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Abstract
Background There is no documented experience in the use of the WHO standards for improving the quality of care (QOC) for children at the facility level. We describe the use of 10 prioritised WHO-Standard-based Quality Measures to assess QOC for children with acute diarrhoea (AD) in Italy.
Methods In a multicentre observational study in 11 paediatric emergency departments with different characteristics and geographical location, we collected data on 3061 children aged 6 months to 15 years with AD and no complications. Univariate and multivariate analyses were conducted.
Results Study findings highlighted both good practices and gaps in QoC, with major differences in QOC across facilities. Documentation of body weight and temperature varied from 7.7% to 98.5% and from 50% to 97.7%, respectively (p<0.001); antibiotic and probiotic prescription rates ranged from 0% to 10.1% and from 0% to 80.8%, respectively (p<0.001); hospitalisations rates ranged between 8.5% and 62.8% (p<0.001); written indications for reassessment were provided in 10.4%–90.2% of cases (p<0.001). When corrected for children’s individual characteristics, the variable more consistently associated with each analysed outcome was the individual facility. Higher rates of antibiotics prescription (+7.6%, p=0.04) and hospitalisation (+52.9%, p<0.001) were observed for facilities in Southern Italy, compared with university centres (−36%, p<0.001), independently from children characteristics. Children’s clinical characteristics in each centre were not associated with either hospitalisation or antibiotic prescription rates.
Conclusions The 10 prioritised WHO-Standard-based Quality Measures allow a rapid assessment of QOC in children with AD. Action is needed to identify and implement sustainable and effective interventions to ensure high QOC for all children.
- Qualitative research
Data availability statement
Data are available upon reasonable request.
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WHAT IS ALREADY KNOWN ON THIS TOPIC
Previous studies conducted in the European region highlighted substandard practices in the quality of care (QOC) for children with diarrhoea, but limited evidence exists from Italy. WHO published in 2018 a set of Standards for improving the QOC for children, but no study so far described their implementation.
WHAT THIS STUDY ADDS
The utilisation of 10 prioritised WHO-Standard-based Quality Measures to assess the provision of care for children with diarrhoea across 11 Italian emergency departments revealed significant differences across hospitals—in particular on the prescription of probiotics, hospitalisation rates and on indications for reassessment—persisting even after the correction by children characteristics.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
The 10 WHO-Standard-based Quality Measures offer a rapid assessment of QOC in children with diarrhoea, providing policymakers and practitioners valuable evidence for planning interventions aiming at improving and unfirming practices of care.
Background
High-income countries in the WHO European region show the lowest rates of child mortality worldwide, together with North America and Australia.1 2 However, even in high-income countries, quality of care (QOC) has been reported as heterogeneous.3–9 Specific to children with acute diarrhoea, a recent WHO report3 highlighted that, across the European region, the rate of children with diarrhoea receiving oral rehydration therapy and continued feeding ranged between 61% in Switzerland and 22% in Turkey. A multicentre study in the UK observed that the admission rates for children with common conditions such as diarrhoea varied substantially by single emergency department (ED).4 A multicentre study in Canada and the USA, reported significant heterogeneity in the frequency of admissions to ED and use of intravenous fluids among children with gastroenteritis,5 while another multicountry survey noted significant variation in antibiotic prescription in children with febrile enteritis.6
Yet very few multicentre studies provided information on key indicators of QOC for children with diarrhoea,10 thus hampering monitoring and action to improve QOC.3 11 According to a WHO survey in the European Region, data on diarrhoea treatment were available only from 16 out of 53 countries,3 despite diarrhoea treatment being recognised as a key sentinel indicator for the Sustainable Development Goals for 2030.11 12 In general, as pointed out by a systematic review, existing literature on the paediatrics inpatient QOC in high-income settings is still limited.13
WHO developed in 2018 a list of ‘Standards for improving the QOC for children and young adolescents at facility level’.14 Such WHO standards are expected to be implemented following the ‘Plan Do Study Act’ cycle, which implies, as a first step, a baseline assessment prioritising the Quality Measures most relevant to each local context.14 However, there is a lack of experience in using WHO standards.14 In 2019, in dialogue with WHO, we established a multicountry study called CHOICE (Child HOspItal CarE), with the objective of conducting implementation research on the WHO standards in high and middle-income countries.14 Preliminary products of the CHOICE study, including WHO Quality Measures prioritised,14 identification of data sources and the validation of data collection tools, have been reported elsewhere.15 The present paper relates to the initial implementation (ie, the baseline assessment) of the WHO standards and reports specifically on the ‘provision of care’ for acute diarrhoea (AD), and factors affecting it across facilities with different characteristics. The paper complements other manuscripts included in a journal collection and reporting on other children’s conditions (ie, acute respiratory infections and pain management), as well as on other domains of QOC (experience of care, resources), for a total of 175 WHO Standard-based Quality Measures reported (online supplemental table 1).
Supplemental material
Methods
Study design
This was a multicentre observational study and it is reported according to the Strengthening the Reporting of Observational studies in Epidemiology (STROBE) Statement.16 The STROBE Checklist is provided in online supplemental table 2.
Study population
The study was conducted in 11 EDs, distributed across the Italian geographical territory (north, centre and south) and including facilities with different characteristics in terms of volume of work, facility level (referral facilities vs lower levels) and type (university vs non-university hospital), as detailed in online supplemental table 3.
We included children with an age between 6 months and 15 years and AD, with or without fever, with or without vomiting, accessing the EDs over 2 years (from January 2019 to December 2020). Children with any bloody stool and persistent diarrhoea (>10 days) and children with underlying conditions—such as inflammatory bowel disease, malnutrition, immunodepression or any other underlying infection/condition that may require antibiotic therapy—were excluded.
Study variables and data collection
A set of WHO Quality Measures to assess ‘provision of care’ in paediatric ED on three common paediatric conditions (Acute Respiratory Infections - ARI, AD and pain) was prioritised through a Delphi process17 by a team of experts with long-term experience in developing and/or using WHO standards as well as other standards proposed by scientific societies18 (details in online supplemental table 1). Among these, 10 were pertinent to AD, and specifically, 3 were pertinent to the clinical assessment of the patients and 7 to treatment. Data on socio-demographic variables of children were also collected.
Data were extracted from discharge letters, which in Italy are the official written reports provided by the doctor in charge to the family at the time of discharge, including all relevant aspects of the child assessment and treatment. The data extraction tool was designed as a standardised Excel document with explicit guidelines for completion and pre-established tables for data entry. It underwent practical testing by an impartial data collector across 660 cases, and subsequent refinements were made based on the feedback received during the field test. These improvements included the incorporation of more thorough and explicit instructions directly within the tool. Data were extracted by independent researchers, adequately trained, under the supervision of an independent data analyst and of a senior paediatrician. Cases were selected at random, and, to avoid seasonality bias, the sample was equally distributed across seasons. According to the seasonal pattern of Italy, four seasons of 3 months each were identified. If cases in one season were lacking to reach the total sample, this was achieved by equally dividing the remaining cases across the remaining seasons.
Data analysis
The minimum sample size for inclusion for each hospital was 115 cases, based on an expected minimum frequency for each indicator of 4% and an absolute precision of 97.5%. For the year 2020, given the drastic reduction of access to paediatric EDs due to the COVID-19 pandemic, the sample was set as the maximum number of available cases with the given case definition in each facility. One facility (C11), due to the reorganisation changes during the COVID-19 emergency, was unable to provide any data for the year 2020.
First, we conducted a descriptive analysis of patients’ characteristics and of the results of the 10 Quality Measures assessed. We also assessed the quality of the prescription of the oral rehydration solution (ORS) and the type of hospitalisation (whether short duration of stay or formal hospitalisation). Data were presented as percentage frequencies, by centre and on the overall sample. To study the differences in the frequency of Quality Measures between the data collected in the 2 years, the Wilcoxon-Mann-Whitney test for non-normally distributed data was applied. To verify whether the results for the Quality Measures differ significantly between facilities, the χ2 homogeneity test was applied.
We conducted univariate and multivariate logistic regression analyses, to assess the association between key Quality Measures and individual children characteristics. Five Quality Measures were identified of greatest interest for these analyses: (1) accurate ORS prescription, (2) antibiotic prescription at discharge from ED, (3) probiotic prescription, (4) clear indications for reassessment and (5) hospitalisation. Five separate logistic regression models were estimated, considering the five Quality Measures as binary outcome variables and the following individual children characteristics as explanatory variables: age, sex, temperature, dehydration level, the facility where the child was treated and the year in which the child was treated. Observations from centres with extreme values (0% or 100%) in the dependent variable were removed from the corresponding model data set to exclude sources of bias in the estimates. Hospitalised children were excluded from the first four models, respectively, since the Quality Measures under evaluation (ie, accurate ORS prescription, antibiotic prescription, probiotic prescription, clear indications for reassessment) were not pertinent to hospitalised children. In these models, the facility named C1, was taken as the reference value and the facility named C11 was excluded due to the lack of 2020 data. For analysis of the function of antibiotic prescription, facility C1 was excluded because it had no prescriptions in both years. Centre C7 was chosen as the reference both because of its geographical proximity and because it had similar values in the variables of interest compared with C1. Frequencies, ORs and adjusted ORs (aOR) were calculated, with 95% CI and p value of significance.
Lastly, to assess the association between two key Quality Measures (ie, hospitalisation and antibiotic prescription) and the characteristics of each facility, when adjusted for characteristics of the population in each facility, we performed a multivariate analysis with a general linear model using Gaussian family with identity link function. The independent variables included in this model as key characteristics of each facility were: geographical location, university centre, number of paediatricians, number of residents, number of nurses. For the characteristics of the population in each facility, we included: % of children in each age subgroup and sex subgroup, % of children with maximum temperature ≥40°C, % of children in each dehydration class. In these models, data were considered by year, so we included two observations for each facility, except for C11 (2019 data only). For the selection of the optimal model, the automatic backward elimination method was applied, based on Akaike information criterion value. Findings were presented with β coefficients with 95% CI and p value of significance.
A p value of <0.05 was taken as statistically significant. R V.4.1.2 was used for data analysis.
Results
Characteristics of the sample
A total of 3061 cases of children accessing care in ED in the 11 facilities were assessed (online supplemental table 4). Children’s age was almost equally distributed in the three age groups of children aged 6–23 months (35.3%), 24–59 months (30.1%) and 5–15 years (34.6%). Male sex was significantly more frequent than female (57.6%, and 42.5%, respectively, OR 1.83, 95% CI 1.65 to 2.02, p<0.001), across all the facilities. Out of the total sample, 28.3% of children had a maximum temperature equal or greater than 38°C. In total, about one-fifth (21.4%) of children were mildly dehydrated and less than 1 out of 10 (8.3%) were moderately or severely dehydrated either at the visit or during the hospitalisation. All these indicators had significant variations across the 11 centres (p<0.001).
Quality Measures
The distribution of the Quality Measures across the 2 years was not statistically different (p values ranged from 0.11 to 0.95), therefore results for the 2 years were analysed together.
All Quality Measures, both those related to child assessment and treatment, had large variations across centres (figure 1, online supplemental table 5). Among the 3061 children analysed, only in 1897 (62%) body weight was documented, with extreme variability across centres (range 7.7%–98.5%, p<0.001). Temperature was documented in 2638 (86.2%) children, again with significant variations across centres (range 50.0%–97.7%, p<0.001).
Findings on the 10 CHOICE priority WHO Quality Measures on acute watery diarrhoea. 1Accurate ORS prescription=clear indications for parents in terms of quantity, timing and duration. 2Indication for reassessment=clear indications for parents on which signs and symptom need immediate reassessment from a doctor (eg, blood in the stools). ED, emergency department; IV, intravenous; ORS, oral rehydration solution; T°, body temperature (Celsius).
Among measures of treatment, several key Quality Measures had major variations across centres: the hospitalisation rate ranged from 8.5% to 62.8% (p<0.001); the rate of children treated with intravenous fluids ranged from 2.3% to 35.5% (p<0.001); the rate of probiotic prescriptions varied in between 0% and 80.8% (p<0.001 across facilities). The other two measures explored had less important, although still clinically relevant variations: antibiotic prescription rate ranged from 0% to 10.1%, while antidiarrhoea prescription rate varied in between 0% and 10.5% (p<0.001 for both measures).
With regards to information for parents, the rate of children whose parents were receiving clear written indications for reassessment (ie, for which signs and symptom seek immediate advice) and accurate ORS prescriptions (ie, quantity, duration, timing) in the discharge letter ranged from 10.4% to 90.2%, (p<0.001) and 2.5% to 51.3% (p<0.001), respectively.
Other process indicators also showed high variability (online supplemental table 6). Prescriptions for racecadotril (anti-secretory drug) were generally low, but still very variable between facilities (ranging from 0% to 34.1% and from 0% to 20%, respectively, both p<0.001). Only 722 (23.6%) children were given an accurate ORS prescription, in terms of quantity, duration, timing. Although short stay in ED was more frequent than hospitalisation, practices were very different across facilities (rate of short stay ranging from 5.9% to 61.8%, rates of hospitalisation ranging from 0% to 28.6%, both p<0.001).
Factors associated with key Quality Measures
At the multivariate analysis, after correction for children’s characteristics, in each model the variable most strongly associated with each analysed Quality Measure was the facility where the child was managed.
For accurate ORS prescriptions (figure 2A, online supplemental table 7), all but one facility (C9) showed a tendency to provide fewer ORS prescriptions with correct quantity, timing and duration than the reference C1 (aOR range 0.02–0.56). Children with mild levels of dehydration were more likely to receive accurate ORS prescriptions (aOR 1.59, 95% CI 1.23 to 2.06), while those who received intravenous fluids and antibiotics or were assessed in ED in 2020 were less likely (aOR range between 0.49 and 0.62).
Factors significantly associated with accurate ORS prescription (A) antibiotic prescription (B) and probiotic prescription (C). Accurate ORS prescription=clear indications for parents in terms of quantity, timing and duration. IV, intravenous; ORS, oral rehydration solution.
For antibiotic prescription (figure 2B, online supplemental table 7), a group of three hospitals (C3, C5 and C7) was found to have a substantial higher probability of prescribing antibiotics (aOR range between 4.03 and 9.75). Treatment in 2020 and temperature greater than or equal to 38°C significantly increased antibiotic prescription (aOR 1.88, 95% CI 1.13 to 3.10, and 5.29, 95% CI 3.22 to 8.83, respectively). Children older than 5 years were more likely to receive antibiotics than younger patients (aOR 1.86, 95% CI 1.03 to 3.44).
For probiotics, (figure 2C, online supplemental table 7), after correction for other variables, five centres (C2, C3, C4, C5 and C9) showed significantly more prescription than the reference C7 (C1 was excluded from this analysis because zero probiotics were prescribed in both years) (aOR range between 1.59 and 22.29). Being admitted in 2020 corresponded to a lower probability of receiving probiotics (aOR 0.61, 95% CI 0.49 to 0.75).
The variable most strongly associated with the availability in the discharge letter of clear indications for reassessment (figure 3A, online supplemental table 7), was the centre where the child was managed, with all centres having lower odds of providing clear indications for reassessment than the reference C1 (aOR range between 0.01 and 0.57). Children accepted in 2020 were less likely to receive clear indications for reassessment (aOR 0.58, 95% CI 0.48 to 0.71).
Factors significantly associated with clear indications for reassessment (A) and hospitalisation (B). Clear indication for reassessment=clear indications for parents on which signs and symptom need immediate reassessment from a doctor (eg, blood in the stools). IV, intravenous.
For hospitalisation (figure 3B, online supplemental table 7), the event rate was low thus limiting the power of the analysis, however, a group of facilities (C2, C3 and C5) showed significantly more hospitalisation than the reference C1 (aOR range between 4.28 and 15.68). Children treated in 2020 (aOR 1.83, 95% CI 1.14 to 2.92) and children who had a temperature greater than or equal to 38°C, a moderate or severe level of dehydration and had received intravenous fluids (aOR range between 2.22 and 11.12) were significantly more likely to be hospitalised. The probability of being hospitalised was lower for older children (aOR 0.59, 95% CI 0.34 to 0.99, for ages between 24 and 59 months and aOR 0.48, 95% CI 0.28 to 0.81 for ages over 5 years).
The analysis of the associations between two key predefined Quality Measures—antibiotic prescription and hospitalisation rates—with facility characteristics, when corrected for the population of children accessing each facility (table 1), showed that Quality Measures were strongly associated with the geographical location of the facility. When a facility was located in Southern Italy, the percentage of cases with an antibiotic prescription increased by 7.6% (95% CI 0.3% to 14.9%, p=0.04), while hospitalised cases increased by 52.9% (95% CI 39.9% to 65.9% p<0.001). Being a university centre was associated with a decrease of hospitalisation rate by—36% (95% CI −50.9% to −21.1%, p<0.001). Children’s clinical characteristics in each centre were not associated with either hospitalisation or antibiotic prescription rates.
Linear regression models—associations between characteristics of the EDs with antibiotic prescription and hospitalisation
Discussion
CHOICE is the first project reporting on the implementation of the WHO ‘Standards to Improve the Quality of Care for Children and Young Adolescents at Facility Level’.14 Specifically, this study contributes to existing knowledge by providing several lessons and new evidence. First, this study suggests that the use of 10 key WHO-Standard-based Quality Measures related to the management of AD, as prioritised by the CHOICE Project, can help identifying key gaps in the domain of provision of care. Second, the study generates new evidence on the QOC for children in EDs in Italy, providing quantitative data that can be easily monitored in future quality improvement projects. Third, the comparison of the pre-pandemic to the pandemic period (year 2019 vs 2020) failed to identify a consistent trend for change in practices, and suggested that gaps in the provision of care for children with AD were pre-existing and independent of the COVID-19 pandemic. Fourth, multivariate analyses showed higher rates of antibiotics prescription and hospitalisation for facilities in Southern Italy, in line with findings of other CHOICE studies, showing, for facilities in the south of Italy, a significantly higher hospitalisation and antibiotic prescription rate for children with acute respiratory infections (CROSS-REF to ARI paper of the collection)19 and a lower rate of pain measurement (CROSS-REF to PAIN paper of the collection).20
Although 10 Quality Measures may sound as a small number, it may be sufficient to describe key practices related to AD management. The benefit of feasibility versus the additional burden of collecting more indicators on QOC for children with AD may be evaluated in more studies. Overall, the CHOICE study provided an overview on about 175 Quality Measures, covering all domains of the WHO framework including measures of provision of care relevant to other children’s conditions (pain and acute respiratory infections), availability of resources and experience of care (online supplemental table 1).
Although the study confirms existing evidence on the low adherence to recommendations on diarrhoea case management,3 5 6 21–26 it should be acknowledged that most of the existing literature relates to the assessment performed in low-income and middle-income countries.21–25 Despite children with diarrhoea represent a significant workload in ED,27 and although diarrhoea significantly impacts the quality of life,28 we identified relatively few studies reporting on hospital QOC for children with AD in high-income countries.3 5 6 25 26 Importantly, large regional or national studies are lacking, while the use of a simple set of 10 Quality Measures may facilitate their conduction.
Results of this study suggest that high quality of care in paediatric EDs in Italy is in principle achievable, with several facilities showing good practices. However, it also highlighted existing gaps in the provision of care, with key gaps being: (1) the lack of documentation in the discharge letter of temperature and body weight, the latter being a critical parameter for follow for children with AD; (2) the lack of accurate ORS or other preferred fluids prescription and clear indications for reassessment, as well as heterogeneity in the use of intravenous fluids, despite the existence of clear WHO recommendations29; (3) the widespread use of probiotics despite no evidence in support from existing high-level systematic reviews4 30; (4) very variable hospitalisation rates, with value reaching 62.8%, likely suggesting inappropriate practices. These results provide a solid evidence-base for future expected quality improvement interventions, which can be tailored to the local needs. Specifically, the results of this study call for actions to standardise practices across facilities so that each child and their families can have access to high QOC regardless of where they live or are treated. Overmedicalisation should be avoided, considering the potential side effects of medical interventions. Probiotics have shown no clinical benefits in children with AD in a recent Cochrane review,30 while an increasing number of case reports suggest they may be associated with invasive infections, especially in children with susceptibility to infections.31 Systematic reviews32 33 document that hospitalisation is often a traumatic event for children and their parents and it can favour the spread of infectious diseases, including COVID-19. Intravenous fluids increase the risk of infections23 34 yet were administered to one in three children in some centres.
Clearly, improving QOC is not simple, and there is no ‘magic pill’ to achieve it. Actions are needed at different levels, in the health system and in the community, to change both health professionals’ practices and parents’ attitudes.7 35–37 Based on a rapid review of the literature that we conducted, we were able to identify only few randomised controlled trials (RCT) reporting on interventions to improve QOC for children with diarrhoea.38 39 In an RCT in the Netherlands, the implementation of a nurse-guided clinical decision support system on rehydration treatment in children with acute gastroenteritis showed high compliance and increased standardised use of ORS.38 In an RCT in Georgia (USA), brief video discharge instructions improved caregiver understanding of their child’s ED visit, plan and follow-up, as well as satisfaction with the service received.39 More intervention studies should aim at documenting the effectiveness and sustainability of different approaches for quality improvement in the paediatric field. Further results of the CHOICE study will be reported in future publications.
Strengths of the study include the use of objective measures of QOC, which should be routinely reported in discharge letters in Italy as well as in other existing forms of medical records in other settings, thus allowing simple data extraction and comparison of quantitative data across facilities and over time. While the results of this study cannot be generalised to other facilities, methods developed by the study can be easily replicated.
Study limitations include the relatively small sample of facilities assessed; we did not aim at collecting data from a large sample of facilities, but rather at getting lessons on the implementation of WHO standards.14 Under-reporting in the ED discharge letters of key information (vital signs and information for families) may have overestimated gaps in QOC; however, completeness of discharge letter is a key aspect of QOC and should therefore be one of the priorities for quality improvement interventions.14
Still, many high-income countries lack standardised systems to routinely measure and compare over time different domains of QOC for children at facility level. Although the definition of the WHO Standards14 was a key step in this direction, still more implementation research is needed to learn how better to use the WHO Standards and to make data on QOC available to inform policy and implementation in a timely manner.14 40 More generally, there is a need to invest in quality of care for children.41 42 More studies are warranted to understand how to better incorporate quality assessments in routine data collection systems, and how to triangulate data from different sources with other indicators such as health outcomes. Such systems should ideally aim at linking, as performed in this study, Quality Measures to the individual children and facility characteristics.
Data availability statement
Data are available upon reasonable request.
Ethics statements
Patient consent for publication
Ethics approval
Approval for data collection was obtained by the Ethical Committee of the Friuli Venezia Giulia Region for the coordinating center (Study ID: 2976, RC 15/2019 Prot. 0035348, 3 December 2019) and by the ethical committees of each participating hospital. Anonymity in data collection was ensured by not collecting any information that could disclose participants’ identity. Participants gave informed consent to participate in the study before taking part.
Acknowledgments
CHOICE project was supported by the Ministry of Health, Rome - Italy, in collaboration with the Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste - Italy. We would like to thank all CHOICE partners and volunteer who helped in the development of the questionnaire and all health workers who took the time to respond to this survey despite the burden of the COVID-19 pandemic. Special thanks to the CHOICE Study Group for their contribution to the development of this project and support for this manuscript. We are grateful to all health workers involved in data collection: Massimo Dagnelut from Trieste; Andrea Iuorio from Firenze; Michela Pandullo from Udine; Marta Gagliardi from Alessandria; Riccardo Pavanello from Treviso; Silvia Galiazzo from Padova; Francesca Patanè, Laura Portale, Marta Arrabito from Catania; Riccardo Lubrano, Vanessa Martucci, Mariateresa Sanseviero, Silvia Bloise, Alessia Marcellino from Latina; Mariangela Labruzzo from Mantova; Sara Dal Bo, Angela Troisi from Ravenna; Sarah Contorno, Massimo Lo Verde from Palermo.
References
Footnotes
Collaborators CHOICE Study Group: Alessandria: Kevin Valentino, Chiara Grisaffi; Bari: Fabio Cardinale, Annunziata Lucarelli, Lucia Grazia Tricarico, Mariateresa De Sario, Alessandra Pisani; Catania: Maria Carla Finocchiaro, Laura Portale, Francesca Patanè, Vita Antonella Di Stefano; Firenze: Stefano Masi, Marco Greco, Emiliano Talanti, Andrea Iuorio, Anna Madera, Paola Stillo, Rosa Santangelo, Nicolò Chiti; Latina: Vanessa Martucci, Silvia Bloise, Alessia Marcellino; Mantova: Silvia Sordelli, Maria Luisa Casciana; Padova: Francesca Tirelli; Palermo: Massimo Lo Verde, Domenico Cipolla, Sarah Contorno, Roberta Parrino, Giuseppina De Rosa; Ravenna: Federico Marchetti, Alessandra Iacono, Vanna Graziani, Carlotta Farneti, Francesco Oppido, Giulia Sansovini; Treviso: Chiara Stefani, Marcella Massarotto, Paola Crotti, Giada Sartor, Benedetta Ferro, Riccardo Pavanello, Marta Minute, Trieste: Egidio Barbi, Ilaria Mariani, Elia Balestra, Benmario Castaldo, Marta Magnolato, Michele Maiola, Giorgio Cozzi, Alessandro Amaddeo, Alice Del Colle, Massimo Dagnelut; Udine: Maristella Toniutti, Sara Rivellini, Chiara Pilotto, Paola Cogo.
Contributors ML is the guarantor and conceived the study; study indicators were agreed among all authors. PD analysed data, with inputs from ML and all other authors. ML wrote the first draft with major inputs from PD, the draft was revised by all authors. ML, IS, IL, EF, SM, SB, GLT, RL, SF, AT, MP, MG, PM, SG, MA, MS, ML, SDB, VB, PD read and approved the final manuscript.
Funding This article is part of a supplement entitled Lesson learnt with the implementation of the WHO standards for improving the quality of care for children and young adolescents in health facilities (CHOICHE study) in Italy published with support from WHO Collaborating Centre for Maternal and Child Health - Institute for Maternal and Child Health IRCCS Burlo Garofolo, Ospedale Ca’ Foncello’s Hospital - Pediatric Unit and Università Degli Studi di Padova – Dipartimento di Salute della Donna e del Bambino. The research was supported by the Ministry of Health, Rome - Italy, in collaboration with the Institute for Maternal and Child Health IRCCS Burlo Garofolo, Trieste – Italy (CHOICE Study- RC 15/19).
Disclaimer VB is a staff member of the WHO. The author alone is responsible for the views expressed in this article; they do not represent the decisions or policies of the WHO.
Competing interests None declared.
Patient and public involvement Both health service users (children and their parents) and health providers (health workers at facility level) were involved in the CHOICE (Child HOspItal CarE) study in multiple stages. As a first step, in 2019-2020 they were involved in the prioritization of Quality Measures, thus affecting the selection of research outcomes. Secondly, they were involved in the validation of data collection tools, which included collecting their opinion on the acceptability of the questionnaire. Lastly, their opinion on quality of care was actively collected; more specifically, the option of service users was collected on 75 prioritized Quality Measure,43 and the opinion of service providers was collected on another 75 prioritized Quality Measure.44 In each facility health workers were involved in the dissemination of study findings (year 2022-2023), and in planning quality improvement interventions. In the nearest future we plan to further involve the general public in data dissemination.
Provenance and peer review Not commissioned; externally peer reviewed.
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