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Year : 2022  |  Volume : 66  |  Issue : 2  |  Page : 176-181  

Effect of a quality improvement package on reducing newborn mortality from 26 to 14 in a Himalayan North Indian State

1 Associate Professor, Department of Pediatrics, Dr. RPG Medical College, Kangra, Himachal Pradesh, India
2 Associate Professor, Department of Pediatrics, Indira Gandhi Medical College, Shimla, Himachal Pradesh, India
3 Medical Student, Department of Pediatrics, MM Medical College, Solan, Himachal Pradesh, India
4 Medical Student, Department of Pediatrics, Indira Gandhi Medical College, Shimla, Himachal Pradesh, India

Date of Submission07-Aug-2021
Date of Decision02-Feb-2022
Date of Acceptance16-Feb-2022
Date of Web Publication12-Jul-2022

Correspondence Address:
Seema Sharma
Department of Pediatrics, Dr. RPG Medical College, Kangra - 171 001, Himachal Pradesh
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijph.ijph_1647_21

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Background: In India, newborn mortality remains high due to a number of factors, including poor quality of care at health facilities. The experience of executing complete neonatal care quality improvement (QI) package at selected hospitals in Himachal Pradesh and reduction in newborn mortality rate (NMR) is described in this study. Objective: The short-term objective was the participants' retention of knowledge and skills, and the achievement of uniform QI objectives following training and after a minimum of 6 months. Overall reduction in NMR was long-term objective. Methods: Newborn care QI package was implemented according to India Newborn Action Plan over a period of 48 months from 2013 to 2016, through infrastructure, trainings, and supportive supervision. Results: Total 13 health facilities were upgraded; 350 staff nurses and medical officers were trained. The mean posttraining knowledge score was 75% compared to 29% in the pretraining test, and 63% 1 year later. The competencies of health workers in the care of high-risk babies and 12 QI targets had improved, resulting in a 46% reduction in neonatal mortality in the state across all gestations and weights based on sample registration survey. Conclusion: Implementation of a bundle of evidence-based practices in low-resource setting for health system strengthening for intrapartum and neonatal care was linked to changed care behaviors among health-care providers, and reduction in NMR.

Keywords: Capacity building, health system strengthening, infant mortality, newborn care, quality improvement

How to cite this article:
Sharma S, Sood M, Sharma K, Sood I. Effect of a quality improvement package on reducing newborn mortality from 26 to 14 in a Himalayan North Indian State. Indian J Public Health 2022;66:176-81

How to cite this URL:
Sharma S, Sood M, Sharma K, Sood I. Effect of a quality improvement package on reducing newborn mortality from 26 to 14 in a Himalayan North Indian State. Indian J Public Health [serial online] 2022 [cited 2022 Aug 16];66:176-81. Available from:

   Introduction Top

India has witnessed dramatic reduction in maternal and child mortality rates over the past two decades. However, in comparison to postneonatal deaths, neonatal deaths have not decreased significantly, thereby increasing the contribution of neonatal deaths to under-five deaths from 41% in 1990 to 56% in 2012,[1]and major contribution to more than 1 million under-five deaths in India in 2017.[2] The newborn mortality rate (NMR) is not the same anywhere in the country. While the state of Kerala has attained single-digit NMR (7/1000 live births), Odisha, Madhya Pradesh, Uttar Pradesh, Rajasthan, and Chhattisgarh have a higher NMR (≥30/1000 live births).[3] According to the sample registration survey (SRS) 2013, Himachal Pradesh, a Himalayan state in North India with a population of 70 lakhs has infant mortality rate of 35, and an newborn mortality rate of 26 per 1000 live births.[3]An estimated 19% of all live births have low birth weight and 11.2% born preterm.[4] Many among them do not survive even their 1st day of life. Institutional deliveries are taken by staff nurses and midwives, on an average two to three of them covering each shift.[5]

Substandard neonatal care at health facilities continues to be a factor for poor newborn outcome.[1] Efforts to implement the India Newborn Action Plan (INAP) in accordance with the sustainable development goals to increasingly address reduction in NMR by implementing evidence-based practices during the intrapartum and immediate neonatal period should be encouraged. The health department frames policies to improve newborn survival by strengthening health systems, making proven but underused solutions available to every mother and newborn including training and equipping health-care providers (HCPs) with skills, exempting pregnant women and sick infants from all user fees. To combat the major causes of newborn death with focus on sick and small newborn, there are low-cost interventions including appropriate use of antenatal corticosteroids, stimulation and resuscitation, essential newborn care including Kangaroo mother care (KMC), and management of neonatal sepsis. The uptake of these evidence-based practices is low; hospitals lack infrastructure, equipment, drugs, supplies, and protocols for newborn care, and the majority of health workers lack knowledge and skills to care for vulnerable neonates.[6] An increase in demand for services would not necessarily save lives without commensurate improvements in health facility quality.[1]

We hypothesized that key to NMR reduction is implementation of these interventions together, rather than individually for improved quality of care.[6]


The rationale of this study was to see how a complete neonatal care quality improvement (QI) package affected NMR in HP. The process of building health systems in HP, in order to improve the quality of care at 13 different health institutions, is described. The short-term objective was the participants' retention of knowledge and skills following training and after a minimum of 6 months, as well as the achievement of uniform QI objectives at selected health institutes within that time. A long-term goal was to reduce neonatal mortality rates across all gestational ages and birth weights.

   Materials and Methods Top

Study design

This was an implementation research study to access the impact of QI package as has been envisaged in INAP on reducing newborn mortality [Figure 1].
Figure 1: Study design

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Thirteen hospitals, which together catered to 70% of the total institutional deliveries within HP, were selected and both sick newborn care unit (SNCU) and labor room (LR) were established/upgraded. The various phases of this study were conducted over a period of 48 months from 2013 to 2016, including infrastructure development and workforce recruitment. Other than staff employed for LR and SNCU, no additional HCPs were hired during the study period.

India's Sample Registration System (SRS) is the primary source of information on fertility and mortality statistics at both the state and national levels. It has a large sample size and is distributed geographically in most districts; additionally, the system has the unique feature of dual recording, namely continuous enumeration and retrospective half-yearly community surveys. SRS ensures the completeness of the events of birth and death by matching the two records and then field verifying unmatched and partially matched events.[3] The SRS data were used for the purpose of documentation in NMR change within state.

PHASE I: Implementation

Establishment of sick newborn care unit

Sensitization workshops with state and district health officials were arranged to stress the importance of maternal and neonatal care. National Health Mission established 13 fully equipped SNCU in the health facilities with annual delivery load of more than 1000 in 2013–2014 as part of health system infrastructure strengthening. This was followed by workforce (staff nurse) recruitment for SNCUs.

PHASE II: Research

Skill building

Facility-based newborn care (FBNC) training package was implemented by the Ministry of Health and Family Welfare to the Government of India in 2013. Following the national training of trainers, cascade trainings were conducted at state and district levels.[7] FBNC consisted of four days of classroom training for nurses and medical officers, primarily in the form of small group discussions with demonstrations. Each participant took part in repeated practice while the facilitator used the skill checklist as a reference. It was followed by hands-on skill learning for 2 weeks in the newborn unit of two medical colleges of the state under the supervision of the facilitators, where trainees were allowed to practice all the skills taught in the initial 4 days.[8] At the end, all the participants were invited to share feedback in a supportive way. Concept of QI was simultaneously taught with all its components, including team building, framing of smart objectives, work around analysis using fishbone tool, 5 WHYs, dynamics of PDSA cycles, and the most important sustainability phase.[9]

All participants' knowledge of critical newborn care, breastfeeding, and resuscitation was assessed using precoaching multiple-choice questions (MCQs).[8] For skill assessment, any of the seven simulated case scenarios was randomly allotted to each participant in all groups. These scenarios were prepared on prebirth preparation, essential newborn care, birth of crying neonate, birth of noncrying neonate, postresuscitation care, breastfeeding, and admission of sick neonate inside SNCU. All seven skill scenarios were marked using OSCE, and total scores were calculated for each skill which were averaged to give a mean score to each group. Both written test and scenarios were carried out in a room setup for the purpose under examination conditions. Baseline scores were recorded (pretest). This was compared with MCQ and skill assessment posttest immediately at the end training (posttest I). During the supervisory visit, another MCQ and skill assessment posttest test was conducted to ensure that information and skills were retained (posttest II).

Establishment of quality improvement teams

In all 13 hospitals, QI teams comprising of local champions were established, with the goal of providing quality care in the areas of birth, infection prevention in LRs and SNCUs, encouraging the use of partograph, antenatal corticosteroids in preterm labour, neonatal resuscitation, sick newborn care, and KMC. Maternal and perinatal death review committees were established. Maternal and perinatal mortality audit forms, indoor patient charts, and registers approved by the Ministry of Health were reintroduced to standardize record-keeping and to facilitate data availability for the audit sessions.[10],[11] At each SNCU treatment, feeding, monitoring, and discharge protocols were designed and displayed.[12] Twelve QI objectives were selected. The QI coaches advised the care providers on the completeness and accuracy of the data collected on a regular basis. The final data were entered into the Health Management Information System and used in quarterly evaluations by local and state authorities for quality assurance.[13]

Supervisory visits

Supervisory visits were planned at each health facility after a minimum of 6 months posttraining to assess the progress in quality of care, mentor QI teams, and document retention of HCP knowledge and abilities. Prior information about the date of visit to the facility was communicated telephonically and by E-mail to ensure maximum participants' availability. The facilitators in pairs visited the facilities, and most hospitals were visited within a median time of 14 months (range: 6–24 months). Both assessment (posttest II) and mentoring were done by the supervisory team at the contact point itself. Total 19 participants could not be tested for second posttest, 9 staff nurses were on maternity leave, 3 were on medical leave, 4 were out of station on day of supervisory visit, and the remaining 3 were transferred out to non-SNCU health facility.


For QI, baseline data were extracted for 6 months prior to the implementation. FBNC training written and skill assessment scores of participants were manually entered into MS excel, before analysis on Stata 13 software (StataCorp. 2013. Stata Statistical Software: College Station, TX: StataCorp LP.). Data were summarized with percentages for categorical values, or median and range for continuous variables. Difference between pretest and posttest was performed using t-test. Repeated measure ANOVA tested difference between all three tests' mean scores. Because anonymized data were utilized and a QI project was approved by the government to reduce NMR, the study qualified for a waiver of consent. As a result, no approval from the institute ethics committee was required.

   Results Top

A total of 350 participants split into 280 staff nurses and 70 medical officers were trained in 14 batches over 18-month period from January 2014 to June 2015 with the help of three facilitators. Each training session included 25 participants in the ratio of 20:5 nursing staff to medical officers. Forty percent (140/350) of health-care workers had worked in two or more health facilities in the last 5 years. Twenty-seven percent (95/350) of health-care staff had previously received newborn care training, but none of them had gotten a refresher or follow-up training. The median time between coaching and final evaluation (posttest II) was 14 months (range: 6–24).

Evaluation of written scores

There was a significant increase in written scores immediately following training. Mean written scores increased from 5.93 (± standard deviation [SD] 0.83) to 15.14 (± SD 0.77) (P < 0.001). At the time of the reassessment during supervisory visits, mean scores were 12.64 (± SD 0.84), a reduction of 2.5 from posttest I to posttest II. Overall, the mean MCQ-based written scores increased by 9.2, from 5.93 (± SD 0.83) to 12.64 (± SD 0.84) (P < 0.001). A repeated measure ANOVA test was applied on all 14 groups to examine the effect that three different time periods had on scores. Results showed that the time to training leads to statistically significant differences in scores (F = 580.48, P < 0.001) [Figure 2].
Figure 2: Training outcome

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Evaluation of skills

Skill assessment was also done thrice, i.e., before the training, immediate posttraining (posttest I), and once at the time of supervisory visits (posttest II). Mean skill assessment scores increased from 29 (± SD 4.16) to 89.2 (± SD 3.16) (P < 0.001) immediately posttraining (posttest 1). At the time of posttest II, mean scores were 81.5 (± SD 3.15), a reduction of 7.7 from posttest I. Overall, the skill scores increased by 52.5 (P < 0.001) after gap of 14 months (range 6–24). A repeated measure ANOVA test was applied on 14 groups to examine the effect that three different time periods had on scores. Results showed that the time to training leads to statistically significant differences in scores (F = 2955.17, P < 0.001) [Figure 2].

Training feedback

The structured feedback received from 87% of participants found the content in the FBNC program “just right.” Three percent found the course “a little too complicated,” 5% “a little simple,” and 5% “too simple.”

Impact of quality care implementation

The use of QI tools and PDSA cycles for each QI objective resulted in significant improvement in the health-care service quality and the availability of health information over the course of the implementation. The data became readily available and were sought by administrators and district leaders through the HMIS. The accuracy and completeness of data on partograph use,documentation of weight, feeding, and treatment in inpatient and outpatient registers, as well as individual patient charts documentation improved [Figure 3]. The data showed achievement of goals from baseline to post QI, with significant sustainability phase [Table 1].
Figure 3: A-L R Registers Data completion,B-SNCU Data completion,C-NB given STS for 1 hour after birth,D- Delayed cord clamping after birth,E-NB initiated on BF within 1 hour, F-NB received vitamin K within 24hrs, G-NB examined within 90 minute of birth,H- NB not breathing at birth, I-NB resuscitated using of bag & mask, J-NB for post resuscitation care, K-SNCU admissions following protocol,L-SNCU Staff Hand washing ,M- Neonatal Sepsis among Inborn babies, N-Hypothermia in LR babies

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Table 1: Quality improvement scores

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Impact on newborn mortality rate

SRS data from 2012, 2013, 2014, 2015, 2016, and 2017 showed NMR of 26, 25, 25, 19, 16, and 14, respectively. This showed a reduction of 38% in NMR from 26 to 14 over the period of 5 years from 2012 to 2016, which increased up to 46% during the sustainability period as per SRS 2017 NMR data.

   Discussion Top

More and more countries are implementing QI projects to improve health outcomes.[9] With the intention to reduce the NMR, a comprehensive newborn care QI package was implemented synergistically over a period of 2013 till 2016, to increase skilled delivery outcomes and promote behavior change for improved quality care. The study's efforts to strengthen health systems reflected the limited material input available within the current infrastructure. The package comprises LR and SNCU data quality improvement, a QI component, and a newborn simulation-based team training program to influence provider behaviour throughout labour, birth, and the newborn period across 13 health facilities.[14] When QI intervention is combined with improved skill and knowledge of HCPs, followed by administrative review meetings and supervisory visits by experts, the result is increased accountability, improved LR and SNCU data collection, better utilization of infrastructure, and resources for satisfactory institutional care outcome.

Initial phase challenge to convince administrators was overcome through preintervention data presentation on factors responsible for high infant mortality in state and emphasis on INAP package implementation in totality. Subsequently, infrastructure was upgraded including SNCUs and LRs in selected hospitals.[7]

Barrier to capacity building was accomplished with the use of an FBNC training package that included most aspects of essential newborn care as well as efficient management of sick and small newborns by staff nurses and medical officers.[8] The training model guaranteed that learning was a collaborative effort by maintaining a 5:1 staff-to-doctor ratio. Pretest and posttest I scores revealed a considerable improvement in knowledge and skills. Feedback from participants posttraining showed well acceptance. The retention in provider knowledge and skills over 1-year gap reflected the importance of continued mentoring and supportive supervision even after trainings, as also seen by Tosif et al.[15]

Addition of the QI package with well-defined QI objectives as training component, followed by formation of QI teams at each facility, resulted in improved care around birth and immediate newborn period synergistically. Furthermore, the practical approach of working within real-world strengths and constraints suggested that this intervention might be scaled up in similar contexts without a major investment in neonatal care technologies. A study by Singh et al. in Ghana[16] showed maternal and child health improved with QI in low- and middle-income countries.

We used a QI approach to improve data quality around birth, and were successful to enter 90% of data from labor room and SNCU registers, which was similar to the BetterBirth trial, which used facility registers to analyze outcomes as part of a QI tool that encouraged systematic adherence to practices linked to better delivery outcomes,[17] data being acquired within the framework of an existing health system. Long-term evaluation of facility-based QI-focused projects that rely on government HMIS necessitates an investment in data systems,[13] on which workforce capacity development can be carried out if necessary. As a result, data from the SRS survey were utilized to corroborate the real drop in NMR over time, both during and after the implementation research.

A strategy involving infrastructure improvement, in-service training opportunities, effective team-based mentorship, formation of QI teams, and increased documentation has been the key to strengthen the capacity of the providers to care for vulnerable newborn babies.[18] Our success lies in synergistically implementing the entire package which spanned labor, delivery, and immediate newborn care to increase the awareness and consistent use of practices known to improve outcomes. We believe our intervention was successful in large part because we chose locally appropriate techniques that focused on provider knowledge and abilities, as well as identifying and overcoming shortcomings and bottlenecks in the delivery of vital quality care. Initially, factors such as misunderstanding the principles of QI, feeling overburdened with data collection, fear of being monitored or blamed for poor performance, or just an inertia to change were sometimes challenging, but over time, health facilities adopted QI into their daily operations, resulting in an overall improvement in the quality of services given and increase in the number of people seeking medical help with declined mortality.

Factors such as a lack of ambulances and other emergency transportation services, as well as equipment breakdowns, remained a challenge due to a lack of budgeting for maintenance and replacement, as well as competent administration. With an increasing number of pregnant women opting for institutional deliveries, it is critical to arrange for the continual supply of consumables and equipment in LRs and SNCU.

Limitation of our study was no comparison or control group. This implementation research was scaled up in all 13 health facilities at the same time, serving 70% of institutional delivery load. Over time, all these health facilities implemented the QI approach into their daily work, with overall improvement in NMR rates. This QI study revealed an overall improvement in quality of services offered to families, observed skills of HCPs, and a population-level decline in NMR, as measured by SRS. Furthermore, the pragmatic approach of working within the existing health system strengths and limitations demonstrates that this can be replicated in other nations and states without substantial investments in newborn care.

   Conclusion Top

Improving community knowledge and demand for newborn care services needs collaboration with health-care facilities to ensure that services are available and of appropriate quality. In this low-resource scenario, basic health system strengthening was possible, primarily with existing resources. The potential for replication in similar circumstances is demonstrated by alignment with the QI package and national standards for newborn health care. From the start, local leadership assistance is necessary, particularly in terms of enlisting key champions and getting buy-in from frontline health practitioners. Overcoming quality-of-care bottlenecks, on the other hand, is a significant issue, and resource-constrained settings require more imaginative solutions to save newborn babies' lives and help them thrive. Investment in current health-care and data systems is not only necessary for long-term capacity growth, but it also provides a unique platform for facility-based QI projects that rely on government HMIS.


We thank all the staff and leadership of health facilities for their active participation in the various components of the intervention.

Financial support and sponsorship

National Health Mission (NHM) Himachal Pradesh funded the infrastructure and human resource (staff nurse) of SNCU, FBNC trainings, supervision visits, and quarterly quality improvement meetings on data and maternal newborn care. NHM has no role in data collection, data analysis, data interpretation, or writing of article. The HCPs and local authorities were involved in implementation of activities based upon their roles and priorities.

Conflicts of interest

There are no conflicts of interest.

   References Top

India Newborn Action Plan (INAP): National Health Mission. Available from: [Last accessed on 2021 Jul 18].  Back to cited text no. 1
Burstein R, Henry NJ, Collison ML, Marczak LB, Sligar A, Watson S, et al. Mapping 123 million neonatal, infant and child deaths between 2000 and 2017. Nature 2019;574:353-8.  Back to cited text no. 2
Census of India Website: SRS Statistical Report. Available from: [Last accessed on 2021 Jul 18].  Back to cited text no. 3
Sood M. Institutional births analysis from labour room registries in North Indian hilly state. Int J Contemp Pediatr 2020;7:838-42.  Back to cited text no. 4
Himachal Pradesh | National Health Portal of India. Available from: [Last accessed on 2021 Jul 18].  Back to cited text no. 5
Bhutta ZA, Das JK, Bahl R, Lawn JE, Salam RA, Paul VK, et al. Can available interventions end preventable deaths in mothers, newborn babies, and stillbirths, and at what cost? Lancet 2014;384:347-70.  Back to cited text no. 6
National Institute of Health & Family Welfare. Available from: [Last accessed on 2021 Aug 03].  Back to cited text no. 7
Sachan R, Yadav R, Singh D, Shukla K. To evaluate the effectiveness of FBNC training programme in terms of knowledge of the participants in Uttar Pradesh. J Neonatol 2015;29:37-41.  Back to cited text no. 8
Point of Care Quality Improvement. [Last accessed on 2022 Jan 11].  Back to cited text no. 9
Maternal Death Review (MDR) | NHM. Available from: [Last accessed on 2021 Aug 05].  Back to cited text no. 10
LaQshya | National Health Systems Resource Centre | Technical Support Institute with National Health Mission. Available from: [Last accessed on 2021 Aug 06].  Back to cited text no. 11
SNCU Online. Available from: [Last accessed on 2021 Aug 05].  Back to cited text no. 12
HMIS-Health Management Information System. Available from:!/. [Last accessed on 2021 Aug 05].  Back to cited text no. 13
Mathur N. National rural health mission and reduction of neonatal mortality rate. J Neonatol 2005;19:196-7.  Back to cited text no. 14
Tosif S, Jatobatu A, Maepioh A, Gray A, Sobel H, Mannava P, et al. Healthcare worker knowledge and skills following coaching in WHO early essential newborn care program in the Solomon Islands: A prospective multi-site cohort study. BMC Pregnancy Childbirth 2020;20:84-92.  Back to cited text no. 15
Singh K, Brodish P, Speizer I, Barker P, Amenga-Etego I, Dasoberi I, et al. Can a quality improvement project impact maternal and child health outcomes at scale in northern Ghana? Heal Res Policy Syst 2016;14:45-57.  Back to cited text no. 16
Semrau KE, Hirschhorn LR, Marx Delaney M, Singh VP, Saurastri R, Sharma N, et al. Outcomes of a coaching-based WHO safe childbirth checklist program in India. N Engl J Med 2017;377:2313-24.  Back to cited text no. 17
Walker D, Otieno P, Butrick E, Namazzi G, Achola K, Merai R, et al. Effect of a quality improvement package for intrapartum and immediate newborn care on fresh stillbirth and neonatal mortality among preterm and low-birthweight babies in Kenya and Uganda: A cluster-randomised facility-based trial. Lancet Glob Health 2020;8:e1061-70.  Back to cited text no. 18


  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]


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