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Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality.

ABSTRACT: Despite widespread faith that quality indicators are key to healthcare improvement and regulation, surprisingly little is known about what is actually measured in different countries, nor how, nor why. To address that gap, this article compares the official indicator sets--comprising some 1100 quality measures-- used by statutory hospital regulators in England, Germany, France, and the Netherlands. The findings demonstrate that those countries' regulators strike very different balances in: the dimensions of quality they assess (e.g. between safety, effectiveness, and patient-centredness); the hospital activities they target (e.g. between clinical and non-clinical activities and management); and the 'Donabedian' measurement style of their indicators (between structure, process and outcome indicators). We argue that these contrasts reflect: i) how the distinctive problems facing each country's healthcare system create different 'demand-side' pressures on what national indicator sets measure; and ii) how the configuration of national healthcare systems and governance traditions create 'supply-side' constraints on the kinds of data that regulators can use for indicator construction. Our analysis suggests fundamental differences in the meaning of quality and its measurement across countries that are likely to impede international efforts to benchmark quality and identify best practice.

SUBMITTER: Beaussier AL

PROVIDER: S-EPMC7677115 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality.

Beaussier Anne-Laure AL Demeritt David D Griffiths Alex A Rothstein Henry H

Health policy (Amsterdam, Netherlands) 20200229 5

Despite widespread faith that quality indicators are key to healthcare improvement and regulation, surprisingly little is known about what is actually measured in different countries, nor how, nor why. To address that gap, this article compares the official indicator sets--comprising some 1100 quality measures-- used by statutory hospital regulators in England, Germany, France, and the Netherlands. The findings demonstrate that those countries' regulators strike very different balances in: the d ...[more]

PMID: 32192738

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Project description:BackgroundLifting The Burden (LTB) and European Headache Federation (EHF) have developed a set of headache service quality indicators, successfully tested in specialist headache centres. Their intended application includes all levels of care. Here we assess their implementation in primary care.MethodsWe included 28 primary-care clinics in Germany (4), Turkey (4), Latvia (5) and Portugal (15). To implement the indicators, we interviewed 111 doctors, 92 nurses and medical assistants, 70 secretaries, 27 service managers and 493 patients, using the questionnaires developed by LTB and EHF. In addition, we evaluated 675 patients' records. Enquiries were in nine domains: diagnosis, individualized management, referral pathways, patient education and reassurance, convenience and comfort, patient satisfaction, equity and efficiency of headache care, outcome assessment and safety.ResultsThe principal finding was that Implementation proved feasible and practical in primary care. In the process, we identified significant quality deficits. Almost everywhere, histories of headache, especially temporal profiles, were captured and/or assessed inaccurately. A substantial proportion (20%) of patients received non-specific ICD codes such as R51 ("headache") rather than specific headache diagnoses. Headache-related disability and quality of life were not part of routine clinical enquiry. Headache diaries and calendars were not in use. Waiting times were long (e.g., about 60 min in Germany). Nevertheless, most patients (> 85%) expressed satisfaction with their care. Almost all the participating clinics provided equitable and easy access to treatment, and follow-up for most headache patients, without unnecessary barriers.ConclusionsThe study demonstrated that headache service quality indicators can be used in primary care, proving both practical and fit for purpose. It also uncovered quality deficits leading to suboptimal treatment, often due to a lack of knowledge among the general practitioners. There were failures of process also. These findings signal the need for additional training in headache diagnosis and management in primary care, where most headache patients are necessarily treated. More generally, they underline the importance of headache service quality evaluation in primary care, not only to identify-quality failings but also to guide improvements. This study also demonstrated that patients' satisfaction is not, on its own, a good indicator of service quality.

Project description:BackgroundInternationally, people in prison should receive a standard of healthcare provision equivalent to people living in the community. Yet efforts to assess the quality of healthcare through the use of quality indicators or performance measures have been much more widely reported in the community than in the prison setting. This review aims to provide an overview of research undertaken to develop quality indicators suitable for prison healthcare.MethodsAn international scoping review of articles published in English was conducted between 2004 and 2021. Searches of six electronic databases (MEDLINE, CINAHL, Scopus, Embase, PsycInfo and Criminal Justice Abstracts) were supplemented with journal searches, author searches and forwards and backwards citation tracking.ResultsTwelve articles were included in the review, all of which were from the United States. Quality indicator selection processes varied in rigour, and there was no evidence of patient involvement in consultation activities. Selected indicators predominantly measured healthcare processes rather than health outcomes or healthcare structure. Difficulties identified in developing performance measures for the prison setting included resource constraints, data system functionality, and the comparability of the prison population to the non-incarcerated population.ConclusionsSelecting performance measures for healthcare that are evidence-based, relevant to the population and feasible requires rigorous and transparent processes. Balanced sets of indicators for prison healthcare need to reflect prison population trends, be operable within data systems and be aligned with equivalence principles. More effort needs to be made to meaningfully engage people with lived experience in stakeholder consultations on prison healthcare quality. Monitoring healthcare structure, processes and outcomes in prison settings will provide evidence to improve care quality with the aim of reducing health inequalities experienced by people living in prison.

Project description:BackgroundRecently, measuring and benchmarking provision of healthcare services has drawn a considerable attention. This scoping review was conducted to identify, describe, and summarize studies in which the Delphi technique was used to develop quality indicators of pharmaceutical care. The study also aimed to identify activities and services that could be used to capture the impact of pharmacist in integrative medicine.MethodsDatabases were searched from inception to February 2020 using key terms that were combined using Boolean operators. Studies were included if they were relevant to development of quality indicators of pharmaceutical care with regard to medications or complementary and alternative medicine (CAM) modalities. Full text of the selected studies was imported into EndNote. Studies were screened and data were extracted into a standard extraction form.ResultsData were extracted from 31 studies. Of those, 24 (77.4%) were related to provision of pharmaceutical services relevant to medications and 7 (22.6%) were related to provision of care using CAM modalities. Most of the studies (67.7%) were published in 2010 and beyond. Almost half of the studies (48.4%) originated from the United States, United Kingdom, and Canada. A total of 42 different activities and services that could be used as quality indicators were identified from the studies included in this review. Activities and services were related to history taking, performing reconciliations, identifying and resolving therapy problems, providing collaborative care, designing care plans, optimal performance, and continuing education.ConclusionsAlthough there is an increasing interest in improving healthcare delivery, quality indicators of pharmaceutical services and those relevant to CAM provision in healthcare facilities adopting the integrated healthcare paradigm are still limited. Future studies are needed to develop validated quality indicators that could be successfully used in measuring and benchmarking quality of services in integrated healthcare facilities.

Project description:ObjectiveAll healthcare systems require valid ways to evaluate service delivery. The objective of this study was to identify existing content validated quality indicators (QIs) for responsible use of medicines (RUM) and classify them using multiple frameworks to identify gaps in current quality measurements.DesignSystematic review without meta-analysis.SettingAll care settings.Search strategyCINAHL, Embase, Global Health, International Pharmaceutical Abstract, MEDLINE, PubMed and Web of Science databases were searched up to April 2018. An internet search was also conducted. Articles were included if they described medication-related QIs developed using consensus methods. Government agency websites listing QIs for RUM were also included.AnalysisSeveral multidimensional frameworks were selected to assess the scope of QI coverage. These included Donabedian's framework (structure, process and outcome), the Anatomical Therapeutic Chemical (ATC) classification system and a validated classification for causes of drug-related problems (c-DRPs; drug selection, drug form, dose selection, treatment duration, drug use process, logistics, monitoring, adverse drug reactions and others).Results2431 content validated QIs were identified from 131 articles and 5 websites. Using Donabedian's framework, the majority of QIs were process indicators. Based on the ATC code, the largest number of QIs pertained to medicines for nervous system (ATC code: N), followed by anti-infectives for systemic use (J) and cardiovascular system (C). The most common c-DRPs pertained to 'drug selection', followed by 'monitoring' and 'drug use process'.ConclusionsThis study was the first systematic review classifying QIs for RUM using multiple frameworks. The list of the identified QIs can be used as a database for evaluating the achievement of RUM. Although many QIs were identified, this approach allowed for the identification of gaps in quality measurement of RUM. In order to more effectively evaluate the extent to which RUM has been achieved, further development of QIs may be required.

Project description:The need to reduce antimicrobial use (AMU) in livestock production has led to the establishment of national AMU data collection systems in several countries. However, there is currently no consensus on which AMU indicator should be used and many of the systems have defined their own indicators. This study sought to explore the effect of using different internationally recognized indicators on AMU data collected from Irish pig farms and to determine if they influenced the ranking of farms in a benchmarking system. AMU data for 2016 was collected from 67 pig farms (c. 35% of Irish pig production). Benchmarks were defined using seven AMU indicators: two based on weight of active ingredient; four based on the defined daily doses (DDD) used by the European Medicines Agency and the national monitoring systems of Denmark and the Netherlands; and one based on the treatment incidence (TI200) used in several published studies. An arbitrary "action zone," characterized by farms above an acceptable level of AMU, was set to the upper quartile (i.e., the top 25% of users, n = 17). Each pair of indicators was compared by calculating the Spearman rank correlation and assessing if farms above the threshold for one indicator were also above it for the comparison indicator. The action zone was broadly conserved across all indicators; even when using weight-based indicators. The lowest correlation between indicators was 0.94. Fifteen farms were above the action threshold for at least 6 of the 7 indicators while 10 farms were above the threshold for all indicators. However, there were important differences noted for individual farms between most pairs of indicators. The biggest discrepancies were seen when comparing the TI200 to the weight-based indicators and the TI200 to the DDDANED (as used by Dutch AMU monitoring system). Indicators using the same numerator were the most similar. All indicators used in this study identified the majority of high users. However, the discrepancies noted highlight the fact that different methods of measuring AMU can affect a benchmarking system. Therefore, careful consideration should be given to the limitations of any indicator chosen for use in an AMU monitoring system.

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Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality.

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Steering by their own lights: Why regulators across Europe use different indicators to measure healthcare quality.

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