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1.
Implement Sci ; 15(1): 1, 2020 01 03.
Article in English | MEDLINE | ID: mdl-31900167

ABSTRACT

BACKGROUND: The BetterBirth trial tested the effect of a peer coaching program around the WHO Safe Childbirth Checklist for birth attendants in primary-level facilities in Uttar Pradesh, India on a composite measure of perinatal and maternal mortality and maternal morbidity. This study aimed to examine the adherence to essential birth practices between two different cadres of birth attendants-nurses and auxiliary nurse midwives (ANMs)-during and after a peer coaching intervention for the WHO Safe Childbirth Checklist. METHODS: This is a secondary analysis of birth attendant characteristics, coaching visits, and behavior uptake during the BetterBirth trial through birth attendant surveys, coach observations, and independent observations. Descriptive statistics were calculated overall, and by staffing cadre (staff nurses and ANMs) for demographic characteristics. Logistic regression using the Pearson overdispersion correction (to account for clustering by site) was used to assess differences between staff nurses and ANMs in the intervention group during regular coaching (2-month time point) and 4 months after the coaching program ended (12-month time point). RESULTS: Of the 570 birth attendants who responded to the survey in intervention and control arms, 474 were staff nurses (83.2%) and 96 were ANMs (16.8%). In the intervention arm, more staff nurses (240/260, 92.3%) received coaching at all pause points compared to ANMs (40/53, 75.5%). At baseline, adherence to practices was similar between ANMs and staff nurses (~ 30%). Overall percent adherence to essential birth practices among ANMs and nurses was highest at 2 months after intervention initiation, when frequent coaching visits occurred (68.1% and 64.1%, respectively, p = 0.76). Practice adherence tapered to 49.2% among ANMs and 56.1% among staff nurses at 12 months, which was 4 months after coaching had ended (p = 0.68). CONCLUSIONS: Overall, ANMs and nurses responded similarly to the coaching intervention with the greatest increase in percent adherence to essential birth practices after 2 months of coaching and subsequent decrease in adherence 4 months after coaching ended. While coaching is an effective strategy to support some aspects of birth attendant competency, the structure, content, and frequency of coaching may need to be customized according to the birth attendant training and competency. TRIAL REGISTRATION: ClinicalTrials.gov: NCT2148952; Universal Trial Number: U1111-1131-5647.


Subject(s)
Delivery, Obstetric/standards , Mentoring/organization & administration , Midwifery/standards , Nurses/standards , Peer Group , Adult , Checklist/standards , Female , Guideline Adherence , Humans , India/epidemiology , Logistic Models , Maternal Mortality/trends , Middle Aged , Perinatal Mortality/trends , Practice Guidelines as Topic , Socioeconomic Factors , World Health Organization
3.
Health Policy Plan ; 34(8): 574-581, 2019 Oct 01.
Article in English | MEDLINE | ID: mdl-31419287

ABSTRACT

In India, most women now delivery in hospitals or other facilities, however, maternal and neonatal mortality remains stubbornly high. Studies have shown that mistreatment causes delays in care-seeking, early discharge and poor adherence to post-delivery guidance. This study seeks to understand the variation of women's experiences in different levels of government facilities. This information can help to guide improvement planning. We surveyed 2018 women who gave birth in a representative set of 40 government facilities from across Uttar Pradesh (UP) state in northern India. Women were asked about their experiences of care, using an established scale for person-centred care. We asked questions specific to treatment and clinical care, including whether tests such as blood pressure, contraction timing, newborn heartbeat or vaginal exams were conducted, and whether medical assessments for mothers or newborns were done prior to discharge. Women delivering in hospitals reported less attentive care than women in lower-level facilities, and were less trusting of their providers. After controlling for a range of demographic attributes, we found that better access, higher clinical quality, and lower facility-level, were all significantly predictive of patient-centred care. In UP, lower-level facilities are more accessible, women have greater trust for the providers and women report being better treated than in hospitals. For the vast majority of women who will have a safe and uncomplicated delivery, our findings suggest that the best option would be to invest in improvements mid-level facilities, with access to effective and efficient emergency referral and transportation systems should they be needed.


Subject(s)
Delivery, Obstetric/statistics & numerical data , Maternal Health Services/statistics & numerical data , Patient Satisfaction/statistics & numerical data , Quality of Health Care/statistics & numerical data , Adult , Ambulatory Care Facilities/statistics & numerical data , Delivery, Obstetric/methods , Delivery, Obstetric/psychology , Female , Hospitals, Public/statistics & numerical data , Humans , India , Infant Care/statistics & numerical data , Infant, Newborn , Patient-Centered Care/statistics & numerical data , Surveys and Questionnaires
4.
PLoS One ; 13(11): e0207987, 2018.
Article in English | MEDLINE | ID: mdl-30481209

ABSTRACT

BACKGROUND: Maternal and neonatal outcomes in the immediate post-delivery period are critical indicators of quality of care. Data on childbirth outcomes in low-income settings usually require home visits, which can be constrained by cost and access. We report on the use of a call center to measure post-discharge outcomes within a multi-site improvement study of facility-based childbirth in Uttar Pradesh, India. METHODS: Of women delivering at study sites eligible for inclusion, 97.9% (n = 157,689) consented to follow-up. All consenting women delivering at study facilities were eligible to receive a phone call between days eight and 42 post-partum to obtain outcomes for the seven-day period after birth. Women unable to be contacted via phone were visited at home. Outcomes, including maternal and early neonatal mortality and maternal morbidity, were ascertained using a standardized script developed from validated survey questions. Data Quality Assurance (DQA) included accuracy (double coding of calls) and validity (consistency between two calls to the same household). Regression models were used to identify factors associated with inconsistency. FINDINGS: Over 23 months, outcomes were obtained by the call center for 98.0% (154,494/157,689) consenting women and their neonates. 87.9% of call center-obtained outcomes were captured by phone call alone and 12.1% required the assistance of a field worker. An additional 1.7% were obtained only by a field worker, 0.3% were lost-to-follow-up, and only 0.1% retracted consent. The call center captured outcomes with a median of 1 call (IQR 1-2). DQA found 98.0% accuracy; data validation demonstrated 93.7% consistency between the first and second call. In a regression model, significant predictors of inconsistency included cases with adverse outcomes (p<0.001), and different respondents on the first and validation call (p<0.001). CONCLUSIONS: In areas with widespread mobile cell phone access and coverage, a call center is a viable and efficient approach for measurement of post-discharge childbirth outcomes.


Subject(s)
Call Centers , Patient Reported Outcome Measures , Postpartum Period , Program Evaluation , Female , Humans , India , Infant, Newborn , Male , Parturition , Patient Discharge , Postnatal Care , Quality Improvement , Reproducibility of Results , Spouses
5.
Trials ; 18(1): 418, 2017 09 07.
Article in English | MEDLINE | ID: mdl-28882167

ABSTRACT

BACKGROUND: There are few published standards or methodological guidelines for integrating Data Quality Assurance (DQA) protocols into large-scale health systems research trials, especially in resource-limited settings. The BetterBirth Trial is a matched-pair, cluster-randomized controlled trial (RCT) of the BetterBirth Program, which seeks to improve quality of facility-based deliveries and reduce 7-day maternal and neonatal mortality and maternal morbidity in Uttar Pradesh, India. In the trial, over 6300 deliveries were observed and over 153,000 mother-baby pairs across 120 study sites were followed to assess health outcomes. We designed and implemented a robust and integrated DQA system to sustain high-quality data throughout the trial. METHODS: We designed the Data Quality Monitoring and Improvement System (DQMIS) to reinforce six dimensions of data quality: accuracy, reliability, timeliness, completeness, precision, and integrity. The DQMIS was comprised of five functional components: 1) a monitoring and evaluation team to support the system; 2) a DQA protocol, including data collection audits and targets, rapid data feedback, and supportive supervision; 3) training; 4) standard operating procedures for data collection; and 5) an electronic data collection and reporting system. Routine audits by supervisors included double data entry, simultaneous delivery observations, and review of recorded calls to patients. Data feedback reports identified errors automatically, facilitating supportive supervision through a continuous quality improvement model. RESULTS: The five functional components of the DQMIS successfully reinforced data reliability, timeliness, completeness, precision, and integrity. The DQMIS also resulted in 98.33% accuracy across all data collection activities in the trial. All data collection activities demonstrated improvement in accuracy throughout implementation. Data collectors demonstrated a statistically significant (p = 0.0004) increase in accuracy throughout consecutive audits. The DQMIS was successful, despite an increase from 20 to 130 data collectors. CONCLUSIONS: In the absence of widely disseminated data quality methods and standards for large RCT interventions in limited-resource settings, we developed an integrated DQA system, combining auditing, rapid data feedback, and supportive supervision, which ensured high-quality data and could serve as a model for future health systems research trials. Future efforts should focus on standardization of DQA processes for health systems research. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02148952 . Registered on 13 February 2014.


Subject(s)
Data Accuracy , Health Services Research/standards , Maternal Health Services/standards , Parturition , Quality Assurance, Health Care/standards , Quality Improvement/standards , Quality Indicators, Health Care/standards , Research Design/standards , Delivery, Obstetric/adverse effects , Delivery, Obstetric/mortality , Female , Humans , India , Infant , Infant Mortality , Infant, Newborn , Maternal Mortality , Pregnancy
6.
Trials ; 17(1): 576, 2016 12 07.
Article in English | MEDLINE | ID: mdl-27923401

ABSTRACT

BACKGROUND: Effective, scalable strategies to improve maternal, fetal, and newborn health and reduce preventable morbidity and mortality are urgently needed in low- and middle-income countries. Building on the successes of previous checklist-based programs, the World Health Organization (WHO) and partners led the development of the Safe Childbirth Checklist (SCC), a 28-item list of evidence-based practices linked with improved maternal and newborn outcomes. Pilot-testing of the Checklist in Southern India demonstrated dramatic improvements in adherence by health workers to essential childbirth-related practices (EBPs). The BetterBirth Trial seeks to measure the effectiveness of SCC impact on EBPs, deaths, and complications at a larger scale. METHODS/DESIGN: This matched-pair, cluster-randomized controlled, adaptive trial will be conducted in 120 facilities across 24 districts in Uttar Pradesh, India. Study sites, identified according to predefined eligibility criteria, were matched by measured covariates before randomization. The intervention, the SCC embedded in a quality improvement program, consists of leadership engagement, a 2-day educational launch of the SCC, and support through placement of a trained peer "coach" to provide supportive supervision and real-time data feedback over an 8-month period with decreasing intensity. A facility-based childbirth quality coordinator is trained and supported to drive sustained behavior change after the BetterBirth team leaves the facility. Study participants are birth attendants and women and their newborns who present to the study facilities for childbirth at 60 intervention and 60 control sites. The primary outcome is a composite measure including maternal death, maternal severe morbidity, stillbirth, and newborn death, occurring within 7 days after birth. The sample size (n = 171,964) was calculated to detect a 15% reduction in the primary outcome. Adherence by health workers to EBPs will be measured in a subset of births (n = 6000). The trial will be conducted in close collaboration with key partners including the Governments of India and Uttar Pradesh, the World Health Organization, an expert Scientific Advisory Committee, an experienced local implementing organization (Population Services International, PSI), and frontline facility leaders and workers. DISCUSSION: If effective, the WHO Safe Childbirth Checklist program could be a powerful health facility-strengthening intervention to improve quality of care and reduce preventable harm to women and newborns, with millions of potential beneficiaries. TRIAL REGISTRATION: BetterBirth Study Protocol dated: 13 February 2014; ClinicalTrials.gov: NCT02148952 ; Universal Trial Number: U1111-1131-5647.


Subject(s)
Checklist , Delivery of Health Care, Integrated/organization & administration , Infant Health , Maternal Health Services/organization & administration , Maternal Health , Patient Care Team/organization & administration , Pregnancy Complications/prevention & control , World Health Organization , Clinical Protocols , Female , Fetal Death/etiology , Fetal Death/prevention & control , Health Status , Humans , India , Infant , Infant Mortality , Infant, Newborn , Leadership , Maternal Mortality , Mentoring , Pregnancy , Pregnancy Complications/diagnosis , Pregnancy Complications/etiology , Pregnancy Complications/mortality , Program Evaluation , Quality Improvement , Quality Indicators, Health Care , Research Design , Risk Assessment , Risk Factors , Severity of Illness Index , Time Factors
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