Predicting Patients at Risk for Prolonged Hospital Stays.

BACKGROUND: Patients with prolonged hospitalizations account for 14% of all hospital days in US hospitals. Predicting which medical patients are at risk for prolonged hospitalizations would allow early proactive management to reduce their length of stay. METHODS: Using the National Inpatient Sample, we examined risk factors for prolonged hospitalizations among adults hospitalized on the medicine service in 2014. We defined prolonged hospitalizations as those lasting 21 days or longer. We divided the sample into derivation and validation sets, and used logistic regression to identify significant risk factors in the derivation set, which were validated in the validation set. We used the estimates from the model to derive a risk score for prolonged hospitalizations. RESULTS: Our sample included 2,997,249 hospitalizations (median age of 66 y, 53.5% female). 1.2% of hospitalizations were 21 days or longer. Patients with prolonged hospitalizations were younger, and had a greater number of chronic diseases. A prolonged hospitalization risk score, derived from the many significant predictors in our model, performed well in discriminating between prolonged and nonprolonged hospitalizations, with c-statistics of 0.80 in both the derivation and validation sets. CONCLUSIONS: Our predictive model using readily available administrative data was able to discriminate between prolonged and nonprolonged hospitalizations in a national sample of medical patients, and performed well on internal validation. If prospectively validated, such a tool could be of use to hospitals and researchers interested in targeting development, testing, and/or deployment of programs to reduce length of stay.

Does Scheduling a Postdischarge Visit with a Primary Care Physician Increase Rates of Follow-up and Decrease Readmissions?

BACKGROUND: Driven in part by Medicare's Hospital Readmissions Reduction Program, hospitals are focusing on improving the transition from inpatient to outpatient care with particular emphasis on early follow-up with a primary care physician (PCP). OBJECTIVE: To assess whether the implementation of a scheduling assistance program changes rates of PCP follow-up or readmissions. DESIGN: Retrospective cohort study. SETTING: An urban tertiary care center PATIENTS: A total of 20,918 adult patients hospitalized and discharged home between September 2008 and October 2015. INTERVENTION: A postdischarge appointment service to facilitate early PCP follow-up. MAIN MEASURES: Primary outcomes were rates of follow-up visits with a PCP within seven days of discharge and hospital readmission within 30 days of discharge. Our first analysis assessed differences in outcomes among patients with and without the use of the service. In a second analysis, we exploited the fact that the service was not available on weekends and conducted an instrumental variable analysis that used the interaction between the intervention and day of the week of admission. RESULTS: In our multivariable analysis, use of the appointment service was associated with much higher rates of PCP follow-up (+31.9 percentage points, 95% CI: 30.2, 33.6; P < .01) and a decrease in readmission (-3.8 percentage points, 95% CI: -5.2, -2.4; P < .01). In the instrumental variable analysis, use of the service also increased the likelihood of a PCP follow-up visit (33.4 percentage points, 95% CI: 7.9, 58.9; P = .01) but had no significant impact on readmissions (-2.5 percentage points, 95% CI: -22.0, 17.0; P = .80). CONCLUSIONS: The postdischarge appointment service resulted in a substantial increase in timely PCP followup, but its impact on the readmission rate was less clear.

The Changing Distribution of Length of Hospitalization at Academic Medical Centers 2007-2016.

BACKGROUND: Length of stay (LOS) remains a primary focus for hospitals, and patients with prolonged LOS disproportionately affect hospital capacity and costs. We recently showed that long LOS patients are increasingly hospitalized at academic centers, but their effect on the distribution of LOS is unknown. METHODS: Using the Vizient Clinical Data Base/Resource Manager (CDB/RM), which includes over 90% of the academic medical centers in the United States, we examined trends in the distributions of LOS for acute medical/surgical hospitalizations from 2007 to 2016 in 117 hospitals. We excluded patients under 18 years and those with primary psychiatry, obstetric or rehabilitation diagnoses. RESULTS: Two separate trends were evident during this time period. Mean LOS decreased steadily from 2007 to 2010, but then rose steadily from 2011 and reached its maximum in 2016. Median LOS remained consistent at 3 days from 2007 to 2013 but it too rose from 2014 to 2016. As expected from the difference between the mean and median values, LOS at the 99th percentile dropped from 2007 to 2010 but then rose back by 2016. Gini coefficient values, used to measure inequalities in distribution, declined modestly from 2007 to 2010 but then remained unchanged through 2016. Results were similar in analyses adjusted for age, sex, and case-mix index. CONCLUSIONS: The beginning of the study period was characterized by a reduction in mean LOS, driven largely by decreases of the longest hospitalizations and greater uniformity in LOS. The latter portion saw steady increases in LOS that were similar across the entire distribution of hospitalizations. If the nadir in LOS has truly been reached, these trends will complicate the long-term health of academic medical centers and their staff, faculty, and trainees.

Preventability of early vs. late readmissions in an academic medical center.

BACKGROUND: It is unclear if the 30-day unplanned hospital readmission rate is a plausible accountability metric. OBJECTIVE: Compare preventability of hospital readmissions, between an early period [0-7 days post-discharge] and a late period [8-30 days post-discharge]. Compare causes of readmission, and frequency of markers of clinical instability 24h prior to discharge between early and late readmissions. DESIGN, SETTING, PATIENTS: 120 patient readmissions in an academic medical center between 1/1/2009-12/31/2010. MEASURES: Sum-score based on a standard algorithm that assesses preventability of each readmission based on blinded hospitalist review; average causation score for seven types of adverse events; rates of markers of clinical instability within 24h prior to discharge. RESULTS: Readmissions were significantly more preventable in the early compared to the late period [median preventability sum score 8.5 vs. 8.0, p = 0.03]. There were significantly more management errors as causative events for the readmission in the early compared to the late period [mean causation score [scale 1-6, 6 most causal] 2.0 vs. 1.5, p = 0.04], and these errors were significantly more preventable in the early compared to the late period [mean preventability score 1.9 vs 1.5, p = 0.03]. Patients readmitted in the early period were significantly more likely to have mental status changes documented 24h prior to hospital discharge than patients readmitted in the late period [12% vs. 0%, p = 0.01]. CONCLUSIONS: Readmissions occurring in the early period were significantly more preventable. Early readmissions were associated with more management errors, and mental status changes 24h prior to discharge. Seven-day readmissions may be a better accountability measure.

Postdischarge Clinics and Hospitalists: A Review of the Evidence and Existing Models.

Over the past 10 years, postdischarge clinics have been introduced in response to various health system pressures, including the focus on rehospitalizations and the challenges of primary care access. Often ignored in the discussion are questions of the effect of postdischarge physician visits on readmissions. In addition, little attention has been given to other clinical outcomes, such as reducing preventable harm and mortality. A review of dedicated, hospitalist-led postdischarge clinics, of the data supporting postdischarge physician visits, and of the role of hospitalists in these clinics may be instructive for hospitalists and health systems considering the postdischarge clinic environment. Journal of Hospital Medicine 2017;12:467-471.

Trends in Prolonged Hospitalizations in the United States from 2001 to 2012: A Longitudinal Cohort Study.

BACKGROUND: Health policy debate commonly focuses on frequently hospitalized patients, but less research has examined trends in long-stay patients, despite their high cost, effect on availability of hospital beds, and physical and financial implications for patients and hospitals. METHODS: Using the National Inpatient Sample, a nationally representative sample of acute care hospitalizations in the US, we examined trends in long-stay hospitalizations from 2001-2012. We defined long stays as those 21 days or longer and evaluated characteristics and outcomes of those hospitalizations, including discharge disposition and length of stay and trends in hospital characteristics. We excluded patients under 18 years of age and those with primary psychiatry, obstetric, or rehabilitation diagnoses, and weighted estimates to the US population. RESULTS: Prolonged hospitalizations represented only 2% of hospitalizations, but approximately 14% of hospital days and incurred estimated charges of over $20 billion dollars annually. Over time, patients with prolonged hospitalizations were increasingly younger, male, and of minority status, and these hospitalizations occurred more frequently in urban, academic hospitals. In-hospital mortality for patients with prolonged stays progressively decreased over the 10-year period from 14.5% to 11.6% (P <.001 for trend in grouped years), even accounting for changes in demographics and comorbidity. CONCLUSIONS: The profile of patients with prolonged hospitalizations in the US has changed, although their impact remains large, as they continue to represent 1 of every 7 hospital days. Their large number of hospital days and expense increasingly falls upon urban academic medical centers, which will need to adapt to this vulnerable patient population.

Physician Perspectives on Factors Contributing to Readmissions and Potential Prevention Strategies: A Multicenter Survey.

BACKGROUND: The transition out of the hospital is a vulnerable time for patients, relying heavily on communication and coordination of resources across care settings. Understanding the perspectives of inpatient and outpatient physicians regarding factors contributing to readmission and potential preventive strategies is crucial in designing appropriately targeted readmission prevention efforts. OBJECTIVE: To examine and compare inpatient and outpatient physician opinions regarding reasons for readmission and interventions that might have prevented readmission. DESIGN: Cross-sectional multicenter study. PARTICIPANTS: We identified patients readmitted to general medicine services within 30 days of discharge at 12 US academic medical centers, and surveyed the primary care physician (PCP), discharging physician from the index admission, and admitting physician from the readmission regarding their endorsement of pre-specified factors contributing to the readmission and potential preventive strategies. MAIN MEASURES: We calculated kappa statistics to gauge agreement between physician dyads (PCP-discharging physician, PCP-admitting physician, and admitting-discharging physician). KEY RESULTS: We evaluated 993 readmission events, which generated responses from 356 PCPs (36 % of readmissions), 675 discharging physicians (68 % of readmissions), and 737 admitting physicians (74 % of readmissions). The most commonly endorsed contributing factors by both PCPs and inpatient physicians related to patient understanding and ability to self-manage. The most commonly endorsed preventive strategies involved providing patients with enhanced post-discharge instructions and/or support. Although PCPs and inpatient physicians endorsed contributing factors and potential preventive strategies with similar frequencies, agreement among the three physicians on the specific factors and/or strategies that applied to individual readmission events was poor (maximum kappa 0.30). CONCLUSIONS: Differing opinions among physicians on factors contributing to individual readmissions highlights the importance of communication between inpatient and outpatient providers at discharge to share their different perspectives, and suggests that multi-faceted, broadly applied interventions may be more successful than those that rely on individual providers choosing specific services based on perceived risk factors.

Inpatient-outpatient transitions for patients with resident primary care physicians: access and readmission.

BACKGROUND: Transition from hospitalization to postdischarge care is a vulnerable period for patients. How the experience of this transition differs for patients with resident primary care physicians is unknown. METHODS: In a single, large academic primary care practice, we examined an inception cohort of consecutive hospitalizations and postdischarge visits of hospitalized patients with resident or faculty primary care physicians between 2008 and 2013. We compared patient demographics, readmission risk, and access to outpatient care between resident and faculty primary care physicians by using generalized estimating equations to account for repeated hospitalizations. RESULTS: We documented 8161 hospitalizations among patients with resident primary care physicians and 20,844 hospitalizations among patients with faculty primary care physicians. Hospitalized patients with resident primary care physicians were generally younger, more likely to be on Medicaid, and more likely to be African American (P < .001). Patients with resident primary care physicians were less likely to be seen within 7 and 30 days of discharge (adjusted relative risk, 0.83; 95% confidence interval [CI], 0.81-0.93 at 7 days; adjusted relative risk, 0.88; 95% CI, 0.85-0.92 at 30 days) and had an increased risk of readmission within 30 days (adjusted odds ratio, 1.25; 95% CI, 1.13-1.37). They also were considerably less likely to see their own provider at first follow-up (relative risk, 0.55; 95% CI, 0.52-0.59). CONCLUSIONS: Hospitalized patients with resident primary care physicians had lower rates of timely postdischarge follow-up, higher rates of readmission, and a lower likelihood of seeing their own provider than did patients with faculty primary care physicians. These findings highlight the challenges facing academic centers for patients with resident primary care physicians.

The characteristics and impact of a hospitalist-staffed post-discharge clinic.

BACKGROUND: Limited primary care access and care discontinuities hamper care for patients following hospital discharge. As the proportion of inpatient care delivered by hospitalists continues to increase, hybrid models that incorporate hospitalists in post-discharge care may ameliorate this problem. METHODS: We established a post-discharge clinic staffed by hospitalists in a large academic urban primary care practice in October 2009. We compared visits of recently hospitalized patients seen in the post-discharge clinic with post-discharge visits elsewhere in the practice, including patient demographics, health care utilization, and duration from discharge, using generalized estimating equations to account for repeated hospitalizations. RESULTS: Patients seen in the post-discharge clinic and elsewhere in the practice were generally similar, although patients seen in the post-discharge clinic were particularly likely to be black and receive primary care from residents. Relative to other patients seen following discharge, patients in the post-discharge clinic were seen 8.45 ± 0.43 days earlier (P <.001). Among all 10,845 discharges of Healthcare Associates patients between 2009 and 2011, patients were 40% more likely to be seen within a week of discharge when the post-discharge clinic was open than when it was closed (adjusted odds ratio 1.41; 95% confidence interval, 1.25-1.57). CONCLUSION: In this primary care practice, a hospitalist-staffed post-discharge clinic was associated with substantially shorter time to first post-hospitalization visit and with improvement in the overall likelihood of an early visit among all hospitalized patients. It was particularly used by black patients and those seen by residents, in whom access tends to be most fragmented, and may represent a novel approach to the problem of post-discharge care.