Ready to Go Home? Assessment of Shared Mental Models of the Patient and Discharging Team Regarding Readiness for Hospital Discharge
BACKGROUND: A critical task of the inpatient interprofessional team is readying patients for discharge. Assessment of shared mental model (SMM) convergence can determine how much team members agree about patient discharge readiness and how their mental models align with the patient’s self-assessment.
OBJECTIVE: Determine the convergence of interprofessional team SMMs of hospital discharge readiness and identify factors associated with these assessments.
DESIGN: We surveyed interprofessional discharging teams and each team’s patient at time of hospital discharge using validated tools to capture their SMMs.
PARTICIPANTS: Discharge events (n = 64) from a single hospital consisting of the patient and their team (nurse, coordinator, physician).
MEASURES: Clinician and patient versions of the validated Readiness for Hospital Discharge Scales/Short Form (RHDS/SF). We measured team convergence by comparing the individual clinicians’ scores on the RHDS/SF, and we measured team-patient convergence as the absolute difference between the Patient-RHDS/SF score and the team average score on the Clinician-RHDS/SF.
RESULTS: Discharging teams assessed patients as having high readiness for hospital discharge (mean score, 8.5 out of 10; SD, 0.91). The majority of teams had convergent SMMs with high to very high interrater agreement on discharge readiness (mean r*wg(J), 0.90; SD, 0.10). Yet team-patient SMM convergence was low: Teams overestimated the patient’s self-assessment of readiness for discharge in 48.4% of events. We found that teams reporting higher-quality teamwork (P = .004) and bachelor’s level–trained nurses (P < .001) had more convergent SMMs with the patient.
CONCLUSION: Measuring discharge teams’ SMM of patient discharge readiness may represent an innovative assessment tool and potential lever to improve the quality of care transitions. Journal of Hospital Medicine 2020;15:XXX-XXX.
© 2020 Society of Hospital Medicine
Contextual Variables
We reviewed the literature to identify potential patient and system factors associated with adverse transitional care outcomes1-8 and/or higher quality SMMs in other settings.10-19 For example, patient characteristics included age, principal diagnosis, length of stay, number of comorbidities, and cognition impairment (using the Short Portable Mini Mental Status Questionnaire29).2,22,30 Examples of system factor include teamwork and communication quality1-6 on day of discharge, as well as educational background and experience of clinicians on the team.31-33 We adapted a validated survey using 7-point Likert scale questions to determine teamwork quality and communication quality during individual patent discharges.33 Appendix C provides descriptions of all variables.
Data Collection
Patient recruitment occurred from February to October 2017 in a single community hospital in Iowa.9 We identified potentially eligible events in collaboration with the unit charge nurses. Patients were screened 24 to 48 hours prior to anticipated day of discharge; those interested/eligible underwent informed consent procedures.9 We collected data from the patient and their corresponding bedside nurse, coordinator, and attending physician on the day of discharge. After the discharge order was placed and care instructions were provided, the patient completed a demographic survey, Short Portable Mini Mental Status Questionnaire, and the Patient-RHDS/SF. Individual team members completed a survey with the demographic information, their respective versions of RHDS/SF, and day-of-discharge teamwork-related questions. On average, the survey took clinicians less than 5 minutes to complete. We performed a chart review to determine additional patient characteristics such as principal diagnosis, length of stay, and number of comorbidities.
Data Analysis
Team Assessment of Patient Discharge Readiness
The teams’ shared assessment (SMM content) was determined by averaging the members’ individual scores on the Clinician-RHDS/SF.34 Discharge events with higher team assessments indicated the team perceived the patient as being readier for hospital discharge. Guided by prior research, we examined the RHDS/SF scores as a continuous variable and as a four-level categorical variable of readiness: low (<7), moderate (7-7.9), high (8-8.9), and very high (9-10).20
Team SMM Convergence
To determine the teams’ convergence on patient discharge readiness, we calculated an adjusted interrater agreement index (r*wg(j))35,36 for each team using the individual clinicians’ scores on the RHDS/SF. These convergence values were categorized into four agreement levels: low agreement (<0.7), moderate agreement (0.7-0.79), high agreement (0.8-0.89), and very high agreement (0.9-1). See Appendix D for the r*wg(j) equation.35,36
Team-Patient SMM Convergence
To determine the team-patient SMM convergence, we subtracted the team’s assessment of patient discharge readiness from the Patient-RHDS/SF score. We used a one-unit change on the RHDS/SF (1 point on the 0-10 scale) as a meaningful difference between the patient’s self-assessment and teams’ assessment on readiness for hospital discharge. This definition for divergence aligns with prior RHDS psychometric testing studies20,27 and research examining convergence between patient and nurse assessments.28 For example, Weiss and colleagues27 found a 1-point decrease in the RN-RHDS/SF item mean was associated with a 45% increase in likelihood of postdischarge utilization (hospital readmission and emergency room department visits). Therefore, we defined convergence of team-patient SMMs (or similar patient and team scores) as those with an absolute difference score less than 1 point, whereas teams with low team-patient SMM convergence (or divergent patient and team scores) were defined as having an absolute difference score greater than 1 point.
