Dataset Information

The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health Services Delivery Model Implemented in Rural India.

ABSTRACT: BACKGROUND:Although around 10% of Indians experience depression, anxiety, or alcohol use disorders, very few receive adequate mental health care, especially in rural communities. Stigma and limited availability of mental health services contribute to this treatment gap. The Systematic Medical Appraisal Referral and Treatment Mental Health project aimed to address this gap. OBJECTIVE:This study aimed to evaluate the effectiveness of an intervention in increasing the use of mental health services and reducing depression and anxiety scores among individuals at high risk of common mental disorders. METHODS:A before-after study was conducted from 2014 to 2019 in 12 villages in Andhra Pradesh, India. The intervention comprised a community antistigma campaign, with the training of lay village health workers and primary care doctors to identify and manage individuals with stress, depression, and suicide risk using an electronic clinical decision support system. RESULTS:In total, 900 of 22,046 (4.08%) adults screened by health workers had increased stress, depression, or suicide risk and were referred to a primary care doctor. At follow-up, 731 out of 900 (81.2%) reported visiting the doctor for their mental health symptoms, compared with 3.3% (30/900) at baseline (odds ratio 133.3, 95% CI 89.0 to 199.7; P<.001). Mean depression and anxiety scores were significantly lower postintervention compared with baseline from 13.4 to 3.1 (P<.001) and from 12.9 to 1.9 (P<.001), respectively. CONCLUSIONS:The intervention was associated with a marked increase in service uptake and clinically important reductions in depression and anxiety symptom scores. This will be further evaluated in a large-scale cluster randomized controlled trial.

SUBMITTER: Maulik PK

PROVIDER: S-EPMC7068463 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health Services Delivery Model Implemented in Rural India.

Maulik Pallab K PK Devarapalli Siddhardha S Kallakuri Sudha S Bhattacharya Amritendu A Peiris David D Patel Anushka A

Journal of medical Internet research 20200227 2

<h4>Background</h4>Although around 10% of Indians experience depression, anxiety, or alcohol use disorders, very few receive adequate mental health care, especially in rural communities. Stigma and limited availability of mental health services contribute to this treatment gap. The Systematic Medical Appraisal Referral and Treatment Mental Health project aimed to address this gap.<h4>Objective</h4>This study aimed to evaluate the effectiveness of an intervention in increasing the use of mental h ...[more]

PMID: 32130125

Similar Datasets

Project description:BackgroundHealth information technologies (HITs) are becoming increasingly recognized for their potential to provide innovative solutions to improve the delivery of mental health services and drive system reforms for better outcomes.ObjectiveThis paper describes the baseline results of a study designed to systematically monitor and evaluate the impact of implementing an HIT, namely the InnoWell Platform, into Australian mental health services to facilitate the iterative refinement of the HIT and the service model in which it is embedded to meet the needs of consumers and their supportive others as well as health professionals and service providers.MethodsData were collected via web-based surveys, semistructured interviews, and a workshop with staff from the mental health services implementing the InnoWell Platform to systematically monitor and evaluate its impact. Descriptive statistics, Fisher exact tests, and a reliability analysis were used to characterize the findings from the web-based surveys, including variability in the results between the services. Semistructured interviews were coded using a thematic analysis, and workshop data were coded using a basic content analysis.ResultsBaseline data were collected from the staff of 3 primary youth mental health services (n=18), a counseling service for veterans and their families (n=23), and a helpline for consumers affected by eating disorders and negative body image issues (n=6). As reported via web-based surveys, staff members across the services consistently agreed or strongly agreed that there was benefit associated with using technology as part of their work (38/47, 81%) and that the InnoWell Platform had the potential to improve outcomes for consumers (27/45, 60%); however, there was less certainty as to whether their consumers' capability to use technology aligned with how the InnoWell Platform would be used as part of their mental health care (11/45, 24% of the participants strongly disagreed or disagreed; 15/45, 33% were neutral; and 19/45, 42% strongly agreed or agreed). During the semistructured interviews (n=3) and workshop, participants consistently indicated that the InnoWell Platform was appropriate for their respective services; however, they questioned whether the services' respective consumers had the digital literacy required to use the technology. Additional potential barriers to implementation included health professionals' digital literacy and service readiness for change.ConclusionsDespite agreement among participants that HITs have the potential to result in improved outcomes for consumers and services, service readiness for change (eg, existing technology infrastructure and the digital literacy of staff and consumers) was noted to potentially impact the success of implementation, with less than half (20/45, 44%) of the participants indicating that their service was ready to implement new technologies to enhance mental health care. Furthermore, participants reported mixed opinions as to whether it was their responsibility to recommend technology as part of standard care.

Project description:BackgroundThe recent Australian National Agenda for Eating Disorders highlights the role technology can play in improving accessibility and service development through web-based prevention, early access pathways, self-help, and recovery assistance. However, engagement with the eating disorders community to co-design, build, and evaluate these much-needed technology solutions through participatory design processes has been lacking and, until recently, underresourced.ObjectiveThis study aims to customize and configure a technology solution for a nontraditional (web-based, phone, email) mental health service that provides support for eating disorders and body image issues through the use of participatory design processes.MethodsParticipants were recruited chiefly through the Butterfly National Helpline 1800 ED HOPE (Butterfly's National Helpline), an Australian-wide helpline supporting anyone concerned by an eating disorder or body image issue. Participants included individuals with lived experience of eating disorders and body image issues, their supportive others (such as family, health professionals, support workers), and staff of the Butterfly Foundation. Participants took part in participatory design workshops, running up to four hours, which were held nationally in urban and regional locations. The workshop agenda followed an established process of discovery, evaluation, and prototyping. Workshop activities included open and prompted discussion, reviewing working prototypes, creating descriptive artifacts, and developing user journeys. Workshop artifacts were used in a knowledge translation process, which identified key learnings to inform user journeys, user personas, and the customization and configuration of the InnoWell Platform for Butterfly's National Helpline. Further, key themes were identified using thematic techniques and coded in NVivo 12 software.ResultsSix participatory design workshops were held, of which 45 participants took part. Participants highlighted that there is a critical need to address some of the barriers to care, particularly in regional and rural areas. The workshops highlighted seven overarching qualitative themes: identified barriers to care within the current system; need for people to be able to access the right care anywhere, anytime; recommendations for the technological solution (ie, InnoWell Platform features and functionality); need for communication, coordination, and integration of a technological solution embedded in Butterfly's National Helpline; need to consider engagement and tone within the technological solution; identified challenges and areas to consider when implementing a technological solution in the Helpline; and potential outcomes of the technological solution embedded in the Helpline relating to system and service reform. Ultimately, this technology solution should ensure that the right care is provided to individuals the first time.ConclusionsOur findings highlight the value of actively engaging stakeholders in participatory design processes for the customization and configuration of new technologies. End users can highlight the critical areas of need, which can be used as a catalyst for reform through the implementation of these technologies in nontraditional services.

Project description:BackgroundDespite the widely acknowledged potential for health information technologies to improve the accessibility, quality and clinical safety of mental health care, implementation of such technologies in services is frequently unsuccessful due to varying consumer, health professional, and service-level factors. The objective of this co-design study was to use process mapping (i.e. service mapping) to illustrate the current consumer journey through primary mental health services, identify barriers to and facilitators of quality mental health care, and highlight potential points at which to integrate the technology-enabled solution to optimise the provision of care based on key service performance indicators.MethodsInteractive, discussion-based workshops of up to six hours were conducted with representative stakeholders from each participating service, including health professionals, service managers and administrators from Open Arms - Veterans & Families Counselling Service (Sydney), a counselling service for veterans and their families, and five headspace centres in the North Coast Primary Health Network, primary youth mental health services. Service maps were drafted and refined in real time during the workshops. Through both group discussion and the use of post-it notes, participants worked together to evaluate performance indicators (e.g. safety) at each point in the consumer journey (e.g. intake) to indicate points of impact for the technology-enabled solution, reviewing and evaluating differing opinions in order to reach consensus.ResultsParticipants (n=84 across participating services) created service maps illustrating the current consumer journey through the respective services and highlighting barriers to and facilitators of quality mental health care. By consensus, the technology-enabled solution as facilitated by the InnoWell Platform was noted to enable the early identification of risk, reduce or eliminate lengthy intake processes, enable routine outcome monitoring to revise treatment plans in relation to consumer response, and serve as a personal data record for consumers, driving person-centred, coordinated care.ConclusionsService mapping was shown to be an effective methodology to understand the consumer's journey through a service and served to highlight how the co-designed technology-enabled solution can optimise service pathways to improve the accessibility, quality and clinical safety of care relative to key service performance indicators, facilitating the delivery of the right care.

Project description:BackgroundEven before COVID-19, there has been an urgent need to expand access to and quality of mental health care. This paper introduces an 8-week treatment protocol to realize that vision-Technology Enabled Clinical Care (TECC). TECC offers innovation in clinical assessment, monitoring, and interventions for mental health. TECC uses the mindLAMP app to enable digital phenotyping, clinical communication, and smartphone-based exercises that will augment in-person or telehealth virtual visits. TECC exposes participants to an array of evidence-based treatments (cognitive behavioral therapy, dialectical behavior therapy, acceptance and commitment therapy) introduced through clinical sessions and then practiced through interactive activities provided through a smartphone app called mindLAMP.ObjectiveTECC will test the feasibility of providing technology-enabled mental health care within an outpatient clinic; explore the practicality for providing this care to individuals with limited English proficiency; and track anxiety, depression, and mood symptoms for participants to measure the effectiveness of the TECC design.MethodsThe TECC study will assess the acceptability and efficacy of this care model in 50 participants as compared to an age- and gender-matched cohort of patients presenting with similar clinical severity of depression, anxiety, or psychotic symptoms. Participants will be recruited from clinics in the Metro Boston area. Aspects of TECC will be conducted in both Spanish and English to ensure wide access to care for multiple populations.ResultsThe results of the TECC study will be used to support or adapt this model of care and create training resources to ensure its dissemination. The study results will be posted on ClinicalTrials.gov, with primary outcomes related to changes in mood, anxiety, and stress, and secondary outcomes related to engagement, alliance, and satisfaction.ConclusionsTECC combines new digital mental health technology with updated clinical protocols and workflows designed to ensure patients can benefit from innovation in digital mental health. Supporting multiple languages, TECC is designed to ensure digital health equity and highlights how mobile health can bridge, not expand, gaps in care for underserved populations.International registered report identifier (irrid)PRR1-10.2196/23771.

Project description:BackgroundPrior to the COVID-19 pandemic, major shortcomings in the way mental health care systems were organized were impairing the delivery of effective care. The mental health impacts of the pandemic, the recession, and the resulting social dislocation will depend on the extent to which care systems will become overwhelmed and on the strategic investments made across the system to effectively respond.ObjectiveThis study aimed to explore the impact of strengthening the mental health system through technology-enabled care coordination on mental health and suicide outcomes.MethodsA system dynamics model for the regional population catchment of North Coast New South Wales, Australia, was developed that incorporated defined pathways from social determinants of mental health to psychological distress, mental health care, and suicidal behavior. The model reproduced historic time series data across a range of outcomes and was used to evaluate the relative impact of a set of scenarios on attempted suicide (ie, self-harm hospitalizations), suicide deaths, mental health-related emergency department (ED) presentations, and psychological distress over the period from 2021 to 2030. These scenarios include (1) business as usual, (2) increase in service capacity growth rate by 20%, (3) standard telehealth, and (4) technology-enabled care coordination. Each scenario was tested using both pre- and post-COVID-19 social and economic conditions.ResultsTechnology-enabled care coordination was forecast to deliver a reduction in self-harm hospitalizations and suicide deaths by 6.71% (95% interval 5.63%-7.87%), mental health-related ED presentations by 10.33% (95% interval 8.58%-12.19%), and the prevalence of high psychological distress by 1.76 percentage points (95% interval 1.35-2.32 percentage points). Scenario testing demonstrated that increasing service capacity growth rate by 20% or standard telehealth had substantially lower impacts. This pattern of results was replicated under post-COVID-19 conditions with technology-enabled care coordination being the only tested scenario, which was forecast to reduce the negative impact of the pandemic on mental health and suicide.ConclusionsThe use of technology-enabled care coordination is likely to improve mental health and suicide outcomes. The substantially lower effectiveness of targeting individual components of the mental health system (ie, increasing service capacity growth rate by 20% or standard telehealth) reiterates that strengthening the whole system has the greatest impact on patient outcomes. Investments into more of the same types of programs and services alone will not be enough to improve outcomes; instead, new models of care and the digital infrastructure to support them and their integration are needed.

Project description:BackgroundAbout 25% of the Indian population experience common mental disorders (CMD) but only 15-25% of them receive any mental health care. Stigma, lack of adequate mental health professionals and mental health services account for this treatment gap, which is worse in rural areas. Our project evaluated task shifting and mobile-technology based electronic decision support systems to enhance the ability of primary care health workers to provide evidence-based mental health care for stress, depression, and suicidal risk in 30 remote villages in the state of Andhra Pradesh, India.MethodsThe Systematic Medical Appraisal Referral and Treatment (SMART) Mental Health project between May 2014 and April 2016 trained lay village health workers (Accredited Social Health Activists - ASHAs) and primary care doctors to screen, diagnose and manage individuals with common mental disorders using an electronic decision support system. An anti-stigma campaign using multi-media approaches was conducted across the villages at the outset of the project. A pre-post evaluation using mixed methods assessed the change in mental health service utilization by screen positive individuals. This paper reports on the quantitative aspects of that evaluation.ResultsTraining was imparted to 21 ASHAs and 2 primary care doctors. 5007 of 5167 eligible individuals were screened, and 238 were identified as being positive for common mental disorders and referred to the primary care doctors for further management. Out of them, 2 (0.8%) had previously utilized mental health services. During the intervention period, 30 (12.6%) visited the primary care doctor for further diagnosis and treatment, as advised. There was a significant reduction in the depression and anxiety scores between start and end of the intervention among those who had screened positive at the beginning. Stigma and mental health awareness in the broader community improved during the project.ConclusionsThe intervention led to individuals being screened for common mental disorders by village health workers and increase in mental health service use by those referred to the primary care doctor. The model was deemed feasible and acceptable. The effectiveness of the intervention needs to be demonstrated using more robust randomized controlled trials, while addressing the issues identified that will facilitate scale up.

Project description:Standard methods for indirect comparisons and network meta-analysis are based on aggregate data, with the key assumption that there is no difference between the trials in the distribution of effect-modifying variables. Methods which relax this assumption are becoming increasingly common for submissions to reimbursement agencies, such as the National Institute for Health and Care Excellence (NICE). These methods use individual patient data from a subset of trials to form population-adjusted indirect comparisons between treatments, in a specific target population. Recently proposed population adjustment methods include the Matching-Adjusted Indirect Comparison (MAIC) and the Simulated Treatment Comparison (STC). Despite increasing popularity, MAIC and STC remain largely untested. Furthermore, there is a lack of clarity about exactly how and when they should be applied in practice, and even whether the results are relevant to the decision problem. There is therefore a real and present risk that the assumptions being made in one submission to a reimbursement agency are fundamentally different to-or even incompatible with-the assumptions being made in another for the same indication. We describe the assumptions required for population-adjusted indirect comparisons, and demonstrate how these may be used to generate comparisons in any given target population. We distinguish between anchored and unanchored comparisons according to whether a common comparator arm is used or not. Unanchored comparisons make much stronger assumptions, which are widely regarded as infeasible. We provide recommendations on how and when population adjustment methods should be used, and the supporting analyses that are required to provide statistically valid, clinically meaningful, transparent and consistent results for the purposes of health technology appraisal. Simulation studies are needed to examine the properties of population adjustment methods and their robustness to breakdown of assumptions.

Project description:BACKGROUND:Despite their high prevalence and significant burden, mental disorders such as depression remain largely underdiagnosed and undertreated. OBJECTIVE:The aim of the Allillanchu Project was to design, develop, and test an intervention to promote early detection, opportune referral, and access to treatment of patients with mental disorders attending public primary health care (PHC) services in Lima, Peru. METHODS:The project had a multiphase design: formative study, development of intervention components, and implementation. The intervention combined three strategies: training of PHC providers (PHCPs), task shifting the detection and referral of mental disorders, and a mobile health (mHealth) component comprising a screening app followed by motivational and reminder short message service (SMS) to identify at-risk patients. The intervention was implemented by 22 PHCPs from five health centers, working in antenatal care, tuberculosis, chronic diseases, and HIV or AIDS services. RESULTS:Over a period of 9 weeks, from September 2015 to November 2015, 733 patients were screened by the 22 PHCPs during routine consultations, and 762 screening were completed in total. The chronic diseases (49.9%, 380/762) and antenatal care services (36.7%, 380/762) had the higher number of screenings. Time constraints and workload were the main barriers to implementing the screening, whereas the use of technology, training, and supervision of the PHCPs by the research team were identified as facilitators. Of the 733 patients, 21.7% (159/733) screened positively and were advised to seek specialized care. Out of the 159 patients with a positive screening result, 127 had a follow-up interview, 72.4% (92/127) reported seeking specialized care, and 55.1% (70/127) stated seeing a specialist. Both patients and PHCPs recognized the utility of the screening and identified some key challenges to its wider implementation. CONCLUSIONS:The use of a screening app supported by training and supervision is feasible and uncovers a high prevalence of unidentified psychological symptoms in primary care. To increase its sustainability and utility, this procedure can be incorporated into the routine practices of existing health care services, following tailoring to the resources and features of each service. The early detection of psychological symptoms by a PHCP within a regular consultation, followed by adequate advice and support, can lead to a significant percentage of patients accessing specialized care and reducing the treatment gap of mental disorders.

Dataset Information

The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health Services Delivery Model Implemented in Rural India.

Publications

The Systematic Medical Appraisal Referral and Treatment Mental Health Project: Quasi-Experimental Study to Evaluate a Technology-Enabled Mental Health Services Delivery Model Implemented in Rural India.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets