Inpatient Hospital Factors and Resident Time With Patients and Families

Time-motion observations to characterize the developmental environment in a paediatric post-acute care hospital

BACKGROUND

Chronically hospitalized children are at risk for neurodevelopmental delay, compounded by restricted social interactions, movement and environmental stimulation. We measured patients' movements and interactions to characterize developmentally relevant aspects of our inpatient environment and identify opportunities for developmental enrichment.

METHODS

As part of a quality improvement initiative to inform neurodevelopmental programming for children with medical complexity at our paediatric post-acute care specialty hospital, we conducted >232 hours of time-motion observations. Trained observers followed 0- to 5-year-old inpatients from 7 am to 7 pm on weekdays, categorizing observations within five domains: Where, With, Position, State and Environment. Observations were collected continuously utilizing REDCap on iPads. A change in any domain initiated a new observation.

RESULTS

Patients were median 1 year and 8 months of age (range 2 months to 3 years 9 months) with a median length of hospitalization of 514 days (range 66-1298). In total, 2636 unique observations (or median 134 observations per patient-day [range 95-210]) were collected. Patients left their rooms up to 4 times per day for median 1 h and 34 min (range 41 min to 4 h:30 min). Patients spent 4 h:6 min (2 h:57 min to 6 h:30 min) interacting with someone and 3 h:51 min (57 min to 6 h:36 min) out of bed each day. Patients were simultaneously out of their beds, interacting with someone and awake for 2 h:21 min (51 min to 4 h:19 min) each day.

CONCLUSIONS

Despite a care model prioritizing time out of bed and social interaction, time-motion observations indicate patients spent many of their waking hours in bed and alone. Quantifying our inpatients developmental opportunities will inform neurodevelopmental programming initiatives.

Association of Mobile Workstations and Rounding-in-Flow with Resident Efficiency: A Controlled Study at an Academic Internal Medicine Department

BACKGROUND

Residents commonly use a batched workflow to round on hospitalized patients, creating redundancy and decreasing efficiency.

OBJECTIVE

To improve resident efficiency through a novel workflow using mobile laptops and modified rounding-in-flow.

DESIGN, SETTING, PARTICIPANTS

A controlled experimental study conducted at an academic medical center for 3 months. One internal medicine team served as the intervention group, and two other teams served as a control group; 34 interns and 20 senior residents participated.

INTERVENTION

Residents in the intervention group were provided a novel workflow and a mobile laptop to allow them to round "in-flow." Control group residents rounded as usual (batched workflow without laptops).

MAIN MEASURES

Fourteen interns were monitored for a time-motion study. Time-stamped electronic medical record (EMR) data were used to assess percentage of progress notes and orders placed during rounds (9 a.m.-12:30 p.m.) and percentage of discharge summaries signed within 24 h of discharge. A post-intervention survey measured perceived efficiency.

RESULTS

A time-motion study showed non-significant differences between time in the intervention group and that in the control group: communication time with patients (128 min vs 105 min, p = 0.37) and computer time (289 min vs 306 min, p = 0.71). EMR data for 664 visits in the control group and 374 in the intervention group showed that rounding-in-flow was associated with an odds ratio (OR) of 1.5 for placing progress notes during rounds (95% CI: 1.2-1.7, p < 0.001), an OR of 1.1 for placing non-discharge orders during rounds (95% CI: 1.0-1.2, p = 0.01), and an OR of 3.9 for signing discharge summaries within 24 h of discharge (95% CI: 2.3-7.2, p < 0.001). Post-intervention survey, completed by 23 of 34 interns, showed that interns in the intervention group perceived that orders were completed during rounds more often than the control group (OR 7.8; 95% CI: 1.3-60.1, p = 0.03).

CONCLUSIONS

Using mobile laptops with modified rounding-in-flow was associated with earlier completion of residents' work, suggesting improved efficiency.

Creating a better learning environment: a qualitative study uncovering the experiences of Master Adaptive Learners in residency

BACKGROUND

Adaptive expertise is an important physician skill, and the Master Adaptive Learner (MAL) conceptual model describes learner skills and behaviors integral to the acquisition of adaptive expertise. The learning environment is postulated to significantly impact how MALs learn, but it is unclear how these successful learners experience and interact with it. This study sought to understand the authentic experience of MALs within the learning environment and translate those experiences into practical recommendations to improve the learning environment for all trainees.

METHODS

Following a constructivist paradigm, we conducted a thematic analysis of transcripts from focus groups composed of MALs to identify commonalities in experiences and practices of successful postgraduate trainees in the learning environment. Saturation was achieved after seven focus groups, consisting of thirty-eight participants representing fourteen specialties from four institutions. Researchers coded transcripts using constant comparison analysis, which served as the foundation for our thematic analysis.

RESULTS

We identified eight themes and situated them within a 4-component model of the learning environment. Four themes were identified within the personal component: (1) patients drive learning; (2) learning has no endpoint; (3) management of emotions is crucial for learning; (4) successful learning requires a structured approach. Two themes were identified in the social component: (5) positive social relationships are leveraged to maximize learning; (6) teaching facilitates personal learning. Two themes were identified in the organizational component: (7) transitions challenge learners to adapt; (8) the learning environment dictates goal setting strategy. No major themes were identified in the physical/virtual component, although participants frequently used technology when learning.

CONCLUSIONS

Master Adaptive Learners experience similar facilitators of, and barriers to, success in the learning environment. Overall, our data show that acquisition of many successful strategies and skills that support learning are relegated to the hidden curriculum of residency training. Educators could support a more effective learning environment for all trainees by: (1) highlighting patients as the focal point of learning, (2) building a professional 'learner' identity, (3) teaching learning skills, and (4) creating opportunities for collaborative learning.

Drip System for Admissions to Resident Teams: Impact on Workload and Education

OBJECTIVES

Assigning patients to a call team every fourth day (bolus system) caused the maldistribution of patients among resident teams and required additional faculty effort for overflow patient care. We changed to a continuous daily rotation (drip system) and examined the effect on clinical workload among resident teams, resident education, and faculty utilization.

METHODS

This is a retrospective study based on the daily records of 7 am team census, the attending physician schedules for a pediatric hospital medicine service with 5 teams, and the measures of resident education, including noon conference attendance, scores on in-service examinations, and duty hour violations. Data from the bolus system (May 2014-June 2015) were compared with the drip system (May 2016-June 2017).

RESULTS

Data from 348 bolus days and 338 drip days were analyzed. There was a decrease in interteam variation from 6.2 to 3.9 patients (P < 0.001). There were fewer days with the following: large interteam variation (143 to 25, P < 0.001), days with resident teams at or above capacity (26 to 11, P = 0.01), resident teams below a minimum 7 am census (133 to 18, P < 0.001), and days when additional faculty were pulled for clinical care (61 to 9, P < 0.001). Resident noon conference attendance was unchanged and there was no adverse effect on examination scores or duty hour violations.

CONCLUSIONS

Changing from a bolus to a drip model for admissions to inpatient teams resulted in a more even distribution of the workload and a more efficient use of physician resources without negatively affecting resident education.

Teaching at the Bedside: Strategies for Optimizing Education on Patient and Family Centered Rounds

Resident and attending concern about the potential for decreased teaching has been cited as one of the drawbacks to the adoption of family-centered rounds (FCR). Despite these concerns, FCR can enhance clinical education through direct exposure to multiple patients by all team members, as well as by allowing faculty to teach, model, observe, and assess learners' clinical skills more effectively than in nonbedside settings. This article provides many strategies and approaches to bedside teaching designed to enhance education and communication among care team members as well as patients and their families.

Family-Centered Rounds: Past, Present, and Future

Bedside rounds have evolved concurrently with hospitalist medicine and patient-centered care. Family-centered rounds are the foundation of effective communication in the in-patient pediatric setting. Participant perspectives (family members, patients, nurses, faculty, and trainees) on family-centered rounds differ and goals may not always align. Further, the practical components of how rounds are conducted varies and have continued opportunities for improvement. This article summarizes the most recent experience with rounds in an attempt to identify unified and effective strategies moving forward.

Less direct patient care delivered by medical trainees by the end of a hematology-oncology ward rotation: Association with empathy and related factors

OBJECTIVE

The education of trainee physicians in hematology-oncology is challenged by inherent stressors of hematology-oncology. Clinical work load, death and dying, and the known phenomenon of empathy decline during clinical education affect trainees. Time spent with patients or direct patient care time (DPCT) is influenced by many factors, which ultimately affect medical education. Therefore, DPCT may decrease by the end training on a busy hematology-oncology ward rotation.

METHODS

Internal medicine interns and residents (n = 64) rotating on a hematology-oncology ward rotation were consecutively selected to participate. Questionnaires containing Likert scale questions assessing time spent with patients before and after the rotation, empathy/resilience/distress measurements (Interpersonal Reactivity Index [IRI], Connors-Davidson Resilience Scale [CD-RISC], and Impact of Events Scale-Revised [IES-R], respectively), and demographic and situational information were collected at the beginning and end of the rotation RESULTS: DPCT decreased from over 10 to 15 minutes per patient to slightly over 1 to 5 minutes with over half of the trainees spending less than 1 minute per patient per day (P < .001, Cohen's d = 1.05). Empathy scores decreased 2.01 points from 58.9 to 56.8 (P = .018, Cohen's d = 0.33) during the rotation. DPCT decrease was associated mistreatment (P < .001) and lack of support (P = .001) while endorsing external issues (P = .002) and longer rotation time predicted for greater DPCT accounting for 67% of DPCT variance on multivariate analysis.

CONCLUSION

Medical trainees in oncology who feel a lack of social/familial support and feel mistreated by mentors/superiors spend significantly less time with patients. Educational initiatives should replicate and utilize these associations to enhance patient-centric care in oncology.

Automatic Detection of Front-Line Clinician Hospital Shifts: A Novel Use of Electronic Health Record Timestamp Data

OBJECTIVE

Excess physician work hours contribute to burnout and medical errors. Self-report of work hours is burdensome and often inaccurate. We aimed to validate a method that automatically determines provider shift duration based on electronic health record (EHR) timestamps across multiple inpatient settings within a single institution.

METHODS

We developed an algorithm to calculate shift start and end times for inpatient providers based on EHR timestamps. We validated the algorithm based on overlap between calculated shifts and scheduled shifts. We then demonstrated a use case by calculating shifts for pediatric residents on inpatient rotations from July 1, 2015 through June 30, 2016, comparing hours worked and number of shifts by rotation and role.

RESULTS

We collected 6.3 × 10⁷ EHR timestamps for 144 residents on 771 inpatient rotations, yielding 14,678 EHR-calculated shifts. Validation on a subset of shifts demonstrated 100% shift match and 87.9 ± 0.3% overlap (mean ± standard error [SE]) with scheduled shifts. Senior residents functioning as front-line clinicians worked more hours per 4-week block (mean ± SE: 273.5 ± 1.7) than senior residents in supervisory roles (253 ± 2.3) and junior residents (241 ± 2.5). Junior residents worked more shifts per block (21 ± 0.1) than senior residents (18 ± 0.1).

CONCLUSION

Automatic calculation of inpatient provider work hours is feasible using EHR timestamps. An algorithm to assess provider work hours demonstrated criterion validity via comparison with scheduled shifts. Differences between junior and senior residents in calculated mean hours worked and number of shifts per 4-week block were also consistent with differences in scheduled shifts and duty-hour restrictions.