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Implementation of a quality improvement initiative for standardising essential newborn care in a teaching public hospital in rural central India
  1. Manish Jain1,
  2. Payal Meshram2,
  3. Akash Bang3,
  4. Varsha Chauhan2,
  5. Vikram Datta4,5,
  6. Ramasubbareddy Dhanireddy6
  1. 1 Pediatrics, MGIMS, Wardha, Maharashtra, India
  2. 2 Paediatric, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Maharashtra, India
  3. 3 Pediatrics, All India Institute of Medical Sciences, Nagpur, Maharashtra, India
  4. 4 Neonatology, Kalawati Saran Children's Hospital, New Delhi, India
  5. 5 Neonatology, Lady Hardinge Medical College, New Delhi, India
  6. 6 Pediatrics, The University of Tennessee Health Science Center, Memphis, Tennessee, USA
  1. Correspondence to Professor Manish Jain; manish{at}


Objective Our aim was to refine the essential newborn care practices by employing the multidisciplinary peer team-led quality improvement (QI) projects.

Design In 2017, concerning the same, the department focused on early initiation of breast feeding, prevention of hypothermia within an hour of life and rational usage of antibiotics among babies admitted to neonatal intensive care unit (NICU). Baseline data reported the rate of initiation of breast feeding, hypothermia and antibiotic exposure rate as 35%, 78% and 75%, respectively. Root causes were analysed and a series of Plan-Do-Study-Act cycles were conducted to test the changes. The process of change was studied through run charts (whereas control charts were used for study purpose).

Result After the implementation of the QI projects, the rate of initiation of breast feeding was found to be improved and sustained from 35% to 90%, the incidence of hypothermia got reduced from 78% to 10% and the antibiotic exposure rate declined from 75% to 40%. Along with the improvement in indicators related to essential newborn care, down the stream we found a decrease in the percentage of culture-positive sepsis rate in the NICU.

Conclusion Peer team-led QI initiatives in a resource-limited setting proved beneficial in improving essential newborn care practices.

  • Evidence-Based Practice
  • Healthcare quality improvement
  • PDSA

Data availability statement

Data are available on reasonable request.

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  • Quality improvement (QI) model is a systematic, formal approach to the analysis of practice, performance and efforts to improve performance.


  • This project highlighted the role of QI in refining the essential newborn care practices in a resource-limited settings.

  • Instituted a way towards antibiotic stewardship.

  • Emphasised on the role of stakeholders as a team and internal resources in improvement.


  • This project presented a simple, sustainable, rationale and reproducible model.

  • Replicating the same, across the country or developing world will help in standardisation of processes and practices to achieve predictable outcome and improvement in healthcare system and organisation.


Problem statement

Globally children who die within the first 28 days of birth mainly suffer from conditions related to inadequate care at and around birth or in the first few days of life.1 Ours is a rural tertiary medical college and hospital in central India which caters approximately 5000–6000 deliveries and 500 neonatal intensive care unit (NICU) admissions annually. The hospital provides round-the-clock emergency obstetrics and newborn care services, with inadequate essential newborn care.

The Nationwide Quality of Care Network team, in 2017, presented a simple model of quality improvement (QI). A formal training was given by them to a team of doctors and nurses and promised mentoring for QI projects.

Essential newborn care such as thermal protection, early and exclusive breast feeding, care of cord and skin, immunisation has a role in the prevention of neonatal mortality.1

The routine we followed immediately after birth is cleaning and draping the baby in the clothes provided by relatives and handling them for weighing, injection vitamin K and footprints to NICU on the first floor. Until the mother is shifted from labour room or operation theatre (OT), the baby is managed by relatives in the corridor. Breast feeding and rooming in was done after shifting mother, which was mostly delayed during busy days. The average time for initiation of breast feeding during day was found to be 1 hour and 36 min for vaginal delivery and 4 hours 20 min for caesarean section. During night hours, the average time of initiation of breast feeding was 3 hours 25 min for vaginal delivery and 5 hours 45 min for caesarean section. Hence, the documented baseline rate of early initiation of breast feeding in an hour was found to be 35% and percentage of hypothermia at 1 hour was found to be 78%. Antibiotic stewardship was introduced by neonatologist during their visit to our setting. Prior to that antibiotics were considered for all the neonates admitted to NICU, moreover, escalation and stoppage of antibiotics was a subjective phenomena. The antibiotic exposure rate documented during that period was 75%.

With this premise, department of paediatrics planned QI projects to improve essential newborn services such as early initiation of breast feeding, thermoregulation, implementation of evidence-based practices and rational antibiotic usage.


Globally 2.4 million neonatal deaths have been documented in 2019, a substantial declined from 5 million reported in 1990. There are approximately 6700 newborn deaths recorded every day, amounting to 47% of all child deaths under the age of 5 years.1 In Southern Asia, the proportion of neonatal deaths is among the highest 62% despite a relatively high under-5 mortality rate.1 Analysis of a large cohort of almost 100 000 newborns from three large trials conducted in India, Ghana and Tanzania has shown that the risk of neonatal death was 41% and 79% higher among children in whom breast feeding was initiated between 2–23 hours and 24–96 hours after birth, respectively.2–4 Neonatal hypothermia was also found to be associated with a fivefold higher mortality during the first 5 days of life.5 6 Previous studies have revealed that every 1°C decrement of neonate’s body temperature increases the mortality risk by 80%.5–8 The antimicrobial agents are prescribed frequently, either for prophylaxis or treatment of infections in NICU. The dangers of antimicrobial resistance are greatest with inadequate facilities.9 Estimates indicate that 56 524 neonates die each year from resistance-attributable neonatal sepsis, caused by bacteria resistant to first-line antibiotics in India.9 10 As more than half, that is, 53% of infections were associated with these three pathogens (Klebsiella spp, Acinetobacter spp and Escherichia coli). 181 (82%) of 222 infections caused by Acinetobacter spp were multidrug-resistant, confirming pan resistant untreatable Acinetobacter spp infections associated with high mortality in neonatal nurseries, a subcontinental-wide problem.9 11 WHO responded to the call by investing in strengthening care and improving the quality of mother and baby care around birth or with in first few days of birth. It also promoted the participation of parents, families and communities in demanding quality care for newborn.12 Hence, it is important to find the existing barriers and facilitators to design and deliver effective strategies to improve the practice and accelerate progress in newborn survival.

The aim was to improve essential neonatal care by using multidisciplinary peer team-led QI projects.

Our objectives were (1) improving initiation of breast feeding within an hour up to 100%; (2) decreasing the percentage of hypothermia at 1 hour after birth to zero and (3) reduction of antibiotic exposure rates to 30% over a period of 5 months.


We did a baseline assessment of the existing system by documenting the time of initiation of breast feeding and the temperature of the baby at 1 hour of birth. Similarly, antibiotic usage was determined by the number of babies on antibiotics at a particular time, that is, point prevalence and the duration of antibiotics per baby. The data obtained were compiled, entered and analysed to determine the baseline percentage of initiation of breast feeding in an hour, percentage of hypothermia at 1 hour and percentage of antibiotic exposure in NICU at a point of time. The baseline percentages were 35%, 78% and 75%, respectively. The indicators measured were (1) Percentage of breast feeding initiated within an hour=number of babies with breast feeding initiated within time/total live births×100; (2) Percentage of hypothermia at 1 hour of birth=number of babies with hypothermia/total live births×100 and (3) Percentage of antibiotic exposure in NICU at a point of time=number of babies on antibiotics/total number of babies in NICU at a point×100.

We decided to extend it to all shifts and cater babies born by both vaginal deliveries and caesarean sections. The impact of QI projects on neonatal mortality, rate of NICU admission and percentage of culture-positive sepsis in NICU were also studied.


Broadly the steps followed were as follows: (a) formation of team, (b) measurement of baseline data, (c) problem analysis using fishbone diagram, (d) Plan-Do-Study-Act (PDSA) cycles to test the change ideas and (e) study of impact using control charts. The team formed is composed of consultants, residents, nurses and data entry operator.


Three teams each of two residents, one consultant, two nursing staff (labour room and I NICU) were formed to analyse each issue and to come up with QI measures. The PDSAs were run accordingly and data were presented in weekly meets to the faculty. One data entry operator was recruited for daily entry of data in Excel sheet. The average time for initiation of breast feeding reported was 1 hour 36 min for vaginal deliveries and 4 hours 20 min for caesarean section. Root causes as shown in figure 1A for delay in initiation of breast feeding enlisted were deficient knowledge on Baby-friendly Hospital Initiative (BFHI) polices, lack of awareness among parents, unwarranted methods of care around birth, more emphasis on mothers’ comfort, documentation and scarcity of dedicated staff. The ideas generated by discussion with staff were tested through PDSA cycles for the implementation (table 1 (intervention 1)) and figure 2A. PDSA I: Healthcare providers (doctors and nursing staff (labour room and postnatal care wards)) were sensitised to BFHI measures through focus group discussions and policy dissemination by the team members.

Figure 1

Fishbone diagram. (A) Fishbone bone diagram for root cause analysis of delayed initiation of breast feeding; (B) fishbone diagram for root cause analysis of hypothermia; (C) fishbone diagram for root cause analysis on high antibiotic usage. AC vent, Air conditioner vent; BFHI, Baby-friendly Hospital Initiative; NICU, neonatal intensive care unit; Inj vit K, Injection Vitamin K.

Figure 2

Control charts on indicators: (A) percentage of newborn breastfeed within 1 hour after birth; (B) percentage of newborn with hypothermia 1 hour after birth; (C) percentage of newborn exposed to antibiotics at a point of time. PDSA, Plan-Do-Study-Act.

Table 1

PDSA cycles of all project (kindly refer to the methodology section of manuscript for the details of PDSA cvcles)

This was carried out weekly for a month. Posters, audio visuals were displayed for parents and relatives in outpatient unit and outside labour room. PDSA II: Evidence-based practices such as putting baby on mother’s abdomen for breast feeding, skin-to-skin contact and delayed cord clamping were promoted. These were explained and demonstrated to the nursing staff in labour room by the team members. The process was monitored by sister in charge of labour room and feedback was also taken from the mother. After the first two PDSA cycles, the rate of initiation of breast feeding in an hour reported to be 33%, which was noted due to improved reporting. This drop was attributed to low compliance of staff and early handover of baby to relatives for further process (figure 2A). Team focused on training staff for improvement. PDSA III: Weighing, injection vitamin k and foot print documentation were then shifted to newborn corner of Labor room (LR) from NICU. As labour room staff was unable to handle all the tasks simultaneously as they have to care for the mother also, a nursing staff was appointed for day shift. This curtailed the delay in rooming in and initiation of breast feeding. The rate improved to 50%. On analysis of the available data, team found that average time to latch baby on the breast for feeding in babies born by vaginal delivery at night was similar to babies born by caesarean—sections that is, 3 hours 25 min. At night, LR staff is less, due to which baby care was inadequately managed during busy nights. Hence team posted the intern nursing staff to LR for assisting the on-duty staff with baby care. PDSA IV: The interns were trained by LR and NICU staff in newborn care. Training the intern every fortnightly was not possible. Hence team requested the authorities for more staff. Similarly, the average time required for initiation of breast feeding in babies born by caesarean section was 4 hours 20 min in day and 5 hours 45 min at night-time. PDSA V: Team involved Operation theater staff, by requesting them to latch the babies in postoperation care unit. These two PDSA raised the initiation rate to 89%. However, it did not stay longer and dropped to 58% due to staff scarcity and fatigue. The labour room and OT nursing staff reported difficulty in managing and maintaining records during busy days and night shift and demanded for new staff. Recruitment of new staff was required as per the tremendous workload though improvement in indicators observed but not sustained due to severe shortage of staff compared with the patient load. Hence, we requested for staff to streamline the process efficiently. PDSA VI: After their training of 1 week, the newly appointed staff was posted in LR under three shifts. They were assisted by LR, OT staff and intern posted in NICU. The average time reported after implementing the changes was found to be 30 min for vaginal deliveries and 75 min for caesarean section.

The rate of early initiation of breast feeding peaked to 80% and sustained to 90% over a period of 1 year.

Similarly, our baseline survey showed 78% newborns were hypothermic (axillary temperature <36.5°C) at 1 hour of birth. Root causes as shown in figure 1B found were a lack of evidence-based practices (abdominal delivery, skin-to-skin contact, delayed cord clamping), cold delivery rooms with AC vents near newborn corner, emphasis on completion of documentation as mentioned above and inadequate nursing staff. The team tested each of the change ideas using PDSA cycles (table 1 (intervention 2) and figure 2B), which included PDSA I: Residents and nursing staff were sensitised on thermoregulation through focus group discussions by the team weekly for a period of month along with breastfeeding practices. PDSA II: Evidence-based practices such as abdominal delivery; delayed umbilical cord clamping; immediate drying, early skin-to-skin contact, using prewarm sheets were demonstrated by the team members and similarly feedbacks were taken from relatives and mothers. The percentage of babies having hypothermia was found to be increased to 87%, which was attributed to low compliance and increased reporting. Regular training and monitoring of the staff are done to improve the compliance. PDSA III: For further prevention from hypothermia, the newborn corner was set away from cooling vent, labour room temperature was regulated at 25°C and documentation was started in labour room. Early rooming in and latching was also facilitated. Only 20% were found to be hypothermic after introduction of these measures. The major delay was noted mainly at night due to less staff. PDSA IV: As mentioned earlier, intern nursing staff was also involved. PDSA V: Similarly, in postoperation care unit, two radiant warmers were shifted and use of prewarm sheets was ensured. This has dropped rate of hypothermia to 9.6% but it could not be sustained due to staff scarcity and fatigue. Hence, percentage of hypothermia reported in babies raised up to 43% PDSA VI: recruitment of new permanent staff smoothen the ongoing process. Specific focus on this subgroup for adherence to protocols resulted in overall hypothermia reduction from baseline 78% to 0%. Monitoring data over the next year showed a sustained reduction, upto 10% with occasional variations due to staff shuffling, or increased workload in postnatal wards. Such occasional variations are expected and normal. As mentioned earlier, in these two QI projects which we carried out simultaneously for improvising our essential newborn care, we introduced evidence-based measures, made changes at our settings, created awareness among staff but to sustain and streamline these changes we ended up with hiring of additional staff.

While we were witnessing improvement through QI projects, we headed to our third project. It started with the visit of neonatologist in march 2018, when he introduced the concept of antibiotic stewardship and encouraged us to work on it. In the departmental meet, team of consultant, residents and NICU nursing staff were formed. The baseline data collected on prevalence of antibiotic usage in NICU (75%) weres an eye-opener for us. Route causes as shown in figure 1C enlisted were lack of standard protocol for antibiotic usage, inappropriate universal aseptic measures, more turnaround time for report validation and lack of confidence among treating doctors. The ideas were tested through PDSA cycles to implement change (table interventions (3) and figure 2C). PDSA I: Formulation of policy of antibiotic usage depicting criteria for starting and stoppage of antibiotics, standard first and second-line antibiotics in accordance to culture sensitivity pattern by the head of department and team done. The policy was explained to all the consultants and residents posted in NICU by the team and advised to follow, which reduced antibiotic exposure to 73% and 3 median antibiotic days per baby.

PDSA II: An infection control nurse was appointed to reinforce aseptic practices such as handwashing. Daily sessions were conducted by the staff to emphasise on handwashing practices, swabs of equipment’s and staff were taken for bacterial culture weekly. A sudden drop to 30% was noted during this period due to low admission rate. PDSA III: Delay in validation of reports due to huge sample load and scarcity of staff in microbiology department was noticed by team, were tackled by tracing reports telephonically by residents at 72 hours to facilitate stoppage of antibiotics at 72 hours in culture with no growth. PDSA IV: Concern of consultants in streamlining antibiotics based on culture sensitivity pattern in babies responding to previous antibiotics was tackled by conducting session with medicine department antibiotic surveillance team weekly and channelised by regular reporting to the head of department. PDSA V: Prompt stoppage of antibiotics at 72 hours was found to be not followed by residents due to busy duties, hence it was streamlined by involving NICU nursing staff by entrusted responsibility of taking residents signature on order book for antibiotic continuation beyond 72 hours, as a reminder for residents to trace reports; though antibiotic exposure rate dropped to 40% with median of 1 day per baby. This impacted the work culture of NICU. PDSA VI: As team spirit is important in achieving any goal, confidence-building sessions were conducted to tackle these rapport issues. The team introduced a culture of fortnightly staff meet to deal with the issues of working staff. The median antibiotic days were reduced to zero with similar antibiotic exposure rate. Journey of redirecting from conventional practices towards antibiotic stewardship practice was difficult but we ultimately succeed.

Weekly audits were done by senior resident doctors and reported back to the team to ensure that all the interventions were being implemented.

Hence, we were able to introduce antibiotic stewardship, by merely streamlining the process and involving our entire NICU staff (consultants, residents and nursing staff) to sustain the changes.

Patient and public involvement

Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.


Data collected were compiled and coded regularly and plotted over time to see the trends of process and outcome indicators weekly. Control charts comprising x-axis and y-axis were used to study variability.


In the baseline survey, the percentage of breast feeding initiated within an hour was 35%, the percentage of hypothermia documented was 78% and antibiotic exposure rate was 75%. After six PDSA cycles, the rate of initiation of breast feeding improved from 35% to 80% over a period of 5 months. Similarly, the percentage of hypothermia reported within an hour of birth declined from 78% to 0% after six PDSA cycles over a period of 5 months. The antibiotic exposure rate also declined from 75% to 42% over a period of 5 months. The result was sustained even after the last PDSA cycle, without any additional resources.

The introduction of measures of essential newborn care also reported decline in neonatal mortality rate, newborn admission in NICU and percentage of culture-positive sepsis in newborn admitted to NICU along the period of time. The run charts were used to study the impact of changes over time, as easy to plot, but here we were representing the data using control charts. The lower confidence level, median and the upper confidence levels were plotted for all these measures. We also used the AnhQj rules to assess for special cause variation. Unusually long runs were calculated using the formula log2(n)+3log2(n)+3 while the unusually few crossings were calculated using the equation b(n—1, 0.5), where n is the number of observations and b is the lower prediction limit which are presented in the tables below with control charts. The figure 2A shows a control chart for the percentage of breast feeding initiated within 1 hour. The median percentage was found to be 64.00% with the lower confidence level of 49.8% and upper confidence level of 79.5%. The dots marked in red are falling beyond the limits of the control charts. The baseline assessment was lower than the lower limit of the confidence level while the endline assessment was higher than the upper limit of the confidence level. As per the AnhQj rules, there was special cause of variation in the data as the values for longest run remained higher than the longer run max for our data and the number of crossings was less than the crossings minimum value for our observations reporting significant improvement after PDSA cycles.

Figure 2B shows a control chart for percentage of hypothermia with median 22.06%, lower confidence level 10.73% and upper confidence level 33.39%. The baseline assessment was higher than the lower limit of the confidence level while the endline assessment was lower than the upper limit of the confidence level. The data values for longest run reported to be higher than the longest run max and the number of crossings was less than minimum value for our observation reporting significant improvement over a period of 5 months.

Figure 2C shows a control chart of point prevalence of antibiotic usage in admitted babies with median 50.3%, lower confidence level of 41.68% and upper confidence level of 58.93%. There was special cause of variation in the data as the longest run is higher than the longest run max and the crossing is lower than the crossing minimum, demonstrating significant improvement after the PDSA cycles.

Figure 3A shows a control chart of all cause mortality rate with median 19%, lower confidence level −2.47% and upper confidence level 41%. The baseline assessment was higher than the lower limit of the confidence level while the endline assessment was lower than the upper limit of the confidence level. There was no special cause of variation in the data as the lower run is lower than lower run max and the crossing is more than the crossing minimum.

Figure 3

Control charts on indirect indicators. (A) Percentage of births that required NICU admission; (B) percentage of NICU admission with culture-positive sepsis; (C) over all cause mortality among all birth. NICU, neonatal intensive care unit.

Figure 3B shows a control chart of total NICU admissions with median 10.09%, lower confidence level 4.86% and upper confidence level 15.32%. The baseline assessment was higher than the lower limit of the confidence level while the endline assessment was lower than the upper limit of the confidence level. The data as the longest run is slightly lower than longest run max and the crossing is slightly less than the crossing minimum hence depicts possibility of improvement.

The data on percentage of NICU admission with culture-positive sepsis when shown as control chart (figure 3C) had median 18.48%, lower confidence level 3.03% and upper confidence level 33.93%. The baseline assessment was higher than the lower confidence limit and lower than the upper confidence limit. There was a special cause of variation in the data as the longest run is more than the longest run max and the crossing is lower than the crossing mini, depicting improvement.

The staff confidence and involvement increased dramatically especially with the QI dashboard displaying the data trends and with the regular internal and external review


QI methods are being increasingly deployed in healthcare to support the delivery of high-quality patient care and improved patient outcomes. PDSA provides a structured experimental learning approach to test changes. In a tertiary care rural hospital, through QI projects we were able to improve and sustain the rate of initiation of breast feeding from 35% to 90%, reduced the incidence of hypothermia from 78% to 10% and decreased the antibiotic exposure rate from 75% to 20%. Percentage of culture-positive sepsis among NICU admitted was found to be declined due to QI measures. This was possible as we involved front-line staff right from the beginning and used scientific methods to diagnose the root causes, to deduce possible solutions and objective testing, which helped us to learn about the challenges of implementation. This helped us to adapt our approach to make it more acceptable and practically doable. Literature similar to our study: Two studies reported improvement in initiation of breast feeding from 12% to 80% and 55% to 95% through implementation of QI projects.13 14 Patodia et al in their QI study on reducing admission hypothermia in newborns at tertiary care NICU reported the preintervention incidence of hypothermia to be 82% which dropped to 45% over a period of 6 months.15 Similarly study reported decline in incidence of hypothermia from 39% to 0% over 8 weeks through three PDSA.16

Makri et al a QI reported reduction in antibiotic usage rate upto 43% (from 347 to 198 per 1000 patient days) which is similar to our study.17 Agarwal et al in their recent study reported decline in antibiotic usage rate upto 42% using QI.18 The lesson we learnt through QI projects was every problem can be solved by analysing the cause, searching for simple solutions, stepwise implementation of the solutions, analysing the performance and doing required modification. Involvement of all stakeholders is a key to success.

Limitations of study

Rotatory posting of the residents in NICU and postings of the nursing staff to different wards during epidemics were the major pitfalls for sustainability. The objective evaluation of the awareness measures and correctness of evidence-based practices was not possible.


This QI initiative was done involving the existing caregivers and was executed without any external funding. We described a successful sustainable approach to implement essential newborn care services. The simplicity of QI principles makes it reproducible in healthcare facilities across the country. To sustain positive result for longer time, we planned to extend the QI practice to postnatal unit to improve the exclusive breastfeeding rate, temperature regulation and usage of antibiotics. QI projects across country will help to highlight the common problems, possible solutions and implementation challenges. This will help policy-makers in formulation of sustainable measures benefiting neonatal outcome.

Data availability statement

Data are available on reasonable request.

Ethics statements

Patient consent for publication


We acknowledge Nationwide Quality of Care Network (NQOCN) as training body and mentoring quality improvement initiatives in the present intervention. We also acknowledge the neonatal intensive care unit staff nurses and resident doctors for supporting this initiative. We thank the secretary, dean and medical superintendent for providing us with infrastructure and technical support.



  • X @ManishJ51080713

  • Correction notice This article has been corrected since it was first published. Percentage of antibiotic usage has been corrected under the abstract.

  • Contributors MJ, AB and RD contributed to the conception and study design. MJ, AB, PM and VC contributed to the reviewing of the database, conducting the project, collection of data and writing the article. MJ, VD and RD critically reviewed the manuscript for accuracy and intellectual content. All authors approved the final version of the article. MJ responsible for the conduct of the studyas the guarantor.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Provenance and peer review Not commissioned; externally peer reviewed.