Typical solutions for improving discharge planning often rely on one-way communication mechanisms and static data entry into the eHR. We have designed a discharge readiness tool that has been integrated into the electronic health record (eHR), which allows providers to communicate the status of patient discharge readiness in real-time to all clinical staff providing care. This information will enhance prioritization of care and patient flow. Stakeholder engagement to inform user-centered design was imperative to ensure our discharge readiness tool is successfully integrated into existing workflows such that all clinical staff will this tool with every patient.

To engage hospitalists, nurses, other clinical staff, patients, families and caregivers, and hospital leadership, we met with different stakeholder groups across the inpatient setting to obtain feedback about tool design and functionality.

We employed multiple user-centered design strategies, including exploring current functionality for documenting discharge readiness and directing discharge planning, iterative low-fidelity mock-ups, multi-disciplinary stakeholder meetings, Brainwriting Premortem exercise, and pre-production user testing (Figure 1). Utilization and feedback were evaluated using EHR and survey data.

We found most providers who responded to the survey reported that the tool either saved time or did not change the amount time required to complete their discharge workflow (21, 87.5%). During the pilot phase, 352 care team members, including hospitalists, residents, nurses, care managers, and physician therapists, have added the tool to their workflow. At the conclusion of the post-implementation phase, 467 care team members have added the tool to their workflow. In addition, providers assigned a discharge status to 84.9% of patients discharged during the pilot implementation period and 87.4% of patients discharged post-implementation. The most common barriers identified by providers were medical improvement (40.9%), placement (12.3%), subspecialty consults (9.6%), physical therapy (9.3%), and social work or care management (8.9%).

Typical solutions for improving discharge planning often rely on one-way communication mechanisms and static data entry into the EHR or in-person meetings for discharge rounds. We have designed a dynamic EHR discharge readiness tool, allowing the care team to communicate the status of patient discharge readiness and patient discharge needs in real-time across hospital settings. Survey and EHR data suggest that this electronic discharge readiness tool has been successfully adopted by providers and clinical staff. Frequent stakeholder engagement and iterative user-centered design was critical to the successful implementation of this tool.

Rehabilitation after total knee arthroplasty (TKA) is typically generic and based on population-level estimates of recovery. Individualized, patient-centered care improves orthopedic outcomes1 and is desired by patients after TKA.2, 3 However, clinicians lack the necessary tools to deliver this kind of care consistently. We developed a novel approach for generating individualized recovery trajectories in rehabilitation to improve patient-centered care for patients with TKA.4 We worked closely with relevant stakeholders to incorporate our approach into a clinical support tool—the Knee Recovery App—designed for TKA rehabilitation. The purpose of this project is to evaluate the effectiveness of the Knee Recovery App while gathering information about its implementation using the RE-AIM framework.5

The Knee Recovery App will be implemented as standard of care in two physical therapy clinics in Greenville, SC, owned by ATI Physical Therapy. The app will be used directly by physical therapists to generate individualized recovery information for all patients between the ages of 40 and 90 seeking rehabilitation after TKA (n=30).

We will use a Hybrid Type 1 design to test the effectiveness of the Knee Recovery App while gathering information about its implementation potential.6 Physical therapists will use the app to generate patient-specific recovery estimates to (1) inform patients of their expected recovery and (2) develop a patient-centered plan of care. Outcomes will be collected prospectively throughout the episode of care and compared to a retrospective cohort of age and sex-matched patients (n=60) in ATI’s quality improvement database of patients with TKA. Group differences will be examined using linear models and effect size will be calculated with Cohen’s d. Effectiveness outcomes will include functional measures and surveys related to patient-centered care (Table 1). We will evaluate the implementation potential of our app using a mixed-methods approach informed by the RE-AIM framework (Table 1).7 Our qualitative approach will consist of directed content analysis of semi-structured interviews with representation from all stakeholders (n=30).8 Quantitative implementation outcomes will be extracted from three sources: (1) ATI’s quality improvement database, (2) information stored on the Knee Recovery App, and (3) survey administered to clinicians.

Our novel approach for individualized rehabilitation has the potential to improve patient-centered care and outcomes in TKA rehabilitation. The RE-AIM framework informed our implementation strategy and will provide the structure to examine barriers and facilitators to clinical use of the Knee Recovery App. We anticipate the results of this project will inform a future cluster randomized trial in the ATI system guided by the PRISM framework.

Cigarette smoking is the leading preventable cause of death and disability in the U.S., accounting for almost half a million deaths per year1,2. Despite ongoing efforts to improve cessation rates through treatment development and dissemination of evidence-based practices, less than one-third of the population use proven cessation methods and the average quit rate is 7.4%3. Qualitative research methodologies have the potential to highlight limitations and identify novel approaches or adaptations to existing behavioral treatments4 that may increase engagement, adherence, and success. Using a mixed methods approach, we examine whether smokers have insight into changes needed to quit smoking and how this insight affects actual changes made during a smoking cessation attempt as well as cessation success.

Stratified random sampling5 (Figure 1) was used to select 100 current cigarette smokers participating in an aided smoking cessation attempt as part of a larger comparative effectiveness trial. Bachelors level Health Counselors completed brief individual qualitative interviews at baseline and two-week post-quit visits. Interviews were audio-recorded and transcribed, then entered into a MS-excel file for coding purposes. Rapid data analytic methods 6,7 are being used to examine three separate domains: planned changes, used changes, and consistency in changes.

Initial themes for planned changes prior to quitting include: changing routines (no plan), change alcohol consumption, limiting smoking urges, focus on benefits of quitting, reduce exposure to social smoking cues, identify other coping mechanisms for stress, get support from friends/loved ones, make other health changes, reduce stress (no plan), get partner to quit, identify problem (no plan), planned changes unknown. Initial used changes themes include: reduce exposure to non-social paraphernalia/smoking cues, distraction/keep busy, make other health changes, changed daily routine, change mindset, reduce exposure to social smoking cues, get support from friends/loved ones. Consistency between planned and used changes revealed participants use both planned and unplanned changes, while some reported not knowing what to do prior to quitting and others identified additional changes needed.

Ongoing rapid content analysis6 revealed multiple themes for smoker-identified planned and used changes to improve cessation success, but analyses need to be completed. We will then examine distribution of themes based on race, gender, psychiatric history, and nicotine dependence as well as the ability of smokers to identify and make changes. Exploratory analyses will descriptively examine differences between smokers who did and did not identify changes on cessation success. Findings will guide treatment development and adaptations for behavioral smoking cessation treatments.