Vishwajeet Kumar

Effect of community-based behaviour change management on neonatal mortality in Shivgarh, Uttar Pradesh, India: a cluster-randomised controlled trial

BACKGROUND In rural India, most births take place in the home, where high-risk care practices are common. We developed an intervention of behaviour change management, with a focus on prevention of hypothermia, aimed at modifying practices and reducing neonatal mortality. METHODS We did a cluster-randomised controlled efficacy trial in Shivgarh, a rural area in Uttar Pradesh. 39 village administrative units (population 104,123) were allocated to one of three groups: a control group, which received the usual services of governmental and non-governmental organisations in the area; an intervention group, which received a preventive package of interventions for essential newborn care (birth preparedness, clean delivery and cord care, thermal care [including skin-to-skin care], breastfeeding promotion, and danger sign recognition); or another intervention group, which received the package of essential newborn care plus use of a liquid crystal hypothermia indicator (ThermoSpot). In the intervention clusters, community health workers delivered the packages via collective meetings and two antenatal and two postnatal household visitations. Outcome measures included changes in newborn-care practices and neonatal mortality rate compared with the control group. Analysis was by intention to treat. This study is registered as International Standard Randomised Control Trial, number NCT00198653. FINDINGS Improvements in birth preparedness, hygienic delivery, thermal care (including skin-to-skin care), umbilical cord care, skin care, and breastfeeding were seen in intervention arms. There was little change in care-seeking. Compared with controls, neonatal mortality rate was reduced by 54% in the essential newborn-care intervention (rate ratio 0.46 [95% CI 0.35-0.60], p<0.0001) and by 52% in the essential newborn care plus ThermoSpot arm (0.48 [95% CI 0.35-0.66], p<0.0001). INTERPRETATION A socioculturally contextualised, community-based intervention, targeted at high-risk newborn-care practices, can lead to substantial behavioural modification and reduction in neonatal mortality. This approach can be applied to behaviour change along the continuum of care, harmonise vertical interventions, and build community capacity for sustained development. FUNDING USAID and Save the Children-US through a grant from the Bill & Melinda Gates Foundation.

60 million non-facility births: Who can deliver in community settings to reduce intrapartum-related deaths?

For the worlds 60 million non‐facility births, addressing who is currently attending these births and what effect they have on birth outcomes is a key starting point toward improving care during childbirth.

Population Health Metrics Research Consortium gold standard verbal autopsy validation study: design, implementation, and development of analysis datasets

BackgroundVerbal autopsy methods are critically important for evaluating the leading causes of death in populations without adequate vital registration systems. With a myriad of analytical and data collection approaches, it is essential to create a high quality validation dataset from different populations to evaluate comparative method performance and make recommendations for future verbal autopsy implementation. This study was undertaken to compile a set of strictly defined gold standard deaths for which verbal autopsies were collected to validate the accuracy of different methods of verbal autopsy cause of death assignment.MethodsData collection was implemented in six sites in four countries: Andhra Pradesh, India; Bohol, Philippines; Dar es Salaam, Tanzania; Mexico City, Mexico; Pemba Island, Tanzania; and Uttar Pradesh, India. The Population Health Metrics Research Consortium (PHMRC) developed stringent diagnostic criteria including laboratory, pathology, and medical imaging findings to identify gold standard deaths in health facilities as well as an enhanced verbal autopsy instrument based on World Health Organization (WHO) standards. A cause list was constructed based on the WHO Global Burden of Disease estimates of the leading causes of death, potential to identify unique signs and symptoms, and the likely existence of sufficient medical technology to ascertain gold standard cases. Blinded verbal autopsies were collected on all gold standard deaths.ResultsOver 12,000 verbal autopsies on deaths with gold standard diagnoses were collected (7,836 adults, 2,075 children, 1,629 neonates, and 1,002 stillbirths). Difficulties in finding sufficient cases to meet gold standard criteria as well as problems with misclassification for certain causes meant that the target list of causes for analysis was reduced to 34 for adults, 21 for children, and 10 for neonates, excluding stillbirths. To ensure strict independence for the validation of methods and assessment of comparative performance, 500 test-train datasets were created from the universe of cases, covering a range of cause-specific compositions.ConclusionsThis unique, robust validation dataset will allow scholars to evaluate the performance of different verbal autopsy analytic methods as well as instrument design. This dataset can be used to inform the implementation of verbal autopsies to more reliably ascertain cause of death in national health information systems.

Using verbal autopsy to measure causes of death: the comparative performance of existing methods

BackgroundMonitoring progress with disease and injury reduction in many populations will require widespread use of verbal autopsy (VA). Multiple methods have been developed for assigning cause of death from a VA but their application is restricted by uncertainty about their reliability.MethodsWe investigated the validity of five automated VA methods for assigning cause of death: InterVA-4, Random Forest (RF), Simplified Symptom Pattern (SSP), Tariff method (Tariff), and King-Lu (KL), in addition to physician review of VA forms (PCVA), based on 12,535 cases from diverse populations for which the true cause of death had been reliably established. For adults, children, neonates and stillbirths, performance was assessed separately for individuals using sensitivity, specificity, Kappa, and chance-corrected concordance (CCC) and for populations using cause specific mortality fraction (CSMF) accuracy, with and without additional diagnostic information from prior contact with health services. A total of 500 train-test splits were used to ensure that results are robust to variation in the underlying cause of death distribution.ResultsThree automated diagnostic methods, Tariff, SSP, and RF, but not InterVA-4, performed better than physician review in all age groups, study sites, and for the majority of causes of death studied. For adults, CSMF accuracy ranged from 0.764 to 0.770, compared with 0.680 for PCVA and 0.625 for InterVA; CCC varied from 49.2% to 54.1%, compared with 42.2% for PCVA, and 23.8% for InterVA. For children, CSMF accuracy was 0.783 for Tariff, 0.678 for PCVA, and 0.520 for InterVA; CCC was 52.5% for Tariff, 44.5% for PCVA, and 30.3% for InterVA. For neonates, CSMF accuracy was 0.817 for Tariff, 0.719 for PCVA, and 0.629 for InterVA; CCC varied from 47.3% to 50.3% for the three automated methods, 29.3% for PCVA, and 19.4% for InterVA. The method with the highest sensitivity for a specific cause varied by cause.ConclusionsPhysician review of verbal autopsy questionnaires is less accurate than automated methods in determining both individual and population causes of death. Overall, Tariff performs as well or better than other methods and should be widely applied in routine mortality surveillance systems with poor cause of death certification practices.

Impact of an integrated nutrition and health programme on neonatal mortality in rural northern India

OBJECTIVE To assess the impact of the newborn health component of a large-scale community-based integrated nutrition and health programme. METHODS Using a quasi-experimental design, we evaluated a programme facilitated by a nongovernmental organization that was implemented by the Indian government within existing infrastructure in two rural districts of Uttar Pradesh, northern India. Mothers who had given birth in the 2 years preceding the surveys were interviewed during the baseline (n = 14 952) and endline (n = 13 826) surveys. The primary outcome measure was reduction of neonatal mortality. FINDINGS In the intervention district, the frequency of home visits by community-based workers increased during both antenatal (from 16% to 56%) and postnatal (from 3% to 39%) periods, as did frequency of maternal and newborn care practices. In the comparison district, no improvement in home visits was observed and the only notable behaviour change was that women had saved money for emergency medical treatment. Neonatal mortality rates remained unchanged in both districts when only an antenatal visit was received. However, neonates who received a postnatal home visit within 28 days of birth had 34% lower neonatal mortality (35.7 deaths per 1000 live births, 95% confidence interval, CI: 29.2-42.1) than those who received no postnatal visit (53.8 deaths per 1000 live births, 95% CI: 48.9-58.8), after adjusting for sociodemographic variables. Three-quarters of the mortality reduction was seen in those who were visited within the first 3 days after birth. The effect on mortality remained statistically significant when excluding babies who died on the day of birth. CONCLUSION The limited programme coverage did not enable an effect on neonatal mortality to be observed at the population level. A reduction in neonatal mortality rates in those receiving postnatal home visits shows potential for the programme to have an effect on neonatal deaths.

Behavior change for newborn survival in resource-poor community settings: bridging the gap between evidence and impact.

Despite an established evidence base of simple, affordable, and low-cost interventions to avert neonatal deaths, global progress in reducing neonatal mortality has stagnated in recent years. Under-recognition of the critical role played by behavior change in ensuring adoption and dissemination of innovations is a major reason for this gap between evidence and impact. A general lack of understanding of the mechanisms underlying behavior change at a population level coupled with an under-appreciation of the sociocultural context of newborn care behaviors has underscored ill-informed approaches towards behavior change that have met with limited success. This article draws upon available evidence from prevention-oriented, community-based newborn survival trials to derive insights into the role of behavior change in neonatal mortality reduction. We propose a simple model, the intervention-causation pathway, to explain the pathway through which behavior change interventions may lead to reductions in mortality. Further, we explore the unique nature of newborn care behaviors and their underlying sociocultural context, along with state-of-the-art advances in social, behavioral, and management sciences. These principles form the basis of the behavior change management framework that has successfully guided intervention design and implementation, leading to high impact on neonatal mortality reduction, in Uttar Pradesh, India. We describe how the behavior change management framework can be applied to inform the design of theoretically and empirically sound behavior change interventions with greater precision, predictability and pace towards reduction in neonatal mortality. We finally touch upon key overarching principles that should guide intervention execution for maximal impact.

Comparing modelled predictions of neonatal mortality impacts using LiST with observed results of community-based intervention trials in South Asia

Background There is an increasing body of evidence from trials suggesting that major reductions in neonatal mortality are possible through community-based interventions. Since these trials involve packages of varying content, determining how much of the observed mortality reduction is due to specific interventions is problematic. The Lives Saved Tool (LiST) is designed to facilitate programmatic prioritization by modelling mortality reductions related to increasing coverage of specific interventions which may be combined into packages. Methods To assess the validity of LiST outputs, we compared predictions generated by LiST with observed neonatal mortality reductions in trials of packages which met inclusion criteria but were not used as evidence inputs for LiST. Results Four trials, all from South Asia, met the inclusion criteria. The neonatal mortality rate (NMR) predicted by LiST matched the observed rate very closely in two effectiveness-type trials. LiST predicted NMR reduction was close (absolute difference <5/1000 live births) in a third study. The NMR at the end of the fourth study (Shivgarh, India) was overestimated by 39% or 16/1000 live births. Conclusions These results suggest that LiST is a reasonably reliable tool for use by policymakers to prioritize interventions to reduce neonatal deaths, at least in South Asia and where empirical data are unavailable. Reasons for the underestimated reduction in one trial likely include the inability of LiST to model all effective interventions.

Community-driven impact of a newborn-focused behavioral intervention on maternal health in Shivgarh, India.

To assess the effect on maternal health outcomes of a community‐based behavior change management intervention for essential newborn care leading to a reduction in neonatal mortality.

Birth Interval and Risk of Stillbirth or Neonatal Death: Findings from Rural North India

Short birth intervals have been associated with adverse birth outcomes. This study examines the association between preceding interval and risk of stillbirth or neonatal death in rural north India (n = 80 164). Adjusted odds ratios (OR) and 95% confidence interval (CI) of stillbirth and neonatal mortality were calculated. The odds of stillbirth were significantly greater among birth intervals of <18 months (OR 3.10; CI: 2.69-3.57), 18-35 months (OR 1.47; CI 1.30-1.68) and >59 months (OR 1.44; CI 1.19-1.73), compared with intervals of 36-59 months. Neonatal death was associated with birth intervals of <18 months (OR 4.12; CI 3.74-4.55) and 18-35 months (OR 1.78; CI 1.63-1.94), compared to births spaced 36-59 months. Previous history of either stillbirth or neonatal death was significantly associated with risk of stillbirth and neonatal death, respectively, as were multiple births.

The BetterBirth Program: Pursuing Effective Adoption and Sustained Use of the WHO Safe Childbirth Checklist Through Coaching-Based Implementation in Uttar Pradesh, India

The BetterBirth Program relied on carefully structured coaching that was multilevel, collaborative, and provider-centered to motivate birth attendants to use the WHO Safe Childbirth Checklist and improve adherence to essential birth practices. It was scaled to 60 sites as part of a randomized controlled trial in Uttar Pradesh, India. The BetterBirth Program relied on carefully structured coaching that was multilevel, collaborative, and provider-centered to motivate birth attendants to use the WHO Safe Childbirth Checklist and improve adherence to essential birth practices. It was scaled to 60 sites as part of a randomized controlled trial in Uttar Pradesh, India. Shifting childbirth into facilities has not improved health outcomes for mothers and newborns as significantly as hoped. Improving the quality and safety of care provided during facility-based childbirth requires helping providers to adhere to essential birth practices—evidence-based behaviors that reduce harm to and save lives of mothers and newborns. To achieve this goal, we developed the BetterBirth Program, which we tested in a matched-pair, cluster-randomized controlled trial in Uttar Pradesh, India. The goal of this intervention was to improve adoption and sustained use of the World Health Organization Safe Childbirth Checklist (SCC), an organized collection of 28 essential birth practices that are known to improve the quality of facility-based childbirth care. Here, we describe the BetterBirth Program in detail, including its 4 main features: implementation tools, an implementation strategy of coaching, an implementation pathway (Engage-Launch-Support), and a sustainability plan. This coaching-based implementation of the SCC motivates and empowers care providers to identify, understand, and resolve the barriers they face in using the SCC with the resources already available. We describe important lessons learned from our experience with the BetterBirth Program as it was tested in the BetterBirth Trial. For example, the emphasis on relationship building and respect led to trust between coaches and birth attendants and helped influence change. In addition, the cloud-based data collection and feedback system proved a valuable asset in the coaching process. More research on coaching-based interventions is required to refine our understanding of what works best to improve quality and safety of care in various settings. (After publication of this article, the impact results of the BetterBirth intervention were published in the New England Journal of Medicine [volume 377, pages 2313-2324, doi: 10.1056/NEJMoa1701075]. The results showed that the intervention had no significant effect on maternal or perinatal mortality or maternal morbidity, despite having positive effects on essential birth practices.)