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location variables have not been of concern to researchers for several reasons, such as:
1. Limited data on location, such as in the recording of malaria cases, not all houses/locations of transmission have been recorded, while other variables related to people and time are relatively more complete
2. Not all health practitioners are properly exposed to applications to process location data, and location-related data requires multidisciplinary involvement, such as slope data, and landscape appearances such as rivers, lakes, etc.The place where people live or work is recognized as a determinant of certain diseases because the place or location makes a person less or more exposed to disease risk. For example, people who live in forests or forest edges have a greater risk of getting malaria because they are more exposed to the risk of mosquito bites
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Hi All,
Here is the dashboard https://bit.ly/3yUFZCU , which contains:
-a map containing comparisons of confirmed cases between countries
-Card that contains information on total confirmations, cures, and deaths globally
-Table containing confirmed case data by country
– Barchart containing case confirmation data per continent
– Line chart containing daily trend of cases, cures, and deaths
– Slicer to filter data by date range
This dashboard contains daily data that can be cumulative with a slicer, so it is easy for readers if you want to know the total data per certain time range either per country, the continent, or the global total. -
Dear all,
Here is my updated dashboard https://bit.ly/3IcqCsn
The dashboard consists of:Page 2:
Cards and multi-row cards contain confirmation data for all Covid-19 cases in the world, as well as recovery and death data. Barchart contains data on confirmed cases of Covid-19 per continent and a distribution map per country, plus a slicer to view data per time range. This data visualization can describe the distribution of caseloads per continent and country.Page 3:
A line chart that contains data on confirmed cases, cures, and deaths per day, this data can be used to evaluate daily data and can be selected per country with a slicer.
line chart containing daily cases and forecasting
line and clustered column chart containing daily case confirmation data and the cumulative number of casesPage 4:
a stacked column chart containing data on confirmed cases per continent per country with the highest filtering of 10 cases and a treemap containing GDP data per continent per country. Based on the visualization, it can be seen that the top 10 countries have GDPs above 2T.Page 5:
Funnel chart containing the top 10 mortality data and a sunburst pie containing mortality data per continent and per country. Death data is important to evaluate the control of a pandemic in a country.Page 6:
Sparkline chart containing daily death data that can be filtered by country with a slicerpAGE 7:
Scatter plot chart that contains a comparison of GDP and cases per 1 billion population, based on the chart, many countries with cases over 60 billion have GDP less than 1 billion -
Dear all
Here is my dashboard for covid data analysis,
Consist of:
1. Table of daily confirmation, recovery, and death per country to evaluate the burden
2. Matrix of GDP and daily confirmation casesThank you
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https://infeksiemerging.kemkes.go.id/dashboard/covid-19
Hello every one, here is dashboard Covid-19 in Indonesia.
The dashboard consists of:
1. Absolute data on the number of cases
2. Case distribution map
3. Trend chart of confirmed cases, recovered, died, recovery rate, and CFR
4. Case graph by gender and age.The graphs used are easy to understand, most graphs and diagrams use the Length principle. but the colors used are too many and the trend graph of confirmed cases, recovered, died, recovery rate, and CFR contains a lot of data
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I have no experience doing studies, my experience in data management is developing routine information systems for malaria, processes such as:
– Audit trial/Time stamp
– User authentication and access control level
– Edit check and logical check
– Data backup and recovery plan
the above process is done, and the application to store and manage data is MYSQL and I do data analysis using excel. -
Based on my experience in data collection and data management for routine surveillance activities for malaria programs, the steps that have been taken include:
1. Protocol discussion, this is carried out with the person in charge of each division, such as laboratories, case management, discussions are held to find out the flow and work processes in the laboratory, treatment, monitoring of treatment etc.
2. Data design (Variables/ Data workflow), determines important and useful variables for monitoring and evaluation
3. Data acquisition, to determine the method of data collection, whether offline or online
4. CRF Development
5. Data Management plan development, not well written
6. Databased access control, carried out to provide authorization at every level of admin and superuser
7. Databased setup and edit check programming, have been done but edit check type has not been done
8. Data entry screen test, done
9. Investigator meeting/ CRF Completion Training, done
10 Data entry and processing, already done
11. Data validation and quality control have been carried out.If I can repeat then the step that will be done is edit check to check the consistency and range of the data
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I work in the malaria program, specifically the monitoring and evaluation division. In my experience collecting data for surveillance, I created a form to collect secondary and primary data in health services in the form of routine data on malaria patients. methods for collecting data, namely administered interviews and collecting laboratory data. problems that arise in data collection are inaccurate data, for example over 100 years of age, inconsistent data such as men but pregnant.
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Hi Prof,
Here my summary
Thank you
https://drive.google.com/file/d/1TxjmwbfiQF_LokL4mjfzEYA7BHhnKcyM/view?usp=sharing
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Hi Prof,
Here my infographic
Thank You
https://drive.google.com/file/d/1ePisFdQqSpoaS-hxjbrrSI7PEkGsXW0f/view?usp=sharing
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Hi Prof,
Here my infographic
Thank you
https://drive.google.com/file/d/1QZGfJBESmERYJyPMTbvjWDzWhUVWBQNI/view?usp=sharing
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Hi Prof,
Here my infographic,
Thank Youhttps://drive.google.com/file/d/1GDcI6W7u0llF9h_bksG6AwjVycE58JUT/view?usp=sharing
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Hi, My name is Fajar; I work in the National Malaria Program in Indonesia. I am a data manager, and my experience is developing a malaria information system, analyzing routine malaria data, and preparing documents for data dissemination. We collaborated with researchers at EOCRU to analyze individual malaria data collected through routine reporting applications.
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I will conduct a structured interview using a questionnaire to determine why people don’t use mosquito nets. In Indonesia, the data on the coverage of mosquito nets is known through a KAP survey (Knowledge, Attitude, and Action). Community perceptions and knowledge of mosquito nets were also identified. KAP survey is a quantitative survey, so it does not describe the community’s reasons so that the program does formative research to understand the knowledge, attitudes, and perceptions of the community regarding the use of mosquito nets.
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Based on my experience working in the malaria program, several things were done in the Covid-19 situation, including:
1. Provide PPE (Personal Protective Equipment) for malaria officers in the field.
2. Coordination activities are carried out virtually, including the implementation of a malaria elimination assessment for the sub-country elimination program, after the virtual assessment, the assessment committee will go to the field to validate the data and activities, the virtual meeting which is conducted first makes the implementation of the field validation shorter.
3. The training is conducted online and the training is digitized through the e-Learning platform
4. Health promotion activities on malaria are carried out by using electronic media. -
Health insurance in Indonesia is handled by an organization called BPJS. started in 2015 and has not yet reached UHC, BPJS coverage until 2021 is 85% of the population. The problem with BPJS in Indonesia is the financial deficit experienced by the agency. The financial deficit was resolved by increasing the contributions paid by the participants. this received a strong rejection from the community, but the government continued to do it, this was based on a survey which stated that the amount of contributions was very low than what was stipulated. In addition, the government also conducts a comprehensive BPJS management audit to determine the cause of the deficit. Previously, many people suspected the deficit was due to high levels of fraud, namely excessive claims made by health facilities, but based on the audit results, it was found that the low contributions caused losses.
since 2021, BPJS has finally experienced a financial surplus. This is due to the increase in the fees paid by participants and the pandemic period which makes visits to health facilities low.
BPJS continues to improve services, by providing convenience to participants. one of them is through the digitization of information systems. at the beginning of the implementation of this social security, patients had to queue for hours to get treatment. as is
e-JKN patients receive a queue number electronically.Improvement of services should continue to be carried out, as well as efforts to expand access by increasing the number of health facilities that collaborate with BPJS so that users have many choices of quality health facilities.
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The health informatics workforce in Indonesia is good, seen from the availability of personnel and education for medical informatics, but the problem is in the structure of job arrangements in the health environment for civil servants in the health environment. Functional positions for medical recorders in health facilities are included in the list, but the position of health information system designer at MoH is not yet available. This is one of the reasons why the health information system in Indonesia is not good. EHR is still segmented, and there is no EHR system that is used nationally.
Medical recorders in hospitals and health facilities are also not considered an important division, because EHR and health surveillance, including diseases in Indonesia have not been integrated, so that many applications must be used by health facilities. This causes the medical informatics workload to be overloaded. There should be a medical record division to record EHR and a public health division to record the data needed by public health surveillance of health programs.
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Sharing data provides the benefit of discovering something new by the other party. before doing data sharing, we need to know the target and the type of data according to the target. For example, sharing data for high-level dashboards for leaders, the data displayed is in the form of analytical data on the main indicators, while sharing data for research purposes is usually more detailed. Before sharing data, what we need to ensure is the quality of the data we have, complete and reliable data and in the form of data sets that are easily understood by other parties.
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Fetal Death Rate
-Definition
the number of resident fetal deaths in a specified geographic area (country, state, county, etc.) divided by the number of resident live births plus fetal deaths for the same geographic area (for a specified time period, usually a calendar year) and multiplied by 1,000.-Calculation
(Number of resident fetal deaths/Number of resident live births + Number of resident fetal deaths) x 1,000-Main Usefulness
to determine the rate of fetal death and evaluate the public health programs -
Based on my experience in the Malaria Program, the good things about EMR are:
– Better and complete data availability. individual data available
– Ease of doing data analysis, before there was EMR, the available data was aggregated data, so the data analysis carried out was very limited
– Improved data quality, data validation becomes easier so that the level of data confidence increases.Bad things about EMR are:
– The need for device and network availability. there are still remote areas in Indonesia that have network problems -
Missing data in the study due to incomplete data in the EHR can be overcome by making EHR standards and standard variables mandatory and optional. The metadata standard is an agreement between practitioners and researchers. Data analysis problems can be overcome by involving statisticians so that in research, good collaboration between experts is needed.
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I agree with the recommendations in the journal and, like other classmates, think that it is not an easy thing to do.
In Indonesia, every time we conduct training in the health sector organized by the government, there are particular materials on anti-corruption. Besides that, there are special institutions that deal with corruption, and audit mechanisms are carried out internally and externally, but corruption remains a problem in the health sector in Indonesia.
Improving the quality of information systems and updating technology can prevent corruption. For example, upgrading the flight ticket system to be online can prevent people from marking up airline ticket prices because now auditors can check the status of airline tickets in the information system.
Another example, if there is a good logistics information system, then the distribution of medical equipment and materials to people who do not have rights will decrease.
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An example of a health system improvement based on my experience where I work now is the development of a malaria information system called SISMAL. Previously, using paper-based. After SISMAL implementation data is available, it becomes easier to evaluate the program. SISMAL’s challenge is reporting in remote areas because it requires an internet network.
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Procedures for developing a disaster recovery plan include:
1. Disaster Risk/Threat Identification and Analysis
2. Risk Classification Based on Relative Weight
3. Build a Risk Assessment
4. Determining Disaster Impact
5. Evaluation of Disaster Recovery Mechanism
6. Disaster Recovery CommitteeThe appropriate technology for my organization is data backup in cloud computing. because Indonesia is a disaster-prone country, it will be very helpful if the data is stored in the cloud.
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High Availability technology in hospital information system (HIS) is helpful for patients, including:
1. Get fast and efficient service. Information technology that can be accessed at any time by health workers in hospitals makes the system can be integrated between divisions in the hospital so as to facilitate the coordination process between divisions such as pharmacy, care, payment, etc.
2. Patients get real-time information such as the availability of treatment rooms, doctor’s schedule, patient examination results, etc. -
The security of the information system is disturbed. There is an additional menu created by hackers. The effects of this are :
1. There is an additional menu
2. Flooding technique (flood the system with unhandled requests so that the system becomes sluggish)Based on this experience, the following steps were taken to prevent the incident from happening again:
1. Improve system security by adding SSL
2. Added HTacces, which are a number of rules written in programming languages to protect root applications from unauthorized users.
3. Changing the HTTP/HTTPS port
4. Database Using long and unique user and password -
The following is a ganchart of the process of developing SISMAL V3 in the form of a malaria surveillance application. I am now involved in the process of developing the application. SISMAL is a comprehensive recording and reporting of malaria programs from cases, logistics, laboratory quality assurance, vector surveillance, epidemiological investigations, and other interventions.
https://drive.google.com/file/d/1OXDfs1rzBb7wtzhi4nmSz3VOLZlmft7n/view?usp=sharing
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Hi Anawat, Thank you for the very clear presentation. In Indonesia, syndromic surveillance for leptospirosis is carried out integrated into one information system for potentially epidemic diseases, namely e-WARS (early warning and alert Response System). Is there e-WARS in Thailand too? If so, what is the difference between this surveillance and e-WARS. Thank You
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Hi Karin, Thank You for your very clear presentation, EWARS is very useful for detecting malaria outbreaks, especially in low endemic areas and for elimination, especially for malaria in eWARS not in the form of syndromic surveillance because what is reported is positive malaria cases that have been confirmed by the laboratory.
eWARS needs to be increased so that it is more sensitive to detect outbreaks. Right now, the reporting period is every week. Preferably in the future, it can be reported daily. Reports are still sourced from primary health care only. While reports directly from the hospital are not yet in the system. The possibility of missing a case report from the hospital is very high. Thank you
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Here’s a comparison of communications between Singapore’s prime minister and American president based on the six CREC principles recommended by the CDC:
1. Be First
Singapore: at the beginning of the video, he explains that Singapore has faced an epidemic for two weeks. This shows a fast communication response
America: communication when cases arise and things worsen
2. Be Right
Singapore: provides data on most of the issues from China, but some cases cannot be traced to the source. It is possible that transmission has occurred in the community.
America: less use of data as a basis for an opinion
3. Be Credible
Singapore: Provides an overview of the seriousness of the disease based on data, provides information on things that cannot be done, that traces the origin of transmission of several cases
America: Looks like blaming Europe for rising cases in America
4 Express empathy
Singapore: Expressing empathy by giving advice not to panic because the country has not locked down cities and has logistics supplies so that people don’t have to pile up instant noodles and toilet paper.
America: It looks more proud of its country than showing sympathy for the people
5. Promote action Singapore: The message given to the community is clear:
– to pay attention to personal hygiene
-Wash your hand often
-avoid touching your eye or face
-take your temperature twice daily
-if you do not well avoid crowded places and see the doctor
-as well as advise not to panic
America: same message as Singapore and adding a lot of economic mechanisms to help people
6. Show respect
Singapore: At the end of the video, he appreciates volunteers who distribute masks, students who distribute food, health workers, etc. The prime minister of Singapore also makes videos in 3 languages, English, Malay, and Mandarin. it shows respect for all ethnic majority in the country
America: not giving appreciation to people who are struggling in a pandemic situation -
The covid information system in Indonesia is quite complete, and several applications used:
1. New All record (NAR) to record laboratory tests (PCR)
2. SILACAK to record the results of contact tracing
3. Peduli-lindungi as an individual health passport to record vaccine status, latest laboratory examination results, and travel dataWhat still needs to be improved is to enter the results of the RDT examination into the New All record to obtain the results of the PCR and RDT examinations. To increase vigilance, as in Thailand, Indonesia needs to conduct sentinel surveillance at several locations and carry out periodic screening at these locations. So that early detection can be done if there are signs of increasing cases.
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Six events were declared PHEIC between 2007 and 2020: the 2009 H1N1 influenza pandemic, Ebola (West African outbreak 2013-2015, outbreak in Democratic Republic of Congo 2018-2020), poliomyelitis (2014 to present), Zika (2016) and COVID- 19 (2020 to present)
A PHEIC is defined in the IHR (2005) as, “an extraordinary event which is determined to constitute a public health risk to other States through the international spread of disease and to potentially require a coordinated international response”. This definition implies a situation that is:
serious, sudden, unusual or unexpected;
carries implications for public health beyond the affected State’s national border; and
may require immediate international action.future events that can become a PHEIC according to Says are catastrophic due to climate change
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I once weighed 62 kg with a BMI of 26.5 and was included in the overweight category, and this happened because I often went out of town and went on culinary tours in that place and held meetings at hotels that served tasty food. Besides that, due to the high workload, I often feel pressured and relaxed with food. As a result of being overweight, I often feel sleepy and tired quickly at work, and sometimes I also feel pain in the left chest area. I finally decided to go on a diet and exercise regularly. It is tough to do because of the busy schedule and mobility. I tried to learn how to diet by watching many videos on YouTube and found diet influencers who gave complete knowledge about diet based on research evidence in journals. I had never been to a gym before, and I decided to become a gym member and set a calorie deficit diet. Initially, I weighed all my meals and recorded the number of calories I ate each day. I lost weight up to 54 Kg with a BMI of 23.1, and the percentage of fat in my body also decreased from 35% to 27%. I now adopt a healthy lifestyle by eating nutritious food and a calorie deficit and exercising every day. I feel healthier, and chest pain complaints have also disappeared. Lifestyle changes can be done if we have high motivation, knowledge, and have a support system.
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Information systems are beneficial in the process of investigating an outbreak. Based on my experience with malaria outbreaks. Early warning of an outbreak can be known through an information system called E-WARS (Early Warning, Alert and Response System), an information system that collects aggregate data every week for cases with potential outbreaks. After the outbreak report is received and verified, an investigation is carried out. The national malaria surveillance information system, namely SISMAL, is a general information system, so it needs to be added with other tools.
Malaria epidemiological investigation begins by mapping cases based on the smallest administrative level, namely sub-village. SHP data in Indonesia only reached villages, so the team made their own regional boundaries per sub-village. Malaria case data was taken from the SISMAL malaria information system and visualized in real-time with google studio because more special visualization was needed, which was not accommodated by SISMAL. Based on the data visualization in Google studio, the coordinate points of cases, mosquito breeding sites per sub-village can be mapped so that the number of people and houses that are targeted for intervention can be identified for further LLINs, IRS distribution, and health promotion interventions. The visualization helps convey the problem clearly to stakeholders so that the outbreak gets attention and assistance in handling it. -
The existence of Covid-19 in Indonesia has made the government’s attention to the information system better. stakeholder awareness of the digitization of health information systems is getting better. There are 3 covid information systems in Indonesia, namely the New All Record (NAR) in the form of a laboratory-based information system that records all confirmed cases and their examinations and is connected to the peduli-lindungi application as a health passport application if the results of the examination are negative and have been vaccinated up to the second dose. travelers may travel by plane. In addition, before entering the center of the crowd, everyone is required to scan the barcode of the place and check-in through the Care-Protect application so that the number of people in the building can be monitored.
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– How can surveillance help to detect and control the disease?
surveillance can help detect and control Covid-19. the availability of data makes it easier for officers to respond quickly to tracking cases so that they can control the spread of cases– Should we conduct active or passive surveillance or both for the disease, why?
Covid-19 surveillance is carried out passively and actively. Passive surveillance is carried out to determine disease trends and must become disease surveillance that mandatory notifiable disease by all health facilities. Active surveillance is carried out for preventive responses such as case tracing– Which method should be best to identify cases, why?
Cases in medical facilities VS community
both are important in covid surveillance. Case-based surveillance in health facilities is important to do to find out the number of confirmed cases and community-based surveillance serves to capture cases that have obstacles to go to health facilities
Sentinel VS population-based surveillance
Case-based VS aggregated surveillance
Cased-based surveillance is better than aggregated surveillance in handling Covid-19. The data variables obtained from cased-based surveillance are more numerous and varied so that it is easy to conduct a more in-depth data analysis to find out the epidemiology of the case. besides that case tracking is also easy to do if cased base surveillance
Syndromic VS laboratory-confirmed surveillance
Laboratory-based surveillance is more appropriate to implement than syndromic surveillance for covid-19 surveillance because other diseases can have the same symptoms as covid and covid diagnostic enforcement can be done easily and quickly– What dissemination tools will you choose to disseminate COVID-19 surveillance information? Why do you choose this/these tools?
Dissemination of data to the public on the official website is data that has been verified by each level in order to avoid data errors -
Based on Indonesian regulations, health-related data is sensitive personal data. Based on the health law, every person has the right to keep his health condition confidential, but this does not apply in the case of statutory orders, court orders, relevant permits, the interests of the community, and the interests of the person.
The utilization of data for research is beneficial for the wider community. as a data manager, I will discuss with my supervisor first and I will explain the rules to my supervisor after the supervisor agrees to provide the data I will ask the researcher to make an official data request letter and make an NDA (Non-Disclosure Agreement) which states that the researcher will maintain the confidentiality of the data and if the data will publish the results of his research then with the permission and knowledge of the malaria program. after that, we will provide data by hiding the identity of the name and residence code
Regarding researchers from abroad, we will first ask for permission to research in Indonesia. Based on Indonesian regulations, foreign researchers who will research in Indonesia must involve researchers from Indonesia and the relevant ministry permission. and the malaria program will consult the bureau of foreign cooperation affairs in MoH
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as a health information professional who has the task of recording the medical records of HIV patients, I Cannot disclose the patient’s HIV status, this is in accordance with the General Principles of informatics ethics in the health information system, namely the Principle of Information Privacy and Disposition. Indonesia has implemented and made regulations regarding counseling for HIV patients. patients with positive HIV test results will be accompanied by a counselor and patients will be advised to notify their sexual partners. related to the principle of doing good and doing no harm to others, at the time of counseling, it will be notified if an HIV patient intentionally transmits his disease to others, he will be subject to sanctions and his HIV status will be disclosed to the public.
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Before SISMAL V2 was implemented, because SISMAL V1 failed, program data collection was done manually using paper-based. After SISMAL V2 was implemented, there was a change, digitization in the recording and reporting system. organizations are successful in making changes. the following analysis according to the ADKAR model:
1. Awareness: this change is made easy because the awareness to change to the recording and reporting system is owned by the leadership and all staff
2. Desire: the motivation to use the new system is not shared by all users, especially some officers in primary health care, districts, and provinces. support from important people such as leaders at MoH, experts, WHO members, by motivating to use the new system in every meeting to motivate officers.
3. Knowledge: Socialization of the new system is carried out massively and in a cascading system with sufficient funding support
4. Ability: the user’s ability is improved through intensive training and tiered guidance as well as having a team as a helpdesk
5. Reinforcement: to maintaining the users continue to use the new system, regular evaluation, and feedback monitoring is carried out as well as rewards for users who are submitting reports complete in timely manners -
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