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Global Health: Original Clinical Research Report

Newborn Resuscitation Skills in Health Care Providers at a Zambian Tertiary Center, and Comparison to World Health Organization Standards

Mistry, Sara C. MBBS*; Lin, Richard MBBS*; Mumphansha, Hazel MMed (Anesthesia); Kettley, Laura C. MBChB*; Pearson, Janaki A. MBChB*; Akrimi, Sonia MBBS*; Mayne, David J. MBBS; Hangoma, Wonder PGDip; Bould, M. Dylan MBChB, MEd†,‡

Author Information
doi: 10.1213/ANE.0000000000003337
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  • Question: What are the interprofessional standards of newborn resuscitation in a lower–middle income tertiary referral center?
  • Findings: There is a wide interprofessional variation in newborn resuscitation knowledge and skill with a similar standard seen between anesthesiologists and pediatricians and lower test scores attained by midwifery participants.
  • Meaning: There is a requirement for multidisciplinary training with clinical reenforcement to ensure best practice and prevent attrition of skill.


Inadequate respiratory effort at birth is a common phenomenon. Approximately 10% of all newborns require additional respiratory support at birth.1,2 Birth asphyxia is one of the most frequent causes of early death, accounting for approximately 23% of the 4 million neonatal deaths seen worldwide each year.3 Timely and appropriate basic interventions are key in preventing morbidity and mortality.4 However, data from the World Health Organization suggest that resuscitation is often not initiated or is not conducted in an appropriate manner.5 Reducing neonatal mortality is a priority for health care systems, especially in low- and middle-income countries. Zambia has seen a 41% reduction in neonatal mortality between 1990 and 2015.4 This profound improvement is a direct result of efforts to achieve the Millennium Development Goal 4A.6 Despite these encouraging statistics, 2015 data reveal that Zambia’s neonatal mortality rate is still 21 per 1000 live births,4 with nearly one third of deaths (32%) attributable to birth asphyxia and trauma.7

Rationale and Significance

Manasyan et al8 found that providing Essential Newborn Course training is a low-cost intervention that reduces death and disability in infants.9 This illustrates that basic, cost-effective, standardized interventions can improve neonatal outcomes.10 In Zambia, training midwives from low-risk, urban, community health clinics in neonatal care (Essential Newborn Course and the Neonatal Resuscitation Programme11 [NRP]) reduces early 7-day neonatal mortality.9 This includes newborn deaths attributable to birth asphyxia. Nationally, there are 109 obstetrician-run facilities in Zambia, of which 6 are classed as tertiary referral centers.12 The largest of these facilities is the University Teaching Hospital (UTH) in Lusaka, with approximately 18,000 deliveries annually. As a tertiary referral center, UTH attracts a large number of high-risk obstetric and neonatal cases. Currently, there are little data on the quality of newborn resuscitation in the context of a large tertiary center in a lower–middle income country.13 The provision of newborn resuscitation at UTH is from a diverse group of health care providers including midwives, physician anesthesiologists (including physician anesthesiology residents), and pediatric physicians (including those of resident grade). Ascertaining the skill base and knowledge of clinical practitioners is key to ensuring that those individuals are best equipped to offer appropriate and timely interventions.

Study Aims and Objectives

The goal of this study was to quantify the quality of newborn resuscitation in a high-risk tertiary referral hospital, specifically in a lower–middle income country. This was achieved using low–medium fidelity simulation. We hypothesized that newborn resuscitation skills would be superior in participants who had previously received formal training. We also aimed to compare the skills and knowledge of midwives, anesthetic, and pediatric residents.


Study Location

Written approval was sought and obtained from the University of Zambia Biomedical Research and Ethics Committee, and data were collected prospectively over a 5-month period between October 2016 and February 2017 at the UTH, Lusaka, Zambia. This manuscript adheres to the Standards for Quality Improvement Reporting Excellence (SQUIRE) 2.0 reporting guidelines.

Study Design

This is a cross-sectional observational study, conducted to inform future educational interventions.


Participants were recruited on a voluntary basis across the specialties of midwifery, anesthesia, and pediatrics. The anesthetic and pediatric participants were physician residents in their second and subsequent years. They were eligible for recruitment if their practice included resuscitating newborn babies without supervision. Those who were not expected to practice without immediate supervision, such as midwifery students, were not included in the study.

Although Zambia has over 70 indigenous languages, the official language of Zambia is English, which is also the default language of communication between health care professionals at UTH. We conducted the study in English and excluded any potential participants who were not fluent. We also note that the language of instruction in training programs for both medicine and midwifery at the University of Zambia is English. Candidates were provided with information sheets regarding the study and given prior notice to performing the assessment. Written informed consent was obtained before undertaking the assessments.


Assessors were trained over 1 day by the project lead (S.C.M.) in conducting standardized low–medium fidelity, simulation-based assessments. Participant performance was video recorded, and later rated using a standardized scoring system. The assessments were taken directly from the established resuscitation course, Helping Babies Breathe (HBB).14 An initiative of the American Academy of Pediatrics, the World Health Organization, and other global health care partners, HBB is an interactive, tutorial, and workshop-based course, with formalized end assessments. It has been shown to be highly cost-effective and, in countries such as Tanzania, has resulted in significant improvements in newborn mortality.15

Before commencing the assessments, background data were obtained from the participants, including qualifications, years in practice, and previous newborn resuscitation training (NRT). Type of resuscitation training course was not specified, though it needed to be formal and certified, such as the Newborn Resuscitation Program (NRP) or Advanced Paediatric Life Support. Candidates were also asked to describe their confidence (self-efficacy) in performing newborn resuscitation without supervision. This self-rated confidence scoring was assessed using a 0–10 Likert scale, with zero being no confidence and 10 being very highly confident.

Participants were then asked to complete 4 separate assessments in the following order:

  1. A short multiple-choice question (MCQ) paper, featuring 17 MCQs from the newborn resuscitation course, HBB.14 Questions focus on priorities of care, for example, preparing for the birth, management of the apneic newborn, and acceptable observations in a newborn baby. To pass this element of the assessment, candidates would be required to attain a score of ≥14. This standard is that dictated by the HBB course.
  2. A skills test requiring the candidate to demonstrate an appropriate bag-valve mask ventilation technique on a medium-fidelity manikin. The candidate needs to ventilate to an appropriate depth and also frequency. This assessment is scored out of 7 and requires full marks to pass, as dictated by the HBB guidelines14. If the candidate did not achieve full marks, the facilitator provided a short tutorial and ensured that the participant was adequately able to ventilate the mannequin before the further stages of the assessment.
  3. A simulation scenario requiring the participant to demonstrate appropriate, basic resuscitation techniques in an uncomplicated, term delivery. The candidate was required to appropriately prepare the environment and equipment for birth, assess breathing effort and efficacy, and provide appropriate basic interventions. This includes techniques such as head positioning, stimulation, and efforts to minimize hypothermia. All should be performed while ensuring a clean technique. The newborn would respond positively to these interventions (we will refer to this as the “responder” scenario). A score of 10 out of 13 is required to pass the scenario, as dictated by the HBB guidelines.14
  4. A simulation scenario requiring the participant to demonstrate appropriate basic resuscitation techniques in a complicated delivery, where the newborn did not respond to resuscitation interventions (we will refer to this as the “nonresponder” scenario). In this scenario, candidates are expected to prepare and care for a premature newborn, 34 weeks postconceptual age. The participant is expected to swiftly assess, recognize, and treat apnea, providing ventilation with a bag-valve mask. Along with parameters mentioned in the first scenario, time from birth to the provision of effective ventilation is assessed, examining adherence to the concept of the “Golden Minute” (effective ventilation established within 1 minute after birth). A score of 14 out of 18 is required to pass the scenario, as dictated by the HBB guidelines.14

In the ventilation skills test, responsive newborn, and unresponsive newborn scenarios, participant performance (including time to effective ventilation) was video recorded and later reviewed by 2 independent and appropriately trained raters (S.M., R.L., L.K., J.P., S.A., D.M.).

The primary outcome was the HBB checklist score in the nonresponder scenario. Secondary outcomes were the time taken to ventilate the newborn in the nonresponder scenario, the HBB checklist score for the responder scenario, the HBB checklist score for the ventilation skills test, the MCQ, and self-efficacy scoring.

Simulation Environment

Figure 1.
Figure 1.:
Standardized set up of equipment available to the participant during the assessments including a suction bulb, a self-inflating bag, a variety of facemasks, a towel, and a stethoscope.
Figure 2.
Figure 2.:
The NeoNatalie manikin (Laerdal, Stavenger, Norway).

The NeoNatalie manikin (Laerdal, Stavenger, Norway) was accompanied by a standardized set of equipment to assess candidates in the skills test and simulated scenarios (Figures 1–2). This manikin can be filled with water so that the simulated newborn is heavy and wet. The manikin can be dried, stimulated, ventilated, and the airway suctioned. The manikin comes with the facility to simulate both spontaneous ventilation and an arterial pulse (precordial and umbilical artery).

Statistical Analysis

The intraclass correlation coefficient was used to determine the interrater reliability of the 2 independent reviewers of the videos. The Mann-Whitney U test was used to compare the primary outcome and time to ventilate in participants who had previously received formal NRT and those who had not. The Kruskal-Wallis test compared the 3 professional groups for both the primary and secondary outcomes. The Dunn test was used for post hoc pairwise comparisons, and the reported P values from the Dunn test were divided by the number of comparisons.16 As a secondary, exploratory analysis, Spearman correlation coefficient was used to examine the relationship between confidence and performance in the unresponsive newborn simulation, as well as the relationship between years since NRT and performance in the unresponsive newborn simulation. Two comparisons were made for the primary outcome (the unresponsive newborn scenario): (1) participants trained in resuscitation versus those not trained and (2) evaluation of professional groups. For the secondary outcome measures (time to ventilate and checklist scores for the responsive newborn scenario), a Bonferroni correction was used to result in a P < .025 denoting significance. IBM SPSS Statistics software was used (Version 22; IBM, Armonk, NY).

Sample Size

In a previous study, Carlo et al3 found an improvement of simulation performance checklist scores from 43% to 88% immediately after training. In our cohort, we anticipated that there would be some attrition of skills after previous NRT. On the assumption that an improvement in simulation performance checklist scores from 43% to 55% would be educationally meaningful, we calculated that a sample size of 80 participants would be required.17 This percentage improvement in performance corresponded to 2 additional actions being performed on the simulation checklist. We considered this to be the minimal acceptable change in performance to justify the cost of training. The sample size was calculated to a power of 80% with a 2-tailed α of .05 and a minimum asymptotic relative efficiency of the parent distribution for a nonparametric pairwise comparison. We also aimed for a minimal recruitment of 80% of eligible staff within each of the 3 disciplines to ensure that our sample was representative of current practice.


Seventy-eight health care professionals completed the study (82% of the eligible cohort), including 13 anesthesia residents, 13 pediatric residents, and 52 midwives. Participant characteristics are summarized in the Table. The anesthesia participants were all of resident grade and were undertaking a Masters of Medicine in anesthesia. They had all satisfactorily achieved their Initial Assessment of Competency (a basic skillset mandated by the Royal College of Anaesthetists in the United Kingdom, allowing unsupervised practice in low-risk cases). The pediatricians were also all of resident grade and undertaking a Masters of Medicine in pediatrics. The anesthesia and pediatrics participants had all been in practice as doctors for a 2-year “intern” period before commencing specialty training. Midwifery participants were all postqualification and independent practitioners, delivering and resuscitating newborn babies. Fifteen of the participants (29%) qualified with a direct entry midwifery certificate, while the remaining 37 (71%) attained a nursing diploma with an additional midwifery certificate.

Participant Demographics

The average measures intraclass correlation coefficient of the video assessors were 0.91 (95% confidence intervals [CIs], 0.87–0.95) for the ventilation skills test, 0.96 (95% CI, 0.93–0.98) for the responsive newborn, and 0.95 (95% CI, 0.92–0.97) for the unresponsive newborn scenarios (P < .001 for each). Consequently, the mean score from the 2 reviewers was calculated and used for all further statistical analysis.

For our primary outcome, a Kruskal-Wallis test did not find a difference in the checklist score (out of 18) for the unresponsive newborn simulation, between participants with previous resuscitation training, 11 (7.9–13.8) as compared to those who had not had previous training, 12 (9.4–14.0) (P = .246). The checklist scores were 14.0 (13.0–14.75) for the anesthesia residents, 11.0 (8.5–12.3) for the pediatric residents, and 10.8 (8.3–13.9) for the midwives (Figure 3). A Kruskal-Wallis test found a significant difference between groups (P = .006). A post hoc Dunn test found a significant difference between the performance of anesthetic residents and midwives (P = .006), between anesthesia and pediatric residents (P = .029), but not between pediatric residents and midwives (P > .99). For those participants who had previously undertaken NRT, the number of years since training and performance in the unresponsive newborn simulation showed no significant evidence of correlation, Spearman coefficient = −0.13 (P = .55).

Figure 3.
Figure 3.:
Boxplot demonstrating the scores attained in the nonresponder newborn simulation scenario versus clinical specialty. The central bar represents the median, the box represents the interquartile range, and the whiskers represent the range. The dotted red line represents the preset pass mark of 14 out of 18.

The time to ventilate was no different in participants who had previously been trained in newborn resuscitation, 87 (61−107) seconds, compared to those who had not had previous training, 84.5 (57.3−120) (P = .677). Median ventilation times for all groups in the nonresponder scenario exceeded 1 minute; however, the midwifery cohort revealed the widest range in performance. The median (quartiles) time to ventilate was 61 seconds (37−97) for the anesthesia residents, 63 seconds (42.5−97.5) for the pediatric residents, and 93.5 seconds (66.3−129) for the midwives (Figure 4). A Kruskal-Wallis test found a significant difference between groups (P = .01), and a post hoc Dunn test found a significant difference between the performance of anesthesia residents and midwives (P = .027), but no significant evidence of correlation between anesthesia and pediatric residents (P > .99) or between pediatric residents and midwives (P = .124). Notes from the video raters indicated that the primary reason for delayed ventilation was premature and persistent suctioning of the airway, which prevented other steps in the resuscitation algorithm, as well as inappropriate measures for the prevention of hypothermia (such as placing socks) and showing the mother the sex of the baby.

Figure 4.
Figure 4.:
Boxplot illustrating time taken to provide effective ventilation (seconds) in the unresponsive newborn simulation scenario. The central bar represents the median, the box represents the interquartile range, and the whiskers represent the range. The dotted red line represents the gold standard of providing ventilatory breaths within 60 s.

The median (quartiles) checklist score (out of 13) for the responsive newborn simulation scenario was 9 (8.0−9.5) in anesthesia residents, 9 (7.5−10) in the pediatric residents, and 9 (7.5−10) in the midwives (P = .911). The median (quartiles) score for the ventilation skills test was 6 (4.5−6) in anesthesia residents, 4 (3.3−5.0) in pediatric residents, and 5 (3.5−6) for the midwives. Post hoc Dunn tests showed anesthesia residents performed significantly better than pediatric residents (P = .016) but not than midwives (P = .094), nor was there a difference between midwives and pediatric residents (P = .501). Failure to adequately check the correct functioning of the self-inflating bag-mask valve was the most commonly failed component of the ventilation skills test. The median score (quartiles) for the MCQ was 15.7 (15.5−16) for anesthesia residents, 16.0 (15−17) for pediatric residents, and 16 (15−17) for midwives (P = .851).

Self-rated confidence in performing newborn resuscitation was 6 (5.5−7.5) in anesthesia residents, 6 (5−7) in pediatric residents, and 6 (5−8) in the midwives (P = .889). There was no significant evidence of correlation between confidence level and performance in the unresponsive newborn simulation, Spearman coefficient = 0.06 (P = .55).


This study included 78 participants from different specialties, all of whom undertake newborn resuscitation in their clinical practice. Previous resuscitation training did not improve performance in a simulated scenario. A significant difference in performance was observed among the different health care providers. On average, anesthetics residents performed better on all assessments excluding the multiple-choice questionnaire, and they were the only group with a median score above the predetermined pass mark of 14 out of 18 for our primary outcome. Pediatric residents obtained, on average, better results than the midwifery participants; however, both groups failed to achieve the minimum required pass mark indicating safe practice. Self-efficacy scores were uniform between groups. An exploratory secondary analysis suggests that self-efficacy scores had no correlation to performance. This may suggest a lack of insight into knowledge gaps and inadequate performance although we note that this study was not powered for this secondary analysis.

Our research outcomes suggest likely suboptimal care of newborn babies. Of particular concern, the provision of ventilation in an apneic newborn was delayed in most of the midwifery participants. Midwives are responsible for the majority of newborn resuscitation at UTH, especially in an out-of-operating-theater environment. Anesthesiologists and pediatricians are seldom present at delivery, featuring only if there is an operative intervention, or an anticipated need for resuscitation. This is the minority of cases. Our findings mirror those of Carlo et al.3 In this study, evaluation of Zambian midwives from low-risk, urban delivery clinics found that pretraining knowledge and skills were low, coupled with high self-rating scores. Similar to our study, this was despite previous advanced formal education, training, and experience.3 Additionally, it should be noted that pediatric residents are commonly only involved in complex, high-risk cases. The pediatric median checklist scores in the unresponsive newborn simulation scenario were less than our predetermined pass mark of 14, indicating that a multidisciplinary training intervention would be beneficial to all groups.

Suboptimal resuscitation is a challenge faced by similar lower–middle income countries, such as Kenya and Ethiopia.13,18,19 A study by Murila et al18 formatively assessed professionals from a medical and nursing background in newborn resuscitation. This was achieved using MCQs. Only 35.4% scored the minimum competency level with nursing staff performing worst. This was explained by a shorter duration of training and lack of postgraduate training opportunities.18 A study by Gebreegziabher et al19 in Ethiopia demonstrated similar findings. Despite a different methodology, all studies agree that a lack of regular updates and continual professional development within nursing and midwifery participants is contributory to poor resuscitation scores. Training is dependent on professional opportunities and, in the case of residents, their curriculum. Regular updates may be more accessible to those of resident grade, due to an emphasis on education. This highlights the need for continual professional development in those groups that are of nonresident status.

It is important to be mindful that the retention of skills and knowledge is often poor after a single, structured resuscitation course.20 Research relating to pulse oximeter training has indicated that despite the implementation of a learning program, there was little benefit in clinical outcome.21 It could be asked why there is an apparent difference between qualitative data indicating that learning has taken place, and quantitative clinical outcomes? Scott and McDougall22 suggest that training often focuses on “catastrophic events,” which seldom occur in clinical practice. Therefore, there is a lack of practical reenforcement, and consequently a decline in recall and skill base. This could be a feasible explanation as to why there was no correlation between previous NRT and subsequent simulation performance. We can hypothesize that resuscitation training would be best supported by an ongoing, multifocal “bundle” of learning, which may include clinical reenforcement, practical reminders in day-to-day practice (such as posters or debriefing sessions), competency-based assessment, as well as regular short simulation “boosters.” Albert et al23 found that the implementation of a logbook was particularly helpful in minimizing decline in knowledge and skill recall 8 months after training in pulse oximeter use. This bundle of learning support may also improve insight into performance by continual clinical reflection and comparison with best practice. Training in a multidisciplinary environment may also encourage interprofessional dialogue and learning opportunities.

Our study methodology has limitations. One could argue that simulation-based performance does not necessarily reflect actual clinical performance, especially if a participant has had minimal exposure to low-fidelity simulation training. Participants may have been taught newborn resuscitation in different formats (eg, Advanced Paediatric Life Support and NRP). If we had documented the type of training each participant had received before partaking in this study, a potential source of bias may have been identified. Although the assessment tools that were used within this study were taken directly from an established course, one could consider certain drawbacks associated with them. The multiple-choice questionnaires and simulated assessments attempted to assess basic knowledge and resuscitation skills of each participant. However, multiple-choice questionnaires with short numbers of items are known to poorly reflect the student’s actual knowledge. It should be emphasized that the correlation between the study results and clinical performance outcomes is unknown.

In conclusion, our study demonstrated that newborn resuscitation knowledge and skill at a large Zambian tertiary center are varied. Inadequate performance was seen among most participants. Midwives and pediatricians perform poorly when compared to anesthesia residents, which is of particular concern given that they are often the primary resuscitation providers. Previous training was not associated with the level of performance. To address this discrepancy, we suggest an interprofessional, simulation-based NRT program, appropriate for the local context. An excellent example would be the well-established and validated HBB course.15 Regular updates, clinical reenforcement, and simple, cost-effective techniques such as logbook implementation will promote retention of knowledge and skills and therefore best practice among professional groups.


The authors acknowledge the contribution of the following individuals and organizations. Dr B. U. Chirwa, MBChB, MPH, Senior Medical Superintendent, University Teaching Hospital, Lusaka, Zambia—project approval. Dr H. A. Blackwood, MBChB, BSc (Hons), DTHM, Honorary Clinical Fellow, Zambian Anaesthesia Development Programme, University Teaching Hospital, Lusaka, Zambia—data collection and project collaborator. Dr M. Zyambo, MBChB, Masters of Medicine (Anesthesia), University Teaching Hospital, Lusaka, Zambia—data collection and project collaborator.


Name: Sara C. Mistry, MBBS.

Contribution: This author helped lead the project, obtain research and ethics approval, and participate in data collection. This author was also the principal investigator and primary manuscript author.

Name: Richard Lin, MBBS.

Contribution: This author helped edit the manuscript and was the coprincipal investigator.

Name: Hazel Mumphansha, MMed (Anesthesia).

Contribution: This author helped with project design and helped edit the manuscript.

Name: Laura C. Kettley, MBChB.

Contribution: This author helped collect the data and edit the manuscript.

Name: Janaki A. Pearson, MBChB.

Contribution: This author helped collect the data and edit the manuscript.

Name: Sonia Akrimi, MBBS.

Contribution: This author helped collect the data and edit the manuscript.

Name: David J. Mayne, MBBS.

Contribution: This author helped collect the data and edit the manuscript.

Name: Wonder Hangoma, PGDip.

Contribution: This author helped collect the data and edit the manuscript.

Name: M. Dylan Bould, MBChB, MEd.

Contribution: This author helped with project design, analysis and editing of the manuscript, and was the primary supervisor of the project.

This manuscript was handled by: Angela Enright, MB, FRCPC.


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