impact of government regulations and programmatic ......3.6 dmpa-sc is available over the...

Impact of Government Regulations and Programmatic Decisions on Demand

for a Novel Contraceptive Product in Developing Countries

Matthew Westling

PharmD/MPA Candidate

March 29, 2020

rjeev

Typewriter

April 10, 2020

rjeev

Textbox

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Contents

Abstract 1

Summary 2

Background 4

Problem Identification 5

Literature Review 6

Research Design 11

Data Sources 13

Analysis and Findings 16

Conclusion and Recommendations 20

Bibliography 23

Appendix A 24

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Tables

Table 1: Indicator Groupings 12

Table 2: Example of Indicator Definitions 14

Table 3: Summary Statistics 16

Table 4: Factor Analysis Results 17

Panel (A): Eigenvalues and Accounted Variance

Panel (B): Factor Loadings

Panel (C): Scoring Coefficients

Table 5: Correlation Table 18

Table 6: Index Robust Linear Regression Results 19

Table 7: Indicator Collection Robust Linear Regression Results 20

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Abstract

Family planning and contraceptive use is becoming an area of emphasis for developing

countries. The important role family planning has in the growth and development of personal

wealth and the larger economy is already well understood. However, there is little information

about how planning, policy, and programmatic decisions influence contraceptive consumption.

Accordingly, this paper established an index which explores the weight program planning,

contraceptive delivery, and national policies have on contraceptive consumption. The index was

established through a factor analysis which utilized monthly indicators from the dissemination of

a novel contraceptive product called Sayana Press® in twelve developing countries. Results

showed, an index which weighed program planning and logistical indicators heavier than

indicators evaluating contraceptive delivery or national policies was associated with an increase

in contraceptive consumption. The results of this paper emphasize the importance factors

surrounding program planning and logistics have on the consumption of a novel contraceptive

product in developing countries.

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Summary

Family planning and contraceptive use has become a valuable resource for increasing the

economic prospects of families and governments in developing countries. However, there is still

a large unmet need for family planning services. Accordingly, country governments, non-

government organizations, and manufacturers have come together to commit resources toward

increasing family planning services. Unfortunately, when introducing contraceptive products in

these developing countries, there is little literature to help guide the complex decision-making

process often involved. Specifically, the literature does not quantify the impact programmatic or

regulatory decisions have on the uptake or consumption of contraceptive products. Given

stakeholders are looking to maximize the impact of their decisions on contraceptive use, there is

a need for more evidence to help guide this process.

This analysis utilizes information from the distribution of a novel subcutaneous

contraceptive product, medroxyprogesterone acetate (DMPA-SC) or Sayana Press®, in twelve

developing countries. The NGO collaborative assisting in the distribution of DMPA-SC to

foreign governments collects monthly indicators representing a variety of possible decisions and

check points completed by governments in charge of country-wide dissemination. A full list of

indicators included in the analysis can be found in Appendix A. Utilizing these indicators with

the country level consumption of the product provides a unique opportunity to assess the impact

of these decisions on contraceptive use. The aim of this paper is to provide support for decision

making and assess the influence decisions can have on the consumption of a novel contraceptive

product.

Indicator collection started in 2018. All indicators available to the researcher were

assigned an equally distributed score ranging from zero to one depending on the status of a

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selected indicator. Scoring information for each indicator can be found in Appendix A.

Indicators were then grouped together according to three broad areas: planning and logistics,

contraceptive access and delivery, and national policies and guidelines. Indicators included in

each area can be found in Table 1. These indicators were then summated into a score which

represented one of the three larger groupings. Given high covariance between all the indicators

involved, a factor analysis was utilized to develop the following predictive index:

𝑆𝑐𝑜𝑟𝑒𝐼𝑛𝑑𝑒𝑥 = 0.463 ∗ 𝑆𝑐𝑜𝑟𝑒𝑃𝑙𝑎𝑛𝑛𝑖𝑛𝑔 + 0.217 ∗ 𝑆𝑐𝑜𝑟𝑒𝐴𝑐𝑐𝑒𝑠 + 0.326 ∗ 𝑆𝑐𝑜𝑟𝑒𝑃𝑜𝑙𝑖𝑐𝑦

This index assesses the impact of indicator changes in one general area with overall

program function. The results of the factor analysis and associated index implies program

planning and logistics have a greater impact on program function than contraceptive access or

national policies and guidelines. The index was then utilized to assess if these assumptions were

associated with a significant change in consumption of DMPA-SC. To do this, a robust linear

regression was run. The regression analyzed the influence of the index on DMPA-SC

consumption and controlled for time and country. Almost all variables within the regression were

statistically significant utilizing a p-value less than 0.05. However, the index accounted for a

larger change in DMPA-SC consumption than normal time trends. Additionally, the regression

confirmed each country had a unique influence on consumption as expected given the inability to

control for extraneous variables. Results of this regression can be found in Table 6. Another

regression assessing the influence of a binary dummy variable representing indicator collection

found similar results.

This index creation and subsequent analysis implies program planning and logistics carry

a greater impact on contraceptive consumption than access or national policies and guidelines.

Although this may seem intuitive, stakeholders often pressure NGOs to quickly introduce a

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product into a country through tight contract timelines and arbitrary assessments. This may result

in delaying difficult planning and logistical decisions which could have a larger impact on

program function and subsequently, contraceptive consumption. Looking forward, more

controlled confirmatory analyses are necessary to validate this index as well as the associated

changes seen in consumption.

Background

Family planning and contraceptive access has been pushed as a major global health issue

in developing countries. The World Health Organization (WHO) identifies the benefits of family

planning as well as the serious unmet need of family planning options in many developing

countries.1 Additionally, over the past 20 years reproductive health has gained support from

many governments as they seek to improve citizen health outcomes and their country’s economic

development. In fact, many developed countries’ foreign aid programs, such as United States

Agency for International Development (USAID), have taken a large interest in developing

countries family planning programs as a means of furthering development.

Accordingly, these countries as well as non-government organizations (NGOs) and

interested philanthropic organizations, such as the Bill and Melinda Gates Foundation, came

together at the July 2012 London Summit on Family Planning and established the Family

Planning 2020 (FP2020) development partnership.2 This partnership “works with governments,

civil society, multilateral organizations, donors, private sector individuals, and research and

development in order to enable 120 million more women and girls to use contraceptives by

1 World Health Organization. “Family planning/Contraception”, 2018, February 8. Accessed June 27, 2019.

https://www.who.int/news-room/fact-sheets/detail/family-planning-contraception 2 Family Planning 2020. “About Us | Family Planning 2020”. Accessed June 27, 2019.

https://www.familyplanning2020.org/about-us

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2020.”2 Currently, 41 governments have committed to addressing the policy, financing, delivery,

and sociocultural barriers to women trying to access contraceptive information, services, and

supplies.2 Partnerships such as FP2020 have helped push the development of infrastructure for

family planning programs in foreign countries with the use of multiple resources from a large

base of stakeholders and investors.

Problem Identification

With developing family planning infrastructure, stakeholders are looking for ways to

closely monitor the impact of provided resources, program actions, and policy interventions.

Collaborative partnerships between NGOs and governments have given stakeholders the ability

to measure the impact of their resources and closely monitor the needs of existing supply chains.

Although these measurements are useful when forecasting contraceptive requirements within

established supply chains, there is little information to guide the introduction of new

contraceptive methods or modifications to existing delivery pathways. Particularly, governments

and NGOs know very little about the demand anticipated from new potential contraceptive users.

Yet, information shows when countries introduce a new method of contraception, overall

modern contraceptive prevalence rate (mCPR) increases significantly within the country.3

However, stakeholders struggle to predict the rate of contraceptive uptake and are uninformed

about what actions can be taken to improve uptake within potential users. Although current

research does attempt to attribute contraceptive use changes with specific program strategies,

donor decisions, or government policies, these claims are entirely anecdotal and often provide no

quantitative measurement of their impact. With this is mind, investors may be allotting time or

3 J. Ross and J. Stover, "Use of modern contraception increases when more methods become available: analysis of

evidence from 1982-2009," Glob Health Sci Pract 1, no. 2 (Aug 2013), https://doi.org/10.9745/GHSP-D-13-00010,

https://www.ncbi.nlm.nih.gov/pubmed/25276533.

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scarce resources towards changes/decisions that do not significantly impact contraceptive

consumption. Likewise, stakeholders are looking for more specific answers about how to create

fruitful environments when introducing contraceptive products or modifying current delivery

systems.

The aim of this research is to quantify the impact of certain programmatic and regulatory

decisions on the consumption for a novel contraceptive product called Sayana Press. Sayana

Press is a subcutaneous form of the medication medroxyprogesterone acetate (DMPA-SC)

similar to the more commonly known intramuscular injection: Depo-Provera (DMPA-IM). I

hope this research will shed light on the quantifiable impact specific regulatory decisions have on

contraceptive demand. Additionally, this research may help focus future decision making by key

stakeholders as well as highlight areas for new or improved data collection. However, given I am

looking at one specific contraceptive product, these findings may not be applicable to other

contraceptive methods. Furthermore, family planning is often cultural and religious in nature and

these influences may play a larger role than anticipated in contraceptive success.

Literature Review

Questions surrounding what makes contraceptive products successful has been an area of

interest for drug companies, healthcare providers, and governments around the world. However,

most research focuses on physical and medicinal qualities of contraceptive products rather than

education, policy, and program evaluations. Although some research about product launch and

program success in foreign countries exists to help guide relevant stakeholders, there is still a

significant need for the evaluation of policy impact. In this section, I will review relevant

literature pertaining to contraceptive program and policy evaluation in developing countries.

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Many contraceptive methods introduced in foreign countries have had a notoriously slow

uptake. However, when looking for a global contraceptive success story, one might turn to long

acting reversible contraceptives (LARCs) and more specifically contraceptive implants.

Implantable methods had extremely low uptake among women of reproductive age in sub-

Saharan Africa upon introduction, comprising of 2-6% of modern contraceptive methods used by

married women.4 Additionally, the contraceptive prevalence rate (CPR) of implants, defined as

the percent of women of reproductive age using a specified contraceptive method, ranged from

0.6-1.7% upon introduction.4 Soon after this slow start, their use began to dramatically rise,

eventually averaging around 20% of modern contraceptive methods and reaching a CPR of 7-

18% across 12 African countries.4

Jacobstein summarizes the increased use among unmarried women and women with

children, finishing with reasons for the product’s unconventional success. In this, he addresses

the characteristics of implants, international consensus on family planning, greater country

commitments, reductions in cost, and high impact delivery practices as some of the reasons for

success.4 Although there was an increase in implant use, there is no data to quantify or validate

the impact of these individual changes on implant use within countries. Furthermore, there is a

lack of explanation about why some countries performed better than others and why other

products which received similar benefits did not see a similar increase.4

A presentation from the Bill and Melinda Gates Foundation summarized five barriers to

product delivery: Failure to develop and adapt interventions to target populations and plan for

launch, lengthy opaque policy and regulatory processes at global and local levels, limited

funding available at the local and global level, underperforming delivery platforms, and lack of

4 R. Jacobstein, "Liftoff: The Blossoming of Contraceptive Implant Use in Africa," Glob Health Sci Pract 6, no. 1

(Mar 21 2018), https://doi.org/10.9745/GHSP-D-17-00396, https://www.ncbi.nlm.nih.gov/pubmed/29559495.

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champions and leadership.5 Although Jacobstein’s explanations fall into these broad categories,

it is still unclear the impact overcoming these barriers can have.4 Notably, the Gates Foundation

did attempt to look at the impact of removing these barriers, but the presentation contained

mostly case studies and no rigorous statistical analysis of true impact.

Considering this, stakeholders need the ability to measure the impact of program

decisions in order to help optimize resources. However, studies that utilize changing mCPR

without rigorous statistical analysis are insufficient because the introduction of new

contraceptive methods can increase contraceptive use overall.3 Ross & Stover looked at

countries that had one or more modern contraceptive methods available, the extent of access to

which they were available (20-80%), and mCPR from 1982 through 2009. The research found

that there was an approximate 5-10% increase in mCPR for every new method introduced and

that mCPR increased as availability increased.3 This information indicates the need to correlate

changes of CPR in one product more closely with the decisions based around that product and

program independent of other external contraceptive products and decisions.

Differences in differences is one of the best tools analysts use to isolate the impact of

policy or programs separate from other confounding variables. However, there are relatively few

done in the area of family planning evaluation. Additionally, these studies are usually

prospective as data reporting from developing countries can be incomplete or inconsistent. In one

study evaluating the impact of a contraceptive voucher program on LARC use in Cambodia,

researchers took surveys of households, medical facilities, interviewed clients of providers, and

observed client-provider interactions.6 The researchers then matched regional areas using a

5 Bill and Melinda Gates Foundation, BMGF Delivery Scoping (2008), Powerpoint. 6 A. Bajracharya et al., "Increasing Uptake of Long-Acting Reversible Contraceptives in Cambodia Through a

Voucher Program: Evidence From a Difference-in-Differences Analysis," Glob Health Sci Pract 4 Suppl 2 (Aug 11

2016), https://doi.org/10.9745/GHSP-D-16-00083, https://www.ncbi.nlm.nih.gov/pubmed/27540118.

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propensity score accounting for multiple variables of facility characteristics such as ownership,

size, level of care, and characteristics of population in facility service areas.6

Researchers found women who were “exposed” to the voucher program (lived near a

hospital that serviced the voucher program) had a significantly higher use of LARCs than those

in the control group when controlling for confounding factors.6 Contrarily, in a different analysis

of a large-scale program aimed to increase LARC use in Bangladesh researchers tried to identify

reasons for poor performance.7 This program was implemented in 21 districts with significantly

poor family planning indicators and utilized a SEED (supply, enabling environment, demand)

model for designing the program. Here the researchers did not use a propensity score to match

intervention and control districts based off certain characteristics.7 Instead, researchers choose

districts that were on the border of intervention districts in hopes of controlling for cultural and

religious differences that might exist elsewhere in the country.7

Researchers found an overall increase in LARC use in program and non-program districts

but the increase in non-program districts was significantly smaller.7 However, according to the

multivariate analysis the program did not significantly increase the probability of married women

of reproductive age choosing LARCs as a preferred contraceptive method.7 Additionally, surveys

found that higher coverage of provider trainings in program districts did not translate into better

knowledge or practice and even though public information was more available in program

districts people were more likely to report learning more from non-program districts.7 This

analysis exposes the difficulties of trying to evaluate the failures of comprehensive programs that

7 M. Rahman et al., "The Mayer Hashi Large-Scale Program to Increase Use of Long-Acting Reversible

Contraceptives and Permanent Methods in Bangladesh: Explaining the Disappointing Results. An Outcome and

Process Evaluation," Glob Health Sci Pract 4 Suppl 2 (Aug 11 2016), https://doi.org/10.9745/GHSP-D-15-00313,


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have multiple aspects and emphasizes the need for isolating factors in order to determine

programmatic shortcomings.

Although these difference in differences look at program effects, there is almost no

similar style of evidence when looking at contraceptive product introduction. However, there is

some emerging literature about pilot programs of DMPA-SC within African countries. Stout et

al. looked at different programmatic structures for DMPA-SC pilot programs in four African

countries and collected data to look at consumption patterns over a two-year period.8 Researchers

found that 44% of DMPA-SC doses administered were to young women less than 25 years old,

29% of doses administered were to new contraceptive users, varying amount of doses

administered were to women switching from intramuscular DMPA (DMPA-IM), and that

DMPA-SC held a large market portion of injectable contraceptives at the community level.8

Although this information is useful in learning about demographics of DMPA-SC users, it does

little to evaluate the programmatic impacts on DMPA-SC consumption and associated success.

Moreover, DMPA-SC has a unique characteristic of being the first long acting product

that can safely be self-administered when users learn how to inject the medication. In fact,

research found that women who self-inject DMPA-SC are likely to use the product for a longer

period compared to those who have a provider inject the medication.9 As countries distribute

DMPA-SC, evaluating isolated policy impacts of self-injection would be more feasible since the

product is relatively new. In fact, since DMPA-SC is relatively new it would be a good candidate

8 A. Stout et al., "Expanding Access to Injectable Contraception: Results From Pilot Introduction of Subcutaneous

Depot Medroxyprogesterone Acetate (DMPA-SC) in 4 African Countries," Glob Health Sci Pract 6, no. 1 (Mar 21

2018), https://doi.org/10.9745/GHSP-D-17-00250, https://www.ncbi.nlm.nih.gov/pubmed/29602866. 9 H. M. Burke et al., "Effect of self-administration versus provider-administered injection of subcutaneous depot

medroxyprogesterone acetate on continuation rates in Malawi: a randomised controlled trial," Lancet Glob Health 6,

no. 5 (May 2018), https://doi.org/10.1016/S2214-109X(18)30061-5,


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for evaluating isolated policy choices given sub-Saharan countries are at different points in their

implementation of DMPA-SC.

Overall, the research surrounding family planning program choices and policy decisions

is inadequate for helping stakeholders make decisions and focus resources for efficient use.

Additionally, there is a clear need to evaluate the impact that specific decisions can have on

program operations and success. While there is research on specific government programs for

family planning, even these studies lack the evaluation needed to help focus future decision-

making.

Research Design

For my research design, I utilized factor analysis to construct an index that helped to

identify the impact of three broad factors related to demand for DMPA-SC in developing African

countries. The factor analysis utilized specific monthly indicators from twelve African countries

collected by an NGO sponsored initiative called the DMPA-SC Access Collaborative. These

indicators, listed in Appendix A, measure a range of country plans, program checkpoints, and

specific policy/regulatory decisions. Out of the 79 indicators recorded, 45 indicators were used in

the analysis. These indicators were then grouped to represent three larger factors:

planning/logistics, contraceptive access and delivery, and national policies/guidelines (Table 1,

next page).

Indicators were assigned a score ranging from zero to one. Weights were distributed

evenly over each response to the indicator. For example, there are four possible entries to record

stock status: stock out, under stocked, stocked according to plan, and over stocked. Since weights

are distributed equally the scoring would be as follows: stock out = 0, under stocked = 0.33,

stocked according to plan = 0.66, over stocked = 1. Indicator responses, definitions, and weights

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can be found in Appendix A. Ideally, information could have been collected from experts to

better understand the weight each individual indicator on the larger unmeasurable factor at play

and a Delphi weighting system applied. However, this was not possible with given resources.

Table 1: Indicator Groupings Group 1: Planning and

Logistics

1.4 DMPA-SC integrated into national logistics management information system

2.1 Costed introduction/scale-up plan for DMPA-SC developed

2.2 Costed introduction/scale-up plan for DMPA-SC includes self-injection

2.3 Percent of DMPA-SC costed plan funded

2.4 Service delivery channels reflected in the DMPA-SC introduction/scale-up plan

3.1 Registration status for DMPA-SC

4.3 DMPA-SC integration into the national health management information system

Stock status

Group 2: Contraceptive

Access and Delivery

2.5 Service delivery channels active in DMPA-SC provisions

2.7 Introduction model for DMPA-SC

2.8 Introduction status for DMPA-SC

3.6 DMPA-SC is available over the counter/non-prescription

4.6 number and percent of DMPA-SC service delivery points active

7.1 Introduction status for self-injection of DMPA-SC

Stock status

Group 3: National

Policies and Guidelines

2.9 DMPA-SC is included in national information, education and communication

(IEC) materials for family planning

3.2 Status of policy allowing community health workers to administer

3.3 Status of policy allowing pharmacists to administer

3.4 DMPA-SC is included on the essential medicines list

3.5 DMPA-SC is included in the national FP policy/strategy

4.1 FP training guidelines and curricula include DMPA-SC

7.2 Regulatory approval exists for the self-injection label

7.3 Status of policy that authorizes self-injection of DMPA-SC

7.4 Family planning training guidelines and curricula include self-injection

The scores from these indicators were then summarized together according to the

respective groups in Table 1. The weight of these scores on the program function was evaluated

through a factor analysis. Additionally, when running a factor analysis for all 45 indicators, the

first factor, a weighted average of all the indicators, accounted for over 99% of the variance in

the model. This result made isolating the impact of specific indicators more difficult.

Accordingly, the groupings in Table 1 were made in attempt to isolate the weight of broad

planning, delivery, and policy decisions. A factor analysis was most applicable for developing an

index given the high rate of covariance among variables and that program function is hard to

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efficiently or effectively measure. Once the factor analysis confirmed these groupings were

weighted on the primary component factors of the analysis, the associated coefficients of the

index were formed utilizing factor coefficients.

In order to see if the associated weights from the index were associated with

contraceptive demand, a robust linear regression was run over 72 months utilizing absolute

consumption of DMPA-SC as the dependent variable. Ideally, this regression would have

controlled for population size, percent of population female, female enrollment rates within

primary education, contraceptive use, urban and rural poverty rates, and gross domestic product.

However, given that all countries involved are developing African countries, control data were

sparse and collected yearly as opposed to monthly or quarterly like the indicator and

consumption data. Furthermore, given DMPA-SC indicators were collected starting in 2018 and

consumption data were collected starting as far back as 2014 for some countries. All indicators

were assumed to be zero prior to 2018 in order to be more conservative. To identify the

associated impact of indicator collection on consumption, a binary dummy variable was created

based off the total sum of indicators to identify collection had started. Another robust regression

was then performed to evaluate the influence of this collection on DMPA-SC consumption.

Country specific coefficients were also included in the regression to validate the idea that

country specific factors do significantly influence contraceptive consumption rates.

Data Sources

DMPA-SC Indicators

The Access Collaborative Dashboard is a database established by a group of stakeholders

that collects specific program and regulatory indicators specifically relating to the dissemination

of DMPA-SC within developing countries. This data is collected through survey responses

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which are sent out to government officials and ministries of health responsible for immediate

oversight of the program. Currently, there are 46 different indicators, some of which can be

disaggregated into separate parts leading to a total of 79 possible recordings. Monthly indicators

began collection in January 2018, although the start of collection varies by country. These

indicators are intended to measure specific progress points in the dissemination of DMPA-SC

within a specific country. Every indicator is specifically defined by the organization and outlines

response definitions.

Table 2 shows an example of a specific indicator definition. A full list of indicators and

associated definitions can be found in Appendix A. As described earlier, these indicators were

coded for analysis by the researcher on a scale from zero to one with the weight of each indicator

being distributed evenly across all possible answer choices. If data was not collected in a specific

month between January 2018 and January 2020, data was assumed to be unchanged and based on

the prior months data entry. For example, if no policy authorizing pharmacists to administer

DMPA-SC existed in February 2019 but one existed in April 2019, it is assumed that policy did

not exist in March 2019. However, if the policy did exist in February 2019, it was assumed to

have existed in March 2019. Lastly, these coded variables were grouped together and

Table 2: Example of Indicator Definitions

Indicator 3.3: Status of policy that authorizes pharmacists or staff in an accredited drug shop to

administer contraceptive injectables to users Precise Definition(s): Policy refers to decisions, plans, and actions that are undertaken to achieve specific health

care goals. It does not specifically require to a change in law.

No Policy The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users does not currently exist and is not currently being

written.

In Process The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users is being written.

Enacted/Authorized The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users has been made legal or allowable.

Implemented Measures to put into practice the policy allowing pharmacists or staff in an accredited

drug shop to administer contraceptive injectables to users exist.

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summarized to generate new variables as described in Table 1. Notably, these indicators are

collected from governments, reporting bias may exist given governments are under pressure to

implement changes in order to receive funding.

Demand for DMPA-SC

In the confirmatory regression to assess if the index helps explain increased consumption

of DMPA-SC, the absolute country level consumption of DMPA-SC was utilized as the key

dependent variable in this research. The absolute consumption for DMPA-SC comes from an

NGO which controls the distribution of DMPA-SC into countries based off current stock

indicators and reporting from government bodies such as ministries of health. This data is most

ideal as it is collected and reassessed every three months, being the most time sensitive product

data available. Collecting actual consumer level consumption, although ideal in order to better

understand individual user responses to program or policy changes, proves difficult with

inconsistent infrastructure across differing countries.

This information may be collected every six months within a handful of countries, but the

collection of this data is not consistent in every country and the inclusion of DMPA-SC in these

measurements is not guaranteed. The collection of absolute consumption ranges from 13 months

to 72 months depending on the country. As stated, since this information is collected quarterly,

the amount consumed was distributed equally over three months to improve functionality with

the monthly reporting of indicator data.

The assumption underlying this data is the consumption of the product is equal to if not

greater than the amount given to the country. However, it is important to note that the amount of

DMPA-SC a country receives includes stock forecasting from the NGO controlling distribution

of the product. With this, it is important to remain cognizant that an introduction of bias can

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occur during the forecasting and distribution of the product to specific countries. Additionally, if

countries are trying to maximize the product received, then the ministries of health may falsely

report distribution or consumption rates. Lastly, given that this is sensitive international market

data, countries were anonymized in order to protect international trade, specific countries, and

NGOs providing it.

Analysis and Findings

Summary Statistics

Twelve countries were utilized in this study for a total of 561 unique observations across

72 months of data. Indicator scores for planning and logistics ranged from 0 to 13.22 with an

average of 4.13 out of 14 possible points. Scores for contraceptive access and delivery ranged

from 0 to 14.41 with an average of 3.36 out of 21 possible points. Scores for national policies

and guidelines ranged from 0 to 8.32 with an average of 2.77 out of 10 possible points. Absolute

consumption ranged from 0 to 234858 units per month depending on the country with an average

of 27164 units per month. There were 309 total observations where no indicators were collected

which were then coded utilizing a binary categorical dummy variable. Summary statistics can be

found in Table 3.

Table 3: Summary Statistics

Observations Mean Std. Deviation Min Max

DMPA-SC Consumption n=519 27163.96 36595.13 0 234858

Total Indicator Score n=561 15.19 18.72 0 62.40

Planning/Logistics Score n=561 4.13 5.06 0 13.22

Access/Distribution Score n=561 3.36 4.37 0 14.41

National Policy Score n=561 2.13 2.77 0 8.32

Factor Score n=561 0 .98 -.79 2.03

Index Score n=561 3.33 4.10 0 11.66

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Factor Analysis

The results of the factor analysis produced three total factors using the three summary

scores shown in Table 4 Panel A. The first factor had an eigenvalue of 2.76 indicating it

accounted for the variance of 2.76 out of 3 variables which ended up explaining over 100 percent

of the variance between the variables. The first factor resulted in three different factor loadings

and varying uniqueness for all variables as shown in Table 4 Panel B.

Given most of the variance between the variables was explained by the first factor, a

weighted average of all variables involved, the factor loadings were distributed almost equally

amongst factor one. Justification for utilizing a factor analysis was supported given the high

covariance of the original indicators, all of which received a Kaiser-Meyer-Olkin measure > 0.5,

the point at which using a factor analysis is justified.

Index Creation

If the original factor loadings were utilized as index coefficients for each grouping score

the final index would be very similar to a total sum of all the indices, shown by the high rate of

Table 4: Factor Analysis Results Panel (A): Eigenvalues and Accounted Variance

Factor Eigenvalue Difference Proportion Cumulative

Factor 1 2.757 2.781 1.022 1.022

Factor 2 -0.024 0.012 -0.009 1.013

Factor 3 -0.036 - -0.013 1.000

Panel (B): Factor Loadings

Variable Factor Loading

Planning/Logistics Score 0.972

Access/Delivery Score 0.942

National Policy Score 0.961

Panel (C): Scoring Coefficients

Variable Factor 1 Scoring Coefficient

Planning/Logistics Score 0.463

Access/Delivery Score 0.217

National Policy Score 0.326

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correlation between the factor and total sum of indicators in Table 5. Therefore, the scoring

coefficients from the linear regression used to predict the factor 1 variable (Table 4 Panel C)

were used in the construction of the following index:

𝑆𝑐𝑜𝑟𝑒𝐼𝑛𝑑𝑒𝑥 = 0.463 ∗ 𝑆𝑐𝑜𝑟𝑒𝑃𝑙𝑎𝑛𝑛𝑖𝑛𝑔 + 0.217 ∗ 𝑆𝑐𝑜𝑟𝑒𝐴𝑐𝑐𝑒𝑠 + 0.326 ∗ 𝑆𝑐𝑜𝑟𝑒𝑃𝑜𝑙𝑖𝑐𝑦

These coefficients were used given the desire to develop a predictive index and the regression

coefficients are utilized to predict factor 1, a variable similar to the weighted average of the total

score. Likewise, the index ideally reflects a value which is predictive of all choices made. The

underlying assumption of the index is all choices made increase consumption of the product, but

the coefficients of the index reflects the weight of the choices made in a specific area. For

example, a one-point increase in access resulting from a DMPA-SC delivery decision such as

allowing pharmacists to administer DMPA-SC will increase the average impact on all other

choices by 0.217 units.

Thinking about the coefficients in a realistic sense validates the index further. For

instance, one would expect increased planning to produce a greater impact of future decisions

compared to increased access which would likely increase demand but would have a smaller

impact on future planning or policy decision given these choices usually precede the distribution

of a product.

Table 5: Correlation Table

Index Factor 1 Score Total Indicator Score

Index 1.0000

Factor 1 Score 0.9994 1.0000

Total Indicator Score 0.9932 0.9938 1.0000

Confirmatory Regression

A robust linear regression was executed to better understand the ability of this index to

predict the consumption of DMPA-SC in different countries over 72 months. As stated earlier,

19

this regression was unable to control for baseline characteristics of countries given these are

collected yearly and not frequently updated in many developing African countries. However, the

model did control for country, time, and the index score. Results from the regression are found in

Table 6. A factor notation was used to compare countries involved to the first country listed. This

confirmed the notion that countries have unique factors influencing DMPA-SC consumption.

Almost all results in this regression were statistically significant utilizing a p-value

threshold of <0.05. This analysis shows that there was a significant increase in DMPA-SC

consumption over time and that most of the countries had a unique influence on DMPA-SC

consumption. However, the index created explains the increase in DMPA-SC consumption

beyond the time trend over 72 months.

A separate robust linear regression was run controlling for time, country, and the binary

dummy variable representing the collection of indicators (Table 7, next page). This regression

shows the dummy variable explained a significant amount of DMPA-SC consumption beyond

time trends. These results imply that indicators and more specifically, the decisions recorded by

Table 6: Index Robust Linear Regression Results

Coefficient Robust Std. Error P-value 95% Confidence Interval

Index Score 2054.603 452.5943 <0.05 (1165.403 - 2943.802)

Country

2 19827.15 2348.407 <0.05 (15213.3 – 24441)

3 2625.547 1866.32 0.160 (-1041.16 - 6292.254)

4 1919.686 2648.791 0.469 (-3284.321 - 7123.693)

5 68414.08 4339.394 <0.05 (59888.59 - 76939.57)

6 51069.13 4709.078 <0.05 (41817.34 - 60320.93)

7 11430.52 2540.041 <0.05 (6440.166 - 16420.87)

8 4696.77 3909.293 0.230 (-2983.71 - 12377.25)

9 12984.43 2432.597 <0.05 (8205.174 - 17763.69)

10 -13160.53 3356.467 <0.05 (-19754.89 - -6566.17)

11 52234.98 5805.279 <0.05 (40829.5 - 63640.45)

12 24680.75 10871.02 0.024 (3322.746 46038.75)

Time 570.345 80.463 <0.05 (412.2605 - 728.43)

Constant -28227.45 4183.374 <0.05 (-36446.41 - -20008.49)

20

the indicators, had a significant influence on DMPA-SC consumption. Although ideally these

linear regressions would control for more extraneous variables, the regressions confirmed the

index created as well as the collection of indicators is strongly associated with the consumption

of DMPA-SC.

Conclusion and Recommendations

Family planning continues to be pushed as a top priority to improve mortality, economic,

and health outcomes in developing countries. However, stakeholders are still uninformed on

what decisions lead to increased demand or consumption of contraceptive products. Utilizing

information from the distribution of the novel contraceptive product DMPA-SC in developing

countries, a weighted index representing a country’s DMPA-SC program was constructed to

predict the impact of broad decisions on that program. The program index contained three scores

which covered planning/logistics, contraceptive access and delivery, and national

policies/guidelines.

Table 7: Indicator Collection Robust Linear Regression Results

Coefficient Robust Std. Error P-value 95% Confidence Interval

Dummy Variable 17647.93 3098.643 <0.05 (11560.11 - 23735.75)

Country

2 20322.85 2546.16 <0.05 (15320.48 - 25325.22)

3 2394.48 2216.40 0.281 (-1960.008 - 6748.972)

4 1224.04 2916.16 0.675 (-4505.254 - 6953.333)

5 67431.26 4558.26 <0.05 (58475.76 - 76386.75)

6 46518.78 4753.08 <0.05 (37180.52 - 55857.03)

7 10324.82 2929.91 <0.05 (4568.513 - 16081.13)

8 6031.42 3417.97 0.078 (-683.7701 - 12746.6)

9 13213 2559.91 <0.05 (8183.613 - 18242.39)

10 -14424.01 3299.52 <0.05 (-20906.49 - -7941.534)

11 52695.67 6562.13 <0.05 (39803.23 - 65588.1)

12 21578.28 11248.42 0.056 (-521.1789 - 43677.75)

Time 524.29 95.15 <0.05 (337.3514 - 711.236)

Constant -26715.17 5016.92 <0.05 (-36571.78 - -16858.56)

21

The index explained a significant amount of DMPA-SC consumption beyond time trends

over 72 months, indicating the index is associated with a program’s ability to increase DMPA-

SC consumption. Index coefficients imply that planning/logistical decisions, and regulatory

policies/guidelines possess more impact on program operations than purely increasing the

distribution and access to contraceptives. Accordingly, country governments and NGOs may

have more effective product uptake and program success if given more time to plan and ensure

the stability of project execution. Looking back at the sudden success of LARCs shows a similar

result. Although there is no definitive data to support the claims, Jacobstein did note that the

sudden increase in LARC occurred around a time of improved planning, funding, and policies

surrounding LARCs throughout developing countries.4

However, NGOs are still pressured to quickly introduce new contraceptive products or

programs into developing countries using short-term contracts and arbitrary evaluations usually

based of quantity of product distributed. Given planning, logistics, and regulatory changes often

take a while to implement on a country wide level, it would be reasonable to suggest that

government aid contracts and stakeholder standards start to shift their evaluation methods or

definition of program success. Moving forward more rigorous data collection and controlled

detailed analysis is necessary to validate the created index and associated increase in

consumption. Additionally, improved and more frequent data collection at both the country and

consumer level would help identify the impact of specific decision making on individual user

response compared to the country wide responses observed in this paper.

\In the end, although it might seem intuitive that increased planning and improved

policies or guidelines have a larger impact on consumption than contraceptive delivery and

access, there was no significant data to guide this inference. Utilizing regularly collected

22

indicators to establish a program index, where the weights of these group scores were based off

existing program data, allowed the confirmation of these suspicions through basic statistical

methods.

23

Reference List

Bajracharya, A., L. Veasnakiry, T. Rathavy, and B. Bellows. "Increasing Uptake of Long-Acting

Reversible Contraceptives in Cambodia through a Voucher Program: Evidence from a

Difference-in-Differences Analysis." Glob Health Sci Pract 4 Suppl 2 (Aug 11 2016):

S109-21. https://doi.org/10.9745/GHSP-D-16-00083.


Burke, H. M., M. Chen, M. Buluzi, R. Fuchs, S. Wevill, L. Venkatasubramanian, L. Dal Santo,

and B. Ngwira. "Effect of Self-Administration Versus Provider-Administered Injection of

Subcutaneous Depot Medroxyprogesterone Acetate on Continuation Rates in Malawi: A

Randomised Controlled Trial." Lancet Glob Health 6, no. 5 (May 2018): e568-e78.

https://doi.org/10.1016/S2214-109X(18)30061-5.


Family Planning 2020. “About Us | Family Planning 2020”. Accessed June 27, 2019.

https://www.familyplanning2020.org/about-us

Foundation, Bill and Melinda Gates. Bmgf Delivery Scoping. 2008. Powerpoint.

Jacobstein, R. "Liftoff: The Blossoming of Contraceptive Implant Use in Africa." Glob Health

Sci Pract 6, no. 1 (Mar 21 2018): 17-39. https://doi.org/10.9745/GHSP-D-17-00396.


Rahman, M., M. M. Haider, S. L. Curtis, and P. M. Lance. "The Mayer Hashi Large-Scale

Program to Increase Use of Long-Acting Reversible Contraceptives and Permanent

Methods in Bangladesh: Explaining the Disappointing Results. An Outcome and Process

Evaluation." Glob Health Sci Pract 4 Suppl 2 (Aug 11 2016): S122-39.

https://doi.org/10.9745/GHSP-D-15-00313.


Ross, J., and J. Stover. "Use of Modern Contraception Increases When More Methods Become

Available: Analysis of Evidence from 1982-2009." Glob Health Sci Pract 1, no. 2 (Aug

2013): 203-12. https://doi.org/10.9745/GHSP-D-13-00010.


Stout, A., S. Wood, G. Barigye, A. Kabore, D. Siddo, and I. Ndione. "Expanding Access to

Injectable Contraception: Results from Pilot Introduction of Subcutaneous Depot

Medroxyprogesterone Acetate (Dmpa-Sc) in 4 African Countries." Glob Health Sci Pract

6, no. 1 (Mar 21 2018): 55-72. https://doi.org/10.9745/GHSP-D-17-00250.


World Health Organization. “Family planning/Contraception”, 2018, February 8. Accessed June

27, 2019. https://www.who.int/news-room/fact-sheets/detail/family-planning-

contraception

https://doi.org/10.9745/GHSP-D-16-00083

https://www.ncbi.nlm.nih.gov/pubmed/27540118

https://doi.org/10.1016/S2214-109X(18)30061-5










24

Appendix A

Indicator Definitions

Indicator 1.4: DMPA-SC is integrated into the national logistics management information system

(LMIS) Precise Definition(s): “Integrated” means that DMPA-SC is specifically listed in all LMIS standard operating

procedures, data collection tools, reporting tools, etc. and that individuals have received instructions on how to

account for the product

No DMPA-SC is not currently integrated in LMIS standard operating procedures, data

collection tools, reporting tools, etc. and there is no indication that the MOH (or

relevant decision-making body) intends to include it. 0

In Process DMPA-SC is not currently integrated in LMIS standard operating procedures, data

collection tools, reporting tools, etc., but the MOH (or relevant decision-making

body) is making efforts to include it (holding discussions, troubleshooting issues,

etc.) or has indicated they intend to include it. 0.5

Yes DMPA-SC is integrated in LMIS standard operating procedures, data collection

tools, reporting tools, etc. and individuals have received instructions on how to

account for the product. 1

Indicator 2.3: Percent of DMPA-SC costed introduction/scale-up plan funded Numerator Amount (USD) of the DMPA-SC costed introduction/scale-up plan that has been

funded to date

% Denominator Total cost (USD) of the DMPA-SC costed introduction/scale-up plan

Indicator 2.1: Costed introduction/scale-up plan for DMPA-SC developed Plan not started The introduction/scale-up plan is not yet started. 0

In process The introduction/scale-up plan is under development. 0.33

Plan developed, not

costed

The introduction/scale-up plan is fully developed and includes the necessary

details for costing, but detailed costs associated with activities are not yet

included. 0.66

Plan costed The introduction/scale-up plan is fully developed and includes detailed costs

associated with activities. 1

Indicator 2.2: Costed introduction/scale-up plan for DMPA-SC includes self-injection No The introduction/scale-up plan does not include self-injection, and the country

does not intend to introduce self-injection. 0

In Process The introduction/scale-up plan is still in process and will include SI and/or the

inclusion of SI is under discussion. 0.5

Yes The introduction/scale-up plan includes self-injection. 1

25

Indicator 2.4: Service delivery channels reflected in the DMPA-SC introduction/scale-up plan Precise Definition(s): A service delivery channel refers to the combination of sector and supply chain level by

which a client can access the product (e.g. public sector health facilities, private sector pharmacies, etc.). A new

channel is one that had not previously provided injectable contraceptives, but is doing so now that DMPA-SC has

been introduced

Sector Supply Chain Level

Does the intro/scale-up plan reflect

DMPA-SC offering at this level?

Public Facility Yes/No 1/0

Community-based sites Yes/No 1/0

Private Facility Yes/No 1/0


Pharmacy Yes/No 1/0

Drug shop Yes/No 1/0

Social Marketing Organization SMO Yes/No 1/0

Indicator 2.5: Service delivery channels active in DMPA-SC provision Precise Definition(s): A service delivery channel refers to the combination of sector and supply chain level by

which a client can access the product (e.g. public sect health facilities, private sector pharmacies, etc.). An active

channel is one that is reflected in the intro/scale-up plan, has launched DMPA-SC, and is currently providing the

product

Sector Supply Chain Level

Is DMPA-SC actively offered

through this channel?

Public Facility Yes/No 1/0


Private Facility Yes/No 1/0


Pharmacy Yes/No 1/0

Drug shop Yes/No 1/0

Social Marketing Organization SMO Yes/No 1/0


administer contraceptive injectables to users

Disaggregated by sector and supply chain levels above

TBD The introduction model is under discussion 0

Co-positioning Offering DMPA-SC side-by-side with DMPA-IM at the same service delivery

points 0.33

Transition/Replacement In a given channel that previously offered majority (or only) DMPA-IM, the

country intends to shift 85% or more of injectable supplies to DMPA-SC 0.66

Targeted Offering DMPA-SC only (not side-by-side with IM) in a new channel 1

26

Indicator 2.8: Introduction status for DMPA-SC Pre-introduction The possibility of introducing DMPA-SC into the market is being discussed by

the MOH and partners and/or ground work is ongoing to create a favorable

environment for the introduction of the product. 0

Limited

introduction

DMPA-SC has been introduced into the market for use on a limited scale,

typically as a standalone project (e.g. research study or introduction at limited

geographic scale in specific channels or regions). 0.25

Comprehensive

introduction

planning

Partners and governments are working to develop and cost a comprehensive

introduction and national scale-up plan which draws from earlier pilot studies or

projects, as applicable. 0.5

Scale-up underway DMPA-SC has been introduced into the market for wider use with the intention to

scale the product country wide. Governments are using a targeted, co-positioning,

or transition strategy, or some combination of these strategies, and training

consistent with the introduction/scale up plan has been initiated. 0.75

Scale-up complete MPA-SC has been introduced in the market for use at the coverage level identified

in the introduction/scale-up plan; DMPA-SC is integrated into family planning

and country information systems (e.g. LMIS, HMIS) and is part of a

comprehensive package of family planning methods available in country. 1

Indicator 2.9: DMPA-SC is included in national information, education and communication (IEC)

materials for family planning Precise Definition(s): Materials to support family planning service delivery and community sensitization,

including but not limited to family planning method flip charts, posters, health talk supports and other standard

national IEC materials, have integrated information on DMPA-SC. This may include print or radio spots, where

relevant to national family planning communications plans

No DMPA-SC is not currently included in national information, education and

communication (IEC) materials for family planning. 0

In Process The process to integrate DMPA-SC into national IEC materials for family

planning is underway. 0.5

Yes DMPA-SC has been fully integrated into all national IEC materials for family

planning. 1

Indicator 3.1: Registration status for DMPA-SC, 3-year shelf life, 200 pack Precise Definition(s): Refers to the process of registering a product on the country’s relevant drug regulatory

authority list.

Registration

required to import

The product must be registered in order to be imported.

0

Waiver required to

import

Until registration is complete, a waiver is required to import the product.

0.5

Registered/waiver

not required to

import

The product is either registered or can be imported without requiring a registration

waiver.

1

27

Indicator 3.2: Status of policy that authorizes community health workers to administer contraceptive

injectables to users Precise Definition(s): Policy refers to decisions, plans, and actions that are undertaken to achieve specific health


No Policy The policy allowing community health workers to administer contraceptive

injectables to users does not currently exist and is not currently being written. 0

In Process The policy allowing community health workers to administer contraceptive

injectables to users is being written. 0.33

Enacted/Authorized The policy allowing community health workers to administer contraceptive

injectables to users has been made legal or allowable. 0.66

Implemented Measures to put into practice the policy allowing community health workers to

administer contraceptive injectables to users exist. 1


administer contraceptive injectables to users Precise Definition(s): Policy refers to decisions, plans, and actions that are undertaken to achieve specific health


Disaggregated by Pharmacist and Drug shop

No Policy The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users does not currently exist and is not currently

being written. 0

In Process The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users is being written. 0.33

Enacted/Authorized The policy allowing pharmacists or staff in an accredited drug shop to administer

contraceptive injectables to users has been made legal or allowable. 0.66

Implemented Measures to put into practice the policy allowing pharmacists or staff in an

accredited drug shop to administer contraceptive injectables to users exist. 1

Indicator 3.4: DMPA-SC is included on the Essential Medicines List No DMPA-SC is not included on the EML, and there has been no indication that the

MOH (or relevant decision-making body) intends to include it. 0

In Process DMPA-SC is not currently included on the EML, but the MOH (or relevant

decision-making body) has indicated that they intend to include it; discussion

ongoing. 0.5

Yes DMPA-SC is included on the EML. 1

28

Indicator 4.3: DMPA-SC is integrated into national health management information system (HMIS) Precise Definition(s): “Integrated” means that DMPA-SC is specifically listed in all HMIS standard operating

procedures, data collection tools, reporting tools, etc. and that providers, supervisors, data managers, etc. have

received instructions on how to properly account for DMPA-SC using these forms.

Not integrated DMPA-SC is not currently integrated in HMIS standard operating procedures,

data collection tools, reporting tools, etc. 0

Integrated but not

disaggregated

DMPA-SC is specifically listed in all HIS standard operating procedures, data

collection tools, reporting tools, etc.; providers, supervisors, data managers, etc.

have received instructions on how to properly account for DMPA-SC using these

forms, however, DMPA-SC is not disaggregated from other injectables. 0.33

Integrated but

disaggregation in

process

DMPA-SC has been integrated in the HIS and providers, supervisors, data

managers, etc. have received instructions on how to properly account for DMPA-

SC; the MOH is also working on disaggregating DMPA-SC from other

injectables. 0.66

Integrated and

disaggregated

DMPA-SC is specifically listed in all HMIS standard operating procedures, data

collection tools, reporting tools, etc.; providers, supervisors, data managers, etc.

have received instructions on how to properly account for DMPA-SC using these

forms; and DMPA-SC is disaggregated from other injectables. 1

Indicator 3.5: DMPA-SC is included in the National Family Planning Policy/Strategy Precise Definition(s): The National Family Planning Policy/Strategy may be a specific document, or may be a

combination of documents such as the FP2020 action plan, the family planning costed implementation plan, etc

No DMPA-SC is not included in the FP policy/strategy, and there has been no

indication that the MOH (or relevant decision-making body) intends to include it. 0

In Process DMPA-SC is not currently included in the FP policy/strategy, but the MOH (or

relevant decision-making body) has indicated that they intend to include it;

discussions ongoing. 0.5

Yes DMPA-SC is included in the FP policy/strategy. 1

Indicator 4.6: Number and percent of service delivery points active in DMPA-SC delivery

Precise Definition(s): Active in DMPA-SC delivery means the SDP is currently managing DMPA-SC

and offering the product to clients. Experiencing a stockout of DMPA-SC does not make an SDP

inactive.

Disaggregated by sectors (public, private, SMO)

Numerator Number of SDPs active in DMPA-SC delivery

% Denominator Total number of SDPs in the country

Indicator 4.1: Family planning training guidelines and curricula include DMPA-SC Precise Definition(s): Training guidelines and curricula can refer to pre-service trainings, in-service training,

training guidelines for a specific cadre, etc.

No DMPA-SC is not included in the FP training guidelines and curricula, and there

has been no indication that the MOH (or relevant decision-making body) will

include it in the future. 0

In Process DMPA-SC is not currently included in the FP training guidelines and curricula,

but the MOH (or relevant decision-making body) has indicated that they intend to

include it and/or revisions are underway. 0.5

Yes FP training guidelines and curricula include DMPA-SC. 1

29

Indicator 7.1: Introduction status for self-injection of DMPA-SC Pre-introduction The possibility of introducing self-injection is being discussed by the MOH and

partners and/or groundwork is ongoing to create a favorable environment for SI. 0

Limited

introduction

SI has been introduced on a limited scale, typically a standalone project (e.g. SI

research study or introduction at limited geographic scale in specific channels or

regions). 0.25

Comprehensive

introduction

planning

Partners and governments are working to develop and cost a comprehensive

introduction and national scale-up plan which includes SI and/or an SI plan is

being developed separately, which draws from earlier pilot studies or projects, as

applicable. 0.5

Scale-up underway SI has been introduced for wider use with the intention to scale-up country wide

and training consistent with the SI introduction/scale up plan has been initiated. 0.75

Scale-up complete SI has been introduced in the market for use at the coverage level identified in the

introduction/scale-up plan. 1

Indicator 7.2: Regulatory approval exists for the self-injection label Precise Definition(s): Refers to the process of registering a product on the country’s relevant drug regulatory

authority list.

No The SI label is not approved 0

Yes SI label has been approved 1

Indicator 7.4: Family planning training guidelines and curricula include self-injection Precise Definition(s): Training guidelines and curricula can refer to pre-service trainings, in-service training,

training guidelines for a specific cadre, etc.

No SI is not included in the FP training guidelines and curricula and there has been no

indication that the MOH (or relevant decision-making body) will include it in the

future. 0

In Process SI is not currently included in the FP training guidelines and curricula, but the

MOH (or relevant decision-making body) has indicated that they intend to include

it and/or revisions are underway. 0.5

Yes FP training guidelines and curricula include SI. 1

Stock Status Stock out DMPA-SC is not available 0

Under stocked Supply chain does not have enough DMPA-SC for projected demand 0.33

Stocked according to plan Supply chain has enough DMPA-SC for projected demand 0.66

Over stocked Supply chain has too much DMPA-SC for projected demand 1

Indicator 7.3: Status of policy that authorizes self-injection of DMPA-SC Precise Definition(s): Policy refers to decisions, plans, and actions that are undertaken to achieve specific health


No Policy The policy allowing self-injection of DMPA-SC does not currently exist and is

not currently being written. 0

In Process The policy allowing self-injection of DMPA-SC is being written. 0.33

Enacted/Authorized The policy allowing for self-injection of DMPA-SC has been made legal or

allowable. 0.66

Implemented Measure to put into practice the policy of self-injection of DMPA-SC exist. 1

impact of government regulations and programmatic ......3.6 dmpa-sc is available over the...

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