How to investigate Adherence to Antiretroviral Treatment ... - INRUD
How to investigate Adherence to Antiretroviral Treatment ... - INRUD
How to investigate Adherence to Antiretroviral Treatment ... - INRUD
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<strong>How</strong> <strong>to</strong> Investigate <strong>Adherence</strong> <strong>to</strong> <strong>Antiretroviral</strong> <strong>Treatment</strong> in Health Facilities: <strong>Adherence</strong> Indica<strong>to</strong>rs<br />
There is a difference between having a series of small gaps and one long gap in terms of<br />
adherence. For this reason the other indica<strong>to</strong>r measures the rate of patients with gaps in<br />
treatment of 30 days or more. Between the four countries in the feasibility trial, this varied<br />
from 2 percent <strong>to</strong> 18 percent of patients, but in the worst facility 60 percent of patients had<br />
such a gap. This may be because they dropped out permanently through defaulting or death,<br />
or that they remained in treatment. This would be an important follow-up question.<br />
Indica<strong>to</strong>r 3. Percentage of patients who experienced a gap in ARV availability of more<br />
than 30 days in a row during a defined period.<br />
Rationale<br />
Source of data<br />
Data collection<br />
Computation<br />
Comments<br />
Pitfalls<br />
A gap in medicine supply of more than 30 days has serious implications for<br />
resistance and treatment failure<br />
Pharmacy records<br />
Based on the same sample of 100 patients and the same data on dates of<br />
dispensing and number of days dispensed since index visit<br />
For individual patient: Discontinuation—If patient ever experiences a gap of<br />
> 30 days between the end of days’ supply in one dispensing (or end of <strong>to</strong>tal<br />
days’ supply available if ARVs remain from previous dispensings) and date<br />
of the next dispensing<br />
For facility: Percent discontinuation (number of patients experiencing a gap<br />
in ARV treatment > 30 days/number of patients) × 100<br />
This can be calculated au<strong>to</strong>matically using the spreadsheet analysis <strong>to</strong>ol<br />
As with the previous indica<strong>to</strong>r, identifying reliable patient-specific<br />
longitudinal records may be a problem in some systems, if one visit is not<br />
recorded then the patient will appear <strong>to</strong> have a gap of 30 days, so a low<br />
measure on the indica<strong>to</strong>r may reflect poor record keeping.<br />
Patient Attendance and Defaulting Measure<br />
A missed appointment should trigger programme action <strong>to</strong> reach out <strong>to</strong> patients at risk of<br />
defaulting on their treatment. <strong>How</strong>ever, because the patient may have had extra days of<br />
medicine, attendance failure within three days of an appointment can also be a trigger point.<br />
The two core performance indica<strong>to</strong>rs related <strong>to</strong> attendance are—<br />
4. Percentage of patients who attend on or before the day of their appointment<br />
5. Percentage of patients who attend within three days of their appointment<br />
The purpose is <strong>to</strong> look at a visit the patient made, note when the next appointment was made<br />
for, and then see if the patient kept the appointment. Because some programmes give certain<br />
patients three months of medicine, it is necessary <strong>to</strong> review the records <strong>to</strong> see the patient’s<br />
attendance four months before, see the date of the next appointment, and then note whether<br />
the patient’s next visit was on or before that date (indica<strong>to</strong>r 4), or within three days of that<br />
date (indica<strong>to</strong>r 5).<br />
When filling in the dispensing data collection form, alternate attendance indica<strong>to</strong>rs can be<br />
calculated easily. This means that we have two alternative attendance indica<strong>to</strong>rs—<br />
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