University of nairobi idis research papers


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A Case Of Abyei sudan. Intercommunal Armed Conflict And Government. Kenya — China Bilateral Foreign Relations: Case Study Of Kenya. Refugee Influx And in security: Kenya's Experiences, - Intercommunal Conflict Over Natural Resource. Many [field staffs] do not understand it. With incomplete data, it is difficult to retrieve valid results from DHIS 2. There is male, female and transgender.

There should be a system that [the] computer would recognize the gender automatically when pregnant women has been marked. We should not put it manually. Instead of using unique health identification numbers to track patients, their cell phone numbers are used. However, it is difficult and time-consuming to search the database with a cell phone number. To get around this, CHCPs prefer to enroll follow-up patients as new ones.

This raises a data quality issue since repeat clients are identified in the system as new clients. According to the key informants, this has created a gap in the system, as it is not possible to track the health status of a single patient in the existing system during data analysis and visualization. It was also noted that the platform design makes data validation challenging. Updating the data entry forms to facilitate comparisons among data variables is challenging. DHIS 2 has started with version 2. Each time the data entry forms are changed it becomes more difficult to compare the old and new data because the software cannot match the data variables, resulting in invalid findings.

They think, there was a box here in the older version, where did the box goes now with the newer version?

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Several informants reported that in the existing system, searching for sub-districts is a time-consuming process. At the supervisory level, district and sub-district health managers could not find the time to use DHIS 2 on a daily basis because they were involved in other activities. Sometimes they can escape the use of DHIS 2 too. So they do not need to open the computer and get into the DHIS 2.

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The DHIS2 is an additional task for the statisticians with other regular administrative duties e. They need to do extra hour work for that. National-level key personnel acknowledged the shortage of statisticians or other staff trained in data analysis. They admit that in many areas, qualified statisticians have not been recruited. Even so, many statisticians are not efficient in using computer software and do not understand health indicators and data compilation. In many areas, statisticians do not even attend trainings.

But, in many districts there is no designated statistician. Although the participants said the number of electronics provided for data collection is sufficient, slow Internet connectivity makes real-time data entry difficult. As one CHCP described,. In most cases, I enter the data at this time. It happened, I could not report for one week, two weeks, as the speed was slow. The provision of offline data entry could make the things little easier.

The process of sending broken tablets to capital city for repairs and transporting them back to the community took a long time. The majority of respondents reported internet modem shortages as well. In many areas, sub-district and district health managers personally obtain a modem and Wi-Fi router. Statisticians reported not receiving any specific training on DHIS 2; rather it was a part of computer literacy training. Participants received DHIS 2 training manuals, though these were not updated to reflect changes in newer versions of the software and forms.

Since DHIS 2 was introduced, all the line directorates want to incorporate their relevant indicators to be collected and analyzed through DHIS2 using same workforce. In some cases, the reporting format is also different than the one used by DHIS 2. Mandatory quality checks at different tiers and regular monthly feedback meetings have played a significant role in improving data quality. For example, when we check MMR [maternal mortality ratio], we locate where the ratio is high.

Then we review the ratio of that particular district for consecutive months to explore the consistency of data and reporting status, either it was low or high for the previous months. We check all these. Then we send an e-mail, to respective authority, to look into the matter.

A positive competition for service improvement has been nurtured. The best-performing district or division receives recognition from the national level. We always analyze the data, hence our performance is better!! They share financial costs with the government for national- and international-level training for the staff, IT equipment purchases, and other needs. In collaboration with other NGOs, like icddr,b, they are providing technical support to the IT programmer for online platform improvement and organizing a training on the DHIS 2 manual for staff working at different tiers of health system.

Donor organizations have demonstrated a strong commitment to the successful implementation of DHIS 2 by deploying their staff as monitoring officers at each administrative division and ensuring their physical presence and participation during monthly coordination meetings at the divisional and central levels.

The government has limited capacity and could not develop that capability till now. From the side of development partners, we are giving them that support. If development partners withdraw their support, how will the system run? But the DHIS 2 dashboard is already sustainable, and its automatic; staff have training and they can handle it. The government is cordial, and they have sufficient resources, training arrangement, hardware. In this context, strict monitoring and defined role of staffs are important.

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  8. In addition, ownership of data is a major concern, many health managers do not own the data. Section 4. A pop-up box with the indicator definition, calculation if applicable , and any possible disaggregation should be included. This will provide instant help to the CHCPs and standardize data collection. The software should be translated into Bangla the local language to help create a clear understanding of instructions and RMNCAH indicators.

    University of nairobi idis research papers

    An online dashboard should be installed in the platform where instant RMNCAH-related reporting and performance status updates should be exhibited automatically at the sub-district and district levels. Statisticians should be informed in advance about software updates and notified of specific changes so they can prepare the CHCPs. Data collection forms should be simplified to ease the data collection process and data reporting.

    Creating unique health identification numbers for patients and issuing individual health cards will decrease the time spent on data entry and help mitigate data duplication.