Intelligent Information Management, 2012, 4, 194-206 Published Online September 2012 (
Measuring Effectiveness of Health Program
Intervention in the Field
Om Prakash Singh1, Santosh Kumar2
1Suresh Gyan Vihar University, Jaipur, India
2Indian Institute of Health Management Research, Jaipur, India
Received May 6, 2012; revised June 23, 2012; accepted July 12, 2012
Improving and sustaining successful public health interventions relies increasingly on the ability to identify the key
components of an intervention that are effective, to identify for whom the intervention is effective, and to identify under
what conditions the intervention is effective. Bayesian probability an “advanced” experimental design framework of
methodology is used in the study to develop a systematic tool that can assist health care managers and field workers in
measuring effectiveness of health program intervention and systematically assess the components of programs to be
applied to design program improvements and to advocate for resources. The study focuses on essential management
elements of the health system that must be in place to ensure the effectiveness of IMNCI intervention. Early experiences
with IMNCI implemented led to greater awareness of the need to improve drug delivery, support for effective planning
and management at all levels and address issues related to the organization of work at health facilities. The efficacy of
IMNCI program from the experience of experts and specialists working in the state is 0.67 and probability o f effective-
ness of all management components in the study is 58%. Overall the standard assessment tool used predicts success of
around 39% for the IMNCI intervention implemented in current situation in Rajasthan. Training management compo-
nent carried the high est weight-age of 21% with 7 3% probability of being effective in the state. Human resource man-
agement has weight-age of 13% with 53% probability of being effective in current scenario. Monitoring and evalu ation
carried a weight-age of 11% with only 33% probability o f being effective. Op erational planning carried a weigh t-age of
9% with 100% probability of being effectively managed. Supply management carried a weight-age of 8% with zero
probability of being effective in the current field scenario. In the study, each question that received low score identifies
it as a likely obstacle to the success of the health program. The health program should improve all sub-components with
low scores to increase the likelihood of meeting its objectives. Public health interventions tend to be complex, pro-
grammatic and context dependent. The evaluation of evidence must distinguish between the fidelity of the evaluation
process in detecting the success or failure of the intervention, and relative success or failure of the intervention itself.
We advocate management attributes incorporation into criteria for appraising evidence on public health interventions.
This can strengthen the value of evidence and their potential contributions to the process of public health management
and social development.
Keywords: Effectiveness; Efficacy; Performance; Evaluation; Measuring; Capacity Building of Health Interventions
1. Introduction
Health systems have a vital and continuing responsibility
to people throughout the lifespan. Comparing the way
these functions are actually carried out provide a basis
for understanding performance variations over the time
and among countries. There are minimum requirements
which every health care system should meet equitably:
access to quality services for acute and chronic health
needs; effective health promotion and disease prevention
services; and appropriate response to new threats as they
emerge (emerging infectious diseases, growing burden of
non-communicable diseases and injuries, and the health
effects of global environmental changes) [1].
The scarcity of public health resources in today’s heal-
thcare environment requires that interv en tions to improv e
the public’s health be evaluated using rigorous scientific
and management methods. Public health interventions
that cannot demonstrate effective use of resources may
not be implemented. Thus, evaluation designs must reco-
gnize and integrate the requirements of funding agents,
ensure that intervention benefits can be accurately meas-
ured and conveyed, and ensure that areas for improve-
ment can be continuou sly identified.
There is great interest in measuring the effectiveness
and impact of programs developed to assist populations
opyright © 2012 SciRes. IIM
affected by disasters and to aid in their recovery [2,3]. To
evaluate the effectiveness or cost-effectiveness of a speci-
fic health intervention typically involves comparing two
populations, one that has received the intervention and
the other that has not received it. The two populations are
compared based on the probability th at th e interv en tion is
effective in preventing or reducing the severity of the
selected health outcome. In lieu of operations research,
the probability of preventing the health outcome usually
is based only on the clinical efficacy of the intervention,
if it is known. For example, the estimated efficacy of
poliomyelitis vaccination is 95% in laboratory trials, and
this is the percentage used to describe the effectiveness
of poliomyelitis vaccination [4,5]. This approach assum-
es a one-to-one relationship between efficacy and effecti-
veness and supposes that all programmatic elements for
the health intervention (vaccination) are in place and ef-
fective and that the community has access to and wants
the intervention . As a result, these assumptions over-esti-
mate actual program effectiveness and fail to identify ba-
rriers to successful program implementation [6,7].
A great deal of applied research remains to be done to
establish the efficacy and effectiveness of health inter-
ventions and to assess the impact. In the meantime, field
staffs need a systematic method to assess program effecti-
veness that is timely, inexpensive, and measures program
capacity as well as acceptance by the population. This
will help describe actual impediments to program success
and to identify methods and resources for program imp-
rovement. Thus, to this end, an assessment process for
field workers would be developed to explore and meas-
ure whether a health program or interv ention is or will be
effective to what extent.
2. Related Work
As early as during the 1960s, an explanation of process
evaluation appeared in a widely used textbook on program
evaluation [8] (Suchman, 1967), although Suchman does
not label it “process ev aluation” per se. Suchman writes:
In the course of evaluating the success or failure of a
program, a gre at de al can be l earned about how a nd w hy
a program works or does not work. Strictly speaking, this
analysis of the process whereby a program produces the
results it does is not an inherent part of evaluative rese-
arch. An evaluation study may limit its data collection
and analysis simply to determining whether or not a pro-
gram is successful. However, an analysis of process can
have both admin istrative and scientific significance , par-
ticularly where the evaluation indicates that a program is
not working as expected. Locating the cause of the fa ilure
may result in modifying the prog ram so that it will work,
instead of its bei ng discarded as a comple te f ail ure .”
This early definition of process evaluation includes the
basic framework that is still used today; however, as is
discussed later in this chapter, the definitions of the com-
ponents of process evaluation have been further deve-
loped and refined. Few references to process evaluation
were made in the literature during the 1970s. In evaluation
research, the 19 70s w ere devoted to the issues of improv-
ing evaluation designs and measuring program effects.
For instance, Struening and Guttentag’s Handbook of
Evaluation Research (1975) does not contain any refere-
nce to process evaluation [9]. In their influential book,
Green, Kreuter, Deeds, and Partridge [10] (1980) define
process evaluation in a somewhat unusual way:
In a process evaluation, the object of interest is pro-
fessional practice, and the standard of acceptability is
appropriate practice. Quality is monitored by various
means, including audit, peer review, accreditation, certi-
fication, and government or administrative surveillance
of contracts and grants.”
The emphasis on professional practice as the focus of
process evaluation as suggested by Green, Kreuter, Deeds,
and Partridge (1980) faded as attention returned to the
idea of assessment of program implementation. By the
mid-1980s, the definition of process evaluation had ex-
panded. Windsor, Baranowski, Clark, and Cutter [11]
(1984) explain the purpose of process evaluation in the
following way:
Process produces documentation on what is going on
in a program and confirms the existence and availab ility
of physical and structural elements of the program. It is
part of a formative evaluation and assesses whether spe-
cific elements such as facilities, staff, space, or services
are being provided or being established according to the
given program plan. Process evaluation involves docum-
entation and description of specific program activities
how much of what, for whom, when, and by whom. It inc-
ludes monitoring the frequency of participation by the
target population and is used to confirm the frequency
and extent of implementation of selected programs or
program elements. Process evaluation derives evidence
from staff, consumers, or outside evaluators on the qual-
ity of the implementation plan and on the appropriate-
ness of content, methods, materials, media, and instru-
Effectiveness is defined emphasizing that it is a pro-
blem domain measure which needs to support the comp-
arison of systems. A simple thought experiment clarifies
and illustrates various issues associated with aggregating
measures of performance (MoP) and comparing measure
of effectiveness (MoEs). This experiment highlights the
difficulty in creating MoEs from MoPs and prompts a
mathematical characterization of MoE which allows De-
cision Science techniques to be applied. Value Focused
Thinking (VFT) provides a disciplined approach to decom-
posing a system and Bayesian Network (BN) Influence
Diagrams provide a modeling paradigm allowing the ef-
Copyright © 2012 SciRes. IIM
fectiveness relationships between system components to
be modeled and quantified. The combination of these two
techniques creates a framework to support the rigorous
combination measurement of effectiveness.
To overcome the shortcomings of traditional approa-
ches to measuring effectiveness it is proposed that it is
critical to measure effectiveness in the problem domain
and an approach from Decision Science is used to produ-
ce a clear distinction between the problem and solution
domain. The problem domain objectives are used to cre-
ate a Bayesian Network model of the interactions between
elements in such a way that the effectiveness of the ele-
ments can be combined to indicate overall effectiveness.
Various definitions have been proposed, beginning in
the 1950’s and progressing through MORS and NATO
definitions in the 1980’s [12]. These definitions are larg-
ely hierarchical and h ave yet to resolve how to aggregate
and propagate performance and effectiveness measures
through the h ierarchies. Th ese d efinitions tended to fo cus
on measurement and effectiveness criteria. Sproles (2002)
[13] refocused the discussion of effectiveness back to the
more general question of “Does this meet my need?” and
hence defined Measures of Effectiveness (MoE) as:
Standards against which the capability of a solution
to meet the needs of a problem may be judged. The stan-
dards are specific properties that any potential solution
must exhibit to some extent. MoEs are independent of
any solution and do not specify performance or criteria.”
Needs may be satisfied by various solutions. The so-
lutions may be unique or may share aspects of other so-
lutions. Each solution may (and usually will) have dif-
ferent performance measures. Sproles distinguishes be-
tween Measures of Performance (MoP) and MoE by de-
claring that MoP measures the internal characteristics of
a solution while MoE measure external parameters that
are independent of the solution—a measurement of how
well the problem has been solved.
The primary focus of the framework proposed here is
to compare systems and to produce a rank ordering of
effectiveness, as suggested by Dockery’s (1986) MoE
definition [14]:
A measure of effectiveness is any mutually agreeable
parameter of the problem which induces a rank ordering
on the perceived set o f goals.
The goal is not to derive absolute measures as they do
not support the making of comparisons between disparate
systems whose measures may be based on totally different
characteristics and produce values with different ranges
and scales.
The two aspects of these definitions of MoE were em-
phasised in the definition of MoE by Smith and Clark
(2004) [15]:
A measure of the ability of a system to meet its spe-
cified needs (or requirements) from a particular view-
point(s). This measure may b e quantitative or qua litative
and it allows comparable systems to be ranked. These
effectiveness measures are defined in the problem-space.
Implicit in the meeting of problem requirements is that
threshold values must be exceeded.”
In common with Sproles [16], it is accepted that effec-
tiveness is a measure associated with the problem domain
(what are we trying to achieve) and that performance me-
asures are associated with the solution domain (how are
we solving the problem).
To develop a practical method to measure program ef-
fectiveness in the field, the literature on program eva-
luation and performance was reviewed, looking for des-
cription of program success. To calculate the expected
effectiveness of public health intervention (Eph), the
relationship between the expected effectiveness of a heal-
th program and the factors that influence its success are a
product of the efficacy of the strategy or intervention (SE)
and the probability that the health program in place can
deliver the interventions successfully. Sharon M. Mac-
Donnel, et al. used Bayes theorem as essential too l in Af-
ghanistan and retested in six different settings Zimbabwe,
Tanzania, Guetamala, Philiphines and Ghana and found-
ed that this method systematically assessed the compo-
nents of program and results can be applied to design
program improvements and to advocate for resources. On
carefully reviewing this, it was noticed that it mainly
consists of four components human resource, training,
infrastructure and community support.
The adoption of Bayes’ theorem has led to the deve-
lopment of Bayesian methods for data analysis. Bayesian
methods have been defined as “the explicit use of external
evidence in the design, monitoring, analysis, interpreta-
tion and reporting” of studies. The Bayesian approach to
data analysis allows con sideration of all possible sou rces
of evidence in the determination of the posterior proba-
bility of an event. It is argued that this approach has more
relevance to decision making than classical statistical inf-
erence, as it focuses on the transformation from initial
knowledge to final opinion rather than on providing the
“correct” inference. In addition to its practical use in pro-
bability analysis, Bayes’ theorem can be used as a norm-
ative model to assess how well people use empirical info-
rmation to update the probability that a hypothesis is true.
Bayes’ theorem is a logical consequence of the product
rule of probability, which is the probability (P) of two
events (A and B) happening—P(A,B)—is equal to the
conditional probability of one event occurring given that
the other has already occurred—P(A|B)—multiplied by
the probability of the other event happening—P(B). The
derivation of the theorem is as follows:
 
PA|B PB|APA/PB . Thus:
Copyright © 2012 SciRes. IIM
Capacity assessment tools designed to assess organi-
zational performance were reviewed. The majority of the
23 tools reviewed employ several data collection instru-
ments. Nearly half of them used a combination of quali-
tative and quantitative methods, four used quantitative
method and seven used qualitative methods. Half of the
tools are applied through self-assessment techniques,
while nine tools use a combination of self and external
assessment and two tools use external assessment. Self-
assessment tools can lead to greater ownership of the
results and a greater likelihood that capacity improves.
However, many such techniques measure perceptions of
capacity, and thus may be of limited reliability if used
over time. The use of a self-assessment tool as part of a
capacity building intervention may preclude its use for
monitoring and evaluation purposes. Methodologies for
assessing capacity and monitoring and evaluating capa-
city building interventions are still in the early stages of
development. Experience of monitoring changes in
capacity over time is limited. Do cumentation of the range
of steps and activities that comprise capacity develop-
ment at the field level is required to improve under-
standing of the relationship between capacity and perfor-
mance, and capacity measurement in general. Finally,
there are few examples of use of multiple sou rces of data
for triangulation in capacity measurement, which might
help capture some of the complex and dynamic capacity
changes occurring within systems, organizations, program
personnel, and individuals/communities.
Nearly one third of tools reviewed include adminis-
trative and legal environment aspect and one fourth in-
clude socio cultural, political and advocacy environment
while doing the assessments. External factors represent
the supra-system level and the milieu that directly or in-
directly affects the existence and functioning of the public
health organization. It incorporates phenomenon such as
the social, political, and economic forces operating in the
overall society, the extent of demand and need of public
health services within community, social values. Inclusion
of external factors in assessment tool demonstrates that
organization is engaged in dynamic relationships.
Based on the review of capacity assessment tools and
discussion with experts of public health, we grouped ele-
ments of program effectiveness in 10 management com-
ponent namely mission and values, strategic manage-
ment, operational planning, human resource management,
financial management, monitoring and evaluation systems,
logistics and supply system, quality assurance, and respon-
siveness to client/service delivery.
3. Material and Methods
The research fra mework for the study is based on Bayes’
theorem. Bayes’ theorem deals with the role of new info-
rmation in revising probability estimates. To develop a
practical method to measure program effectiveness in the
field, the literature on program evaluation and perform-
ance was reviewed, looking for description of program
success. To calculate the expected effectiveness of public
health intervention (Eph), the relationship between the
expected effectiveness of a health program and the fact-
ors that influence its success are a product of the efficacy
of the strategy or intervention (SE) and the probability
that the health program in place can deliver th e interven-
tions successfully.
Seven step process to calculate effectiveness of pro-
gram intervention in demons trated in Table 1.
The following steps followed to calculate the expected
effectiveness of public health intervention:
Step 1: Selection of the public health program or in-
tervention which needs to be evaluated.
Integrated Management of Neonata l Chil dhood Ill nesses
(IMNCI) program based on the discussion with public
health experts was selected as case study for evaluation.
Step 2: Define the efficacy of the intervention.
The efficacy of the intervention is defined using avail-
able health literature or field trials. If it is unknown, it
can be discussed and estimated. In this study IMNCI pro -
gram efficacy is based on the opinion of experts working
on IMNCI in India and Rajasthan.
Step 3: Define the key components/elements of pro-
gram effectiveness.
Based on literature review of performance measuring
studies of health interventions and discussions with the
public health experts, decision makers and implementers
identify key elements of program success and factors
influencing the success of the program. Using this infor-
mation, develop a set of standard questions and instruc-
tions. To help staff members to determine whether these
elements increase or decrease their overall program ef-
fectiveness, and in what ways, a standard field assessment
tool was developed. The standard field assessment tool is
designed to describe and measure the essential variables
within the health program effectiveness categories and
the proportion of weight age each element carries for
Table 1. Seven step process to calculate effectiveness of
program intervention.
Seven step process to calculate effectiveness of program interven-
Step 1: Selection of the public health program or intervention which
needs to be evaluated
Step 2: Define the efficacy of the intervention
Step 3: Define the key components/eleme n t s o f p rogram effectiveness
Step 4: Selection of the assessment team and define scoring
Step 5: Conduct the interview with program decision makers, mangers
and field level workers
Step 6: Using worksheet to calculate the program effectiveness
Step 7: Calculate aggregate probability (PA) that the program in place
delivers the health intervention effectively
Copyright © 2012 SciRes. IIM
success of the program. Identified 10 elements of health
program effectiveness are mentioned in Table 2.
Step 4: Selection of the assessment team and define
Review and adopt the criteria and essential features of
each of the key management components of health pro-
gram effectiveness. All answers “a” are 0 points, “b” is 1
point, “c” answers are 2 points and “d” answers are 3
points. If there are more than one respondent for a ques-
tion, the mode value is calculated for scoring.
Step 5: Conduct the interview with program decision
makers, mangers and field level workers.
Five state level officials having stake in IMNCI plan-
ning and implementation including State Program Man-
ager, State IMNCI Coordinator, Child Health Coordina-
tor and Additional Director and State Demographer offi-
cials was interviewed personally. UNICEF officials at
state level involved in conceptualizing, planning and sup-
porting the state government in implementing IMNCI
Program were personally interviewed. The officials in-
terviewed were Health Specialist, Health Officer and
IMNCI Consultants. Total four persons were int erviewed.
The IMNCI program managers at zonal level and dis-
trict level were approached through email. The question-
naire was circulated to them with instruction of best
knowing and responding to the questions as per their un-
In the month of February 2010, the data collection
tools were finalized. Five state level officials are having
say in IMNCI planning and implementation including
State Program Manager, State IMNCI Coordinator, Child
Health Coordinator and Additional Director and State
Demographer officials was interviewed personally.
UNICEF officials at state level involved in conceptu-
alizing, planning and supporting the state government in
implementing IMNCI Program were personally inter-
viewed. The officials interviewed were Health Specialist,
Health Officer and IMNCI Consultants. Total four per-
sons were interviewed.
Table 2. Management components of health program effec-
S.No. Management components
1 Mission and values
2 Strategy development
3 Operational planning
4 Human resource a nd manageme n t
5 Training
6 Monitoring and evaluation
7 Quality assurance
8 Financial management
9 Supply management
10 Community support
Reproductive Child Health officer, District Program
Manager, District IMNCI Coordinator, 10 Medical offi-
cers, two District IMNCI Monitoring Supervisors, and
three IMNCI tutors were interviewed. In addition to this,
10 ANMs and 30 ASHAs were interviewed with the sup-
port of nursing tutors.
In order to obtain consent from the participants, a me-
thodology of “implied consent” [17] was used. The ob-
jective of survey was read out to each of the person inter-
viewed personally and shared via email and shared that
all individual information would be confidential. Names
were recorded only on the consent of the participants
otherwi s e n ames were not recorded.
Step 6: Using worksheet to calculate the program ef-
Record the responses from questionnaire on to the
worksheet. Add the points of each component and calcu-
late the subtotal score. Calculate the maximum possible
scores assigned to each component. Calculate the propor-
tion of each component by dividing the sub total score
with maximum possible points. This gives probabilities
of effectiveness of each component based on scoring sys-
tem (P). As demo nstrated in Table 3 for two management
components the P value is calculated for all the 10 mana-
gement components.
Program effectiveness (PE) is product of P and contri-
bution i.e., weight age (W) assigned to each management
component. The tabular form for calculation is men-
tioned in Table 4. As a formulae it is represented as PE =
P1*W1 + P2*W2 + P3*W3··· where P1 and W1 repre-
sent individual component effectiveness weight age re-
Step 7: Calculate aggregate probability (PA) that the
program in place delivers the health intervention effect-
tively using the following:
PA = PE* efficacy of the intervention.
The aggregate overall probability of health program
effectiveness is the product of efficacy of the specific
intervention multiplied by the sum of the probabilities of
each of the weighted components contributions.
Experimental design is used as study intends to predict
P phenomenon. Bayesian probability an “advanced” ex-
perimental design is main framework of methodology
Table 3. Worksheet to calculate the p rogram effectiven es s .
Mission and values Strategy
Sub component
Existence and knowledge
of mission
Defined organizational
values and principles
Sub total score
Sub total score divide
by total possi
le score
(0 - 3)
Sub component
Program strategies linke
to Mission
and values
Program Strategies linked
to clients
and communities
Subtotal score
Subtotal score divided by
total possible score (P)
(0 - 3)
Copyright © 2012 SciRes. IIM
Copyright © 2012 SciRes. IIM
used in the study [18]. This advanced experimental de-
sign is used for settings as there are many variables
which are hard to isolate.
Judgmental sampling technique is used in the study.
Judgmental sampling is a non-probability sampling tech-
nique where the researcher selects units to be sampled
based on their knowledge and professional judgment (by
Joan Joseph Castillo (2009)). This type of sampling
technique is also kno wn as purposive sampling and auth-
oritative sampling.
Data entry and cleaning was done by self. Data entry
and analysis was done using SPSS for Windows 16.0. In-
itial data analysis included frequency tables on the indiv-
idual items of the interview. Subsequently, using the qual-
ity dimensions that form the framework of Bayes theorem
the ten management attributes and their subsequent sub
components we re analyzed based on sc o re syst em.
Several forms of research bias could not be prevented
due to various constrains encountered: time, resources,
research implementation, analysis and design. Selection
bias could not be ruled out because of non-random meth-
od used to select the participan ts.
4. Experimental Result and Discussion
Integrated Management of Child hood Illness Program
(IMNCI) is run by Government of Rajasthan with mana-
gerial and technical support of UNICEF designed to
combat the high Infant Mortality Rate (IMR) in the state
through training and support to field level h ealth workers
such as ASHAs and ANMs. During the study, the program
effectiveness tool to measure the program effectiveness
was used in collaboration with Program Managers and
implementers to evaluate the likelihood of this public
health program in the state. The findings from this study
are described here and scored numerically on worksheet
for refer en ce.
IMNCI program effectiveness in the state of Rajasthan
calculates to be 58% from probabilities of effectiveness
for each program component based on scoring system
and the contribution (weight) given to each category. The
worksheet for the calculation of program effectiveness is
reflected in Table 5.
Table 1. Calculating probability of program effectiveness.
Probabilities of effectiveness of each program
component based on th e scoring system (P)Contribution (weight) given to
each category (W) Probability of program
effectiveness (PES*W)
Mission and values
Strategy development
Operational planning
Human resource an d managemen t
Monitoring and evaluation
Quality assurance
Financial management
Supply management
Community support
Probability of PE
Table 5. Worksheet for calculating the health program effectiven ess.
Probabilities of effectiveness of each program
component based on th e scoring system (P)Co ntribution (weight) given to
each category (W) Probability of program
effectiveness (PES*W)
Mission and values (MV) 0.50 0.08 0.04
Strategy (S) 0.67 0.07 0.05
IMNCI OP (OP) 1.00 0.09 0.09
IMNCI HR (HR) 0.56 0.13 0.07
IMNCI training (T) 0.73 0.21 0.15
M & E (ME) 0.33 0.11 0.04
QA (QA) 0.67 0.09 0.06
FM (FM) 0.44 0.08 0.04
SM (SM) 0.00 0.08 0
CS (CS) 0.67 0.06 0.04
Probability of PE 0.58
The aggregate overall probability of health program
effectiveness is the product of efficacy of the specific
intervention multiplied by the sum of the probabilities of
each of the weighted components contributions.
Probability of aggregate program effectiveness
Efficacy of interventionhealth program effecti
PA PEefficacy of the intervention
10.58 assuming 100 percent efficacy of i
0.58 or
The study focuses on essential management elements
of the health system that must be in place to ensure the
effectiveness of IMNCI intervention. Early experiences
with IMNCI implemented led to greater awareness of the
need to improve drug delivery, support for effective
planning and management at all levels and address issues
related to the organization of work at health facilities.
The efficacy of IMNCI program from the experience of
experts and specialists working in the state is 0.67 and
probability of effectiveness of all management compo-
nents in the study is 58%. Overall the standard assess-
ment tool used predicts success of around 39% for the
IMNCI intervention implemented in current situation in
Rajasthan. Training management component carried the
highest weight age of 21% with 73% probab ility of being
effective in the state. Human resource management has
weight age of 13% with 53% probability of being ef-
fective in current scenario. Monitoring and evaluation
carried a weight age of 11% with only 33% probability
of being effective. Operational planning carried a weight
age of 9% with 100% probability of being effectively
managed. Supply management carried a weight age of
8% with zero probability o f being effective in th e current
field scenario.
In the study, each question that received a zero for any
element of the 10 management components and its sub-
components identifies a likely obstacle to the success of
the health program. The health program should improve
all sub-components with low scores to increase the like-
lihood of meeting its objectives. If the total score is less
than 50%, the program is unlikely to be effectively im-
plemented, and if the total score is more than 80%, the
program is likely to be effectively implemented. If the
score of any entire component is zero, the actual proba-
bility of program effectiveness should be considered zero .
The formula as provided does not naturally lead to this
conclusion because it is additive rather than multiplicative.
Evidence-based health care is untended to take account
of efficiency as well as effectiveness, although to date
efficiency questions have not been emphasized in evi-
dence-based medicine [19]. The appraisal of evidence on
public health interventions must inevitably determine
whether the efficiency has been assessed, and if so, how
well. Public health interventions are rarely a standard
package. To assess the success of intervention, informa-
tion is needed on the multiple components of interven-
tion. This should also include details about the design,
development and delivery of the various intervention
strategies. Information is also needed on the charac-
teristics of people for whom the intervention effective,
and the characteristics of those for whom it was less ef-
fective. The social, organizational and political setting
(context) in which a public health intervention is imple-
mented usually influences the intervention effectiveness
[20]. It is important to distinguish between components
of interventions that are highly context dependent and
those that may be less so.
Field workers need tools to systematically describe
and measure key elements of program effectiveness so
that they can rapidly identify specific areas of insuffi-
ciency and communicate these needs more effectively to
program managers and decision makers. Tools for prog-
ram effectiveness that do not consider health worker
training, infrastructure, and community assessment can
greatly overestimate program effectiveness [21]. A known
good intervention (e.g., immunization) delivered through
a poor program cannot be effective.
Field staff reported that using the assessment tool pro-
moted more detailed and creative discussions about the
actual problems and potential solutions that had to be
considered in the design and improvement of their pro-
In fact, the discussions among staff members regard-
ing their programs often were reported as being just as
important as the actual calculation of the numbers. For
example, the health workers in the Afghanistan case study
used the information gathered to discourage their NGO
from adding more curriculum material in the basic course
for female health workers. Instead, the program focuses
and grant proposal emphasized a shift to improved rec-
ruitment, applied training, and infrastructure components
relating to supervision and continuing education. For
some program staff, the calculations might appear dis-
couraging and can be skipped. Many mentioned the value
of reviewing the distinction between efficacy and effecti-
veness and to explicitly understand that for many prog-
ram interventions, the efficacy is not known and effecti-
veness has not been well researched. The major limi-
tation of this approach is the potential for inter-observer
variability. Different persons using the same question-
naire can get different results even in the same situation.
However, within a program, the field staff usually work-
ed with the questionnaire to define the terms and indi-
cators. Another limitation of this method is that it has not
been tested over time to determine how well it corre-
sponds with actual program performance or health out-
There are not gold-standard tools available to measure
Copyright © 2012 SciRes. IIM
program capacity and effectiveness [22]. To improve this
methodology and its tools, the authors intend to refine
the questions within each component and to increase the
specificity of the information collected. This is needed,
particularly in the community support components. Fur-
ther validation should assess inter-observer variation.
The method’s instructions also must be tested with new
evaluators and within a variety of programs, to assess
how easy it is for others to administer the questions, use
alternative data sources, and calculate the overall proba-
bility. Staff members in Tanzania assessing health in-
formation systems raised the issue of the availability of
allied services (e.g., laboratory); this method could be
modified to address specific program elements.
Based on the information collected in the field tests,
one of the most important areas that should be addressed
is whether the weighting of the components should be
changed. For example, infrastructure problems were na-
med as the biggest impediment to program effective-
ness by health workers, ministry officials, and donors,
and might need to be given a higher weight. The infras-
tructure measures used for this category often were asso-
ciated with the con cept of higher-level “political support”
and long-term viabil it y [23] . The usefulness of this met hod
will increase with more thorough descriptions of core
health worker functions.
Finally, the usefulness of this tool must be judged
through further field-testing and validation to determine
if its use by field work ers leads to substantive changes in
the processes and outcomes of health programs. Beyond
the field level, it is hoped that by measuring and using
these programmatic variables, more attention will be
focused on innovative methods that improve the training
and support of health workers, the quality and type of
infrastructure, and the support of communities, thereby
addressing well-known, but often ignored, problems of
health programs.
The major challenges were noted in effective imple-
mentation of IMNCI in Rajasthan: drug supply with zero
effectiveness; poor financial and HR management, poor
monitoring and evaluation and low level of implemen-
tation at health facilities by trained staff. At the facility
level, low take up of implementation of the strategy is
partly attributed to factors which are specific to IMCI,
such as inadequate supply of job aids, lack of IMCI su-
pervision and protocol length. Other constraints to im-
plementation include staff shortages at lower level faci-
lities, infrequent routine supervision that includes case
management observations, and frequent drug stock-outs.
Findings from the Multi Country Evaluation (MCE)
study of IMCI effectiveness carried out in 5 countries
(Bangladesh, Brazil, Peru, Tanzania and Uganda) from
1998-2004 suggested that IMCI was more effective and
less costly than routine care. Health workers who received
IMCI case management training in Tanzania, for example,
provided a better quality of care than untrained health
workers [24], and there were notable improvements in
classification, diagnoses, treatment and counseling by
trained health workers, compared to those who had not
received any training. Similarly, in Uganda, it was repo-
rted that health workers who had been trained in IMCI
consistently provided better care for sick children than
untrained health workers [25]. These positive results
were not, however, r eported by all of th e MCE countries.
Arifeen et al. (2005) [26] showed that, even though Bang-
ladeshi health providers were trained in IMCI, skill-
suptake was not guaranteed, resulting in littl e or no ap pli-
cation of IMCI case management in practice. Similarly,
doctors and nurses in Brazil did not show any major diff-
erence in the quality of care given to sick children com-
pared to untrained health providers [27].
Impact studies conducted in Peru did not look at the
effects of IMCI training on health worker behaviour;
however, one study showed no significant associations
between training coverage and changes in mortality or
nutrition indicators [28]. Even where positive impacts
were achieved, the MCE findings emphasized that more
efforts should be made to ensure better coverage of IMCI,
such as availability of sufficient resources to sustain
IMCI implementation activities and cover all 3 compon-
ents of the strategy.
Studies on IMCI implementation in other countries
have some similar findings, suggesting that the issues
raised by this study can still provide important insights
into implementation challenges in similar contexts [29].
Several past studies which examined implementation
challenges of IMCI have also highlighted poor health
worker compliance, indicating that it is likely to be a ge-
neric issue across many different country settings. In a
study conducted by Rowe et al. (2001) in Benin, determi-
nants for poor implementation of IMCI by health workers
were identified using qu alitative research appro aches (in-
terviews, case management observations). These studies
focused on selected component of IMNCI interventions
and thus not represent complete assessment of IMNCI
program implementation.
Our study results were surprisingly close to their fin-
dings, with health workers reporting almost all of the
same reasons for poor implementation, such as poor
facility support (job aids, equipment, and drugs), high
workloads, short-staffing, and no or little IMCI-specific
Nsungwa-Sabiitii et al. (2004) repo rted th at health sys-
tems and resource constraints similar to those found in
Kenya have also affected IMCI implementation in Uga-
nda [30]. For example, difficulties in drug acquisition led
to Uganda adopting a “pull system” to improve drug de-
liveries to facilities but this has had little effect. In terms
Copyright © 2012 SciRes. IIM
of financial support, IMCI was noted as requiring vast
amounts of resources and, despite there being several
funders, not a lot of money has been raised to support
existing or future activities. This study focused on direct
supply process and did not take human resource required
for supply management.
Supply management with zero effectiveness needs to
be paid attention in the state. A system to procure, track
and regulate supplies needs to be in place. Health de-
partment needs to train staff to handle IMNCI supplies.
One major constraint to poor implementation of IM-
NCI in Rajasthan is the lack of financial management
system for the facility component of the strategy. Our
interviews/inv estigation showed that this d eclinin g interest
reflects the high cost of training, difficulties in demons-
trating the public health i mpact of IMCI, increased focus
on the community aspect of the strategy, lack of consensus
on new or alternative training approaches. Financial sys-
tem for IMNCI needs improvement. Program Managers
need to work with financial staff to develop IMNCI
budgets that support programmatic decision. The finan-
cial system needs to present an accurate, complete pic-
ture of IMNCI expenditures, revenue, and cash flow in
relation to program output and services. The health de-
partment to follow a long term fund generation strategy,
balancing diverse sources of revenue to meet current and
future needs. In our literatu re review we did not find any
paper or research article focusing on financial manage-
ment of IMNCI system.
Variations in the implementation experience were also
noted. These include differences in human resource man-
agement systems, health worker adherence to IMNCI
guidelines, and overall support o f the strategy. The major
determinant of these differences appeared to be the
leadership role of the IMNCI.
Major barriers to IMNCI implementation arising from
broader health system issues were documented in many
countries. These barriers included: the difficulties of con-
ducting regular supervisory visits that included systema-
tic observation and feedback on case manage ment; in ade-
quate referral facilities; high staff turnover; low utiliza-
tion of the public sector for a variety of reasons (accessi-
bility, user fees, poor perceived quality, etc.); and inconsi-
stencies between IMNCI guidelines and existing policies
and regulations. Health department needs to regularly
monitor its IMNCI progress, evaluate results ad use find-
ings to improve services and plan the next phase of work.
Health system to provide cr oss-checking to guarantee the
accuracy of routine IMNCI services and data. Staff mem-
bers who submit report consistently should get prompt
feedback. With their managers, they analyze the infor-
mation and use their findings to analyze the trends, im-
prove management and performance, and achieve out-
High-quality training in IMNCI case management can
lead to rapid and dramatic improvement in the quality of
case management in first-level health facilities. In this
context, “high quality” is defined as training that is based
on the IMNCI clinical guidelines and includes sufficient
opportunities for trainees to practise the new skills in cli-
nical settings. In some Regions this training also includes
follow-up visits to health workers in their facilities after
training to reinforce skills and assist health workers in
applying them. However, IMNCI training can only be
effective in improving th e quality of case manag ement in
the presence of health system supports. A common find-
ing across the 12 MCE country reviews was that these
supports were not in place. Although the constellation of
health system deficits varies to some extent from region
to region, and especially in the post-Soviet countries
versus all others, many of the challenges are similar. In
Tanzania, health system supports had been reinforced in
the two intervention districts through the introduction of
two relatively simple interventions: making available
district-level data on the burden of disease, and epide-
miological mapping. Outside the intervention districts,
however, Tanzania faces many of the same health system
deficits as the other countries visited. From the assess-
ment study we found that training carries maximum
weight-age of 21 percent for effective implementation of
IMNCI in the state of Rajasthan. The effectiveness of
training in Rajasthan w as found to be 73 percent. Almost
80 percent of respondents felt IMNCI workers had
relevant education or experience for being IMNCI work-
er and half of respondents felt the IMNCI orientation
program is in place. From the study it is revealed that
training is formal component of the health department
and it allows adequate time for each participant for on
hand practice.
Development and implementation of interventions to
improve key family behaviors has proven more difficult
and time-consuming than anticipated at the time MCE
was designed. Among the 10 countries visited that were
actively implementing IMNCI, only Brazil had com-
munity component—delivered by community health
workers—that seemed likely to achieve high levels of
coverage. In short, several of the assumptions underlying
the IMNCI impact model need to be re-examined in light
of experience with IMNCI implementation to date and
the findings of MCE country reviews.
An Evaluation of the Quality of IMCI assessments
among IMCI Trained Health Workers in South Africa
2009 found that health workers are implementing IMCI,
but assessments were frequently incomplete, and children
requiring urgent referral were missed. If coverage of key
child survival interventions is to be improved, interven-
tions are required to ensure competency in identifying
specific signs and to encourage comprehensive assess-
Copyright © 2012 SciRes. IIM
ments of children by IMCI practitioners. The role of su-
pervision in maintaining health worker skills needs fur-
ther investigation. Further research is required to inves-
tigate the factors leading to poor health worker per-
formance, which is frequently ascribed just to a lack of
knowledge and skills. Health workers often find it dif-
ficult to transfer new skills to the work place, and to
maintain these skills, especially as IMCI consultations
take longer. Implementing and sustaining IMCI follow
up after training has been shown to be difficult in several
previous evaluations of IMCI However, supervision has
been shown to improve performance and may also im-
prove motivation and job satisfaction. The role of IMCI
supervision in IMCI implementation and different mo-
dels for provision of supervision should be investigated
Performance Analysis of IMNCI in Madhya Pradesh
2006 reported that training under IMNCI is reported to
be very beneficial by all the respondents but the lack is
that there is no provision of follow up or refresher train-
ings especially for field staffs. While in non-IMNCI
districts the skills and knowledge of field staffs is not as
sound as that of MNCI districts staffs on children health
care and disease management. The home based care has
been given special emphasis under IMNCI and is very
effective strategy for disease management at an early
stage. But the functional problem found in home based
care is that the field staffs are highly overloaded with a
wide area and various activities including too much paper
work. So it becomes practically impossible for field staff s
to manage sufficient time to provide home based manage-
ment and counseling to all the beneficiaries for children
and maternal health care. In non-IMNCI districts the
status of home visit is further in bad shape as compared
to the IMNCI districts. Under IMNCI the staffs is ori-
ented to identify and refer the sick children to public
health institutes at earliest. But due to the lack of proper
information among community about the childhood ill-
ness and services under IMNCI the community doesn’t
approach to the aaganwadi center for referral support.
Also, the system and facilities at public health institutes
are in so bad conditions that those who are reaching to
the institutes by hard efforts of field staffs get so annoyed
that they don’t wish to visit again. Also AWW are mostly
making oral referral & not ready to take-up the respon-
sibility for child referral. The instructions and the process
regarding the incentive distribution are not at all clear.
There is severe shortage of manpower & essential faci-
lities for safe child birth, newborn care & treatment of
childhood illness at block & district levels public health
institutions. The most positive approach visible in IMNCI
district is the establishment of SNCU that leads to pre-
vention of child mortality in newborn period. But block
level institutions at IMNCI districts are still lacking such
Though in spite of being a very innovative program
IMNCI is not meeting its objective of securing better
child health and all these problems are due to the neglect
or the neutral attitude of the administration. While in
practical it is always seen that the lower most link i.e. the
field staffs are often blamed for non-achievement of the
set targets. Moreover, if someone complaints about the
non-functioning of any program/activities or if anything
goes wrong then the foremost step taken is the removal/
suspension of these field staffs who can do nothing to
resurrect the things nor there is any support system
available for them at district or state level which could
help these field staffs to prevent the casualties.
To make IMNCI (or any program) really working and
result orienting, the government should develop all the
connected wings equally whether it is the training of
implementing staffs, follow-up, supervision or the infras-
tructural su pport.
Report of IMCI evaluation in the District of Kirehe in
Rwanda, July 2008 concludes that on the operational
level, managers of HCs were able to implement IMCI
through the collaboration of parents and other health
workers who have welcomed this new approach of mana-
gement of sick children. But significant barriers impede a
final and sustainable IMCI implementation and this is an
appeal to health authorities from the central level. These
barriers are: lack of supervision, insufficient number of
trained health care providers, non-harmonization of mal-
aria management guidelines, non-integration of IMCI in
the health management information system, non-equit-
able management of ambulances to promote children’s
access to emergency care, the insufficient availability of
patient forms and especially the fact that IMCI is not
integrated with the group of activities quoted by the
performance based financing approach to increase moti-
vation and retention of staff in general and trained per-
sonnel in particular. The training of health workers in
IMCI is necessary to improve the quality, but not enough
to ensure a continuously acceptable quality level without
the establishment of a mechanism for monitoring and
strengthening of techn ical skills such as formative super-
vision. IMCI is not considered in the performance based
financing approach at health centers level and is not inte-
grated into the health information management system.
Effect of Supportive Sup ervision on ASHA s’ Perform-
ance under IMNCI in Rajasthan UNICEF 2008-09 find-
ings show that supportive supervision by an external agent
can lead to substantial improvement in the performance
of ASHAs as related to IMNCI. Under the current
supervisory system, many line supervisors lack a clear
understanding of their roles and respon sibilities as super-
visors. In addition, they lack sufficient time and training
to provide supervisory support to ASHAs under IMNCI.
Copyright © 2012 SciRes. IIM
We find that supportive supervision has the greatest
effect in improving ASHAs’ capacity, and hence their
performance under IMNCI in the following areas: record
keeping, motivation, and knowledge and skills, such as
the use of IMNCI reference materials and techniques in
home visit assessments. However, while external suppor-
tive supervisors were effective in providing IMNCI mat-
erials, registers, and case sheets, we find less evidence
that they can improve access to medicine. Regardless of
the presence of supportive supervision, ASHAs continue
to face resistance from their communities against insti-
tutional deliveries, immunizations, health checks for new
born, and referral to hospital facilities.
In general, IMCI could be said to be a typical example
of a top-down approach to implementation, with the policy
set at the central level then communicated to lower lev els,
such as the provincial, district level and facility level,
with minimal adaptation taking place at each level. This
model assumes actors at the top have the most power,
and actors at other levels follow a chain of command.
Debates about the top-down approach highlight the
following issues and/or assumptions, making such models
of implementation unrealistic through: ignoring the im-
portance of involvement of non-government actors in de-
cision-making as well as those from lower levels of the
health system; assuming that all actors are committed,
skilled, willing (compliant) and supportive of the policy;
ignoring the possibility of constraints imposed by external
agencies or circumstances that might undermine efforts;
and/or assuming perfect coordination of implementation
activities [31].
The success of policy implementation is, moreover,
linked to the types of relationships between actors at dif-
ferent levels, with some policies being entirely rejected
by implementers at the periphery. The bottom up pers-
pective, thus, suggests that implementation management
should allow for the involvement and interaction of a
variety of actors in the implementation process.
The facility component of IMCI specifically aims to
improve health worker practice, and relies on good uptake
of IMCI case management skills. Victora et al. (2004)
argue that strategies like IMCI require close management
of health workers [32]. Results from our study have,
however, shown that health worker performance has not
been assessed regularly as minimal IMCI-focused super-
vision takes place, partly due to the lack of a supervisory
checklist incorporating IMCI. Consequently, IMCI case
management observations are almost never conducted,
and district managers may not be informed by health
workers of the challenges faced at facility level.
Poor information on health worker adherence to proto-
col is further exacerbated by the information asymmetry
which exists between district managers and health workers.
Moreover, IMNCI is a holistic approach to treatment
which focuses on health worker treatment and case man-
agement skills; therefore, it is inherently difficult to mo-
nitor adherence to protocol using simple monitoring indi-
cators, in contrast to other interventions, such vaccina-
tions, where implementation is more easily tracked through
routine records.
The issue of information asymmetry is a factor influ-
encing relationships between the national and district
levels. The health department is not able to monitor pre-
cisely the level of effort and supervision put into imp-
lementing IMCI by district managers and staff. Moreover,
many national level stakeholders lack a complete under-
standing of implementation difficulties happening on the
ground. One possible factor explaining the one-sided
flow of information is the organizational work culture
where information tends to flow mainly in a top-down
We have argued that asymmetry of information gives
health workers the opportunity to deviate from the pro-
tocol but this then begs the question—where health
workers have been trained on IMCI why are they choos-
ing to not implement the strategy?
A key reason is likely to be the increased workload
that IMCI adherence is perceived to produce. In addition,
on top of their daily clinical duties, health workers might
have other pressures in the workplace, such as adminis-
trative duties, which could explain non-adherence to the
guidelines. We can also postulate that health workers feel
that there is no clear, added benefit to them in adopting
IMCI skills: health workers are awarded certificates at
the end of training but there are no tangible benefits to
implementation in the form of career progression or re-
The situation may be similar for district managers,
especially those who have not been properly sensitized to
the strategy. In some cases, managers may fail to recog-
nize societal benefits of implementing IMCI, resulting in
minimal supervision of IMCI i mplementation at facilities.
Moreover, there are no direct incentives to encourage
good IMCI performance at the district lev el.
In addition to the impact on health worker and district
manager behavior, the lack of visibility of IMCI imple-
mentation means that routine data are not available on
the achievements of IMCI, in process or impact terms.
The lack of these data is reported to be one factor leading
to declined interest in providing IMCI funding. Collec-
ting it would have required additional studies, which
were not put in place, perhaps reflecting a lack of appre-
ciation of the importance of demonstrating impact.
The top down hierarchical use of power may lead to
poor communication of challenges and low motivation
which, in turn, leads to little or no problem-solving (a
form of non-decision-making), reflecting the lack of
policy ownership amongst IMNCI implementers.
Copyright © 2012 SciRes. IIM
Finally, limited facility autonomy in resource alloca-
tion has led to facilities having no capacity to replace es-
sential equipment, such as thermometers, or purchasing
recommended drugs during stock-outs. All of these inf-
luences may also be underpinned by street-level burea-
ucracy (SLB) behavior, as health workers respond to
their demanding environments by adopting coping mech-
anisms to manage workloads and challenge domination
from above.
5. Conclusions and Future Work
Although everyone recognizes that improving health sys-
tems is an important aspect of making health services
more responsive and more effective, people do not al-
ways agree about which interventions will produce these
results. Management systems convert the materials and
resources needed to carry out an implementation plan
(“inputs”, such as money, equipment, staff time, and
expertise) into activities (“outputs”, such as training pro-
grams, information, or behavior change communica-
tions). The management components key to program ef-
fectiveness is not independent and change in one of the
parameters may influence the other parameters too. The
health system relies on overlapping and interconnected
management systems and subsystems. Changes in one
system can trigger changes in another system—changes
that might go undetected until they cause trouble. For
example, moving an organization’s financial manage-
ment system onto computers might mean that financial
reports take less time to prepare and, therefore, might
lead to new responsibilities for staff or perhaps a reduc-
tion in accounting staff. In this instance, the human re-
source management system needs to be involved to sup-
port the changes in the financial management system.
Public health interventions tend to be complex, pro-
grammatic and context dependent. The evaluation of evi-
dence must distinguish between the fidelity of the eva-
luation process in detecting the success or failure of the
intervention, and relative success or failure of the inter-
vention itself. The evaluation of an intervention’s should
be matched to the stage of development of that inter-
vention. The evaluation should be also designed to detect
all the important effects of intervention and to encap-
sulate the interest of all the important stakeholders. We
advocate their incorporation into criteria for appraising
evidence on public health interventions. This can streng-
then the value of evidence and their potential contri-
butions to the process of public health management and
social development.
6. Acknowledgements
First of all, I sincerely want to thank my supervisor Dr.
Santosh Kumar for his gu idance, support and encour age-
ment. He gave me constructive criticism as well as re-
warding praises, which motivated and trained me to im-
prove the quality of my research. I would like to ack-
nowledge Professor S. C. Dwivedi for motivating and
guiding me to in completing this work.
I am thankful to my ex and current colleagues working
with Directorate of Medical and Health Services, Go-
vernment of Rajasthan and United Nations Fund for
Children for providing their insight and support in com-
pleting the thesis work. I would like to acknowledge my
supervisors for extending their support in completing th e
research work. I am thankful to all program managers,
consultants, trainers, auxiliary nurse midwifes and ASHAs
for actively participating in the research.
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