India Toolkit: Advocacy
Using Data to Effectively Manage the Family Planning Program
Purpose: To help district officials to monitor performance of Family Planning (FP) strategies as per Expected Level of Achievement (ELA), to analyze relevant indicators and to take timely corrective measures to meet the FP objectives of the district and the state.
- Chief Medical and Health Officers (CMHO/CDMO/CMO)
- Nodal Officer – Urban Health and FP
- District Program Managers (DPMs), District Health Officers(DHOs)
- Assistant Research Officers(AROs)
- Data Entry Operators
Background: The Ministry of Health and Family Welfare’s (MoHFW) routine Health Management Information System (HMIS) captures various data related to FP. In addition, the private sector reports FP data to the government via different mechanisms. However, there are issues in data management such as facilities not reporting on FP in the HMIS; reporting formats being filled incompletely; inconsistencies such as IUCD uptake being reported for facilities that have not had IUCD supply in the past months etc. In addition, this available data is not routinely consolidated, fully analyzed or presented in a manner that can help the district level officials, managers, hospital administrators or providers in understanding the current performance or in taking programmatic decisions on the basis of an understanding of the relationship between unmet need and the available resources for FP across both government and private sector facilities. Only when the data is analyzed and discussed in review meetings can it inform decisions for taking corrective measures and encouraging good performance.
The TCI tutorial below features a webinar held in May 2020 showcasing TCIHC’s data management solution.
Evidence of Effectiveness
The Urban Health Initiative (UHI) experience showed that the use of data for program management could be a powerful, low cost means to increase access and quality of services as well as provider’s motivation and accountability. FP performance improved when available data was analyzed routinely (presented through simple line graphs and bar charts) in CMHO meetings and was utilized to inform progress of FP strategies against ELA over the given period. By reviewing and discussing the monthly program achievements and the trends over time, health officials were able to identify specific problems requiring attention and were able to take corrective actions including reallocation of human and other resources to address those problems. Furthermore, the routine review of data in these meetings led to increased visibility, attention and priority given to the FP program in general.
Specific examples from UHI include the following:
- Based on an analysis of the HMIS data, CMHOs requested for funding to increase the number of obstetricians in government hospitals having high volume of deliveries
- No-Scalpel-Vasectomy(NSV) surgeons were more enthusiastic when CMOs monitored their performance and recognized their contributions
- When CMOs used available data to monitor the performance of community volunteers and rewarded their achievements in increasing coverage of households and the number of new family planning acceptors, their motivation increased and improved their performance over time
Guidance on Using Data to Manage Urban FP Programs
The key to effective data management for better program decision making includes:
- Determining the indicators that need to be captured, along with their source and frequency. For example, an indicator like the number of clients given different FP methods should be monitored on a monthly basis, while HR and capacity building indicators may require six-monthly monitoring
- Clearly defining indicators with the numerator and the denominator, wherever required
- Devising ELAs against which these indicators can be monitored
- Ensuring that the indicators are understood by all the staff
- Providing appropriate training to the staff including to the analysts responsible for data management
Important points on use of data
- Key FP indicators should be reviewed and discussed in monthly review meetings by the CMHO/CMO/CDMO and concerned authorities
- Line and bar graphs should be produced and displayed each month and at the end of the year in the district health office
- Feedback including bar charts and graphs showing comparative performance and performance over time should be provided to all facilities
- Feedback and supportive supervision using data should be provided to individual staff from their supervisors at each level
Using data for feedback: While it is important for the district health teams, facility-in-charges, and ASHA supervisors to review the available data and reports, and take corrective actions on the basis of identified gaps and weaknesses; it is equally important to communicate the gaps to the team in a constructive manner so that it boosts morale and yet provides direction for course correction. A simple way of doing this is to ‘Appreciate and Acknowledge each person right in the beginning, followed by suggested improvement (including offering any support / peer coaching that the person may require) instead of direct blaming, public shaming as it actually demotivates people.
Training staff in data usage: All the staff handling data should be informed and oriented on all the data forms, the definitions of key indicators and basic analysis of the data and indicators. Annual training / refresher training on data management should be considered and funds are available through the PIP. Master trainers can be identified at the city level. Support can be taken from NGOs to support this task.
Roles and Responsibilities towards Data Usage for Program Management
|ARO/DPM/Urban Health Coordinator||
|Chief Medical Superintendent (CMS)/Nodal Officer Urban Health and FP||
Monitoring the Usage of FP Data for Program Management
Monitoring of data usage for program management should be based on the following indicators:
The following indicators should be reported and reviewed on a monthly and annual basis:
- Percentage of facilities / service delivery points (public and private) reporting in the HMIS
- Percentage of facilities / service delivery points (public and private) reporting on FP indicators in the HMIS
- Number and percentage of FP acceptors, by method, by facility (public and private)
- Method-specific percentages of all FP acceptors by facility
- Number of Fixed Day Static (FDS) service days, by facility
- Number of clients served per FDS
- Number of new FP acceptors mobilized by ASHA
- Number of clients served per FDS
- Number and percentage of Post-Partum Family Planning (PPFP) acceptors, by method
- Number and percentage of Post-Abortion Family Planning (PAFP) acceptors, by method, by facility
- For 3-9 indicator, Monthly Facility / Service Delivery Point Report
- Percentage of staff positions filled against those planned to be filled (Reported and Reviewed Quarterly):
- Doctors trained on NSV/ mini-lap, facility wise
- U-PHC – Medical Officers In-Charge (MOIC), Staff Nurses, ANMs, FP Counsellors, ASHAs
Source: Monthly Facility Report
- Number of trained staff by facility (Reported and Reviewed Periodically)
- Number of NSV surgeons trained
- Number of staff nurses/ ANMs trained in PP-IUCD
- Number of doctors trained in Minilap/Laproscopic female sterilization
- Number of ASHAs trained on FP
Source: Training database updated periodically
- Percentage of funds utilized against funds budgeted by facility (Reported and Reviewed Monthly and Annually)
Source: District monthly fiscal report
Number of accredited facilities with various government schemes
- In UP: Hausala Sajhedari Dashboard
- Other states: Monthly Report, Department of Health
Commodities and Equipment
- Contraceptive stock outs by method, by month and by facility (reported and reviewed monthly and annually)
- Equipment available and functional against planned
- Kelly’s forceps
- IUCD kit
- NSV kit
- Mini lap kit
Source: Monthly Facility Indenting Format
The following elements are required for an effective data usage and management system. Their PIP codes are provided below for easy reference. A state may already have these elements, but if not, then they should be budgeted for in the PIP:
|Cost Elements||FMR Code||Source|
|HR Personnel Cost||P.2.1.1, P.3.2.1 and P.4.1||ROP UP 2017-18, NHM-UP|
Monitoring – NUHM monitoring/Evaluation – IT
|P.4.1.10||ROP UP 2017-18, NHM-UP|
|Computer, printer and UPS – NUHM at city||P.22.214.171.124||ROP UP 2017-18, NHM-UP|
|NUHM Office expenses at city level||P.2.2.3||ROP UP 2017-18, NHM-UP|
|Internet – NUHM Office expenses at city level||P.2.2.3||ROP UP 2017-18, NHM-UP|
This table is indicative and illustrates the manner in which cost elements are provisioned in a government PIP, thus giving guidance to the audience on where to look for elements related to a particular task, such as using data to effectively manage the FP program.
Routine HMIS provides the basic data and the staff who can conduct the data entry and basic analysis is already in place. If the available data is analyzed and made part of the routine review process where people can see the benefit of analyzing data and using that to make necessary corrections / adaptations, then the entire process of data collection, analysis and feedback will continue and be sustained.
Disclaimer: This document is based on the learnings collated from Urban Health Initiative, Health of the Urban Poor (supported by USAID) and Expanded Access and Quality (EAQ) to broaden method choice in Uttar Pradesh. This document is not prescriptive in nature but provides overall guidance of how this particular aspect was dealt with in these projects for possible adoption and adaptation.
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Effective data management for better program decision making includes:CorrectIncorrect
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