EUGLOREH project
THE STATUS OF HEALTH IN THE EUROPEAN UNION:
TOWARDS A HEALTHIER EUROPE

FULL REPORT

PART II - HEALTH CONDITIONS

5. HEALTH IMPACTS OF NON COMMUNICABLE DISEASES AND RELATED TIME-TRENDS

5.4. Diabetes

5.4.2 Data sources

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5.4.2 Data sources

 

 

5.4.2 Data sources

 

The different priorities adopted by EU Member States for the collection of data on chronic diseases hamper the establishment of common tools to monitor diabetes policy on a large scale, including an accurate measurement of the prevalence of the disease, risk factors, quality of care, and population outcomes.

In the year 1989, increasing awareness of the problem led to a meeting in St. Vincent (Italy) where representatives of Governmental Health Departments and PatientsAssociations from EU countries joined diabetes experts under the aegis of WHO regional Offices for Europe and the European Region of the International Diabetes Federation (IDF), European Region, to agree on a set of fundamental recommendations (Table 5.4.1). The Declaration acknowledged the need to optimise health care in all EU countries through the definition of targets for the reduction of complications and the development of an information infrastructure allowing constant monitoring of the  progress made.

For a number of reasons, among which an objective difficulty in measuring and exchanging of data on a large scale in a timely manner, the St.Vincent's objectives are still very relevant 20 years later.

Tracking quality of care is paramount to prevent diabetes complications, but it is not an easy matter to realise it Europe-wide, for the presence of a target population that is so large and diverse. Diabetes itself is a multifactorial disease, with a large number of variables entering the quality equation that must be taken simultaneously into account. Yet, the organization of diabetes information would represent an almost ideal model for chronic diseases, with very little technical obstacle to impede it: a huge pile of evidence is available, there is agreement on how to contrast it, it is clear what precisely needs to be measured.

However, collecting standardized and comparable data across countries remains a difficult job, mainly of collaborative nature, for which the support of health professionals is crucial, given their role in providing accurate clinical information.

On a technical level, computerised medical records may be harmonised by information systems linking individual clinical items to other databases routinely available. Some of the best diabetes registers in Europe have adopted innovative strategies to maximise the information available on diabetics, although their accuracy and reciprocal comparability seems still relatively limited.

Methodological problems must still be resolved:

·         in most cases population-based denominators are not known, since disease management programs and/or diabetes registers only cover those diagnosed with the diseases, and other sources are not available;

·         diabetes status is heterogeneously classified: earlier diagnosis due to increasing awareness of diabetes and to the diffusion of opportunistic screening among high risk individuals overestimate prevalence; different portion of cases with less severe diabetes are more likely to be recorded in some regions

·         epidemiological conclusions can be drawn on the basis of average national indicators (e.g. blood pressure increase by classes of age), but results would be different by directly using individual records, or at least sub-national averages (effect of different sources of variation, or ecological fallacy).

Relative to the last point, the issue of comparability becomes an obvious limitation in the frequent case where different countries/regions adopt different sets of indicators, an aspect that still limits the validity of local outputs at a broader international level.

 

Table 5.4.1Recommendations St.Vincent Declaration 1989:

 

Diabetes mellitus is a major and growing European health problem, a problem at all ages and in all countries.

It causes prolonged ill health and early death.

It currently (1989) threatens at ten million European citizens.

It is within the power of national governments and health departments to create conditions in which major reduction in this heavy burden of disease and death can be achieved.

 

Countries should be given formal recognition to the diabetes problem and deploy resources for its solution.

 

Plans for the prevention, identification and treatment of diabetes and particularly its complications - blindness, renal failure, gangrene and amputation aggravated heart disease and stroke, - should be formulated at local, national and European levels.

 

Investments now will earn great dividends in reduction of human misery and in massive savings of human and material resources.

 

General goals and 5yr targets should be achieved by the Organised activities of the medical services in active partnership with diabetic citizens, their families, friends and workmates:

 

-> Management of their own diabetes and education for it

-> Planning, provision and quality audit of health care

-> National, regional and international organisations for disseminating

   information about health maintenance

-> Promoting and applying research

 

 

5.4.2.1. National and regional registries

 

The construction of population-based diabetes registers represents an obvious solution to the problem of data collection to fulfil precise epidemiological requirements: each citizen diagnosed with T1DM/T2DM within a defined population enters a master index including individual characteristics at baseline, and at each visit clinical measurements, procedures, and outcomes are accurately recorded.

To make the profile more accurate, such information can be linked to administrative data including hospital discharges, pharmaceuticals, etc via a unique identifier assigned to the patient. This way, denominators are well set (population from a precise catchment area), and main epidemiological measures may be correctly estimated.

Unfortunately, only few examples of this kind exist in Europe, showing a heterogeneous degree of completeness, accuracy, and standardization.

At the National level, it is worth mentioning the cases of Sweden (Gudbjörnsdottir et al. 2003) and Denmark (Carstersen et al. 2008), while at the regional level the best referenced example is that of Tayside, Scotland (Morris et al 1997; Boyle et al 2001), followed by others more recently, among which Umbria, Italy (Massi Benedetti et al. 2006) has played a role in proposing its innovative approach as a basis for data exchange across collaborating registers in Europe (Carinci et al 2006).

In other cases, registers are client-based, i.e. they use only a portion of the information required, either by collecting data in a disease management program or one or more specialist clinics (Pruna et al. 2002; Azzopardi et al. 1995; Beck et al. 2001), or by extracting a list of subjects from databases that do not involve clinical measurements (e.g. hospital discharges), frequently without the presence of a diabetes diagnosis field validated by an expert clinician.

Client-based registers may provide valuable information on the average results obtained on a selected population, but their results are limited for policy, as we are uncertain on the level of representativeness of denominators, which in many cases lead to reports that are overoptimistic and do not include those hard-to-reach, that are more likely to experience bad outcomes.

 

5.4.2.2. IDF Diabetes Atlas

 

The International Diabetes Federation (IDF) has published regularly the Diabetes Atlas, containing estimates of the prevalence of diabetes and impaired glucose tolerance. Data of health expenditure are also provided. Currently, reported estimates refer to more than 200 Countries for the years 2007 and forecasts are given for 2025.

 

5.4.2.3. Quality of care monitoring

 

The St.Vincent Declaration paved the way for the definition of quality of care (QOC) information across Europe.

A landmark of QOC monitoring in Europe has been undoubtedly represented by the “Diabcarestream of projects, directly favoured by the Declaration and funded by the EU across the 90s. Diabcare allowed agreeing a basic set of parameters to be uniformly collected, as well as a common set of targets (indicators) that can be conveniently used to compare own results against national and international averages.

The approach of a common benchmarking system for quality improvement is still valid today and underpins many monitoring systems currently existing in Europe, and beyond. Quality of care can be measured by a range of processes and outcomes indicators.

The OECD basic set of quality indicators undoubtedly reflect the original situation of Diabcare, showing that a large number of indicators may result into an ambitious task if confronted with everyday practice. As a matter of fact, out of only nine indicators judged to be immediately feasible (Greenfield et al 2004, see Table 5.4.2), only three were available in the first report (i.e. lower extremity amputations rates, annual eye examination and poor control of Glycated HaemoglobinHbA1c, see Armesto et al. 2006) due to problems in national representativeness of data and other comparability issues.

More recently, an opportunity for fine monitoring of QOC in primary care has been created by national professional contracts, which have included target indicators as a basis for budgeting. In the UK, data collection on a range of indicators (of which several for diabetes) takes place on a regular basis through the National Diabetes Audit and the Quality and Outcomes Framework.

 

Table 5.4.2. OECD indicators

 

 

Areas

 

Indicator Name

Processes of diabetes care

Annual HbA1c testing

Annual LDL cholesterol testing

Annual screening for nephropathy

Annual eye exam

Proximal outcomes

 

HbA1c control                                      

LDL-C  control

Distal outcomes

Lower extremity amputation rates

Kidney disease in persons with diabetes

Cardiovascular mortality in patients with diabetes

 

 

 

5.4.2.4. Health Surveys

 

Health Interview Surveys (HIS) are based on self reported information provided by the participants, whereas Health Examination Surveys (HES) include in addition also validated information through physical examination and blood analysis

It is well known that the self reporting of the HIS can cause measurement problems on a range of individual due to recall bias and imprecise estimates. Differences between different national surveys persist, particularly for sensitive topics e.g. heavy drinking, smoking etc. The usual recommendation in this field is that surveys should include national population-based samples and must be repeated at regular time-intervals.

A HES, provided that the sample is well drawn, delivers the most reliable information on the disease status. As such, it should be a component of national/international health monitoring for different parameters. However, projects to finalise a series of HES at the European level are still in their initial phase.

Detailed methodologies have been described by the HMP Health surveys in the EU: HIS and HIS/HES evaluations and models, (01/09/2002).

 

5.4.2.5. Sentinel Surveillance Network

 

Another possibility to obtain information was sought through the Sentinel Practice Surveillance Network (SPSN). In several EU countries, primary care based sentinel practice surveillance networks have been established, to recruit clusters of motivated GP’s to perform surveys on different items. Among these items, diabetes prevalence and diabetes management have been included (Fleming, 2004).

In this case participants are motivated and the standards are well defined. However, representativeness at a national level must be carefully ascertained, as recruitment on the basis of self-motivation can be very prone to selection bias. Furthermore, only primary care is included and mainly diagnoses are monitored. Currently, SPSN is considered an interesting but not an optimal data source.

 

5.4.2.6. Hospital discharge records

 

Hospital Discharge Records (HDRs) have been used for a long time to abstract information on procedures and outcomes experienced by patients identified with a diagnosis of diabetes mellitus.

The establishment of national reimbursement systems in most countries, mostly based on Diagnosis Related Groups (DRG), has favoured consistent and uniform coding for all admissions, and the definition of national data formats that have been fairly constant during the last years.

Normally, an HDR involves the registration of individual characteristics, plus a variable number of diagnoses and procedures (based upon the standardized ICD classification) administered during the hospital stay, and other main aspects related to the admission/discharge (admission from other hospital, discharge at home, death, etc.). The main hospital discharge diagnosis usually determines the reimbursement for the hospital, and data are generally accessible by request for research and analysis through national/regional health departments.

Several methodological problems exist with the use of HDRs

Coding for primary and secondary diagnosis may be biased by reimbursement algorithms and highly heterogeneous across hospitals and territories. An admission for diabetes, unless linked to the occurrence of complications, is increasingly considered to be inappropriate, particularly as a first diagnosis, which leads it to be frequently under-reported in all instances. Furthermore, harmonisation of hospital data is still to be realised across the EU and it will require considerable work in the future.

Nevertheless, HDRs may considerably increase information content on diabetes  through linkage with other databases: diabetic patients may be identified by other means, including pharmaceutical prescriptions, ambulatory and specialist visits, etc. The pattern of hospitalisation may become much more complete through a unified list, contributing significantly to define estimates of rates of complications that are frequently recorded in hospitals.

A particular case of outcome is that of mortality: HDRs may provide information on fatality rates, but they can also hide part of the results as patients may be discharged when conditions get critical. To obtain unbiased event rates after hospital interventions is necessary to organize a mortality register that is lacking in most EU countries at the national level.

 

5.4.2.7. Insurance/reimbursement records

 

Insurance/reimbursement schemes (RS) are increasingly making use of specific national unique identification numbers, including the use of smart cards, which involve the use of a specific flag that would identify diabetes as a specific condition granting access to a range of ad hoc services.

Information on age, sex and linked medication, doctor’s visits and special diagnostic or therapeutic interventions can be obtained in an anonymous and very reliable way using this source.

However, there is usually no clinical information being collected, meaning that most indicators cannot be estimated using this source.

However, RS can provide useful information to complete an existing register, through a central identification number that can be used for quality control purposes.

 

5.4.2.8. National drug sales

 

Some studies have utilised national drug sales to estimate prevalence of different pathologies (e.g. diabetes mellitus). National annual drug sales are recorded in most countries.

Through this source and the standard classification of ATC and DDDs (Defined Daily Doses) it is possible to derive an indirect estimate of prevalence and the pharmaceutical use made by diabetic patients.

A limitation of this method lies in the variations of mean daily doses adopted by different countries (Papoz 1993), which poses issues of comparability of the results.

 

5.4.2.9. Conclusion

 

Different data sources provide very different information on diabetes.

Registers may become the most accurate source, but they need to be complete both in terms of individual measurements and coverage of the target population. In all cases, they do not provide us with information on undiagnosed patients and the general population. This must be extracted from other sources.

Through self-reporting and sentinel networks, all diagnosed patients will be included in statistical reports, whereas information obtained through hospitals and health insurances only includes patients receiving a treatment or having been hospitalised.

Health examination surveys detect both diagnosed and undiagnosed patients which is impossible health interview surveys. Whether the evaluated cohort is representative for the population in a given geographical area should be carefully considered in each of the above.

As a matter of fact, there are only few examples of truly population-based, harmonised, and complete diabetes sources. The case of Tayside, Scotland provides a good example of diabetes information system through which clinical practice and statistical information may get the best estimates using large scale record linkage.

The human as well as economic burden of diabetes necessitates the development and implementation of a surveillance system on diabetes and its complications of this nature across Europe. Close monitoring of the impact of therapeutic approaches and new medications may help to improve the outcome and reduce the cost of this chronic disease.

To make targets clearer and more realistic, the EUDIP project, funded by the European Commission, has delivered a short-list of core and secondary indicators that is now given considerable attention and are presented in Tables 5.4.3 and 5.4.4.

 

Table 5.4.3. EUDIP core indicators and their availability in EUCID over 20 countries

 

Core indicator

 

Countries with recent data

Data sources

 

I Risk factors of diabetes

 

 

% of the general population with a BMI30 kg/m2            

14

 

HES/HIS Registry

II Epidemiology of diabetes

 

 

Annual incidence of Type 1 diabetes by age/100,000 population 014 years

12

HES/HIS Registry

Prevalence of diabetes mellitus/1000 population   

15

HIS/HES/SPSN/RS Registries

IV Epidemiology of complications

 

 

Annual incidence of blindness due to diabetic retinopathy/total annual incidence of blindness                        

4

HIS/HES/SPSN/RS Registries

Annual incidence of dialysis and/or transplantation (renal replacement therapy in patients with diabetes/1,000,000 general population                    

11

HIS/HES/SPSN/RS Registries

Prevalence (stock) of dialysis/transplantation (renal replacement therapy) in patients with diabetes /1,000,000 general population                   

11

HIS/HES/SPSN/RS Registries

Annual death rate in patients who have as primary or any cause of death diabetes mellitus/100,000 general population             

12

National Registry

Annual death rate in the general population from all causes /100,000 general population, adjusted for European Standard Population

12

National Registry

Acronyms:

ICD 9: Diabetes mellitus 250; ICD 10: Diabetes mellitus E1014; HES: Health Examination Survey; HIS: Health Interview Survey; UNN: Unique national Number; RS: Reimbursement Structure; SPSN: Sentinel Practice Surveillance network; HDR: Hospital Discharge Records.

Definitions

Annual incidence of diabetes in children (0-14 year), with type 1 and 2 not separated, is defined by EUCID as the number of new cases of diabetes in children in one year per 100.000 children.

Prevalence of diabetes, defined by EUCID as the ratio of the number of cases of diabetes present in the population per 1000 individuals in that population using the definition of diabetes provided by WHO/ADA criteria (1998-9), is extremely variable.

Prevalence over 25 yrs, an EUCID indicator, is very similar to the pattern found for all ages. Almost in all countries, prevalence reaches a peak over 75 years of age, with values all over 100/1000 for EUCID participating countries. Notably, the difference is really striking with the IDF Atlas 2006, reporting a range between 40/1000 (UK) and 118/1000 (Germany), and a median of 87.5/1000. These different results, probably deriving from the lack of uniform surveillance in the EU, emphasize the importance of the problem as well as the need for an immediate action.

Annual incidence of blindness due to diabetic retinopathy is defined as the ratio of the number of new cases of blindness in one year due to diabetic retinopathy/total number of cases of blindness in the same year tracked by independent blindness national registries, where blindness is defined as legal blindness (according to the national legislation). EUCID found that the percentage for this indicator varied from 2% (Turkey) to 15% (Germany) amongst the four countries that could provide data.

Annual incidence of dyalisis and/or transplantation is defined as the number of new cases with dialysis and/or transplantation (renal replacement therapy) per 100,000 individuals in the diabetic population in one year.

Prevalence (stock) of dialysis/transplantation per 100.000 diabetic population is defined as the number of all cases with dialysis/transplantation per 100,000 individuals in the diabetic population.

Mortality is the most fundamental outcome indicator of all, through which countries can evaluate the long term impact of health policies. This indicator is defined as the annual death rate in patients who have as primary or any cause of death diabetes mellitus/100,000 general population. Despite the simplicity to measure such condition, mortality data in diabetes are not very reliable. This is because, with the exception of diabetes coma, most diabetic patients die from macrovascular complications, which lead to record diabetes not as a primary cause, and often not even as a secondary cause.

 

Table 5.4.4. EUDIP secondary indicators and their availability in EUCID over 20 countries

Secondary indicator

 

Countries with

recent data

II Epidemiology of diabetes

 

Prevalence of subjects with impaired glucose tolerance and/or diet only

2

III Risk factors for complications

 

Percent of diabetic subjects and a HbA1c tested in last 12 months

16

Percent of diabetic subjects and a HbA1c tested, with HbA1c>7.5%

14

Percent of diabetic subjects with a lipid profile in the last 12 months

14

Percent of diabetic subjects tested in the last 12 months with total cholesterol>5 mmol/l

14

Percent of diabetic subjects tested in the last 12 months with LDL>2.6 mmol/l (>3 mmol/l)

13

Percent of diabetic subjects tested in the last 12 months with HDL<1.15 mmol/l (<1.0 mmol/l)

11

Percent of diabetic subjects tested in the last 12 months with triglycerides >2.3 mmol/l (>2.0 mmol/l)

12

Percent of diabetic subjects tested for microalbuminuria in the last 12 months

12

Percent of diabetic subjects with a tested microalbuminuria in the last 12 months, with an abnormal level

11

Percent of diabetic subjects with a tested blood pressure measurement in last 12 months

14

Percent of of diabetic subjects with a tested blood pressure in the last 12 months showing a value >140/90

10

Percent of diabetic subjects who are smoking

14

Percent of diabetic subjects and a BMI25 kg/m2, ≥30 kg/m2

13

Age at diagnosis of diabetes mellitus by 10 year age bands

2

IV Epidemiology of complications

 

Percent of diabetic subjects with fundus inspection in the last 12 months

11

Percent of diabetic subjects tested in the last 12 months, with proliferative retinopathy in last 12 months

6

Percent of diabetic subjects who received laser treatment<3 months after diagnosis of proliferative retinopathy

1

Percent of diabetic subjects tested serum creatinine in last 12 months

13

Percent of diabetic subjects with ESRF serum creatinine400 mol/l

9

Annual incidence of amputations above the ankle (if available: non traumatic but medical) in diabetic patients /100,000 general population

9

Annual incidence of stroke in diabetic patients /100,000 general population

10

Annual incidence of myocardial infarction in diabetic patients/100,000 general population

10

 

Definitions:

In terms of clinical management in diabetes, parameters include blood glucose management, blood pressure, blood lipids, kidney functions and microalbuminuria. The complete set is difficult to obtain, thus it is important to concentrate on the most relevant factors.

Impaired glucose tolerance is defined as the percentage of general population with impaired fasting glucose, defined as a fasting plasma glucose equal or above 6.1 mmol/l and below 7.0 mmol/l (fasting plasma glucose6,1 mmol/l and <7,0 mmol/l).

Measurement of glycated haemoglobin (HbA1c) in the last 12 months is measured as the percentage of the total diabetic population that had their HbA1c measured in the last 12 months. EUCID results were obtained with very different sources, and the fact that for many of them the result was extremely positive (60% countries above 90%) casts some doubts on the actual reliability of these estimates and are not reported here.

Level of HbA1c>7.0% is an indicator of poor management causing intermediate outcomes that can lead to severe complications. It is defined as the percentage of total diabetic population with HbA1c tested and a value of HbA1c above 7.0%. This indicator is also measured by OECD, albeit with a different cut-off value (9.5%) that makes data less comparable and applicable at EU level.

Measurement of total cholesterol in the last 12 months is an important parameter for lipids in the diabetic population. It is measured as the percentage of total diabetic population that had their total cholesterol tested in the last 12 months.

Total cholesterol level>5 mmol/l is an important indicator of lipidic control that is measured as the percentage of diabetic population with their total cholesterol tested in last 12 months showing a total cholesterol above 5 mmol/l.

Measurement of LDL cholesterol in the last 12 months is another important aspect of lipid management, as measured by the percentage of the diabetic population that had their LDL-cholesterol tested in the last 12 months.

LDL cholesterol level >2.6 mmol/l is an important indicator of lipidic control that is measured as the percentage of the diabetic population with LDL-cholesterol tested in the last 12 months and presenting a value above 2.6 mmol/l.

Measurement of HDL cholesterol in the last 12 months is also taken as an indicator for lipids, measured by the percentage of the diabetic population that had their LDL-cholesterol tested in the last 12 months.

HDL cholesterol level <1.0 mmol/l for men and <1.25 mmol/l for women is measured as the percentage of the diabetic population with their HDL-cholesterol tested in the last 12 months and HDL cholesterol below 1.0 for men and 1.25 mmol/l for women.

Measurement of triglycerides in the last 12 months is the last important parameter for lipids in the diabetic population. It is measured as the percentage of total diabetic population that had their total triglycerides tested in the last 12 months.

Triglycerides level >2.3 mmol/l is an important indicator of lipidic control that is measured as the percentage of diabetic population with their total cholesterol tested in last 12 months showing a total cholesterol above 2.3 mmol/l.

Microalbuminuria should be also tested every year. The clinical management indicator is defined as the percentage of total diabetic population that had microalbuminuria tested (or proteinuria tested if persistent proteinuria exists) in the last 12 months.

An abnormal level of albuminuria and proteinuria is an important element of clinical management. It is measured as the percentage of diabetic population with microalbuminuria/proteinuria tested in last 12 months with a microalbuminuria above the threshold of normal (locally defined) or a proteinuria.

Blood pressure control is measured through the percentage of diabetic subjects that had their blood pressure measured in the last 12 months. The median is 95% for Germany. This clinical parameter seems to have the highest priority in Europe with a total of 8 countries achieving a percentage of at least 80%. Interestingly, there seems to be no clear association between the measurement of blood pressure and age.

Level of blood pressure is measured as the percentage of diabetic subjects that had their blood pressure measured in the last 12 months and reported a diastolic blood pressure above 90 and/or a systolic blood pressure above 140 mm Hg.

Smoking is defined as any type of smoking and relates to the percentage of smokers in the diabetic population.

Levels of BMI among diabetics are measured as the percentage of diabetic population that had their BMI measured or had both weight and height available and had a value above or equal to 25/30 kg/m2.

Age at diagnosis by age bands is an extremely difficult indicator to collect, unless there are sophisticated registers in place. Indeed, this fact was not reported by EUCID, due to the small number of countries submitting data (N=2).

Fundus inspection is a fundamental examination to check for the existence of ophthalmologic complications. The process indicator is measured by the percentage of diabetic population that had their eye fundus inspected in last 12 months. This indicator is the only one reported by the OECD (Armesto et al 2006) as fit for international comparisons in diabetes.

Proliferative retinopathy is defined as the percentage of diabetic population that had their eye fundus inspected in the last 12 months and were diagnosed with a proliferative retinopathy.

Indicator on timely laser treatment of retinopathy is defined as the percentage of diabetic population that had their eye fundus inspected in the last 12 months and were diagnosed with a proliferative retinopathy and had laser treatment within 3 months.

Control of serum creatinine is defined as the percentage of diabetic population that had their serum creatinine tested during the last 12 months.

Renal failure is measured as the percentage of diabetic population with creatinine tested in the last 12 months and End Stage Renal Failure (ESRF), which in turn is defined as serum creatinine above or equal to 400 umol/l (WHO).

The annual incidence of major amputations is defined as the number of new cases of major amputations (above ankle) per 100,000 individuals in the diabetic population in one year. Amputations are also recorded by OECD, albeit not included in the list of indicators fit for international comparisons.

The annual incidence of stroke is defined as the number of new cases with stroke (both ischemic and bleeding) per 100,000 individuals in the diabetic population in one year.

The annual incidence of any myocardial infarction is defined as the number of new cases with any myocardial infarction per 100,000 individuals in the diabetic population in one year.