Category Archives: Data for Decision Making Series

Data for Decision Making: HIFA Online Discussion

Though an interview series in summer 2015, Data for Decision Making, the One Million Community Health Workers (1mCHW) Campaign and mPowering Frontline Health Workers (mPowering) have brought together experts to discuss the critical need for data on the number, availability, and locations of frontline health workers, particularly community health workers (CHWs). In the series, we brainstormed how creative solutions and collaborations can address the frontline health worker data gap. The original interviews can be found here on our blog.

The driver for this series was  a 2014 report, A Commitment to Community Health Workers: Improving data for decision-making, which stated, “The… lack of human resources information systems data on CHWs cause significant challenges in making data-driven decisions about how to best involve CHWs in national health systems.”

To expand upon this report and conversations on our blog, the 1mCHW Campaign and mPowering have come together with Health Information for All (HIFA 2015) to host an online discussion during September. The goal of this discussion is to hear from frontline health workers and other health professionals about how we can create  innovative solutions to address the CHW data gap. And to address this issue meaningfully – not to create data for the sake of data. This discussion will build on the conversation started in the interviews, using responses from the initial interviewees to stimulate conversation.

The discussion will take place for 4 weeks this  September on the HIFA 2015 e-mail forum, beginning Tuesday, September 1st. We will use this discussion, and the interviews, to inform a short report on ways to improve and expand the data available on CHWs.

An overview of the series can be found on HIFA 2015’s website. Each week, for the month of September, two questions will be emailed to the forum and responses will be posted to the HIFA’s Daily Post Digest.

How to join the conversation:

  1. Sign up for HIFA’s email forum here: http://www.hifa2015.org/joinhifa/
  2. Review the previous questions and interviews on our blog
  3. At the end of the day on September 1st , check your email for the discussion questions from HIFA
  4. Submit your responses via email and refer to the forum link for updated responses

We can’t wait to hear your thoughts!

Data for Decision Making: Interview with Bill Brieger

Bill BThis week marks our final installment in the Data for Decision Making series with the One Million Community Health Workers Campaign. For our final interview we talked with Dr. William (Bill) Brieger, Senior Malaria Specialist at Jhpiego and a Professor in the Health Systems Program of the International Health Department at Johns Hopkins Bloomberg School of Public Health. For over two decades Dr. Brieger taught at the African Regional Health Education Center at the University of Ibadan, Nigeria. He also previously served as a public health and health education consultant to various international organizations including the World Bank, the African Program for Onchocerciasis Control, UNICEF, the World Health Organization, US Peace Corps, and various USAID implementing partners. Dr. Brieger is internationally known for his expertise in social and behavioral aspects of disease control and prevention.

What are the most pressing challenges in the development of scaled-up CHW programs today?

I think part of the challenge is that it is difficult to obtain a clear commitment and approach regarding the implementation of CHW programs. A good contrast is seen in the difference between integrated community case management (iCCM) and community directed intervention (CDI).  With iCCM, organizations focus on getting treatments to people, whereas with CDI, organizations are interested in building up capacity within communities to support distribution of key health services. Philosophically, iCCM and CDI programs are two different approaches, with CDI aiming to help communities make a conscious decision about participating in the process and making a commitment to support any volunteers within the community.

The other challenge is that NGOs provide different programs and interventions, which is difficult for countries  – mainly Ministries of Health – to manage. I think Rwanda has been the most successful with harmonization and represents a good example of overcoming NGO program fragmentation. Rwanda has systematized the implementation of NGO programs, by requiring NGOs to go through the Ministry of Health to ensure that their programs adhere to the national standards.  Burkina Faso has also tried to tackle this problem, and the Ministry of Health has created a “Community Health Promotion Directorate” to assist in harmonizing service provision amongst NGOs. There are certain structural approaches to management that can help scale-up programs while maintaining community commitment; but CHW scale-up will not work unless the community is strongly involved in the selection of health volunteers and is holding those volunteers accountable to community norms and expectations.

Why is data on frontline health workers, particularly CHWs, important?

Data on CHWs and data from CHWs are equally important. Organizations need to know who is providing services in the community so they can plan for training and continuing education. Having a good record of community volunteers and keeping that record updated is important, especially at the health center level. Data collection starts with the health center keeping data on the villages where they operate – the geographical coverage, counts on the volunteers within that village, demographic information about the volunteers, and where they work.  Monthly records should be submitted by CHWs to ensure proper service delivery and patient tracking. If all of this is being done, then the data needed for making programmatic decisions can be sent forward to the district, state, or regional province.

In your opinion, what are the largest gaps in data on frontline health workers, particularly CHWs, right now?

I believe one of the largest gaps in CHW data is data showing whether CHW deployment mirrors community needs. For example, based on experiences in Rwanda and Nigeria, we know it is very important to have older female CHWs provide maternal health services, particularly woman who have been pregnant before. It is critical for an older woman to provide these services because she will be able to gain the trust of her community, which will allow pregnant women in the community to see the volunteer to discuss their pregnancy and receive treatment without any stigma. Situations like this demonstrate how important it is to keep track of the demographics of CHWs, along with the service needs of communities, especially services involving confidentiality like home-based care for HIV. With this information in hand, it can be quickly determined if an organization has CHWs with the appropriate characteristics to serve a community.

How can we begin to close these gaps?

Currently, most health centers do not keep a good record of community volunteers. This is where we can start to close the gaps in CHW data. If organizations and governments start streamlining data at the health center level, this data can then be reported to other levels of the health system. It is important to at least have an annual or semiannual assessment to determine changes, such as exits and promotions, within the CHW population. I have always envisioned it as a partnership between the health center and the community, so that the health center really knows the catchment area. For example, in most of the health centers and small clinics in Nigeria, the staff draws a hand-drawn map of their catchment area so that they know where their clients will come from. While imperfect, this allows the health center staff to have a good understanding of the community demographics. However, before this can happen it is critical that we start to actually keep track of community volunteers and health workers.

Community Health Worker Data Series: Kate Tulenko

Kate Tulenko

The lack of data on frontline health workers, particularly community health workers, constrains training, service delivery, and decision-making in global health. To understand better why this data is critical, and what can be done to improve it, mPowering Frontline Health workers and the One Million Health Workers Campaign are conducting a series of interviews to hear from the experts.

This week, we interviewed Dr. Kate Tulenko, Vice President, Health Systems Innovation for IntraHealth International and Director of CapacityPlus, USAID’s flagship health workforce project.  Dr. Tulenko previously coordinated the World Bank’s Africa Health Workforce Program and has served on expert panels for the World Health Organization, the Rockefeller Foundation, and the American Hospital Association, amongst others. Her latest book, Insourced, identifies the links between the US and global health worker shortage and offers affordable solutions.  Follow her on twitter at @ktulenko.

Why is data on frontline health workers, particularly CHWs, important? 

Better data on CHWs would help demonstrate their impact and cost-effectiveness, especially in medically underserved communities.  There are still many policy makers who are skeptical of the value of CHWs.  If we can demonstrate their value, we can get CHWs added as a formal member of the health team, with proper support supervision, a career ladder, and a salary.  Better data will also help policy makers see how fragmented CHW programs are geographically and thematically and will push them to integrate the disparate CHW programs into a unified program that addresses the largest causes of preventable mortality and morbidity in the country.

What are the most pressing challenges in the development of scale-up of CHW programs today?

The biggest challenges are resistance to the formalization and scaling up of CHW cadres by medical and nursing associations; and the perception by Ministries of Finance that health workers are an expense, rather than an investment with long-term benefits. Ministries of Health Human Resources for Health teams need improved capacity to manage their workforces.  Donor support for CHWs is still constrained by the continued pattern of investment in vertical programs- moving forward, donors and should provide systemic, focused, long-term investment in CHWS.

In your opinion, what type are the largest gaps in data on frontline health workers, particularly CHWs, right now?   

There’s so little data that one can’t speak about specific gaps.  It’s all a gap. 

In what ways is your organization using innovative solutions to collect data on frontline health workers? 

IntraHealth supports the free, open-source iHRIS software. iHRIS  is being used by 20  countries to track and manage more than 1.3 million health workers, many of whom are CHWs.  iHRIS stores data including: health worker cadre, posting site, gender, date of birth, and salary. iHRIS has been shown to save countries millions of dollars in proprietary software fees. Plus, iHRIS has saved countries millions of dollars by helping them remove ghost workers from the payroll and reinvest that money in real health workers.  Most importantly, iHRIS helps countries place their health workers more efficiently.

For example, in Jharkhand, the government was able to double the number of health facilities providing emergency obstetric care and increase care to a population of 900,000.  In Guatemala, iHRIS has reduced hiring times from three months to 3 weeks.  This is extremely important since many health workers emigrate or drop out of the job market if hiring takes too long.   iHRIS has been made interoperable with DHIS2, a popular open source district health information system, so that that staffing can be compared to service levels to determine health worker productivity. IntraHealth is also supporting countries to determine workloads and staff needs via Workload Indicators of Staffing Needs (WISN) analyses of existing health teams. In Namibia, IntraHealth has assisted the government to conduct WISN analysis in all government health facilities in the country (hospitals, health centers and clinics). The results have been used for budgeting of health workers for the last three years.

Together with UNICEF, IntraHealth has developed and deployed mHero, a system that enables regular, targeted SMS communication with health workers via SMS on standard mobile phones.  mHero was used in Liberia during the Ebola crisis to determine which health workers were reporting to work and which health facilities had sufficient protective equipment. mHero can be used by other countries to communicate with CHWs and other health workers in remote areas.

How can we begin to close those gaps?

The first step is to help Ministries of Health formalize CHWs. This means developing standard training curricula; creating regulations to guide CHWs in their work; establishing professional associations for CHWs; defining career ladders to help CHWS stay motivated and advance professionally; and to gather and use data on CHWS. CapacityPlus created a brief on professionalizing under-recognized cadres that guides countries through this process.

Data for Decision Making Series: The Importance of CHW Data with Michael Bzdak

This week in our Data fMichael_Bzdak_2013_021-300x200or Decision Making Series, the One Million Community Health Workers Campaign interviewed Michael Bzdak, Ph.D., Executive Director of Corporate Contributions at Johnson & Johnson. Dr. Bzdak is responsible for driving the company’s strategy around strengthening the health care workforce, manages its volunteer support program, and oversees philanthropic support of K-12 education. He serves on the New Jersey Governor’s Advisory Council for volunteerism and community service and on the advisory board for the One Million Community Health Workers Campaign. Dr. Bzdak is also a visiting part-time lecturer in the School of Communications and Information Studies at Rutgers University and an adjunct faculty member at New York University. This post originally appeared on the One Million Community Health Workers blog here.

What are the most pressing challenges in the development of scale-up of CHW programs today?

While there are many projects in existence today, the evidence base on “what works” is not always being used to scale-up the most effective programs. Additionally, we are missing critical information on the existing health workforce. I am concerned with the WHO Global Health Observatory report that 53 of 186 countries have fewer than 7 annual data points on midwives, nurses and physicians across the past 20 years – let alone information on CHWs. When you look at data reporting on overall health workforce, you see an overall lack of standard definitions and of registry. There is also no real standardization of training across the board for CHWs, nor is there any validation or accreditation on what it means to be a CHW. This information is so important when it comes to understanding country health workforce needs and filling the gaps. We have the ability to remedy some of these challenges if we use all of the intelligence available to us, such as information on labor economics and other disciplines, to inform the appropriate scale-up of CHW programs. I also contend that the private sector has a great deal to contribute to this dialogue.

Why is data on frontline health workers, particularly CHWs, important?

The data on frontline health workers is essential as it gives us a view to where they are working and how effectively their skills and services are utilized within the community and health systems. Overall we do not have enough data, so we have to better understand who does have access to data and how it is being utilized. Programs like the Operations Room, for example, are critical as they provide everyone a democratic view of the current situation involving CHWs. I am also encouraged by the recent Health Measurement and Accountability Post 2015: Five Point Call to Action put forward by the World Bank, USAID, and WHO, which commits to a strategic approach to strengthening country health information systems.

In your opinion, what type are the largest gaps in data on frontline health workers, particularly CHWs, right now?

One of the most important gaps today is the lack of raw numbers of CHWs. Another issue is that the data that we have does not provide an accurate view, for most countries, as to the pipeline of frontline health workers. While we do have this information on traditional doctors for many countries, including what factors affect their retention currently, it is not mapped out where CHWs are on this chain. For example, in Kenya we know that, because of attrition and migration, we have to train three doctors to get one practicing doctor. However, we do not have this information for other cadres of health workers. By knowing this information, we can strengthen training and development plans to improve retention, and more effectively utilize and direct resources.

In what ways is your organization using innovative solutions to collect data on frontline health workers?

At Johnson & Johnson, in addition to our role as a funder, we view our role as being a convener. We work to bring together various organizations doing great work separately to spark new collaborations that can bring forward further innovations to use data to strengthen health systems.

One of the projects that Johnson & Johnson is working on involves bringing together education workforce and health workforce organizations. For example, we facilitated a meeting between IntraHealth and FHI 360 to create an avenue in which the skills and data sources that FHI 360 was using in their analysis of education in Kenya could be applied to issues in the health workforce. IntraHealth’s nurse leadership program will also be enhanced with knowledge from the Touch Foundation’s work in Tanzania and by building capacity utilizing the experience of many partners.

Currently, we are at a juncture where global health funding is changing at the same time that we are seeing an increased focus on producing, sharing and using health data. Many countries that have been recipients of aid are graduating from low to middle-income status. Their local governments are now beginning to manage the various programs on the ground and determining for themselves how funds should be allocated. This means that the call for well-trained professionals and for tools to plan, implement, and monitor health delivery, is critical.

Data for Decision Making Series: Henry Perry

PerryThis week for our Data for Decision Making Series with the One Million Community Health Workers Campaign, Dr. Henry Perry talks to the Campaign about the challenges of CHW scale-up.

Dr. Perry is a Senior Scientist in the Health Systems Program of the Department of International Health at the Johns Hopkins Bloomberg School of Public Health. He is the author or co-author of more than 125 scientific articles and other publications, many of which focus on community-based approaches to improving maternal and child health. He has worked as a consultant with UNICEF, the US Agency for International Development, the Gates Foundation, and many others. Dr. Perry has a special interest in community health workers and their capacity to improve access to health services and improve the health of underserved populations.

What are the most pressing challenges in the development of scale-up of CHW programs today?

There are many challenges in the development of CHW programs scale-up. Providing adequate and logical support for medicines and supplies have always been pressing challenges for large-scale CHW programs. Some newer challenges that are being recognized include the need for strong monitoring and evaluation systems and for independent transparent evaluations to guide continual strengthening of large-scale CHW programs. Large-scale CHW programs are complex entities, and expansion or development of such  programs is a difficult endeavor that requires thorough and careful planning. Planning demands the involvement of multiple stakeholders from the national to the village level. Finally, the need to assure secure long-term funding for these programs is essential so that they don’t become undercut by short-falls in government budgets and other unstable sources of funding

Why is data on frontline health workers, particularly CHWs, important?

We need to have a better quantification of local need for frontline health workers, including CHWs, and the gaps that remain as the numbers of those health workers grow.  Additionally, we also need to better understand what the turnover rates are of frontline healthworkers who leave their positions, and why they are leaving their positions. These data are essential for program planning and program improvement. We also need more research on the cost-effectiveness of large-scale CHW programs­—studies that describe how well those programs are functioning and how they can be improved. These data are essential for continuing to make the case for the importance of CHWs as a fundamental component of the health system.

In your opinion, what are the largest gaps in data on frontline health workers, particularly CHWs, right now?

We need to strengthen our understanding of the current programs. Our knowledge base is not as strong as it should be. How do current CHW programs function? What are their strengths and weaknesses? What about cost? To ensure effectiveness in our future CHW programs, it’s necessary to begin with a clear understanding of current programs. Data is required for continuous improvement. To know what is actually happening requires adequate tracking and monitoring on a continual basis that is informed by evidence from the evaluation, from recommendations generated at the local level, and from evidence generated by the global health community.

How can we begin to close those gaps?

More funding for research on large-scale CHW programs and for independent evaluations of those large-scale CHW programs is essential to closing the gaps. Large-scale CHW programs themselves also need support and encouragement to help them strengthen their monitoring and evaluation programs, which is crucial to program strengthening.