Pre-Transplant Evaluation Period Efficiency Through the Use of an Electronic Scheduling Template

Practice Problem: Candidacy for transplant evaluation is a complex and lengthy evaluation process. Delays in National Organ Registry have significant unfavorable impacts on patient outcomes as 22 people a day die awaiting a lifesaving treatment. Operational efficiencies can improve the pre-transplant evaluation period and significantly improve patient outcomes. PICOT: In an outpatient transplant clinic (P), will leveraging an evidence-based scheduling template (I) compared to the current practice of first available appointment (C) reduce the evaluation period by 66% from a 3–4-week evaluation to a 1-week evaluation resulting in expedited listing on the National Organ Registry (O), when applied over a 10-week period (T)? Evidence: Electronic scheduling templates are evidenced to improve access, workflow efficiencies, and reduce patient wait times by 25% (Suss et al., 2017). Leveraging a value stream mapping tool, gaps in process time can be identified while improving quality outcomes Intervention: An evidence-based scheduling template was applied to measure impact on access availability to appointments for pre-liver transplant patients. Pre-and-post intervention data measured the impact of the scheduling process efficiency, process waste, and total lead time. Outcome: The scheduling template was found to have a statistically significant impact on scheduling efficiency, resulting in a 65.2% (p\u3c.001) reduction in total lead time, reducing evaluation days from an average of 22.71 days (545.04 hours) to an average of 7.9 days (189.6 hours). Conclusion: The new scheduling template improved appointment access and expedited patient’s National Organ Registry by 15 days. Operational efficiencies gained by use of an electronic scheduling template not only have favorable impacts to patient outcomes, but also on organizational costs through improved workflows, and a favorable staff and patient experience

An evaluation of an appointment scheduling system in an ophthalmology clinic

Appointment scheduling systems are often not appropriate based on the patient population’s needs and the nature of the medical specialty. Timeliness, access, and efficiency are compromised if a health system’s scheduling model is not well-suited for its environment. These compromises can be detrimental to the health of patients, the workload burden on providers, and the financial viability of health systems. An outpatient ophthalmology clinic was evaluated and proved to have a scheduling model that was causing a number of concerns. Accounting for the nature of the medical specialty, the variation in appointment lengths, and the needs of patients, a hybrid scheduling model with carve-out access accompanied by an electronic health record timing data is more appropriate for the outpatient ophthalmology clinic

Integrating Clinical Decision Support into Workflow

Purpose: The aims were to (1) identify barriers and facilitators related to integration of clinical decision support (CDS) into workflow and (2) develop and test CDS design alternatives. Scope: To better understand CDS integration, we studied its use in practice, focusing on CDS for colorectal cancer (CRC) screening and followup. Phase 1 involved outpatient clinics of four different systems—120 clinic staff and providers and 118 patients were observed. In Phase 2, prototyped design enhancements to the Veterans Administration’s CRC screening reminder were compared against its current reminder in a simulation experiment. Twelve providers participated. Methods: Phase 1 was a qualitative project, using key informant interviews, direct observation, opportunistic interviews, and focus groups. All data were analyzed using a coding template, based on the sociotechnical systems theory, which was modified as coding proceeded and themes emerged. Phase 2 consisted of rapid prototyping of CDS design alternatives based on Phase 1 findings and a simulation experiment to test these design changes in a within-subject comparison. Results: Very different CDS types existed across sites, yet there are common barriers: (1) lack of coordination of “outside” results and between primary and specialty care; (2) suboptimal data organization and presentation; (3) needed provider and patient education; (4) needed interface flexibility; (5) needed technological enhancements; (6) unclear role assignments; (7) organizational issues; and (8) disconnect with quality reporting. Design enhancements positively impacted usability and workflow integration but not workload. Conclusions: Effective CDS design and integration requires: (1) organizational and workflow integration; (2) integrating outside results; (3) improving data organization and presentation in a flexible interface; and (4) providing just-in time education, cognitive support, and quality reporting

Evaluation of Patient Throughput in an Outpatient Pediatric Hematology, Oncology, and Bone Marrow Transplant Clinic

Background: Outpatient oncology clinics are complex environments. The multi-step, sequential nature of oncology treatment contributes to delays. Prolonged wait time impacts patient compliance, satisfaction, and staff satisfaction. Objectives: To assess throughput in the outpatient pediatric oncology clinic and explore staff’s assessment of throughput and their opinions of what might be improved. Methods: Our descriptive-comparative study used retrospective reviews to measure four time intervals for 312 visits at our mid-Atlantic outpatient clinic. Patient and appointment factors were explored. Mean interval times were calculated and differences impacting throughput were analyzed using ANOVA. Prospective survey data were obtained from 22 clinic staff and themes were identified. Results: The shortest interval was check-in to triage (18.49 ± 18.21 minutes) while the longest was from receiving laboratory results to treatment initiation (136.73 ± 77.98 minutes). Throughput was significantly shorter for appointments consisting of provider visit and laboratory studies only compared to visits involving infusions and blood product transfusions (p \u3c .001). Throughput for 8:00-10:00 a.m. appointments was significantly longer than 2:01-6:00 p.m. appointments (p = .013). Staff respondents reported throughput was suboptimal. Common problems identified were appointment noncompliance, laboratory workflow, triage and front desk bottlenecks, physician timeliness, fellow workflow, and “saving seats”. Conclusions: Delays occurred at each clinic intersection but were significantly longer with early clinic appointments and infusion and transfusion visits. Staff highlighted problems at each clinic juncture and overarching problems that caused inefficiencies. We identified priority areas to be addressed via targeted interventions in a structured action plan to improve clinic efficiency and throughput

Adding value to outpatient heart failure services and the patient journey through digital transformation of services

Introduction Heart failure (HF) is a chronic condition affecting over 900,000 people in the UK. The management of patients with HF frequently involves regular face-to-face appointments. Digital transformation of care with telemedicine, remote monitoring and mobile applications (Apps) may help improve patient experience and relieve demand on services. The Covid-19 pandemic resulted in an acceleration in telemedicine. This thesis evaluates pre-pandemic HF services at the Royal Brompton Hospital (RBH), identifying potential areas for improving patient journeys. Methods Retrospective cohort studies including over 200 patients were used to analyse the activities and actions resulting from HF clinic appointments over 3 years. Time-and-motion studies were conducted for each of the 4 consultant-led HF clinics at RBH, where flow through hospital was analysed for 58 patients. Eight clinicians and 8 patients who had undergone telemedicine consultations were interviewed about their experiences and perceptions, with narrative data thematically analysed. Focus groups and existing educational material were used to design an educational App for HF. Results Most HF patients under long-term follow-up were followed up twice yearly. At clinic visit, worsening HF symptoms and therapy change by clinicians were uncommon (21% and 36% of appointments respectively). Patients spent a median of 103 minutes in hospital on the day of an appointment for a median 20-minute consultation. The majority of consultations ran late. Clinicians and patients found telemedicine consultations generally acceptable, but both groups identified changes in time utilisation, clinical assessment, communication, and technology. Telemedicine appointments were shorter and involved less time waiting and travelling for patients. Patients and clinicians agreed that when patients are “stable”, telemedicine is preferred. A prototype HF educational “Avatar”-based App was produced. Conclusion Digital transformation of outpatient services, including telemedicine can improve patient and clinician experience, efficiency and rationalise limited resources, thus adding value to outpatient HF care.Open Acces

J Nurs Care Qual

We implemented a transitional care management service led by a nurse care manager. An interdisciplinary team developed a workflow using a Plan-Do-Study-Act cycle for contacting patients. Of the 146 (97.9%) eligible patients, 143 (97.9%) had a phone call within 48 hours. There were 84 of 120 (70.0%) and 117 of 120 (97.5%) attendance rates of those attending visits within 7 and 14 days. A care manager-led workflow was successfully and easily implemented within a primary care practice.K23 AG051681/AG/NIA NIH HHS/United StatesU48 DP005018/DP/NCCDPHP CDC HHS/United StatesU48DP005018/ACL HHS/UL1 TR001086/TR/NCATS NIH HHS/United States2019-10-01T00:00:00Z29271832PMC60133136705vault:3045

Optimisation of Patient Flow and Scheduling in an Outpatient Haemodialysis Clinic

The demand for renal replacement therapy (RRT) from the growing number of patients suffering from chronic kidney disease (CKD) and end stage renal disease (ESRD) in Nigeria is reported to be on the rise. However, dialysis clinics are few with limited facilities to meet the increasing demand leading to congestion, long waiting time and increased length of stay (LOS) in dialysis clinics. This paper presents an optimisation model for scheduling patient flow in an outpatient haemodialysis clinic. The objective is to minimize patient LOS using Genetic Algorithm (GA), implemented in Python programming language with Spyder Integrated Development Environment (IDE). The model was tested using data obtained from a haemodialysis clinic, in Lagos, Nigeria. The model generated optimum LOS values (193.01, 275.02 and 390.01) minutes compared to the mean LOS values at the haemodialysis clinic (235.50, 296.62 and 424.50) minutes for the 3-hour, 4-hour and 6-hour dialysis sessions. Furthermore, a simulation experiment of patient flow in a typical haemodialysis clinic was performed by gradual variations in patient arrival rates, λ. Simulation results at (λ=0.1,0.2,0.3,0.4) revealed mean LOS (minutes) as (312.85 ± 73.45, 348.18 ± 84.89, 342.18 ± 81.30, 305, 28 ± 63.67) respectively. The optimisation model was effective in reducing patient LOS

Gaining Efficiency and Reducing Cost: The Re-design of a Preoperative Screening Clinic

Purpose: The purpose of this project was to focus on the redesign of the preoperative screening clinic (PSC) at a 410-bed acute care facility. The process change took place at a healthcare facility where surgical volume has been growing annually since 2011, with an average growth rate of 3% per year. The facility has projected business plans to add capacity for 6 operating rooms in the next three years due to the increased growth. The organization needed the ability to support continued surgical growth prior to the development of adding operating rooms. Understanding the current PSC operations with the need to support future growth, was the motivation for the development of this project to redesign the PSC operations. Methods: A literature review was preformed prior to the development of a plan for change in the PSC. This project is based on using an all registered nurse (RN) group to staff the prescreening clinic for patients needing anesthesia services. The intent was to demonstrate reduced day of surgery cancellations. To complete this process, specific nurse assignments with sequential assembly of the medical chart, and patient information was used. Following approved permissions for use, the Prosci's change management methodology, and the ADKAR model were used to guide the change process. Quantitative data was collected over two separate six month time periods, to compare metrics before and after the change. Results: The z-test was used to determine the significance of the changes made in the pre screening clinic. The results suggest that the changes made to the operational design in the pre screening clinic were significant in reducing day of surgery cancellations. Day of surgery cancellation rate for avoidable causes decreased from 15 cases per month to just two from December 2014 to April 2015. Conclusions: The implementation of the project achieved the goal of decreasing day of surgery cancellations. Additional benefits from the changes implemented included reduced patient wait times in the PSC to an average of less than 15 minutes, and an increased number of patient visits per day by 55%. These changes resulted in an increase in patient satisfaction. Data sources: Data was obtained using Epic's electronic software, which included the Cadence scheduling software. Additional software programs that were used to obtain data were the Kronos time keeping software, and Cisco phone reports. Daily schedules were developed by the manager to coordinate nursing assignments. Researched data sources used included; PubMed, Cochrane Collaboration, CINAHL, and Google Scholar. Key words: pre-screening clinic, pre-admission testing, pre-surgical labs, pre-operative anesthesia consultations, set-up and functioning of pre-anesthesia clinic, cost effective preoperative clinic, design of pre-operative clinic, surgery cancellation rate and the pre-operative clinic.Doctor of Anesthesia Practice (DAP)School of Health Professions and Studies: Doctor of Anesthesia PracticeUniversity of Michiganhttps://deepblue.lib.umich.edu/bitstream/2027.42/137960/1/Flint2016.pd

Modeling the workflow of one primary care physician-nurse team.

Primary care has been identified as a vital part of the healthcare system in the U.S., and one that operates in a challenging, unique environment. Primary care sees a wide variety of patients and is undergoing a series of major transformations simultaneously. As a result, primary care would greatly benefit from a systemic approach to the analysis of its workflows. Discrete-event simulation has been identified as a good tool to evaluate complex healthcare systems. The existing primary care DES models focus on the physician. Also, those models are limited in (a) their usefulness to produce generic models that can easily and quickly be customized and (b) the analysis of the specific tasks performed to treat a patient. Hence, a research idea was developed to address these limitations, which led to a progressive multi-part study developing the necessary components to model a primary clinic. The study was constructed to allow each progressive study to build on the previous. The first part of the study developed a new approach to address those limitations: modeling a primary care clinic from the viewpoint that the physician is the entity that moves through the system. This approach was implemented based on observational data and a standardized primary care physician task list using ARENA© simulation software. The completed model is evidence-based, with the simulation producing predictions and analysis associated with a given patient visit that has not happened by mimicking reality. The benefits of this type of flexible model are that it allows for analysis of any type of “cost” that can be quantified, and it can then be utilized for predicting and potentially subsequently reducing procedural errors and variation in order to increase operational efficiency. The second part of the study was to develop a standardized primary care nurse task list, which is needed given the current transformation of primary care from a doctor-based model to a team-based model. A comprehensive, validated list of tasks occurring during clinic visits was complied from a secondary data analysis. For this, primary care clinics in Wisconsin were selected from a pre-existing study based on 100% participation of the physician-nurse teams. The final task list had 18 major tasks and 174 second-level subtasks, with 103 additional third-level tasks. This task list, combined with the primary care physician task list, provides a tool set that facilitates clinics’ analysis of the workflow associated with a complete patient encounter. Finally, the third part of the study used observational data, the standardized primary care nurse task list, and a similar modeling methodology to the first part to develop a simulation model of the primary care nurse. The model was implemented using ARENA© simulation software. This model is flexible, resulting in an easily-customizable model, and robust in that it allows the analysis of any type of “cost” that can be quantified, such as time, physical or mental resources, money, et cetera. This can potentially be used to predict, and reduce, procedural errors and variation in response to changes to the workflows or environment; hence, the operational efficiency and medical accuracy can be more accurately evaluated