Newborn signal functions in Bangladesh: identification through expert consultation and assessment of readiness among public health facilities—study protocol using Delphi technique

Rahman, Ahmed Ehsanur; Banik, Goutom; Mhajabin, Shema; Tahsina, Tazeen; Islam, Md. Jahurul; Ahmed, Farid Uddin; Islam, Mushair Ul; Mannan, Abdul; Dey, Sanjoy; Sharmin, Shamina; Mehran, Fida; Khan, Muhammad Abbas; Ahmed, Anisuddin; Sabir, Ahmed Al; Sultana, Shahin; Ahsan, Ziaul; Rubayet, Sayed; George, Joby; Karim, Afsana; Shahidullah, Mohammod; Arifeen, Shams El

doi:10.1136/bmjopen-2020-037418

Cited by 3 publications

(3 citation statements)

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“…Project research physicians (PRPs) measured the variables’ construct and content validity by field testing them in seven different public health facilities. The operational definition of these validity measures is described in the published protocol [ 13 ]. Content validity was analysed using descriptive statistics and it was considered achieved when more than 80% of the newborn Delphi experts agreed that the language of the newly added question appropriately reflects the content/variable that it was supposed to measure.…”

Section: Methodsmentioning

confidence: 99%

“…A set of signal functions is crucial in planning policy and programs for correctly identifying health facilities that provide newborn services. Acknowledging the necessity and significance, NNHP & IMCI Program of the Directorate General of Health Services (DGHS) has designated the identification of newborn signal functions (NSFs) as a priority task for successful planning and scaling-up of newborn interventions in Bangladesh [ 13 ]. This study aimed to identify a set of NSFs, develop a set of indicators and required assessment tools, and assess service availability and readiness of the public health facilities as per NSFs in Bangladesh.…”

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confidence: 99%

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Newborn signal functions in Bangladesh: Identification through expert consultation and assessment of readiness among public health facilities

et al. 2022

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Background This study aimed to identify a set of newborn signal functions (NSFs) that can categorize health facilities and assist policymakers and health managers in appropriately planning and adequately monitoring the progress and performance of health facilities delivering newborn health care in Bangladesh and similar low-income settings. Methods A modified Delphi method was used to identify a set of NSFs and a cross-sectional health facility assessment among the randomly selected facilities was conducted to test them in public health facilities in Bangladesh. In the modified Delphi approach, three main steps of listing, prioritizing, and testing were followed to identify the set of NSFs. Then, to finalize the set of NSFs and its variables, a total of five Delphi workshops and three rounds of Delphi surveys were conducted. Finally, 205 public health facilities located in 41 randomly selected districts were assessed for the availability and readiness of finalized NSFs using the updated tool of Bangladesh Health Facility Survey (BHFS) 2017. Results Twenty NSFs were identified and finalized, nine of which were categorized as primary NSFs, 13 as basic NSFs, 18 as comprehensive NSFs, and 20 as advanced NSFs. Almost all district hospitals (DHs), Upazila health complexes (UHCs,) and maternal and child welfare centres (MCWCs) performed the primary NSFs in the last three months. However, around one-third of the union health and family welfare centres (UH&FWCs) and very few community clinics (CCs) performed them during the same period. The basic, comprehensive, and advanced NSF readiness was inadequate and inappropriate across all types of facilities, including DHs and UHCs. Conclusions In the absence of internationally or nationally agreed-upon NSFs to measure a health facility's service availability and readiness for providing newborn care, this study becomes the first to identify and finalize a set of NSFs and to incorporate relevant variables in the health facility assessment tool which can be used to monitor the availability and readiness of a newborn care facility. The identified NSFs can also be adapted for the countries with similar contexts and can serve as a standard base to determine a global set of NSFs.

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Newborn signal functions in Bangladesh: Identification through expert consultation and assessment of readiness among public health facilities

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“…However, there is as yet no evidence base to inform signal functions for level-2 + SSNC. Ongoing revisions to the emergency obstetric care (EmOC) monitoring framework aim to include expert-informed newborn signal functions for level-2 + care [ 14 , 15 ]. To fill this gap in service readiness measurement for level-2 + SSNC, two new scoring approaches were developed.…”

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confidence: 99%

Quantifying health facility service readiness for small and sick newborn care: comparing standards-based and WHO level-2 + scoring for 64 hospitals implementing with NEST360 in Kenya, Malawi, Nigeria, and Tanzania

Penzias,

Bohne,

Gicheha

et al. 2024

BMC Pediatr

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Background Service readiness tools are important for assessing hospital capacity to provide quality small and sick newborn care (SSNC). Lack of summary scoring approaches for SSNC service readiness means we are unable to track national targets such as the Every Newborn Action Plan targets. Methods A health facility assessment (HFA) tool was co-designed by Newborn Essential Solutions and Technologies (NEST360) and UNICEF with four African governments. Data were collected in 68 NEST360-implementing neonatal units in Kenya, Malawi, Nigeria, and Tanzania (September 2019-March 2021). Two summary scoring approaches were developed: a) standards-based, including items for SSNC service readiness by health system building block (HSBB), and scored on availability and functionality, and b) level-2 + , scoring items on readiness to provide WHO level-2 + clinical interventions. For each scoring approach, scores were aggregated and summarised as a percentage and equally weighted to obtain an overall score by hospital, HSBB, and clinical intervention. Results Of 1508 HFA items, 1043 (69%) were included in standards-based and 309 (20%) in level-2 + scoring. Sixty-eight neonatal units across four countries had median standards-based scores of 51% [IQR 48–57%] at baseline, with variation by country: 62% [IQR 59–66%] in Kenya, 49% [IQR 46–51%] in Malawi, 50% [IQR 42–58%] in Nigeria, and 55% [IQR 53–62%] in Tanzania. The lowest scoring was family-centred care [27%, IQR 18–40%] with governance highest scoring [76%, IQR 71–82%]. For level-2 + scores, the overall median score was 41% [IQR 35–51%] with variation by country: 50% [IQR 44–53%] in Kenya, 41% [IQR 35–50%] in Malawi, 33% [IQR 27–37%] in Nigeria, and 41% [IQR 32–52%] in Tanzania. Readiness to provide antibiotics by culture report was the highest-scoring intervention [58%, IQR 50–75%] and neonatal encephalopathy management was the lowest-scoring [21%, IQR 8–42%]. In both methods, overall scores were low (< 50%) for 27 neonatal units in standards-based scoring and 48 neonatal units in level-2 + scoring. No neonatal unit achieved high scores of > 75%. Discussion Two scoring approaches reveal gaps in SSNC readiness with no neonatal units achieving high scores (> 75%). Government-led quality improvement teams can use these summary scores to identify areas for health systems change. Future analyses could determine which items are most directly linked with quality SSNC and newborn outcomes.

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Health facility assessment of small and sick newborn care in low- and middle-income countries: systematic tool development and operationalisation with NEST360 and UNICEF

Penzias,

Bohne,

Ngwala

et al. 2024

BMC Pediatr

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Background Each year an estimated 2.3 million newborns die in the first 28 days of life. Most of these deaths are preventable, and high-quality neonatal care is fundamental for surviving and thriving. Service readiness is used to assess the capacity of hospitals to provide care, but current health facility assessment (HFA) tools do not fully evaluate inpatient small and sick newborn care (SSNC). Methods Health systems ingredients for SSNC were identified from international guidelines, notably World Health Organization (WHO), and other standards for SSNC. Existing global and national service readiness tools were identified and mapped against this ingredients list. A novel HFA tool was co-designed according to a priori considerations determined by policymakers from four African governments, including that the HFA be completed in one day and assess readiness across the health system. The tool was reviewed by > 150 global experts, and refined and operationalised in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania between September 2019 and March 2021. Results Eight hundred and sixty-six key health systems ingredients for service readiness for inpatient SSNC were identified and mapped against four global and eight national tools measuring SSNC service readiness. Tools revealed major content gaps particularly for devices and consumables, care guidelines, and facility infrastructure, with a mean of 13.2% (n = 866, range 2.2–34.4%) of ingredients included. Two tools covered 32.7% and 34.4% (n = 866) of ingredients and were used as inputs for the new HFA tool, which included ten modules organised by adapted WHO health system building blocks, including: infrastructure, pharmacy and laboratory, medical devices and supplies, biomedical technician workshop, human resources, information systems, leadership and governance, family-centred care, and infection prevention and control. This HFA tool can be conducted at a hospital by seven assessors in one day and has been used in 64 hospitals in Kenya, Malawi, Nigeria, and Tanzania. Conclusion This HFA tool is available open-access to adapt for use to comprehensively measure service readiness for level-2 SSNC, including respiratory support. The resulting facility-level data enable comparable tracking for Every Newborn Action Plan coverage target four within and between countries, identifying facility and national-level health systems gaps for action.

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Newborn signal functions in Bangladesh: identification through expert consultation and assessment of readiness among public health facilities—study protocol using Delphi technique

Cited by 3 publications

References 20 publications

Newborn signal functions in Bangladesh: Identification through expert consultation and assessment of readiness among public health facilities

Newborn signal functions in Bangladesh: Identification through expert consultation and assessment of readiness among public health facilities

Quantifying health facility service readiness for small and sick newborn care: comparing standards-based and WHO level-2 + scoring for 64 hospitals implementing with NEST360 in Kenya, Malawi, Nigeria, and Tanzania

Health facility assessment of small and sick newborn care in low- and middle-income countries: systematic tool development and operationalisation with NEST360 and UNICEF

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