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Indiana University-Purdue University Indianapolis (IUPUI) / Depression is the most commonly occurring mental illness the world over. It poses a significant health and economic burden across the individual and community. Not all occurrences of depression require the same level of treatment. However, identifying patients in need of advanced care has been challenging and presents a significant bottleneck in providing care. We developed a knowledge-driven depression taxonomy comprised of features representing clinical, behavioral, and social determinants of health (SDH) that inform the onset, progression, and outcome of depression. We leveraged the depression taxonomy to build decision models that predicted need for referrals across: (a) the overall patient population and (b) various high-risk populations. Decision models were built using longitudinal, clinical, and behavioral data extracted from a population of 84,317 patients seeking care at Eskenazi Health of Indianapolis, Indiana. Each decision model yielded significantly high predictive performance. However, models predicting need of treatment across high-risk populations (ROC’s of 86.31% to 94.42%) outperformed models representing the overall patient population (ROC of 78.87%). Next, we assessed the value of adding SDH into each model. For each patient population under study, we built additional decision models that incorporated a wide range of patient and aggregate-level SDH and compared their performance against the original models. Models that incorporated SDH yielded high predictive performance. However, use of SDH did not yield statistically significant performance improvements. Our efforts present significant potential to identify patients in need of advanced care using a limited number of clinical and behavioral features. However, we found no benefit to incorporating additional SDH into these models. Our methods can also be applied across other datasets in response to a wide variety of healthcare challenges.

Indiana University-Purdue University Indianapolis (IUPUI) / Healthcare industry in United States of America is facing a big paradox. Although US is a leader in the industry of medical devices, medical practices and medical researches, however there isnt enough satisfaction and quality in performance of US healthcare operations. Despite the big investments and budgets associated with US healthcare, there are big threats to US healthcare operational side, that reduces the quality of care. In this research study, a step by step Systems Engineering approach is applied to improve healthcare delivery process in an Emergency Department of a hospital located in Indianapolis, Indiana. In this study, different type of systems engineering tools and techniques are used to improve the quality of care and patients satisfaction in ED of Eskenazi hospital. Having a simulation model will help to have a better understanding of the ED process and learn more about the bottlenecks of the process. Simulation model is verified and validated using different techniques like applying extreme and moderate conditions and comparing model results with historical data. 4 different what if scenarios are proposed and tested to find out about possible LOS improvements. Additionally, those scenarios are tested in both regular and an increased patient arrival rate. The optimal selected what-if scenario can reduce the LOS by 37 minutes compared to current ED setting. Additionally, by increasing the patient arrival rate patients may stay in the ED up to 6 hours. However, with the proposed ED setting, patients will only spend an additional 106 minutes compared to the regular patient arrival rate.

BACKGROUND: Telehealth is a healthcare delivery platform that allows for clinicians to deliver care via the phone or computer. The public health restrictions associated with the Covid-19 pandemic have shown how telehealth could be used as a platform to deliver care. With state-wide stay at home orders and the associated suspension of elective medical procedures telehealth rose as an option to deliver care to patients. Prior authors described that telehealth usage increased at the start of the pandemic and then decreased once the reopening processes in several states commenced in the May to June period. Although these studies have provided valuable information regarding telehealth, many of these did not look beyond the June time frame. In addition, the implications from the range of telehealth policies remain largely unexplored. OBJECTIVE: We sought to assess policies and other drivers of telehealth use. In order to achieve this, we described the change in telehealth usage over the year of 2020, identified potential drivers of increased telehealth usage at the patient and policy level, and explored the heterogeneity of state policies. METHODS: We performed a retrospective cohort study of 417,963 de-identified individuals with healthcare visits between December 2019 to December 2020. This data was extracted from HealthJump, which contains Electronic Health Record data sourced from participating members of its network. Visits were labeled telehealth by using CPT billing codes. We explored national and state-level trends in telehealth use, as well as patient-level drivers such as demographics, medical diagnoses, and Covid-19 status. RESULTS: Telehealth usage increased at the onset of the pandemic across the nation, different age groups, and various health diagnoses. The relaxation of state policies led to a decrease in telehealth usage across the nation and individual states but was higher than pre-pandemic conditions. Telehealth was used more by those with conditions deemed “at-high-risk” for Covid-19 as well as medical specialties that were more feasible for the virtual platform. Patients who were Covid-19 positive used telehealth more in the latter part of the year. Patients who were 65 and older did use telehealth, even though it was at a lower volume than the other age group (under 65). CONCLUSION: The Covid-19 pandemic has shown how telehealth can be an effective alternative to in-person visits for medical needs that are elective or non-life-threatening. Although telehealth may not be used in the same capacity as it was during Covid-19, the results show that people are willing to use it and that looking into the future Telehealth can be implemented into the healthcare system.

Problems in healthcare are difficult to comprehend due to complexity, involvement of multiple stakeholders in decision making and fragmented structure of delivery systems. Major Problem Structuring Methods (PSMs) have been used to aid problem understanding which, in principle, can provide greater clarity to strategic problems and engage diverse decision makers using transparent representation that capture differing perceptions of problems. In reality, PSMs can be difficult in accurately representing problems, limited in highlighting improvement opportunities due to non-intuitive visual representations and requirements for facilitators and stakeholders to be experts in tools used. This research aims to address this gap by developing a framework, taking into account characteristics of healthcare delivery systems, advantages and limitations of PSMs with an aim of providing accurate and holistic representation of delivery workflow, so as to promote problem understanding in a rapid manner. The framework, termed CARE, first establishes nature of problem and a commonly agreed problem statement along with an understanding of stakeholder involvement and operating regulations. It then sets specific guidelines for data collection, representation, verification and validation from stakeholders and provides methodology for data analysis which allows facilitator insight into possible flaws in workflow. A case study approach is used to test effectiveness of CARE across two different healthcare settings, each involving a different nature of problem. Implementation of CARE leads to improved participation and ownership amongst stakeholders, ease of facilitation during individual or multidisciplinary meetings, intuitive and informative representation of workflow, minimized time and effort for implementation and minimized dependencies on learning new tools and terminologies. A post mortem indicates the positive impact of CARE on services rendered to the patients, leading to an increase in patient satisfaction and workflow efficiencies. The research concludes by noting the contributions and lessons learnt from this research for healthcare practitioners and possible future work.

Healthcare industry in United States of America is facing a big paradox. Although US is a leader in the industry of medical devices, medical practices and medical researches, however there isnt enough satisfaction and quality in performance of US healthcare operations. Despite the big investments and budgets associated with US healthcare, there are big threats to US healthcare operational side, that reduces the quality of care. In this research study, a step by step Systems Engineering approach is applied to improve healthcare delivery process in an Emergency Department of a hospital located in Indianapolis, Indiana. In this study, different type of systems engineering tools and techniques are used to improve the quality of care and patients satisfaction in ED of Eskenazi hospital. Having a simulation model will help to have a better understanding of the ED process and learn more about the bottlenecks of the process. Simulation model is verified and validated using different techniques like applying extreme and moderate conditions and comparing model results with historical data. 4 different what if scenarios are proposed and tested to find out about possible LOS improvements. Additionally, those scenarios are tested in both regular and an increased patient arrival rate. The optimal selected what-if scenario can reduce the LOS by 37 minutes compared to current ED setting. Additionally, by increasing the patient arrival rate patients may stay in the ED up to 6 hours. However, with the proposed ED setting, patients will only spend an additional 106 minutes compared to the regular patient arrival rate.<br>

The multi-cultural demographics of those who are diagnosed with Alzheimer’s disease should be closely examined. From a designer’s standpoint, its cultural traits can foster positive behaviors that lead to better quality of life for patients and caregivers. A patient-centered approach in design was explored in order to shape community-based care that empowers (1) individuality in care services, (2) interpersonal connection in caregiver–patient activities, and (3) a communal culture of being valued via humanitarian approaches.

Chronic disease is rising globally, but LMICs may require novel approaches to management suited to a low-resource setting. Private health care providers in LMICs have experimented and developed new models for organizing, financing, and delivering care. This thesis examines some of the innovations that have emerged in LMICs to manage chronic disease. Using a common performance measurement framework and drawing from a database of over 1200 innovative health programs, I identify and evaluate 46 programs addressing chronic disease in LMICs. I then go on to identify, innovative practices used by the subset of 19 diabetes focussed programs and catalogue them according to the Chronic Care Model (CCM). Delivery system design is the most commonly used domain of the CCM, which even earlier has shown to have great potential to impact health outcomes. Few of the identified innovations may also have the potential for ‘Reverse innovation’ in high income countries.

Chronic disease is rising globally, but LMICs may require novel approaches to management suited to a low-resource setting. Private health care providers in LMICs have experimented and developed new models for organizing, financing, and delivering care. This thesis examines some of the innovations that have emerged in LMICs to manage chronic disease. Using a common performance measurement framework and drawing from a database of over 1200 innovative health programs, I identify and evaluate 46 programs addressing chronic disease in LMICs. I then go on to identify, innovative practices used by the subset of 19 diabetes focussed programs and catalogue them according to the Chronic Care Model (CCM). Delivery system design is the most commonly used domain of the CCM, which even earlier has shown to have great potential to impact health outcomes. Few of the identified innovations may also have the potential for ‘Reverse innovation’ in high income countries.

The implementation of Electronic Health Records (EHR) has improved medical documentation in terms of accuracy, team communication, and ease of ordering tests and prescriptions; however, charting in an EHR strains the provider/patient relationship and contributes to physician burnout. Medical scribes are a promising potential solution to these problems. Our study aims to demonstrate that implementation of scribes into a medical residency program positively affects provider/patient satisfaction and improves quality and efficiency of EHR documentation. Our study evaluated the effectiveness and utility of scribes in a residency training program utilizing the established implementation framework “RE-AIM,” or Reach, Effectiveness, Adoption, Implementation (quality), and Maintenance. During the study’s initial “Training Phase,” 11 first and second-year Family Medicine residents conducted scribe-facilitated patient visits. Patient and provider satisfaction ratings were collected, note quality was evaluated, and time to note closure was measured. During the subsequent “Choice Phase,” residents were given the option of whether to utilize scribes, and the same data measures were collected. Resident satisfaction ratings during the Training Phase showed an average score of 6.03 (on a 1-7 scale where “7” = “strongly agree” with positive statements), and a pilot sample of 9 patients showed an average patient satisfaction rating of 4.77 (on a 1-5 scale where “5” = “strongly agree” with positive statements). Scribe-facilitated notes coded for quality had an average score of 3.375 (on a 1-5 scale where 5 is “extremely” high quality). Finally, residents’ average time to note closure was decreased by more than 8 hours in scribe-facilitated visits. During the Choice Phase, all 11 participating residents requested scribe-facilitated visits, again with very high patient satisfaction scores (4.67 on a 1-5 scale) as well as high clinician satisfaction scores (6.06 on a 1-7 scale). Choice Phase note quality and note-closure time are currently being assessed. These results demonstrate that scribes improve clinician and patient satisfaction, as well as quality and efficiency of EHR documentation. Limitations include a small sample size of clinicians and patients. Further research is needed with larger sample sizes to determine whether scribes in a medical residency program represent a sustainable and effective intervention.