An application of computable biomedical knowledge to transform patient centered scheduling.

Introduction: Efficient appointment scheduling in the outpatient setting is challenged by two main factors: variability and uncertainty leading to undesirable wait times for patients or physician overtime, and events such as no-shows, cancellations, or walk-ins can result in physician idle time and under-utilization of resources. Some methods have been developed to optimize scheduling and minimize wait and idle times in the inpatient setting but are limited in the outpatient setting. Methods: People and Organization Development, an internal group of organizational developers, led the development of a solution that selects the optimal group of appointments for a patient that minimizes the time between associated procedures as well as lead time built using a linear integer program. This program takes appointment requests, availability of resources, order constraints, and time preferences as inputs, and provides a list of the most optimal groupings as an output. Included in the methodology is the technical infrastructure necessary to deploy this within an electronic medical record system. Implementation and Test Plan: A pilot has been designed to run this algorithm in a single department. The pilot will include training staff on the new workflow, and conducting informal interviews to gather qualitative data on performance. Key performance indicators such as schedule utilization, resource idle time, patient satisfaction, average appointment lead time, and average waiting time will be closely monitored. Discussion: The model is limited in accounting for variability in appointment length potentially resulting in inaccurate schedules for healthcare providers and patients. Future states would incorporate certain visit types starting through machine learning techniques. Additionally expanding our data pipeline and processing, developing greater communication software, and expanding our research to include other departments and subspecialties, will enhance the accuracy and flexibility of the algorithm and enable healthcare providers to provide better care to their patients.

Application of the Consolidated Framework for Implementation Research Model to Design and Implement an Optimization Methodology within an Ambulatory Setting.

BACKGROUND: Following the implementation of a new electronic health record (EHR) system at Columbia University Irving Medical Center (CUIMC), the demands of the novel coronavirus disease 2019 (COVID-19) pandemic forced an abrupt reallocation of resources away from EHR adoption. To assist staff in focusing on techniques for improving EHR utilization, an optimization methodology was designed referencing the Consolidated Framework for Implementation Research (CFIR) approach. METHODS: The study was performed using a methodology that comprised of two primary components as follows: (1) analysis of qualitative and quantitative data and (2) participation of frontline staff in project work groups. Working groups mapped out the current state of the identified workflows, designed and implemented interventions, monitored the effectiveness of each intervention, and scaled the proposed changes. RESULTS: As a result of the optimization methodology, clinical and operational workflows improved in the pilot department. Operationally, the pilot department increased enrollment of patients in the virtual patient portal by 20%, increased schedule utilization by 25%, and reduced average check-in time by 19%. Clinically, the pilot department had a statistically significant increase in dictation and NoteWriter tool note composition from their baseline month to their observed month. Compared with the control department, the pilot department had a statistically significant increase in SmartTool and dictation note composition. The control department showed smaller increases, and in some cases a decline in performance, in these areas of operational and clinical workflows. CONCLUSION: The CFIR framework helped design an optimization methodology by applying a set of constructs to support effective organizational optimization, accounting for inner and outer settings. Through this methodology, the inner setting was supported in leading the identification and execution of interventions targeted to impact the outer setting. The phase-1 data at CUIMC suggest this strategy is effective in identifying opportunities, implementing interventions and creating a scalable process for continued organizational optimization.

An application of Harrison's system theory model to spark a rapid telehealth expansion in the time of COVID-19.

Introduction: In response to the COVID-19 pandemic, health systems had to quickly adopt a process for enabling targeted and patient-centered care delivery. This case study describes the utilization of Harrison's open-systems model to create an approach for rapid adoption of existing telehealth technologies in a large scale academic medical center. Methods: An internal group of organizational developers, was enlisted to enable this effort. Local networks were employed and organized into focus groups to rapidly assess and address barriers to adoption and informal interviews with executive leadership were conducted to align organizational goals. Interventions include rapid deployment of focused and data driven provider, staff and patient support bolstered by effective communication and resource management. Results: There was an increase in the number of patient portal activation codes by 75% during the month of March. The number of activation codes generated expectedly decreased in April as many patients now had activated patient portals. The video visit volume as a result of provider self-scheduling increased went from a baseline of 0 to over 600 clinical visits. Discussion: Experienced organizational development programs can facilitate adoption of change. The faculty practice of CUIMC has years of experience with supporting wide scale operational change centered on technology. In this case, providing engaged networks with tailored content that is focused on the process and available technology promoted rapid adoption and optimization. Conclusion: In the setting of profound external pressure, experience with the ability to focus on tailoring training and support to the culture of the organization helped to rapidly increase the availability and success of telehealth visits for a large scale academic medical center.