Dataset Information

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

ABSTRACT:

Background

Mobile health (mHealth) is showing increasing potential to address health outcomes in underresourced settings as smartphone coverage increases. The NeoTree is an mHealth app codeveloped in Malawi to improve the quality of newborn care at the point of admission to neonatal units. When collecting vital demographic and clinical data, this interactive platform provides clinical decision support and training for the end users (health care professionals [HCPs]), according to evidence-based national and international guidelines.

Objective

This study aims to examine 1 month's data collected using NeoTree in an outcome audit of babies admitted to a district-level neonatal nursery in Malawi and to demonstrate proof of concept of digital outcome audit data in this setting.

Methods

Using a phased approach over 1 month (November 21-December 19, 2016), frontline HCPs were trained and supported to use NeoTree to admit newborns. Discharge data were collected by the research team using a discharge form within NeoTree, called NeoDischarge. We conducted a descriptive analysis of the exported pseudoanonymized data and presented it to the newborn care department as a digital outcome audit.

Results

Of 191 total admissions, 134 (70.2%) admissions were completed using NeoTree, and 129 (67.5%) were exported and analyzed. Of 121 patients for whom outcome data were available, 102 (84.3%) were discharged alive. The overall case fatality rate was 93 per 1000 admitted babies. Prematurity with respiratory distress syndrome, birth asphyxia, and neonatal sepsis contributed to 25% (3/12), 58% (7/12), and 8% (1/12) of deaths, respectively. Data were more than 90% complete for all fields. Deaths may have been underreported because of phased implementation and some families of babies with imminent deaths self-discharging home. Detailed characterization of the data enabled departmental discussion of modifiable factors for quality improvement, for example, improved thermoregulation of infants.

Conclusions

This digital outcome audit demonstrates that data can be captured digitally at the bedside by HCPs in underresourced newborn facilities, and these data can contribute to a meaningful review of the quality of care, outcomes, and potential modifiable factors. Coverage may be improved during future implementation by streamlining the admission process to be solely via digital format. Our results present a new methodology for newborn audits in low-resource settings and are a proof of concept for a novel newborn data system in these settings.

SUBMITTER: Crehan C

PROVIDER: S-EPMC7641784 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

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

Crehan Caroline C Kesler Erin E Chikomoni Indira Angela IA Sun Kristi K Dube Queen Q Lakhanpaul Monica M Heys Michelle M

JMIR mHealth and uHealth 20201021 10

<h4>Background</h4>Mobile health (mHealth) is showing increasing potential to address health outcomes in underresourced settings as smartphone coverage increases. The NeoTree is an mHealth app codeveloped in Malawi to improve the quality of newborn care at the point of admission to neonatal units. When collecting vital demographic and clinical data, this interactive platform provides clinical decision support and training for the end users (health care professionals [HCPs]), according to evidenc ...[more]

PMID: 33084581

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Project description:Introduction: Understanding the extent and cause of high neonatal deaths rates in Sub-Saharan Africa is a challenge, especially in the presence of poor-quality and inaccurate data. The NeoTree digital data capture and quality improvement system has been live at Kamuzu Central Hospital, Neonatal Unit, Malawi, since April 2019. Objective: To describe patterns of admissions and outcomes in babies admitted to a Malawian neonatal unit over a 1-year period via a prototype data dashboard. Methods: Data were collected prospectively at the point of care, using the NeoTree app, which includes digital admission and outcome forms containing embedded clinical decision and management support and education in newborn care according to evidence-based guidelines. Data were exported and visualised using Microsoft Power BI. Descriptive and inferential analysis statistics were executed using R. Results: Data collected via NeoTree were 100% for all mandatory fields and, on average, 96% complete across all fields. Coverage of admissions, discharges, and deaths was 97, 99, and 91%, respectively, when compared with the ward logbook. A total of 2,732 neonates were admitted and 2,413 (88.3%) had an electronic outcome recorded: 1,899 (78.7%) were discharged alive, 12 (0.5%) were referred to another hospital, 10 (0.4%) absconded, and 492 (20%) babies died. The overall case fatality rate (CFR) was 204/1,000 admissions. Babies who were premature, low birth weight, out born, or hypothermic on admission, and had significantly higher CFR. Lead causes of death were prematurity with respiratory distress (n = 252, 51%), neonatal sepsis (n = 116, 23%), and neonatal encephalopathy (n = 80, 16%). The most common perceived modifiable factors in death were inadequate monitoring of vital signs and suboptimal management of sepsis. Two hundred and two (8.1%) neonates were HIV exposed, of whom a third [59 (29.2%)] did not receive prophylactic nevirapine, hence vulnerable to vertical infection. Conclusion: A digital data capture and quality improvement system was successfully deployed in a low resource neonatal unit with high (1 in 5) mortality rates providing and visualising reliable, timely, and complete data describing patterns, risk factors, and modifiable causes of newborn mortality. Key targets for quality improvement were identified. Future research will explore the impact of the NeoTree on quality of care and newborn survival.

Project description:BackgroundNeonatal mortality is high in low-resource settings. NeoTree is a digital intervention for neonatal healthcare professionals (HCPs) aiming to achieve data-driven quality improvement and improved neonatal survival in low-resource hospitals. Optimising usability with end-users could help digital health interventions succeed beyond pilot stages in low-resource settings. Usability is the quality of a user's experience when interacting with an intervention, encompassing their effectiveness, efficiency, and overall satisfaction.ObjectiveTo evaluate the usability and usage of NeoTree beta-app and conduct Agile usability-focused intervention development.MethodA real-world pilot of NeoTree beta-app was conducted over 6 months at Kamuzu Central Hospital neonatal unit, Malawi. Prior to deployment, think-aloud interviews were conducted to guide nurses through the app whilst voicing their thoughts aloud (n = 6). System Usability Scale (SUS) scores were collected before the implementation of NeoTree into usual clinical care and 6 months after implementation (n = 8 and 8). During the pilot, real-world user-feedback and user-data were gathered. Feedback notes were subjected to thematic analysis within an Agile "product backlog." For usage, number of users, user-cadre, proportion of admissions/outcomes recorded digitally, and median app-completion times were calculated.ResultsTwelve overarching usability themes generated 57 app adjustments, 39 (68%) from think aloud analysis and 18 (32%) from the real-world testing. A total of 21 usability themes/issues with corresponding app features were produced and added to the app. Six themes relating to data collection included exhaustiveness of data schema, prevention of errors, ease of progression, efficiency of data entry using shortcuts, navigation of user interface (UI), and relevancy of content. Six themes relating to the clinical care included cohesion with ward process, embedded education, locally coherent language, adaptability of user-interface to available resources, and printout design to facilitate handover. SUS scores were above average (88.1 and 89.4 at 1 and 6 months, respectively). Ninety-three different HCPs of 5 cadres, recorded 1,323 admissions and 1,197 outcomes over 6 months. NeoTree achieved 100% digital coverage of sick neonates admitted. Median completion times were 16 and 8 min for admissions and outcomes, respectively.ConclusionsThis study demonstrates optimisation of a digital health app in a low-resource setting and could inform other similar usability studies apps in similar settings.

Project description:BackgroundOver one million babies are stillborn or die within the first 28 days of life each year due to preventable causes and poor-quality care in resource-constrained countries. Death audit may be a valuable tool for improving quality of care and decreasing mortality. However, challenges in implementing audit and their subsequent action plans have been reported, with few successfully implemented and sustained. This study aimed to identify factors that affect stillbirth and neonatal death audit at the facility level in the southern region of Malawi.MethodsThirty-eight semi-structured interviews and seven focus group discussions with death audit committee members were conducted. Thematic analysis was guided by a conceptual framework applied deductively, combined with inductive line-by-line coding to identify additional emerging themes.ResultsThe factors that affected audit at individual, facility and national level were related to training, staff motivation, power dynamics and autonomy, audit organisation and data support. We found that factors were linked because they informed each other. Inadequate staff training was caused by a lack of financial allocation at the facility level and donor-driven approaches to training at the national level, with training taking place only with support from funders. Staff motivation was affected by the institutional norms of reliance on monetary incentives during meetings, gazetted at the national level so that audits happened only if such incentives were available. This overshadowed other benefits and non-monetary incentives which were not promoted at the facility level. Inadequate resources to support audit were informed by limited facility-level autonomy and decision-making powers which remained controlled at the national level despite decentralisation. Action plan implementation challenges after audit meetings resulted from inadequate support at the facility level and inadequate audit policy and guidelines at the national level. Poor documentation affected audit processes informed by inadequate supervision and promotion of data usage at both facility and national levels.ConclusionsGiven that the factors that facilitate or inhibit audits are interconnected, implementers, policymakers and managers need to be aware that addressing barriers is likely to require a whole health systems approach targeting all system levels. This will require behavioural and complex intervention approaches.

Project description:BackgroundParents of preterm infants increasingly use their mobile phone to search for health information. In a recent review, websites targeted toward parents with infants in the neonatal intensive care unit (NICU) were found to have poor to moderate quality educational material; however, there is a dearth of literature regarding mobile apps for NICU parents.ObjectiveThis study aimed to identify and evaluate apps targeting parents of infants in the NICU for quality of information, usability, and credibility.MethodsWe systematically searched the Apple App Store and Google Play using 49 key terms (eg, "preterm infant") from July 26 to August 18, 2017. English apps targeting NICU parents that cost less than $20 were included. Apps for health care professionals, e-books/magazines, or nonrelevant results were excluded. In total, 3 tools were used for evaluation: Mobile Application Rating Scale (MARS) to measure quality; Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-AV) to measure the app's content usability; and Trust it or Trash It to measure credibility.ResultsThe initial search yielded 6579 apps, with 49 apps eligible after title and description screening. In total, 27 apps met the eligibility criteria with 9 apps available in both app stores; of those, the app with the most recent update date was chosen to be included in the analysis. Thus, 18 unique apps were included for final analysis. Using MARS, 7 apps (7/18, 39%) received a good score on overall quality (ie, 4.0 out of 5.0), with none receiving an excellent score. In addition, 8 apps (8/18, 44%) received a PEMAT-AV score between 51% and 75% on the understandability subscale, and 8 apps (8/18, 44%) scored between 76% and 100% on the actionability subscale. Trust It or Trash It deemed 13 apps (13/18, 72%) as trash for reasons including no identification of sources or lack of current information, with only 5 (5/18, 28%) deemed trustworthy. Reviewer's expert evaluation found 16 apps contained content that matched information provided by multiple sources; however, most apps did not meet other objective measurement items to support credibility. When comparing the MARS overall quality and subjective quality scores with trustworthiness of apps, there was no statistically significant difference. A statistically significant difference was found between the 2 MARS quality scores, indicating that, on average, apps were ranked significantly lower on subjective quality compared with overall quality measures.ConclusionsThis evaluation revealed that of the available apps targeting NICU parents, less than half should be considered as acceptable educational material. Over two-thirds of the apps were found to have issues regarding credibility and just over a quarter were considered good quality. The apps currently available for NICU parents are lacking and of concern in terms of quality and credibility.

Project description:BackgroundAudits provide a rational framework for quality improvement by systematically assessing clinical practices against accepted standards with the aim to develop recommendations and interventions that target modifiable deficiencies in care. Most childbirth-associated mortality audits in developing countries are focused on a single facility and, up to now, the avoidable factors in maternal and perinatal deaths cataloged in these reports have not been pooled and analyzed. We sought to identity the most frequent avoidable factors in childbirth-related deaths globally through a systematic review of all published mortality audits in low and lower-middle income countries.MethodsWe performed a systematic review of published literature from 1965 to November 2011 in Pubmed, Embase, CINAHL, POPLINE, LILACS and African Index Medicus. Inclusion criteria were audits from low and lower-middle income countries that identified at least one avoidable factor in maternal or perinatal mortality. Each study included in the analysis was assigned a quality score using a previously published instrument. A meta-analysis was performed for each avoidable factor taking into account the sample sizes and quality score from each individual audit. The study was conducted and reported according to PRISMA guidelines for systematic reviews.ResultsThirty-nine studies comprising 44 datasets and a total of 6,205 audited deaths met inclusion criteria. The analysis yielded 42 different avoidable factors, which fell into four categories: health worker-oriented factors, patient-oriented factors, transport/referral factors, and administrative/supply factors. The top three factors by attributable deaths were substandard care by a health worker, patient delay, and deficiencies in blood transfusion capacity (accounting for 688, 665, and 634 deaths attributable, respectively). Health worker-oriented factors accounted for two-thirds of the avoidable factors identified.ConclusionsAudits provide insight into where systematic deficiencies in clinical care occur and can therefore provide crucial direction for the targeting of interventions to mitigate or eliminate health system failures. Given that the main causes of maternal and perinatal deaths are generally consistent across low resource settings, the specific avoidable factors identified in this review can help to inform the rational design of health systems with the aim of achieving continued progress towards Millennium Development Goals Four and Five.

Project description:BackgroundMaternal and child health (MCH)-related mobile apps are becoming increasingly popular among pregnant women; however, few apps have demonstrated that they lead to improvements in pregnancy outcomes.ObjectiveThis study aims to investigate the use of MCH apps among pregnant women in China and explore associations with pregnancy outcomes.MethodsA retrospective study was conducted at 6 MCH hospitals in northern China. Women who delivered a singleton baby at >28 weeks' gestation at the study hospitals were sequentially recruited from postnatal wards from October 2017 to January 2018. Information was collected on the women's self-reported MCH app use during their pregnancy, along with clinical outcomes. Women were categorized as nonusers of MCH apps and users (further divided into intermittent users and continuous users). The primary outcome was a composite adverse pregnancy outcome (CAPO) comprising preterm birth, birth weight <2500 g, birth defects, stillbirth, and neonatal asphyxia. The association between app use and CAPO was explored using multivariable logistic analysis.ResultsThe 1850 participants reported using 127 different MCH apps during pregnancy. App use frequency was reported as never, 24.7% (457/1850); intermittent, 47.4% (876/1850); and continuous, 27.9% (517/1850). Among app users, the most common reasons for app use were health education (1393/1393, 100%), self-monitoring (755/1393, 54.2%), and antenatal appointment reminders (602/1393, 43.2%). Nonusers were older, with fewer years of education, lower incomes, and higher parity (P<.01). No association was found between any app use and CAPO (6.8% in nonusers compared with 6.3% in any app users; odds ratio 0.77, 95% CI 0.48-1.25).ConclusionsWomen in China access a large number of different MCH apps, with social disparities in access and frequency of use. Any app use was not found to be associated with improved pregnancy outcomes, highlighting the need for rigorous development and testing of apps before recommendation for use in clinical settings.

Dataset Information

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

Background

Objective

Methods

Results

Conclusions

Publications

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

Similar Datasets

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