Literature DB >> 29370845

Quality improvement initiatives for hospitalised small and sick newborns in low- and middle-income countries: a systematic review.

Nabila Zaka1, Emma C Alexander2, Logan Manikam3,4, Irena C F Norman2, Melika Akhbari2, Sarah Moxon5, Pavani Kalluri Ram6,7, Georgina Murphy8, Mike English8, Susan Niermeyer7,9, Luwei Pearson1.   

Abstract

BACKGROUND: An estimated 2.6 million newborns died in 2016; over 98.5% of deaths occurred in low- and middle-income countries (LMICs). Neonates born preterm and small for gestational age are particularly at risk given the high incidence of infectious complications, cardiopulmonary, and neurodevelopmental disorders in this group. Quality improvement (QI) initiatives can reduce the burden of mortality and morbidity for hospitalised newborns in these settings. We undertook a systematic review to synthesise evidence from LMICs on QI approaches used, outcome measures employed to estimate effects, and the nature of implementation challenges.
METHODS: We searched Medline, EMBASE, WHO Global Health Library, Cochrane Library, WHO ICTRP, and ClinicalTrials.gov and scanned the references of identified studies and systematic reviews. Searches covered January 2000 until April 2017. Search terms were "quality improvement", "newborns", "hospitalised", and their derivatives. Studies were excluded if they took place in high-income countries, did not include QI interventions, or did not include small and sick hospitalised newborns. Cochrane Risk of Bias tools were used to quality appraise the studies.
RESULTS: From 8110 results, 28 studies were included, covering 23 LMICs and 65,642 participants. Most interventions were meso level (district and clinic level); fewer were micro (patient-provider level) or macro (above district level). In-service training was the most common intervention subtype; service organisation and distribution of referencing materials were also frequently identified. The most commonly assessed outcome was mortality, followed by length of admission, sepsis rates, and infection rates. Key barriers to implementation of quality improvement initiatives included overburdened staff and lack of sufficient equipment.
CONCLUSIONS: The frequency of meso level, single centre, and educational interventions suggests that these interventions may be easier for programme planners to implement. The success of some interventions in reducing morbidity and mortality rates suggests that QI approaches have a high potential for benefit to newborns. Going forward, there are opportunities to strengthen the focus of QI initiatives and to develop improved, larger-scale, collaborative research into implementation of quality improvement initiatives for this high-risk group. TRIAL REGISTRATION: PROSPERO CRD42017055459 .

Entities:  

Keywords:  Hospital stay; Infection control; Low- and middle-income countries; Neonatal mortality rates; Newborns; Preterm; Quality improvement; Systematic review

Mesh:

Year:  2018        PMID: 29370845      PMCID: PMC5784730          DOI: 10.1186/s13012-018-0712-2

Source DB:  PubMed          Journal:  Implement Sci        ISSN: 1748-5908            Impact factor:   7.327


Background

Newborns, or infants under 28 days of age, account for the greatest proportion of deaths amongst under-five children. The vast majority of these deaths occur in low- and middle-income countries (LMICs), which in 2016 comprised 98.5% of the 2.61 million neonatal deaths worldwide [1]. The estimated average of neonatal mortality rates in LMICs was 20 per 1000 live births, compared to 3 per 1000 in high-income countries [1]. Targeting this high-risk group is thus an urgent policy priority, particularly regarding the three major causes of neonatal deaths, which are preterm birth complications, severe infections, and intrapartum complications [2]. Low birth weight newborns (birthweight of < 2500 g) are especially vulnerable. Newborns can have low birth weight due to prematurity and/or being small for gestational age (SGA). A neonatal mortality relative risk analysis found that preterm and SGA babies had relative risks of 6.82 and 1.83, respectively, compared to non-low birth weight infants [3]. Survivors of premature birth are at risk of cardiovascular dysfunction, chronic lung disease of prematurity, neurodevelopmental problems, and visual and sensory impairment [4]. SGA newborns likewise have a higher risk of stunting and later, cardiac, metabolic, and cognitive impairment (although to a lesser extent than preterm babies) [5, 6]. Babies who become ill also suffer severe consequences—meta-analysis of newborns in sub-Saharan Africa, South Asia, and Latin America estimated an incidence risk of 7.6% for possible severe bacterial infection, with an associated case-fatality risk of 9.8% [7]. Intrapartum complications can result in neonatal encephalopathy and longer term consequences of disability and cerebral palsy [8]. Most small and sick newborns require inpatient hospital care, ideally in a dedicated unit, and there is a great potential for quality improvement (QI) in this setting, especially in LMICs. Quality improvement is defined by Ovretveit as “better patient experience and outcomes achieved through changing provider behaviour and organisation through using a systematic change method and strategies” [9]. Change of behaviour and organisation can occur at different levels, for example, micro interventions, at the level of the patient-provider interaction (e.g., distribution of referencing materials to providers); meso interventions, at the district and clinic level (e.g., service organisation); or macro, above district level (e.g., regulation and governance) [10, 11]. The Lancet Every Newborn series estimated that increased coverage and improvements at and around the time of birth could avert 71% of deaths [12]. Preventing nosocomial infections [13, 14], irrational antibiotic usage [15], inadequate use of Kangaroo Mother Care [16], low adherence to use of breast milk [17], unsafe oxygen use [18], insufficient bonding with mothers and parents [19], and increasing adherence to humane [20] and baby friendly [21, 22] hospital care are all potential areas for QI. As LMICs are increasingly committing to plan and invest in hospital infrastructure and capacity building of health providers for small and sick newborn care, it is timely to strategise and support simultaneous quality improvement efforts. Previous reviews that have touched on QI initiatives for newborns in LMICs have focused on maternal and child health outcomes together. Dettrick et al. found that evidence in this area is often poor, and most research focuses on service utilisation above other indicators [23]. Additionally, Althabe et al. conducted a review of systematic reviews [24]. Amongst reviews covering over 300 studies, only 18 of these were conducted in LMICs, illustrating the disparity in the amount of research undertaken in these countries [24]. Austin et al. examined approaches to improve maternal and newborn care across all types of countries and observed that quality improvement interventions in LMICs have tended to be community based, rather than hospital based [25]. This review seeks to contribute to the existing evidence base by synthesising data on quality improvement initiatives for hospitalised small and sick newborns in LMICs. We aim to address the following objectives within eligible studies: To identify and categorise quality improvement approaches for small/sick hospitalised newborns in LMICs To identify and categorise outcomes investigated by quality improvement initiatives for small/sick hospitalised newborns in LMICs To identify barriers and promoters, at a local level and systems level, to the implementation of quality improvement initiatives for small/sick hospitalised newborns in LMICs Our work will serve as a guide to quality improvement initiatives in this area by synthesising evidence on approaches used, outcome measures employed to estimate effects, and the nature of implementation challenges, for the information of future healthcare workers undertaking similar initiatives which should be evidence-based.

Methods

A protocol for this review was published on the PROSPERO register in January 2017, registration number CRD42017055459 (PROSPERO, 2017).

Eligibility criteria

Studies were included if they met the following criteria: Populations: hospitalised small and/or sick newborns in LMICs and admitted for inpatient healthcare. LMICs were identified according to the World Bank list of LMICs [26]. Facilities for this population must be defined as ‘hospitals’ or units within hospitals. Interventions: quality improvement initiatives, according to the Ovretveit definition—“better patient experience and outcomes achieved through changing provider behaviour and organisation through using a systematic change method and strategies” [9]. Outcomes: objective clinical outcomes relating to mortality, morbidity, and process of care measures. Language: studies published in English, or with translation available. Year: published from 2000 or later. The year cut-off was chosen in order to focus the review on recent practice in the context of changing healthcare systems. Studies that focused solely or primarily on practices in the delivery room that encompassed small/sick newborns only as a subset, or studies that focused on community interventions, were deemed not to meet the eligibility criteria of hospitalised small and sick newborns. Outcomes of self-assessed competency, or patient-assessed satisfaction, were also deemed not to meet the eligibility criteria of clinical outcomes, as this method of assessment was seen to be an insufficient proxy for an objectively measured clinical outcome. Finally, in order to simplify the review, studies focusing only on implementation of Kangaroo Mother Care (KMC), a specific method of care for preterm infants that focuses on encouraging skin-to-skin contact between mother and infant, were not included unless the study involved modification to KMC implementation, because KMC has been well covered in systematic reviews elsewhere [27, 28].

Information sources

We searched the following electronic databases from January 2000 onwards: Medline, EMBASE, WHO Global Health Library, and Cochrane Library. We searched the trial registries: WHO ICTRP and ClinicalTrials.gov for completed and ongoing studies. Searches were conducted in April 2017. The literature searches of peer-reviewed publications were supplemented by scanning the reference lists of relevant studies and systematic reviews. Interlibrary lending was used to access certain papers.

Search strategy

The following search strategy was designed to capture studies that were suitable for inclusion in the review. For example, the search strings used in EMBASE were: Term 1: Quality improvement (Quality or performance or effectiveness) AND (care or improvement* or increase* or service$ or indicator$) Term 2: Newborns Neonat* or neo-nat* or Baby or Babies or Newborn$ or new-born$ or infant$ Term 3: Hospitalised Inpatient$ or in-patient$ or hospitalis* or NICU or neonatal intensive care unit. These search terms were then combined to give a final search of Term 1 AND Term 2 AND Term 3, which was used to search abstracts in these databases.

Study selection, extraction, and analysis

The titles and abstracts were screened by two researchers independently for inclusion/exclusion, with disagreements resolved with arbitration from a third reviewer. The results shortlisted for inclusion and then underwent full-text screening, again undertaken by two researchers independently with arbitration from a third, to produce a final shortlist of articles to be included in the review. Data were extracted from each paper by one researcher and checked by a second, using a piloted worksheet, the details of which are supplied in Additional file 1. Summary results from fields that are not presented in the main manuscript are available on request. To standardise study classifications, the following definitions were used, based on NICE definitions [29]: Randomised controlled trial—similar people are allocated, at random, to different groups in order to test the efficacy of an intervention, with one group receiving the tested intervention Intervention study (non-random)—similar people are allocated, via a non-random process, to different groups in order to test the efficacy of an intervention, with one group receiving the tested intervention Before and after study—dependent variables are assessed in a setting before and after an intervention is applied, where the population may be the same or differ QI approaches were classified according to the Kruk and Gage schema ‘Synthesizing improvement approaches’ [10]. This classifies approaches at the micro, meso, or macro level, meaning at the level of the patient-provider interaction, such as on the sick newborn care unit; at the district and clinic level; at an individual hospital; or at the above district level, such as across a health system. It then provides sub-classifications of approaches within each of these classes. The relevant outcomes of the studies were extracted. Each outcome was then classified by a research team member. These classifications were based on the WHO-defined components of ‘quality of care’ [30]. This states that high-quality care should be Safe, Effective, Timely, Efficient, Equitable, and People-centred. Studies were sub-sorted by results, according to whether they reported that there was a significant increase in the metric during their study, a significant decrease, no significant change, or if statistical significance was not assessed or not reported. Significance was defined as either p < 0.05 or using the 95% confidence interval. Barriers and promoters of quality improvement were classified as local level, meaning individual to the particular hospital or location where the intervention was based, and systems level, meaning a factor that would necessarily influence hospitals and locations beyond the local area. We utilised a wide scope for extraction of barriers and promoters, including both barriers and promoters that were specific objects of study and those that were informally reported such as through staff feedback reported in the discussion. In order to assess bias in the included studies, we utilised the Cochrane Risk of Bias for Non-Randomised Studies of Interventions (ROBINS-I) and revised tool for Risk of Bias in randomised trials (RoB 2.0) to assess included quantitative studies [31, 32]. Any study with a Critical ROBINS-I Overall Bias or a High RoB 2.0 Overall Bias classification was omitted from the “Results” and “Discussion” sections of this review. Two independent reviewers conducted the quality appraisal, and adjudication was provided by a third reviewer if warranted.

Results

Study selection

In total, the searches returned 8110 results across the four databases, with 49 results identified from other sources. After 2228 duplicates were excluded, a total of 5931 results’ titles and abstracts were screened against inclusion criteria. Of these, 5677 results were excluded for not meeting inclusion criteria at this stage, as demonstrated by Fig. 1.
Fig. 1

Screening strategy for included studies (PRISMA flow diagram) [75]

Screening strategy for included studies (PRISMA flow diagram) [75] This left 254 papers, which underwent full-text review. As shown in Fig. 1, the most common reason for exclusion at this stage was that studies took place in countries that were not LMICs (n = 79) according to the World Bank classifications [26]. The second most common reason was that studies were not describing QI interventions (n = 68). Twenty-eight studies were ultimately identified as suitable for inclusion in the narrative synthesis. Owing to the heterogeneity of QI methodologies, settings, and outcomes measured, meta-analysis was not undertaken.

Study and participant characteristics

The 28 studies consisted of 25 controlled before and after studies, two intervention studies (non-random), and one randomised controlled trial. Table 1 provides a summary of all the included studies.
Table 1

Summary of included studies

AuthorStudy typeLocationPopulationSample sizeQI measureOutcomes
Agarwal et al. 2007 [36]Controlled before and after studyIndiaNeonates born within the obstetric teaching hospital15,249Package of interventions including rational practice, protocol usage, training and empowerment of nursesMortality: 30% decline in NMRLength of admission: reduction from 8.6 days to 7.1.Sepsis: reduction in deaths due to sepsis from 37.9 to 15.5%Appropriate antibiotic use: antibiotics use decreased to 23.2%.
Bastani et al. 2015 [48]Randomised controlled trialIranMothers with preterm infants91A family centred care (FCC) programmeHospital admission/readmission: FCC group were significantly less likely to be rehospitalised, p = 0.04.Length of admission: 6.96 in FCC group, 12.96 in control group, p < 0.001.Maternal satisfaction: FCC group were significantly more satisfied.
Bhutta et al. 2004 [49]Controlled before and after studyPakistanVery low birth weight infants509A step-down unit for mothers and babiesMortality: rates of survival increased, from 65 to 84% (p < 0.05).Length of admission: length of stay fell from mean of 34 to 16.Patient weight gain: there was a reduction in mean weight at discharge from 1.6 to 1.289 kg (p < 0.001).Patient infection rates: rates of overall nosocomial infections dropped significantly.Sepsis: increased relative risk of culture proved neonatal sepsis (95% CI 0.92–1.26).Severe illness: non-significant changes in rates of intraventricular haemorrhage, apnoeic spells, respiratory distress, and necrotising enterocolitis; significant decrease in patent ductus arteriosus rates.Presence of hyperbilirubinaemia: rates fell from 28.8% to 17.9%.
Cavicchiolo et al. 2016 [58]Controlled before and after studyMozambiqueNICU residents—inborn and outborn patients of all gestational ages up to the postnatal age of 7 days4276A continuous multi-level quality improvement intervention focused on infrastructure, equipment and protocol refinementMortality: reduction in death rate from 26 to 18%, significant.Hospital admission/readmission rate: admissions for prematurity, sepsis and asphyxia increased significantly.Sepsis: admissions for sepsis increased significantly, deaths decreased non-significantly.Severe illness: deaths for asphyxia increased significantly, admissions increased significantly.
Clark et al. 2012 [50]Controlled before and after studySierra LeoneChildren presenting for emergency care500Training course based on ETAT WHO course, ward combined to form ICU and ER, triage area created, improved equipment, experienced nurses in triage, structured clerking pack introducedMortality: decreased from 12.38 to 5.85%.Length of admission: no change.
Crouse et al. 2016 [38]Controlled before and after studyGuatemalaRandom sample of all patients presenting to the PED and all patients admitted to the PICU1027Emergency Triage Assessment and Treatment (ETAT)-based emergency triage processMortality: decreased from 12 to 6% amongst critically ill, not significant.Hospital admission/readmission: admission from the Paediatric Emergency Department fell significantly from 8 to 4%, and also fell significantly in critically ill group.Length of admission: decreased, not significant.
Darmstadt et al. 2005 [51]Controlled before and after studyBangladeshPreterm infants in Special Care NurseryInfection control programmeMortality: decline in deaths of certain causes, significance not mentioned.Patient infection rates: decrease in nosocomial infection reports, and K. pneumoniae.Infection detection rates: decline in cases of culture-proven sepsis and suspected sepsis.Sepsis: significant decline in patients with clinical diagnosis of sepsis (79%).Appropriate antibiotic use: antibiotic use guidelines were reviewed, no data.Adherence to national guidelines of care: staff trained in standard guidelines, antibiotic guidelines were adhered to.
dos Santos et al. 2015. [47]Intervention study (non-random)BrazilNICU newborns24NIPS scale; non-pharmacological actions in pain control in newbornsAdherence to national guidelines of care: significantly lower NIPS (pain scale) score with intervention.
Erdeve et al. 2008 [52]Intervention study (non-random)TurkeyAll mother−preterm infant dyads that were consecutively admitted to the NICU60Use of individual roomsHospital admission/readmission: rehospitalisation rate was higher in non-intervention group p < 0.05.Length of admission: no significant difference regarding duration of intensive care hospitalisation.Patient weight gain: no significant change on discharge in body weight.Breastfeeding practice: no significant change in groups regarding breastfeeding rates.
Gathara et al. [39]Controlled before and after studyKenyaSick newborns aged 0–7 days and malnourished children aged 6–59 months798Package of interventions including clinical guidance booklets, admission record form, a training course on emergency and admission care, external support supervision, local facilitation, performance assessment, and feedbackMortality: mortality was reduced by 3% post intervention in intervention group, control group was static.Appropriate antibiotic use: overdoses of penicillin were reduced in intervention vs control group, but overdoses of gentamicin were increased.Adherence to national guidelines of care: documentation of gestation in weeks were increased in intervention group, and mean documentation score was higher. More vitamin K was prescribed in intervention groups.
Gilbert et al. 2014 [53]Controlled before and after studyBrazilNeonates admitted to NICU1242A 5-phase POINTS of Care packageMortality: crude survival rates did not change over time significantly except in one NICU where it decreased.Patient weight gain: days to regain birth weight were significantly higher in post-intervention period.Retinopathy of prematurity: no significant change.Sepsis: rates did not change—11.3/12.3 cases per 1000 infant days.Lower respiratory tract disease: non-significant increase in bronchopulmonary dysplasia.Severe illness: non-significant increase in bronchopulmonary dysplasia, no change in necrotising enterocolitis.
Leng et al. 2016 [40]Controlled before and after studyChinaVery low birth weight neonates172Use of radiant warmers, warmer delivery room, STABLE programme, consulting services, standardised transportation, education of staff, review and feedbackMortality: mortality rates decreased from 12 to 7%, p = 0.03.Length of admission: reduced from 60 to 45 days, p = 0.01Sepsis: sepsis rates did not change significantly.Hypothermia rates: significant decrease in patients with temperatures < 36 degrees Celsius.Lower respiratory tract disease: percentage with chronic lung disease did not change significantly.Severe illness: rates of intraventricular haemorrhage and necrotising enterocolitis did not change significantly, but SNAPPE-II score increased significantly.
Mais et al. 2015 [41]Controlled before and after studyLebanonNeonates with central lines in NICU213Theoretical and practical teaching sessions, dressing change guidelines, sterile technique, auditing adherence to guidelinesLength of admission: there was no significant change.Patient infection rates: CLABSI rates declined significantly, p < 0.05.Mechanical ventilation: no significant change.Central line duration: no significant decline in usage.
Namazzi et al. 2015 [42]Controlled before and after studyUgandaAll pregnant and newly delivered mothers residing within the villages of the Iganga/Mayuge Health and Demographic Surveillance SiteDistrict led training, support supervision, mentoring, supply of essential medicine and equipmentMortality: hospitalised NMR declined from 17 to 9%, not significant.Kangaroo Mother Care: by the end of the study, 547 preterm babies had been cared for in a KMC unit.Premature delivery rate: rate was 8% in deliveries in health units.
Pinto et al. 2013 [43]Controlled before and after studyBrazilNewborns with very low birth weight136Dissemination of a new protocol proposed by the Brazilian National Health Surveillance Agency for antibiotic usage in LBW infantsMortality: overall mortality decreased from 20.9 to 4.4%, significant.Patient infection rates: no significant change in multi-resistant infection rates.Sepsis: no difference in relation to confirmed sepsis, but a significant reduction in diagnoses of probable sepsis.Severe illness: no change in diagnoses of severe illnesses, e.g., PDA, PBD, necrotising enterocolitis.Appropriate antibiotic use: decrease in number of antimicrobial regimens used and days of antibiotic use.
Rahman et al. 2017 [44]Controlled before and after studyBangladeshChildren identified as having systemic sepsis1036Triage, fast assessment, immediate results, immediate antibiotics, training package, slow charts, checklist, records system, infection control measures, equipment stockingMortality: mortality decreased, significance not reported.Length of admission: increase in % with syndromic sepsis staying for over 48 h, significance not reported.Appropriate oxygen use: post intervention 94% were given oxygen with hypoxaemia.Appropriate antibiotic use: first-line recommended antibiotic usage increased from 49 to 75%, p < 0.005.
Ramaswamy et al. 2015 [59]Controlled before and after studyGhanaObstetric and neonatal cases in regional referral facilitiesRidge-Kybele model for obstetric and neonatal care—an integrated approach to systems changeAdherence to national guidelines of care: 37% improvement in NICU hand hygiene rates.Waiting times: 74% reduction in mothers with unacceptable waiting times.
Rosenthal et al. 2012 [33]Controlled before and after studyArgentina, Colombia, El Salvador, India, Mexico, Morocco, Peru, the Philippines, Tunisia, TurkeyNICU patients6829VAP (ventilator-associated pneumonia) bundle—11 itemsPatient infection rates: ventilator-associated pneumonia rates per 1000 mechanical ventilator days decreased from 17.8 to 12.0.Lower respiratory tract disease: ventilator-associated pneumonia rates per 1000 mechanical ventilator days decreased from 17.8 to 12.0.Adherence to National Guidelines of Care: hand hygiene compliance rates rose from 62 to 81%.Mechanical ventilation: days of MV did not change.
Rosenthal et al. 2013 [34]Controlled before and after studyEl Salvador, Mexico, Philippines, and TunisiaNICU patients with central line insertion2214INICC multidimensional infection control approachPatient infection rates: CLABSI rate reduction from baseline of 54%, 95% CI 0.33–0.63 RR.Adherence to National Guidelines of Care: hand hygiene and sterile gauze rates rose significantly.
Salehi et al. 2015 [45]Controlled before and after studyIranHospitalised ‘infants’100Implementation of guidelines and educationPatient weight gain: patients in intervention group had a mean weight change of + 96 g compared to − 59, p = 0.001.
Sethi et al. 2017 [54]Controlled before and after studyIndiaPreterm neonates26 neonates, 23 mothersCPNC—comprehensive post-natal counselling package, comprising education of health care providers and family membersBreastfeeding practice: the proportion of mothers expressing milk on day 1 increased to 86.6% from 12.5%, after 1 year the proportion of neonates on exclusive breast milk was more than 80%.
Soni et al. 2016 [55]Controlled before and after studyIndiaInfants admitted to a rural Indian neonatal intensive care unit (NICU)648Presence of physician championsLength of admission: length of stay was greater with champions, at 9 days, compared to 7 without, p = 0.01.Patient infection rates: patients who experienced infections decreased significantly as physician champions left.Appropriate antibiotic use: no association between champions and antibiotic usage.Breastfeeding practice: breastfeeding rates were not changed.Usage of Kangaroo Mother Care: skin to skin care increased with champions and lasted longer hours per day.Premature delivery rate: with KMC champions there was a higher percentage of premature deliveries, p = 0.01 for trend.
Srofenyoh et al. 2012 [35]Controlled before and after studyGhanaMothers and neonates in Ridge Regional Hospital29,508An interdisciplinary approach, high-level sponsorship, establishment of guidelines, measurement, feedback, leadership and teamwork coaching, training including QI training, and a multimodal focus on patients, providers, and systemsMortality: perinatal mortality was reduced, no information on significance.Maternal satisfaction: this improved.Maternal health: 34% decrease in maternal mortality.Stillbirth: reduced by 36%, p < 0.05.
UNICEF 2014 [37]Controlled before and after studyBangladeshHospitalised newbornsQuality improvement initiatives delivered alongside SCANUs—Special Care Newborn UnitsMortality: average case fatality rates dropped in most SCANUs.Hospital admission/readmission: admissions at SCANUs increased.
Wrammert et al. 2017 [56]Controlled before and after studyNepalNeonates in maternity hospital, Kathmandu299Implementation of Helping Babies Breathe ProtocolMortality: decrease in death rate in first 24 h, p < 0.01. No significant change in 7/28 day mortality.
Yawson et al. 2016 [60]Controlled before and after studyGhanaUsers of Ghanaian newborn care serviceBNA tool to identify service gaps with group discussions, leading to national and regional operational plans and monitoring/evaluation frameworkMortality: mortality reduced in the intervention regions.
Zhou et al. 2013 [57]Controlled before and after studyChinaAll neonates who received mechanical ventilation for at least 48 h and were hospitalised in the NICU for ≥ 5 days491A bundle of comprehensive preventive measures against VAP were gradually implemented using the evidence-based practice for improving quality method.Mortality: mortality rates decreased from 14% in phase 1 to 3% in phases 2 and 3, statistically significant.Patient infection rates: sustained decline in VAP rates, p = 0.01.
Zhou et al. 2015 [46]Controlled before and after studyChinaNeonates in the NICU171EPIQ programme—team taught for 2 days, who then identified strategies for adoption of CLABSI prevention, and trained other membersPatient infection rates: CLABSI rates declined in each successive phase.Central line duration: time in situ increased across the phases, significance not reported.
Summary of included studies The 28 included studies included data from 23 different countries. This included data from India (4 studies), China (3 studies), Bangladesh (3 studies), Ghana (3 studies), Brazil (3 studies), Iran (2 studies), El Salvador (2 studies), Mexico (2 studies), the Philippines (2 studies), Tunisia (2 studies), Turkey (2 studies), Uganda, Nepal, Kenya, Guatemala, Mozambique, Lebanon, Sierra Leone, Pakistan, Argentina, Colombia, Peru, and Morocco. The review includes two multi-country analyses, with one covering Argentina, Colombia, El Salvador, India, Mexico, Morocco, Peru, the Philippines, Tunisia, and Turkey and the other covering El Salvador, Mexico, the Philippines, and Tunisia [33, 34]. There were a total of 65,642 reported participants included in analyses across the studies, although one large study included 29,508 deliveries in its analysis and another included 15,249 [35, 36]. Table 2 presents the ROBINS-I and RoB 2.0 ratings awarded to each of the studies. One study scored Critical in Overall Risk of Bias, and thus was excluded from data synthesis, but is included in Tables 1 and 2 [37].
Table 2

Quality appraisal of included studies

ROBINS-I tool for non-randomised studies of interventions
StudiesBias due to confoundingBias in selection of participants into the studyBias in classification of interventionsBias due to derivations from intended interventionsBias due to missing dataBias in measurement of outcomesBias in selection of the reported resultOverall bias
 Agarwal et al. [36]ModerateLowLowLowLowLowModerateModerate
 Bhutta et al. [49]ModerateLowLowLowLowModerateSeriousSerious
 Cavicchiolo et al. [58]ModerateLowLowLowLowModerateModerateModerate
 Clark et al. [50]SeriousLowLowLowLowLowModerateSerious
 Crouse et al. [38]ModerateLowLowLowSeriousLowModerateSerious
 Darmstadt et al. [51]ModerateLowLowLowNo infoLowModerateModerate
 Dos Santos et al. [47]SeriousNISeriousLowLowSeriousModerateSerious
 Erdeve et al. [52]ModerateLowLowLowLowModerateModerateModerate
 Gathara et al. [39]ModerateModerateLowLowSeriousModerateModerateSerious
 Gilbert et al. [53]ModerateLowLowLowModerateLowModerateModerate
 Leng et al. [40]ModerateLowLowLowLowModerateModerateModerate
 Mais et al. [41]ModerateLowLowLowLowLowModerateModerate
 Namazzi et al. [42]SeriousLowLowLowNo infoModerateModerateSerious
 Pinto et al. [43]ModerateLowLowLowLowLowModerateModerate
 Rahman et al. [44]ModerateLowLowLowNo infoNo infoModerateModerate
 Ramaswamy et al. [59]No infoNo infoNo infoNo infoNo infoNo infoSeriousSerious
 Rosenthal et al. [33]ModerateLowLowLowLowModerateModerateModerate
 Rosenthal et al. [34]ModerateLowLowLowLowLowModerateModerate
 Salehi et al. [45]SeriousLowLowLowNo infoLowLowSerious
 Sethi et al. [54]SeriousLowLowLowLowLowModerateSerious
 Soni et al. [55]ModerateLowLowLowSeriousLowModerateSerious
 Srofenyoh et al. [35]ModerateLowLowLowLowLowModerateModerate
 UNICEF [37]No infoNo infoNo infoNo infoNo infoNo infoCriticalCritical
 Wrammert et al. [56]ModerateLowLowLowLowLowModerateModerate
 Yawson et al. [60]No infoNo infoLowLowNo infoNo infoSeriousSerious
 Zhou et al. [57]SeriousLowLowLowLowLowModerateSerious
 Zhou et al. [46]SeriousLowLowLowLowLowModerateSerious
Risk of Bias 2.0 tool for randomised studies
StudiesBias arising from the randomisation processBias due to deviations from intended interventionsBias due to missing outcome dataBias in the measurement of the outcomeBias in the selection of the reported resultOverall bias
 Bastani et al. [48]LowMediumLowMediumLowMedium
Quality appraisal of included studies The core narrative themes extracted from the papers are presented under the headings, classified QI approaches, groups of outcomes measured in QI approaches, and barriers and promoters to implementing QI approaches. Henceforth, summary data comes from the 28 studies with Overall Risk of Bias of Serious or lower.

Classified quality improvement approaches

We categorised the overarching approaches for quality improvement used for sick newborn care using the Kruk and Gage ‘Synthesizing improvement approaches’ schema [10]. We found 11 studies with micro interventions [33, 38–47], 23 studies with meso interventions [34–36, 38–42, 44–46, 48–59], and two studies with macro interventions [59, 60]. Nine of the studies had mixed-level interventions, with eight of these being meso and micro and one being macro and meso. Table 3 provides information on approaches for quality improvement by subtype. In addition to the included subtypes in Table 3, there were additional categories according to the Kruk and Gage schema, for which no studies utilised those particular methods; these were, at the macro level, pay for performance, other financing and incentives, pre-service training, and external to health system and, at the meso level, mortality audits and social franchising [10].
Table 3

Subtype of intervention

LevelStrategyTotalCitation
MicroDistribution of referencing materials to providers8 studies[33, 38, 39, 41, 4346]
Decision support2 studies[39, 40]
Care coordination5 studies[33, 39, 42, 46, 47]
MesoStrengthening facility infrastructure6 studies[35, 42, 44, 50, 57, 58]
Continuous quality improvement7 studies[34, 35, 41, 46, 51, 58, 59]
Supervision5 studies[35, 39, 51, 55, 57]
Feedback6 studies[34, 35, 39, 40, 51, 59]
In-service training20 studies[3436, 3842, 4446, 48, 50, 51, 53, 54, 5659]
Service organisation9 studies[35, 36, 39, 40, 44, 49, 50, 52, 59]
MacroRegulation and governance1 study[59]
Task shifting1 study[60]
Subtype of intervention The most frequent subtype of intervention was the meso approach ‘In-service training’, used by 20 studies. Such interventions were often delivered as part of a group of innovations—for example, Rosenthal et al. introduced a multifaceted infection control bundle incorporating education on hand hygiene and asepsis, and Agarwal et al. developed a package of interventions that included on-job training of nurses in common neonatal skills [34, 36]. The intervention of Clark et al. was based on a WHO Emergency Triage and Treatment training course, and Sethi et al. utilised a Comprehensive Post-Natal Counselling package, comprised of education of health care providers and family members [50, 54]. In Zhou et al., key staff members attended a training workshop run by the Canadian Neonatal Network for 2 days, and attendees in turn then trained the other Neonatal Intensive Care Unit (NICU) team members [46]. The second most frequent subtype of intervention was the meso approach, ‘Service organisation’, used by nine studies. For example, Rahman et al. described an approach that involved service reorganisation with triage and fast assessment and use of a record system [44]. Erdeve et al. evaluated the impact of individual rooms on patients and families in the NICU [52]. The most frequent micro approach was ‘Distribution of Referencing Materials to Providers’ by eight studies. Pinto et al. disseminated a new protocol proposed by the Brazilian National Health Surveillance Agency for antibiotic usage in low birth weight infants [43]. Salehi et al. also described the implementation of new guidelines, as did Mais et al. and Gathara et al. as part of their approaches [39, 41, 45]. Two studies utilised macro approaches, which were regulation and governance, and task shifting. Ramaswamy et al. used regulation and governance in their development of the Ridge-Kybele Model for Obstetric and Neonatal Care, an integrated approach for systems change which prioritises capacity building in order to properly embed change practices [59]. Yawson et al. utilised task shifting, by using a tool to identify service gaps which led to national and regional operating plans being developed and implemented to improve neonatal care [60].

Groups of outcomes measured in quality improvement approaches

A total of 23 broad outcomes were used to assess the efficacy of the QI interventions, shown in Table 4. The majority of these, 13, were outcomes that were classified as aiming at delivering safe care, defined as “delivering health care which minimises risks and harm to service users, including avoiding preventable injuries and reducing medical errors” [30]. Five were aimed at delivering effective care, two efficient care, two people-centred care, and one timely care. No studies were identified as including outcomes addressing the delivery of equitable care.
Table 4

Quality improvement outcomes

Quality of care classification of QI outcome measureQuality improvement outcomeSignificant increaseSignificant decreaseNo significant changeSignificance not assessed or not reported
Safe (minimising risks and harm)Mortality8 studies—[36, 40, 43, 49, 50, 5658]4 studies—[38, 42, 53, 56]5 studies—[35, 39, 44, 51, 60]
Patient weight gain1 study—[45]2 studies—[49, 53]1 study—[52]
Patient infection rates1 study—[55]7 studies—[33, 34, 41, 46, 49, 51, 57]1 study—[43]
Effect on retinopathy of prematurity1 study—[53]
Sepsis rates3 studies—[36, 43, 51]5 studies—[40, 43, 49, 53, 58]
Rates of hypothermia1 study—[40]
Patient lower respiratory tract disease1 study—[33]2 studies—[40, 53]
Severe illness (various)2 studies—[40, 58]1 study—[49]4 studies—[40, 43, 49, 53]
Presence of hyperbilirubinaemia1 study—[49]
Effect on breastfeeding practice1 study—[54]2 studies—[52, 55]
Maternal health1 study—[35]
Stillbirth1 study—[35]
Premature delivery rate1 study—[55]1 study—[42]
Effective (utilising evidence)Appropriate oxygen use1 study—[44]
Antibiotic usage1 study—[44]2 studies—[36, 43]1 study—[55]2 studies—[39, 51]
Adherence to national guidelines of care4 studies—[33, 34, 47, 59]2 studies—[39, 51]
Mechanical ventilator days2 studies—[33, 41]
Central line duration1 study—[41]1 study—[46]
Efficient (avoiding waste)Length of admission1 study—[55]4 studies—[36, 40, 48, 49]2 studies—[38, 41]3 studies—[44, 50, 52]
Hospital admission/readmission1 study—[58]3 studies—[38, 48, 52]1 study—[49]
People-centred (accounting for preferences of service users)Usage of Kangaroo Mother Care1 study—[55]1 study—[42]
Maternal satisfaction1 study—[48]1 study—[35]
Timely (reducing delays)Waiting times1 study—[59]
Quality improvement outcomes

Mortality rate

Mortality rate was the most frequently measured outcome, assessed by 16 studies. Studies used a variety of mortality metrics, including 28-day mortality, mortality within the study period, and specific cause mortality. Eight studies found that introduction of the QI intervention was associated with a significant decrease in mortality, four found no significant change, and five others reported results but not the statistical significance of those results. Amongst the more successful interventions, Bhutta et al. found that survival in their NICU increased from 65 to 84%, p < 0.05, after a policy change to create a stepdown unit and involve mothers earlier in the care of their at risk infants [49]. Pinto et al. also found a significant reduction in mortality, from 20.9 to 4.4%, p = 0.009, after the dissemination of a new antibiotic protocol to their NICU, which was supervised by two neonatologists in charge of the clinical routine [43]. Leng et al. also found mortality rates decreased, from 12 to 7%, p = 0.03, amongst newborns transferred from eight hospitals to their Level III NICU, after the introduction of a package of interventions including the STABLE programme and staff education [40]. Crouse et al. found that overall mortality for the critically ill patients decreased with their new emergency triage process, from 12.4% pre-intervention to 6.0% post-intervention, but this was not statistically significant (p = 0.15) [38].

Length of admission

Length of admission was the second most assessed outcome, by ten studies. Studies reported mixed outcomes, with one reporting a significant increase, four a significant decrease, two no change and three where significance was not assessed. Soni et al. found that length of stay in the NICU increased with identified Kangaroo Mother Care champions, at a median of 9 days, compared to a median of seven without the champions [61]. Conversely, Bastani et al. found that, in their RCT, mean length of stay in the NICU for their family-centred care group was 6.96 days compared to 12.96 in the control group, p < 0.001 [48]. Bhutta et al. found that length of stay more than halved after their stepdown unit was introduced, from a mean of 34 days pre-intervention to 16 post-intervention [49].

Sepsis rates

Sepsis rates were the joint third most frequently measured outcome, assessed by eight studies. Three studies reported a significant decrease in sepsis rates, and five reported no significant change. Amongst the studies that reported significant decreases were Agarwal et al., who found that there was a severe reduction in deaths in their neonatal unit due to sepsis after the introduction of their multi-faceted intervention package, from 37.9% pre-intervention to 15.5% post, p < 0.01 [36]. Their package included greater involvement of mothers in caregiving, as with Bhutta et al., alongside enforced aseptic routines, greater use of protocols, education, and other features [36, 49]. However, in Gilbert et al., the introduction of an educational package, POINTS of Care, did not change sepsis rates across five neonatal units nor did the multi-faceted intervention incorporating education, feedback, and other elements in Leng et al. [40, 53].

Patient infection rates

Patient infection rates, across a variety of different specific infections, were assessed by nine studies. Seven studies reported a significant decrease in infection rates, one a significant increase and one reported no significant change. Amongst the studies that reported significant decreases was Rosenthal et al., who found that a multi-faceted ventilator-associated pneumonia (VAP) bundle intervention was associated with a reduction in VAP rates from 17.8/1000 ventilation days pre-intervention to 12.0/1000 ventilation days post-intervention, across 15 NICUs in ten countries [33]. Rosenthal et al. found that after an infection control bundle, central line-associated bloodstream infection (CLABSI) rates reduced across four NICUs in four countries, resulting in a relative risk of 0.45 post-intervention (95% CI 0.33–0.63) [34]. Both interventions utilised infection control teams and surveillance. Mais et al. also reported on CLABSI rates, which declined from 15/1000 central line days before the introduction of a bundle of interventions to 6.4/1000 afterwards (p < 0.05) [41]. For Zhou et al., CLABSI rates also fell significantly from 16.7/1000 before the introduction of a nursing training programme to 5.2/1000 afterwards [46].

Barriers and promoters to implementing quality improvement approaches

Many factors have the potential to either promote or inhibit the successful implementation of interventions for quality improvement [62, 63], and several of these were covered by the studies. These factors are noted in Table 5 and are identified as either barriers or promoters operating at a local or systems level. In total, 11 barriers were identified, with six at the local level and five at the systems level, and 13 promoters were identified, with nine at the local level and four at the systems level. No study assessed the statistical significance of any barrier or promoter; identified barriers and promoters were largely inductive by the investigators.
Table 5

Factors influencing efficacy of QI measures

Local levelStudiesSystems levelStudies
Promoters
 Motivation of key individuals3 studies—[35, 42, 51]Relationships between health workers, community leaders and district officials1 study—[42]
 Continuous monitoring throughout2 studies—[38, 56]High-quality national data collection1 study—[60]
 Interdisciplinary collaboration2 studies—[35, 38]Formal health service support1 study—[35]
 Abandonment of unnecessary practices1 study—[36]NGO collaboration initiatives1 study—[58]
 Schemes tailored to participants1 study—[38]
 On-site support1 study—[44]
 Refresher programmes1 study—[44]
 Formal training in QI methods1 study—[35]
 Low cost of intervention1 study—[38]
Barriers
 Overburdened staff4 studies—[36, 42, 53, 56]Insufficient funding1 study—[42]
 Lack of sufficient equipment4 studies—[36, 38, 42, 58]Insufficient health services relative to demand1 study—[42]
 High changeover of workforce3 studies—[35, 36, 53]Government redistribution of staff1 study—[53]
 Defects in staff knowledge and practice1 study—[35]Inadequate documentation1 study—[39]
 Unmotivated staff1 study—[53]Confounding health policy changes1 study—[50]
 Multiple QI measures/audits simultaneously1 study—[55]
Factors influencing efficacy of QI measures

Promoters

Nine promoters were identified at the local level by seven studies. Three studies highlighted the importance of motivation of key individuals. Darmstadt et al. highlighted the will and effort of key individuals as being important, especially the nursing supervisor; Srofenyoh et al. and Namazzi et al. noted the importance of local champions [35, 42, 51]. Four promoters were identified at the systems level by four studies. Yawson et al. stated that good quality national data collection is essential for designing QI interventions [60]. Namazzi et al. highlighted structured community relationships, Cavicchiolo et al. said NGO collaboration could be helpful, and Srofenyoh et al. valued formal support from the Ghanian Health Service [35, 42, 58].

Barriers

Six barriers to quality improvement initiatives were identified at a local level by eight studies. The barrier posed by overburdened staff was the joint most frequently mentioned barrier, by four studies. This includes Gilbert et al. who mentioned staff being overstretched as an impediment, and Namazzi et al. who discussed the fact that facility staff had competing demands on their time [42, 53]. Four studies also mentioned the problem of insufficient equipment, such as Crouse et al. who stated that paper supplies running low and no computerised patient records hampered record keeping [38]. Five barriers were identified at a systems level by four studies. Namazzi et al. highlighted both the problems of increasing demand for services at all hospitals and lack of finances for necessary medicines [42]. Gilbert et al. said government policies enforcing redistribution of staff from study NICUs to underserved areas also created barriers [53].

Discussion

Many LMICs have focused on developing the infrastructure for inpatient care of sick newborns in public health systems. The recent focus on quality of care with the launch of the Quality, Equity and Dignity Network co-led by the WHO and United Nations International Children’s Emergency Fund (UNICEF), alongside ongoing efforts to raise the standard of paediatric care, has increased the interest in addressing gaps in quality of care for sick newborns. To our knowledge, this is the first systematic review to specifically examine quality improvement initiatives for hospitalised small and sick newborns in LMICs. Previous reviews have focused on maternal and child care as a whole [23, 24], or did not focus on LMICS individually [25], or have focused on a subtype of quality improvement interventions (in service training) [64], with all of these also encompassing non-hospitalised newborns.

Programmatic implications

Programme planners should consider that the majority of interventions are at the meso level, and many studies (20 studies) involved in-service training as part of their interventions. Educational interventions may be frequently represented because exposure of the intervention to the relevant staff can be appropriately monitored, implemented, and tailored to local needs, whereas macro-level interventions like regulation and governance or task shifting require greater continuous coordination. For planners designing their first QI projects, in-service training may be an advisable first step. However, structural adjustments remain necessary in order to facilitate QI at all levels of care. It will be especially relevant to formulate and implement policies to retain skilled nursing staff alongside providing financing to achieve national standards of minimum infrastructure and equipment, and to increase staffing for optimal nurse-patient ratios. Increasing adoption of perinatal death reviews in LMICs will also provide an opportunity to review and address common gaps in a country through macro-level interventions. The most frequently assessed outcomes were mortality rates, sepsis and infection rates. Eight of the 12 studies that investigated statistically significant differences in mortality rates observed a statistically significant decrease in mortality. Particularly high reductions occurred in Bhutta et al. and Pinto et al., with mortality falling by 19% in the former after the creation of a stepdown unit and mortality falling by 16.5% in the latter after the dissemination of a new antibiotic protocol [43, 49]. These studies demonstrate the potential for QI to produce swift and significant benefits for this vulnerable patient group. However, it is important to note that the majority of the included studies were non-randomised before-after studies, and a review by Schouten et al. found that observational studies tend to demonstrate larger effects than more rigorous designs [65]. There are many feeders into mortality rates and a number of the studies had important confounders. With regards to other outcomes, in general, studies did not report greater involvement of family members as part of their interventions, but those that did reported significant positive results for mortality, sepsis, and readmission rates, suggesting this area could be explored further [36, 48, 49]. It will be important to focus future QI efforts on sepsis due to rising rates of antibiotic resistant infections and sepsis in this group [66]. Some successful studies in this area did incorporate holistic interventions involving family members [36, 49]. Several studies benefitted from focusing their efforts on single pathologies (ventilator-associated pneumonia, central line-associated blood stream infections) for quality improvement, which allowed for collation of findings across multiple centres [33, 34]. Other interventions utilised training courses included the POINTS of Care training (a six module training programme covering topics including pain control and nutrition interventions) [53, 67] and the STABLE programme (a continuing education course that focuses on stabilising sick newborns) [40]. Such approaches allow easy monitoring of attendance and hence exposure for future studies that may choose to utilise control groups. For programme planners, our identification of barriers and promoters to successful QI interventions will be helpful to accelerate efforts for meeting the objectives of Every Newborn Action Plan, Every Woman Every Child, and other quality of care agendas [68, 69]. Planners should consider resolving barriers such as overburdened staff, which may be more severe during times of higher seasonal demand, and consider identifying ‘staff champions’ to promote their projects which were reported as promoters in several studies [35, 42, 51]. A previous review of barriers and enablers of KMC identified similar influential factors, such as the barrier posed by a high workload [70]. Finally, it is important to reflect that quality improvement approaches are heavily dependent on data linked to action and evidence to drive positive change. Moxon et al. have advocated for the urgent need to improve health management information systems and monitoring of hospital care for newborns for better measurement of quality of care and to identify and address quality gaps [62]. Thus, the allocation of resources on improving quality of sick newborn care needs to factor in requirements for improving local, country-led sustainable information systems, as well as systematic use of perinatal death audits [71]. Mortality audits were not utilised by any of the included studies, despite a recent focus via Maternal and Perinatal Deaths Surveillance and Response projects [72]. The bottlenecks of health financing, health workforce, data and community engagement need more varied approaches to implementation and research, especially at Macro level, and advanced information systems would be valuable in order to optimise QI if used for action at the correct level of the health system.

Research implications

Regarding future research into QI initiatives in LMICs, we recommend QI implementation takes place in tandem with strong data collection and monitoring. The majority of research takes place in high-income countries, whose settings may not be fully applicable to LMICs [12, 25]. We also note the impact of several interventions was hard to assess because studies did not analyse statistical significance. These interventions would benefit from further, larger-scale studies, or more rigorous evaluation. The sharing of outcome measures across studies would also allow for improved future quantitative synthesis. We found that research often focused on single centres, also noted by Dettrick et al. [23]. More work should be done to evaluate quality improvement at multiple centres in different settings, such as comparisons between rural and urban hospitals, and to investigate the impact of scaling up existing projects [12, 73]. This may need specific capacity building of public health programmes and clinical staff on research in LMICs and provision of grants to undertake context-specific projects on a range of interventions. Barriers and promoters were not assessed for statistical significance by any study, and multi-centre studies could enable such analysis and the provision of richer qualitative data. Generally, we would recommend that QI projects are rigorously evaluated and the experience documented or reported in peer-reviewed literature wherever feasible.

Limitations of our study

The heterogeneity of our study population, the interventions for quality improvement and multiple outcome measures were key challenges. Quality improvement approaches is an umbrella term for a variety of interventions, and though we cast a wider net, some studies may have been missed from our selection criteria, especially if they did not use the exact term. Many healthcare interventions in LMICs are community- rather than hospital-based, and care during pregnancy was not considered, so many interventions that may be useful in mitigating overall newborn morbidity and mortality were not eligible [74]. In general, many quality improvement projects do not progress to published literature, particularly small-scale projects, so publication bias is likely to be present. Unpublished ongoing initiatives ongoing in collaboration with WHO, UNICEF, USAID and others could not be included. This study did not capture solely qualitative literature, and qualitative synthesis would be useful going forward, particularly for identifying barriers and promoters. There was generally little information on the methodology for identifying barriers and promoters in the included studies, which may mean that findings are not fully representative. The study method did not allow for collection of information relating to parental experience, which is a critical dimension of quality of care improvement. This study is also limited by only including studies published from 2000 onwards and published in English. We did not conduct overall outcome-specific assessments of quality of evidence with a tool such as GRADE. Finally, although we aimed to analyse with reference to wealth, rural/urban, and type of facility as measures of healthcare equity, data on financing of health settings were available for only a minority of the included papers, and many hospital settings were anonymised. As a result, these analyses were not undertaken.

Conclusion

Going forward, we recommend more rigorous evaluation of quality improvement in neonatal hospital care. Interventions are commonly at the meso level and educational in nature, and more focus is required around macro- and micro-level interventions; other study designs should be explored, with direct investigation of barriers and promoters. This should be linked to programmatic efforts where possible, in order to combine implementation and research. Small and sick hospitalised newborns in LMICs are a population at the highest risk—they should be one of the prime beneficiaries of quality of care interventions and investments. Targeted resources will be needed to strengthen human resource capabilities for implementation research into quality improvement for small and sick newborn care and to document outcomes, costs, and lessons learnt.
  61 in total

1.  Reducing length of stay in hospital for very low birthweight infants by involving mothers in a stepdown unit: an experience from Karachi (Pakistan).

Authors:  Zulfiqar A Bhutta; Iqtidar Khan; Suhail Salat; Farukh Raza; Husan Ara
Journal:  BMJ       Date:  2004-11-13

2.  What is "quality improvement" and how can it transform healthcare?

Authors:  Paul B Batalden; Frank Davidoff
Journal:  Qual Saf Health Care       Date:  2007-02

3.  Impact of a family-centered care initiative on NICU care, staff and families.

Authors:  L G Cooper; J S Gooding; J Gallagher; L Sternesky; R Ledsky; S D Berns
Journal:  J Perinatol       Date:  2007-12       Impact factor: 2.521

4.  Infection control practices reduce nosocomial infections and mortality in preterm infants in Bangladesh.

Authors:  Gary L Darmstadt; A S M Nawshad Uddin Ahmed; Samir K Saha; M A K Azad Chowdhury; Muhammad Asif Alam; Mahamuda Khatun; Robert E Black; Mathuram Santosham
Journal:  J Perinatol       Date:  2005-05       Impact factor: 2.521

5.  Prevalence of nosocomial infections in neonatal intensive care unit patients: Results from the first national point-prevalence survey.

Authors:  A H Sohn; D O Garrett; R L Sinkowitz-Cochran; L A Grohskopf; G L Levine; B H Stover; J D Siegel; W R Jarvis
Journal:  J Pediatr       Date:  2001-12       Impact factor: 4.406

6.  Impact of simple interventions on neonatal mortality in a low-resource teaching hospital in India.

Authors:  R Agarwal; K Agarwal; U Acharya; P Christina; V Sreenivas; S Seetaraman
Journal:  J Perinatol       Date:  2007-01       Impact factor: 2.521

7.  Handwashing program for the prevention of nosocomial infections in a neonatal intensive care unit.

Authors:  Sau-Pin Won; Hung-Chieh Chou; Wu-Shiun Hsieh; Chien-Yi Chen; Shio-Min Huang; Kuo-Inn Tsou; Po-Nien Tsao
Journal:  Infect Control Hosp Epidemiol       Date:  2004-09       Impact factor: 3.254

8.  Strategies for improving the quality of health care in maternal and child health in low- and middle-income countries: an overview of systematic reviews.

Authors:  Fernando Althabe; Eduardo Bergel; María Luisa Cafferata; Luz Gibbons; Agustín Ciapponi; Alicia Alemán; Lisandro Colantonio; Alvaro Rodríguez Palacios
Journal:  Paediatr Perinat Epidemiol       Date:  2008-01       Impact factor: 3.980

Review 9.  Effects of being born small for gestational age on long-term intellectual performance.

Authors:  Ester Maria Lundgren; Torsten Tuvemo
Journal:  Best Pract Res Clin Endocrinol Metab       Date:  2008-06       Impact factor: 4.690

10.  The impact of individual room on rehospitalization and health service utilization in preterms after discharge.

Authors:  O Erdeve; S Arsan; S Yigit; D Armangil; B Atasay; A Korkmaz
Journal:  Acta Paediatr       Date:  2008-06-06       Impact factor: 2.299

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1.  Study protocol: Impact of quality improvement interventions on perinatal outcomes in health facilities-a systematic review.

Authors:  Rejina Gurung; Nabila Zaka; Shyam Sundar Budhathoki; Avinash K Sunny; Jeevan Thapa; Hong Zhou; Ashish Kc
Journal:  Syst Rev       Date:  2019-08-15

2.  Categorising interventions to levels of inpatient care for small and sick newborns: Findings from a global survey.

Authors:  Sarah G Moxon; Hannah Blencowe; Patricia Bailey; John Bradley; Louise Tina Day; Pavani K Ram; Jean-Pierre Monet; Allisyn C Moran; Willibald Zeck; Joy E Lawn
Journal:  PLoS One       Date:  2019-07-11       Impact factor: 3.240

3.  What topics should we teach the parents of admitted neonates in the newborn care unit in the resource-limited setting - a Delphi study.

Authors:  Jean Aime Musabyemungu; Alice Willson; Sean Batenhorst; James Webbe; Peter Thomas Cartledge
Journal:  Matern Health Neonatol Perinatol       Date:  2019-07-11

4.  Effective coverage and budget implications of skill-mix change to improve neonatal nursing care: an explorative simulation study in Kenya.

Authors:  Apostolos Tsiachristas; David Gathara; Jalemba Aluvaala; Timothy Chege; Edwine Barasa; Mike English
Journal:  BMJ Glob Health       Date:  2019-12-02

5.  Programme theory and linked intervention strategy for large-scale change to improve hospital care in a low and middle-income country - A Study Pre-Protocol.

Authors:  Mike English; Jacinta Nzinga; Grace Irimu; David Gathara; Jalemba Aluvaala; Jacob McKnight; Geoffrey Wong; Sassy Molyneux
Journal:  Wellcome Open Res       Date:  2020-11-05

6.  Developing a Model for National Health Information Governance Program in Iran.

Authors:  Fatemeh Rouzbahani; Farkhondeh Asadi; Reza Rabiei; Hamid Moghaddasi; Hassan Emami
Journal:  J Med Life       Date:  2020 Oct-Dec

7.  Annual trend of neonatal mortality and its underlying causes: population-based study - São Paulo State, Brazil, 2004-2013.

Authors:  Ruth Guinsburg; Adriana Sanudo; Carlos Roberto V Kiffer; Ana Sílvia S Marinonio; Daniela T Costa-Nobre; Kelsy N Areco; Mandira D Kawakami; Milton H Miyoshi; Paulo Bandiera-Paiva; Rita de Cássia X Balda; Tulio Konstantyner; Liliam Cc Morais; Rosa Mv Freitas; Mônica Lp Teixeira; Bernadette Waldvogel; Maria Fernanda B Almeida
Journal:  BMC Pediatr       Date:  2021-01-26       Impact factor: 2.125

8.  Neurodevelopmental disorders in children aged 2-9 years: Population-based burden estimates across five regions in India.

Authors:  Narendra K Arora; M K C Nair; Sheffali Gulati; Vaishali Deshmukh; Archisman Mohapatra; Devendra Mishra; Vikram Patel; Ravindra M Pandey; Bhagabati C Das; Gauri Divan; G V S Murthy; Thakur D Sharma; Savita Sapra; Satinder Aneja; Monica Juneja; Sunanda K Reddy; Praveen Suman; Sharmila B Mukherjee; Rajib Dasgupta; Poma Tudu; Manoja K Das; Vinod K Bhutani; Maureen S Durkin; Jennifer Pinto-Martin; Donald H Silberberg; Rajesh Sagar; Faruqueuddin Ahmed; Nandita Babu; Sandeep Bavdekar; Vijay Chandra; Zia Chaudhuri; Tanuj Dada; Rashna Dass; M Gourie-Devi; S Remadevi; Jagdish C Gupta; Kumud K Handa; Veena Kalra; Sunil Karande; Ramesh Konanki; Madhuri Kulkarni; Rashmi Kumar; Arti Maria; Muneer A Masoodi; Manju Mehta; Santosh Kumar Mohanty; Harikumaran Nair; Poonam Natarajan; A K Niswade; Atul Prasad; Sanjay K Rai; Paul S S Russell; Rohit Saxena; Shobha Sharma; Arun K Singh; Gautam B Singh; Leena Sumaraj; Saradha Suresh; Alok Thakar; Sujatha Parthasarathy; Bhadresh Vyas; Ansuman Panigrahi; Munish K Saroch; Rajan Shukla; K V Raghava Rao; Maria P Silveira; Samiksha Singh; Vivek Vajaratkar
Journal:  PLoS Med       Date:  2018-07-24       Impact factor: 11.069

9.  Admissions to a Low-Resource Neonatal Unit in Malawi Using a Mobile App: Digital Perinatal Outcome Audit.

Authors:  Caroline Crehan; Erin Kesler; Indira Angela Chikomoni; Kristi Sun; Queen Dube; Monica Lakhanpaul; Michelle Heys
Journal:  JMIR Mhealth Uhealth       Date:  2020-10-21       Impact factor: 4.773

10.  Healthcare worker perceptions of the implementation context surrounding an infection prevention intervention in a Zambian neonatal intensive care unit.

Authors:  Carter Cowden; Lawrence Mwananyanda; Davidson H Hamer; Susan E Coffin; Monica L Kapasa; Sylvia Machona; Julia E Szymczak
Journal:  BMC Pediatr       Date:  2020-09-10       Impact factor: 2.125

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