance of 100% correct data transmission, identifying faulty sensors, the privacy of patients, and the increasing cost of investment.
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I found your dashboard styling very advanced and well organized to fit on one page. On the other hand, there are some areas I would improve in terms of human perception.
_ less red color in the scorecard area on the left side; instead, the text color will be black by default, if serious, it will be red in title or number
_ use text for labelling instead of using scorecard default field name labelling which cannot be modified (in state / region scorecards, beneficiaries count labelling)
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Hello Wannisa, as always, your presentation is elegant and aesthetic. I notice that controls, charts, and buttons are well organized and placed in the appropriate positions. Conditional formatting styling allows us to focus on the important information. I see that in this dashboard, you’ve followed all the principles learned from this course, for example, using graphic in donut chart.
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Hi Kedsarin, your infographic is super creative and includes most of the discussion points in the webinar. If there is a legal case from using a teleconsultation app, not only doctors but also the platform could be held responsible in places where the platform is not required legally to have a physical hospital and services.
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Hi Wannisa, thanks for sharing a summary that covers everything we’ve learned and discussed this week. I think the challenge of “legal issues when a problem occurs” could be simplified when a teleconsultation service via an app requires physical hospital and healthcare services, as in Thailand. Otherwise, as you said, legal issues could be debatable when a problem occurs.
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Very detailed and concise infographics including our discussion points. As Jumbo discussed in the webinar, there could also be a case in which employees sometimes do not differentiate between ethical and unethical actions. In that case, as you mentioned in the graphics, reinforced training would be definitely helpful.
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Thank you for sharing your experience, Aung. My valuable lesson from the lecture is that determining the data collection method should be based on the familiarity of people at the operational level because my experience with communities suggests that electronic data capture (a method unfamiliar to data collectors despite being trained for several months) can slow down their data entry causing less data than aimed if it is validated excessively while moderate validation can lead to invalid data. I agree that digital survey or mobile-based data collection is the best for us who are already familiar with it. Regarding data, I believe that making de-identifiable data public (if permitted) would be highly beneficial. This also requires planning at the beginning of the project. The value of data is realized through sharing and analysis. Archived data is dead and useless. On the flip side, in the Myanmar context, de-identifiable data could be re-identified by the authoritarian regime for strategic misuse, such as the total population in a specific area and resource distribution.
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I agree that community-based surveys can not satisfy this workflow standard. Data checks are also essential before processing data for analysis if paper-based data collection is used. Additionally, I think that we could also add single or double data entry with manual or peer review to ensure the quality of data.
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I agree that field-based and remote-based experiences are different. Not only are data skills important, but also communicating between multiple stakeholders (focal person, research team, technical team) requires a lot of soft skills. Because the way we communicate can impact the result (I would call it communication bias)
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I agree that people in rural areas do not traditionally receive quality care with being in a low priority. If basic health care is not managed to be distributed equally to the entire population (or state/region/division) of all races, health equity is a fancy term used by public health professionals.
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I like the idea of giving more incentives to work in rural areas. According to the law of economics of scale, people in rural areas are not financially viable, therefore, those places cannot scale up many resources and infrastructures. Regardless of those factors, doctors should be assigned enough for patients. If assigning doctors to where they have to work is determined by themselves, providing more incentives could be an attractive factor.
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Thank you for sharing SSS and CSMBS in Thailand. I understood that the difference between them is that they include the benefits of family members for CSMBS. However, from a different perspective, to be fair, employees working in private sectors are assumed to earn more than civil servants. With this assumption, I think that the benefits are skewed into civil servants.
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