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Can a community health worker administered postnatal checklist increase health-seeking behaviors and knowledge?: evidence from a randomized trial with a private maternity facility in Kiambu County, Kenya.

ABSTRACT: Since the 2009 WHO and UNICEF recommendation that women receive home-based postnatal care within the first three days after birth, a growing number of low-income countries have explored integrating postnatal home visit interventions into their maternal and newborn health strategies. This randomized trial evaluates a pilot program in which community health workers (CHWs) visit or call new mothers three days after delivery in peri-urban Kiambu County, Kenya.Participants were individually randomized to one of three groups: 1) early postnatal care three days after delivery provided in-person with a CHW using a simple checklist, 2) care provided by phone with a CHW using the same checklist, or 3) a standard of care group. Surveys were conducted ten days and nine weeks postnatal to measure outcomes related to compliance with referrals, self-reported health problems for mother and baby, care-seeking behaviors, and postnatal knowledge and practices around the recognition of danger signs, feeding, nutrition, infant care and family planning.The home visit administration of the checklist increased the likelihood that women recognized postnatal problems for themselves and their babies and increased the likelihood that they sought care to address those problems identified for the child. In both the home visit and mobile phone implementation of the checklist, actions taken for postnatal problems happened earlier, particularly for infants. Knowledge was found to be high across all groups, with limited evidence that the checklist impacted knowledge and postnatal practices around the recognition of danger signs, feeding, nutrition, infant care and family planning.We find evidence that CHW-administered postnatal checklists can lead to better recognition of postnatal problems and more timely care-seeking. Furthermore, our results suggest that CHWs can affordably deliver many of the benefits of postnatal checklists.ClinicalTrials.gov NCT02104635 ; registered April 2, 2014.

SUBMITTER: McConnell M

PROVIDER: S-EPMC4893209 | biostudies-literature | 2016 Jun

REPOSITORIES: biostudies-literature

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Can a community health worker administered postnatal checklist increase health-seeking behaviors and knowledge?: evidence from a randomized trial with a private maternity facility in Kiambu County, Kenya.

McConnell Margaret M Ettenger Allison A Rothschild Claire Watt CW Muigai Faith F Cohen Jessica J

BMC pregnancy and childbirth 20160604 1

<h4>Background</h4>Since the 2009 WHO and UNICEF recommendation that women receive home-based postnatal care within the first three days after birth, a growing number of low-income countries have explored integrating postnatal home visit interventions into their maternal and newborn health strategies. This randomized trial evaluates a pilot program in which community health workers (CHWs) visit or call new mothers three days after delivery in peri-urban Kiambu County, Kenya.<h4>Methods</h4>Parti ...[more]

PMID: 27260500

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Project description:BackgroundPrompt and effective case management is needed to reduce malaria morbidity and mortality. However, malaria diagnosis and treatment is a multistep process that remains problematic in many settings, resulting in missed opportunities for effective treatment as well as overtreatment of patients without malaria.MethodsPrior to the widespread roll-out of malaria rapid diagnostic tests (RDTs) in late 2011, a national, cross-sectional, complex-sample, health facility survey was conducted in Malawi to assess patient-, health worker-, and health facility-level factors associated with malaria case management quality using multivariate Poisson regression models.ResultsAmong the 2,019 patients surveyed, 34% had confirmed malaria defined as presence of fever and parasitaemia on a reference blood smear. Sixty-seven per cent of patients with confirmed malaria were correctly prescribed the first-line anti-malarial, with most cases of incorrect treatment due to missed diagnosis; 31% of patients without confirmed malaria were overtreated with an anti-malarial. More than one-quarter of patients were not assessed for fever or history of fever by health workers. The most important determinants of correct malaria case management were patient-level clinical symptoms, such as spontaneous complaint of fever to health workers, which increased both correct treatment and overtreatment by 72 and 210%, respectively (p<0.0001). Complaint of cough was associated with a 27% decreased likelihood of correct malaria treatment (p=0.001). Lower-level cadres of health workers were more likely to prescribe anti-malarials for patients, increasing the likelihood of both correct treatment and overtreatment, but no other health worker or health facility-level factors were significantly associated with case management quality.ConclusionsIntroduction of RDTs holds potential to improve malaria case management in Malawi, but health workers must systematically assess all patients for fever, and then test and treat accordingly, otherwise, malaria control programmes might miss an opportunity to dramatically improve malaria case management, despite better diagnostic tools.

Project description:BACKGROUND:While health worker strikes are experienced globally, the effects can be worst in countries with infrastructural and resource challenges, weak institutional arrangements, underdeveloped organizational ethics codes, and unaffordable alternative options for the poor. In Kenya, there have been a series of public health worker strikes in the post devolution period. We explored the perceptions and experiences of frontline health managers and community members of the 2017 prolonged health workers' strikes. METHODS:We employed an embedded research approach in one county in the Kenyan Coast. We collected in-depth qualitative data through informal observations, reflective meetings, individual and group interviews and document reviews (n =?5), and analysed the data using a thematic approach. Individual interviews were held with frontline health managers (n?=?26), and group interviews with community representatives (4 health facility committee member groups, and 4 broader community representative groups). Interviews were held during and immediately after the nurses' strike. FINDINGS:In the face of major health facility and service closures and disruptions, frontline health managers enacted a range of strategies to keep key services open, but many strategies were piecemeal, inconsistent and difficult to sustain. Interviewees reported huge negative health and financial strike impacts on local communities, and especially the poor. There is limited evidence of improved health system preparedness to cope with any future strikes. CONCLUSION:Strikes cannot be seen in isolation of the prevailing policy and health systems context. The 2017 prolonged strikes highlight the underlying and longer-term frustration amongst public sector health workers in Kenya. The health system exhibited properties of complex adaptive systems that are interdependent and interactive. Reactive responses within the public system and the use of private healthcare led to limited continued activity through the strike, but were not sufficient to confer resilience to the shock of the prolonged strikes. To minimise the negative effects of strikes when they occur, careful monitoring and advanced planning is needed. Planning should aim to ensure that emergency and other essential services are maintained, threats between staff are minimized, health worker demands are reasonable, and that governments respect and honor agreements.

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Project description:BackgroundA simple indicator of technical efficiency, such as productivity of health workers, measured using routine health facility data, can be a practical approach that can inform initiatives to improve efficiency in low- and middle-income countries. This paper presents a proof of concept of using routine information from primary healthcare (PHC) facilities to measure health workers' productivity and its application in three regions of Ethiopia.MethodsIn four steps, we constructed a productivity measure of the health workforce of Health Centers (HCs) and demonstrated its practical application: (1) developing an analytical dataset using secondary data from health management information systems (HMIS) and human resource information system (HRIS); (2) principal component analysis and factor analysis to estimate a summary measure of output from five indicators (annual service volume of outpatient visits, family planning, first antenatal care visits, facility-based deliveries by skilled birth attendants, and children [< 1 year] with three pentavalent vaccines); (3) calculating a productivity score by combining the summary measure of outputs and the total number of health workers (input), and (4) implementing regression models to identify the determinant of productivity and ranking HCs based on their adjusted productivity score.ResultsWe developed an analytical dataset of 1128 HCs; however, significant missing values and outliers were reported in the data. The principal component and factor scores developed from the five output measures were highly consistent (correlation coefficient = 0.98). We considered the factor score as the summary measure of outputs for estimating productivity. A very weak association was observed between the summary measure of output and the total number of staff. The result also highlighted a large variability in productivity across similar health facilities in Ethiopia, represented by the significant dispersion in summary measure of output occurring at similar levels of the health workers.ConclusionsWe successfully demonstrated the analytical steps to estimate health worker productivity and its practical application using HMIS and HRIS. The methodology presented in this study can be readily applied in low- and middle-income countries using widely available data-such as DHIS2-that will allow further explorations to understand the causes of technical inefficiencies in the health system.

Dataset Information

Can a community health worker administered postnatal checklist increase health-seeking behaviors and knowledge?: evidence from a randomized trial with a private maternity facility in Kiambu County, Kenya.

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Can a community health worker administered postnatal checklist increase health-seeking behaviors and knowledge?: evidence from a randomized trial with a private maternity facility in Kiambu County, Kenya.

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