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SESSION GUIDE SAMPLING TO STUDY DRUG USE

SAMPLING TO STUDY DRUG USE

INTRODUCTION

Sampling is a process by which we study a small part of a population to make judgments about that population.

We sample as a part of our daily lives.

For example, if we want to know if Fruit Seller A is better than Fruit Seller in a market, we would go to Seller

A and examine a number of his!her fruits for "uality and price and then repeat the process for Seller . #t would

not be fair or accurate to base judgment on a single fruit from each seller and it would be impractical to check

every fruit in the stall. $he "uestions are% &ow do we select which fruit to examine, and how many to examine'

(bviously, if we only examine the fruit at the front of the stall we may get an incorrect answer. So we need to

find a sample method to check all the fruit by examining a sample of the fruit.

Whenever we want to learn about health in the community or practices in the health system, we need to draw

samples since it would be impractical to collect data on every person or event. #n drug use surveys we need to

draw samples to select facilities to survey, prescriptions to study, or patients to observe.

#f we wanted to know about prescribing in primary care facilities in a country, we would probably get the wrong

impression of the real situation if we only surveyed the five health centers closest to the central office of the

)inistry of &ealth because these would likely be better than the average. #f we wanted to examine prescribing in

a health center, we would be misled if we surveyed the first *+ cases attending on a )onday morning. $here may

be an excess of men with hangovers from weekend drinking or workers wanting sick notes to excuse them from

going to work. So, to get a representative sample, we would need to ensure that all facilities or patients can be

included in the survey.

DEFINITIONS

Asampling unitmay be a person, a health facility, a prescription, or another such unit.

A study population sometimes called the reference population, is the collection of all possible study units.

Again, this population may be people, health facilities, prescriptions or other such units.

A !"p!"s"ntati#" sampl" $as all t$" impo!tant %$a!a%t"!isti%s o& t$" population &!om '$i%$ it is d!a'n(

SAMPLING MET)ODS

A sampling &!am"is a list of all of the available units in the study population. #f a complete listing is available,

the sampling frame is identical to the study population.

$here are two broad types of sampling methods. $hese are%

onprobability sampling

-robability sampling

$he type of sampling depends whether there is a sampling frame available. #f a sampling frame exists, or if it can

be created, probability sampling is used. #f there is none available, probability samplings cannot be used.

Sampling in#ol#"s t$" s"l"%tion o& a num*"! o& study units &!om a d"&in"d study population(

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#t is always better to use probability sampling, if possible. &owever, in some situations, nonprobability sampling

is the only possible method because a sampling frame is not available. A sample drawn using nonprobability

methods is likely to be less representative than a probability sample so study results are less valid. When non

probability sampling is used in a survey, this fact should be included in any report.

NONPRO+A+ILITY SAMPLING MET)ODS

$here are two common methods of non probability sampling% convenience sampling and "uota sampling.

Con#"ni"n%" samplingis a method by which, for convenience sake, the study units that happen to be available at

the time of data collection are selected. $his is the least representative sampling method.

,uota sampling is a method by which different categories of sample units are included to ensure that the sample

contains units from these categories. For example, a "uota sample of patients from a health center might include

/+ patients with A0#, /+ with diarrhea, and /+ with malaria.

oth of these methods may be used in drug use studies. $o measure prescribing and dispensing times or assess

patient understanding, a convenience sample of patients may be the only practical method. A "uota sample may

be used for males and females to ensure that both genders are observed or interviewed. $his may be important

since men are often treated with more respect and have higher literacy rates. Also, men may be given priority over

women or children and receive more thorough care.

on probability samples are not necessarily representative of the reference population. &owever, we often need to

use these methods when we have inade"uate sample frames or when a time constraint exists which forces us to

use them.

PRO+A+ILITY SAMPLING MET)ODS

#f a sampling frame 1a list of the population units2 exists, then probability sampling may be used.

-robability sampling involves RANDOM selection procedures to ensure that each sample unit is chosen on the

basis of C)ANCE(

Whenever possible, use probability sampling to obtain results that are less biased. $here are five different

sampling methods% simple random, systematic, stratified, cluster, and multistage.

Simpl" Random Sampling

$his is the simplest form of simple probability sampling. A lottery is an example of a random sample. $he simplerandom sampling procedure is as follows%

a2 )ake a numbered list of all units in the reference population from which you will select the sample 1for

example, a list all the health centers in the country2.

b2 3ecide on the si4e of the sample 1the W&( 3rug 5se #ndicators method re"uires a minimum of *+

facilities2.

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c2 6hoose the facilities to include by a lottery method. 1For example the numbers of all the facilities can be

placed in a box and drawn, a random number table can be used, or random numbers can be generated

using a spreadsheet or calculator.2

$his is the method used in Worksheet /./

Syst"mati% Sampling#n systematic sampling, sample units are selected from a numbered list of all units in the study population by

using a regular interval, starting from a random starting point.

$o calculate the sampling int"!#al, divide the si4e of the list by the desired sample si4e. For example, if we want

to select *+ health centers from a list of 78 in our sampling frame, our sampling interval would be 78!*+ 9 *.:.

$he first facility chosen in this case can be either /, * or :, which are all the possible sampling units within the

first sampling interval. $he procedure is as follows%

a2 choose a random number between + and / 1with at least : digits after the decimal point2

b2 multiply this random number by the sampling interval, and

c2 round this result upward to get the number of the first facility.

For example, if the random number chosen is +./;:, the first unit for the sample is +./;: x *.: 9 +.7*/ which

rounds upward to /, thus, the first facility on the list is chosen for the sample.

*/ so Facility : 10emember% al'ays !ound up'a!d2

*.>*/ = *.: 9 ?.+*/ so Facility 8

?.+*/ = *.: 9 >.:*/ so Facility ;

and so forth.

#f the first result had been /.>7@, then the first facility would be Facility *, and the next facilities selected would

be%

Facility *

/.>7@ = *.: 9 7.+7@ so Facility ?

7.+7@ = *.: 9 8.:7@ so Facility >

8.:7@ = *.: 9 ;.87@ so Facility @

and so forth.

$he method just described gives every unit an equalchance of being selected. $his method is used in Worksheet

/.*. $his method can also be used with minor modification to select units allowing for how large they are.

Sometimes it is desirable for clinics serving larger populations to have a greater chance of being included in a

sample. $his method is called sampling with probability proportional to si4e. $his method is used in Worksheet

/.:.

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Systematic sampling is also useful when sampling prescriptions from a patient register. #f a register contains /++

pages, each with *? lines of prescriptions, and you need to select :+ prescriptions, the sampling interval would be%

/++ x *? 9

;:.:

:+

$hus every ;:rd prescription would be sampled. )ultistage sampling, described as the fifth method below, couldalso be used to select a sample from a patient register.

St!ati&i"d Sampling

Stratified sampling is used when the reference population contains different subpopulations that should be

considered separately.

For example, this might be the case in a study that included urban and rural facilities, facilities with and without

doctors, or male and female patients.

When stratified sampling is used, the sampling frame 1the list of the overall population2 is sorted into two or more

groups. $hese different strata 1groups2 may then be sampled either randomly or systematically.

#n our fruit sellers example, we might want to check the "uality and price of each of the varieties of fruit sold.

$he W&( manual 1pp. ?@8+2 recommends the use of stratified systematic sampling methods for selecting

facilities. For example, the sampling frame might include the following list of facilities%

Fa%ility Num*"! Typ"

/ 5rban

* 0ural: 0ural

7 0ural

? 5rban

8 0ural

> 5rban

; 5rban

@ 0ural

/+ 0ural

etc. etc.

$his list could then be grouped and sorted into * strata as follows%

/ 5rban * 0ural

? 5rban : 0ural

> 5rban 7 0ural

; 5rban 8 0ural

tc. @ 0ural

/+ 0ural

etc.

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and a sample would be selected separately from both the urban list and the rural list.

$his is the method used in Worksheet /.*, /.7, /.?, and /.8.

Clust"! Sampling

#n a %lust"! sampl", a group of sample units is selected together, rather than each unit being selected separately.

$his method may not be as representative as single unit sampling, but for logistic reasons may be necessary. $he

recommended W&( sampling procedure of selecting :+ groups of > children is a common cluster samplingmethod.

$he main advantage of cluster sampling is that the method is easy to use and often logistically simpler to organi4e.

For example, when choosing houses in a community, it is easier to walk between neighboring houses than all over

the community. $he disadvantage is that the samples selected may be less representative, especially when the

number of clusters selected is low. $hus, when the cluster method is used, try to increase the sample si4e 1by

increasing the number of clusters sampled2.

#n drug use studies, cluster sampling may be used for selecting facilities when distances are great. For example, a

cluster of two facilities could be selected by randomly selecting a single facility and then selecting the closest

facility to the one selected. $his method might allow two facilities to be surveyed in a day when travel time

between facilities is significant. $his method is used in Worksheet /.>.

Multistag" Sampling

#n multistag" sampling, the methods described above can be combined. For example, we might wish to select :*

health facilities in a country containing ?8 districts, each of which contains a number of health facilities. From

the ?8 districts, /8 districts would first be selected. #n each district two health facilities would then be randomly

selected. $his would be twostage random sampling.

#n the example above of selecting :+ prescriptions from a patient ledger of /++ pages containing *? prescriptions

per page, we can use systematic sampling of the pages and random selection of the prescription per page.

$hus we would calculate the sampling interval for the pages as follows%

/++ B :+ 9 :.:

0andomly select the starting page from page number / through 7, as described above, then add :.: repeatedly to

select the page numbers. 0andomly select a number from /*? using a calculator or a random number table to

select which individual prescription would actually be chosen on each page.

SAMPLE SI-E

$he method of deciding the desirable sample si4e is described in the manual Designing and Conducting Health

Systems Research Projects 1pp. *+?*+@ and $able >./2 and in WHO Manual of Epidemiology for District

Health Management 1p.>;2. $he -##F( computer package contains a statistical calculator which calculates

minimum sample si4es based on different assumptions.

$he appropriate sample si4e depends on%

C E.p"%t"d #a!iation o& t$" data. $he more variation, the larger sample re"uired.

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C T$" ".p"%t"d !at" o& t$" #a!ia*l". For example, a smaller sample will be re"uired to obtain the same

degree of accuracy if the rate of antibiotic prescribing is *+ percent than if the rate is ?+ percent.

C T$" d"g!"" o& a%%u!a%y !"/ui!"d. ecause the entire population is not studied, every sample has some

degree of uncertainty. $he larger the sample, the less the uncertainty. $his certainty is often measured in

terms of a @? percent confidence interval. For example, if we find a rate of ?+ percent in a sample, how

sure can we be that this is the true rate in the reference population'

For a sample si4e of ?+, the range of certainty will be :8D 87D 1@?D 6#2

/++, the range will be 7+D 8+D

*++, the range will be 7:D ?>D

?++, the range will be 7?D ??D

/+++, the range will be 7>D ?:D

#ncreasing the si4e of the sample increases the certainty however, after a certain point, the value of the increase in

certainty is not in proportion to the increase in effort and resources to collect the data.

$he appropriate sample si4e is usually a compromise between what is STATISTICALLY DESIRA+LE and

what is FEASI+LE.

In g"n"!al a minimum sampl" si0" is 12(

$he W&( manual Ho to !n"estigate Drug #se in Health $acilitiesreflects the experiences of a number of

surveys carried out in Africa, Asia, and

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be included in the survey. very effort should be made to avoid bias 1systematic error2 in selecting sampled units

for study.

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