Screening
patients to identify those who are stable on treatment in a high-volume, large,
urban, public-sector clinic in Johannesburg, South Africa has the potential to
reduce total doctor visits by 40% (14,000 each year), ease clinic congestion,
reduce the time patients spend at the clinic, and maintain a high quality of
care, researchers report in the advance online edition of the Journal of Acquired Immune Deficiency Syndromes.
Taking
data gathered on patients who had been taking antiretroviral treatment (ART) for at least six months, the
researchers assessed the extent to which a number of criteria, including CD4
count, viral load and the absence of abnormal laboratory test results,
predicted that a patient was stable on treatment, and therefore did not need to
see a doctor at that clinic visit.
The
analysis showed high sensitivity (true number of non-stable patients) ranging
from 72.6 to 88.9% and low specificity (true number of stable patients)
ranging from 43.9 to 46.1%.
This
means using these criteria would result in missing a small proportion of
patients needing a doctor visit – where a change of regimen or additional care
might be needed – while having a limited (but not inconsequential) effect on
reducing the overall number of doctor visits.
Nonetheless,
the safety of this approach, the authors write, will need to be evaluated in a
primary care setting.
In
South Africa,
expansion of HIV counselling and testing, as well as raising the CD4 cell count for
starting ART, has resulted in a 50% increase in those now eligible for ART. By
2016 an estimated 3.5 million people could be on ART.
In
a healthcare system with limited resources and clinic staff already working at
capacity, the South African government is looking at how to better manage people on ART
while maintaining quality of care.
'Task-shifting' –
notably, nurse-initiated and managed ART care (NIMART) and the accreditation of
public health facilities – are the primary strategies.
Identifying
stable patients at routine medical visits who are well enough not to need to see either
a NIMART-trained nurse or a doctor can ease the healthcare burden, so
offering a complementary approach, the authors suggest.
A
screening tool able to correctly identify those people only needing
monitoring tests and to pick up their medication would allow clinician visits
to target those most in need and reduce time patients spend at the clinic.
So
the authors chose to look at how successful and how safe using such a screening
tool would be at the Themba Lethu clinic where, in 2009-10, over 13,000 patients were receiving ART. Medical visits increased from 40,537 in 2009 to 47,467 in 2010,
averaging 176 each day.
The
authors identified stable and non-stable visits among all patients who had been on ART for
more than six months and were visiting the clinic between 1 January 2007 and 7 September 2011.
Stable
patients were defined after asking HIV clinicians to identify which criteria would
cause concern during a clinical visit. These included the criteria used to define
treatment failure, a change in WHO stage, and the presence of side-effects and/or toxicity, as well as
good clinical practice.
The
authors defined a medical visit as stable if it included all of the following:
- Stable CD4 cell count (greater than 75% of previous count if CD4 count under 200 cells/mm3 with a viral load ≥
400 copies/ml within twelve months, or within six months if on ART for less than
12 months);
- Undetectable viral load (under 400 copies/ml) within 12
months (within six months if on ART for less than 12 months);
- Stable weight (less than 5% change since last visit within
six months for all patients; weight gain if rapid may be of concern since it
could be a side-effect);
- No change in ART regimen in the past three months;
- No laboratory values showing a possible side-effect or
adverse event: if on AZT (zidovudine), haemoglobin under 8g/dl (denoting anaemia); if
on nevirapine, ALT >
100 (liver function); if on tenofovir, creatinine clearance <
50ml/min (kidney function).
Among
over 14,000 patients with close to 140,000 medical visits between them, over a third of visits (46,532)
were defined as stable.
The
most common reasons for not being considered stable included: having a detectable viral load
(26.8%); weight change – loss or gain greater than 5% (18.6%); declining CD4 cell
count (12.9%); co-morbid conditions (11.3%); and regimen change in the past
three months (9.3%).
The
first three reasons, note the authors, are likely to overstate non-stable
visits because missing and out-of-date data will trigger a visit. CD4 cell
counts and viral load tests were out of date for 6 and 6.8% of visits,
respectively.
However,
they add, while over-classifying patients as non-stable may reduce the
efficiency of such an approach it should increase the sensitivity, so missing
fewer patients needing to see a clinician.
The
data used in the analysis were collected prospectively at a full-clinic visit.
Putting this into practice means all information for determining whether a patient
is stable has to be collected at a pre-clinical interview with review of test
results, the authors write.
High
quality care at this well-run clinic has produced a patient population with
good clinic attendance. How well these criteria could be applied in a less
well-resourced ART clinic and/or without regular laboratory testing is unknown,
they add.
For
those patients who remain stable, the additional criterion of a minimum schedule
for a full-clinic visit needs to be considered. Inclusion of this criterion
would then reduce the true number of non-stable patients.
Strengths
of the study include the large number of visits included in the model, using a comprehensive
clinical database.
The authors
conclude “implementation…in a primary care setting is needed to determine the
extent to which the criteria could reduce visits without compromising safety or
follow-up.”