Browsing by Subject "Continuity of Patient Care"
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Item Cancer survivorship care: instructions not included!(2019-08-09) Sadeghi, NavidItem Consult a sickle cell expert: how to apply NIH guidelines in caring for adult sickle cell patients(2017-01-20) Nero, AleciaItem Designing an Audit and Feedback System to Drive Handoff Redesign and Implementation(2021-03-18) Dao, Anthony Quang; Reed, W. Gary; Greilich, Philip; Lynch, IsaacBACKGROUND: Following the handoff efficacy pilot that was implemented 6 quarters ago at Clements University Hospital, a new measurement system needs to be implemented for preparation of a diffusion pilot to 4-6 additional units. At present there is no such system to monitor and provide feedback to key stakeholders. An Epic based clarity report was identified as a potential measurement system and this project revolved around the feasibility, acceptability, and appropriateness of implementing such a system. A survey was sent out to identify top handoff outcomes to be included in the system and to assess the feasibility of the system. From preliminary results, it was understood that it is possible to successfully implement an acceptable, appropriate, and feasible measurement system. LOCAL PROBLEM: Information loss during care transfers, or "handoffs", can disrupt care coordination and lead to adverse events, especially in high risk, error prone environments like the perioperative setting. Clements University Hospital piloted the redesign and implementation of a structured handoff process to Enhance Communication for Handoffs from the Operating room to the Intensive Care Unit (ECHO-ICU) to improve team-based communication and care. As a result of this successful efficacy pilot, an implementation science-based approach is being taken to prepare for widespread adoption of inpatient handoff redesign. This requires the development of an acceptable and feasible audit and feedback system to support the work led by an inter-professional, unit-based change team guided by institutional subject matter experts. Previous attempts to relay feedback to the original units from the efficacy pilot were unresponsive and slow, leading to disengagement of the stakeholders. This project will attempt to make this process easier, timelier, and scalable. The aim of this project is to reduce the time it takes to perform and Audit and Feedback by 50% by May 2021. METHODS: An initial literature review was performed to identify candidate important outcome measures related to successful handoffs. To assess acceptability, the primary stakeholders were surveyed on what they identified as the most important outcome measures related to handoffs. Feasibility was assessed by determining end users' personal motivation level for entering critical data into the electronic medical record and the complexity of generating an automated report by data specialists from Epic, enterprise, and clinical data registries. Data was collected using multiple methods, including a REDCap survey, small group discussions, and individual interviews. The top three voted upon measures will be added as new data fields into Epic for data collection. RESULTS: The outcomes deemed most important by the survey were all team members present during handoff, the receiving team feeling capable of meeting patient needs, and unanticipated postoperative events. Using these measures of meaning, a prototype dashboard audit and feedback system was designed for use in future efforts. By using participatory design, usability was addressed by focusing on feasibility, acceptability, and fidelity. The guidance team will work with the unit-based change team for handoff redesign and implementation of this audit and feedback. Initially, the feedback will occur quarterly, but each unit will determine their preferred feedback period. CONCLUSIONS: The next steps of this project will be to pilot this prototype with other handoff redesign efforts to collect usability data and assess whether the prototype remains feasible, acceptable, and fidelity. This prototype hopes to align with the University Hospital handoff diffusion pilot within 4 to 6 clinical units. Acceptability and feasibility are leading indicators of successful of widespread adoption, penetration, and sustainability. These latter implementation measure will be applied to future work from this project team.Item Development of the Liang Handover Assessment Tool for Simulation (L-HATS)(2020-05-01T05:00:00.000Z) Liang, Tyler; Greilich, Philip; Phelps, Eleanor; Reed, W. GaryINTRODUCTION: Clinical handovers are critical to patient safety and outcomes. Handover simulation prepares healthcare students for handoffs in the clinical setting upon graduation. UT Southwestern has developed a longitudinal handover educational curriculum in which student handovers will be assessed. Although valid and reliable tools exist for assessing clinical handovers, assessment tools adapted for the undergraduate simulation environment currently do not exist. Our objective was to develop a reliable and valid assessment tool that could be used by scholarly healthcare students to assess undergraduate simulated handovers throughout the longitudinal handover education curriculum. METHODS: A literature review was conducted to identify critical elements of high-quality, effective handovers. Following the tool's creation, we underwent several PDSA cycles to optimize the tool for medical student evaluation and ease of grading. Grader inclusion criteria were students who had completed the transition to clerkship (T2C) handover activity. A training curriculum was developed to train graders on proper use of the tool and to promote reliable grading with the tool. 62 pre-clinical student handovers were conducted in the simulation setting and recorded. The handovers were stratified into three levels (low, intermediate, and high quality), and 10 handovers were selected from each of the three levels for grading (30 handovers total). Each handover was scored by four clerkship medical students "graders". Two-way random effects intra-class correlation coefficients (ICC) were used to establish inter-rater reliability and inter-rater agreement among graders using the tool. Three external handover experts were used to establish the tool's validity using face validity. RESULTS: The product of this project is Liang Handover Assessment Tool for Simulation (L-HATS) which evaluated three domains: handover content, handover process, and language with a maximum score of 28. Two-way random effects ICC for agreement was 0.804, 95% CI [0.601, 0.906]. Two-way random effects ICC for reliability was 0.866, 95% CI [0.765, 0.930]. Three external handover experts have sufficiently validated the tool. CONCLUSIONS: The L-HATS had good to excellent inter-rater reliability and agreement. The L-HATS is the first reliable and valid handover assessment tool used for undergraduate simulation education. By using a two-way random effects model, the results suggest that the tool can be used in settings outside of the T2C handover simulation activity. Having good to excellent absolute agreement suggests that the tool is suitable for assigning grades. Future studies include comparing faculty vs student grading of handovers as well as evaluating the tool in the clinical setting.Item Effect of Fragmentation of Cancer Care on Treatment Use and Survival in Hepatocellular Carcinoma(2020-05-01T05:00:00.000Z) Karbhari, Nishika; Yopp, Adam; Mansour, John; Porembka, Matthew R.BACKGROUND: Fragmentation of care (FC) refers to treatment received at multiple facilities. Implications of FC include increased health care costs and amplification of existing healthcare disparities. This study aimed to identify patient and hospital-level factors associated with FC and analyze the effect of FC on patient outcome measures (overall survival and time to treatment). OBJECTIVE: Fragmented care in HCC patients is associated with worse overall survival and increased time to treatment compared to patients receiving non-fragmented care. METHODS: The Texas Cancer Registry (TCR) was queried from 2004-2015 for a 12-year study span. Patient- and hospital-level factors were characterized within 2 groups: patients receiving fragmented care (FC) and those receiving non-fragmented care (NFC). Cox proportional hazards regression models were used to identify those factors that were independently and significantly associated with overall survival and time to treatment. Kaplan-Meier curves were generated to evaluate differences in overall survival between the FC and NFC groups, as well as between every type of transition within the FC group (stratified on the basis of safety net hospital status or volume status). All statistical analyses were performed with SPSS. RESULTS: Of our cohort (n = 4329), 72.6% received NFC, and 27.4% received FC. In comparison to patients receiving NFC, patients receiving FC had larger median tumor sizes at diagnosis (≥4 cm, 52.6% vs 35.2%; p < .001). NFC patients also tended to present with regional or metastatic disease (35.9% vs 26.7%; P < .001). A subset analysis of patients with localized stage HCC who received curative therapy showed that FC was associated with decreased odds of curative therapy (odds ratio, 0.83; 95% confidence interval [CI], 0.7-0.9). In this subgroup analysis, FC was associated with worse OS (median survival, 67 vs 43 months; HR, 1.2; 95% CI, 1.0-1.4) and increased TTT (HR, 0.74; 95% CI, 0.7-0.8). Ultimately, in our global cohort, FC was associated with worse OS (hazard ratio [HR], 1.14; 95% CI, 1.05-1.24) and increased TTT (HR, 0.76; 95% CI, 0.7-0.8). CONCLUSION: Patients receiving FC had worse OS and increased TTT compared to patients receiving NFC. Several patient and hospital-level factors were found to be associated with FC, including age, insurance, non-safety net hospital status, accreditation, and disease stage. This work has implications for encouraging initiatives geared toward increasing care coordination, especially when managing cancer. Future work may aim to elucidate the reasons for the associations described and delineate steps by which to mitigate FC in the context of these factors.Item Improving Teamwork Competencies and Patient Handovers of Students in the Emergency Medicine Clinical Learning Environment(2024-05) Lokesh, Nidhish; Reed, W. Gary; Greilich, Philip; Pierce, Ava E.BACKGROUND: Communication failures contribute to significant teamwork failures causing adverse events for patients and providers, especially during patient handovers when providers transition care of patients to each other. Teamwork education has been shown to improve knowledge, skills, and communication in prelicensure learners. Despite knowledge of the problem and potential solutions, as well as requirements and recommendations by national medical accreditation and oversight agencies, there exists a gap in standardized teamwork education and assessment. The Emergency Department is a setting rife with inherent barriers to teamwork with a high frequency of patient handovers. LOCAL PROBLEM: At UT Southwestern, students used to have limited opportunities to improve teamwork in structured ways during their time on the clinical wards. In response, the institution developed and is implementing an educational quality enhancement plan - TeamFIRST - with the goal of developing a competency-based teamwork education (CBTE) strategy for students that is progressive, interprofessional, and continuous through the pre-clerkship, clerkship, and post-clerkship phases of medical school. Module 4 out of the 5 modules TeamFIRST developed focuses on improving teamwork competencies specifically in the clinical learning environment, i.e. during clinical rotations in most students' second years and beyond. This includes the Emergency Medicine clinical rotation, which most students undergo at Parkland Memorial Hospital, the busiest emergency department in the nation, as well as at other local Emergency Departments like Clements University Hospital and Presbyterian Dallas. Until now, the Emergency Medicine clinical rotation at UT Southwestern did not have any formal handover or teamwork education, despite being the clinical setting in which teamwork and handovers arguably provide the most value. METHODS: Continuous Quality Improvement (QI) and Implementation Science tools and methodologies were used in the study of the current state of handovers in the ED and in the design of interventions to implement effective handovers. Define-Measure-Analyze-Design-Verify methodology was used to iterate our interventions. Interviews with stakeholders were conducted to determine critical needs, learn about the main drivers for intervention, and map the current state of the ED clerkship rotation so that a suitable educational module could be developed. These stakeholders mainly included faculty, course directors, residents, and students in the Emergency Medicine rotation as well as members of TeamFIRST. Shared requirements from stakeholders included focusing on improving handovers, limiting time commitment due to already busy schedules, and mixing virtual with in-person education. Information was also gathered on the state of different handover types in the ED to design assessment tools that captured the critical components. TeamFIRST identified nine of the twelve Teamwork Competencies - Structured Communication, Closed Loop Communication, Asking Clarifying Questions, Sharing Unique Information, Mutual Trust, Team Mental Models, Mutual Performance Monitoring, Obstacles to Teamwork, and Psychological Safety - for the Module 4 interventions to address. Working in concert with TeamFIRST and the Emergency Medicine stakeholders, we developed a teamwork education curriculum that integrated into the existing Emergency Medicine clerkship rotation and focused specifically on improving patient handovers. Each teamwork competency was explored to differing degrees among the spectrum of inform, demonstrate, practice, and feedback. We selected various process, outcome, and balancing measures such as impact (effectiveness), fidelity of activities, acceptability and appropriateness, and feasibility. Impact of the curriculum was measured by assessing students' knowledge, confidence in skills, and attitudes on the teamwork competencies. Both quantitative and qualitative data was collected. Statistical methods such as Z test of proportion and Mann-Whitney U test were used to analyze pre- and post- data to determine any significant changes. INTERVENTIONS: The teamwork curriculum initially designed for the Emergency Medicine clerkship rotation (the "test" phase, designated "Curriculum 1.0") had three main aspects: a pre-orientation, asynchronous, virtual educational module on teamwork and handovers, integrated handover practice and assessment throughout the rotation, integrated teamwork participation/observation, reflection, and debriefing during the rotation. The pre-orientation module was designed with a pre-assessment to determine students' capacities before being exposed to the material and a post-assessment to measure changes in knowledge and receive feedback after going through the didactic curriculum that covered the teamwork competencies and dedicated a full section to patient handovers. The handover practice was scattered throughout teaching shifts, simulation center cases and a dedicated handover station, and while working on regular emergency department shifts with accompanying assessment tools made to allow residents and faculty to evaluate student handovers and provide learners feedback. Lastly, students participated in and observed teamwork instances throughout their rotation and were encouraged to note these experiences down in a Teamwork Competency Journal so they could reflect and debrief on them in a group session late in the rotation. Finally, an end-of-rotation assessment was administered to capture changes in knowledge, skills, and attitudes, as well as feedback on acceptability, appropriateness, and feasibility. Whereas feasibility data were derived from the qualitative feedback, fidelity to the learning activities were assessed quantitatively. These interventions were first tested with a non-representative student sample outside of the EM rotation at the end of the summer 2020 and during field tests in Spring 2021 to improve the process and optimize the interventions. The official, representative test within the clerkship, "Curriculum 1.0", began in June 2021 and ran through March 2023 (22 months total). "Curriculum 2.0", the more streamlined version, is our pilot phase, and has been running from April 2023 through the present. RESULTS: We had 124 students participate in the Curriculum 1.0 test over 13 rotation blocks and collected qualitative and quantitative data on acceptability, appropriateness, fidelity, feasibility, and impact. So far, the curriculum has shown to be effective in improving knowledge (significant in 5/8 categories, p<0.05) and confidence in teamwork skills (significant in 11/11 categories, p<0.05). Also, students have deemed the curriculum acceptable and appropriate (all average ratings >4/5). However, some learning activities were deemed less feasible, and the fidelity (completion as intended) of different activities was low (48% completion or less). Feedback was generally positive, with common themes being that the handover education and practice were useful and relevant, the teamwork debrief was excellent, and the course was unique. Negative feedback commonly addressed a lack of clarity in communication about the curriculum requirements and the need for more active student roles. CONCLUSION: Overall, the impact and acceptability/appropriateness of Curriculum 1.0 were high, feasibility of the curriculum was moderate, and fidelity was low. Some of the key takeaways include that our stakeholders found the education to be effective and valuable, a combination of asynchronous and synchronous learning seemed the most feasible and acceptable, and that the time pressures on our EM residents and faculty are high. Going forward, we will continue to pilot the streamlined "Curriculum 2.0", which has already shown to be more feasible and sustainable, to improve the experience for learners and instructors, improve data collection, and focus on getting students more practice on patient handovers.Item Improving the HIV care continuum in 2021(2021-06-25) Chow, JeremyItem Optimizating and Diffusing a Handover Behavioral Assessment Tool for Simulation(2021-03-18) Chen, Rodney; Reed, W. Gary; Greilich, Philip; Phelps, EleanorINTRODUCTION: With multiple simulated and clinical scenarios included in the ongoing Quality Enhancement Plan (QEP), a standardized approach to assessing and trending handover quality across class years could quantify the improvements established through the QEP. This study assesses the utility of the Liang Handover Assessment Tool for Simulation (L-HATS), a valid and reliable behavioral assessment tool tested during the transition to clerkship (T2C) handover module. Here, we use the L-HATS to assess handovers delivered during residency essentials (RE) and COVID-19 telehealth courses, checking for tool reliability in settings other than T2C. In cases where we find the tool to be less reliable, we optimize the L-HATS by improving the observer training course. The study aim is to confirm tool reliability of ICC>0.75, consistent with levels of reliability found during testing in the T2C module. METHODS: We select volunteer observers from a group of medical students who had completed the T2C course, with each observer assigned a set of videos to score for each activity. The primary outcome measure for this study is the two-way random effects ICC, which represents tool inter-rater reliability in each novel activity. An ICC>0.75 is considered good reliability, an ICC 0.5-0.75 is considered moderate reliability, and an ICC<0.5 is considered poor reliability. As the volunteer observer training improves across activities, we assess for observers' intra-rater reliability. Intra-rater reliability is assessed along the same scale used for inter-rater reliability. RESULTS: RE inter-rater reliability was 0.561 [0.167, 0.953], with each of six observers scoring four videos. COVID-19 telehealth inter-rater reliability was 0.644 [0.244, 0.964], with five observers each scoring four videos. The intra-rater reliability calculated for the telehealth course ranged from 0.105 [-0.361, 0.863] to 0.667 [0.020, 0.971]. CONCLUSION: This study demonstrates moderate levels of reliability in both the RE and telehealth courses. However, neither novel activity could match the reliability scores calculated during original L-HATS testing, suggesting that the tool is less reliable in settings outside of the T2C course. Future studies might increase the number of graded videos per handover activity, to narrow the confidence intervals found in the present study. Moreover, we find that a universally flexible assessment tool is difficult to design, suggesting that each new learning activity may require a uniquely tailored behavioral assessment tool.Item Reducing Patient No-Show Rates in Diabetes Clinic(2022-05) Jafri, Farzan Haider; Reed, W. Gary; Phelps, Eleanor; Gunasekaran, UmaBACKGROUND: Patients missing scheduled appointments, or no-shows, is a pervasive issue across outpatient clinics. The estimated no-show rate among primary care clinics is estimated to be between 14% and 50% (Daggy, Lawley et al. 2010). In addition, no-shows are estimated to cost the US healthcare system $150 billion a year (Toland 2013). At many clinics no-shows have necessitated overbooking clinic slots to maintain efficiency (Muthuraman and Lawley 2008). However, patient no-shows themselves and the overbooking that no-shows necessitate causes problems for both the patient and provider. LOCAL PROBLEM: No-show rates have a number of adverse effects on the clinic, including at the Parkland Diabetes Clinic in Dallas, TX. This leads to longer wait times when all patients show, patient/provider/staff stress and frustration, and reduced clinical efficiency. No-shows and late cancellations can also lead to reduced patient access to care and potential increase in disease progression risk for those patients who fail to receive follow-up care. METHODS: This project used the PDSA cycle from quality improvement methodology. We started by analyzing the current situation at the diabetes clinic to determine the baseline no-show rate and the reasons for patient no-shows. Baseline data on no-shows were provided by Dr. Gunasekaran and Miriam Gomez-Wakeling; data was analyzed by Farzan Jafri. The scheduling process was mapped in an effort to identify inefficiencies in the scheduling process. Phone calls were then conducted with patients who no-showed in which a survey helped pinpoint reasons for no-shows. Using the process map and survey data, we brainstormed interventions to target root causes of no-shows at the clinic. PLANNED OR ACTUAL INTERVENTIONS: Our first intervention is ensuring that every patient receives a phone call reminder for their appointment. Our second intervention is limiting the degree to which the Patient Access Center, a call center, handles scheduling for the Diabetes clinic. RESULTS: Interventions were implemented in August 2020, and subsequent data collected from November 2020 to October 2021 was analyzed to determine changes in the no-show rate. The average no-show rate during this post-intervention period was ~22.2% ± 2.50 (t-test, p <0.05), a significant decrease from the baseline rate of ~31.9% ± 2.19. We predict this reduction will result in more consistent follow-up care, less risk of disease progression, and increased clinical efficiency. Our next step will be to transition our interventions into long-term sustainable solutions to maintain the lower no-show rate. CONCLUSIONS: Our project demonstrates that by following quality improvement methodology and the PDSA cycle, root causes for system inefficiencies can be targeted with site specific interventions. With support from leadership and buy-in from staff, these interventions can go on to positively impact the main problem being studied, or in our case the high no-show rate at the Parkland Diabetes clinic. While our specific interventions may not apply to every clinical context, the methods employed in this study can certainly be reproduced to target high no-show rates at other outpatient centers.Item Transitions of care in cystic fibrosis(2021-06-11) Cohen, LeahItem Transitions of care: the missing links(2016-01-08) Thomas, Abey K.Item Using Ethnography to Capture Learner Experience in Handover Simulation Modules(2022-05) Jacob, Benjamin Richard; Reed, W. Gary; Greilich, Philip; Phelps, EleanorBACKGROUND: Patient handovers, frequent, diverse, and integral parts of modern medical practice, involve the transfer of patient responsibility from one team of providers to another.1 This transition of care is often fragmented and has been shown to cause various adverse events, including patient injury, medication errors, and lengthened hospital stays.2-4 LOCAL PROBLEM: As simulation-based activities have increased in medical schools across the nation, an accompanying need to understand the learner experience has developed.5,6 UTSW has incorporated simulation-based learning with the Quality Enhancement Plan (QEP) to teach medical and health professions students team based communication. The aim of this study was to characterize learner attitudes toward simulation education during two simulation-based modules and to determine critical-to-quality elements of these courses through focused ethnography. METHODS: We describe a focused ethnographic study of two simulation-based modules of handover education using direct participant observation. The observers, medical students, and physician assistant student participant of these modules were asked to provide reflective summaries of their experiences during the simulation, including a description of what happened, attitudes about the experience, and reflections on potential improvement. Using qualitative analysis software, these ethnographic summaries were coded, and major themes were identified These themes were subsequently used to develop critical elements of the simulation activity in a Critical to Quality (CTQ) tree. RESULTS: Our analysis showed that the handover-simulation modules were regarded as generally both acceptable and appropriate. Coding of the ethnographic summaries clarified the major proponents of and deterrents to acceptability (Figure 2). Our analysis determined five components for a quality experience: organization, safety/security, engagement, reinforcement, and standardization. Out of the five critical to quality elements we identified, all five needs were described and confirmed in two concomitant focus group analyses of handover-simulation module participants, further validating an ethnographic approach in this context. CONCLUSION: Ethnographic research methods are an efficient and effective way to characterize learner attitudes and experiences in simulation education. Focused ethnography has identified several significant targets for improving the Safe Patient Handover simulation.