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Sexually transmitted infection (STI) surveillance is vital for tracking the scale and pattern of epidemics; however, it often lacks data on the underlying drivers of STIs.
This study aimed to assess the acceptability and feasibility of implementing a bio-behavioral enhanced surveillance tool, comprising a self-administered Web-based survey among sexual health clinic attendees, as well as linking this to their electronic health records (EHR) held in England’s national STI surveillance system.
Staff from 19 purposively selected sexual health clinics across England and men who have sex with men and black Caribbeans, because of high STI burden among these groups, were interviewed to assess the acceptability of the proposed bio-behavioral enhanced surveillance tool. Subsequently, sexual health clinic staff invited all attendees to complete a Web-based survey on drivers of STI risk using a study tablet or participants’ own digital device. They recorded the number of attendees invited and participants’ clinic numbers, which were used to link survey data to the EHR. Participants’ online consent was obtained, separately for survey participation and linkage. In postimplementation phase, sexual health clinic staff were reinterviewed to assess the feasibility of implementing the bio-behavioral enhanced surveillance tool. Acceptability and feasibility of implementing the bio-behavioral enhanced surveillance tool were assessed by analyzing these qualitative and quantitative data.
Prior to implementation of the bio-behavioral enhanced surveillance tool, sexual health clinic staff and attendees emphasized the importance of free internet/Wi-Fi access, confidentiality, and anonymity for increasing the acceptability of the bio-behavioral enhanced surveillance tool among attendees. Implementation of the bio-behavioral enhanced surveillance tool across sexual health clinics varied considerably and was influenced by sexual health clinics’ culture of prioritization of research and innovation and availability of resources for implementing the surveys. Of the 7367 attendees invited, 85.28% (6283) agreed to participate. Of these, 72.97% (4585/6283) consented to participate in the survey, and 70.62% (4437/6283) were eligible and completed it. Of these, 91.19% (4046/4437) consented to EHR linkage, which did not differ by age or gender but was higher among gay/bisexual men than heterosexual men (95.50%, 722/756 vs 88.31%, 1073/1215;
Implementing a bio-behavioral enhanced surveillance tool in sexual health clinics was feasible and acceptable to staff and groups at STI risk; however, ensuring participants’ confidentiality and anonymity and availability of resources is vital. Bio-behavioral enhanced surveillance tools could enable timely collection of detailed behavioral data for effective commissioning of sexual health services.
Globally, the burden of sexually transmitted infections (STI) continues to be high [
In the context of HIV, globally, since the late 1990s, tailoring surveillance to the epidemic state of a country and collecting and comparing behavioral and prevalence data have helped better understand the course of epidemics [
Our aim was to assess the acceptability and feasibility of implementing a BBEST, comprising offering a self-administered Web-based survey to SHC attendees in England, to be completed using digital devices, and subsequently linking their survey responses to their EHR. Although we undertook this assessment in SHCs, our primary focus was on people of BC ethnicity and MSM as exemplar populations because of high STI burden among these groups, as mentioned previously.
We used a mixed methods study design (
Study design for developing and implementing the bio-behavioral surveillance tool (BBEST) for sexually transmitted infections. MSM: men who have sex with men; STI: sexually transmitted infection.
Due to dearth of data on contextual drivers of STI among MSM and BC populations [
We anticipated that the implementation of the BBEST in SHCs would involve the staff offering study envelopes and digital tablets to clinic attendees to participate in a Web-based survey. Participants could also use their personal digital device for survey completion. The survey would be administered using the Snap software (Snap Surveys Ltd, UK) and hosted on a secure remote server.
Therefore, internet connectivity would be required in SHCs to enable attendees to log in to the survey and for the data to upload automatically to a remote server. The study team would provide SHCs with study envelopes and tablets that could be remotely deactivated in the event of theft. SHC staff would offer all attendees a study envelope, which would contain a PIS, a card with a survey Web link, and a unique study passcode (USP), which they would use to access the survey. The PIS contained study details including information that only the research team would have access to the survey data, their right to withdraw at any point during or before submitting the survey online, the linkage of their survey responses to the data SHCs routinely collect on STI tests, and results collated by PHE for surveillance purposes. Attendees who could not use digital devices or read English would be ineligible for participation. Each envelope would have a detachable receipt with the same USP (
On logging into the survey, participants would again be shown online the same PIS given to them in the study envelope. They would then be asked to give online consent separately for survey participation and linkage of their survey data to the EHR. If they declined to participate, they would exit the survey (
Subsequently, eligible participants would complete the Web-based survey, which was designed to take approximately 10 to 15 min depending on the sections of the survey that were applicable to them. On completion, researchers could download the participants’ survey data from the server and link these to the EHR (for consenting participants only), using the participant’s clinic number and USP recorded by the staff, to create a study dataset. We anticipate that the BBEST would be implemented periodically in SHCs or settings that routinely collect GUMCAD data to provide in-depth intelligence on issues of particular public health concern, including STI outbreaks.
Survey invitation envelope: back side with a tear-off tab.
Screening process to identify participants eligible to complete the Web-based survey. EHR: electronic health records.
From June 2014 to August 2015, face-to-face or telephone interviews were conducted with 20 staff members recruited from all study sites to assess the acceptability of the proposed BBEST model. A total of 61 MSM were recruited to 1 of the 8 focus group discussions (FGDs) with the help of lesbian, gay, bisexual and trans/sexual health community-based organizations (CBOs) via newsletters and Facebook pages and an MSM geospatial sociosexual networking application [
Two separate Web-based questionnaires were developed, because of differences in STI epidemiology in MSM and BC populations [
After completing survey recruitment, short, audio-recorded, semistructured face-to-face/telephone interviews were conducted, between December 2016 and February 2017, with 25 SHC staff from study sites to understand their experiences of implementing the BBEST.
Deterministic and probabilistic methods were used to match records in the survey data and GUMCAD using the following key variables: participants’ clinic number, age, gender, and clinic attendance date. Probabilistic methods allowed matching of records with erroneous or missing data based on minor discrepancies in age, attendance date, and clinic number. After matching, participants’ clinic numbers were dropped to create an anonymous dataset.
Phase 1 and phase 2 qualitative data were thematically analyzed using NVivo 11 for Windows (QSR International Pty Ltd, Australia) to assess acceptability of the proposed BBEST model and to examine barriers and facilitators to implementing the BBEST in SHCs, respectively. We used the Framework method to thematically analyze qualitative data [
The feasibility of implementing the BBEST in phase 2 was assessed quantitatively by examining the recruitment sheets for the number of attendees who were invited to participate in the Web-based survey. The study dataset was examined for the total number of attendees who actually logged in and gave online consent for survey participation and for linkage and the number of eligible participants who completed the survey. The Snap survey software metadata were examined to determine whether a study tablet or other device was used for survey completion. The feasibility of linkage was determined from the number of surveys that were successfully linked to EHR for those who had consented to linkage. Univariable logistic regression was used to examine the association between consent to linkage and the sociodemographic characteristics of survey participants. Representativeness of the survey sample was ascertained by comparing the sociodemographic and sexual health characteristics (only for participants who had consented to and could be linked to their EHR) of the survey participants recruited from the BC only and combined study sites with all the SHC attendees during the study period (data extracted from GUMCAD) using z-test for proportions. The sample recruited from the MSM-only study sites was excluded from this analysis because it was not expected to be representative of “all” SHC attendees due to the study eligibility criteria in these sites (ie, the exclusion of all women and men reporting only female sex partner(s) in the last 12 months;
The lack of internet/Wi-Fi connectivity required to administer the Web-based survey and upload the data automatically to a remote server was one of the most commonly perceived barriers by the clinic staff to implementing the BBEST. Staff from clinics located in areas of high deprivation felt that participants may be reluctant to use their own smartphones for survey completion if free Wi-Fi was unavailable in the clinics.
Clinic staff expressed inability to monitor the security of the tablets because of work pressures and challenges in having dedicated staff members to offer tablets to participants. Although some clinics had separate research staff to help with recruitment, other clinics felt that they would have to depend on regular clinic staff, which was perceived as challenging due to staff cuts that were taking place during our study in several clinics and their high workload. Several research studies being undertaken in the clinic simultaneously were also perceived as a potential barrier. A need to seek help from local clinical research networks (CRNs) who provided temporary staff support for research was identified.
Some clinic staff expressed anxiety about using tablets for administering the survey because of their lack of/limited experience of using either tablets or the internet or both. They expressed a need for training to use the tablets and administer the survey.
One of the clinics had concerns about sharing the clinic numbers of survey participants who had not agreed for linkage of their survey responses to EHR, but were willing to provide clinic numbers of participants who had given consent to linkage.
Overall, there were few differences in the perceived acceptability of the BBEST among MSM and BC participants, with similar views being expressed by interview and FGD participants.
Majority of the participants expressed an ability and willingness to use a digital device to self-complete a Web-based survey because it was considered to be potentially confidential due to immediate online submission of responses post survey completion. Web-based surveys were also perceived to be less embarrassing than a face-to-face paper questionnaire because of the lack of potential for clinic staff to read participants’ survey responses. Using a personal digital device compared with a device offered by the clinic for survey completion was preferred because of concerns about applications that may be installed on clinic devices and its impact on confidentiality:
Int: And would you be willing to complete this survey on your own device, if you had one, which had access to the internet?
IDI_001: I’d feel more comfortable doing it on my own device than something that was given to me.
Int: And why do you say that?
IDI_001: Because I don’t know what else that device has on it, whereas I know what my device has on it. So, like, there are apps that can log key strokes, for example, and stuff like that, so again I’d be trusting that device and that person that gave me that device.
Int: Sure.
IDI_001: Whereas if it was just a URL and a pass code and I could use my own device, I’d feel much more comfortable doing that.
Unlike the BC participants, majority of the MSM were familiar with completing Web-based surveys on their phones and considered it to be a secure and efficient method and had greater preference for single or multiple-choice tick-box questions. However, they were unwilling to download a survey app on their phone. Nevertheless, some participants were not willing to use their personal device for survey completion if they did not have access to free Wi-Fi in the clinic:
Respondent 6 Group 5: I’ve found, because I’ve done quite a few of these. When you do one, for some reason slightly straight away, once you’ve done one, this is easy they give you more to do. It almost becomes like great fun.
Int: Okay, that’s what it feels like?
Respondent 6 Group 5: I, I personally find, I’m just talking about me now as an individual, is the multiple choice questions (you) touch on an iPhone, iPad, I love them. I love them because I don’t mind.
Int: Okay, sure.
Respondent 6 Group 5: But I really hate when you have to type in open-ended (answers).
Respondent 5 Group 5: I think you run the risk of people not doing it. You know if it’s there in paper form or iPad form or whatever, I’d do it. But I know full well I would leave, probably do the shopping, get the iPad out, life would kick in.
Participants with experience of completing Web-based surveys perceived it to be a time-saving method because of routing to subsequent questions being informed by their responses to previous questions. However, a few participants expressed an inability to complete a Web-based survey because they did not know how to use the internet, although some were willing to do so if they were shown how to use the digital devices for survey completion:
Respondent 1 Group 3: And obviously you can ask questions that, you know…or miss questions. You don’t need to ask seventeen questions.
Respondent 2 Group 3: You only get the ones pertinent to you.
Many participants expressed a preference to complete the survey in the clinic because of concerns of getting busy with other things once home. The need to log on to a personal computer once home was perceived to be time-consuming, and not living alone was perceived as a barrier to privacy. However, some participants expressed a preference to complete the survey at home to allow for more considered responses and privacy. Private clinic rooms/booths were preferred for survey completion compared with crowded waiting rooms. Some participants suggested tailoring survey recruitment to the patients flow through the clinic or the layout of services to reduce anxiety about losing their place in the clinic appointment queue:
Int: And do you think, if you were to take part in the survey, you’d rather it all happened in the clinic, rather than doing it in your own time at home?
IDI-17: Well, not necessarily, it’s just when you get home, you’ve got to make something to eat, you’ve got to do all this kind of stuff, and then you need to get your computer out and log in and all this kind of stuff, so it’s that kind of impetus to do that really.
Int: Okay.
IDI-17: Whereas if you get given a tablet which is secure obviously, and it’s there set up for you ready, then it’s a lot kind of easier.
Overall, most participants were supportive of the proposed linkage of survey data to EHR because they considered it to “be for something constructive” like improving health care. But some participants perceived it as “too much information gathering on people.” Thereby, providing anonymous online consent, separately for linkage to EHR, was perceived to be acceptable. The proposed usage of a USP as opposed to identifiable details to access the survey was considered important to ensure anonymity.
The above-mentioned findings informed the development of site-specific BBEST models. Temporary staff from the local CRN, who are funded by UK Health Department to provide infrastructural support for patient benefit–related research [
Of the 7367 attendees recorded by SHCs as invited, 6283 (85.28%) agreed to participate (
Phase 2 staff interviews highlighted that SHC with a culture of valuing and prioritizing research and innovation, championed by senior clinicians, was an important factor for successfully implementing the BBEST. Having enthusiastic staff members, especially with dedicated roles and time to implement the study, maximized the recruitment. However, structural changes in clinical services, including a London-wide reorganization of sexual health, negatively affected staff morale and their engagement with the study, and in some SHCs, it led to frequent staff turnover. This affected recruitment with subsequent staff receiving limited training in study procedures, resulting, for example, in one clinic not documenting participants’ clinic numbers. Nevertheless, despite initial concerns, the majority of staff involved with implementing the survey became familiar and gained confidence with the use of tablets. However, some clinics offered tablets to participants only if they had dedicated staff to monitor them because of concerns of theft or damage. One tablet was stolen from a locked cabinet in a staff-only access area, and in 2 clinics, the lack of ability to secure tablets to immovable objects prevented their use. The limited number of tablets available per clinic for administering the survey restricted their ability to recruit multiple participants simultaneously. However, in clinics that had Wi-Fi, the option for participants to complete the survey using their own digital device was considered a facilitator for recruitment. Some staff felt overburdened with the requirement to record participants’ clinic number and sending the recruitment sheet monthly to the research team. Nonetheless, they appreciated the real-time feedback from the study team on survey completion rates, which enabled them to promote completion in the clinic, as opposed to home, to address lower home completion rates.
Altogether, 91.19% (4046/4437) of the eligible participants consented to link their survey data to EHR (
Feasibility of implementing the Bio-Behavioral Enhanced Surveillance Tool by population of interest. MSM: men who have sex with men.
Recruitment cascade among clinics grouped by recruitment success.
Comparison of sociodemographic characteristics of survey participants with all clinic attendees during the study period.
Sociodemographic characteristics and indicators of sexual health | GUMCAD data on attendees in clinics administering only heterosexual survey (N=97,054) | Survey population in clinics administering only heterosexual survey (N=4184) | |||||
n (%) | Percentage excluding unknown/missing variables | n (%) | Percentage excluding unknown/missing variables | ||||
Male | 41,609 (42.87) | 42.87 | 1722 (41.16) | 41.16 | .03 | ||
Female | 55,411 (57.09) | 57.09 | 2447 (58.48) | 58.48 | .08 | ||
Trans/othera | Not available | Not available | 15 (0.36) | 0.36 | Not calculated | ||
Unknown/missing | 34 (0.00) | —b | 0 (0.00) | 0.00 | — | ||
Gay/bisexual | 9597 (23.06) | 23.90 | 519 (30.14) | 31.52 | <.001 | ||
Heterosexual | 30,585 (73.51) | 76.10 | 1165 (67.65) | 70.61 | <.001 | ||
Unknown | 1427 (3.43) | — | 73 (4.24) | — | — | ||
<25 | 30,034 (30.94) | 30.94 | 1,599 (38.21) | 38.21 | <.001 | ||
≥25 | 67,020 (69.05) | 69.05 | 2585 (61.78) | 61.78 | <.001 | ||
Unknown/missing | 0 (0.00) | — | 0 (0.00) | — | — | ||
White | 49,409 (50.91) | 56.00 | 2092 (50.00) | 51.20 | <.001 | ||
Black African | 7960 (8.19) | 9.01 | 418 (9.99) | 10.2 | <.001 | ||
Black Caribbean | 8368 (8.62) | 9.51 | 640 (15.29) | 15.7 | <.001 | ||
Black other | 4441 (4.60) | 5.01 | 42 (1.00) | 1.00 | <.001 | ||
Mixed | 6549 (6.78) | 7.41 | 370 (8.80) | 9.11 | <.001 | ||
Asian | 8224 (9.29) | 9.29 | 400 (9.62) | 9.81 | .32 | ||
Other ethnicities | 3288 (3.38) | 3.38 | 125 (2.98) | 2.98 | .25 | ||
Unknown/missing | 8815 (9.08) | — | 97 (2.31) | — | — | ||
Yes | 74,217 (76.52) | 76.52 | 2552 (73.98) | 73.98 | <.001 | ||
No | 22,837 (23.53) | 23.53 | 895 (25.96) | 25.96 | <.001 | ||
Yes | 14,240 (14.67) | 14.67 | 585 (16.97) | 16.97 | <.001 | ||
No | 82,814 (85.32) | 85.32 | 2862 (83.03) | 83.03 | <.001 |
aTrans not currently recorded on GUMCAD surveillance.
bIndicates "not applicable".
cThere is no “missing” data for these categories as there is no requirement to code when there is no STI screen or STI diagnosis.
dSexual health screen—one of the following test combinations: chlamydia and gonorrhea; chlamydia, gonorrhea, and syphilis; syphilis and HIV; and chlamydia, gonorrhea, syphilis, and HIV.
eSTI: sexually transmitted infections.
fAcute STI—any of chlamydia, gonorrhea, anogenital herpes (first episode), anogenital herpes (first episode), HIV, infectious syphilis, pelvic inflammatory disease/epididymitis, non-specific genital infections, chancroid, lymphogranuloma venereum, donovanosis, trichomoniasis, scabies, pediculosis pubis, molluscum contagiosum, mycoplasma genitalium, shigella, hepatitis A, hepatitis B, and hepatitis C.
Comparison of sociodemographic characteristics of men who have sex with men (MSM) who participated in the survey compared with all MSM attending all the study sites during the study period.
Sociodemographic characteristics and indicators of sexual health | GUMCAD data (N=11,180) | Survey population (N=751) | |||||
n (%) | Percentage excluding unknown/missing variables | n (%) | Percentage excluding unknown/missing variables | ||||
<25 | 1776 (15.88) | 15.88 | 167 (22.2) | 22.2 | <.001 | ||
≥25 | 9404 (84.11) | 84.11 | 584 (77.8) | 77.8 | <.001 | ||
Unknown/missing | 0 (0.00) | 0.00 | 0 (0.0) | 0.0 | —a | ||
White | 7671 (68.61) | 75.00 | 551 (73.3) | 74.3 | .70 | ||
Black African | 226 (2.02) | 2.02 | 15 (2.0) | 2.0 | .74 | ||
Black Caribbean | 350 (3.13) | 3.40 | 37 (4.9) | 5.0 | .03 | ||
Black other | 132 (1.80) | 1.31 | 2 (0.3) | 0.3 | .02 | ||
Mixed | 487 (4.35) | 4.80 | 50 (6.7) | 6.7 | .02 | ||
Asian | 876 (7.83) | 8.61 | 62 (8.3) | 8.3 | .85 | ||
Other ethnicities | 486 (4.34) | 4.81 | 24 (3.2) | 3.2 | .06 | ||
Unknown/missing | 952 (8.52) | – | 10 (1.33) | – | – | ||
Yes | 9051 (80.89) | 80.89 | 406 (71.1) | 71.1 | <.001 | ||
No | 2129 (19.04) | 19.04 | 165 (28.9) | 28.9 | <.001 | ||
Yes | 2203 (19.70) | 19.70 | 116 (20.3) | 20.3 | .72 | ||
No | 8977 (80.29) | 80.29 | 455 (79.7) | 79.7 | .72 |
aIndicates "not applicable".
bThere is no “missing” for these categories as there is no requirement to code when there is no STI screen or STI diagnosis.
cSexual health screen—one of the following test combinations: chlamydia and gonorrhea; chlamydia, gonorrhea, and syphilis; syphilis and HIV; and chlamydia, gonorrhea, syphilis, and HIV.
dSTI: sexually transmitted infections.
eAcute STI—any of chlamydia, gonorrhea, anogenital herpes (first episode), anogenital herpes (first episode), HIV, infectious syphilis, pelvic inflammatory disease/epididymitis, nonspecific genital infections, chancroid, lymphogranuloma venereum, donovanosis, trichomoniasis, scabies, pediculosis pubis, molluscum contagiosum, mycoplasma genitalium, shigella, hepatitis A, hepatitis B, and hepatitis C.
Compared with all the SHC attendees accessing BC only and combined study sites during the study period (N=97,054), of the 4184 survey participants recruited from these sites a higher proportion were aged <25 years (38.21%, 1599/4184 vs 30.94%, 30034/97,054;
As shown in
Our findings show that the BBEST is largely acceptable to SHC attendees and staff, and it is feasible to implement in SHCs across England. Specifically, the SHC attendees at greatest STI risk participated in the self-administered Web-based surveys using digital devices and consented to linkage. Linking survey data to the EHR was also feasible. However, a lack of resources dedicated to delivering the BBEST was a barrier to its implementation in some SHCs.
Study sites were purposively selected and thus are not representative of SHCs in England. Moreover, the survey offer rates varied considerably across sites increasing the likelihood of recruitment bias. We are unable to fully assess the representativeness of our sample because of the lack of data on decliners, attendees who agreed to participate but did not log in, and those who logged in but did not consent to participate. The representativeness analysis shows that, overall, groups at greater STI risk are overrepresented in the survey, for example, participants aged <25 years, gay/bisexual men, and BC participants. Nevertheless, the proportion of gay/bisexual identifying men who had an acute STI diagnosis on the day of clinic attendance was similar among those in the survey and in the clinic population, highlighting the similar STI risk profile of these men.
Overall, the response rate among those invited to participate was 62.23% (4585/7367); however, survey offer rates between SHCs varied enormously. Similar to our study, this interclinic variation was observed in previous clinic surveys conducted using pen and paper, with response rates among attendees across clinics varying from 41.0% to 70.1% in one study [
Compared with another study, a slightly higher proportion of participants in our study consented to linkage of their survey data to their EHR (91.2% vs 84.0%) [
Our findings suggest that the BBEST can be implemented to collect detailed behavioral data on factors influencing STI risk among SHC attendees, especially among populations at greatest STI risk in the event of outbreaks or periodically in response to significant public health concerns. Furthermore, the BBEST could be implemented in other settings such as hospitals, general practice, and with other populations at STI/HIV risk to strengthen interpretation of existing surveillance data. However, the impact of increasing private health care providers [
bio-behavioral enhanced surveillance tool
black Caribbean
Community Advisory Group
computer-assisted self-interview
community-based organizations
clinical research network
electronic health records
focus group discussions
men who have sex with men
participant information sheet
sexual health clinics
sexually transmitted infections
unique study passcode
The authors thank all the study participants and staff of SHCs involved in this study. The authors also thank all the community-based organizations who helped them to recruit participants for the qualitative study. The authors acknowledge the members of the National Institute of Health Research Health Protection Research Unit (NIHR HPRU) in Blood Borne and Sexually Transmitted Infections Steering Committee: Caroline Sabin, Anthony Nardone, Catherine Mercer, Gwenda Hughes, Greta Rait, Jackie Cassell, William Rosenberg, Tim Rhodes, Kholoud Porter, and Samreen Ijaz and the members of Theme A of the NIHR HPRU in Blood Borne and Sexually Transmitted Infections Steering Committee: Catherine Mercer, Gwenda Hughes, Hamish Mohammed, Jackie Cassell, Fiona Burns, Makeda Gerressu, Jonathan Elford, David Phillips, Gary Brook, Nicola Low, Anthony Nardone, Sarika Desai, Adamma Aghaizu, Alison Rodgers, and Paul Crook. The authors would like to thank Catherine Griffiths and Catherine Aicken for their help with the systematic review; Victoria Gilbart, Jessica Datta, and Emma Garnett for their help with qualitative data collection; and Lorna Sutcliffe and Jessica Datta for their help with coding qualitative data. The research was funded by the NIHR HPRU in Blood Borne and Sexually Transmitted Infections at UCL in partnership with Public Health England (PHE) and in collaboration with the London School of Hygiene and Tropical Medicine. SW and DR are funded by the NIHR HPRU in Blood Borne and Sexually Transmitted Infections at UCL in partnership with PHE and in collaboration with the London School of Hygiene and Tropical Medicine.
SW, DR, and PB set up the study, managed by PW, GH, and CM. SW and DR secured ethics and R&D permissions, and SW coordinated and managed the implementation of the study in all study sites, with support from PW, GH, and CM. SW undertook the systematic review; SW and DR undertook qualitative data collection and data analyses; SW, DR, and PB oversaw the delivery of the patient survey in GUM clinics; PB undertook the linkage of the patient survey data to GUMCAD. SW and PB analyzed the quantitative data. CM and GW secured funding from the National Institute for Health Research for the Health Research Health Protection Research Unit (NIHR HPRU) in Blood Borne and Sexually Transmitted Infections at University College London in partnership with Public Health England (PHE), in collaboration with London School of Hygiene & Tropical Medicine. All authors contributed to the drafting of the paper and approved the final version. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, the Department of Health, or Public Health England.
None declared.