Background Due to the COVID-19 pandemic, there was a significant reduction in in-person healthcare visits as a precautionary measure to minimize the risk of infection for both patients and healthcare provides. Consequently, there was a remarkable surge in the adoption of telehealth services, although mental healthcare services were already using it more frequently than primary and specialty care services before the pandemic. Despite the continued increase in telehealth services, there are differing views among healthcare providers on the efficacy of providing healthcare services remotely, leading to an opportunity to investigate this matter further. Objective The primary goal of this study was to evaluate differences in perceptions and attitudes, experience with patient interactions and overall telehealth experiences between mental health providers and non-mental health providers. Methods The proposed study collected primary data through surveying providers across the United States from November 2022-March 2023. The surveys were conducted through REDCap, and disseminated through research staff outreach and recruitment. Providers were asked to complete a 33-item survey, which took them about 30 minutes to finish and queried them about their satisfaction, utilization, and experiences with telehealth. The provider survey was disseminated to both mental health providers and non-mental health providers who use telehealth technology. Descriptive analysis was conducted to determine the characteristics of the population surveyed. Data was then dichotomized by mental health providers vs. non-mental health providers. Differences in mean responses for all variables between mental health and non-mental health providers was assessed using Mann-Whitney U (MW) tests. Results A Mann-Whitney Wilcoxon test indicated that the satisfaction with the telemedicine platform was greater for non-mental healthcare providers than mental healthcare providers (p < .05). A Mann-Whitney Wilcoxon test indicated that the reliability of the telemedicine app for facilitating health care services, that the ability to trust the telemedicine application to work, the lack of physical contact during a video visit being a problem, the video visits being a convenient form of healthcare delivery, the visits on the telehealth system are the same as in-person visits, and that continued use of telehealth services in the future was greater for mental healthcare providers than non-mental healthcare providers (p < .05). Conclusions Looking forward, we expect to see more extensive studies involving providers from various regions and the implementation of additional approaches to enhance their experiences.

Introduction: Diabetic retinopathy (a diabetes complication that affects eyes) is one of the leading causes of blindness and low vision in the US. More than 90% of vision loss caused by diabetes can be prevented by a routine annual eye examination and early treatment. However, data shows that about half of people with diabetes in the US do not receive the recommended annual eye screening exams, and there is a scarcity of literature assessing the specific role of health insurance. This study aimed to assess if having health insurance had an impact on eye screening. Methods: The nationally representative 2021 Behavioral Risk Factor Surveillance System (BRFSS) was used to examine having an eye exam within the past year among individuals 18 years of age and older who self-reported living with diabetes. Those who reported having some form of health insurance were considered as having access to health insurance and those who reported no, or don’t know or refused or missing responses were considered as having no access to insurance. Meeting the national recommendations of having a dilated eye exam within the past year was the primary outcome of interest. Those who reported having an eye exam within the past year were considered as meeting the recommendations and who reported no, or don’t know or more than one year ago were considered as not having the recommended service. Other independent variables were defined according to the Andersen Model of Healthcare Services Utilization (predisposing factors, enabling factors, need factors, environment, and health behavior. Chi-square analysis and multivariable logistic regression with OR and 95% CI were used to determine the association between eye screening and health insurance adjusting for other covariates. Results and conclusions: Ninety-one percent (91.3%, 53,919) of the adults reported having some form of health insurance, as compared to 8.7%(3,697) who reported having no form of insurance coverage. Approximately 66.2% of the study population had an eye exam at least once within the past year. A higher proportion of adults who had health insurance reported having an eye exam compared to those with no health insurance (68.6 vs. 44.8%; p=0.000). Among those older than 65 years, 73.9% had eye exam as compared to 42.7% among those younger than 35 years (p=$50,000, 71% had eye exam as compared to 59.9% in those earning

Family-centered care (FCC) focuses on considering the family in planning/implementing care and is associated with increased patient satisfaction. Little is known about factors that influence FCC. Using linear mixed modeling and Generalized Estimating Equations to analyze data from a cross-sectional survey of primary care practices in Ontario, this study sought to determine whether models of primary care service delivery differ in their provision of FCC and to identify characteristics of primary care practices associated with FCC. Patient-reported scores of FCC were high, but did not differ significantly among primary care models. After accounting for patient characteristics, practice characteristics were not significantly associated with patient-reported FCC. Provider-reported scores of FCC were significantly higher in Community Health Centres than in Family Health Networks. Higher numbers of nurse practitioners and clinical services on site were associated with higher FCC scores but scores decreased as the number of family physicians at a site increased.

Family-centered care (FCC) focuses on considering the family in planning/implementing care and is associated with increased patient satisfaction. Little is known about factors that influence FCC. Using linear mixed modeling and Generalized Estimating Equations to analyze data from a cross-sectional survey of primary care practices in Ontario, this study sought to determine whether models of primary care service delivery differ in their provision of FCC and to identify characteristics of primary care practices associated with FCC. Patient-reported scores of FCC were high, but did not differ significantly among primary care models. After accounting for patient characteristics, practice characteristics were not significantly associated with patient-reported FCC. Provider-reported scores of FCC were significantly higher in Community Health Centres than in Family Health Networks. Higher numbers of nurse practitioners and clinical services on site were associated with higher FCC scores but scores decreased as the number of family physicians at a site increased.

Family-centered care (FCC) focuses on considering the family in planning/implementing care and is associated with increased patient satisfaction. Little is known about factors that influence FCC. Using linear mixed modeling and Generalized Estimating Equations to analyze data from a cross-sectional survey of primary care practices in Ontario, this study sought to determine whether models of primary care service delivery differ in their provision of FCC and to identify characteristics of primary care practices associated with FCC. Patient-reported scores of FCC were high, but did not differ significantly among primary care models. After accounting for patient characteristics, practice characteristics were not significantly associated with patient-reported FCC. Provider-reported scores of FCC were significantly higher in Community Health Centres than in Family Health Networks. Higher numbers of nurse practitioners and clinical services on site were associated with higher FCC scores but scores decreased as the number of family physicians at a site increased.

Family-centered care (FCC) focuses on considering the family in planning/implementing care and is associated with increased patient satisfaction. Little is known about factors that influence FCC. Using linear mixed modeling and Generalized Estimating Equations to analyze data from a cross-sectional survey of primary care practices in Ontario, this study sought to determine whether models of primary care service delivery differ in their provision of FCC and to identify characteristics of primary care practices associated with FCC. Patient-reported scores of FCC were high, but did not differ significantly among primary care models. After accounting for patient characteristics, practice characteristics were not significantly associated with patient-reported FCC. Provider-reported scores of FCC were significantly higher in Community Health Centres than in Family Health Networks. Higher numbers of nurse practitioners and clinical services on site were associated with higher FCC scores but scores decreased as the number of family physicians at a site increased.

Background: Ballad Health participates in the Centers for Medicare and Medicaid Services’ (CMS) Accountable Health Communities (AHC) model. The AHC model is evaluating if universal screening, referral, and navigation services for health-related social needs (HRSN) can improve outcomes and reduce unnecessary utilization and costs of health care services. To ensure the evaluation of the model has sufficient statistical power, navigation services are expected to be provided to a minimum number of individuals. The purpose of this study is to analyze the characteristics of Ballad Health’s AHC navigation services that could be modified to improve opt-in rates. Methods: The primary outcome measure was identified as whether a beneficiary contacted via telephone opted-in or –out of the navigation program. Andersen’s Behavioral Model for Health Service Use was used as the conceptual framework for selecting covariates of interest. Enabling factors were of primary interest because alternate interventions may be designed around them. Data was pulled for the time period of November 17, 2018 through February 14, 2019. Where possible, covariates were associated with data from CMS’ AHC Data Template v3.1 to accommodate replication for all AHC bridge organizations, though additional internally-collected data, which may not be available for all bridge organizations, were needed for some variables. Chi-squared tests were performed for each covariate. Results: No statistical differences were found for the primary covariates of interest. Opt-in rates by Navigator were lowest for Navigator 5 and highest for Navigator 4 (67.53% and 88.24%). Opt-in rates by weekday of decision were lowest on Thursdays and highest on Wednesdays (64.91% and 77.42%). Opt-in rates based on time of day were lowest between 8:00am and 9:59am, and highest between 12:00pm and 1:59pm (62.50% and 100%). Opt-in rates were lowest when the decision was made six days after the screening and highest when made the same day (53.57% and 83.33%). Opt-in rates were lowest when there were five weekdays between screening and navigation decision, and highest when there were three weekdays between the screening and decision (60% and 90%). Other non-process covariates of interest that were statistically significant for opt-in rates were the presence of either food, safety, or utility needs. Conclusions: Several groups had higher opt-in rates that were not statistically significant; small sample sizes may have impacted the significance of these differences. For example, opt-in rates were higher when made the same day as the screening than when made one day after (83.33% and 74.79%). However, only 18 beneficiary decisions were made on the same day, while 119 were made one day after. Increasing the number of same-day phone call attempts may be a method to improve opt-in rates. Importantly, date and time data for contact attempts before a beneficiary decides to opt-in or opt-out were unavailable as of the time of the analysis. These data are captured and will be added to the analysis when available, which could provide more insight into whether a beneficiary is more likely to opt-in or opt-out.

Background: Ballad Health participates in the Centers for Medicare and Medicaid Services’ (CMS) Accountable Health Communities (AHC) model. The AHC model is evaluating if universal screening, referral, and navigation services for health-related social needs (HRSN) can improve outcomes and reduce unnecessary utilization and costs of health care services. To ensure the evaluation of the model has sufficient statistical power, navigation services are expected to be provided to a minimum number of individuals. The purpose of this study is to analyze the characteristics of Ballad Health’s AHC navigation services that could be modified to improve opt-in rates. Methods: The primary outcome measure was identified as whether a beneficiary contacted via telephone opted-in or –out of the navigation program. Andersen’s Behavioral Model for Health Service Use was used as the conceptual framework for selecting covariates of interest. Enabling factors were of primary interest because alternate interventions may be designed around them. Data was pulled for the time period of November 17, 2018 through February 14, 2019. Where possible, covariates were associated with data from CMS’ AHC Data Template v3.1 to accommodate replication for all AHC bridge organizations, though additional internally-collected data, which may not be available for all bridge organizations, were needed for some variables. Chi-squared tests were performed for each covariate. Results: No statistical differences were found for the primary covariates of interest. Opt-in rates by Navigator were lowest for Navigator 5 and highest for Navigator 4 (67.53% and 88.24%). Opt-in rates by weekday of decision were lowest on Thursdays and highest on Wednesdays (64.91% and 77.42%). Opt-in rates based on time of day were lowest between 8:00am and 9:59am, and highest between 12:00pm and 1:59pm (62.50% and 100%). Opt-in rates were lowest when the decision was made six days after the screening and highest when made the same day (53.57% and 83.33%). Opt-in rates were lowest when there were five weekdays between screening and navigation decision, and highest when there were three weekdays between the screening and decision (60% and 90%). Other non-process covariates of interest that were statistically significant for opt-in rates were the presence of either food, safety, or utility needs. Conclusions: Several groups had higher opt-in rates that were not statistically significant; small sample sizes may have impacted the significance of these differences. For example, opt-in rates were higher when made the same day as the screening than when made one day after (83.33% and 74.79%). However, only 18 beneficiary decisions were made on the same day, while 119 were made one day after. Increasing the number of same-day phone call attempts may be a method to improve opt-in rates. Importantly, date and time data for contact attempts before a beneficiary decides to opt-in or opt-out were unavailable as of the time of the analysis. These data are captured and will be added to the analysis when available, which could provide more insight into whether a beneficiary is more likely to opt-in or opt-out.

Dissertation (Ph.D.)--University of South Florida, 2009. / Title from PDF of title page. Document formatted into pages; contains 123 pages. Includes vita. Includes bibliographical references.

Distinct dimensions of quality vary in importance depending on the context in which quality assurance effort takes place. Working through the process of quality assurance and continuous quality improvement may create an environment for transforming the health services and achieving positive health outcome goals. Substantial improvements have been observed in the coverage and access to health service delivery in Ethiopia. However, the quality of care has been lagging behind. The purpose of this study was to develop guidelines for care to enhance quality health services at Gindabarat District, Oromia Regional State, Ethiopia. The study followed a mixed method approach. The participants were purposively included in the study based on their availability, from a total of 7 government health facilities from the Gindabarat District. Self-administered questionnaires and interviews were used to collect data from samples of 127 health care workers and 29 health facilities managers, respectively. Collected data were analysed using SPSS Version 24 and ATLAS TI 8 respectively. The results revealed barriers towards quality health services delivery which were lack of equipment and supplies (inadequacy of blocks, materials, medical equipment; lack of sustainable supplies of drugs); inadequate human resources (low retention of skilled staff; absence of focal person assigned for quality improvement; shortages of health workers); absence of standard operating procedures (protocols, guidelines and manuals); and dissatisfaction of health care providers with services provided at the District. Based on the results, guidelines were developed to enhance quality health care delivery. The reccommendations were aimed at improvement approaches at all levels of health service delivery. / Health Studies / D.Litt. et Phil. (Health Studies)