Location: Adamawa, Delta, Gombe, Jigawa, Kaduna, Kano, Katsina, Kwara, Ogun, Osun, Niger, Taraba, Yobe
Management Sciences for Health (MSH) is an international non-governmental organization working with countries and communities to save lives and improve the health of the world’s poorest and most vulnerable people by building strong, resilient, and sustainable health systems in 150 countries around the world. MSH partners with governments, civil society organizations, the private sector, and thousands of health workers to implement locally-led solutions that expand access to medicines and services, improve quality of care, help prevent and control epidemics, support inspiring leadership and transparent governance, and foster informed, empowered, and healthier communities.
MSH and MC in collaboration with CRS and NMEP as lead PRs in 13 malaria priority states supported by the Global. One of partners’ activities includes improved malaria commodity utilization and improved reporting from the health facilities, through effective and efficient HMIS and LMIS data triangulation, and the test positivity rates (TPR) reported from the routine health facility data through the NHMIS.
One of such activity involves improved malaria commodity utilization and improved reporting from the health facilities, through effective and efficient HMIS and LMIS data triangulation. Theoretically, HMIS and LMIS data should match; however, there are different reasons those numbers do not match. It has however become imperative to compare them, to see what the differences and the magnitude of these differences are, identify the root causes and to take specific actions that will help address the root causes and improve data quality. Comparing both data systems has been proposed by relevant stakeholders as a solution to many of these challenges. In addition, the test positivity rates (TPR) reported from the routine health facility data through the NHMIS have been persistently high ranging from 60% to 80% between Jan and Dec 2018 and was repeated on the February 2020. These persistently high TPRs, despite the numerous malaria interventions, raise questions regarding the true test positivity rate, hence the need to better understand health care workers’ practices in the management of fever cases at the health facilities.
MSH will be supporting this activity across 13 Global Fund supported states namely; Adamawa, Delta, Gombe, Jigawa, Niger, Kaduna, Kano, Kwara, Katsina, Ogun, Osun, Taraba and Yobe states. The exercise will be carried out to have a better understanding of the root causes behind the observed HMIS-LMIS data disparities and provide recommendations/interventions for addressing these root causes.
Position: Data Collector
Location: Adamawa, Delta, Gombe, Jigawa, Kaduna, Kano, Katsina, Kwara, Ogun, Osun, Niger, Taraba, Yobe, Objectives include:
- To compare HMIS and LMIS data from source documents and identify any disparities
- To identify the root causes of any identified disparities in both data sets
- To observe real-time the management of suspected malaria cases by frontline healthcare workers including testing, treatment, documentation practices and other factors
- To understand the root causes of the high-test positivity rates reported from facilities
- To work with the HFs, LGAs and states to proffer adequate solutions by mapping out an improvement plan to address the identified issues.
- To revisit the forecast and quantification and make necessary adjustments as relevant and appropriate.
- To consider impact on distribution plans and actions to be taken thereof
SCOPE OF WORK FOR DATA COLLECTOR
Management Sciences for Health / Global Fund Malaria Project
Period of Performance: [12th October 2020] – [30th November 2020] (5 working days only)
Level of Effort (LOE): 5 working days a week
Technical Supervisor: State Specialist Objective: To improve the level and quality of data documentation in all the supported sites and ensure accuracy and reliability of all reported data
A: Description of Services
Consultancy services and provision of technical assistance
B: Key Data Entry Clerk Skills
1. Basic computer appreciation Knowledge: Data Collector shall be well versed with basic MS word, spreadsheets, other record management and statistical software such as SPSS as added advantage
2. Good Written and Communication Skills: Due to the nature of the work involved Data Collector need to communicate extensively both within and outside teams. Therefore, data entry clerk needs to have excellent written and verbal communication skills. Communicating in local language would be an added advantage
3. Fast Typing Speed: Data Collector is expected to have excellent typing speed as s/he will have to perform huge amounts of data entry in a very short span of time. S/he need to be comfortable with all forms of data entry devices and be comfortable using a mouse, keyboard, scanners, etc.
4. High Levels of Concentration: Data entry & review activities are highly repetitive and s/he need to spend a lot of time on the same task. This activity therefore necessitates that the Data Collector have very high level of concentration and patience.
5. Data Entry accuracy: Should score high in data entry process and accuracy.
C: Working Hours
Data Collectors are expected to be available to support day entry for the period of five days a week, Monday to Thursday, between the hours of 8am to 5.30pm, Fridays 8am to 2.00pm (except on public holidays).
- Attend introductory meeting with key staff of the health facilities led by the LGA personnel
- Retrieval of documents needed for triangulation including OPD registers, Inventory Control Cards (ICC) and Bi-monthly Facility Stock Reports (BFSR). These documents will cover Jan/Feb, Mar/Apr and May/Jun 2020 reporting periods. Data extraction from these tools for this review period will include review of transactions records on the inventory control card (ICC) for completeness.
- Review of Bimonthly Facility Stock Report (BFSR) for Jan/Feb, Mar/Apr and May/Jun 2020 to verify the total malaria commodities utilized and reported within the period.
- The HMIS-LMIS Data Triangulation checklist will be used to document any discrepancies between the HMIS and LMIS values: the differences will be computed, described and discussed for each health facility.
- To the extent possible, the root causes for any identified differences between the HMIS and LMIS values computed during this exercise will be described and investigated.
- Action plans will be developed to address the identified root causes.
- The health facility staff will be debriefed on the key findings from the visit to provide feedback to the health facility, LGA and state teams.
- Analyze the submitted triangulation data with MSH team
- To develop a comprehensive technical report detailing the findings of the triangulation in conjunction with MSH and other partners
- Any other tasks that maybe required in relation to the activity
1. The Data Collector will be a post NYSC graduate with experience in data collection and entry.
2. S/he must be computer literate.
3. S/he must have the ability to use excel at the minimum.
1. Bachelor’s Degree, Biostatistician/Epidemiologist and/or equivalent relevant experience.
2. Excellent attitude and interpersonal skills.
3. Teachability: ability to learn and apply new skill
Interested person may send a comprehensive Resume and Application to email@example.com by COB Monday 9th October 2020 using the position title as the subject of the mail.