abstract: The analysis of clinical workflow offers many challenges to clinical stakeholders and researchers, especially in environments characterized by dynamic and concurrent processes. Workflow analysis in such environments is essential for monitoring performance and finding bottlenecks and sources of error. Clinical workflow analysis has been enhanced with the inclusion of modern technologies. One such intervention is automated location tracking which is a system that detects the movement of clinicians and equipment. Utilizing the data produced from automated location tracking technologies can lead to the development of novel workflow analytics that can be used to complement more traditional approaches such as ethnography and grounded-theory based qualitative methods. The goals of this research are to: (i) develop a series of analytic techniques to derive deeper workflow-related insight in an emergency department setting, (ii) overlay data from disparate sources (quantitative and qualitative) to develop strategies that facilitate workflow redesign, and (iii) incorporate visual analytics methods to improve the targeted visual feedback received by providers based on the findings. The overarching purpose is to create a framework to demonstrate the utility of automated location tracking data used in conjunction with clinical data like EHR logs and its vital role in the future of clinical workflow analysis/analytics. This document is categorized based on two primary aims of the research. The first aim deals with the use of automated location tracking data to develop a novel methodological/exploratory framework for clinical workflow. The second aim is to overlay the quantitative data generated from the previous aim on data from qualitative observation and shadowing studies (mixed methods) to develop a deeper view of clinical workflow that can be used to facilitate workflow redesign. The final sections of the document speculate on the direction of this work where the potential of this research in the creation of fully integrated clinical environments i.e. environments with state-of-the-art location tracking and other data collection mechanisms, is discussed. The main purpose of this research is to demonstrate ways by which clinical processes can be continuously monitored allowing for proactive adaptations in the face of technological and process changes to minimize any negative impact on the quality of patient care and provider satisfaction. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2018

The purpose of this study is to investigate the effectiveness of virtual peer-to-peer (P2P) workgroups as a platform for long-term collaboration in healthcare. Virtual peer-to-peer workgroups were developed and piloted by the Michigan Value Collaborative to increase knowledge and collaboration between providers across Michigan. The workgroups were designed to address barriers to change and long-term collaboration by allowing participants to share their improvement journey and provide feedback and ideas for improvement in a highly accessible platform. The pilot workgroups focused on heart failure readmission reduction initiatives as it is a much scrutinized metric and is penalized by public and private payers. Data on the workgroups were collected using pre and post-workgroup surveys filled out by participants. The results reveal that virtual peer-to- peer workgroups are effective in increasing knowledge and collaboration in the short term, but more study is required to judge their long term effectiveness in improving care at participating providers. Virtual peer-to-peer workgroups can serve as a foundation for increasing regional collaboration in healthcare as it is a very simple platform that does not require major financial or resource commitments.

abstract: Parkinson’s disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The pathology for PD is difficult and expensive. Furthermore, it depends on patient diaries and the neurologist’s subjective assessment of clinical scales. Objective, accurate, and continuous patient monitoring have become possible with the advancement in mobile and portable equipment. Consequently, a significant amount of work has been done to explore new cost-effective and subjective assessment methods or PD symptoms. For example, smart technologies, such as wearable sensors and optical motion capturing systems, have been used to analyze the symptoms of a PD patient to assess their disease progression and even to detect signs in their nascent stage for early diagnosis of PD. This review focuses on the use of modern equipment for PD applications that were developed in the last decade. Four significant fields of research were identified: Assistance diagnosis, Prognosis or Monitoring of Symptoms and their Severity, Predicting Response to Treatment, and Assistance to Therapy or Rehabilitation. This study reviews the papers published between January 2008 and December 2018 in the following four databases: Pubmed Central, Science Direct, IEEE Xplore and MDPI. After removing unrelated articles, ones published in languages other than English, duplicate entries and other articles that did not fulfill the selection criteria, 778 papers were manually investigated and included in this review. A general overview of PD applications, devices used and aspects monitored for PD management is provided in this systematic review. / Dissertation/Thesis / Masters Thesis Computer Engineering 2019

African Americans are adversely affected by Type 2 diabetes at a greater rate than their European American counterparts; however, research on the effects of Type 2 diabetes on African Americans is limited. Lifestyle modifications that include the incorporation of physical activity and dietary changes can help patients with Type 2 diabetes better manage their disease and improve their overall quality of health. The purpose of this phenomenological study was to explore the experiences of African Americans with Type 2 diabetes who incorporated these self-management behaviors, discerning if they had improved health and quality of life. The self-efficacy framework was applied to understand the research problem and interpret study results. An in-depth interview protocol was used to explore participants' perspectives and lived experiences in disease management. Interview transcripts and participant data were analyzed using a thematic-content-analysis approach. According to study findings, participants experienced physical activity and dietary changes, and their self-efficacy directly correlated with their experience of positive changes in their health status. Providing programs that support the adoption of healthy lifestyles for this population will help mitigate the later effects of diabetic complications. Implications for social change include the provision of strategies that will help in formulating programs and policies that will reduce diabetic complications and deaths due to complications.

The purpose of this research study was to determine: (1) the selected job-required activities and (2) the duty performance effectiveness associated with those activities as perceived by Medical Service Corps officers in the United States Army Medical Department who had received a Master's deg / acase@tulane.edu

acase@tulane.edu

acase@tulane.edu

Cost and production functions of US nursing homes were estimated using stochastic frontier approaches based on a 7-year panel data. Efficiency predictions from estimated frontier were then used to identify potential determinants of. This research also evaluated the effects of 1997 Balanced Budget Act on nursing home efficiencies. HCRIS-SNF was the primary database for this study and the final analysis sample size was 45,430 cost reports from 6,490 freestanding nursing homes. Total staff hours per resident-day was included in the frontier models to account for quality difference among nursing homes. Log-linear and translog functional forms were both employed in this study. A TOBIT regression model was estimated in the 2nd stage regression in addition to OLS regressions. Results from this study suggested translog functional form fits the empirical data better than the log-linear functional forms and time varying decay model is better than time invariant model. This study found that over the years US nursing homes operated at 75.4% cost inefficiency and 11.7% technical inefficiency on the average. Significant determinants of efficiency included ownership, chain affiliation, MSA, Certificate of Need/Moratoria regulation, percentage of Medicare patient days, geographic region and fiscal years. It appeared that economies of scale doesn't exist in US nursing home industry. The 1997 BBA PPS didn't seem to affect either technical or cost efficiency as of 2002. The author did observe a significant structural shift of the functions in post-BBA era / acase@tulane.edu

acase@tulane.edu

acase@tulane.edu