Indian Pediatr 2014;51: 136-138
Setting up a Quality Assurance Model for
Newborn Care to Strengthen Health System in Bihar, India
Sutapa B Neogi, *Ghanashyam Shetty, Shomik Ray, Projna Sadhukhan and
From Indian Institute of Public Health- Delhi, Public Health
Foundation of India and UNICEF, Bihar, India.
Correspondence to: Dr Sutapa B Neogi, Plot number 34,
Sector 44, Gurgaon, Haryana, India.
Received: April 03, 2013;
Initial review: May 30, 2013;
Accepted: September 05, 2013.
Published online: September 05, 2013.
Background: A Quality Assurance model was rolled out in Bihar,
India. It had two components: external and internal monitoring and
giving feedback for action. The parameters included infrastructure
and policy, equipment maintenance, stock supply and aseptic
measures. Methods: The performance and gradation into
good/average/poor was measured based on the scores translated from
the data collected after giving appropriate weights. Result:
12%, 63%, and 25% units were categorized as good, average and poor
based on infrastructure. For equipment, 68% of units performed
poorly; for stock maintenance 64% and 35% of NBCCs fell under good
and average categories respectively; most (54%) NBCCs had average
scores for aseptic measures; 30% fell in the poor category.
Conclusions: Involvement of government in monitoring and
feedback mechanism, establishing a system of data collection at the
grass root level and analysis at the state level were the positive
Keywords: Facility based, Health system,
Newborn care, Quality assurance.
In India, neonatal mortality constitutes one third
of infant deaths and 52% of all Under 5 deaths . Neonatal mortality
rate in India stands at 31 per 1000 live births. The rate has shown a
gradual decline but the decline is slower as compared to post- neonatal
rates. A great deal of variation is observed among the states. Few
states that contribute to the huge national burden are Madhya Pradesh
(44%), Odisha (42%), Uttar Pradesh (42%), Chhatisgarh (37%) and Bihar
The state of Bihar has a network of 8 Special Newborn
Care Units (SNCUs) and 463 Newborn care corners (NBCCs). Besides
strengthening the facility based care, it also strives to improve and
maintain the standards of performance of the units. With this objective,
a model on quality assurance (QA) was planned in the state. This
manuscript describes the model and gives the assessment at the baseline.
A model on quality assurance of newborn care units
encompassed quality assessment (based on periodic monitoring) and
quality improvement strategy (addressing the gaps identified during
External assessment comprised of periodic assessments
done every quarter by a pool of trained people from the government using
a structured questionnaire. The assessment covered the four basic
domains reflecting quality- infrastructure and policy, equipment, stock,
and aseptic measures. Internal assessment, on the other hand, was a
reflection of the practices of the staff.
The model covered the entire state over a period of
six months. During the process, data collection tools were finalized,
teams formed and training imparted. The team comprised of a mix of state
and district program managers, and UNICEF and PHFI team members.
A scoring mechanism was devised to grade the
performance with regard to each of the aspects.
Web Table 1
gives the scoring method used. Accordingly, NBCCs were graded into good,
average and poor/bad performing.
Statistical analysis software SPSS version 12 was
used to analyze the date. Collective indicators were developed based out
of the individual parameters that contributed to various aspects of
quality assessment. The districts were graded into good, average and
poor for each domain.
In addition, root cause analysis was done to examine
the reasons behind the gaps highlighted in the assessments. The main
purpose was to highlight the factors which might not be the direct
causes apparently but have significant contribution for the occurrence
of the situation.
The model was rolled out in two districts initially
but then scaled up across all the institutions over a period of six
months. The first quarter data (from 37 districts and 420 NBCCs) was
collected in the month of January 2012 and the second set (38 districts,
463 NBCCs) in April 2012. The data collection process continued for one
month. The findings bring out that majority of the units fared average
or poorly in specific domains.
For infrastructure, majority (63%) of the districts
were in the average category. Nearly 25% (94) had their NBCCs outside
the labor rooms that defeated the purpose of having one. Display of
protocols, clear admission and referral guidelines were absent.
Non-availability of vehicles, refusal by the families to take their
babies to higher level facilities and absence of financial support were
the additional root causes behind lack of implementation of a proper
The QA score for equipment and maintenance were
categorized as good or bad. In this case, absence of a local engineer,
and non-availability of all the 5 essential equipment in a functional
state labelled almost 68% (269) of districts as bad. Respondents opined
lack of required knowledge, frequent voltage fluctuation, absence of
backup support and irregular maintenance as the root causes.
The stock supply was good in most units (64%, 292).
Very few units (1%, 5 out of 463) had an erratic stock supply. The
deficit in the supply of color coded bins, needle cutters, soaps and
towels were the causes behind poor performance of 35% (159) of the
QA for aseptic measure was a composite measure that
had hand hygiene practices, housekeeping and cleanliness and biomedical
waste management as its components. Majority (84%) fared average or
badly. Inappropriate handwashing practices and biomedical waste
management largely led to poor performance. Absence of uniform supply of
materials and ignorance about the use of color coded bins were also some
of the reasons. Negligence, reluctance among sweepers, heavy workload of
ANMs led to poor housekeeping practices. Critical gaps identified were
poor biomedical waste management practices, lack of trained staff for
equipment audit/handling and absence of referral guidelines.
The proportion of missing data reduced, and quality
of data collection improved between the two surveys.
The analysis of QA for NBCCs indicates that most of
the units performed poorly on infrastructure and policy issues,
equipment maintenance and asepsis. The root cause analysis highlights
health system issues as the underlying factors behind poor performance.
External monitoring along with supportive supervision
has been a common strategy adopted in majority of quality assurance
models. Involvement of the government and teaming with the local NGO
partners has proved to be a successful approach in meeting the
The Equadorial health system experienced that
political support is required to inculcate continuous quality
improvement process in the system. Involvement of the Ministry and the
care providers, the nurses, the midwives had a proven outcome. The
success in terms of sustainability as well as integration with other
health programmes could happen with political support. The frequency of
monitoring; however, varies according to study settings and purpose. In
the proposed QA model for Bihar, quarterly monitoring has been chosen so
as to enable the care providers to gradually imbibe the quality
processes and other related activities leading to an improvement. The
approach has a resemblance with one of the quality assurance mechanisms
adopted in Gujarat for reproductive health . Yet, in another study,
monthly monitoring mechanism has been followed .
Involvement of the front level workers, particularly
from state and district levels has been a common feature of all the
models. For our model, commendable support was extended by the state
government and UNICEF that percolated to the local administrative level.
Involvement of government health officials for quarterly monitoring
remained very significant.
Internal monitoring formed another component in the
proposed model that aimed at self-monitoring and introspection among the
care providers. This component did not yield a positive outcome since
there was lack of self-motivation in filling up the forms. Also, people
complained about a lot of paper work and they found it difficult to
budget time out of their regular work schedule. There was also a problem
observed in handing over the filled in questionnaires, even though a
channel was designated. Documents suggest, that in most of the models,
the service providers have been involved that motivated staff to express
themselves and search for a local solution as per their need [3,4].
Several QA models have been tried out across the
globe. Few of them are COPE (client oriented, provider efficient
services), FFSDP (Fully functional service delivery point), Improvement
Collaborative, Improvement Newborn Health, PDQ (partnership defined
quality) and Quality Process Improvement [3-6]. Most of these models
have taken into consideration the community perspective and as well as
facility perspective at the designing stage itself. However, in the
proposed model we have considered facility level quality improvement
side only. It was holistic in nature. Periodic assessment and supportive
supervision was one of the key strengths of the suggested model.
Rolling out a model entails short improvement
reflections and then upscaling. This helps to take up the improvement
process in a phased manner and overcome shortcomings gradually.
All the models use service delivery standards as a
basis for improving quality; however, standards vary. Three models
started with a self-assessment tool that relies on and addresses
approved standards: COPE, Standards based management and recognition
(SBM-R), and the PSP-One QI Package [3-5]. In our model, internal and
external quality checks formed the two components, though internal
quality check did not prove to be a favored process during the first
year of its roll out.
To conclude, the QA model in Bihar was an attempt
towards improving and maintaining the standards of the health facilities
in providing neonatal care. Sustainability of the model can be commented
after a series of data are obtained for at least 5-6 quarters.
Involvement of government in monitoring and feedback mechanism,
establishing a system of data collection at the grass root level and
analysis at the state level were the positive outcomes. Besides,
intervention by proactive stakeholders will go a long way in improving
neonatal health in the state.
Acknowledgements: The authors acknowledge the
contribution of the In-charge of the hospitals and SCNUs in providing us
data, and the district coordinators and project officers of UNICEF who
helped us retrieve the data from secondary sources.
Contributors: All the authors have contributed,
designed and approved the study.
Funding: UNICEF; Competing interests: None
1. National Family Health Survey 3.2005-6.Indian
Institute of Population Sciences Mumbai. Available at: www.nfhs3.org
Accessed September 23, 2012.
2. Registrar General of India. Sample Registration
System. Annual Reports. New Delhi: Office of the Registrar General,
3. Khan ME, Mishra A, Sharma V, Varket LC.
Development of a Quality Assurance Procedure for Reproductive Health
Services for District Public Health Systems: Implementation and Scale-up
in the State of Gujarat. Population council, USAID, UNFPA. April 2008.
4. Hermida J, Robalino ME, Vaca L, Ayabaca P, Romero
P. Scaling up and institutionalizing continuous Quality improvement in
the free maternity and child care program in Ecuador. Available
from: http://www.hciproject.org/node/962 Accessed December 31,
5. Creel LC, Sass JV, Yinger NV. New perspectives of
quality of care-overview of quality of care in reproductive health:
definitions and measurements of quality. Population Council and
Population Refernece Bureau. Available from:
http://www.prb.org/pdf/NewPerspQOC-Overview.pdf. Accessed December 22,
6. Lantis K, Green CP, Joyce S. New perspectives on
quality of care: No. 3: Providers and quality of care. Population
Council and Population Refernece Bureau. Available from:
December 22, 2012.
7. Bradley J, Igras S, Shire A, DialloM, Matwale E,
Fofana F, et al. COPE for Child Health in Kenya and Guinea: An
Analysis of Service Quality. Engender health, USA. August 2002.
8. National Health and Nutrition Communication
Strategy 2008-2013. Islamic Republic of Afghanistan Ministry of Public
Health Afghanistan Public Health Institute Health Promotion Department,
March 2009. Available from:
Accessed December 31, 2012.
9. Lovich R, Rubardt M, Fagan D, Powers MB.
Partnership Defined Quality a tool book for community and health
provider collaboration for quality improvement. Save The Children, Jan
2003. Available from: http://www.savethe children.org/atf/cf/%7B9def2ebe-10ae-432c-9bd0-df91d2eba74a%7D/PDQ-Manual-Updated-Nigeria.pdf.
Accessed December 24, 2012.
10. Technical Report: Finding Common Ground:
Harmonizing the Application of Different Quality Improvement Models in
Maternal, Newborn, and Child Health Programs- October 2010 - United
States Agency for International Development.
11. COPE for Child Health. A process and tools for
improving the quality of child health services. AVSC International 1999.
12. Necochea E, Bossemeyer D. Standards based
management and recognition. A field guide. JHPIEGO, USA 2005.
13. Private health sector- Quality improvement
package for midwives and supervisors. USAID, PSP One. 2007. Available
from: pdf.usaid.gov/pdf_docs/PDACJ147.pdf. Accessed January 2, 2013.