S-MHINT Hub Project Summary
Transcript
DR. PETERSON: Hello, I'm Inge Peterson, and I am presenting on behalf of the SMhINT Hub on our scaleup study which has been looking at implementing integrated depression care in real-world community health settings, using implementation science.
We have used a two-stage iterative mixed-method observational implementation research design, within a learning health systems approach. In stage one, we have been evaluating an initial set-up model, which was originally tested within the PRIME program in South Africa, and then repackaged for scaleup through the mental health integration project, the MhINT program.
We've used both the RE-AIM framework and CFIR framework to understand service-level outcomes, and we have completed this first stage and have also then been involved within our learning collaborative with the provincial department of health to refine and strengthen the intervention for implementation, which we are currently evaluating in the second stage, with some of the activities already being scaled across the province and taken up nationally as well.
In relation to the emergent original MhINT technical support package, we focused on two things, strengthening diagnosis by community healthcare nurses in South Africa, using a strengthened mental health training as an adjunct to adult primary care algorithms, which include the mhGAP algorithms, but are for all conditions. And we also strengthened referral pathways through implementing a co-located counseling service in each facility, and this complements the existing referral pathways, which were to limited primary healthcare doctors, as well as very limited and specialist mental health services at district hospital level.
In terms of implementation strategies, we've used guidelines, cascaded training, as well as quality improvement, mentoring, and supervision, particularly of the counseling program.
Highlights from stage one. In terms of reach along the cascade of care, so looking at diagnosis, to referral, to uptake of referral, we found that nurses were able to diagnose 49 percent of patients in the waiting room, which we had screened positive with depression. Of those they diagnosed, they referred 37 percent, which amounted to 80 percent of the total sample, and of those referred, 25 percent took up treatment, which only amounted to 5 percent of the initial screened-positive sample.
Probability of detection increased with increased depression severity, increased perceived stress, increased alcohol use. It decreased with increased other chronic conditions, which is of concern, and probability of uptake, where the increase was lowered social support.
In terms of effectiveness, what we found was at three-months follow-up, patients diagnosed and referred were twice more likely to have a 50 percent reduction in depressive symptoms, compared to those diagnosed only, and this was not statistically significant however at nine months follow-up.
In terms of adoption and implementation, what we found was variation between and within facilities over time along the cascade of care. Too much detail to present in this short presentation.
In terms of understanding our findings, we used a cross-sectional survey and CFIR interviews. At an individual level, we found enabling factors to be training exposure; barriers were personal emotional issues for both primary healthcare nurses as well as counselors. In terms of the inner setting, barriers were the cascade model of training, which watered down the fidelity of the training received at the facility level, high workloads, no validated screening tool, with nurses questioning the validity of the information generated by the screening and the vital signs room, lack of supervision and mentoring particularly for nurses, and co-located counseling not always available because of other roles and responsibilities of the people tasked with counseling.
Outer setting characteristics, low levels of mental health literacy and demand for services emerged as a strong barrier, and in terms of intervention characteristic, barriers included the additional time taken to make a diagnosis; an enabling factor was that counseling was acceptable to patients.
Strengthening of the MhINT intervention. We have spent the time during the lockdown actually strengthening the MhINT intervention along the cascade of care, so just quickly, to look at what we've done. In terms of the need to increase demand for services and mental health literacy, we have developed and validated a community mental health education and detection tool to be used by community health workers. It uses stories with an algorithm to help educate household members around mental health problems, as well as help community health workers to make referral and it is modeled on the CIDT that was developed in the fall PRIME program.
In terms of educational information within facilities, we've strengthened the morning talks, as well as provided educational material, providing a stepped up approach to self-care, followed by help-seeking in terms of telephonic counseling and face-to-face counseling, and we have embedded self-help videos within this material.
In terms of screening, in order to address the lack of a validated screening, we validated the brief mental health screening tool, which was implemented in all facilities across the province.
In terms of assessment by the nurses, what we've done here is we have shifted the adult primary healthcare training, including mental health, to an online platform, so as to improve fidelity of the training that nurses in the facilities receive, as well as developed an APC wellness resource, which is also available online, for primary healthcare providers.
In terms of treatment initiative, what we've done here is we've strengthened the counseling sessions through shifting towards a facilitated self-help approach, where we have embedded self-help videos focused on healthy thinking, problem management, as well as coping with grief and bereavement, to improve the fidelity of the counseling program, as well as to provide a resource for patients referred for counseling to use at home so they don't need to attend so many sessions either.
So we have continued to use continuous quality improvement to embed the intervention along the cascade, and have been working with the department of health to strengthen the indicators along each of the elements of the cascade. The outstanding one at the time when we were doing this work was actually this positivity rate indicator, which has since been introduced.
In terms of the second stage evaluation, we have some preliminary results which I can share with you. What we have found along the cascade in terms of reach, looking at diagnosis and referral from the first to the second stage evaluation, in stage one, so you will see, if you recall, that the nurses were able to diagnose 49 percent of patients that we identified as screening positive for depression. In the second stage, they were able to diagnose 48 percent, which suggests that we have reached a ceiling with regard to diagnosis, which is around 50 percent, and quite on a par with international findings.
With regard to referral rates, what we see, however, is a large increase from 37 percent of patients referred that were diagnosed to 91 percent of patients diagnosed that were referred, which amounts to an increase from 18 percent of the original sample to 43 percent of the original sample that were screened positive.
Unfortunately, we have not managed to complete the linkage of the data to look at whether there has been an improvement in uptake of referrals.
In terms of lessons learned, then, I would like to focus on two issues, really. That in terms of implementation and scaleup, it really requires a multifaceted approach to embed mental health within the primary healthcare system, and this multifaceted approach requires, one, technical support to assist with material development, master training, mentorship, et cetera, which we really had the opportunity to provide through the mentor program. And implementation research to assess outcomes and determinants, and to see how we need to strengthen the intervention for real-world implementation and scaleup. And we've really had the opportunity at the SMhINT research hub to be able to do that.
And then lastly and most importantly is the need to adopt a learning health system process to strengthen the healthcare system to create an enabling context. So we established a learning system with the provincial department of health, and we used our testing site to actually generate the lessons on how we needed, through our research, how we needed to strengthen the intervention, and this has been fed back into our learning health collaboration at the provincial level. We have been working to create an enabling context. So, for example, in terms of scaleup, the CMED tool, at the community level, was developed in consultation with the provincial department of health and has actually now been adopted by the national department of health as part of the foundation-level training for community health workers nationally.
The strengthened mental health profession talks as well as posters has been scaled up across the province in KZN, as has the brief mental health screening tool, at facility level, and the APC mental health module has been incorporated into the whole of the APC course that nurses are now required to do across the country. Finally, we have worked with the department of health to strengthen the indicators along the cascade.
The second lesson is that mental health really needs to be part of horizontal programing. Mental health continues to be viewed as an add-on and the last problem to be dealt with in busy primary healthcare settings. And what we are seeing is that a shift towards horizontal programming, provides a funding and policy opportunity to embed mental health from the outset into these health system reforms, and we are currently working with the KZN department of health to do this. This really has implications for the siloed positioning of global mental health in relation to mental health more generally that may need to be looked at in the future.
I'd just like to close with thanking my team members for the University of KwaZulu-Natal, University Cape Town, University of East Anglia, and University of Washington, and in particular, Professors Arvin Bhana and Deepa Rao, who are my co-PIs on the SMhINT consortium. Thank you.