Intern workload and discontinuity of care on 30-day readmission

Factors associated with one-year mortality after hospital discharge: A multicenter prospective cohort study

OBJECTIVES

1) To identify predictors of one-year mortality in hospitalized medical patients using factors available during their hospital stay. 2) To evaluate whether healthcare system use within 30 days of hospital discharge is associated with one-year mortality.

STUDY DESIGN AND SETTING

This prospective, observational study included adult patients from four mid-sized hospital general internal medicine units. During index hospitalization, we retrieved patient characteristics, including demographic and socioeconomic indicators, diagnoses, and early simplified HOSPITAL scores from electronic health records and patient interviews. Data on healthcare system use was collected using telephone interviews 30 days after discharge. Survival status at one year was collected by telephone and from health records. We used a univariable analysis including variables available from the hospitalization and 30-day post-discharge periods. We then performed multivariable analyses with one model using index hospitalization data and one using 30-day post-discharge data.

RESULTS

Of 934 patients, 123 (13.2%; 95% CI 11.0-15.4%) were readmitted or died within 30 days. Of 814 patients whose primary outcome was available, 108 died (13.3%) within one year. Using factors obtained during hospitalization, the early simplified HOSPITAL score (OR 1.50; 95% CI 1.31-1.71; P < 0.001) and not living at home (OR 4.0; 95% CI 1.8-8.3; P < 0.001) were predictors of one-year mortality. Using 30-day post-discharge predictors, hospital readmission was significantly associated with one-year mortality (OR 4.81; 95% CI 2.77-8.33; P < 0.001).

SIGNIFICANCE

Factors predicting one-year mortality were a high early simplified HOSPITAL score, not living at home, and a 30-day unplanned readmission.

Associations between post-discharge medical consultations and 30-day unplanned hospital readmission: A prospective observational cohort study

BACKGROUND

The period following hospital discharge is one of significant vulnerability. Little is known about the relationship between post-discharge healthcare use and the risk of readmission.

OBJECTIVES

To explore associations between medical consultations and other healthcare use parameters and the risk of 30-day unplanned hospital readmission.

METHODS

Between July 2017 and March 2018, we monitored all adult internal medicine patients for 30 days after their discharge from four mid-sized hospitals. Using follow-up telephone calls, we assessed their post-discharge healthcare use: consultations with general practitioners (GPs) and specialist physicians, emergency room (ER) visits, and home visits by nurses. The binary outcome was defined as any unplanned hospital readmission within 30 days of discharge, and this was analyzed using logistic regression.

RESULTS

Of 934 patients discharged, 111 (12%) experienced at least one unplanned hospital readmission within 30 days. Attending at least one GP consultation decreased the odds of readmission by half (adjusted OR: 0.5; 95%CI: 0.3-0.7), whereas attending at least one specialist consultation doubled those odds (aOR: 2.0; 95%CI: 1.2-3.3). GP consultations also reduced the odds of the combined risk of an ER visit or unplanned hospital readmission (aOR: 0.5; 95%CI: 0.3-0.7). ER visits were also associated with a higher readmission risk after adjusting for confounding factors (aOR: 10.0; 95%CI: 6.0-16.8).

CONCLUSION

GP consultations were associated with fewer ER visits and unplanned hospital readmissions.

Who is Responsible for Discharge Education of Patients? A Multi-Institutional Survey of Internal Medicine Residents

BACKGROUND

Safely and effectively discharging a patient from the hospital requires working within a multidisciplinary team. However, little is known about how perceptions of responsibility among the team impact discharge communication practices.

OBJECTIVE

Our study attempts to understand residents' perceptions of who is primarily responsible for discharge education, how these perceptions affect their own reported communication with patients, and how residents envision improving multidisciplinary communication around discharges.

DESIGN

A multi-institutional cross-sectional survey.

PARTICIPANTS

Internal medicine (IM) residents from seven US residency programs at academic medical centers were invited to participate between March and May 2019, via email of an electronic link to the survey.

MAIN MEASURES

Data collected included resident perception of who on the multidisciplinary team is primarily responsible for discharge communication, their own reported discharge communication practices, and open-ended comments on ways discharge multidisciplinary team communication could be improved.

KEY RESULTS

Of the 613 resident responses (63% response rate), 35% reported they were unsure which member of the multidisciplinary team is primarily responsible for discharge education. Residents who believed it was either the intern's or the resident's primary responsibility had 4.28 (95% CI, 2.51-7.30) and 3.01 (95% CI, 1.66-5.71) times the odds, respectively, of reporting doing discharge communication practices frequently compared to those who were not sure who was primarily responsible. To improve multidisciplinary discharge communication, residents called for the following among team members: (1) clarifying roles and responsibilities for communication with patients, (2) setting expectations for communication among multidisciplinary team members, and (3) redefining culture around discharges.

CONCLUSIONS

Residents report a lack of understanding of who is responsible for discharge education. This diffusion of ownership impacts how much residents invest in patient education, with more perceived responsibility associated with more frequent discharge communication.

Holiday Discharges Are Associated with Higher 30-Day General Internal Medicine Hospital Readmissions at an Academic Medical Center

OBJECTIVE

Academic medical centers face unique challenges in educating physician trainees in effective discharge practices to prevent readmissions. Meanwhile, residents must handle high workloads coupled with frequent rotations to different services. This study aimed to determine whether daily service census, service turnover, time of discharge, and day of discharge increase the risk of 30-day readmission.

METHODS

All of the discharges from two academic general internal medicine teaching services between October 1, 2013 and September 30, 2014 were included in this observational data analysis. Variables were fit to a 30-day, all-cause readmission outcome using multiple logistic regression with inverse probability of treatment weighting and multiple imputations with chained equations. The following potential confounding variables were included in the model: health system utilization, demographics, laboratory values, and comorbidities.

RESULTS

Among 1935 total discharges, 258 patients (13.3%) were readmitted within 30 days of the index discharge. Turnover, service census, weekend discharge, and time of discharge were not significantly associated with the risk of readmission. Patients discharged during holiday periods had higher odds of readmission (odds ratio 2.56, 95% confidence interval 2.01-3.25), whereas patients discharged on an intern switch day had lower odds of readmission (odds ratio 0.33, 95% confidence interval 0.27-0.41).

CONCLUSIONS

Patients who are discharged during holiday periods are at a higher risk of readmission after adjusting for potential confounders. These results also suggest that discharge on an intern switch day had a protective effect on readmission. Further work is needed to examine whether these findings can be replicated, and, if confirmed, to determine to what extent these associations are causal.

Interhospital Transfer: Transfer Processes and Patient Outcomes

Though often undertaken to provide patients with specialized care, interhospital transfer (IHT) is associated with worse outcomes for select patients. Certain aspects of the transfer process have been suggested as contributors to these outcomes. We performed a retrospective cohort study including patients ≥ 18 years who underwent IHT to a tertiary care hospital between January 2005 and September 2013. We examined the association between "weekend" transfer, "nighttime" transfer, "time delay" between transfer acceptance and arrival, and admission team "busyness" on the day of transfer, and patient outcomes, including transfer to the intensive care unit (ICU) within 48 hours and 30-day mortality. We utilized multivariable logistic regression models, adjusting for patient characteristics. Secondary analyses examined detailed timing of transfer and evaluated 30-day mortality stratified by service of transfer. Among the 24,352 patients who underwent IHT, the nighttime transfer was associated with increased adjusted odds of ICU transfer (odds ratio [OR] 1.54; 95% CI 1.38, 1.72) and 30-day mortality (OR 1.16; 95% CI 1.01, 1.35). Secondary analyses confirmed the association between nighttime transfer and ICU transfer throughout the week and demonstrated that Sunday (and trend towards Friday) night transfers had increased 30-day mortality, as compared with Monday daytime transfer. Stratified analyses demonstrated a significant association between transfer characteristics and adjusted odds of 30-day mortality among cardiothoracic and gastrointestinal surgical service transfers. Our findings suggest high acuity patients have worse outcomes during off-peak times of transfer and during times of high care team workload. Further study is needed to identify underlying reasons to explain these associations and devise potential solutions.

The relationship between workload and length of stay in Singapore

Prior studies link higher workload with longer length of stay (LOS) in the US. Unlike U.S. hospitals, Singaporean hospitals, like other major hospitals in the Asia-Pacific, are partially occupied by patients with non-acute needs due to insufficient alternative facilities. We examined the association between workload and length of stay (LOS) and the impact of workload on 30-day re-hospitalization and inpatient mortality rates in retrospective cohort in this setting. We defined workload as the daily number of patients per physician team. 13,097 hospitalizations of 10,000 patients were included. We found that higher workload was associated with shorter LOS (coefficient, -0.044 [95%CI, -0.083, -0.01]), especially for patients with longer stays (hazard ratios, not significantly greater than 1 before Day 4, 1.04 [95%CI, 1.01, 1.07] at Day 4 and 1.16 [95%CI, 1.10, 1.24] at Day 10), without affecting inpatient mortality (odds ratio (OR), 1.03 [95%CI, 0.99, 1.05]) or 30-day re-hospitalization (OR, 1.01 [95%CI, 0.99, 1.04]). This result differs from studies in the US and may reflect regional differences in the use of acute hospital beds for non-acute needs.

Hospital Readmissions Following Physician Call System Change: A Comparison of Concentrated and Distributed Schedules

BACKGROUND

Physician call schedules are a critical element for medical practice and hospital efficiency. We compared readmission rates prior to and after a change in physician call system at Sunnybrook Health Sciences Centre.

METHODS

We studied patients discharged over a decade (2004 through 2013) and identified whether or not each patient was readmitted within the subsequent 28 days. We excluded patients discharged for a surgical, obstetrical, or psychiatric diagnosis. We used time-to-event analysis and time-series analysis to compare rates of readmission prior to and after the physician call system change (January 1, 2009).

RESULTS

A total of 89,697 patients were discharged, of whom 10,001 (11%) were subsequently readmitted and 4280 died. The risk of readmission was increased by about 26% following physician call system change (9.7% vs 12.2%, P <.001). Time-series analysis confirmed a 26% increase in the readmission rate after call system change (95% confidence interval, 22%-31%; P <.001). The increase in readmission rate after call system change persisted across patients with diverse ages, estimated readmission risks, and medical diagnoses. The net effect was equal to 7240 additional patient days in the hospital following call system change. A modest increase was observed at a nearby acute care hospital that did not change physician call system, and no increase in risk of death was observed with increased hospital readmissions.

CONCLUSION

We suggest that changes in physician call systems sometimes increase subsequent hospital readmission rates. Further reductions in readmissions may instead require additional resources or ingenuity.