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Norwegian Institute of Public Health
WHO Collaborating Centre for Drug Statistics Methodology
Postboks 222 Sk°yen
0213 Oslo

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Tel:  +47 21 07 81 60

Use of ATC/DDD
Published Friday June 26 2009

Implementation and maintenance of the ATC/DDD methodology
When the decision to introduce and use the ATC/DDD methodology is taken, it is essential to realize that its proper use inevitably includes an important and time-consuming first step:  Each pharmaceutical product has to be linked to the appropriate ATC code and DDD.  For monitoring and comparing drug use internationally it is important to ensure that the data retrieved are comparable, in other words that the ATC groups from different countries, regions or health facilities do have the expected contentIn order to achieve this, it is of vital importance that the officially correct ATC code is assigned to each pharmaceutical product package.  If possible, this work should be done on a national basis to secure consistent use of the methodology within a country.  Many countries have established systems of unique identifiers for pharmaceutical products at the package level.  The number of DDDs per package should be calculated for each product package and this information should be added to the pharmaceutical products registry.  The national medicines list and ATC/DDDs should be linked at the level of the unique product identifier. 

It is recommended to have a common structure of these pharmaceutical products registries.  National registries should as a minimum include the following variables:

  • Unique identifier (registration number)
  • Medicinal product name (brand name/trademark)
  • Pharmaceutical form
  • Strength
  • Pack size
  • ATC code
  • Active ingredient(s)
  • DDD
  • Route of administration
  • Number of DDDs in the pack

Good procedures for updating national or other registries with new ATC codes/DDDs and alterations should be established.  It is recommended that the responsibility for quality assurance and validation of national registries is allocated to a national body in each country.  This work should be performed by competent persons with good knowledge of the ATC/DDD methodology.

An updated version of the ATC/DDD Index is issued in January each year.  To be able to compare drug utilization data from different countries and time periods, it is essential to know which ATC codes and DDDs are used.  A minimum number of changes in the ATC codes and DDDs are made annually. Thus, it is important to give proper references to the ATC/DDD version used when presenting drug consumption figures.

Drug Utilization (to the top)
The main purpose of the ATC/DDD system is as a tool for presenting drug utilization statistics with the aim of improving drug use.  This is the purpose for which the system was developed and it is with this purpose in mind that all decisions about ATC/DDD classification are made.  Consequently, using the system for other purposes can be inappropriate. 

Use of the ATC/DDD system allows standardisation of drug groups and represents a stable drug utilization metric to enable comparisons of drug use between countries, regions, and other health care settings, and to examine trends in drug use over time and in different settings.

Collecting and publishing drug utilization statistics are critical elements in the process of improving the prescribing and dispensing of medicines.  For drug utilization statistics to have the best possible impact on drug use, the statistics need to be used in a focused and active manner.

Examples of ways in which drug utilization statistics based on ATC and DDDs have been and can be used to improve drug use include the following:

  • National publications, which provide clinicians, pharmacists and others with a profile of drug consumption in the country (with or without comparisons between countries or between areas within the country).
  • Publications providing feedback within health services to individual health facilities, groups of health care providers, or individual health providers.
  • Use of drug utilization statistics by national health systems, universities, drug information centres, and others to identify possible over use, underuse or misuse of individual drugs or therapeutic groups.  Depending on the situation, this information can then be used to initiate specific studies or specific educational interventions.  Educational interventions may include articles in drug bulletins, articles in scientific journals, letters to clinicians, etc.

Data sources (to the top)
The ATC/DDD system can be used for collection of drug utilization statistics in a variety of settings and from a variety of sources: 

Examples are:

  • Sales data such as wholesale data at a national, regional or local level.
  • Dispensing data either comprehensive or sampled.  Computerised pharmacies can easily collect data on drugs dispensed.  Alternatively, sample data can be collected manually.  Reimbursement systems, which operate in a number of countries at the national level provide comprehensive dispensing data down to the individual prescription level, as all prescriptions are submitted and recorded for reimbursement.  This is generally called “claims” data.  Similar data are often available through health insurance or health maintenance organisations. These databases can sometimes allow collection of demographic information on the patients, and information on dose, duration of treatment and co-prescribing.  Linkage to hospital and medical databases can provide information on indications, and outcomes such as hospitalisation, use of specific medical services, and adverse drug reactions.
  • Patient encounter based data.  This is usually collected by specially designed sampling studies such as those carried out by market research organisations.  However, increasing use of information technology at the medical practice level are making such data more available.  These methods have the advantage of potentially providing accurate information on Prescribed Daily Doses, patient demographics, duration of therapy, co-prescribing, indications, morbidity and co-morbidity, and sometimes outcomes.
  • Patient survey data.  Collection of data at the patient level can provide information about actual drug consumption and takes into account compliance in filling prescriptions and taking medications as prescribed.  It can also provide qualitative information about perceptions, beliefs, and attitudes to the use of medicines.
  • Health Facility data.  Data on medication use at all the above levels is often available in health care settings such as hospitals and health centres at regional, district, or village level.

DDD indicators (to the top)
Drug utilization figures expressed in DDDs are generally reported in units that control for population size differences.  This provides a measure of exposure or therapeutic intensity in a defined population, allowing comparisons across various time periods and population groups.

Drug Utilization figures should ideally be presented using a relevant denominator for the health context such as numbers of DDDs per 1000 inhabitants per day, DDD per inhabitant per year, or as DDDs per 100 bed days.

  • DDD per 1000 inhabitants per day: Sales or prescription data presented in DDDs per 1000 inhabitants per day may provide a rough estimate of the proportion of the study population treated daily with a particular drug or group of drugs.  The figure 10 DDDs per 1000 inhabitants per day can be interpreted as follows: in a representative group of 1000 inhabitants, 10 DDDs of the drug are utilized on average, on any given day of the year analysed.  Alternatively this can be expressed as 10/1000 (1%) of the population are receiving this drug each day in that year.  This estimate is most useful for drugs used chronically and when there is good agreement between the average prescribed daily dose (PDD) and the DDD.

  • DDD per 100 bed days: The DDDs per 100 bed days may be applied when drug use by inpatients is considered.  The definition of a bed day may differ between hospitals or countries.  A common definition is: A bed day is a day during which a person is confined to a bed and in which the patient stays overnight in a hospital.  Day cases (patients admitted for a medical procedure or surgery in the morning and released before the evening) are sometimes included as one bed day and sometimes excluded.  The same definition of bed days should always be chosen when performing comparative studies.  The figure 70 DDDs per 100 bed days of hypnotics provides an estimate of the therapeutic intensity and estimates that 70% of the inpatients receive one DDD of a hypnotic every day.  This indicator is applied in analyses of in-hospital drug use and it is quite useful for benchmarking in and between hospitals.

  • DDD/patient: This indicator is often calculated in pharmacoepidemiological databases and expresses the treatment intensity/total exposure according to a defined study period.  If the actual dose used is equivalent to the DDD, the DDD/patient would also express number of treatment days in a specific period. 

  • DDDs per inhabitant per year: This indicator is often considered useful to present the figures for antiinfectives (or other drugs normally used in short periods).  It will give an estimate of the number of days for which each inhabitant is, on average, treated annually.  For example, 5 DDDs/inhabitant/year indicates that the consumption is equivalent to the treatment of every inhabitant with a 5 days course during a certain year.  Alternatively, if the standard treatment period is known, the total number of DDDs can be calculated as the number of treatment courses, and the number of treatment courses can then be related to the total population.

Drug utilization data presented in DDDs give a rough estimate of consumption and not an exact picture of the actual drug use, and the estimates described above are only true if there is good agreement between the actually prescribed dose and the DDD.

For some drug groups where DDDs have not been established, alternative ways of presenting data are recommended.  For example, consumption of antineoplastic agents in ATC group L01 can be presented in grams of active ingredient.

When there is a known discrepancy between the prescribed daily dose (PDD) and the DDD, it is important to take this into account when interpreting drug consumption figures.  Caution should also be taken in situations where the recommended dosage differs from one indication to another (e.g. antipsychotics), in severe versus mild disease (e.g. antibiotics) and where PDDs may differ from one population to another (e.g., according to sex, age, ethnicity or geographic location).

Since alterations of ATC and DDDs do occur it is important to be aware of which version of the ATC index is used in drug consumption studies especially when comparing the data over time and when making international comparisons.

When presenting trends in drug consumption over time, the data for the whole period (e.g. all years) should always be updated (recalculated) by using the most recent version of the ATC index.

Drug Safety Assessment (to the top)
The WHO Programme for International Drug Monitoring (PIDM): The WHO PIDM aims to enhance patient care and patient safety in relation to the use of medicines; and support public health programmes by providing reliable and balanced information for the effective assessment of the risk-benefit profile of medicines.

One of the main aims of the WHO PIDM is to identify the earliest possible adverse drug reaction signals.  The programme has more than 120 countries contributing to the WHO global database of Individual Case Safety Reports (ICSRs) called Vigibase®. VigiBase® is maintained and developed on behalf of the WHO by The WHO Collaborating Centre for International Drug Monitoring (Uppsala Monitoring Centre), VigiBase® uses the WHO Drug Dictionary which consists of the ATC classification and is useful for drug safety assessment. Please note that many unofficial ATC codes are used in the WHO Dictionary, but these are clearly marked.  The ATC classification allows aggregation of statistics and analysis in reporting of adverse drug reactions.

In pharmacovigilance analyses using VigiBase® or other databases, disproportionality analysis is an acknowledged tool to support signal detection.  Disproportionality metrics, e.g. the proportional reporting ratio (PRR), can be calculated based on the ATC classification.  When PRR is applied at the level of ATC codes, the reporting rate of one specific event is calculated for a given ATC code and compared to the reporting rate of the event in all ICSRs of the database except those that contain one or more drugs from the ATC code of interest.

Drug information (to the top)
ATC codes are included in the pharmaceutical product information (e.g. Summary of Product Characteristics) approved by EMA, the regulatory medicines agency in EU.

ATC codes are included in some international drug textbooks (e.g. the Martindale) and in several national drug catalogues.

ATC codes are also included in the WHO Essential Drug List.

Drug costs, pricing, reimbursement and cost-containment (to the top)
Basing detailed reimbursement, therapeutic group reference pricing and other specific pricing decisions on the ATC and DDD assignments is a misuse of the system.  This is because the ATC and DDD assignments are designed solely to maintain a stable system of drug consumption measurement, which can be used to follow and compare trends in the utilization of drugs within and across therapeutic groups.  None the less, drug utilization data have a central role in the quality of care cycle and ATC and DDD methodologies can be helpful in following and comparing trends in cost, but need to be used with caution.

The DDD is a technical drug use metric.  DDDs do not necessarily reflect therapeutically equivalent doses of different drugs and therefore cannot be assumed to represent daily doses that produce similar treatment outcomes for all products within an ATC category.  Such estimates of therapeutic equivalence are very difficult to establish, particularly to the precision usually required for pricing decisions.  DDDs, if used with caution can be used to compare, for example, the costs of two formulations of the same drug.  However, it is usually not valid to use this metric to compare costs of different drugs or drug groups.  The relationships between therapeutically equivalent doses, the actual prescribed daily dose (PDD) and DDD usually differ between drugs and, for the same drug, between countries.  Moreover, even though PDDs commonly change over time altering a DDD complicates drug utilization research, hence there is a reluctance to alter a DDD. Alterations are not made unless there is evidence that changes in PDD are large, or there is some particular reason such as a change in the main indication.  For these reasons, DDDs are not suitable for comparing drugs for specific, detailed pricing, reimbursement and cost-containment decisions.

Similarly, basing reimbursement and pricing comparisons on inclusion of drugs in ATC groups is not recommended.  The main indications for drugs (on which ATC assignments are based) often differ widely between countries and, like the PDD, can change over time.  However, the ATC classifications can be useful when costs need to be aggregated into drug groups or therapeutic areas to determine, for example, to what extent increased costs can be attributed to increased use of a therapeutic group over time.

Pharmaceutical marketing purposes (to the top)
It is important to emphasise that the ATC classification does not necessarily reflect the recommended therapeutic use in all respects.  Therefore, the ATC system should not be used as a tool for promoting medicines concerning efficacy, mechanism of action or therapeutic profile in relation to other drugs.

It should be emphasised that assignment to different ATC groups does not mean a difference in therapeutic effectiveness and assignment to the same ATC group does not indicate therapeutic equivalence.

Concerning use of price comparisons for marketing purposes, see Drug costs, pricing, reimbursement and cost-containment.



Last updated: 2022-11-25