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Background
Cross-country comparisons of health system performance have become increasingly important. Clear evidence is needed on the prioritization of health system performance assessment (HSPA) indicators. Selected “leading” or “headline” HSPA indicators may provide early warnings of policy impacts. The goal of this paper is to propose a set of h...
Contexts in source publication
Context 1
... we included 43 relevant national and international HSPA initiatives coming from the EC [2,7,13,18,32,36,[40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55], the OECD [26,33,56,57], the WHO [35,58], and other international institutions [37,[59][60][61][62][63][64][65] and EU MSs [66][67][68][69][70][71][72][73][74][75][76][77][78] (Fig. 1). Thirteen initiatives from Belgium, Estonia, Hungary, Ireland, Italy, Malta, Netherlands, Portugal, Sweden and United Kingdom informed the inventory at MS level. The extraction of indicators resulted in a long list of 2168 reported health and HSP indicators, of which 43% were found in reports from MSs. After excluding 132 indicators ...
Context 2
... we included 43 relevant national and international HSPA initiatives coming from the EC [2,7,13,18,32,36,[40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55], the OECD [26,33,56,57], the WHO [35,58], and other international institutions [37,[59][60][61][62][63][64][65] and EU MSs [66][67][68][69][70][71][72][73][74][75][76][77][78] (Fig. 1). Thirteen initiatives from Belgium, Estonia, Hungary, Ireland, Italy, Malta, Netherlands, Portugal, Sweden and United Kingdom informed the inventory at MS level. The extraction of indicators resulted in a long list of 2168 reported health and HSP indicators, of which 43% were found in reports from MSs. After excluding 132 indicators considered irrelevant for HSPA and/or as being too country-specific and adjusting the remaining 2032 indicators for overlaps, a final list of 361 indicators was included in the 1st stage of the euHS_I survey. Fig. 2 shows the distribution of this initial set of consolidated indicators. We found that listed in the domains quality of care (34%, 121/361), health status (15%, 55/361) and determi- nants of health (13%, 47/361) dominate the current HSP indicator landscape. In contrast, indicators of finan- cing (23/361), physical resources (21/361) and healthcare activities (23/361) represent only 6% per chapter. Table 2 describes the characteristics of the euHS_I sur- vey responders by stage. In the 1st stage, we received 28 responses, corresponding to 29% of experts surveyed. Of the total responses, 10 (36%) were complete and 18 (64%) were partially complete through letting partici- pants to focus only on domains that matched their relevant expertise. In the 2nd stage, the overall response rate was 34% (72 out of 209). This increase was mainly achieved through an improved and representative response to the survey coming from EU countries a total of 79% (22 out of 28). In total, out of the 72 responses 52 (72%) were complete and 20 (28%) were partially ...
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Citations
... • The EU project on the international inventory of HSPA indicators [12][13][14][15] and the publications of the EU Expert Group on HSPA (2020) 16 • The OECD "Health at a Glance" publications 17 ...
... The term EU-14 refers to the 14 Member States of the European Union as of 31 December 2003, before the new Member States joined the EU and excluding UK. These 14 Member States are Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, the Netherlands, Portugal, Spain, and Sweden. ...
... Peric et al. Grech et al., 2015;Fekri et al., 2017;Peric et al., 2018. (2) Обобщаване и групиране на идентифицираните показателипоказателите са разпределени в отделни групи, които отговарят на основните измерения в концептуалната рамка за оценка на функционирането на здравната система в България. ...
Изследването и тази монография са резултат от научния проект „Оценка на здравната система в България: ефективност, равнопоставеност, устойчивост“, финансиран от Фонд „Наука“ на Медицински университет „Проф. д-р Параскев Стоянов“ – Варна, с ръководител доц. Мария Рохова, д.у., и реализиран в периода 2018-2023 г. от екип на Катедрата по икономика и управление на здравеопазването на Факултета по обществено здравеопазване на Медицински университет – Варна. Той е естествено продължение на многогодишната изследователска и експертна дейност на Катедрата в областта на анализите на здравната система, здравната реформа и здравната политика в България.
В представеното изследване е направен опит за първоначална оценка на функционирането на здравната система в България – предложена е концептуална рамка, която да ръководи оценката; формиран е комплекс от показатели, с които да се проследят и анализират резултатите от функционирането на здравната система през последните няколко години; разработен и апробиран е инструмент за проучване на чувствителността на здравната система към очакванията на потребителите; събрани са данни по избраните показатели, с помощта на които е направен анализ по отделните измерения на функционирането на системата.
С този първоначален вариант на оценката нашият екип има за цел да постави основите на един регулярен и систематичен процес, който да подпомогне вземането на здравнополитически решения в България. За да се разберат по-добре очертаните проблеми, представените анализи трябва да бъдат допълнени със задълбочени таргетирани изследвания и качествени оценки, които да установят причините за неблагоприятните резултати от работата на системата. Усилията трябва да бъдат съсредоточени върху това някои от проучванията да станат по-редовни и да се допълнят пропуските в информацията и знанията за функционирането на здравната система.
... defined as a quantifiable measurement approach or monitoring tool which can be used to track progress towards strategic targets (e.g. health system performance or policy impacts) and to facilitate comparisons across areas and time periods (Perić et al., 2018). Fuel poverty in NI has an identified and widely-used indicator, with households indicated to be experiencing fuel poverty if they spend more than 10% of household income on heating the home (DECC, 2019). ...
Prior to the February 2019 announcement that the Household Food Security Survey Module (HFSSM) will be used to estimate household food insecurity, there has not been a standardised measurement approach used in the United Kingdom (UK). Measurement has instead been somewhat inconsistent, and various indicators have been included in national and regional surveys. There remains a gap relating to the comparative usefulness of current and past food insecurity measures used in Northern Ireland (NI) (HFSSM; European Union-Survey of Income and Living Conditions (EU-SILC) food deprivation questions), and the potential usefulness of a headline indicator similar to that used to measure fuel poverty. This study presents findings from Northern Ireland (NI) stakeholder interviews (n = 19), which examined their perspectives on food insecurity measures which have previously been or are currently, or could potentially, be used in the UK/NI (HFSSM; EU-SILC food deprivation questions; headline indicator). Interview transcripts were coded using QSR NVivo (v.12) and inductively analysed to identify relevant themes. Stakeholders preferred the HFSSM to the EU-SILC, reasoning that it is more relevant to the food insecurity experience. A headline indicator for food insecurity was considered useful by some; however, there was consensus that it would not fully encapsulate the food insecurity experience, particularly the social exclusion element, and that it would be a complex measure to construct, with a high degree of error. This research endorses the use of the HFSSM to measure food insecurity in the UK, and provides recommendations for consideration of any future modification of the HFSSM or EU-SILC measurement instruments.
... We will come back to the evidence of low performance after a brief look at healthcare performance indicators used outside of Russia. These KPI were reviewed in 2018 by Perić et al. (8), divided in clusters (9) and used to cluster health systems of OECD countries (10). A total of existing 361 KPI of health systems can be divided in several domains; most important domains and indicators within them are: access to care (like insurance coverage), efficiency (like health care expenditure, number of hospital beds), quality of care (like rates of hospital-acquired infections, infant and maternal mortality), equity, health status (like life expectancy, healthy life years), and health determinants (like body mass index, smoking and unemployment rates). ...
Performance of healthcare can be measured as its ability to restore and preserve health with acceptable costs for the society. Under the current prevalence of chronic disease, medical care (the major content of healthcare) underperforms in all key indicators: clinical effectiveness, benefit/risk ratio of interventions, cost/benefit ratio, and general population health. In Russia key performance indicators (KPI) of healthcare do not allow effective decision-making; a similar situation is seen worldwide: most KPIs are either focused on the process (not results) of medical care, or depend on efforts out of control of healthcare decision-makers.
The key root factors limiting clinical effectiveness and cost-effectiveness of healthcare are reactive diagnosis-centered organizational model of care and the underlying biomedical paradigm, generally inadequate in chronic diseases. They make healthcare intervene too late, use less effective prevention and treatment instruments, and be in a state of resource scarcity. In Russia there is also a lack of interdisciplinary and interagency cooperation essential for health preservation and promotion.
Performance of healthcare system in overcoming the chronic disease epidemic can be improved through supplementing the current ‘reactive’ organizational model with preventive person-centered model based on the biopsychosocial paradigm. Enabling patients for early lifestyle-based interventions, the core P4 medicine approach, should prevail in managing chronic disease. Communication and information technologies should allow fast scaling up of the best person-centered practices.
... Some studies have tried to align health system performance indicators between countries to draw comparisons. [3][4][5][6][7][8] However often international comparability is only possible across core health system components, such as those defined by the World Health Organization (WHO) to align with their six building blocks framework. 3,5,[7][8][9] There are also instruments available in the literature that have been developed to analyse a given set of quality indicators in the healthcare system after they have been created, such as QUALIFY and the Appraisal of Indicators through Research and Evaluation (AIRE). ...
... While there is some literature available that describes the selection of health system performance indicators or a broader performance framework in a given context, 4,[13][14][15][16][17][18] there appears to be no comprehensive review of the processes used to select them, and how they compare. 19,20 One recent systematic review considered content validity of indicator sets specifically across the full spectrum of healthcare settings. ...
Background:
Health system performance indicators are widely used to assess primary healthcare (PHC) performance. Despite the numerous tools and some convergence on indicator criteria, there is not a clear understanding of the common features of indicator selection processes. We aimed to review the literature to identify papers that document indicator selection processes for health system performance indicators in PHC.
Methods:
We searched the online databases Scopus, Medline, and CINAHL, as well as the grey literature, without time restrictions, initially on July 31, 2019 followed by an update November 13, 2020. Empirical studies or reports were included if they described the selection of health system performance indicators or frameworks, that included PHC indicators. A combination of the process focussed research question and qualitative analysis meant a quality appraisal tool or assessment of bias could not meaningfully be applied to assess individual studies. We undertook an inductive analysis based on potential indicator selection processes criteria, drawn from health system performance indicator appraisal tools reported in the literature.
Results:
We identified 16 503 records of which 28 were included in the review. Most studies used a descriptive case study design. We found no consistent variations between indicator selection processes of health systems of high income and low- or lower-middle income countries. Identified common features of selection processes for indicators in PHC include literature review or adaption of an existing framework as an initial step; a consensus building process with stakeholders; structuring indicators into categories; and indicator criteria focusing on validity and feasibility. The evidence around field testing with utility and consideration of reporting burden was less clear.
Conclusion:
Our findings highlight several characteristics of health system indicator selection processes. These features provide the groundwork to better understand how to value indicator selection processes in PHC.
... 3 Health expectancy can be considered a 'general term referring to the entire class of indicators expressed in terms of life expectancy in a given state of health'. 4 According to the Réseau Espérance de Vie en Santé, 'health expectancies are indicators of current health and mortality conditions.' 4 Population health measures, such as health expectancy, have been used in different policy settings such as retirement, budgets and sustainable development 5 and were identified by experts, by the European Commission (EC) and by the World Health Organization (WHO) as indicators for health system performance assessment, [6][7][8] having been formally adopted by the latter two. ...
Background
Healthy life expectancy (HLE) is a population health measure that combines mortality and morbidity, which can be calculated using different methods. In this study, we aimed to assess the correlation, reliability and (dis)agreement between two estimates monitored in the European Union (EU), that is, the European Commission's HLE based on self-perceived health (SPH-HLE) and the Institute for Health Metrics and Evaluation's HLE based on disability weight (DW-HLE), by sex, and comparing these results with LE and proportion of life spent in good health (%GH).
Methods
We performed a retrospective study in the EU28 countries, between 2010 and 2017. The HLE methods differ in definition, measurement and valuation of health states. While SPH-HLE relies directly on one question, DW-HLE relies on epidemiological data adjusted for DW. Spearman’s r, intraclass correlation coefficient, information-based measure of disagreement and Bland-Altman plots were used to assess reliability, correlation and disagreement in HLE resulting from both methods and in LE or %GH measured by both institutions.
Results
Correlation and reliability between SPH-HLE and DW-HLE were good (better for males), with low disagreement, and were even better for LE between both institutions. The HLE Bland-Altman plots suggest a variability range of approximately 6 years for both sexes, higher for females. There was also an increasing HLE difference between methods with higher average HLE for both sexes.
Conclusion
We showed wide variations between both methods with a clear and different high impact on female and male HLE, showing a tendency for countries with higher health expectancies to yield larger gaps between SPH-HLE and DW-HLE.
... Accordingly, core targets and indicators that they should jointly implement were selected. A set of headline indicators are useful as a monitoring tool to track and explain progress of SDGs at the regional and local level and provide a reference framework to identify priorities for policy action (Pinter, Hardi, and Bartelmus 2005;Lafortune et al. 2020;Perić, Hofmarcher, and Simon 2018). The shared SDGs indicators also promote mutual learning and accountability by allowing municipalities to compare performance with each other. ...
This study aims to develop and evaluate the indicators of Sustainable Development Goals (hereafter SDGs) for local governments in Gyeonggi Province, South Korea from the perspective of the glocal (global + local) mainstreaming of SDGs and localization. Through surveys and focus group meetings, 35 SDGs indicators that are to be implemented by both the Gyeonggi Provincial government and 31 separate local governments were selected and an overall index was calculated by standardizing 27 indicators whose statistical data was made available at the local level. Through the comparative analysis of the fuzzy-set, this paper revealed the four ideal types along with the arrangement of two variables, the socio-economic SDGs index (S) and the environmental SDGs index (E), which are derived from the thirty-one local governments. In short, some examples of this arrangement are the Type 1 (S*E: “sustainable local gov.”) including Hanam City (fuzzy score, 0.729); Type 2 (S*e: “imbalanced local gov.(I)”) including Hwaseong City (0.862); Type 3 (s*E: “imbalanced local gov.(II)”) including Gapyeong County (0.922); and Type 4 (s*e: “unsustainable local gov.”) including Pyeongtaek City (0.650). As a result, this paper suggests policy priority should be placed on the local governments of Type 4 where all three dimensions of sustainable development pose challenges. Furthermore, it is important for Type 2 and Type 3 to enhance policy coherence for sustainability as the gap between socio-economic and environmental sustainability appears wide.
... " 32 The indicator "unmet healthcare need" has become the dominant measure of access internationally. 33 In the present study, it is operationalised by asking participants if they have experienced any situation within the past twelve months in which they did not seek healthcare because of (1) waiting time, (2) distance or problems with transportation, or (3) financial reasons. To assess the level of unmet need due to financial reasons in more detail, participants are given a list of healthcare services (eg, medical aids, dental treatment) to specify the kind of care they did not seek. ...
Background:
Health system performance assessment (HSPA) is a major tool for evidence-based governance in health systems and patient/population-orientation is increasingly considered as an important aspect. The IPHA study aims (1) to undertake a comprehensive performance assessment of the German health system from a population perspective based on the intermediate and final dimensions defined by the World Health Organization (WHO) and (2) to identify differences in HSPA between (a) common user characteristics and (b) user types, which differ in their interactions and patterns of action within the health system.
Methods and analysis:
A cross-sectional survey was conducted between October and December 2018 with statutorily and privately health insured to assess the German health system from a population perspective related to the past 12 months. The random sample consists of 32 000 persons insured by AOK Nordost and 20 000 persons insured by Debeka. Data from the survey will subsequently be linked with health insurance claims data at the individual level for each respondent who has given consent for data linkage. Claims data covers the time period January 1, 2017 to June 30, 2018. The combination of the 2 data sources allows to identify associations between insured patient characteristics and differences in the assessment of health system performance. The survey consists of 71 items measuring all final and intermediate health system goals defined by the WHO and user characteristics like health literacy, self-efficacy, the attention an individual pays to his or her health or disease, the personal network, autonomy, compliance and sociodemographics. The claims data contains information on morbidity, care delivery, service utilization, (co)payments and sociodemography.
Discussion:
The study represents a promising attempt to perform a holistic HSPA using a population perspective. For this purpose, a questionnaire was designed that contains both validated and new items in order to collect data on all relevant health system dimensions. In particular, linking survey data on HSPA with claims data is of high potential for assessing and analysing determinants of health system performance from the population perspective.
Background
Healthcare-associated infections (HAIs) represent a major threat in Europe. Infection prevention and control (IPC) measures are crucial to lower their occurrence, as well as antimicrobial stewardship to ensure appropriate use of antibiotics. Starting from Italian national data, this study aimed at describing IPC indicators and outcomes related to HAIs and antimicrobial use in Italy, and estimating effects of IPC variables on HAI prevalence and on the proportion of antibiotics without specific reason.
Methods
Based on data collected for Italy during the ECDC PPS-2 Point Prevalence Survey, descriptive statistics were computed at national and macro-regional level. Causal assumption-informed regression models were then built to estimate the impact of structural determinants, staffing parameters and IPC-related variables on HAI prevalence and percentage of antibiotic prescriptions with no reason detailed on medical records, after adjusting for relevant confounders.
Results
The Italian frame showed substantial heterogeneity for both outcomes between macro-regions. The percentage of single-bed rooms was the only structural determinant with significant, positive impact on HAI prevalence (OR = 0.91 for every + 5%, p < 0.001), while the prevalence of antimicrobial agents without specified reason was lower in the presence of one more IPC nurse (OR = 0.78, p < 0.001) or one more antibiotic consultant (OR = 0.67, p < 0.001) per 100 beds. Both outcomes were reduced in the presence of routinely filed IPC plans and reports (p < 0.001), HAI prevention measures (p < 0.001) and post-prescription review (p < 0.01).
Conclusions
Our model confirmed the pivotal role of IPC measures and antimicrobial stewardship in contrasting HAIs and inappropriate antibiotic prescriptions. Post-prescription review appeared to be a valuable indicator of antimicrobial stewardship policies.
