|Promoting Health, Wellness, and Safety With Organizational Behavior Management
|Monday, May 31, 2021
|11:00 AM–12:50 PM
|Area: OBM; Domain: Applied Research
|Chair: Matthew M Laske (University of Kansas)
|Discussant: Terry E. McSween (DEKRA Organizational Safety and Reliability)
Behavior analysis has a rich history of efficacious interventions that increase behaviors related to health, wellness, and safety. Organizational Behavior Management (OBM) is a subfield of behavior analysis that has been successful at promoting targeted behaviors in settings such as health and human services, manufacturing, health care, construction, etc. The current symposium highlights several recent applications of OBM to improve health, wellness, and safety in applied settings. Four presentations have been prepared to (1) present data on an initiative at a health center to reduce readmission rates, (2) summarize a pinpoint-criteria to promote risk identification in the workplace, (3) describe a conversation-based intervention to improve worker safety, and (4) report on smartphone technology and behavioral observations to increase COVID-19 infection control behaviors at a university. The symposium will conclude with a discussant overview of the current topic and advancements in OBM.
|Instruction Level: Intermediate
|Keyword(s): Covid-19 prevention, health, OBM, safety
|Using Non-clinical Quality Improvement Interns to Reduce Readmissions for Specialty Service Patients Within an Academic Medical Center
|ANDRESSA SLEIMAN (Univeristy of Florida ), Alfeil Felipe (University of Florida), Anu Vats (University of Florida), Brian Tran (University of Florida), Katharina Busl (University of Florida), Jacqueline Baron-Lee (University of Florida)
|Abstract: Post-discharge patient calls have shown to decrease unplanned readmissions; however, nurses often are unable to complete the calls because they compete with other clinical obligations. We evaluated the viability of having non-clinical quality improvement (QI) interns conducting initial post-discharge calls and filtering patients who required clinical or nurse follow-up. QI interns completed 83.8% post-discharge patient calls within 72 hours of discharge, and nurses completed 57.2% follow-up requests within the targeted 48 hours and completed the remaining requests within seven days. QI intern post-discharge follow-up calls, in conjunction with nurse follow-up intervention, showed a significant (RR = -3.31, p = 0.012) preventive effect on unplanned readmission rate. QI interns are a viable alternative to nurses to conduct the first contact of post-discharge patient follow-up calls. This system of QI interns filtering calls and assigning them to the correct department of clinical service or nurse department increased post-discharge patient follow-up calls success rate, and it decreased readmission rates.
|7-Pinpoint Criteria to Promote Risk Identification: Preliminary Investigation in Behavioral Safety
|MATTHEW M LASKE (University of Kansas; Cambridge Center for Behavioral Studies), Timothy D. Ludwig (Appalachian State University)
|Abstract: Identifying risk in the workplace is crucial so that it can be intervened upon and mitigated to prevent harm to employee health and wellbeing. For a behavioral observation process to be successful it must be able to identify variance in behavior that puts an employee at-risk. The current presentation provides a case study of an organization’s initiative to increase risk identification in a behavioral observation process. Researchers developed seven pinpoint criteria to evaluate the efficacy of the organization’s intervention to increase risk identification. The criterion was used to evaluate the objectivity and potential ambiguity of behavioral pinpoints. A detailed overview of the development and application of seven pinpoint criteria will be described. Data suggest that pinpoints developed by the organization that met these criteria found more risk in their observation process and led to more preventive initiatives to promote employee health and safety. Considerations for the application and future research regarding the seven pinpoint criteria will be discussed.
|Say Something: The Effectiveness of Conversation-Based Interventions and How They Can Change Organizational Culture
|NICHOLAS MATEY (University of Florida ), Nicole Gravina (University of Florida), John Austin (Reaching Results)
|Abstract: Behavioral safety is a well-known methodology to reduce occupational injuries and incidents. Traditional methods like behavior-based safety (BBS) have proven effective in over 90% of published studies (e.g., Tuncel et al., 2006); however, if enough employees don’t participate in the system, it’s unlikely to work. This talk presents data from one study showing how a conversation-based intervention was introduced to supplement a declining BBS process and successfully created a safer work environment. Following the introduction of the conversation-based intervention, employee participation increased, and injuries declined over 24% and those changes have maintained. In addition to less injuries, employees report that the process has positively changed the culture of the organization. We will discuss why we think this intervention was effective as well as future directions for research and practice alike.
|Targeting COVID-19 Infection Control Behaviors at Multiple University Settings
|TIMOTHY D. LUDWIG (Appalachian State University), Nicole Gravina (University of Florida), Connor Linden (Appalachian State University)
|Abstract: Outbreaks of COVID-19 on university campuses lead to illness, disruption of instruction, and expensive campus shutdowns. A consortium of behavior analysis labs adopted a set of infection control pinpoints, a behavioral observation smartphone application, and standardized observation protocols. Infection control behaviors were systematically observed and tracked across multiple university campuses. Participating student groups (e.g., residence halls, clubs) engaged in observations and received targeted interventions (e.g., group feedback, hand signals, competitions). Observation data showed varied trends in infection control behaviors suggesting “drift” after initial high rates, more adherence in academic buildings and less in residence halls. Data also suggested a lagging relationship between behaviors and positive COVID-19 tests.