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.

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.

Effect of Real-Time Feedback Devices on Primary Care Patient Experience Scores: A Cluster-Randomized Trial.

Patient experience is a critical measure for ambulatory primary care, although it is unclear how to best improve patient experience scores. This study aimed to determine whether use of a real-time feedback (RTF) device improved patient experience scores in a cluster-randomized trial. The primary outcomes were change from baseline in 9 Clinician and Group Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) question and domain scores most closely related to the RTF questions asked in a linear mixed effects model.

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.

Contextual Factors Associated With Quality Improvement Success in a Multisite Ambulatory Setting.

The Model for Understanding Success in Quality (MUSIQ) is a framework of contextual factors for quality improvement (QI) projects. We sought to determine which MUSIQ contextual factors were associated with successful QI initiatives. In a cross-sectional survey study, at a 21-site, ambulatory, urban primary care network, a modified MUSIQ survey tool questionnaire was administered to QI team members.