Development of a framework for the implementation of electronic interventions in mental health: a protocol for a meta-synthesis of systematic reviews

Background: During the COVID-19 pandemic, it has been necessary to incorporate technologies in the care of mental health problems. But there have been difficulties in the application of technology-based interventions in mental health. Some quantitative systematic reviews don’t allow us to fully identify and properly describe this subject. In order to answer the question "how do electronic interventions apply in mental health and what makes the application of any of these interventions work", this study will carry out an overview of systematic reviews, which will make it possible to develop a theoretical framework on the implementation of electronic care in mental health problems. Methods: We will search MEDLINE, EBM Reviews, PsycINFO, EMBASE, SCOPUS, CINAHL Complete, and Web of Science databases from 1st January 2015 to September 2020, with no language restriction. We will follow a qualitative method approach and include systematic reviews that assess primary studies relating to adults with common mental health problems using any type of mobile mental health intervention that includes a synchronic component and communication with a mental health professional. For the analysis, we will make a meta-synthesis of the systematic reviews, using an emergent grounded theory approach to synthesize the information, prioritizing the systematic reviews with the lowest risk of bias in the AMSTAR-2 tool. The meta-synthesis will be based on interpreting, integrating, and inferring the evaluation elements to understand better the e-health implementation process for patients with mental health problems. Finally, we will present the overall assessment in a Summary of Qualitative Findings table. Conclusion: Our results will allow a better understanding of the facilitator and limitations in implementing e-health interventions for mental health problems.

A mathematically rigorous assessment of the efficiency of quarantining and contact tracing in curbing the COVID-19 epidemic

In our model of the COVID-19 epidemic, infected individuals can be of four types, according whether they are asymptomatic (A) or symptomatic (I), and use a contact tracing mobile phone app (Y) or not (N). We denote by f the fraction of A’s, by y the fraction of Y’s and by R0 the average number of secondary infections from a random infected individual.We investigate the effect of non-electronic interventions (voluntary isolation upon symptom onset, quarantining private contacts) and of electronic interventions (contact tracing thanks to the app), depending on the willingness to quarantine, parameterized by four cooperating probabilities.For a given ‘effective’ R0 obtained with non-electronic interventions, we use nonnegative matrix theory and stopping line techniques to characterize mathematically the minimal fraction y0 of app users needed to curb the epidemic. We show that under a wide range of scenarios, the threshold y0 as a function of R0 rises steeply from 0 at R0= 1 to prohibitively large values (of the order of 60 – 70% up) whenever R0 is above 1.3. Our results show that moderate rates of adoption of a contact tracing app can reduce R0 but are by no means sufficient to reduce it below 1 unless it is already very close to 1 thanks to non-electronic interventions.

Development and Deployment of Electronic Dispensing and Inventory Management system (eDIM) for a Rural Clinic in Honduras

Background: Availability of complete, accurate, and timely information is essential for efficient planning and purchasing of medications. This is especially important in remote low-resource clinics that are often difficult to access, have limited health personnel, and receive supplies infrequently. Appropriate application of information technology can help address challenges in the availability and quality of data used for making decisions about purchasing medical supplies.Methods: We used a phased deployment of electronic information systems to address challenges in quantification of the available medical supplies at the clinic in San José. First, we deployed a patient identification system to ensure that all medicines dispensed in the system were associated with a specific patient. This was followed by the deployment of an electronic dispensing and inventory management system that tracks available medicine and automatically deducts from these counts during electronic dispensation.Results: Twenty months post-deployment of the patient identification application and electronic dispensing and inventory management system, 3,238 unique patients have been registered and 22,236 dispensations have been recorded. Of these dispensations, 226 unique drugs have been recorded with acetaminophen being the most prescribed medication followed by adult multivitamins.Conclusion: Electronic interventions show significant promise for dispensaries in limited resource settings globally. However, strong user value propositions are needed to ensure continued usage.

An Electronic Strategy for Eliminating Unnecessary Duplicate Genetic Testing

Objectives To determine the impact of an electronic intervention designed to block duplicate constitutional genetic tests. Methods We constructed, implemented, and studied an electronic intervention that stopped duplicate genetic tests. The activation frequency, types of tests affected, and cost savings achieved with this intervention were determined. The frequency and justification of override requests were also studied. Results This intervention stopped 710 unnecessary duplicate genetic tests over a 3-year period and saved $98,596. The tests with the highest numbers of alerts were those used for screening presurgical or transplant patients and were commonly part of an order set or test panel. Most override requests were justified because of the lack of exclusion codes in the initial programming. Conclusions Electronic interventions that stop duplicate genetic testing, if properly constructed, can reduce waste, save health care dollars, and facilitate patient care by directing the provider to a test that has already been performed. 1.Duplicate molecular genetic testing, although generally unnecessary, occurs due to challenges in locating previous results. 2.Clinical decision support at order entry alerts providers to previous genetic test results and restricts repeat orders. 3.This Once-in-a-Lifetime electronic intervention supports a value-based health care model by reducing unnecessary genetic testing and associated costs.