Health System Performance Assessment Framework for the Czech Republic

Annex D. List of indicators populating the Czech HSPA framework

The list of indicators selected in the comprehensive process during the Setting up of the Czech HSPA Framework project shall serve as an input for the next HSPA implementation phase. Further discussions among HSPA stakeholders, mainly the data custodians and suggested indicator custodians, are foreseen and deemed appropriate to develop detailed technical sheets for each individual indicator (for technical sheet properties see Box 4.1).

In this annex, indicators are provided by each of the 12 domains. In each section, tables detail out indicators selected to populate the first the Czech HSPA and provide information on the availability of data for various perspectives of disaggregation, availability of benchmarks, the primary data source, data custodian, and proposed indicator custodian.

In many cases, the data and indicator custodian are the same for a given indicator. Where it differs, it means a data custodian is responsible for data collection and data processing, as well as for providing the overall calculation of indicator based on the primary data set. The indicator custodian is then responsible for reporting the indicator in the HSPA report while commenting on its wider context, trend development and/or international comparison, and explaining its potential causes and/or consequences on population health or the health system. Typically, the split of the functions concerns survey data indicators, where one institution runs the survey, but the area of interest of the indicator falls within the scope of another institution’s responsibilities.

Indicators have been assigned to indicator custodians based on discussions held during the working group meetings and based on written comments received from various HSPA stakeholders. The assignment was then reviewed during individual consultations held with future HSPA indicator custodians. However, the final distribution of indicators to custodians is open for further discussion during the HSPA implementation phase.

Domain: Health status

The total of 19 indicators have been selected for this domain and they are grouped into 4 subdomains (life expectancy and mortality, avoidable mortality, experienced health, and burden of disease).

Life expectancy and mortality

The subdomain of life expectancy and mortality analyses expected length of life, healthy life years, and main cases of death. The total of 8 indicators were selected. The primary data for these indicators come from the Czech Statistical Office (CZSO) for the Czech population data, from the Institute of Health Information and Statistics (UZIS) for the causes of death, and from Eurostat for international comparison. The healthy life years indicator uses the Eurostat/OECD methodology, which builds on a survey question on long-standing limitations in usual activities due to health problem.

The Mortality registry noted in the table stands for the Registry of Causes of Death, which is being populated by information obtained from Certificate of Examination of the Deceased (List o prohlídce zemřelého, LPZ). Methodologically, the UZIS is responsible for data on causes of death, despite the fact it is the CZSO that reports these data to international datasets. Thus, UZIS has been noted in the following tables as the primary data custodian, though in practice there is a shared responsibility for the dataset methodology, maintenance, and international reporting.

Table A D.1. Life expectancy and mortality indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Life expectancy at birth, by gender (Years)	gender, region	International, time series, regional	Eurostat	Population registry	CZSO	CZSO
Healthy life years at birth, by gender (Years)	Gender, region	International, time series	Eurostat	Population registry, mortality registry (LPZ), EU-SILC survey	UZIS	UZIS
Life expectancy at 65, by gender (Years)	gender, region	International, time series, regional	Eurostat	Population registry	CZSO	CZSO
Healthy life years at 65, by gender (Years)	Gender, region	International, time series	Eurostat	Population registry, mortality registry (LPZ), EU-SILC survey	UZIS	UZIS
Main causes of mortality (%)	gender, region	International, time series, regional	Eurostat	mortality registry (LPZ)	UZIS	UZIS
Peri-neonatal mortality by age of mother, by residence and occurrence (hlth_cd_aperro)	region	International, time series, regional	Eurostat	Population registry, mortality registry (LPZ)	UZIS	UZIS
Mortality from circulatory diseases (specific disease rate per 100 000 population (age‑standardised))	Age, gender, region	International, time series, regional	Eurostat	mortality registry (LPZ)	UZIS	UZIS
Cancer mortality by cancer site (%)	Gender, region	International, time series, regional	Eurostat	mortality registry (LPZ), National Oncology Registry	UZIS	UZIS

Note: Mortality registry stands for the Registry of Causes of Death, which is being populated by information obtained from Certificate of Examination of the Deceased (List o prohlídce zemřelého, LPZ).

Infographic A D.1 and Infographic A D.2 show possible visualisation and benchmarking, either regional, by age, gender or international for life and healthy life expectancy and mortality.

Infographic A D.1. Life expectancy

Note: The primary source of data used in depicted graphics is the Czech Statistical Office and Eurostat.

Source: Depicted figures are taken from the OECD/European Observatory on Health Systems and Policies (2021[11]) for number 1, UZIS (2020[12]) for number 2 and 4, and CZSO (2022[13]) for number 3.

Infographic A D.2. Mortality

Note: The primary source of data for the depicted graphics is Eurostat and the Czech Statistical Office.

Source: Depicted figures are taken from the OECD/European Observatory on Health Systems and Policies (2021[11]) for number 1, OECD (2023[14]) for number 2, and UZIS (2020[12]) for number 3.

Avoidable mortality

The subdomain of avoidable mortality includes 3 indicators. It analyses deaths for causes that can be mainly avoided through public health and primary prevention interventions (preventable causes of mortality), and deaths for causes that can be mainly avoided through timely and effective healthcare, including screening/diagnosis and treatment (treatable causes of mortality). The Potential Years of Life Lost (PYLL) is a summary measure of premature mortality which provides an explicit way of weighting deaths occurring at younger ages, which are, a priori, preventable. The calculation of PYLL involves summing up deaths occurring at each age and multiplying this with the number of remaining years to live up to a selected age limit. All three indicators refer to premature mortality (under the age of 75). For the avoidable mortalities, data are based on the revised OECD/Eurostat lists, the PYLL uses OECD methodology. The Czech primary data source is the mortality registry, see note below the table and in previous subdomain.

Table A D.2. Avoidable mortality indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Preventable causes of mortality (number of deaths)	gender	International, time series	OECD/Eurostat definition	Mortality registry (LPZ), Eurostat	UZIS	UZIS
Treatable causes of mortality (number of deaths)	gender	International, time series	OECD/Eurostat definition	Mortality registry (LPZ), Eurostat	UZIS	UZIS
Potential Years of Life Lost (PYLL)		International, time series	OECD	Mortality registry (LPZ), OECD Health Statistics	UZIS	UZIS

Note: Mortality registry stands for the Registry of Causes of Death, which is being populated by information obtained from Certificate of Examination of the Deceased (List o prohlídce zemřelého, LPZ).

Infographic A D.3 shows possible visualisation of both the treatable and preventable mortality.

Infographic A D.3. Avoidable mortality

Note: The primary source of data for the depicted graphic is OECD/Eurostat for the European countries and the Czech Statistical Office for the Czech data.

Source: Depicted figures are taken from the OECD/European Observatory on Health Systems and Policies (2021[11]).

Experienced health

The subdomain of experienced health analyses people’s subjective perception of their own health. There are 3 indicators in total. The first two indicators are based on EU-SILC survey, which has annual periodicity and can be disaggregated by age, sex, education, and level of urbanisation (hlth_silc_18). Indicators are comparable across EU countries through the Eurostat database; primary data custodian in the Czech Republic is the CZSO. The second indicator monitors subjectively perceived log-term (at least 6 months) limitations in activities of daily living due to health issues. This indicator was originally selected to be based on the European Health Interview Survey (EHIS), managed every 6 years (from 2019 on), but following the consultation process it was changed to the EU-SILC survey data, because of its annual availability. Both statistical surveys follow international methodologies of the Eurostat. The EHIS as well as the EU-SILC survey offer the possibility of disaggregation based on socio‑economic status (SES) such as education level and income.

The two indicators are assigned to the custody of UZIS; however it is recommended (and agreed on with both institutions) that for the purposes of indicator technical sheet drafting, the public health perspective shall be consulted with the National Public Health Institute (SZU).

The subdomain also contains one placeholder, for an indicator to be developed from the ongoing Patient Reported Indicator Survey (PaRIS project), which in its PROMs part focuses on patient reported outcome measures among patients aged 45 and over who have visited their general practitioner at least once in the preceding half a year, primarily targeting the chronically ill patients. The preliminary indicator custody of SZU can be further discussed based on national PaRIS project development.

Table A D.3. Experienced health indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Limitations due to health reasons (EU-SILC)	Gender, age, SES	International, time series	Eurostat	EU-SILC survey	CZSO	UZIS
Self-perceived health by sex, age and degree of urbanisation (hlth_silc_18)	age group, sex, and degree of urbanisation	International, time series	Eurostat	EU-SILC survey	CZSO	UZIS
Patient reported outcome measures based on the PaRIS project	PLACEHOLDER	international	OECD	PaRIS survey	MoH	SZU

Infographic A D.4 shows possible disaggregation of self-perceived health indicator from the EU-SILC survey.

Infographic A D.4. Experienced health

Source: OECD (2022[15]), OECD Health Statistics (2022).

Burden of disease

The subdomain of burden of disease analyses incidence and prevalence of the most common and/or most serious diseases, and the level of multimorbidity in population. There are 9 indicators in total.

Two indicators, on multiple chronic disease prevalence among the elderly and on limitations in daily activities among the elderly, come from the Survey of Health, Ageing and Retirement in Europe (SHARE). SHARE is a research infrastructure for studying the effects of health, social, economic and environmental policies over the life‑course of European citizens and beyond. It is a multi-disciplinary international time‑collection database of microdata on health, socio-economic status and social and family networks of individuals aged 50+ from all EU countries, Switzerland and Israel. In the Czech Republic, the SHARE team is based at the Economics Institute of the Czech Academy of Sciences and the CERGE‑EI, Charles University, and the survey is run by an agency selected in public procurement by the main project co‑ordinator in Germany.

On the prevalence of diabetes, a discussion was held which primary data source to use. It would be possible to use the EHIS survey, which also offers a disaggregation by socio‑economic status (SES), but since 2019 it will be carried only with a 6‑year period (note, the EHIS survey is run on CZSO sample of respondents, but the primary data custodian is ÚZIS). The claim data at the NRHZS registry, managed by UZIS, do not allow for SES disaggregation, but are available annually and have a potential for regional comparison. Indeed, the claim data involve people cured for diabetes by medicine, while the EHIS data also involve people only on a diet. For these reasons, CZSO, SZU and UZIS supported the use of the claim data for this indicator. In the indicator technical sheet, it is recommended to complement the prevalence indicator based on claim data by the results of the European Health Examination Survey (EHES) which focuses also on non-medicated, potential diabetic patients.

The indicator for adults at risk of depression has been selected due to its policy consequences and the ongoing mental health reform. Either data from Eurofound (European Foundation for the Improvement of Living and Working Conditions) can be used, if the e‑survey on Living, working and COVID‑19 will continue for future cycles, or the data from Eurostat’s EHIS survey can be used – data source to be yet discussed during the HSPA implementation phase.

Two indicators were included in the selection based on the recommendation of the CZSO and agreed on by the working group: indicator on people with health disabilities by age and sex and by the help of a third person, from a sample survey of the CZSO (a sample survey of persons with health limitations, not annual, but in a regular periodicity), and national statistics on incapacity to work, based on sick leaves due to illness data, which are available twice a year. In particular, the later may involve an indicator on the number of sick leaves per sick-insured population and/or average sick leave length in days.

The comorbidity index, calculated by the UZIS based on the methodology of Dey’s modification of Charlson’s comorbidity index (DCCI), has been presented in the Analytical study of the Health 2030 strategic document. For this reason, the indicator has been selected by the working group to populate the HSPA framework.

Table A D.4. Burden of disease indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Multiple chronic diseases among people aged 65 and over, by gender (% people aged 65 and over with at least two chronic diseases) (SHARE)	Gender, SES?	International, time series	SHARE	SHARE survey	SHARE team	SZU
Standardised trend of causes of hospitalisation per 100 000 inhabitants	Gender, region	International, time series, regional	Eurostat / OECD	NRHZS claim data	UZIS	UZIS
Prevalence of (selected) chronic diseases and disabilities (EHIS)	Gender, age, SES	International, time series	Eurostat	EHIS survey	UZIS	SZU
Prevalence of diabetes (% of population aged 15 and over)	gender, age, region	time series, regional	national (UZIS)	NRHZS claim data (Diabetic Registry)	UZIS	UZIS, alt SZU
People with health disabilities by gender and age and by the help of another person	Gender, age	Time series	national (CZSO)	CZSO sample survey	CZSO	CZSO
Share of adults at risk of depression (% of population aged 18+ at risk of depression) // TBD out of 2 sources	Gender	International, time series	Eurofound or Eurostat	Eurofound survey or EHIS survey	Eurofound or UZIS	NUDZ/SZU?
Limitations in daily activities among people aged 65 and over (% people aged 65 and over) (SHARE) // alternatively based on EHIS	Gender, SES?	International, time series	SHARE	SHARE survey	SHARE team	SZU
Comorbidity index by ÚZIS (the share of population with high comorbidity index based on administrative data)	Age, gender, region	Time series, regional	Dey’s modification of Charlson’s comorbidity index (DCCI)	NRHZS claim data	UZIS	UZIS
Incapacity to work (number per sick-insured population and/or average sick leave length) (sick leaves due to illness, CZSO data)	Gender, age, region	Time series, regional	CZSO	eSick-leave administrative data of the Czech Social Security Office	CZSO	CZSO

Note: NUDZ – National Institute of Mental Health [Národní ústav dusevního zdraví].

Infographic A D.5 and Infographic A D.6 show possible disaggregation and visualisation of the burden of disease indicators.

Infographic A D.5. Hospitalisation and chronic diseases

Note: The primary source of data for the depicted graphic is the NRHZS claim data registry at UZIS for number 1 and 2, and OECD Health Statistics for number 3 and 4.

Source: Depicted figures are taken from UZIS (2020[12]) for number 1 and 2, and OECD/European Union (2022[16]) for number 3 and 4.

Infographic A D.6. Sickness rate and risk of depression

Note: The primary source of data for the depicted graphic is the NRHZS claim data registry at UZIS for number 1, Eurofound’s Living, Working, and COVID‑19 e‑survey for number 2, and CZSO information system on sick leaves.

Source: Depicted figures are taken from UZIS (2020[12]) for number 1 and 3, and OECD/European Union (2022[16]) for number 2.

Domain: Health risks

The total of 12 indicators have been selected for this domain and they are grouped into 4 subdomains (habits, diet and nutrition, physical exercise, and environmental risks).

Habits

The subdomain of habits monitors behaviour related to risky lifestyle (i.e. substance abuse). The total of 5 indicators were selected. Except for one indicator, on mortality due to risk factors, other indicators’ primary data source can be the EHIS and EHES surveys, which have a 6‑year periodicity starting 2019 only. Despite the fact the EHIS survey data are in the custody of the UZIS, the indicators are assigned to the custody of the SZÚ, as it is in the scope of its expertise and can be contextualised by using their other surveys as well. Indeed, in between the EHIS rounds, SZU plans to employ the results of the national survey NAUTA, which has been run annually since 2018.

The alcohol consumption area is open for further discussion and decision to be made by the indicator custodian regarding what particular indicator to include. For instance, it can be total consumption of pure alcohol in litres, or the level of engagement in binge drinking, for the adult populations or for the youth. Again, either EHIS data or NAUTA survey data can be used.

Indeed, it is as well possible to include a joint figure on all lifestyle‑related health risks such as obesity, nutrition, exercise, smoking, etc, in comparison to other EU countries, for instance.

Table A D.5. Habits indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Number of deaths by risk factors	gender, age	International, time series	IHME (Eurostat, WHO?)	IHME (primarily CZE mortality registry	IHME	SZÚ
Smoking	Gender, age, SES	International, time series	Eurostat	EHIS survey // NAUTA	UZIS, SZU	SZÚ
Alcohol consumption	Gender, age, SES	International, time series	Eurostat	EHIS survey // NAUTA	UZIS, SZU	SZÚ
Estimate of cardio-vascular risks	gender, age, SES	International, time series	Eurostat	EHES survey	SZU	SZÚ
Health literacy	PLACEHOLDER			Survey data	SZU	SZU

Note: Mortality registry stands for the Registry of Causes of Death, which is being populated by information obtained from Certificate of Examination of the Deceased (List o prohlídce zemřelého, LPZ).

Infographic A D.7 shows possible disaggregation and visualisation of the indicators related to some lifestyle health risks (habits).

Infographic A D.7. Smoking habits, alcohol consumption and cardiovascular risk

Source: Depicted figures are taken from (SZÚ, 2022[17]).

Diet and nutrition

The subdomain of diet and nutrition monitors behaviour related to eating habits. The total of 3 indicators were selected. The primary data source is the EHIS survey, complemented by its European Health Examination Survey (EHES) part for the metabolic syndrome indicator. The EHES survey is managed by the SZÚ.

In the voting exercise, stakeholders selected indicators “metabolic syndrome” and “Body mass index (BMI) by sex, age and country of birth (hlth_ehis_bm1b)”. The indicator describing consumption of sweetened drinks was added based on the working group discussion due to its relevance in the debate of specific taxation of sugar-containing beverages and also due to its relevance for the dental healthcare needs, which has been a current health policy issue.

The draft of indicator technical sheets for the two EHIS indicators shall be consulted by the UZIS team for particular disaggregation, e.g. by the socio‑economic status.

Table A D.6. Diet and nutrition indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Metabolic syndrome	gender, age	International, time series	Eurostat	EHES survey	SZÚ	SZÚ
Body mass index (BMI) by sex, age and country of birth (hlth_ehis_bm1b)	Gender, age, SES	International, time series	Eurostat	EHIS survey	UZIS	SZÚ (UZIS)
Frequency of drinking sugar-sweetened soft drinks by sex, age and body mass index (hlth_ehis_fv7m)	Gender, age, SES	International, time series	Eurostat	EHIS survey	UZIS	SZÚ (UZIS)

Infographic A D.8. Consumption of selected food and prevalence of metabolic syndrome

Source: Depicted figures are taken from (SZÚ, 2022[17]).

Physical exercise

The subdomain of physical exercise monitors behaviour related to active lifestyle. The primary data source is the EHIS survey. In the scoring exercise, originally the stakeholders selected three indicators, but only 2 indicators were finally selected. The principal working group agreed on including one indicator describing work-related physical activity and one indicator describing physical activity not related to work.

Table A D.7. Physical exercise indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Effort involved in performing work-related physical activity by sex, age and degree of urbanisation (hlth_ehis_pe1u)​	Gender, age, SES	International, time series	Eurostat	EHIS survey	UZIS	SZÚ
Performing (non-work-related) physical activities by sex, age and degree of urbanisation (hlth_ehis_pe3u)​	Gender, age, SES	International, time series	Eurostat	EHIS survey	UZIS	SZÚ

Environmental risks

The subdomain of environmental risks monitors health risks related to living conditions. The total of 2 indicators were selected, however only one is a precise one, describing the air pollution. The second indicator is in fact a set of indicators generally referring to regular monitoring managed by the SZU. The monitorings focus on various environmental aspects (quality of water, occupational hazards).

The principal working group suggested to present the air pollution-related deaths in relation to other health risks-related deaths, similar to the OECD figure depicted in Infographic A D.9. Possibly, this subdomain could be merged with the other health risks subdomains, if this way of presenting the environmental indicators is taken on board. An alternative indicator for environmental health risks can be drawn from the Czech national strategy “ČR 2030”,1 which monitors also for the state of the environment, including the air pollution. During the HSPA implementation phase, the SZÚ will further specify what particular indicator to include, or create, for this subdomain in this theme.

Table A D.8. Environmental risks indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Premature deaths due to air pollution PM2.5 (rate per 100 000 population)​	age	international	WHO	SZU model	SZU	SZÚ
Monitorings: air pollution, drinking and bathing water pollution, community noise, contaminants in food chains and dietary exposures, human biomonitoring, occupational health hazards	regional	Time series, regional	SZÚ	SZÚ	SZÚ	SZÚ

Infographic A D.9. Air pollution-related deaths

Source: Depicted figure is taken from (OECD/European Observatory on Health Systems and Policies, 2021[11]).

Domain: Access

The total of 10 indicators have been selected for this domain and they are grouped into 3 subdomains (financial affordability, geographical accessibility, and waiting times).

Financial affordability

The subdomain of financial affordability analysis the financial affordability of healthcare for patients in a total of 4 indicators. The unmet need indicator shows the share of respondents reporting the reason for an unmet healthcare need being of financial nature.

The share of households with catastrophic health spending indicator is a placeholder. In 2012, it has been calculated on an ad hoc basis by the WHO Europe based on household budget survey data of the CZSO. The placeholder needs further discussion during the HSPA implementation phase. CZSO stated it would be feasible to provide update to the 2012 data and the WHO Europe methodology can be used as a basis, also allowing for international comparison. When this indicator is developed in the Czech HSPA, it may also offer comparability in time since household budget survey data are regularly collected.

The principal working group supports the inclusion of all three indicators with the highest level of disaggregation possible because of the high placement of the theme on policy agenda. These indicators will thus inform public discussion related to any policy proposals.

The working group also suggested to include the disaggregation of household out-of-pocket expenditures by type of expenditures (e.g. pharmaceuticals, hospitalisations, outpatient care, dental).

Further to this subdomain, the household out-of-pocket spending indicators can be complemented, in the technical sheet description, by an analysis of pharmaceutical expenditures above the annual cost sharing limit, which are then reimbursed to patients by the HIFs.

Table A D.9. Financial affordability indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
% reporting unmet medical needs by income	Gender, age, SES	International, time series	Eurostat	EU-SILC survey	CZSO	CZSO
Out-of-pocket spending on health as share of final household consumption (%)	income quintiles, seniors, families with children	International, time series	OECD	Household budget survey	CZSO	CZSO
Share of households with catastrophic health spending by consumption quintile (% of all households) // PLACEHOLDER	By income quintile	International, time series	WHO Europe	Household budget survey	CZSO	CZSO
Household out-of-pocket spending by type of expenditures (e.g. pharmaceuticals, hospitalisations, outpatient care, dental)	income quintiles, seniors, families with children	Time series	OECD	Household budget survey	CZSO	CZSO

Geographical accessibility

The subdomain of geographical accessibility analysis the accessibility of health services within a geographical area. Both indicators are placeholders – meaning they have not been regularly published and used. However, for both indicators the data should be readily available. During the HSPA implementation phase, discussions should focus on indicator methodology development. There are two sources of data available for patient registrations, either the claim data in the NRHZS registry, or the information gathered by the Capitation Center. It has been clarified in the discussions to use the Capitation Center data.

The working group participants also suggested to enlarge the indicator to the whole primary care, i.e. to include also registering dentists, gynaecologists, and paediatricians. The working group expressed some concerns regarding the relevance of data for the dentists as many people are provided the dental care outside of the SHI scope.

If data from the Capitation Center is used, age‑standardisation for registered patients would also be possible, similar to the way the Capitation Center applies it for reimbursement purposes.

For the indicator on the share of patients for whom primary care is accessible within a geographical limit, it has been discussed to use the number of people living within an enlarge municipality area [obce s rozšířenou působností, ORP], divided by the full-time equivalents of practicing general practitioners for adults and for children.

Table A D.10. Geographical accessibility indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Average number of patients registered with a GP, by region // PLACEHOLDER, data exist	region	Time series, regional	Capitation Center	Capitation Center	Capitation Center	MoH
Share of patients for whom primary care is accessible within a geographical limit // PLACEHOLDER, data exist	region	Time series, regional	MoH	Capitation Center	Capitation Center	MoH

Waiting times

The subdomain of waiting times analysis the accessibility of health services in time. Eventually 4 indicators were chosen, three of which are placeholders. The only existing indicator – unmet needs for dental examination due to financial, geographic, or waiting time reasons – is in the reality of the Czech Republic however more suitable for the “financial access” domain, as financial reasons are most often stated by responders as the reason for unmet needs for dental examination. Waiting times for appointments or procedures are not systematically measured in the Czech Republic. The issue could be solved if a three‑way electronic referral is introduced (three‑way for the patient, the referred provider, and the HIF), however that is not currently under any preparation in the CZE.

Table A D.11. Waiting times indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Waiting time of more than two weeks to get an appointment with a specialist (% of population asking an appointment)	PLACEHOLDER
Unmet needs for dental examination due to financial, geographic or waiting time reasons (% of unmet needs)	SES	Time series	Eurostat	EHIS survey	UZIS	UZIS
Waiting time for a first face‑to-face contact in an outpatient mental health care centre	Gender, regional PLACEHOLDER					MoH
Share of patients for whom primary care is accessible within a geographical limit // PLACEHOLDER, data exist	region	Time series, regional	MoH	NRHZS claim data	UZIS	UZIS

Domain: Quality

The total of 19 indicators have been selected for this domain and they are grouped into 4 subdomains (safety, clinical effectiveness, people‑centredness, and care appropriateness).

Safety

Indicators in the subdomain of safety explore the “degree to which the health system does not harm the patient”. There are 5 indicators in total.

The primary data source for all the 4 indicators is healthcare provider reporting to the Adverse Event Reporting System [Systém hlášení nežádoucích událostí, SHNU], managed by the UZIS. The reporting of adverse events is obligatory for all healthcare providers since 2018. The methodology has been developed and described in detail for each of the adverse events. At the time of this report drafting, healthcare providers reported only aggregate data, not individual patient data. International comparability of national data needs to be clarified during the HSPA implementation phase.

Table A D.12. Safety indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Prevalence of healthcare‑associated infections (% of patients hospitalised)		International, time series	ECDC	prevalence study (4, 5 years)	SZU	SZU
Number of hospitals monitoring prevalence of bloodstream infections based on ECDC			National (SZU)	SZU provider reporting	SZU	SZU
Share of selected microorganism resistance based on the EARS-NET methodology		International, time series	ECDC, EARS-NET methodology	SZU provider reporting, microbiological laboratories reporting	SZU	SZU
Prevalence of hospital-acquired cat II-IV pressure ulcers (% of patients hospitalised)	regional	International?, time series, region	national (UZIS)	provider reporting to the SHNU system	UZIS	UZIS
Falls in hospitals (ÚZIS)	regional	International?, time series, region	national (UZIS)	provider reporting	UZIS	UZIS

Infographic A D.10 shows available data on some of the safety indicators.

Infographic A D.10. Adverse events

Note: Primary data source is the Adverse Event Reporting System, managed by UZIS.

Source: The depicted table is taken from UZIS (2023[18]).

Clinical effectiveness

The subdomain of clinical effectiveness reviews the degree of achieving desirable outcomes and the degree to which care is provided according to evidence (evidence‑based medicine). There are 5 indicators in total.

Case fatality indicators for AMI and stroke within 30 days after admission have international methodologies developed by the OECD. For HSPA, the linked-data indicators were selected, monitoring mortality of patients also outside, or in a different, hospital. Internationally, data are collected once in two years; national data at UZIS are available annually.

The 5‑year cancer net survival rates are calculated by CONCORD programme, led by the London School of Hygiene and Tropical Medicine. While for international comparison the data may be published with a delay, UZIS generally has more recent national cancer survival data available, as shown by the analytical study to the National Oncology Plan; these however are not always internationally comparable, especially when disaggregated to regional level or cancer type.

In this subdomain, a placeholder is created for indicators on the quality of stroke care, based on the ongoing initiative of the Health Insurance Bureau (KZP) to develop tailored healthcare quality indicators.

This subdomain also includes an indicator on the use of multidisciplinary diagnostic teams (MDT) in cancer patients, for which UZIS has developed a comprehensive methodology in collaboration with the Czech Oncology Society. The use of MDTs has been part of clinical guidelines internationally. This indicator has also been related to the health policy priorities in the area of cancer care, as defined by the National Oncology Plan.

Table A D.13. Clinical effectiveness indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Case fatality within 30 days after admission for AMI (pop aged 45+, linked data, percentage)		International, time series	OECD	NRHZS claim data, mortality registry	UZIS	UZIS
Case fatality within 30 days after admission for ischaemic stroke (pop aged 45+, linked data, percentage)		International, time series	OECD	NRHZS claim data, mortality registry	UZIS	UZIS
Cancer survivals – percentage share by age, sex and type	Age, gender, cancer type	International, time series	CONCORD	National Oncological registry	UZIS	UZIS
Set of indicators on quality of care for patients with stroke		Time series	national (KZP)	claim data from HIFs	KZP	KZP
Patients with cancer reviewed by multidisciplinary diagnostic team (% of newly diagnosed cancer patients)	region	Time series, regional	national (UZIS)	NRHZS claim data	UZIS	UZIS

Infographic A D.11 shows possible disaggregation and visualisation of the clinical effectiveness indicators.

Infographic A D.11. Case fatality, clinical guidelines compliance, and cancer survivals

Note: The primary source of data for the depicted graphic is the NRHZS claim data registry at UZIS for number 1 and 2, and the Czech Oncology Registry at UZIS for number 3; being linked to the mortality registry for number 1 and 3.

Source: Depicted figures are from (OECD/European Union, 2022[16]) for number 1, (ÚZIS, 2022[19]) for number 2, and (OECD, 2023[14]) for number 3.

Care appropriateness

This subdomain targets issues related to the care appropriateness, which is defined as healthcare that is relevant to the patient’s health status, clinical needs, and latest medical knowledge (i.e. care provided by a provider with the right expertise and level of specialisation, in a timely manner and complying to clinical guidelines). There are 6 indicators in total.

Three of the indicators deal with drug consumption. Indicator on antibiotics use has been under development by the SZU, based on health insurers’ claim data processed by the Health Insurance Bureau. These can be further disaggregated by regions or lower municipalities, ab by type of antibiotics. Indeed, the OECD disposes of internationally comparable self-prescribing in primary care measure, looking at overall volume of antibiotics prescribed; the Czech Republic has not yet start to report data to this data collection, however.

The indicator on self-reported use of non-prescribed medicine is based on EHIS survey data, which allows for also SES disaggregation, however starting 2019 has 6‑year collection period.

Palliative care has been receiving special policy focus in recent years in the Czech Republic, which also resulted in new reimbursement schemes and coding assigned to it. This newly allows for calculating the palliative care indicator on cancer patients receiving palliative care, based on the OECD methodology of palliative care pilot, and the Czech Republic aims to start reporting this data to OECD statistics this year.

Indicators on antidepressant use and appropriate follow-up care for diabetic patients need to be further discussed and developed during the HSPA implementation stage; the Belgian HSPA indicators may serve as methodological examples.

Table A D.14. Care appropriateness indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Datasets on antibiotics use // under development in CZE	Region, type of ATB	Time series, regional	national (KZP)	claim data from HIFs	KZP	SZU
Caesarean section rate (per 1 000 live births)	region	International, time series, regional	OECD	NRHZS claim data	UZIS	UZIS
Use of antidepressants (total DDD/1000 pop/day) // to be developed in CZE	Age, gender PLACEHOLDER	Time series		NRHZS claim data or SÚKL	UZIS, alt SUKL	UZIS, after consulting NUDZ
Proportion of adult diabetics with appropriate follow-up (% of diabetic patients under insulin) // to be developed in CZE	Age, gender PLACEHOLDER	Time series	The Czech Medical Society of Diabetology + HIFs	NRHZS claim data	UZIS	UZIS
Patients who received palliative care (% of terminal cancer patients who died in the year) // under development in CZE	region	Time series (in the future), regional	OECD	NRHZS claim data	UZIS	UZIS
Self-reported use of non-prescribed medicines by sex, age and educational attainment level (hlth_ehis_md2e)	Age, gender, SES	International, time series	Eurostat	EHIS survey	UZIS	UZIS

People‑centredness

The patients’ subjective experience with the health system. There are 3 indicators in total in this subdomain, however two of them are placeholders, i.e. not yet existent.

The indicator on doctors providing easy-to‑understand explanations has been inspired by the Commonwealth Fund survey, which however does not include CZE. Discussion is thus needed among the Czech HSPA stakeholders on whether and how to include an extra question in existing patient surveys. One of the options may be to restrict the survey sample to inpatient care only and use the National Patient Satisfaction Survey, managed by the MoH.

The National Patient Satisfaction Survey project is the result of a long-term activity of the Ministry of Health, the main goal of which is to set up a unified system for monitoring and evaluating patient satisfaction in the Czech Republic and to strengthen the patient’s voice in the inpatient facilities. The survey targets patients in hospitals and participation of healthcare providers is voluntary. Since 2020, when the survey was first launched, the number of participating inpatient facilities has grown substantially. Originally, the project has been developed to serve informative purposes of hospital management, i.e. as a managerial tool. Based on consultations within the working group, an indicator is proposed for the HSPA framework building on the overall results of the patient satisfaction survey, with possible disaggregation by regions (however, this needs to be yet clarified in the HSPA implementation phase).

The last placeholder indicator shall be based on the outcomes of the ongoing OECD Patient Reported Indicator Survey project (PaRIS), with a special focus on patient reported experience measures (PREMs). Out of the several ongoing initiatives within the PaRIS project, the most promising for this placeholder indicator is the PaRIS International survey of people living with chronic conditions, which focuses on patients aged 45 and over visiting their general practitioner at least once in the preceding half a year.

Table A D.15. People‑centredness indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Doctor providing easy-to understand explanations (%)	PLACEHOLDER		Commonwealth Fund		?	?
Average rating of healthcare providers in the patient satisfaction survey // PLACEHOLDER – data exist	region	Time series, regional?	to be developed by MoH	Patient satisfaction survey	MoH	MoH
Patient reported experience measure based on the PaRIS project	PLACEHOLDER	international	OECD	PaRIS survey	MoH	MoH

Domain: Financial Stability

The domain of financial stability reviews and analyses the revenues of the health system, with emphasis put on the analysis of health sector financial resources and their stability (and sufficiency) over time. The total of 5 indicators have been selected for this domain.

Two of the indicators are based on OECD international methodology of the System of Health Accounts. The CZSO is generally able to provide updates on these indicators 6 months earlier than the OECD data collection (i.e. in the second half of a year for the preceding year).

Discussion was held among the working group members whether to choose the percent of GDP as the unit of measurement, or for international comparison rather a currency unit, because there is a public perception in the Czech Republic that health sector expenditures in real terms are far below the other EU countries. The group consent was to go with percentage of GDP for the first HSPA implementation, as there is currently an ongoing international discussion on defining a healthcare‑specific purchasing power parity; also, the purchasing power parity calculation is done by the international organisation, not by the CZSO.

The three other indicators are country-specific, looking at revenues and expenditures solely of the health insurance funds (HIF) and at the ration of HIFs’ financial reserves to current expenditures. The latter has been used by the MoH and MoF to supervise the financial development of the statutory health insurance system.

The two indicators on revenues and expenditures of HIFs, based on the MoF methodology of National Accounts, are presented in the HSPA as two separate indicators, however it is foreseen that the two will be interpreted and contextualise in mutual connection.

Table A D.16. Financial stability indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Total revenues of statutory health insurance	na	na	MoH, MoF (National Accounts)	HIFs, MoF	MoH, MoF	MoH, MoF
Total expenditures of statutory health insurance system	na	na	MoH, MoF (National Accounts)	NRHZS claim data	MoH, MoF	MoH, MoF
Health expenditure from public sources as share of total health spending (%)	na	International, time series	OECD, EST, WHO (System of Health Accounts)	System of Health Accounts	CZSO	CZSO
Health expenditure as a share of GDP (% GDP)	na	International, time series	OECD, EST, WHO (System of Health Accounts)	System of Health Accounts	CZSO	CZSO
Ratio of health insurance funds’ reserves to current expenditure	na	na	MoH, MoF	HIFs	MoH, MoF	MoH, MoF

Domain: Integrated care delivery

The total of 18 indicators have been selected for this domain and they are grouped into 4 subdomains (co‑ordination of care, continuity of care, long-term care, and prevention).

Co‑ordination of care

The subdomain of co‑ordination of care aims to monitor the level of an ongoing co‑ordination of multiple providers in the care for a chronically ill patient, including measurement of the consequences of insufficient co‑ordination (e.g. avoidable hospitalisations). There are 3 indicators in total in this subdomain, however two of them are placeholders, i.e. not yet existent.

The avoidable hospital admission indicators are being reported by the Czech Republic to the OECD dataset, i.e. internationally comparable data exist. During the HSPA implementation phase it needs to be discussed whether regional disaggregation is possible, and whether to use age‑standardisation for these calculations.

The use of emergency care is split into two indicators, both needing a methodology development. One of them aims to measure the (in)adequacy of standard outpatient care, while the other looks at the use of emergency care (both the emergency services and the out-of-hours outpatient service). Data for both exist in the NRHZS claim data registry at the UZIS. If only one indicator would be taken on board during the HSPA implementation phase, the working group participant support the inclusion of the indicator on use of emergency services after the last visit.

Table A D.17. Co‑ordination of care indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Avoidable hospital admissions (diabetes, COPD, CHF, hypertension)	Age?, gender?, region?	International, regional?	OECD	NRHZS claim data	UZIS	UZIS
Use of emergency care within 5 days after the last visit (after discharge or after outpatient visit)	Age?, gender?, region? PLACEHOLDER	regional?	[Belgian HSPA]	NRHZS claim data	UZIS	UZIS
Ratio of GP-registered and GP-nonregistered patients using emergency and out-of-hours care	Age?, gender?, region? PLACEHOLDER	regional?	[national (MoH)]	NRHZS claim data	UZIS	UZIS

Infographic A D.12 shows possible benchmarking and visualisation of the co‑ordination of care indicators.

Infographic A D.12. Avoidable hospital admissions

Note: The primary source of data for the depicted graphics is the NRHZS claim data registry at UZIS, and the OECD Health Statistics for the international comparison.

Source: Depicted figures are taken from OECD/European Observatory on Health Systems and Policies (2021[11]) for number 1 and OECD/European Union (2022[16]) for number 2.

Continuity of care

The subdomain of care continuity involves indicators aimed at monitoring patient’s journey through the healthcare system (a patient pathway) and the continuity of healthcare provided to a patient for a chronic condition or for a medical episode, which needs to be organised and provided by a multiple of healthcare providers (e.g. an early rehabilitation after a heart attack). There are 4 indicators selected in this subdomain.

Indicator on patient outcomes one year after discharge for selected diseases is being reported by the Czech Republic to the OECD dataset, i.e. internationally comparable data exists. During the HSPA implementation phase it needs to be discussed whether regional disaggregation is possible, and whether to use age‑standardisation for these calculations.

Two indicators relate to patient pathways for specific conditions and timely treatment recommendations that are generally included in clinical guidelines. UZIS is currently working on clinical guidelines for these specific health conditions and will be able to define the methodology for these two indicators in relatively near future, on time for the first HSPA implementation. Development of these indicators can also benefit from the ongoing projects of the KZP, which is developing mapping of patient pathways for selected procedures in collaboration with Medical Societies and some of the patient pathways templates should be available already during the year 2023.

The last indicator is a placeholder as well, monitoring the follow-up care of elderly patients after hospital discharge. Discussions on methodology of this indicators are already ongoing between the MoH and UZIS.

Table A D.18. Continuity of care indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Patient outcomes one year after discharge from stroke and heart failure (crude rate per 100 people)	region?	International, time series, regional?	OECD	NRHZS claim data/hospitalisation registry, mortality registry	UZIS	UZIS
Time from a positive screening for a certain cancer type to treatment	PLACEHOLDER		[UZIS clinical guidelines]	NRHZS claim data	UZIS	UZIS
Timespan between two episodes of care that should follow one another (according to clinical guidelines)	PLACEHOLDER		[UZIS clinical guidelines]	NRHZS claim data	UZIS	UZIS
General practitioner encounter within 7 days after hospital discharge (% patients 65+)	regional? PLACEHOLDER	Time series, regional?	to be developed (MoH and UZIS)	NRHZS claim data	UZIS	UZIS

Infographic A D.13 shows possible benchmarking of the continuity of care indicators.

Infographic A D.13. Continuity of care – patient outcomes

Note: The primary source of data for the depicted graphics is the NRHZS claim data registry at UZIS and the mortality registry, and the OECD Health Statistics for the international comparison.

Source: Depicted figure is taken from (OECD/European Union, 2022[16]).

Long-term care

The 3 indicators in the subdomain of long-term care are all placeholders and require further discussion to develop the desired indicators. The only indicator, on polypharmacy among the elderly, has known data source to date, but methodology needs further discussion during the HSPA implementation phase; the UZIS will explore the possibility of this indicator development. Still, using the NRHZS claim data registry has limited interpretation, because prescriptions with zero reimbursement are not included; this could be solved by using the SUKL prescription dataset. Still, over-the‑counter drugs are not included in either of the two datasets.

The two indicators on long-term care in residential facilities and home nursing care may potentially be grouped into one joint indicator, provided the two types of long-term care would be visually distinguished in indicator presentation. International comparison for these indicators may be difficult. As several countries use slightly different methodologies/definitions of the long-term care, results may not be completely comparable.

Table A D.19. Long-term care indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Long-term care in residential facility (% pop aged 65+)	PLACEHOLDER
Long-term home nursing care (% pop aged 65+)	PLACEHOLDER
Polypharmacy among the elderly (5 or more drugs of >80 DDD per year) (% of insured population 65+)	PLACEHOLDER – data exist			NRHZS claim data	UZIS

Prevention

There are 8 indicators in this subdomain. 5 of them were selected through the scoring exercise, and additional two were added by the principal working group discussion: one indicator on childhood mandatory vaccination (for SZU experts to decide on the exact vaccination to select, such as the DPT 3^rd dose), and an indicator monitoring the level of early detection of cancer by analysing the share of newly cancer patients diagnosed at early stages, based on the National Oncology Registry data.

An indicator on “Share of spending on prevention in current health expenditure (%)” has been removed from this subdomain, because it is also part of the indicator on healthcare expenditures by type of care in the Financing domain.

Discussions were held on the cancer screening indicators, where there is a possibility of two different data sources. Using the EHIS survey offers the possibility of socio‑economic status (SES) disaggregation but has lower data collection frequency and is less precise than the NRHZS claim data on cancer screenings, which does not allow for disaggregation by SES, but there is a possibility of exploring a disaggregation to regions. The members of the principal working group agreed to use the HRHZS claim data for screenings for the first HSPA report; however, the EHIS information from Eurostat and in particular the information it contains regarding the various socio‑economic disaggregation and international comparison shall be used to complement the context of the information provided by the screening claim-based indicators.

It has been also discussed to include an indicator on non-mandatory childhood vaccination, which has been however covered by the statutory health insurance, such as HPV or meningococcus vaccination, complementing the mandatory vaccination rates. Based on consultations with the SZU, an indicator on voluntary vaccination, represented by the HPV vaccination coverage, was added.

Information on the mandatory vaccination is included in an annual reporting of UZIS to the MoH and in the future there shall be a vaccination registry established at the UZIS.

Finally, interpretation of the dental preventive visits may become more difficult over time with more people opting to get the dental care, including prevention, from dentists who do not contract with HIFs, i.e. such care is not reimbursed. Still, the working group agreed this indicator has a value in itself, also to show how many people are still using the reimbursed dental services.

Table A D.20. Prevention indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Number of patients attending regular GP check-up	region	Time series, regional	MoH	HIF reporting to MoH	MoH	?
Number of patients attending regular dental check-up	region	Time series, regional	MoH	HIF reporting to MoH	MoH	?
Colorectal cancer screening (% of people screened), complemented by EHIS information	Gender, age, region (complemented by EHIS for SES)	Time series (complemented by EHIS for international)	UZIS	NRHZS claim data	UZIS	UZIS
Breast cancer and cervical cancer screenings, complemented by EHIS information	Age, region (complemented by EHIS for SES)	Time series (complemented by EHIS for international)	UZIS	NRHZS claim data	UZIS	UZIS
Vaccination against influenza, people aged 65 (% of people)	gender	International, time series	WHO/ECDC	?	UZIS	SZU
Childhood mandatory vaccination	[to be selected which vaccination]	International, time series, regional?	WHO?	HRHZS claim data or KHS survey	UZIS or SZU/KHS	SZU
HPV vaccination	regional	International, time series, regional	[to be developed within an EU project]	NRHZS claim data, vaccination registry [to be established]	UZIS	UZIS
% of cancer diagnosed at early stage		Time series	UZIS	National Oncology Registry	UZIS	UZIS

Infographic A D.14. Cancer screening and early cancer detection

Source: The depicted figures are taken from (OECD, 2023[14]) for number 1 and from (ÚZIS, 2022[19]) for number 2.

Domain: Cost-effective care delivery

In the domain of cost-effective care delivery, the indicators aim to monitor ways of providing healthcare that are considered cost-effective. It also measures the consequences of care failure, such as avoidable admissions. The total of 6 indicators were selected for this domain, out of which 2 are placeholders that need further development and one indicator needs further clarification to localise the international methodology for the Czech practice.

Table A D.21. Cost-effective care delivery indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Healthcare expenditures from SHI by ICD‑10 chapters, by sex by 1 inhabitant	Gender, age	Time series, regional	WHO	System of Health Accounts	CZSO	CZSO
One‑day surgical admissions (% of surgical admissions) // under development in CZE		International, time series, regional?	OECD	NRHZS claim data	UZIS	UZIS
ER visits for social, mental or psychic reason (% of admission in ER in general hospitals)	PLACEHOLDER
Distribution of the number of hospitalisations according to duration and ICD‑10 chapters		International?, time series, regional?	WHO	NRHZS claim data	UZIS	UZIS
Hospitalisation and average length of treatment by age group		International, time series, regional?	OECD	NRHZS claim data	UZIS	UZIS
Use of low-cost medication (% of total ambulatory DDDs)	PLACEHOLDER

Domain: Equitable care delivery

The total of 2 indicators have been selected for this domain. Both are survey data from the EU-SILC survey. Dental care receives special attention in this domain due to public concerns of limited accessibility to dental services in some areas; evidence however shows the issue may be with unequal opportunities for delivery, also due to financial reasons.

EHIS survey for the indicator on general unmet healthcare needs for various reasons has been considered for its comparability with other indicators selected for the Czech HSPA, however the annual availability of EU-SILC survey data was referred over the 6‑year period of the EHIS survey.

For the two indicators the UZIS is available for consultations for the lead indicator custodian, which has been assigned to CZSO.

Table A D.22. Equitable care delivery indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Self-reported unmet needs for medical examination by sex, age, main reason declared and income quintile (hlth_silc_08)	Age, gender, SES	International, time series	Eurostat	EU-SILC survey	CZSO	CZSO
Self-reported unmet needs for dental examination by sex, age, main reason declared and degree of urbanisation (hlth_silc_22)	Age, gender, SES	International, time series	Eurostat	EU-SILC survey	CZSO	CZSO

Domain: Workforce

The total of 11 indicators have been selected for this domain and they are grouped into 2 subdomains. Originally three subdomains were considered (capacity, shortage, and future needs). The principal working group concluded however that future shortage and future needs were too difficult to separate and suggested to merge them into a single subdomain. The domain is thus divided into current workforce capacity and future workforce capacity.

Current capacity

The subdomain of current workforce capacity monitors the latest availability and capacity of medical personnel. The total of 7 indicators were chosen for this subdomain, two of them are placeholders and require methodological development during the HSPA implementation phase.

The other 5 indicators look at total number of physicians and then at the number of practicing physicians and practising dentists separately, health workforce migration, and number of practicing nurses. The data source shall be the National Healthcare Workforce Registry [Národní registr zdravotnických pracovníků, NRZP]. However, currently the international reporting of physician data is not ideal and is based on the registry of the Czech Chamber of Physicians (data on all licensed physicians, no information on share of the practising physicians of this registry), healthcare providers’ economic reporting to the UZIS, and NRHZS claim data information on contracted full-time equivalents. The Czech Chamber of physicians is also the primary data custodian for physician migration data, e.g. number of physicians who received their medical education abroad.

Table A D.23. Workforce current capacity indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Physicians by sex and age (hlth_rs_phys)	Gender, age	International, time series, regional	Eurostat	Czech Chamber of Physicians // NRZP health workforce registry	UZIS	UZIS
Health workforce migration (hlth_rs_wkmg)	Gender, age	Time series, international	Eurostat	Czech Chamber of physicians // NRZP health workforce registry	UZIS	UZIS
Practising doctors per 1 000 population		International, time series, regional	Eurostat	// NRZP health workforce registry	UZIS	UZIS
Practising dentists per 1 000 population		International, time series, regional	Eurostat	// NRZP health workforce registry	UZIS	UZIS
Practising nurses per 1 000 population		International, time series, regional	Eurostat	// NRZP health workforce registry	UZIS	UZIS
Share of labour costs due to overtime / contracted working hours / total HR costs	PLACEHOLDER
Patient-to-nurse ratio	PLACEHOLDER	International? Time series?

Future capacity

The subdomain of workforce future capacity monitors the future possible availability and capacity of medical personnel. 4 indicators were chosen for this subdomain, with two of them focusing on medical and nursing graduates and the other two the share of older nurses and older physicians in the healthcare workforce. The data source for the numbers of graduates is the Student Registry of the Ministry of Education, Youth, and Sports.

Table A D.24. Workforce future capacity indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Medical graduates (/100 000 population)	Gender, age	International, time series, regional	ISCED F classification	Student registry	MoEdu	CZSO
Nursing and Midwifery graduates (/100 000 population)	Gender, age	International, time series, regional	ISCED F classification	Student registry	MoEdu	CZSO
Nurses aged 50+ (% of those professionally active)	Gender, age	International, time series, regional	Eurostat	NRZP health workforce registry	UZIS	UZIS
% of physicians aged over 60, or 65, based on [physicians by sex and age (hlth_rs_phys)]	Gender, age	International, time series, regional	Eurostat	NRZP health workforce registry	UZIS	UZIS

Note: MoEdu – Ministry of Education, Youth, and Sports.

Infographic A D.15. Medical and nursing students

Source: Depicted figures were taken from CZSO (2022[13]).

Domain: eHealth and technologies

The total of 6 indicators have been selected for this domain and they are grouped into 2 subdomains (health information infrastructure and the R&D and health technologies).

Health information infrastructure

This subdomain evaluates how fast and how easily is the health-related information accessible for a patient and for relevant providers. 4 indicators were chosen for this subdomain, two of them are however placeholders and require further methodology development. The indicator on “share of providers using ePrescription for medical devices” was selected as an indicator that shall monitor a voluntary eHealth activity of providers.

The indicator on “people searching health information online” has been taken from the CZSO’s Household survey on ICT use. There are two more survey questions that may potentially be of an interest: people communication with their physician online; and people who get an appointment online, through the use of an app or webform.

Table A D.25. Health information infrastructure indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
People searching health information online	Gender, age	International, time series	Eurostat	Survey on ICT usage in households and by individuals	CZSO	CZSO
Share of providers who keep medical records solely in electronical form		Time series, Regional	CZSO: ICT in healthcare	Provider reporting to UZIS	UZIS	UZIS
Percentage of physician practices that can share information with hospitals about patients’ current medications	PLACEHOLDER
Share of providers who use e‑prescription for medical devices	PLACEHOLDER	regional

R&D and health technologies

The subdomain monitors availability of hi-tech equipment and innovation in the healthcare sector. 2 indicators were chosen for this domain – CT, MRI and PET exams per 1 000 population and state budget expenditures on R&D in healthcare. However, further investigation into this subdomain may be needed.

Table A D.26. R&D and health technologies indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
CT, MRI and PET exams per 1 000 population		International, regional		NRHZS claim data	UZIS	UZIS
State budget expenditures on R&D in healthcare		International, time series	NAPS classification	R&D Information System (administrative data)	CZSO	CZSO

Domain: Financing

The domain of Financing analyses the expenditure side of the healthcare system, e.g. healthcare expenditures by type of care. The total of 2 indicators were selected for this domain. However, both indicators are quite broad and comprehensive and include a disaggregation to a number of other indicators. Hence, also the expenditures on long-term care and expenditures on prevention are included within these indicators and thus have been dropped from the respective subdomains of long-term care a prevention.

Table A D.27. Financing indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Healthcare expenditure in the Czech Republic by type of care	Type of care	International, time series	OECD/ Eurostat/ WHO	System of Health Accounts	CZSO	CZSO
Healthcare expenditure in the Czech Republic by type of care per 1 inhabitant	Type of care	International, time series	OECD/ Eurostat/ WHO	System of Health Accounts	CZSO	CZSO

Infographic A D.16. Healthcare expenditures per 1 inhabitant by type of care

Source: The depicted figure is taken from (CZSO, 2021[20]).

Domain: Resilience

The total of 8 indicators were selected for this domain, which aims to describe the ability of the healthcare system to absorb, respond to and adapt to unexpected events. Most of the indicators focus on the capacity of the health system to provide health services, reviewing its spare capacity. Three other indicators are placeholders that need to be further discussed and developed during the HSPA implementation phase. To date, none of the indicators capture the ability of a health system to absorb an unexpected event, i.e. system’s flexibility, adaptability, and the level of easiness by which spare capacities can be deployed where needed.

Table A D.28. Resilience indicators

Indicator name	Disaggregation	Benchmarks	Methodology	Data source	Data custodian	Indicator custodian
Long-term care beds in nursing and residential care facilities by NUTS 2 regions (hlth_rs_bdsns)	region	International, time series, regional	Eurostat	NRHZS claim registry, healthcare provider reporting	UZIS	UZIS
Supply of ambulatory child- and adolescent mental health care	PLACEHOLDER
Existence of an early detection drug shortage mechanism	PLACEHOLDER
Primary care capacity	PLACEHOLDER
Hospital beds per 1 000 population	Region	International, time series, regional	Eurostat	NRHZS claim registry, healthcare provider reporting	UZIS	UZIS
Occupancy rate of curative (acute) care beds (%)	Region	International, time series, regional	Eurostat	NRHZS claim registry, healthcare provider reporting	UZIS	UZIS
Adult ICU occupancy rate (%)	Region	International, time series, regional	Eurostat	NRHZS claim registry, healthcare provider reporting	UZIS	UZIS
Adult intensive care beds (per 100 000 population)	Region	International, time series, regional	Eurostat	NRHZS claim registry, healthcare provider reporting	UZIS	UZIS

Note

← 1.  Ministry of Environment, the Czech national strategy “ČR 2030”.