The Impact of Expanded Tele-Mental Health on Quality-Of-Care Indicators: A Three-Pronged Regression Analysis at Los Angeles County’s Department of Mental Health
type: CreativeWork
description: Background: The use of Tele-Mental Health (TMH) skyrocketed after the COVID-19 pandemic led to the announcement of a public health emergency in March 2020. This rise coincided with soaring rates of mental health issues and increasing demand for accessible and sustainable treatment, all while meeting physical distancing requirements. TMH use is theorized to improve timely access to care and provide opportunities to improve quality of care indicators in individuals and at the health systems level. Research Question: How has the widespread adoption of Tele-Mental Health changed quality of care (QoC) indicators among patients of LA County Department of Mental Health’s (LAC DMH) Directly Operated (DO) clinics? Methods: The study design for this analysis is a multivariate quasi-experimental study with a pseudo-control. A three-pronged approach to the analysis was used to tackle the research question and two QoC indicators are defined as the binary “Timely” variable and the continuous “Appointment Adherence” variable. All the models adjusted for covariates (demographic variables and the ratio of patients to providers) and mediators (the Request Type, which determines the timely standards of care). A “Pandemic Time” variable referred to if the data point took place before March 19, 2020, which referred to the date that the Safer-at-Home Order (SHO) was announced, or after. The first prong, approach A, used a logistic regression for the Timely variable and an OLS regression for Appointment Adherence; it compared users of TMH to those receiving in-person care and included the pandemic time variable. Approach B did the same but accounted for crowding effects over time by adding an offset variable for the ratio of appointment requests to providers. An ANOVA for the first two approaches determined the effect size of the variables and those that had an effect size over 0.01 were used to build a parsimonious model for Approach C. Approach C used Interrupted Time Series models to c…
abstract: Background: The use of Tele-Mental Health (TMH) skyrocketed after the COVID-19 pandemic led to the announcement of a public health emergency in March 2020. This rise coincided with soaring rates of mental health issues and increasing demand for accessible and sustainable treatment, all while meeting physical distancing requirements. TMH use is theorized to improve timely access to care and provide opportunities to improve quality of care indicators in individuals and at the health systems level. Research Question: How has the widespread adoption of Tele-Mental Health changed quality of care (QoC) indicators among patients of LA County Department of Mental Health’s (LAC DMH) Directly Operated (DO) clinics? Methods: The study design for this analysis is a multivariate quasi-experimental study with a pseudo-control. A three-pronged approach to the analysis was used to tackle the research question and two QoC indicators are defined as the binary “Timely” variable and the continuous “Appointment Adherence” variable. All the models adjusted for covariates (demographic variables and the ratio of patients to providers) and mediators (the Request Type, which determines the timely standards of care). A “Pandemic Time” variable referred to if the data point took place before March 19, 2020, which referred to the date that the Safer-at-Home Order (SHO) was announced, or after. The first prong, approach A, used a logistic regression for the Timely variable and an OLS regression for Appointment Adherence; it compared users of TMH to those receiving in-person care and included the pandemic time variable. Approach B did the same but accounted for crowding effects over time by adding an offset variable for the ratio of appointment requests to providers. An ANOVA for the first two approaches determined the effect size of the variables and those that had an effect size over 0.01 were used to build a parsimonious model for Approach C. Approach C used Interrupted Time Series models to c…
author: Bhatt, Ami
keywords: Public Health
date published: 2022-01-01T08:00:00Z
date modified: 2026-07-24T01:40:15Z
provider: Claremont Graduate University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Claremont Graduate University