11 research outputs found

    Quality of hospital care for sick newborns and severely malnourished children in Kenya: A two-year descriptive study in 8 hospitals

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    BACKGROUND: Given the high mortality associated with neonatal illnesses and severe malnutrition and the development of packages of interventions that provide similar challenges for service delivery mechanisms we set out to explore how well such services are provided in Kenya. METHODS: As a sub-component of a larger study we evaluated care during surveys conducted in 8 rural district hospitals using convenience samples of case records. After baseline hospitals received either a full multifaceted intervention (intervention hospitals) or a partial intervention (control hospitals) aimed largely at improving inpatient paediatric care for malaria, pneumonia and diarrhea/dehydration. Additional data were collected to: i) examine the availability of routine information at baseline and their value for morbidity, mortality and quality of care reporting, and ii) compare the care received against national guidelines disseminated to all hospitals. RESULTS: Clinical documentation for neonatal and malnutrition admissions was often very poor at baseline with case records often entirely missing. Introducing a standard newborn admission record (NAR) form was associated with an increase in median assessment (IQR) score to 25/28 (22-27) from 2/28 (1-4) at baseline. Inadequate and incorrect prescribing of penicillin and gentamicin were common at baseline. For newborns considerable improvements in prescribing in the post baseline period were seen for penicillin but potentially serious errors persisted when prescribing gentamicin, particularly to low-birth weight newborns in the first week of life. Prescribing essential feeds appeared almost universally inadequate at baseline and showed limited improvement after guideline dissemination. CONCLUSION: Routine records are inadequate to assess newborn care and thus for monitoring newborn survival interventions. Quality of documented inpatient care for neonates and severely malnourished children is poor with limited improvement after the dissemination of clinical practice guidelines. Further research evaluating approaches to improving care for these vulnerable groups is urgently needed. We also suggest pre-service training curricula should be better aligned to help improve newborn survival particularly

    Moving towards routine evaluation of quality of inpatient pediatric care in Kenya.

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    BACKGROUND: Regular assessment of quality of care allows monitoring of progress towards system goals and identifies gaps that need to be addressed to promote better outcomes. We report efforts to initiate routine assessments in a low-income country in partnership with government. METHODS: A cross-sectional survey undertaken in 22 'internship training' hospitals across Kenya that examined availability of essential resources and process of care based on review of 60 case-records per site focusing on the common childhood illnesses (pneumonia, malaria, diarrhea/dehydration, malnutrition and meningitis). RESULTS: Availability of essential resources was 75% (45/61 items) or more in 8/22 hospitals. A total of 1298 (range 54-61) case records were reviewed. HIV testing remained suboptimal at 12% (95% CI 7-19). A routinely introduced structured pediatric admission record form improved documentation of core admission symptoms and signs (median score for signs 22/22 and 8/22 when form used and not used respectively). Correctness of penicillin and gentamicin dosing was above 85% but correctness of prescribed intravenous fluid or oral feed volumes for severe dehydration and malnutrition were 54% and 25% respectively. Introduction of Zinc for diarrhea has been relatively successful (66% cases) but use of artesunate for malaria remained rare. Exploratory analysis suggests considerable variability of the quality of care across hospitals. CONCLUSION: Quality of pediatric care in Kenya has improved but can improve further. The approach to monitoring described in this survey seems feasible and provides an opportunity for routine assessments across a large number of hospitals as part of national efforts to sustain improvement. Understanding variability across hospitals may help target improvement efforts

    Documentation trends of disease specific key essential signs and symptoms.

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    <p>Documentation score of essential disease specific signs and symptoms stratified by PAR use for cases with no co-morbidities; x-axis is the documentation score with the disease total being the maximum value of x. *Outliers excluded.</p

    Definition of the composite indicators of processes of care for each of the diseases.

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    <p>AVPU- consciousness level documented as Alert, Verbal response, Pain response, Unresponsive; ORS-Oral rehydration solution</p><p>Definition of the composite indicators of processes of care for each of the diseases.</p

    Organization of care and availability of essential resources.

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    <p>Percentage availability is determined as the proportion of 22 hospitals in which the specific item is present. 3 items available in less than 20% (4/22) of the hospitals were omitted. **Otoscope and torch omitted in essential equipment domain; * Ampicillin omitted in antibiotics domain.</p

    Structure items assessed for by domain.

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    <p>NGT –Nasogastric tube; PMTCT-Prevention of Mother to Child Transmission; IV- Intra-venous</p><p>The total number of items assessed per domain form the total score of items expected from each domain</p><p>Items in the feeds and minerals, IV fluids and antibiotics were based on those that are listed in the essential medicines and commodities list.</p><p>Structure items assessed for by domain.</p

    Performance of disease specific guideline recommended process indicators.

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    <p>*Indicators are defined in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0117048#pone.0117048.t001" target="_blank">Table 1</a>.</p><p>Performance of disease specific guideline recommended process indicators.</p

    Variability of hospital performance across indicators.

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    <p>Variability funnel plots: X axis represents number of cases available for the indicator per hospital, Y axis represents the proportion of patients that achieve the indicator per hospital while the numbers against the data points are the hospital identifiers. The red line is the mean performance across hospitals while the dashed lines represent the 95% and 99% confidence intervals.</p
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