ANTIBIOTIC CONSUMPTION CALCULATOR

4. ANTIBIOTIC CONSUMPTION CALCULATOR

ABC Calc (Monnet, 2003) is a simple computer tool utilising the ATC/ DDD system to measure antibiotic consumption at both the hospital and ward level as DDDs/100 bed-days (Figure 1). It transforms aggregated data provided by hospital pharmacies (generally as a number of packages or vials) into meaningful antibiotic utilisation rates. It was originally developed in the Department of Antimicrobial Resistance & Hospital Hygiene, Statens Serum Institut (Copenhagen, Denmark), by Dr Dominique Monnet as part of the Danish Integrated Antimicrobial Resistance Monitoring and Research Programme (DANMAP) (Bager, 2000). ABC Calc is freely available as a Microsoft Excel ® file and is modified annually to incorporate any changes made to the ATC/DDD system. It can be downloaded from the European Study Group on Antibiotic Policies (ESGAP) page on the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) website (www.escmid.org). To obtain data measured in DDDs/100 bed-days requires the input of data to calculate both the numerator and denominator.

Figure 1. Monnet DL ABC Calc—Antibiotic consumption calculator (Microsoft Excel ® application). Version 1.9 Copenhagen (Denmark): Statens Serum Institut; 2003.

112 Fiona M. MacKenzie and Ian M. Gould

4.1. ABC Calc numerator data

ABC Calc transforms aggregated data provided by hospital pharmacies (generally as a number of packages or vials) into meaningful antibiotic utilisa- tion rates. For each product issued from the pharmacy, ABC Calc prompts the user for information on (1) the name of the product, (2) number of grams per unit dose, (3) the number of unit doses per package, and (4) the number of packages used in a defined time period. The spreadsheet then automatically calculates the total number of grams and DDDs used for each individual antibiotic, each subclass and class as well as total antibiotic consumption. The spreadsheet has the capacity to allow for multiple products of a single anti- biotic. Care must be taken to enter each product in the appropriate line when prompted, as for some antibiotics the DDD varies depending on the route of administration.

For a given antibiotic, the number of DDDs are calculated as follows:

(grams per unit dose) ⫻ (number of unit doses per pack)

⫻ (number of packs used) Defined daily dose (supplied)

Depending on the product, a unit dose corresponds to one tablet, capsule, vial, etc. Again, depending on the product, a pack corresponds to, for example, a box of 10 tablets, and in some instances the pack may be equal to the unit dose, for example, individually distributed infusion vial.

ABC Calc has gone one step further than the ATC system, in the classifica- tion of antibiotics. The ATC system has not subgrouped some classes of antibi- otics, whereas ABC Calc has. For example, the ATC system only goes as far as class J01DA “cephalosporins and related substances,” whereas ABC Calc has grouped the cephalosporins by generation.

4.2. ABC Calc denominator data

In order to measure consumption as DDDs/100 bed-days it is crucial to provide accurate data on bed-days and enter it into the ABC Calc spreadsheet. Bed-days (during a specific time period) are calculated as follows:

(Number of beds) ⫻ (Occupancy index) ⫻ (Number of days) If the bed occupancy is 85%, then the occupancy index is 0.85. For example if

a hospital has 1,200 beds and an occupancy of 85% in 1 year (365 days), then the number of bed-days for that year ⫽ 1,200 ⫻ 0.85 ⫻ 365 ⫽ 372,300.

Quantitative Measurement of Antibiotic Use 113

4.3. ABC Calc in practice

The authors have had direct experience of using ABC Calc to collate antibiotic consumption data from European hospitals. They coordinate the European Commission Concerted Action project entitled “Antibiotic Resistance, Prevention, and Control” (ARPAC) which runs from January 1, 2002 to December 31, 2004. ARPAC aims to lay the foundations for a better understanding of emergence and epidemiology of antibiotic resistance in human pathogens. It also aims to harmonise strategies for prevention and con- trol of antibiotic resistant pathogens in European hospitals. The project uses ABC Calc to collate and compare antibiotic consumption from European hospitals and to model consumption with antibiotic resistance data as well as infection control and antibiotic policy data.

Although the ABC Calc spreadsheet comes with comprehensive instruc- tions, any problems encountered in the authors’ experience have been due to a failure in following the instructions. Most commonly, the bed-days have not been calculated correctly. Table 2 illustrates how such errors translate into errors in total DDDs/100 bed-days presented.

In example 1, the number of bed-days were stated, but no figures were sup- plied to indicate how they were calculated. Once the raw data were supplied, the bed-days value was modified and the total DDDs/100 bed-days changed from 174 to 37. In example 2, it would appear that the bed occupancy was pre- sented as a percentage rather than an index value and the number of days and the number of bed-days were both entered manually, having been transposed

Table 2. Examples of errors in calculating bed-days and total DDDs/100 bed-days for 1 year (365 days)

Number of

Number of Total beds

of days

bed-days DDD/100

bed-days Example 1

index

Raw data Not stated

87,309 174 Corrected data

Not stated

Not stated

410,204 37 Example 2 Raw data

355 19,964 Corrected data

129,685 55 Example 3 Raw data

6.18 ⫻ 10 9 0 Corrected data

150,219 64 Example 4 Raw data

1,181 84.5 8.7 8,68,212 25 Corrected data

114 Fiona M. MacKenzie and Ian M. Gould giving an automatic calculation of a total of 19,964 DDDs/100 bed-days. Once

the raw data were corrected, the total consumption became more believable at

55 DDDs/100 bed-days. In example 3, again the bed occupancy was originally presented as a percentage and the number of bed-days calculated manually and entered into the wrong box. The automatic calculation then gave 0 DDDs/100 bed-days instead of 64 DDDs/100 bed-days which was correctly calculated after modifying the entries in the spreadsheet.

Other errors in using ABC Calc have included users disabling the macros used to make the automatic calculations thereby underestimating total con- sumption, changing the spreadsheet cell formatting, and typographical errors. For example, in one particular spreadsheet the grams per unit dose for the combination of sulfamethoxazole plus trimethoprim were quoted as 480 and 960 g, resulting in total annual consumption of 572 DDDs/100 bed-days. Once the doses were corrected to 0.48 and 0.96 g, the total antibiotic use was reduced to a more realistic 41 DDDs/100 bed-days.