Defining ambulatory care sensitive conditions for adults in Portugal

The Influence of the COVID-19 Pandemic on Hospitalizations for Ambulatory Care-Sensitive Conditions in Split-Dalmatia County, Croatia

Background and Objectives: We aimed to explore whether the COVID-19 pandemic influenced hospitalizations for ambulatory care-sensitive conditions (ACSCs) in Split-Dalmatia County, Croatia. Materials and Methods: We performed a cross-sectional comparative study using two different time periods, the pre-pandemic (from March 2019 to February 2020) and the pandemic period (from March 2020 to February 2021), to explore the possible influences that the COVID-19 pandemic had on hospitalizations for ACSCs. The ACSCs were classified into the categories of vaccine-preventable, chronic, and acute disease. The indicators were statistically analyzed. Results: During the pandemic, a decrease in the total number of hospitalizations and ACSC hospitalizations was recorded. The relative risk for having any ACSC hospitalization in the pandemic period compared to the pre-pandemic period was 0.67 (95% CI, 0.64-0.71; p = 0). The risk reduction was seen in all three categories of vaccine-preventable ACSCs, chronic disease, and acute disease. Large reductions were found in the relative risk of hospitalization for COPD and asthma. Considering the mode of discharge, there was a statistically significantly higher risk of ACSCs with fatal outcomes during the pandemic than in the pre-pandemic period (relative risk 1.31; 95% CI, 1.01-1.7; p = 0.0197). Conclusions: The results of this study show that the COVID-19 pandemic influenced the total number of hospitalizations as well as hospitalizations relating to ACSCs. Certainly, one of the reasons for these changes was due to organizational changes in the working of the entire health system due to the COVID-19 pandemic.

Development of the China's list of ambulatory care sensitive conditions (ACSCs): a study protocol

BACKGROUND

The hospitalization rate of ambulatory care sensitive conditions (ACSCs) has been recognized as an essential indicator reflective of the overall performance of healthcare system. At present, ACSCs has been widely used in practice and research to evaluate health service quality and efficiency worldwide. The definition of ACSCs varies across countries due to different challenges posed on healthcare systems. However, China does not have its own list of ACSCs. The study aims to develop a list to meet health system monitoring, reporting and evaluation needs in China.

METHODS

To develop the list, we will combine the best methodological evidence available with real-world evidence, adopt a systematic and rigorous process and absorb multidisciplinary expertise. Specific steps include: (1) establishment of working groups; (2) generations of the initial list (review of already published lists, semi-structured interviews, calculations of hospitalization rate); (3) optimization of the list (evidence evaluation, Delphi consensus survey); and (4) approval of a final version of China's ACSCs list. Within each step of the process, we will calculate frequencies and proportions, use descriptive analysis to summarize and draw conclusions, discuss the results, draft a report, and refine the list.

DISCUSSION

Once completed, China's list of ACSCs can be used to comprehensively evaluate the current situation and performance of health services, identify flaws and deficiencies embedded in the healthcare system to provide evidence-based implications to inform decision-makings towards the optimization of China's healthcare system. The experiences might be broadly applicable and serve the purpose of being a prime example for nations with similar conditions.

Preadmission morbidity and healthcare utilization among older adults with potentially avoidable hospitalizations: a Danish case-control study

PURPOSE

Examine preadmission diagnoses, medication use, and preadmission healthcare utilization among older adults prior to first potentially avoidable hospitalizations.

METHODS

A nationwide population-based case-control study using Danish healthcare data. All Danish adults aged ≥ 65 years who had a first potentially avoidable hospitalization from January 1995 through March 2019 (n = 725,939) were defined as cases, and 1:1 age- and sex-matched general population controls (n = 725,939). Preadmission morbidity and healthcare utilization were assessed based on a complete hospital diagnosis history within 10 years prior, and all medication use and healthcare contacts 1 year prior. Using log-binomial regression, we calculated adjusted prevalence ratios (PR) with 95% confidence intervals (CI).

RESULTS

Included cases and controls had a median age of 78 years and 59% were female. The burden of preadmission morbidity was higher among cases than controls. The strongest associations were observed for preadmission chronic lung disease (PR 3.8, CI 3.7-3.8), alcohol-related disease (PR 3.1, CI 3.0-3.2), chronic kidney disease (PR 2.4, CI 2.4-2.5), psychiatric disease (PR 2.2, CI 2.2-2.3), heart failure (PR 2.2, CI 2.2-2.3), and previous hospital contacts with infections (PR 2.2, CI 2.2-2.3). A high and accelerating number of healthcare contacts was observed during the months preceding the potentially avoidable hospitalization (having over 5 GP contacts 1 month prior, PR 3.0, CI 3.0-3.0).

CONCLUSION

A high number of healthcare contacts and preadmission morbidity and medication use, especially chronic lung, heart, and kidney disease, alcohol-related or psychiatric disease including dementia, and previous infections are strongly associated with potentially avoidable hospitalizations.

Non-Adherence to COPD Medications and its Association with Adverse Events: A Longitudinal Population Based Cohort Study of Older Adults

OBJECTIVE

To determine the association between non-adherence to long term chronic obstructive pulmonary disease (COPD) medications and COPD related emergency department (ED) visits and hospitalizations in patients with incident COPD, utilizing time varying measures of adherence as well as accounting for time-varying confounding impacted by prior adherence.

STUDY DESIGN AND SETTING

We conducted a population-based retrospective cohort study between 2007-2017 among individuals aged 66 years and older with incident COPD using multiple linked administrative health databases from the province of Ontario, Canada. Adherence to COPD medications was measured using time varying proportion of days covered based on insurance claims for medications dispensed at community pharmacies. The parametric g-formula was used to assess the association between time-varying adherence (in the last 90-days) to COPD medications and risk of COPD related hospitalizations and ED visits while accounting for time varying confounding by COPD severity.

RESULTS

Overall, 60,251 individuals with incident COPD were included; mean age was 76 (SD 7) and 59% were male. Mean adherence over the entire follow-up was 23% (SD 0.3). There were 7,248 (12%) COPD related ED visits (2.8 events per 100 person years [PY]) and 9,188 (15%) COPD related hospitalizations (3.5 events per 100 PY). Compared to those with 0% 90-day adherence, those with adherence between 1-33% had a 19% decreased risk of COPD related ED visits (adjusted risk ratio[aRR]:0.81, 95% confidence interval [CI]:0.78-0.83), those with adherence between 34%-67% had a 18% decreased risk (aRR: 0.82, 95% CI: 0.77-0.85) while those with 68%-100% 90-day adherence had a 63% increased risk of COPD related ED visits (aRR: 1.63, 95% CI: 1.47-1.78). Nearly identical results were obtained for COPD specific hospitalizations.

CONCLUSION

After accounting for time varying confounding by COPD severity, the highest time varying 90-days adherence was associated with an increased risk of both COPD related ED visits and hospitalizations compared to the lowest adherence categories. Differences in COPD severity between adherence categories, perception of need for medication management in the higher adherence categories, and potential residual confounding makes it difficult to disentangle the independent effects of adherence from the severity of the condition itself.

Trends in outpatient and inpatient visits for separate ambulatory-care-sensitive conditions during the first year of the COVID-19 pandemic: a province-based study

Background

The COVID-19 pandemic led to global disruptions in non-urgent health services, affecting health outcomes of individuals with ambulatory-care-sensitive conditions (ACSCs).

Methods

We conducted a province-based study using Ontario health administrative data (Canada) to determine trends in outpatient visits and hospitalization rates (per 100,000 people) in the general adult population for seven ACSCs during the first pandemic year (March 2020-March 2021) compared to previous years (2016-2019), and how disruption in outpatient visits related to acute care use. ACSCs considered were chronic obstructive pulmonary disease (COPD), asthma, angina, congestive heart failure (CHF), hypertension, diabetes, and epilepsy. We used time series auto-regressive integrated moving-average models to compare observed versus projected rates.

Results

Following an initial reduction (March-May 2020) in all types of visits, primary care outpatient visits (combined in-person and virtual) returned to pre-pandemic levels for asthma, angina, hypertension, and diabetes, remained below pre-pandemic levels for COPD, and rose above pre-pandemic levels for CHF (104.8 vs. 96.4, 95% CI: 89.4-104.0) and epilepsy (29.6 vs. 24.7, 95% CI: 22.1-27.5) by the end of the first pandemic year. Specialty visits returned to pre-pandemic levels for COPD, angina, CHF, hypertension, and diabetes, but remained above pre-pandemic levels for asthma (95.4 vs. 79.5, 95% CI: 70.7-89.5) and epilepsy (53.3 vs. 45.6, 95% CI: 41.2-50.5), by the end of the year. Virtual visit rates increased for all ACSCs. Among ACSCs, reductions in hospitalizations were most pronounced for COPD and asthma. CHF-related hospitalizations also decreased, albeit to a lesser extent. For angina, hypertension, diabetes, and epilepsy, hospitalization rates reduced initially, but returned to pre-pandemic levels by the end of the year.

Conclusion

This study demonstrated variation in outpatient visit trends for different ACSCs in the first pandemic year. No outpatient visit trends resulted in increased hospitalizations for any ACSC; however, reductions in rates of asthma, COPD, and CHF hospitalizations persisted.

20-Year trends of hospitalisation among people with dementia: a region-wide retrospective cohort study from Lombardy, Italy

OBJECTIVES

The aim of this study was to investigate the trends of hospitalisations among people with dementia, linking region-wide hospital and demographic health records.

STUDY DESIGN

A retrospective cohort study was conducted using hospitalisation health records from the Lombardy region in Italy.

METHODS

The study included people aged ≥65 years with a diagnosis of dementia who were hospitalised between 2002 and 2020 in Lombardy, which is the most populated region in Italy with 10 million inhabitants. Using data on resident population, this study computed rates of hospitalisation by calendar year, age, sex and cause of hospitalisation.

RESULTS

In total, 340,144 hospitalised patients with dementia were included in the study. The rate of hospitalisation was 100.6 per 10,000 in 2002 and progressively decreased to 65.1 per 10,000 in 2020. The average age at hospitalisation in 2002 was 78.9 years for men and 81.8 years for women, which increased to 82.0 years and 84.2 years, respectively, in 2020. Respiratory diseases caused 10.4% of all hospitalisations in 2002 and grew steadily to 26.8% in 2020, becoming the leading cause of hospital admissions since 2017.

CONCLUSIONS

Hospitalisation patterns for people with dementia have changed over the last 20 years, reflecting evolving epidemiological trends and the impact of healthcare policies. Region-wide administrative health record data analysis should be further utilised to explore the health needs of people with dementia and inform the planning, implementation and monitoring of effective prevention strategies in this population group.

Real-World Effectiveness in Hypertension and Hyperlipidemia Collaborative Management between Pharmacies and Primary Care in Portugal: A Multicenter Pragmatic Controlled Trial (USFarmácia®)

There is evidence of the efficacy of collaborative health interventions with pharmacies and primary care providers but little of its real-world effectiveness. We aimed to assess the effectiveness and discuss the design and challenges of hypertension and hyperlipidemia management between pharmacies and primary care providers using real-world data exchange between providers and experimental bundled payment. This was a pragmatic, quasi-experimental controlled trial. We collected patient-level data from primary care prescription claims and Electronic Medical Record databases, a pharmacy claims database, and patient telephone surveys at several time points. The primary outcomes were changes in blood pressure and total cholesterol. We used matched controls with difference-in-differences estimators in a Generalized Linear Model (GLM) and controlled interrupted time series (CITS). We collected additional data for economic and qualitative studies. A total of 6 Primary Care Units, 20 pharmacies, and 203 patients entered the study. We were not able to observe significant differences in the effect of intervention vs. control. We experienced challenges that required creative strategies. This real-world trial was not able to show effectiveness, likely due to limitations in the primary care technology which affected the sample size. It offers, however, valuable lessons on methods, strategies, and data sources, paving the way for more real-world effectiveness trials to advance value-based healthcare.

Optimal@NRW: optimized acute care of nursing home residents using an intersectoral telemedical cooperation network - study protocol for a stepped-wedge trial

Background

Increasing life expectancy is associated with a growing number of people living in nursing homes, while the availability of outpatient medical care, especially from family doctors, is stagnating in this sector. Consequently, numerous and often avoidable, low-threshold hospitalizations of nursing home residents are observed. This results in unnecessary use of resources such as emergency services and emergency rooms as well as in potential health risks to the nursing home residents related to hospitalization. This study aims to improve this healthcare gap by implementing an intersectoral telemedicine approach.

Methods

Twenty-five nursing homes are participating and provided with telemedical equipment to perform teleconsultations. Additionally, an early warning system and a digital patient record system are implemented. Telephysicians based at RWTH Aachen University Hospital are ready to support the nursing homes around the clock if the family doctor or an emergency service practice is not available in time. Mobile non-physician practice assistants from the telemedicine centre can be dispatched to perform delegable medical activities. General practitioners and the medical emergency practices also have access to the telemedical infrastructure and the non-physician practice assistants.

Discussion

Optimal@NRW adds a telemedicine component to standard care — combining elements of outpatient and inpatient health care as well as emergency service practices — to enable timely medical consultation for nursing home residents in case of the development of an acute medical condition. In addition to optimized medical care, the goal is to reduce unnecessary hospital admissions. The intersectoral approach allows for the appropriate use of resources to match the individually needed medical treatment.

Trial registration

ClinicalTrials.govNCT04879537. Registered on May 10, 2021

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06613-1.

Portuguese Primary Healthcare and Prevention Quality Indicators for Diabetes Mellitus - A Data Envelopment Analysis

BACKGROUND

Diabetes mellitus (DM) is a worldwide public health priority. The increasing prevalence and the budget constraints force to have effective healthcare, especially at the primary healthcare (PHC) level. We aim to assess primary care efficiency considering the best use of human resources to produce optimal diabetes care in terms of prevention quality indicators (PQIs) rates across national ACES (health centre groupings).

METHODS

We conducted a two-stage data envelopment analysis (DEA) to assess the technical efficiency of 54 Portuguese primary care health centre groupings for the 2016-2017 biennium. In the first stage, efficiency scores were obtained through five output-oriented DEA models under vector return to scale (VRS) assumption, using three input variables representing key primary care human resources and one output representing each one of the five PQIs related to diabetes. In the second stage, Tobit regression models were estimated to assess the determinants of primary care efficiency in diabetes care.

RESULTS

A total of 13 ACES reached the efficiency frontier. Better managing human resources could reduce PQI rates by 52.3% in 2016 and 49.1% in 2017. Higher proportion of patients under 65 years old and better controlled with a hemoglobin A1c (HbA1c) ≤6.5% were associated with better efficiency in diabetes care, whereas higher prevalence of DM and unemployment worsened hospitalizations rates by diabetes short-term complications and lower-extremity amputation.

CONCLUSION

Inefficiency in DM care was found in most of the primary care settings which can substantially improve the avoidable hospitalization rates by DM using their current level human resources. These findings help to improve diabetes care by targeting human resources at primary care level, which should be integrated into performance assessments considering broader and integrated scopes.

Using Ambulatory Care Sensitive Conditions to Assess Primary Health Care Performance during Disasters: A Systematic Review

Ambulatory care sensitive conditions (ACSCs) are health conditions for which appropriate primary care intervention could prevent hospital admission. ACSC hospitalization rates are a well-established parameter for assessing the performance of primary health care (PHC). Although this indicator has been extensively used to monitor the performance of PHC systems in peacetime, its consideration during disasters has been neglected. The World Health Organization (WHO) has acknowledged the importance of PHC in guaranteeing continuity of care during and after a disaster for avoiding negative health outcomes. We conducted a systematic review to evaluate the extent and nature of research activity on the use of ACSCs during disasters, with an eye toward finding innovative ways to assess the level of PHC function at times of crisis. Online databases were searched to identify papers. A final list of nine publications was retrieved. The analysis of the reviewed articles confirmed that ACSCs can serve as a useful indicator of PHC performance during disasters, with several caveats that must be considered. The reviewed articles cover several disaster scenarios and a wide variety of methodologies showing the connection between ACSCs and health system performance. The strengths and weaknesses of using different methodologies are explored and recommendations are given for using ACSCs to assess PHC performance during disasters.

Understanding geographical variations in health system performance: a population-based study on preventable childhood hospitalisations

OBJECTIVE

To investigate interdistrict variations in childhood ambulatory sensitive hospitalisation (ASH) over the years.

DESIGN

Observational population-based study over 2008-2018 using the Primary Health Organisation Enrolment Collection (PHO) and the National Minimum Dataset hospital events databases.

SETTING

New Zealand primary and secondary care.

PARTICIPANTS

All children aged 0-4 years enrolled in the PHO Enrolment Collection from 2008 to 2018.

MAIN OUTCOME MEASURE

ASH.

RESULTS

Only 1.4% of the variability in the risk of having childhood ASH (intracluster correlation coefficient=0.014) is explained at the level of District Health Board (DHB), with the median OR of 1.23. No consistent time trend was observed for the adjusted childhood ASH at the national level, but the DHBs demonstrated different trajectories over the years. Ethnicity (being a Pacific child) followed by deprivation demonstrated stronger relationships with childhood ASH than the geography and the health system input variables.

CONCLUSION

The variation in childhood ASH is explained only minimal at the DHB level. The sociodemographic variables also only partly explained the variations. Unlike the general ASH measure, the childhood ASH used in this analysis provides insights into the acute conditions sensitive to primary care services. However, further information would be required to conclude this as the DHB-level performance variations.

Predicting hospitalisations related to ambulatory care sensitive conditions with machine learning for population health planning: derivation and validation cohort study

OBJECTIVE

To predict older adults' risk of avoidable hospitalisation related to ambulatory care sensitive conditions (ACSC) using machine learning applied to administrative health data of Ontario, Canada.

DESIGN, SETTING AND PARTICIPANTS

A retrospective cohort study was conducted on a large cohort of all residents covered under a single-payer system in Ontario, Canada over the period of 10 years (2008-2017). The study included 1.85 million Ontario residents between 65 and 74 years old at any time throughout the study period.

DATA SOURCES

Administrative health data from Ontario, Canada obtained from the (ICES formely known as the Institute for Clinical Evaluative Sciences Data Repository.

MAIN OUTCOME MEASURES

Risk of hospitalisations due to ACSCs 1 year after the observation period.

RESULTS

The study used a total of 1 854 116 patients, split into train, validation and test sets. The ACSC incidence rates among the data points were 1.1% for all sets. The final XGBoost model achieved an area under the receiver operating curve of 80.5% and an area under precision-recall curve of 0.093 on the test set, and the predictions were well calibrated, including in key subgroups. When ranking the model predictions, those at the top 5% of risk as predicted by the model captured 37.4% of those presented with an ACSC-related hospitalisation. A variety of features such as the previous number of ambulatory care visits, presence of ACSC-related hospitalisations during the observation window, age, rural residence and prescription of certain medications were contributors to the prediction. Our model was also able to capture the geospatial heterogeneity of ACSC risk in Ontario, and especially the elevated risk in rural and marginalised regions.

CONCLUSIONS

This study aimed to predict the 1-year risk of hospitalisation from ambulatory-care sensitive conditions in seniors aged 65-74 years old with a single, large-scale machine learning model. The model shows the potential to inform population health planning and interventions to reduce the burden of ACSC-related hospitalisations.

Patients' Perspectives on Determinants Avoidable Hospitalizations: Development and Validation of a Questionnaire

Ambulatory care sensitive conditions (ACSC) can be avoided through effective care in the ambulatory setting. Patients are the most qualified individuals to express the social and individual contexts of their own experience. Thus, understanding why potentially preventable hospitalizations occur is important to develop patient-centred policies or interventions that may reduce them. This study aims to develop and validate a questionnaire to capture the patients’ perspective on the causes of the hospitalizations for ACSC. The development of a new questionnaire involved four phases: a literature review, face validity, pre-test, and validation. We conducted a three-step face validity verification to confirm the relevance of the identified determinants and to collect determinants not previously identified by interviewing healthcare providers, representatives of patients’ associations, and patients. Determinants were identified through the literature review predominantly in the “Healthcare Access”, “Disease self-management”, and “Social Support” domains. The validated resulting questionnaire comprises 25 questions, distributed by two dimensions (individual/contextual) covering seven domains and 20 determinants of ACSC hospitalization. Currently, there are no validated instruments as comprehensive and easy to use as the one described in this paper. This questionnaire should provide a base for further language/context validations.

Integrated quality assessment for diabetes care in Portuguese primary health care using prevention quality indicators

AIMS

This study evaluates the prevention quality indicators (PQI) for Diabetes Mellitus (DM) in Portugal using contemporary data and explores their variability according to Primary Health Care (PHC) quality indicators.

METHODS

We conducted a retrospective observational analysis of secondary data comprising Portuguese PHC indicators by health centres group (ACES) and the National Hospital Morbidity Database. We calculated and analysed age-sex-adjusted rates for each PQI. Worse-performing ACES were identified using the 2017 median PQI values as an assessment cut-off. A multivariate logistic analysis was carried to find variables associated with the likelihood of being a worse-performing ACES for the biennium.

RESULTS

The median values of the indicator PQI93 - Prevention Quality Diabetes Composite were 79 and 65.2 hospitalizations per 100 000 pop, in 2016 and 2017 respectively. Diabetes long term complications (PQI 03) accounted for most of the hospitalizations. The quality indicator in PHC with greater influence on PQI93 was the proportion of DM patients with <65 years with test results for HbA1c < = 6.5%.

CONCLUSIONS

This study shows that some PHC quality indicators are closely related to DM care, and so their monitoring is of high importance. Diabetes long term complications (PQI 03) demand greater attention from PHC professionals.

An Open Source GIS Application for Spatial Assessment of Health Care Quality Indicators

Prevention quality indicators (PQIs) constitute a set of measures that can be combined with hospital inpatient data to identify the quality of care for ambulatory care sensitive conditions (ACSC). Geographical information system (GIS) web mapping and applications contribute to a better representation of PQI spatial distribution. Unlike many countries in the world, in Portugal, this type of application remains underdeveloped. The main objective of this work was to facilitate the assessment of geographical patterns and trends of health data in Portugal. Therefore, two innovative open source applications were developed. Leaflet Javascript Library, PostGIS, and GeoServer were used to create a web map application prototype. Python language was used to develop the GIS application. The geospatial assessment of geographical patterns of health data in Portugal can be obtained through a GIS application and a web map application. Both tools proposed allowed for an easy and intuitive assessment of geographical patterns and time trends of PQI values in Portugal, alongside other relevant health data, i.e., the location of health care facilities, which, in turn, showed some association between the location of facilities and quality of health care. However, in the future, more research is still required to map other relevant data, for more in-depth analyses.

Landscapes on Prevention Quality Indicators: A Spatial Analysis of Diabetes Preventable Hospitalizations in Portugal (2016-2017)

Preventable hospitalizations due to complications of diabetes mellitus (DM), represented by the related prevention quality indicators (PQI), are ambulatory care-sensitive conditions that can be prevented and controlled through effective primary health care (PHC) treatment. It is important to reduce mortality and promote the quality of life to diabetic patients in regions with higher hospitalization rates. The study aims to analyze the results of the DM age-sex-adjusted PQI, by groups of health centers (ACES), distributed in the Portuguese territory. The most representative PQI at a national level were identified, and the trends were mapped and analyzed. Also, it presents the ACES with the highest age-adjusted rates of avoidable hospitalizations for DM. The absolute number of preventable hospitalizations for all DM complications in Portugal has decreased by 20%, thus passing from the rate of 79 in 2016 to 65.2/100,000 inhabitants in 2017. Despite the improvement in results for PQI 03, 20 of 48 ACES that were above the national 2017 median rate in 2016, achieved better results the following year, and for the overall preventable diabetes hospitalizations (PQI 93) only 11 out 39, revealing the need for further studies and PHC actions to improve the diabetic quality of life.

Comparison and Impact of Four Different Methodologies for Identification of Ambulatory Care Sensitive Conditions

Ambulatory care sensitive conditions (ACSCs) are conditions for which hospitalizations are thought to be avoidable if effective and accessible primary health care is available. However, to define which conditions are considered ACSCs, there is a considerable number of different lists. Our aim was to compare the impact of using different ACSC lists considering mainland Portugal hospitalizations. A retrospective study with inpatient data from Portuguese public hospital discharges between 2011 and 2015 was conducted. Four ACSC list sources were considered: Agency for Healthcare Research and Quality (AHRQ), Canadian Institute for Health Information (CIHI), the Victorian Ambulatory Care Sensitive Conditions study, and Sarmento et al. Age-sex-adjusted rates of ACSCs were calculated by district (hospitalizations per 100,000 inhabitants). Spearman's rho, the intraclass correlation coefficient (ICC), the information-based measure of disagreement (IBMD), and Bland and Altman plots were computed. Results showed that by applying the four lists, different age-sex-adjusted rates are obtained. However, the lists that seemed to demonstrate greater agreement and consistency were the list proposed by Sarmento et al. compared to AHRQ and the AHRQ method compared to the Victorian list. It is important to state that we should compare comparable indicators and ACSC lists cannot be used interchangeably.