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Tag: primary care
06/06/2023

Implementation and workflow strategies for integrating digital therapeutics for alcohol use disorders into primary care: a qualitative study

Mogk JM, Matson TE, Caldeiro RM, Garza Mcwethy AM, Beatty T, Sevey BC, Hsu CW, Glass JE. Implementation and workflow strategies for integrating digital therapeutics for alcohol use disorders into primary care: a qualitative study. Addict Sci Clin Pract. 2023 May 8;18(1):27. doi: 10.1186/s13722-023-00387-w.

This study aimed to identify implementation needs and strategy design considerations for integrating digital therapeutics for alcohol use disorders (AUD) into primary care. Qualitative interviews were conducted with clinicians, care delivery leaders, and implementation staff (N=16). All participants had experience implementing digital therapeutics for depression or substance use disorders in primary care in the United States. Participants were asked to share successes and challenges from implementation efforts and how these experiences could inform the implementation of digital therapeutics for AUD. Common themes were identified across health system staff roles. Participants were committed to digital therapeutics for AUD and anticipated high patient demand for such treatments. Reported facilitators of successful implementation included: 1) use implementation strategies that align with the needs of patients with varying AUD severity, 2) use strategies that minimize burden on clinicians, and 3) offer digital therapeutics as an adjunct to other treatments for AUD. Other helpful implementation strategies included clinician training and electronic health record support. Findings inform future efforts to implement digital interventions for AUD in primary care.

02/28/2023

MHT Delivers New Technology for Measuring and Improving Mental Wellness

Article Excerpt: Mental Health Technologies (MHT) offers a rapidly growing cloud-based platform primary care physicians and mental health professionals use to screen and test for mental health disorders, including depression and substance abuse. MHT helps providers identify areas where their patients are struggling and refers them to the proper behavioral healthcare professional…SmarTest is a tool that uses intelligence and historical data to define when-and how-a patient should be tested for various mental health conditions. It can base its decisions on patient information, such as age, gender, or other demographics.

Full Article: https://tinyurl.com/6ruxh22t

Article Source: Accesswire

07/25/2022

Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder

Megerian JT, Dey S, Melmed RD, Coury DL, Lerner M, Nicholls CJ, Sohl K, Rouhbakhsh R, Narasimhan A, Romain J, Golla S, Shareef S, Ostrovsky A, Shannon J, Kraft C, Liu-Mayo S, Abbas H, Gal-Szabo DE, Wall DP, & Taraman S (2022). Evaluation of an artificial intelligence-based medical device for diagnosis of autism spectrum disorder. NPJ Digital Medicine, 5(1), 57–57. https://doi.org/10.1038/s41746-022-00598-6

Researchers conducted a double-blinded, multi-site, active comparator cohort study to test the accuracy of artificial intelligence software for diagnosing autism spectrum disorder (ASD). The software device collects data about child behavioral features from 3 sources (caregiver questionnaire, analysis of two short 1 minute home videos recorded and uploaded by the child’s caregiver, provider questionnaire). Data are processed using a machine learning algorithm to indicate whether a person is ASD positive, ASD negative, or inconclusive (i.e., inputted data are not sufficient for a predictive output). Researchers evaluated the software in a study with 425 children aged 18-72 months for whom a caregiver or provider had a concern about developmental delay. Researchers compared the software outputs to the clinical standard (diagnosis made by a provider based on DSM-5 criteria). Results demonstrated that data collection with the software device took less time to administer and require less specialty training relative to clinical standard process. For about 33% of the sample, the algorithm output supported accurate diagnoses compared with clinical evaluation. Of the children for whom the software algorithm made a definite evaluation, 98.4% with clinically diagnosed ASD received an ASD positive result and 78.9% without a clinical diagnosis of ASD received an ASD negative result. All children who received a false-positive result (n=15) had a non-ASD developmental condition. Only one child received a false negative result in this study. Overall, this machine learning tool demonstrated high sensitivity and good specificity for diagnosing ASD. The tool can potentially expand the ability to effectively diagnose children with ASD in primary care to facilitate early intervention and more efficient use of specialist resources.

07/06/2022

How Telehealth Can Enhance Mental Health Care Integration

Article Excerpt: With the nation in its third year of the COVID-19 pandemic, people are under tremendous stress. Even patients who in general have been well-adjusted and healthy, particularly children and adolescents, are finding they need mental health care. Using technology to integrate behavioral health care into primary care settings—settings that patients are visiting on a regular basis for routine care or other medical needs—is a key way to help patients access the mental health care they need in a system that doesn’t have enough providers to meet the demand for behavioral health care.

Full Article: https://tinyurl.com/3h46j2fj

Article Source: AMA

 

06/06/2022

Implementation of collaborative care for depressive disorder treatment among accountable care organizations

Newton H, Busch SH, Brunette M, Maust DT, O’Malley J, Meara ER. Implementation of collaborative care for depressive disorder treatment among accountable care organizations. Medicine 2021;100:27(e26539).

Collaborative care is a cost-effective model of primary care that combines care management, consulting behavioral health clinicians and registries to target mental health treatment. A study was conducted to determine the prevalence of collaborative care implementation in accountable care organizations (ACOs) and identify characteristics in ACOs associated with implementation. Researchers examined the association between implementation of collaborative care components and ACO characteristics. Four hundred five total respondents completed questions on collaborative care implementation in the 2017-2018 National Survey of ACOs. Only seventeen percent of ACOs implemented all collaborative care components. The most common components were care managers (71% of ACOs) and consulting mental health clinicians (58%). The least frequently implemented component was using patient registries to track and target mental health treatment (only 26%). The findings also showed ACOs responsible for mental healthcare quality measures were significantly more likely to implement collaborative care. This study demonstrates most ACOs do not have full implementation of behavioral health collaborative care. Payers interested in incentivizing integrated mental health care should address barriers to collaborative care implementation.

05/17/2022

Geisel Researchers Receive $4 Million Grant to Improve Office Visit Interactions Between People Living with Dementia, Care Partners, and Clinicians

Article Excerpt: A team of researchers at Dartmouth’s Geisel School of Medicine and New York University (NYU) Grossman School of Medicine has received a $4 million grant from the National Institute on Aging to improve “triadic” interactions between patients living with dementia, their care partners, and their clinicians. An estimated 6.5 million Americans aged 65 or older currently live with Alzheimer’s disease or Alzheimer’s disease-related dementia, and that number is projected to rise to nearly 13 million by 2050, placing an even greater burden on patients, caregivers, and the healthcare system. People living with dementia and their care partners (typically family members or friends) rely on primary care clinic visits for information about their disease, its management, and community referrals. While research has shown that quality interpersonal communication is associated with improved health outcomes, the degree to which effective communication is achieved during triadic visits is unknown, and few interventions have been developed to support it.

Full Article: https://tinyurl.com/yhmz8phe

Article Source: Dartmouth Geisel School of Medicine News

04/04/2022

A digital health registry with clinical decision support for improving quality of antenatal care in Palestine (eRegQual): a pragmatic, cluster-randomised, controlled, superiority trial

Venkateswaran M, Ghanem B, Abbas E, Khader KA, Ward IA, Awwad T, Baniode M, Frost MJ, Hijaz T, Isbeih M, Mørkrid K, Rose CJ, & Frøen JF. (2022). A digital health registry with clinical decision support for improving quality of antenatal care in Palestine (eRegQual): a pragmatic, cluster-randomised, controlled, superiority trial. The Lancet. Digital Health, 4(2), e126–e136. https://doi.org/10.1016/S2589-7500(21)00269-7

The public health system in Palestine implemented a digital maternal and child health eRegistry with clinical decision support. Researchers compared the quality of antenatal care between primary care clinics with eRegistry and those with paper-based records. The study is a cluster-randomized controlled trial in primary health care clinics that provide antenatal care in the West Bank, Palestine. Fifty-nine clusters were randomly assigned to the control (paper-based records) group and 60 clusters to the intervention (eRegistry with clinical decision support) group. Researchers looked at the effectiveness of the eRegistry system in improving the provision of timely and appropriate screening and management in routine antenatal care, and health outcomes at delivery for mothers and newborns. Between January to September 2017, 3217 pregnant women and 3148 pregnant women received care in the intervention and control clinics respectively. The results found women were more often screened for risk factors and referred to high-risk clinics in intervention clinics (17.6%) compared to control clinics (12.6%). Compared to the control group, pregnant women were more often screened and managed for anemia, gestational diabetes, and hypertension in the intervention group than in the control group (adjusted ORs from 1.45 to 1.88). Only 9.4% of pregnant women attended the full schedule of routine antenatal care across both groups. There were no differences in fetal growth monitoring, antenatal care attendance, or adverse outcomes at delivery in the control and intervention groups. Overall, the improvements in most process outcomes strengthen the evidence of digital client tracking in lower-middle income settings and digital interventions can facilitate better coverage of antenatal care.

11/18/2021

Kudos: Harnessing the Human Heartbeat and More

Article Excerpt: A team of researchers, including Lisa Marsch, the Andrew G. Wallace Professor of psychiatry and biomedical data science and director of the Dartmouth Center for Technology and Behavioral Health; William Torrey, the Raymond Sobel Professor of Psychiatry and interim chair of the Department of Psychiatry, have received Colombian National Academy of Medicine Award for their work implementing a new primary care model that provides widespread access to diagnosis and treatment of depression and unhealthy alcohol use.

Full Article: https://tinyurl.com/yww5y84n

Article Source: Dartmouth News

11/17/2021

A Telehealth Effort to Treat PTSD and Bipolar Disorder in Rural Areas Showed ‘Huge Gains.’ Now Comes the Hard Part

Article Excerpt: A multiyear effort to pipe big-city mental health providers to rural communities over video accomplished a trifecta of telehealth victories: It reached people who wouldn’t otherwise have access to mental health care; it tackled difficult diagnoses that don’t have simple answers; and it stretched how many people the most skilled providers can treat. Now comes the inevitable question that follows any technology breakthrough: Does it scale?

Full Article: https://tinyurl.com/umu55tp7

Article Source: STAT