Dataset Information

Association of the Paediatric Admission Quality of Care score with mortality in Kenyan hospitals: a validation study.

ABSTRACT:

Background

Measuring the quality of hospital admission care is essential to ensure that standards of practice are met and continuously improved to reduce morbidity and mortality associated with the illnesses most responsible for inpatient deaths. The Paediatric Admission Quality of Care (PAQC) score is a tool for measuring adherence to guidelines for children admitted with acute illnesses in a low-income setting. We aimed to explore the external and criterion-related validity of the PAQC score by investigating its association with mortality using data drawn from a diverse sample of Kenyan hospitals.

Methods

We identified children admitted to Kenyan hospitals for treatment of malaria, pneumonia, diarrhoea, or dehydration from datasets from three sources: an observational study, a clinical trial, and a national cross-sectional survey. We extracted variables describing the process of care provided to patients at admission and their eventual outcomes from these data. We applied the PAQC scoring algorithm to the data to obtain a quality-of-care score for each child. We assessed external validity of the PAQC score by its systematic replication in datasets that had not been previously used to investigate properties of the PAQC score. We assessed criterion-related validity by using hierarchical logistic regression to estimate the association between PAQC score and the outcome of mortality, adjusting for other factors thought to be predictive of the outcome or responsible for heterogeneity in quality of care.

Findings

We found 19?065 eligible admissions in the three validation datasets that covered 27 hospitals, of which 12?969 (68%) were complete cases. Greater guideline adherence, corresponding to higher PAQC scores, was associated with a reduction in odds of death across the three datasets, ranging between 9% (odds ratio 0·91, 95% CI 0·84-0·99; p=0·031) and 30% (0·70, 0·63-0·78; p<0·0001) adjusted reduction per unit increase in the PAQC score, with a pooled estimate of 17% (0·83, 0·78-0·89; p<0·0001). These findings were consistent with a multiple imputation analysis that used information from all observations in the combined dataset.

Interpretation

The PAQC score, designed as an index of the technical quality of care for the three commonest causes of admission in children, is also associated with mortality. This finding suggests that it could be a meaningful summary measure of the quality of care for common inpatient conditions and supports a link between process quality and outcome. It might have potential for application in low-income countries with similar disease profiles and in which paediatric practice recommendations are based on WHO guidelines.

Funding

The Wellcome Trust.

SUBMITTER: Opondo C

PROVIDER: S-EPMC5785367 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Publications

Association of the Paediatric Admission Quality of Care score with mortality in Kenyan hospitals: a validation study.

Opondo Charles C Allen Elizabeth E Todd Jim J English Mike M

The Lancet. Global health 20180201 2

<h4>Background</h4>Measuring the quality of hospital admission care is essential to ensure that standards of practice are met and continuously improved to reduce morbidity and mortality associated with the illnesses most responsible for inpatient deaths. The Paediatric Admission Quality of Care (PAQC) score is a tool for measuring adherence to guidelines for children admitted with acute illnesses in a low-income setting. We aimed to explore the external and criterion-related validity of the PAQC ...[more]

PMID: 29389541

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Project description:It is increasingly appreciated that the interpretation of health systems research studies is greatly facilitated by detailed descriptions of study context and the process of intervention. We have undertaken an 18-month hospital-based intervention study in Kenya aiming to improve care for admitted children and newborn infants. Here we describe the baseline characteristics of the eight hospitals as environments receiving the intervention, as well as the general and local health system context and its evolution over the 18 months.Hospital characteristics were assessed using previously developed tools assessing the broad structure, process, and outcome of health service provision for children and newborns. Major health system or policy developments over the period of the intervention at a national level were documented prospectively by monitoring government policy announcements, the media, and through informal contacts with policy makers. At the hospital level, a structured, open questionnaire was used in face-to-face meetings with senior hospital staff every six months to identify major local developments that might influence implementation. These data provide an essential background for those seeking to understand the generalisability of reports describing the intervention's effects, and whether the intervention plausibly resulted in these effects.Hospitals had only modest capacity, in terms of infrastructure, equipment, supplies, and human resources available to provide high-quality care at baseline. For example, hospitals were lacking between 30 to 56% of items considered necessary for the provision of care to the seriously ill child or newborn. An increase in spending on hospital renovations, attempts to introduce performance contracts for health workers, and post-election violence were recorded as examples of national level factors that might influence implementation success generally. Examples of factors that might influence success locally included frequent and sometimes numerous staff changes, movements of senior departmental or administrative staff, and the presence of local 'donor' partners with alternative priorities.The effectiveness of interventions delivered at hospital level over periods realistically required to achieve change may be influenced by a wide variety of factors at national and local levels. We have demonstrated how dynamic such contexts are, and therefore the need to consider context when interpreting an intervention's effectiveness.

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Project description:Mortality rates among hospitalized children in many government hospitals in sub-Saharan Africa are high. Pediatric emergency services in these hospitals are often sub-optimal. Timely recognition of critically ill children on arrival is key to improving service delivery. We present a simple risk score to predict inpatient mortality among hospitalized children. Between April 2010 and June 2011, the Uganda Malaria Surveillance Project (UMSP), in collaboration with the National Malaria Control Program (NMCP), set up an enhanced sentinel site malaria surveillance program for children hospitalized at four public hospitals in different districts: Tororo, Apac, Jinja and Mubende. Clinical data collected through March 2013, representing 50249 admissions were used to develop a mortality risk score (derivation data set). One year of data collected subsequently from the same hospitals, representing 20406 admissions, were used to prospectively validate the performance of the risk score (validation data set). Using a backward selection approach, 13 out of 25 clinical parameters recognizable on initial presentation, were selected for inclusion in a final logistic regression prediction model. The presence of individual parameters was awarded a score of either 1 or 2 based on regression coefficients. For each individual patient, a composite risk score was generated. The risk score was further categorized into three categories; low, medium, and high. Patient characteristics were comparable in both data sets. Measures of performance for the risk score included the receiver operating characteristics curves and the area under the curve (AUC), both demonstrating good and comparable ability to predict deathusing both the derivation (AUC =0.76) and validation dataset (AUC =0.74). Using the derivation and validation datasets, the mortality rates in each risk category were as follows: low risk (0.8% vs. 0.7%), moderate risk (3.5% vs. 3.2%), and high risk (16.5% vs. 12.6%), respectively. Our analysis resulted in development of a risk score that ably predicted mortality risk among hospitalized children. While validation studies are needed, this approach could be used to improve existing triage systems.

Project description:OBJECTIVES:To determine the association of hospital nursing skill mix with patient mortality, patient ratings of their care and indicators of quality of care. DESIGN:Cross-sectional patient discharge data, hospital characteristics and nurse and patient survey data were merged and analysed using generalised estimating equations (GEE) and logistic regression models. SETTING:Adult acute care hospitals in Belgium, England, Finland, Ireland, Spain and Switzerland. PARTICIPANTS:Survey data were collected from 13?077 nurses in 243 hospitals, and 18?828 patients in 182 of the same hospitals in the six countries. Discharge data were obtained for 275?519 surgical patients in 188 of these hospitals. MAIN OUTCOME MEASURES:Patient mortality, patient ratings of care, care quality, patient safety, adverse events and nurse burnout and job dissatisfaction. RESULTS:Richer nurse skill mix (eg, every 10-point increase in the percentage of professional nurses among all nursing personnel) was associated with lower odds of mortality (OR=0.89), lower odds of low hospital ratings from patients (OR=0.90) and lower odds of reports of poor quality (OR=0.89), poor safety grades (OR=0.85) and other poor outcomes (0.80<OR<0.93), after adjusting for patient and hospital factors. Each 10 percentage point reduction in the proportion of professional nurses is associated with an 11% increase in the odds of death. In our hospital sample, there were an average of six caregivers for every 25 patients, four of whom were professional nurses. Substituting one nurse assistant for a professional nurse for every 25 patients is associated with a 21% increase in the odds of dying. CONCLUSIONS:A bedside care workforce with a greater proportion of professional nurses is associated with better outcomes for patients and nurses. Reducing nursing skill mix by adding nursing associates and other categories of assistive nursing personnel without professional nurse qualifications may contribute to preventable deaths, erode quality and safety of hospital care and contribute to hospital nurse shortages.

Dataset Information

Association of the Paediatric Admission Quality of Care score with mortality in Kenyan hospitals: a validation study.

Background

Methods

Findings

Interpretation

Funding

Publications

Association of the Paediatric Admission Quality of Care score with mortality in Kenyan hospitals: a validation study.

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