Patient choice in HIV screening: how we ask matters
A randomised controlled trial
- By: Neil Chanchlani
“Patient choice in opt-in, active choice, and opt-out HIV screening: randomized clinical trial” by Juan Carlos C Montoy and colleagues (BMJ 2016;532:h6895).
Study question—What is the effect of default test offers—opt-in, opt-out, and active choice—on the likelihood of acceptance of an HIV test among patients receiving care in an emergency department?
Methods—This was a randomized clinical trial conducted in the emergency department of an urban teaching hospital and regional trauma center. Patients aged 13-64 years were randomized to opt-in, opt-out, and active choice HIV test offers. The primary outcome was HIV test acceptance percentage. The Denver Risk Score was used to categorize patients as being at low, intermediate, or high risk of HIV infection.
Study answer and limitations—38.0% (611/1607) of patients in the opt-in testing group accepted an HIV test, compared with 51.3% (815/1628) in the active choice arm (difference 13.3%, 95% confidence interval 9.8% to 16.7%) and 65.9% (1031/1565) in the opt-out arm (difference 27.9%, 24.4% to 31.3%). Compared with active choice testing, opt-out testing led to a 14.6 (11.1 to 18.1) percentage point increase in test acceptance. Patients identified as being at intermediate and high risk were more likely to accept testing than were those at low risk in all arms (difference 6.4% (3.4% to 9.3%) for intermediate and 8.3% (3.3% to 13.4%) for high risk). The opt-out effect was significantly smaller among those reporting high risk behaviors, but the active choice effect did not significantly vary by level of reported risk behavior. Patients consented to inclusion in the study after being offered an HIV test, and inclusion varied slightly by treatment assignment. The study took place at a single county hospital in a city that is somewhat unique with respect to HIV testing; although the test acceptance percentages themselves might vary, a different pattern for opt-in versus active choice versus opt-out test schemes would not be expected.
What this paper adds—Active choice is a distinct test regimen, with test acceptance patterns that may best approximate patients’ true preferences. Opt-out regimens can substantially increase HIV testing, and opt-in schemes may reduce testing, compared with active choice testing.
Funding, competing interests, data sharing—This study was supported by grant NIA 1RC4AG039078 from the National Institute on Aging. The full dataset is available from the corresponding author. Consent for data sharing was not obtained, but the data are anonymized and risk of identification is low.
Why do the study?
In 2006 the US Centers for Disease Control and Prevention (CDC) published HIV testing guidelines recommending non-targeted, opt-out testing for all populations. Emergency departments were suggested as best situated to identify the estimated 20% of HIV positive people in the US without a diagnosis.
People without a diagnosis contribute disproportionately to transmission of the virus, accounting for about 30% of HIV transmissions. However, the evidence on which non-targeted, opt-out testing was made remains low grade and mixed, and few institutions have implemented it.
The authors of this study wanted to see whether changes in the way HIV screening questions are asked has an effect on whether patients are likely to accept HIV testing (see box 1).
Box 1: Different ways of asking patients if they would agree to HIV testing
- Opt-in testing—Participants were counselled and asked for formal consent to being tested.
- Opt-out testing—Participants were informed the HIV test is routine and there is no requirement for formal counselling or informed consent (although the participant could decline to have the test performed).
- Active choice—Participants were asked whether they would like to be given an HIV test or not.
What did the authors do?
In a single urban teaching hospital and regional trauma centre based in California, USA, eligible participants were given a questionnaire asking about their HIV related risk and were offered an HIV test during their wait in the emergency department (see box 2). A validated tool known as the Denver Risk Score was used to categorise patients as being at low, intermediate, or high risk of HIV infection.
Box 2: Selection criteria for participants
- Aged 23-64 years old
- Able to consent to HIV testing and study inclusion
- Speaks either English or Spanish
- Known to have HIV infection
- Received an HIV test in the past three months
- In police custody
- Participated in the study in the previous three months
Patients were either offered the HIV test first and then filled out the questionnaire or vice versa on a 1:1 allocation basis across all treatment arms (see box 3). The authors wanted to analyse whether answering the questionnaire first made any difference to test acceptance rates. To test this, 50% received the questionnaire before being asked whether they would like to have an HIV test. Study staff approached the patients a second time, after all the relevant data had been collected, to explain the nature of the study and to obtain patient consent.
Box 3: What patients were asked
“We’re offering routine HIV tests to all of our patients. It’s a rapid test with results available in one to two hours.”
Opt-in—“You can let me, your nurse, or your doctor know if you'd like a test today”
Active choice—“Would you like a test today?”
Opt-out—“You will be tested unless you decline.”
What did theauthors find?
Data were retrieved on 5801 patients who were approached by study staff, of whom 4800 (82.7%) consented to be included in the study. Each group size was similar—1607 in opt-in, 1628 in active choice, and 1565 in opt-out.
On average, patients accepted 51.6% of all offers of HIV tests. Opt-in, active choice, and opt-out test offers resulted in test acceptance percentages of 38.0%, 51.3%, and 65.9%, respectively (see figure). Absolute risk difference, calculated by subtracting two variables of interest concluded a 13.3% (95% confidence interval 9.8% to 16.7%) increase in HIV test acceptance for active choice versus opt-in, and a 27.9% (24.4% to 31.3%) increase for opt-out compared with active choice.
When correlated with the Denver Risk Score, the authors found that patients identified as being at intermediate and high risk were more likely to accept testing than were those at low risk in all arms (difference 6.4% (3.4% to 9.3%) for intermediate and 8.3% (3.3% to 13.4%) for high risk).
Patients who were offered the questionnaire before being offered the HIV test were less likely to accept testing than those who were offered the HIV test first: absolute difference−8.6% (−12.2% to−3.9%) across all treatments, but the authors found no significant interaction between the timing of the questionnaire and treatment assignment with respect to test acceptance percentage.
Strengths and limitations
One of the major strengths of this research is that it is one of the first studies to look at active choice as an option for universal HIV test screening. Whereas previous research has focused on opt-in versus opt-out testing, the study authors added an additional intervention arm—asking patients if they wish to be tested. The authors of the study claim that asking the question this way might best indicate patients’ true preferences.
Secondly, the authors collected information from patients in such a way that there was little room for contamination: which is when participants not intended to receive (or be aware of) other interventions inadvertently find out about them. In this study, this could have occurred by participants talking to each other in the waiting room about how they were asked the screening question. This was avoided, in part, because participants did not know they were being recruited to a scientific study as the researchers obtained retrospective consent.
In this study, it was not possible to blind participants, staff asking the questions, or those analysing the data given the nature of the treatment arms being specific questions. Results were unlikely to be biased because the results were consistent across research staff, and randomisation was achieved with similar baseline characteristics across treatment arms (box 4).
Box 4: Why bother with randomisation?
Randomisation is used in scientific research to ensure participants allocated to treatment groups have similar baseline characteristics. This is to minimise the risk of confounding, so that any differences between treatment groups’ outcomes are more likely to be as a result of the treatment and not differences in baseline characteristics. There are two main ways to randomise participants to interventions:
- Block–A group (“block”) of participants is selected, and participants within each block are allocated to treatment groups on a 1:1 ratio. The allocation sequence of participants within a block (for example, for a block size of four there are six potential allocation sequences) is selected at random. This method ensures that treatment groups have equal numbers of participants.
- Stratified—Researchers divide the study population into strata of important baseline variables and then randomise participants in each stratum. This helps to ensure that potentially confounding baseline variables are equally distributed between treatment groups.
While this study shows that the way you phrase questions has an effect, we do not know the extent to which factors other than phrasing the screening question played a role, such as how the person asking the question looks or sounds. The authors tried to address this concern by rotating the staff who were asking participants to engage around different departments in the emergency department. A limitation of this research is that it is a single centre study, so we do not know if these results are generalisable to other centres in the United States or other countries.
What does the study mean?
How we phrase our questions to patients can achieve different results. The authors reinforced what we already know about the uptake of HIV tests: opt-out achieves considerably higher test acceptance rates. However, researchers and doctors should not just aim to increase test acceptance. They must consider patient preferences too, and that may be achieved by asking patients if they want to be tested at all.
Should active choice be offered over opt-out testing? It depends what policy makers want to achieve: high test acceptance rates (opt out) or for patients wishes to be truly represented (active choice).
Policy makers also need to decide whether to nationally roll out universal HIV screening in emergency departments. Randomised controlled trials at different sites would show whether the results can be replicated. It would be important to capture a qualitative component to ask patients what question wording they would prefer and why. This should be compared against the quantitative element to see if it is consistent.Neil Chanchlani, specialist trainee year one in paediatrics
University College London Hospitals NHS Foundation Trust, London, UK
Competing interests: I have read and understood BMJ policy on declaration of interests and have no relevant interests to declare.
Provenance and peer review: Commissioned; not externally peer reviewed
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- Published: 14 November 2016
- DOI: 10.1136/sbmj.i4651