Hospital length of stay and readmission: an early investigation

Comparing Quality, Costs, and Outcomes of VA and Community Primary Care for Patients with Diabetes

BACKGROUND

The Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act expanded access to independent community providers outside the Veterans Health Administration (VA). Little is known how quality, costs, and outcomes of primary care received in the community compare to that of the VA.

OBJECTIVE

To compare quality, costs, and outcomes of community and VA-provided primary care for patients with diabetes over a 12-month episode.

DESIGN

A cross-sectional study using VA administrative data and community care claims. Adjusted analyses were conducted using inverse probability weighted regression adjustment to balance patient characteristics.

PARTICIPANTS

Veterans with diabetes receiving primary care in the VA or community.

MAIN MEASURES

Quality measures included receipt of hemoglobin A1C tests, eye exams, microalbumin urine tests, and flu shots. Outcomes were measured by hospitalizations for an ambulatory care sensitive condition (ACSC). Costs were measured for VA and community outpatient care, inpatient care, and prescription drugs.

KEY RESULTS

There were 652,648 VA patients and 3650 community care patients. VA patients were less likely to be White, had shorter mean drive time to VA primary care, and were less likely to be rural than community care patients. In adjusted analyses, community care patients had significantly lower probability of receiving a hemoglobin A1C test, eye exam, microalbumin urine test, and flu shot compared to the VA group. There was no difference in probability of an ACSC hospitalization. Community care patients had higher mean total costs ($1741 [95% CI, $431, $3052]), driven by higher inpatient and prescription drug costs but lower emergency care costs than VA patients.

CONCLUSION

Patients receiving community primary care had worse diabetes quality and higher costs than patients receiving VA primary care. There was no difference in health outcomes. Care provided by an integrated delivery system may have advantages in quality and value.

Acute hospitalizations and outcomes in Veterans Affairs Hospitals 2011 to 2017

Hospitals within the Veterans Affairs (VA) health care system exhibited growing use of observation care. It is unknown how this affected VA hospital performance since observation care is not included in acute inpatient measures. To examine changes in VA hospitalization outcomes and whether it was affected by shifting acute inpatient care to observation care. Longitudinal analysis of 986,355 acute hospitalizations and observation stays in 11 states 2011 to 2017. We estimated temporal changes in 30-day mortality, 30-day readmissions, costs, and length of stay (LOS) for all hospitalizations and 6 conditions in adjusted models. Changes in mortality and readmissions were compared including and excluding observation care. A 9% drop in acute hospitalizations was offset by a 157% increase in observation stays 2011 to 2017. A 30-day mortality decreased but readmissions did not when observation stays were included (all P < .05). Mean costs increased modestly; mean LOS was unchanged. There were differences by condition. VA hospital mortality decreased; there was no change in readmissions.

Predicting the risk of mortality and rehospitalization in heart failure patients: A retrospective cohort study by machine learning approach

BACKGROUND

Heart failure (HF) is a global problem, affecting more than 26 million people worldwide. This study evaluated the performance of 10 machine learning (ML) algorithms and chose the best algorithm to predict mortality and readmission of HF patients by using The Fasa Registry on Systolic HF (FaRSH) database.

HYPOTHESIS

ML algorithms may better identify patients at increased risk of HF readmission or death with demographic and clinical data.

METHODS

Through comprehensive evaluation, the best-performing model was used for prediction. Finally, all the trained models were applied to the test data, which included 20% of the total data. For the final evaluation and comparison of the models, five metrics were used: accuracy, F1-score, sensitivity, specificity and Area Under Curve (AUC).

RESULTS

Ten ML algorithms were evaluated. The CatBoost (CAT) algorithm uses a series of decision tree models to create a nonlinear model, and this CAT algorithm performed the best of the 10 models studied. According to the three final outcomes from this study, which involved 2488 participants, 366 (14.7%) of the patients were readmitted to the hospital, 97 (3.9%) of the patients died within 1 month of the follow-up, and 342 (13.7%) of the patients died within 1 year of the follow-up. The most significant variables to predict the events were length of stay in the hospital, hemoglobin level, and family history of MI.

CONCLUSIONS

The ML-based risk stratification tool was able to assess the risk of 5-year all-cause mortality and readmission in patients with HF. ML could provide an explicit explanation of individualized risk prediction and give physicians an intuitive understanding of the influence of critical features in the model.

Small airway dysfunction associated with poor short-term outcomes in patients undergoing thoracoscopic surgery for lung cancer

BACKGROUND

Although small airway dysfunction is a common respiratory dysfunction, its prognosis after lung cancer surgery is often neglected. This study investigated the relationship between small airway dysfunction and outcomes in patients who underwent thoracoscopic surgery for lung cancer.

METHODS

A retrospective cohort study of patients who underwent thoracoscopic surgery was conducted between December 2019 and March 2021 at Ningbo First Hospital. We used univariate and multivariate analyses to assess the possible associations between postoperative outcomes and clinical variables, including small airway dysfunction. To balance the potential confounding factors, propensity score matching was performed to establish 1:1 small airway dysfunction and small airway normal function group matching.

RESULTS

In this study, 1,012 patients undergoing thoracoscopic surgery for lung cancer were enrolled. Small airway dysfunction was present in 18.7% of patients (189/1,012). The incidence of postoperative pulmonary complications in the small airway dysfunction group was higher than that of the small airway normal function group (16.4% vs 6.2%, P < .001). The most significant postoperative pulmonary complications were pneumonia (7.4% vs 2.4%, P < .001) in the small airway dysfunction and normal function groups, respectively. In addition, a significantly prolonged median hospital length of stay was observed in the small airway dysfunction group compared to the small airway normal function group (median [interquartile range], 9 [7-12] vs 8 [7-9], P < .001). After 1:1 propensity score matching, 298 patients (149 pairs) were included in the comparison between small airway dysfunction and small airway normal function, and this association remained. Postoperative pulmonary complications (13.4% vs 6.0%, P = .032) were still higher, and length of stay (median [interquartile range] 9 [7-11] vs 8 [6-10] days, P = .001) was still longer in the small airway dysfunction group. Multivariate analysis indicated that small airway dysfunction was the independent risk factor associated with both postoperative pulmonary complications (odds ratio = 2.694, 95% confidence interval: 1.640-4.426, P < .001) and prolonged length of stay (beta = 1.045, standard error = 0.159, 95% confidence interval: 0.733-1.357, P < .001).

CONCLUSION

Our study showed that small airway dysfunction increased the incidence of postoperative pulmonary complications and prolonged length of stay in patients undergoing thoracoscopic surgery for lung cancer.

Virtual Multidisciplinary Rounds to Reduce Length of Stay, Decrease Variation, and Promote Accountability

PURPOSE

Evidence suggests in-person multidisciplinary rounds can help reduce length of stay (LOS) and improve throughput, but there are limited studies about the effectiveness of virtual multidisciplinary rounds on these measures. The authors hypothesized that virtual multidisciplinary rounds could help reduce LOS, improve throughput, promote accountability, and reduce provider variation.

METHODS

The research team designed and implemented virtual multidisciplinary rounds by a phone conference call with key stakeholders, including hospitalists, case managers, the clinical documentation improvement team, physical and occupational therapy, and nursing leaders. To track progress in real time, dashboards were created using data from electronic medical records. After several months, unit-based discharge huddles were also implemented to supplement the process and sustain the improvement.

RESULTS

The interventions led to more than 60% of discharges below geometric mean LOS after starting the initiative, compared to approximately 52% before the initiative. Mean observation hours went from around 44 hours to 31.9 hours, and the change was sustained for more than a year. In fiscal year 2021, 3,813 excess days were reduced in 10 months, resulting in combined savings of $6.7 million. A decrease in hospitalist provider variation is noted with the initiative, which is a crucial contributor to the results.

CONCLUSION

Virtual multidisciplinary rounds combined with other interventions can effectively reduce LOS and observation hours. Decreasing variation among hospitalists and improved key stakeholder engagement can be achieved with virtual multidisciplinary rounds. More studies to test the effectiveness of virtual multidisciplinary rounds in various patient care settings would provide more insights.

Impact of robotic surgery on patient flow and resource use intensity in ovarian cancer

There is an emerging focus on the role of robotic surgery in ovarian cancer. To date, the operational and cost implications of the procedure remain unknown. The objective of the current study was to evaluate the impact of integrating minimally invasive robotic surgery on patient flow, resource utilization, and hospital costs associated with the treatment of ovarian cancer during the in-hospital and post-discharge processes. 261 patients operated for the primary treatment of ovarian cancer between January 2006 and November 2014 at a university-affiliated tertiary hospital were included in this study. Outcomes were compared by surgical approach (robotic vs. open surgery) as well as pre- and post-implementation of the robotics platform for use in ovarian cancer. The in-hospital patient flow and number of emergency room visits within 3 months of surgery were evaluated using multi-state Markov models and generalized linear regression models, respectively. Robotic surgery cases were associated with lower rates of postoperative complications, resulted in a more expedited postoperative patient flow (e.g., shorter time in the recovery room, ICU, and inpatient ward), and were between $10,376 and $7,421 less expensive than the average laparotomy, depending on whether or not depreciation and amortization of the robotic platform were included. After discharge, patients who underwent robotic surgery were less likely to return to the ER (IRR 0.42, p = 0.02, and IRR 0.47, p = 0.055, in the univariate and multivariable models, respectively). With appropriate use of the technology, the addition of robotics to the medical armamentarium for the management of ovarian cancer, when clinically feasible, can bring about operational efficiencies and entails cost savings.

Association Rules Mining for Hospital Readmission: A Case Study

As an indicator of healthcare quality and performance, hospital readmission incurs major costs for healthcare systems worldwide. Understanding the relationships between readmission factors, such as input features and readmission length, is challenging following intricate hospital readmission procedures. This study discovered the significant correlation between potential readmission factors (threshold of various settings for readmission length) and basic demographic variables. Association rule mining (ARM), particularly the Apriori algorithm, was utilised to extract the hidden input variable patterns and relationships among admitted patients by generating supervised learning rules. The mined rules were categorised into two outcomes to comprehend readmission data; (i) the rules associated with various readmission length and (ii) several expert-validated variables related to basic demographics (gender, race, and age group). The extracted rules proved useful to facilitate decision-making and resource preparation to minimise patient readmission.

Asian Attitudes and Perceptions Toward Hospital-At-Home: A Cross-Sectional Study

Introduction: Hospital-at-Home (HaH) programmes are well-established in Australia, Europe, and the United States. However, there is limited experience in Asia, where the hospital is traditionally seen as a safe and trusted space for healing. This cross-sectional study aimed to explore attitudes and perceptions among patients and caregivers in Singapore toward this care model. Methods: A quantitative study design was adopted to collect data among patients and their caregivers from medical wards within two acute hospitals in Singapore. Using a series of closed-ended and open-ended questions, the investigator-administered survey aimed to explore barriers and facilitators determining patients' and caregivers' responses. The study questionnaire was pretested and validated. Data were summarised using descriptive statistics, and logistic regression was performed to determine key factors influencing patients' decisions to enrol in such programmes. Results: Survey responses were collected from 120 participants (101 patients, 19 caregivers; response rate: 76%), of which 87 respondents (72.5%) expressed willingness to try HaH if offered. Many respondents valued non-quantifiable programme benefits, including perceived gains in quality of life. Among them, reasons cited for acceptance included preference for the comfort of their home environment, presence of family members, and confidence toward remote monitoring modalities. Among respondents who were unwilling to accept HaH, a common reason indicated was stronger confidence toward hospital care. Discussion: Most patients surveyed were open to having acute care delivered in their home environment, and concerns expressed may largely be addressed by operational considerations. The findings provide useful insights toward the planning of HaH programmes in Singapore.

Acute-care hospital reencounters in COVID-19 patients

Acute-care hospital reencounters (ACHEs)—encompassing emergency department visits, observation stays, and hospital readmissions—following COVID-19 hospitalization may exacerbate health care system strain and impair recovery from illness. We sought to characterize these reencounters and factors associated with reencounters. We identified the first consecutive 509 patients hospitalized for COVID-19 within an IL hospital network, and examined ACHEs, experienced within 30 days and 4 months of index hospitalization. We identified independent predictors of reencounter using binary logistic regression. Of 509 patients, 466 (91.6%) were discharged alive from index COVID-19 hospitalization. Within 30 days and 4 months, 12.4% and 21.5% of patients, respectively, experienced ACHEs. The median time to first ACHE was 24.2 (IQR 6.5, 55) days. COVID-19 symptom exacerbation was the leading reason for early ACHE (44.8%). Reencounters, both within 30 days and 4 months, were associated with a history of a neurological disorder before COVID-19 (OR 2.78 [95% CI 1.53, 5.03] and OR 2.75 [95% CI 1.67, 4.53], respectively). Older patients and those with diabetes mellitus, chronic obstructive pulmonary disease, or organ transplantation tended towards more frequent ACHEs. Steroid treatment during COVID-19 hospitalization demonstrated reduced odds of 30-day reencounter (OR 0.31 [95% CI 0.091, 0.79]). Forty-nine patients had repeat SARS-CoV-2 nasopharyngeal testing during a reencounter; twelve (24.5%) patients had positive reencounter tests and experienced more frequent reencounters than those testing negative. COVID-19 symptom exacerbation is a leading cause of early ACHE after COVID-19 hospitalization, and steroid use during index hospitalization may reduce early reencounters. Neurologic illness before COVID-19 predicts ACHEs.

Factors Associated With Readmission in the United States Following Hospitalization With Coronavirus Disease 2019

BACKGROUND

Patients hospitalized for coronavirus disease 2019 (COVID-19) may experience complications following hospitalization and require readmission. In this analysis, we estimated the rate and risk factors associated with COVID-19-related readmission and inpatient mortality.

METHODS

In this retrospective cohort study, we used deidentified chargemaster data from 297 hospitals across 40 US states on patients hospitalized with COVID-19 from 15 February 2020 through 9 June 2020. Demographics, comorbidities, acute conditions, and clinical characteristics of first hospitalization are summarized. Multivariable logistic regression was used to measure risk factor associations with 30-day readmission and in-hospital mortality.

RESULTS

Among 29 659 patients, 1070 (3.6%) were readmitted. Readmitted patients were more likely to have diabetes, hypertension, cardiovascular disease (CVD), or chronic kidney disease (CKD) vs those not readmitted (P < .0001) and to present on first admission with acute kidney injury (15.6% vs 9.2%), congestive heart failure (6.4% vs 2.4%), or cardiomyopathy (2.1% vs 0.8%) (P < .0001). Higher odds of readmission were observed in patients aged >60 vs 18-40 years (odds ratio [OR], 1.92; 95% confidence interval [CI], 1.48-2.50) and those admitted in the Northeast vs West (OR, 1.43; 95% CI, 1.14-1.79) or South (OR, 1.28; 95% CI, 1.11-1.49). Comorbidities including diabetes (OR, 1.34; 95% CI, 1.12-1.60), CVD (OR, 1.46; 95% CI, 1.23-1.72), CKD stage 1-5 (OR, 1.51; 95% CI, 1.25-1.81), and CKD stage 5 (OR, 2.27; 95% CI, 1.81-2.86) were associated with higher odds of readmission; 12.3% of readmitted patients died during second hospitalization.

CONCLUSIONS

Among this large US population of patients hospitalized with COVID-19, readmission was associated with certain comorbidities and acute conditions during first hospitalization. These findings may inform strategies to mitigate risks of readmission due to COVID-19 complications.

Association between the timing of consultation-liaison psychiatry interventions and the length of stay in general hospital

BACKGROUND

Psychiatric comorbidities are frequent in patients admitted in general hospital and are associated with greater lengths of stay (LOS). Early consultation-liaison psychiatry (CLP) interventions may reduce the LOS but previous studies were underpowered to allow subgroup analyses and have generally not considered the severity of the condition for which patients were admitted ('disease severity').

AIMS

To investigate the association between the timing of CLP interventions and LOS in a general hospital.

METHOD

We retrospectively included 4500 consecutive patients admitted in non-psychiatric wards of a university hospital between 2008 and 2016 who had a first CLP intervention. We used general linear models to examine the association between the referral time, defined as log(days before the consultation)/log(LOS), and log(LOS), adjusting for age, gender, year of admission, place of residence, main psychiatric diagnosis, admission to the intensive care unit (ICU), main physical condition and disease severity.

RESULTS

Referral time was associated with log(LOS) (β = 0.31; P <0.001), notably for older patients (β = 0.43; P <0.001) and those admitted to the ICU (β = 0.50; P <0.001), but not for those with psychotic disorders (β = -0.20; P = 0.10). The association was confirmed when considering the expected LOS for each patient. For instance, for an expected LOS of 10 days, a CLP intervention on day 3 compared with day 6 was associated with a reduction of the actual LOS of 2.4 days.

CONCLUSIONS

Earlier CLP interventions were associated with a clinically significant shorter LOS in a large population even after adjusting for disease severity. Early CLP interventions may have benefits for both patients and health-related costs.

Effects of patients' hospital discharge preferences on uptake of clinical decision support

The Centers for Medicare and Medicaid Services identified unplanned hospital readmissions as a critical healthcare quality and cost problem. Improvements in hospital discharge decision-making and post-discharge care are needed to address the problem. Utilization of clinical decision support (CDS) can improve discharge decision-making but little is known about the empirical significance of two opposing problems that can occur: (1) negligible uptake of CDS by providers or (2) over-reliance on CDS and underuse of other information. This paper reports an experiment where, in addition to electronic medical records (EMR), clinical decision-makers are provided subjective reports by standardized patients, or CDS information, or both. Subjective information, reports of being eager or reluctant for discharge, was obtained during examinations of standardized patients, who are regularly employed in medical education, and in our experiment had been given scripts for the experimental treatments. The CDS tool presents discharge recommendations obtained from econometric analysis of data from de-identified EMR of hospital patients. 38 clinical decision-makers in the experiment, who were third and fourth year medical students, discharged eight simulated patient encounters with an average length of stay 8.1 in the CDS supported group and 8.8 days in the control group. When the recommendation was “Discharge,” CDS uptake of “Discharge” recommendation was 20% higher for eager than reluctant patients. Compared to discharge decisions in the absence of patient reports: (i) odds of discharging reluctant standardized patients were 67% lower in the CDS-assisted group and 40% lower in the control (no-CDS) group; whereas (ii) odds of discharging eager standardized patients were 75% higher in the control group and similar in CDS-assisted group. These findings indicate that participants were neither ignoring nor over-relying on CDS.

Triple Aim and the Hospital Readmission Reduction Program

Objectives:

Despite substantial attention on hospital readmission rates, the impact of the Hospital Readmission Reduction Program (HRRP) on a comprehensive set of Triple Aim goals has not been studied: improve hospital quality, reduce cost, and improve patient experience.

Methods:

We analyze inpatient claims data from 2006 to 2015 from the Dallas Fort Worth Hospital Council Foundation with a panel of 27,397 patients with chronic obstructive pulmonary disease and congestive heart failure. We deploy a quasi-natural experiment using a difference-in-difference specification to estimate the effect of HRRP effect on readmission rates, length of stay (LOS), and hospital satisfaction.

Results:

We find that the likelihood of 30-day readmissions declined by 2.6%, average LOS decreased by 7.9%, and overall hospital rating increased by 2.1% among hospitals that fell under the scope of the HRRP, compared to non-HRRP hospitals. Our results provide evidence of a spillover effect of the HRRP in terms of its impact not only on Medicare patients, but across all insurance types, and other performance measures such as cost and patient experience.

Conclusion:

Our findings indicate that HRRP hospitals do not trade-off reductions in readmission rates with lower quality across other patient health outcomes. Rather, we find evidence that the HRRP has affected all 3 dimensions of the Triple Aim with respect to patient and hospital outcomes.

Pharmacologically treated diabetes and hospitalization among older Norwegians receiving homecare services from 2009 to 2014: a nationwide register study

INTRODUCTION

The aim was to assess whether annual hospitalization (admissions, length of stay and total days hospitalized) among persons >65 years receiving home care services in Norway were higher for persons with diabetes than those without diabetes. Given the growing prevalence of diabetes, this issue has great importance for policy makers who must plan for meeting these needs.

RESEARCH DESIGN AND METHODS

Data were obtained from national Norwegian registries, and the study population varied from 112 487 to 125 593 per calendar year during 2009-2014. Diabetes was defined as having been registered with at least one prescription for blood glucose lowering medication. Overall and cause-specific hospitalization were compared, as well as temporal trends in hospitalization. Hospitalization outcomes for persons with and without diabetes were compared using log-binomial regression or quantile regression, adjusting for age and gender. Results are reported as incidence rate ratios (IRRs).

RESULTS

Higher total hospitalization rates (IRR 1.17; 95% CI 1.12 to 1.22) were found among persons with, versus without, diabetes, and this difference remained stable throughout the study period. Similar reductions over time in hospital length of stay were observed among persons with and without diabetes, but total annual days hospitalized decreased significantly (p=0.001) more among those with diabetes than among those without diabetes.

CONCLUSIONS

Among older recipients of home care services in Norway, diabetes was associated with a higher overall risk of hospitalization and increased days in the hospital. Given the growing prevalence of diabetes, it is important for policy makers to plan for meeting these needs.

Early outcomes of supratentorial cranial surgery for tumor resection in older patients

With longevity increasing in the United States, more older individuals are presenting with supratentorial brain tumors. Despite improved perioperative management, there is persistent disparity in surgical resection rates among patients aged 65 years or older. We aim to assess the effects of advanced age (≥65 years) on 30-day outcomes in patients with supratentorial tumors who underwent craniotomy for supratentorial tumor resection. Data obtained in adults who underwent supratentorial tumor resections was extracted from the prospectively-collected American College of Surgeons: National Surgical Quality Improvement Program (NSQIP; 2012-2018) database. Using multivariate regression, we compared odds of major and minor complications; prolonged length-of-stay (LOS); discharge anywhere other than home; and 30-day readmission, reoperation, and mortality rates between patients aged 18-64 years (the control cohort) and those 65-74 years or ≥75 years of age. Of the 14,234 patients who underwent craniotomy for supratentorial tumors and met inclusion criteria, 30.7% were ≥65 years of age; 71.4% of these were 65-74 years and 28.6% were ≥75 years old. Compared to the control group, both older subpopulations had more medical comorbidities. Both older subgroups had increased odds of major complications and prolonged LOS relative to the control group. Older patients had greater odds of mortality at 30 days. Advanced age, defined as ≥65 years, was significantly associated with higher odds of complications, prolonged LOS, and mortality within the 30-day post- operative period after adjusting for potential confounders. Age is one important consideration when prospectively risk-stratifying patients to minimize and mitigate suboptimal perioperative outcomes.

The trade-off between costs and outcome after cardiac surgery. Evidence from an Italian administrative registry

Effective resource allocation policies relating to the long-term effects of complex surgical procedures require accurate prediction of the likelihood of future hospitalization. By approximating clinical conditions with administrative data and controlling for complex case-mix scenarios, we provide evidence of a trade-off between costs and outcome in cardiac surgery. We modelled administrative data to account for clinical conditions in a population of patients admitted for cardiac surgery and their readmissions for complications. Costs were calculated at first admission, the outcome variable was defined as time to readmission within six months post-discharge. Risk factors for readmission were defined as comorbidities and postoperative complications, derived by clinical judgement from the International Classification of Diseases. We predicted health outcome as a function of costs and other patient- and hospital-level features using a two-stage residual inclusion estimation method to tackle endogenous relationships applied to Cox proportional hazard models. We confirmed the trade-off and negative association between costs and hazard of readmission when controlling for all complex risk factors. Accurate matching of standard codes for diseases and procedures with clinical conditions may be a reliable methodology to assess time to readmissions and costs on a large population scale.

Machine Learning With Feature Domains Elucidates Candidate Drivers of Hospital Readmission Following Spine Surgery in a Large Single-Center Patient Cohort

BACKGROUND

Unplanned hospital readmissions constitute a significant cost burden in healthcare. Identifying factors contributing to readmission risk presents opportunities for actionable change to reduce readmission rates.

OBJECTIVE

To combine machine learning classification and feature importance analysis to identify drivers of readmission in a large cohort of spine patients.

METHODS

Cases involving surgical procedures for degenerative spine conditions between 2008 and 2016 were retrospectively reviewed. Of 11 150 cases, 396 patients (3.6%) experienced an unplanned hospital readmission within 30 d of discharge. Over 75 pre-discharge variables were collected and categorized into demographic, perioperative, and resource utilization feature domains. Random forest classification was used to construct predictive models for readmission from feature domains. An ensemble tree-specific method was used to quantify and rank features by relative importance.

RESULTS

In the demographics domain, age and comorbidity burden were the most important features for readmission prediction. Surgical duration and intraoperative oral morphine equivalents were the most important perioperative features, whereas total direct cost and length of stay were most important in the resource utilization domain. In supervised learning experiments for predicting readmission, the demographic domain model performed the best alone, suggesting that demographic features may contribute more to readmission risk than perioperative variables following spine surgery. A predictive model, created using only enriched features showing substantial importance, demonstrated improved predictive capacity compared to previous models, and approached the performance of state-of-the-art, deep-learning models for readmission.

CONCLUSION

This strategy provides insight into global patterns of feature importance and better understanding of drivers of readmissions following spine surgery.

Incidence of Unplanned 30-Day Readmissions in Adult Burn Patients in the United States

This study characterizes adult burn readmissions in the United States using a nationally representative hospital inpatient sample. Readmission rates, diagnoses, and risk factors are discussed. We analyzed the 2013 and 2014 Nationwide Readmission Database for adult burn patients. The data were weighted to estimate national 30-day readmission rates. Principal readmission diagnoses were sorted into burn-specific or other readmission categories. We used multivariable logistic regression to assess the effects of patient and hospital stay risk factors on readmissions. An estimated 42,957 U.S. adult burn patients were discharged between January and November of 2013 and 2014. Of these patients, an estimated 3203 had unscheduled readmissions within 30 days (all-cause readmission rate: 7.5%, 95% CI: 6.7-8.2). An estimated 55.4 per cent of unplanned readmissions were for burn-specific principal readmission diagnoses. Burn-specific readmission was associated with burn severity and increased with both patient age and the number of comorbidities. Patients whose length of stay was less than 1 day per % total body surface area (%TBSA) burned had higher readmission risk (Adjusted odds ratio = 2.10, 95% CI = 1.48-2.99). The results of logistic regression models were similar for burn-specific readmissions and all-cause readmissions. In a nationally representative sample of adult burn patients, 4.1 per cent had unplanned 30-day readmissions for burn-specific reasons; 7.5 per cent were readmitted for any reason. Patient comorbidities and discharge before 1 day per %TBSA from the hospital impact readmission risk. Healthcare providers can use this information to identify at-risk patients, modify their treatment plans, and prevent readmissions.

Impact of structured interdisciplinary bedside rounding on patient outcomes at a large academic health centre

Background

Effective communication between healthcare providers and patients and their family members is an integral part of daily care and discharge planning for hospitalised patients. Several studies suggest that team-based care is associated with improved length of stay (LOS), but the data on readmissions are conflicting. Our study evaluated the impact of structured interdisciplinary bedside rounding (SIBR) on outcomes related to readmissions and LOS.

Methods

The SIBR team consisted of a physician and/or advanced practice provider, bedside nurse, pharmacist, social worker and bridge nurse navigator. Outcomes were compared in patients admitted to a hospital medicine unit using SIBR (n=1451) and a similar control unit (n=770) during the period of October 2016 to September 2017. Multivariable negative binomial regression analysis was used to compare LOS and logistic regression analysis was used to calculate 30-day and 7-day readmission in patients admitted to SIBR and control units, adjusting for covariates.

Results

Patients admitted to SIBR and control units were generally similar (p≥0.05) with respect to demographic and clinical characteristics. Unadjusted readmission rates in SIBR patients were lower than in control patients at both 30 days (16.6% vs 20.3%, p=0.03) and 7 days (6.3% vs 9.0%, p=0.02) after discharge, while LOS was similar. After adjusting for covariates, SIBR was not significantly related to the odds of 30-day readmission (OR 0.81, p=0.07) but was lower for 7-day readmission (OR 0.70, p=0.03); LOS was similar in both groups (p=0.58).

Conclusion

SIBR did not reduce LOS and 30-day readmissions but had a significant impact on 7-day readmissions.

Impact of the Hospitalist System in Japan on the Quality of Care and Healthcare Economics

Objective The hospitalist system is considered successful with respect to the quality of care and cost effectiveness in the United States. Studies have consistently demonstrated an improved clinical efficiency with this system. In Japan, however, the efficacy of the hospitalist system has not yet been examined. As a "super-aged society", Japan has a high number of elderly patients with multiple comorbidities who may theoretically receive better care by the hospitalist system than by the conventional system. This study investigates the impact of the hospitalist system on the quality of care and healthcare economics in a Japanese population. Methods We analyzed 274 patients ≥65 years of age in whom the most resource-consuming diagnosis at admission was aspiration pneumonia over a 1-year period. We categorized patients as those managed by hospitalists and those managed by various departments (control group) and compared the groups. Propensity score matching was used to minimize selection bias. Results For matched pairs, the length of hospital stay in the hospitalist group was shorter than that in the control group. Care by the hospitalist system was associated with significantly lower hospital costs. The quality of care (rate of switching from intravenous to oral antibiotics, duration of antibiotics therapy, number of chest X-rays and blood tests during hospitalization) was also considered to be favorably impacted by the hospitalist system. There was no statistically significant difference in the mortality rate or readmission rate between the groups. Conclusion This study showed that the hospitalist system had a favorable impact on the quality of care and cost effectiveness, suggesting the potential utility of its implementation in the Japanese medical system.

What affects length of hospital stay? A case study from Malta

PURPOSE

Hospital length of stay (LOS) is not only a function of patient- and disease-related factors, but is also determined by other health system-wide variables. Managers and clinicians strive to achieve the best possible trade-off between patients' needs and efficient utilisation of hospital resources, while also embracing ethical decision making. The purpose of this paper is to explore the perceptions of the hospital's major stakeholders as to what affects the duration of LOS of inpatients.

DESIGN/METHODOLOGY/APPROACH

Using a data-triangulated case study approach, 50 semi-structured interviews were performed with management, doctors, nurses and patients. Additionally, the hospitals' standard operating procedures, which are pertinent to the subject, were also included in the thematic analysis.

FINDINGS

This study shows that LOS is a multi-dimensional construct, which results from a complex interplay of various inputs, processes and outcomes.

RESEARCH LIMITATIONS/IMPLICATIONS

The findings emerging from a single case study approach cannot be generalised across settings and contexts, albeit being in line with the current literature.

PRACTICAL IMPLICATIONS

The study concludes that a robust hospital strategy, which addresses deficient organisational processes that may unnecessarily prolong LOS, is needed. Moreover, the hospital's strategy must be sustained by providing good primary care facilities within the community set-up, as well as by providing more long-term care and rehabilitation beds to support the hospital turnover.

ORIGINALITY/VALUE

The subject of LOS in hospitals has so far been tackled in a fragmented manner. This paper provides a comprehensive and triangulated account of the complexities surrounding the duration in which patients are kept in hospital by key stakeholders, most of whom were hands-on in the day-to-day running of the hospital under study.

The Impact of Pharmacy-specific Predictors on the Performance of 30-Day Readmission Risk Prediction Models

RESEARCH OBJECTIVE

Pharmacists are an expensive and limited resource in the hospital and outpatient setting. A pharmacist can spend up to 25% of their day planning. Time spent planning is time not spent delivering an intervention. A readmission risk adjustment model has potential to be used as a universal outcome-based prioritization tool to help pharmacists plan their interventions more efficiently. Pharmacy-specific predictors have not been used in the constructs of current readmission risk models. We assessed the impact of adding pharmacy-specific predictors on performance of readmission risk prediction models.

STUDY DESIGN

We used an observational retrospective cohort study design to assess whether pharmacy-specific predictors such as an aggregate pharmacy score and drug classes would improve the prediction of 30-day readmission. A model of age, sex, length of stay, and admission category predictors was used as the reference model. We added predictor variables in sequential models to evaluate the incremental effect of additional predictors on the performance of the reference. We used logistic regression to regress the outcomes on predictors in our derivation dataset. We derived and internally validated our models through a 50:50 split validation of our dataset.

POPULATION STUDIED

Our study population (n=350,810) was of adult admissions at hospitals in a large integrated health care delivery system.

PRINCIPAL FINDINGS

Individually, the aggregate pharmacy score and drug classes caused a nearly identical but moderate increase in model performance over the reference. As a single predictor, the comorbidity burden score caused the greatest increase in model performance when added to the reference. Adding the severity of illness score, comorbidity burden score and the aggregate pharmacy score to the reference caused a cumulative increase in model performance with good discrimination (c statistic, 0.712; Nagelkerke R, 0.112). The best performing model included all predictors: severity of illness score, comorbidity burden score, aggregate pharmacy score, diagnosis groupings, and drug subgroups.

CONCLUSIONS

Adding the aggregate pharmacy score to the reference model significantly increased the c statistic but was out-performed by the comorbidity burden score model in predicting readmission. The need for a universal prioritization tool for pharmacists may therefore be potentially met with the comorbidity burden score model. However, the aggregate pharmacy score and drug class models still out-performed current Medicare readmission risk adjustment models.

IMPLICATIONS FOR POLICY OR PRACTICE

Pharmacists have a great role in preventing readmission, and therefore can potentially use one of our models: comorbidity burden score model, aggregate pharmacy score model, drug class model or complex model (a combination of all 5 major predictors) to prioritize their interventions while exceeding Medicare performance measures on readmission. The choice of model to use should be based on the availability of these predictors in the health care system.

Trauma transitional care coordination: A mature system at work

BACKGROUND

We have previously demonstrated effectiveness of a Trauma Transitional Care Coordination (TTCC) Program in reducing 30-day readmission rates for trauma patients most at risk. With program maturation, we achieved improved readmission rates for specific patient populations.

METHODS

TTCC is a nursing driven program that supports patients at high risk for 30-day readmission. The TTCC interventions include calls to patients within 72 hours of discharge, complete medication reconciliation, coordination of medical appointments, and individualized problem solving. Account IDs were used to link TTCC patients with the Health Services Cost Review Commission database to collect data on statewide unplanned 30-day readmissions.

RESULTS

Four hundred seventy-five patients were enrolled in the TTCC program from January 2014 to September 2016. Only 10.5% (n = 50) of TTCC enrollees were privately insured, 54.5% had Medicaid (n = 259), and 13.5% had Medicare (n = 64). Seventy-three percent had Health Services Cost Review Commission severity of injury ratings of 3 or 4 (maximum severity of injury = 4). The most common All Patient Refined Diagnosis Related Groups for participants were: lower-extremity procedures (n = 67, 14%); extensive abdominal/thoracic procedures (n = 40, 8.4%); musculoskeletal procedures (n = 37, 7.8%); complicated tracheostomy and upper extremity procedures (n = 29 each, 6.1%); infectious disease complications (n = 14, 2.9%); major chest/respiratory trauma, major small and large bowel procedures and vascular procedures (n = 13 each, 2.7%). The TTCC participants with lower-extremity injury, complicated tracheostomy, and bowel procedures had 6-point reduction (10% vs. 16%, p = 0.05), 11-point reduction (13% vs. 24%, p = 0.05), and 16-point reduction (11% vs. 27%, p = 0.05) in 30-day readmission rates, respectively, compared to those without TTCC.

CONCLUSION

Targeted outpatient support for high-risk patients can decrease 30-day readmission rates. As our TTCC program matured, we reduced 30-day readmission in patients with lower-extremity injury, complicated tracheostomy and bowel procedures. This represents over one million-dollar savings for the hospital per year through quality-based reimbursement.

LEVEL OF EVIDENCE

Therapeutic/care management, level III.

Performance of a Hospital Pathway for Patients With a New Single Brain Mass

PURPOSE:

To reduce care variation and improve the management of patients with newly identified single brain masses and no history of cancer, we implemented a dedicated admission protocol.

METHODS:

We reviewed records of 206 patients who presented to our emergency department between January 2010 and May 2016 with a new single brain mass but no history of cancer. Patients admitted before the protocol implementation were designated the pre-implementation group (PRE), and those admitted after implementation were designated the post-implementation group (POST).

RESULTS:

Ninety-six patients were in the PRE group and 110 in the POST group. Length of stay for POST patients was significantly shorter than for PRE patients (6 v 7 days, respectively; P = .042), and this effect was more robust after excluding the 66 patients who were discharged to rehabilitation, skilled nursing, or hospice facilities (5 v 7 days, respectively; P = .001). Additional comparison of POST with PRE patients showed that time to surgery was significantly reduced (2.7 v 3.5 days, respectively; P = .006) and that computed tomography scans of the chest, abdomen, and pelvis were reduced (12% v 47%, respectively; P < .001). No difference was found in the 30-day readmission rates. For patients with GBM, there also was no significant difference in time to initiation of chemoradiation or in median overall survival.

CONCLUSION:

Implementation of a specialized admission pathway for patients with a new single brain mass decreased average length of hospital stay and time to surgery and reduced unnecessary diagnostic imaging tests in patients with primary brain tumors.

Racial/Ethnic Disparities in Readmissions in US Hospitals: The Role of Insurance Coverage

We examine differences in rates of 30-day readmissions across patients by race/ethnicity and the extent to which these differences were moderated by insurance coverage. We use hospital discharge data of patients in the 18 years and above age group for 5 US states, California, Florida, Missouri, New York, and Tennessee for 2009, the latest year prior to the start of Centers for Medicare & Medicaid Services’ Hospital Compare program of public reporting of hospital performance on 30-day readmissions. We use logistic regression models by state to estimate the association between insurance status, race, and the likelihood of a readmission within 30 days of an index hospital admission for any cause. Overall in 5 states, non-Hispanic blacks had a slightly higher risk of 30-day readmissions relative to non-Hispanic whites, although this pattern varied by state and insurance coverage. We found higher readmission risk for non-Hispanic blacks, compared with non-Hispanic whites, among those covered by Medicare and private insurance, but lower risk among uninsured and similar risk among Medicaid. Hispanics had lower risk of readmissions relative to non-Hispanic whites, and this pattern was common across subgroups with private, Medicaid, and no insurance coverage. Uninsurance was associated with lower risk of readmissions among minorities but higher risk of readmissions among non-Hispanic whites relative to private insurance. The study found that risk of readmissions by racial ethnic groups varies by insurance status, with lower readmission rates among minorities who were uninsured compared with those with private insurance or Medicare, suggesting that lower readmission rates may not always be construed as a good outcome, because it could result from a lack of insurance coverage and poor access to care, particularly among the minorities.

Age stratified analysis of pre-operative factors impacting unplanned thirty day readmission in geriatric general surgery

BACKGROUND

The geriatrics population can no longer be considered as one homogenous group when it comes to patient-centric and value-based care. We aim to determine if there are pre-operative factors which differ between geriatric age strata (65-74, 75-84, 85 + years) that impact unplanned thirty-day readmission.

METHODS

2015 NSQIP general surgery procedure data was utilized. Chi Square and t-tests were utilized to see if certain pre-operative factors impacted readmission. Regressions with age strata as an interaction term were run to determine if age was an effect-modifier. Significant pre-operative factors were included in a multivariate model with step-wise selection for significant age-stratification interaction terms.

RESULTS

Gender, inpatient status, wound classification, disseminated cancer, origin status, functional status, and RVU were significantly impacted by age strata in unadjusted models. Gender, inpatient status, emergency, and transfer/origin status were significant in our adjusted model.

CONCLUSIONS

Exogenous variables between age strata significantly impact unplanned thirty-day readmission in comparison to differing co-morbidity and symptomatology.

Risk Factors for Prolonged Length of Hospital Stay and Readmissions After Laparoscopic Sleeve Gastrectomy and Laparoscopic Roux-en-Y Gastric Bypass

Background

Laparoscopic sleeve gastrectomy (LSG) and laparoscopic gastric bypass (LRYGB) are most commonly performed bariatric procedures. Laparoscopic approach and enhanced recovery after surgery (ERAS) protocols managed to decrease length of hospital and morbidity. However, there are patients in whom, despite adherence to the protocol, the length of stay (LOS) remains longer than targeted. This study aimed to assess potential risk factors for prolonged LOS and readmissions.

Methods

The study was a prospective observation with a post-hoc analysis of bariatric patients in a tertiary referral university teaching hospital. Inclusion criteria were undergoing laparoscopic bariatric surgery. Exclusion criteria were occurrence of perioperative complications, prior bariatric procedures, and lack of necessary data. The primary endpoints were the evaluations of risk factors for prolonged LOS and readmissions.

Results

Median LOS was 3 (2–4) days. LOS > 3 days occurred in 145 (29.47%) patients, 79 after LSG (25.82%) and 66 after LRYGB (35.48%; p = 0.008). Factors significantly prolonging LOS were low oral fluid intake, high intravenous volume of fluids administered on POD0, and every additional 50 km distance from habitual residence to bariatric center. The risk of hospital readmission rises with occurrence of intraoperative adverse events and low oral fluid intake on the day of surgery on.

Conclusions

Risk factors for prolonged LOS are low oral fluid intake, high intravenous volume of fluids administered on POD0, and every additional 50 km distance from habitual residence. Risk factors for hospital readmission are intraoperative adverse events and low oral fluid intake on the day of surgery.

Readmissions Among Sepsis Survivors: Risk Factors and Prevention

Hospital readmissions are common and result in increased mortality and cost while reducing quality of life. Readmission rates have been subjected to increasing scrutiny in recent years as part of a larger effort to improve the quality and value of healthcare in the United States. Emerging evidence suggests that sepsis survivors are at high risk for hospital readmission and experience readmission rates comparable to survivors of congestive heart failure, acute myocardial infarction, pneumonia, and chronic obstructive pulmonary disease, diseases whose readmission rates determine reimbursement penalties from the federal government. In this article, we review the unique challenges that sepsis survivors face as well as the patient-level and hospital-level risk factors that are known to be associated with hospital readmission after sepsis survival. Additionally, we identify the causes and outcomes of readmissions in this population before concluding with a discussion of readmission prevention strategies and future directions.

HIV and early hospital readmission: evaluation of a tertiary medical facility in Lilongwe, Malawi

BACKGROUND

Delivery of quality healthcare in resource-limited settings is an important, understudied public health priority. Thirty-day (early) hospital readmission is often avoidable and an important indicator of healthcare quality.

METHODS

We investigated the prevalence of all-cause early readmission and its associated factors using age and sex adjusted risk ratios (RR) and 95% confidence intervals (CI). A retrospective review of the medical ward database at Kamuzu Central Hospital in Lilongwe, Malawi was conducted between February and December 2013.

RESULTS

There were 3547 patients with an index admission of which 2776 (74.4%) survived and were eligible for readmission. Among these patients: 49.7% were male, mean age was 39.7 years, 36.1% were HIV-positive, 34.6% were HIV-negative, and 29.3% were HIV-unknown. The prevalence of early hospital readmission was 5.5%. Diagnoses associated with 30-day readmission were HIV-positive status (RR = 2.41; 95% CI: 1.64-3.53) and malaria (RR = 0.45; 95% CI: 0.22-0.91). Other factors associated with readmission were multiple diagnoses (excluding HIV) (RR = 1.52; 95% CI: 1.11-2.06), and prolonged length of stay (≥ 16 days) at the index hospitalization (RR = 3.63; 95% CI: 1.72-7.67).

CONCLUSION

Targeting HIV-infected inpatients with multiple diagnoses and longer index hospitalizations may prevent early readmission and improve quality of care.

Association between re-admission rate and hospital characteristics for ischemic heart disease

OBJECTIVE

Hospital re-admission is considered an important marker of patient health outcomes and healthcare system performance. Korea introduced the Korean Diagnosis Procedure Combination (KDPC) for all regional public hospitals in July 2012. This study examined re-admission rates within 30 days to assess whether the hospital payment system is associated with the re-admission rate, focusing on ischemic heart disease.

METHODS

A cross-sectional study was conducted using national claims data for 2013. We analyzed data of patients with a major diagnosis of ischemic heart disease who were admitted to general hospitals with more than 500 beds in Korea. Of the eight general hospitals, two that have been operating under the new Korean payment system were public hospitals using the KDPC, and the remaining six were private general hospitals with fee for service (FFS) systems. Multiple logistic regression analysis was used to identify associations between re-admission rate and hospital characteristics.

RESULTS

The study analyzed 4,290 cases (889 cases in KDPC and 3,401 cases in FFS). The 30-day unplanned re-admission rate was higher in KDPC than in FFS (7.9% vs 5.6%, respectively). The unplanned re-admission odds ratios of KDPC was 1.74.

CONCLUSIONS

KDPC had higher 30-day unplanned re-admissions rates than did FFS.

Managing chronic conditions care across primary care and hospital systems: lessons from an Australian Hospital Avoidance Risk Program using the Flinders Chronic Condition Management Program

Objective The study aimed to determine the impact of the Flinders Chronic Condition Management Program for chronic condition self-management care planning and how to improve its use with Bendigo Health’s Hospital Admission Risk Program (HARP). Methods A retrospective analysis of hospital admission data collected by Bendigo Health from July 2012 to September 2013 was undertaken. Length of stay during admission and total contacts post-discharge by hospital staff for 253 patients with 644 admissions were considered as outcome variables. For statistical modelling we used the generalised linear model. Results The combination of the HARP and Flinders Program was able to achieve significant reductions in hospital admissions and non-significant reduction in emergency department presentations and length of stay. The generalised linear model predicted that vulnerable patient groups such as those with heart disease (P = 0.037) and complex needs (P < 0.001) received more post-discharge contacts by HARP staff than those suffering from diabetes, renal conditions and psychosocial needs when they lived alone. Similarly, respiratory (P < 0.001), heart disease (P = 0.015) and complex needs (P = 0.050) patients had more contacts, with an increased number of episodes than those suffering from diabetes, renal conditions and psychosocial needs. Conclusion The Flinders Program appeared to have significant positive impacts on HARP patients that could be more effective if high-risk groups, such as respiratory patients with no carers and respiratory and heart disease patients aged 0–65, had received more targeted care. What is known about the topic? Chronic conditions are common causes of premature death and disability in Australia. Besides mental and physical impacts at the individual level, chronic conditions are strongly linked to high costs and health service utilisation. Hospital avoidance programs such as HARP can better manage chronic conditions through a greater focus on coordination and integration of care across primary care and hospital systems. In support of HARP, self-management interventions such as the Flinders Program aim to help individuals better manage their medical treatment and cope with the impact of the condition on their physical and mental wellbeing and thus reduce health services utilisation. What does this paper add? This paper sheds light on which patients might be more or less likely to benefit from the combination of the HARP and Flinders Program, with regard to their impact on reductions in hospital admissions, emergency department presentations and length of stay. This study also sheds light on how the Flinders Program could be better targeted towards and implemented among high-need and high-cost patients to lessen chronic disease burden on Australia’s health system. What are the implications for practitioners? Programs targeting vulnerable populations and applying evidence-based chronic condition management and self-management support achieve significant reductions in potentially avoidable hospitalisation and emergency department presentation rates, though sex, type of chronic condition and living situation appear to matter. Benefits might also accrue from the combination of contextual factors (such as the Flinders Program, supportive service management, clinical champions in the team) that work synergistically.

Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease

Background and objective

Patients hospitalized for acute exacerbation of chronic obstructive pulmonary disease (COPD) have a high 30-day hospital readmission rate, which has a large impact on the health care system and patients’ quality of life. The use of a prediction model to quantify a patient’s risk of readmission may assist in directing interventions to patients who will benefit most. The objective of this study was to calculate the rate of 30-day readmissions and evaluate the accuracy of the LACE index (length of stay, acuity of admission, co-morbidities, and emergency department visits within the last 6 months) for 30-day readmissions in a general hospital population of COPD patients.

Methods

All patients admitted with a principal diagnosis of COPD to Liverpool Hospital, a tertiary hospital in Sydney, Australia, between 2006 and 2016 were included in the study. A LACE index score was calculated for each patient and assessed using receiver operator characteristic curves.

Results

During the study period, 2,662 patients had 5,979 hospitalizations for COPD. Four percent of patients died in hospital and 25% were readmitted within 30 days; 56% of all 30-day readmissions were again due to COPD. The most common reasons for readmission, following COPD, were heart failure, pneumonia, and chest pain. The LACE index had moderate discriminative ability to predict 30-day readmission (C-statistic =0.63).

Conclusion

The 30-day hospital readmission rate was 25% following hospitalization for COPD in an Australian tertiary hospital and as such comparable to international published rates. The LACE index only had moderate discriminative ability to predict 30-day readmission in patients hospitalized for COPD.

Using Length of Stay to Understand Patient Flow for Pediatric Inpatients

Objectives:

Develop and test a new metric to assess meaningful variability in inpatient flow.

Methods:

Using the pediatric administrative dataset, Pediatric Health Information System, that quantifies the length of stay (LOS) in hours, all inpatient and observation encounters with 21 common diagnoses were included from the calendar year 2013 in 38 pediatric hospitals. Two mutually exclusive composite groups based on diagnosis and presence or absence of an ICU hospitalization termed Acute Care Composite (ACC) and ICU Composite (ICUC), respectively, were created. These composites consisted of an observed-to-expected (O/E) LOS as well as an excess LOS percentage (ie, the percent of day beyond expected). Seven-day all-cause risk-adjusted rehospitalizations was used as a balancing measure. The combination of the ACC, the ICUC, and the rehospitalization measures forms this new metric.

Results:

The diagnosis groups in the ACC and the ICUC included 113,768 and 38,400 hospitalizations, respectively. The ACC had a median O/E LOS of 1.0, a median excess LOS percentage of 23.9% and a rehospitalization rate of 1.7%. The ICUC had a median O/E LOS of 1.1, a median excess LOS percentage of 32.3%, and rehospitalization rate of 4.9%. There was no relationship of O/E LOS and rehospitalization for either ACC or ICUC.

Conclusions:

This metric shows variation among hospitals and could allow a pediatric hospital to assess the performance of inpatient flow.

Does It Pay to Penalize Hospitals for Excess Readmissions? Intended and Unintended Consequences of Medicare's Hospital Readmissions Reductions Program

To incentivize hospitals to provide better quality care at a lower cost, the Affordable Care Act of 2010 included the Hospital Readmissions Reduction Program (HRRP), which reduces payments to hospitals with excess 30-day readmissions for Medicare patients treated for certain conditions. We use triple difference estimation to identify the HRRP's effects in Virginia hospitals; this method estimates the difference in changes in readmission over time between patients targeted by the policy and a comparison group of patients and then compares those difference-in-differences estimates in patients treated at hospitals with readmission rates above the national average (i.e., those at risk for penalties) and patients treated at hospitals with readmission rates below or equal to the national average (those not at risk). We find that the HRRP significantly reduced readmission for Medicare patients treated for acute myocardial infarction (AMI). We find no evidence that hospitals delay readmissions, treat patients with greater intensity, or alter discharge status in response to the HRRP, nor do we find changes in the age, race/ethnicity, health status, and socioeconomic status of patients admitted for AMI. Future research on the specific mechanisms behind reduced AMI readmissions should focus on actions by healthcare providers once the patient has left the hospital. Copyright © 2016 John Wiley & Sons, Ltd.

Using decision trees to explore the association between the length of stay and potentially avoidable readmissions: A retrospective cohort study

BACKGROUND

There is a growing concern that reduction in hospital length of stay (LOS) may raise the rate of hospital readmission. This study aims to identify the rate of avoidable 30-day readmission and find out the association between LOS and readmission.

METHODS

All consecutive patient admissions to the internal medicine services (n = 5,273) at King Abdullah University Hospital in Jordan between 1 December 2012 and 31 December 2013 were analyzed. To identify avoidable readmissions, a validated computerized algorithm called SQLape was used. The multinomial logistic regression was firstly employed. Then, detailed analysis was performed using the Decision Trees (DTs) model, one of the most widely used data mining algorithms in Clinical Decision Support Systems (CDSS).

RESULTS

The potentially avoidable 30-day readmission rate was 44%, and patients with longer LOS were more likely to be readmitted avoidably. However, LOS had a significant negative effect on unavoidable readmissions.

CONCLUSIONS

The avoidable readmission rate is still highly unacceptable. Because LOS potentially increases the likelihood of avoidable readmission, it is still possible to achieve a shorter LOS without increasing the readmission rate. Moreover, the way the DT model classified patient subgroups of readmissions based on patient characteristics and LOS is applicable in real clinical decisions.

Rehabilitation as "destination triage": a critical examination of discharge planning

PURPOSE

In this paper we examine how the intersection of various social and political influences shapes discharge planning and rehabilitation practices in ways that may not meet the espoused aims of rehabilitation programs or the preferences of older adults and their families.

METHODS

Taking a critical bioethics perspective, we used microethnographic case study methods to examine discharge-planning processes in a well-established older adult inpatient rehabilitation setting in Canada. The data included observations of discharge-planning family conferences and semi-structured interviews conducted with older adults facing discharge, their family members and rehabilitation professionals involved in discharge planning.

RESULTS

From the time of admission, a contextual push to focus on discharge superseded program aims of providing interventions to increase older adults' functional capabilities. Professionals' primary commitment to safety limited consideration of discharge options and resulted in costly and potentially unnecessary recommendations for 24-hour care. The resulting "rehabilitation" stay was more akin to an extended process of "destination triage" biased towards the promotion of physical safety than optimizing functioning.

CONCLUSIONS

The resulting reduction of rehabilitation into "destination triage" has significant social, financial and occupational implications for older adults and their families, and broader implications for healthcare services and overarching healthcare systems. Implications for Rehabilitation Current trends promoting consideration of discharge planning from the point of admission and prioritizing physical safety are shifting the focus of rehabilitation away from interventions to maximize recovery of function, which are the stated aims of rehabilitation. Such practices furthermore promote assessments to determine prognosis early in the rehabilitation stay when accurate prognosis is difficult, which can lead to overly conservative recommendations for discharge from rehabilitation services, thus further negating the impact of rehabilitation. Further work is required to examine the social, occupational and functional implications of superseding rehabilitation interventions to maximize capabilities with practices that prioritize safety over quality of life for older adults and their family members.

Hospital length of stay and all-cause 30-day readmissions among high-risk Medicaid beneficiaries

This study examined the association between index hospitalization characteristics and the risk of all-cause 30-day readmission among high-risk Medicaid beneficiaries using multilevel analyses. A retrospective cohort with a baseline and a follow-up period was used. The study population consisted of Medicaid beneficiaries (21-64 years old) with selected chronic conditions, continuous fee-for-service enrollment through the observation period, and at least 1 inpatient encounter during the follow-up period (N = 15,806). The outcome of 30-day readmission was measured using inpatient admissions within 30-days from the discharge date of the first observed hospitalization. Key independent variables included length of stay, reason for admission, and month of index hospitalization (seasonality). Multilevel logistic regression that accounted for beneficiaries nested within counties was used to examine this association, after controlling for patient-level and county-level characteristics. In this study population, 16.7% had all-cause 30-day readmissions. Adults with greater lengths of stay during the index hospitalization were more likely to have 30-day readmissions (adjusted odds ratio [AOR]: 1.03, 95% confidence interval [CI]: 1.02-1.04). Adults who were hospitalized for cardiovascular conditions (AOR: 1.20, 95% CI: 1.08-1.33), diabetes (AOR: 1.23, 95% CI: 1.10-1.39), cancer (AOR: 1.55, 95% CI: 1.26-1.90), and mental health conditions (AOR: 2.17, 95% CI: 1.98-2.38) were more likely to have 30-day readmissions compared to those without these conditions.

Isolated sacral injuries: Postoperative length of stay, complications, and readmission

AIM: To investigate inpatient length of stay (LOS), complication rates, and readmission rates for sacral fracture patients based on operative approach.

METHODS: All patients who presented to a large tertiary care center with isolated sacral fractures in an 11-year period were included in a retrospective chart review. Operative approach (open reduction internal fixation vs percutaneous) was noted, as well as age, gender, race, and American Society of Anesthesiologists’ score. Complications included infection, nonunion and malunion, deep venous thrombosis, and hardware problems; 90-d readmissions were broken down into infection, surgical revision of the sacral fracture, and medical complications. LOS was collected for the initial admission and readmission visits if applicable. Fisher’s exact and non-parametric t-tests (Mann-Whitney U tests) were employed to compare LOS, complications, and readmissions between open and percutaneous approaches.

RESULTS: Ninety-four patients with isolated sacral fractures were identified: 31 (30.4%) who underwent open reduction and internal fixation (ORIF) vs 63 (67.0%) who underwent percutaneous fixation. There was a significant difference in LOS based on operative approach: 9.1 d for ORIF patients vs 6.1 d for percutaneous patients (P = 0.043), amounting to a difference in cost of $13590. Ten patients in the study developed complications, with no significant difference in complication rates or reasons for complications between the two groups (19.4% for ORIF patients vs 6.3% for percutaneous patients). Eight patients were readmitted, with no significant difference in readmission rates or reasons for readmission between the two groups (9.5% percutaneous vs 6.5% ORIF).

CONCLUSION: There is a significant difference in LOS based on operative approach for sacral fracture patients. Given similar complications and readmission rates, we recommend a percutaneous approach.

The relationship between duration of stay and readmissions in patients undergoing bariatric surgery

BACKGROUND

Hospital readmissions are a quality indicator in bariatric surgery. In recent years, duration of stay after bariatric surgery has trended down greatly. We hypothesized that a shorter postoperative hospitalization does not increase the likelihood of readmission.

METHODS

The University HealthSystem Consortium (UHC) is an alliance of academic medical centers and affiliated hospitals. The UHC's clinical database contains information on inpatient stay and returns (readmissions) up to 30 days after discharge. A multicenter analysis of outcomes was performed by the use of data from the January 2009 to December 2013 for patients 18 years and older. Patients were identified by bariatric procedure International Classification of Diseases, Ninth Revision, codes and restricted by diagnosis codes for morbid obesity.

RESULTS

A total of 95,294 patients met inclusion criteria. The mean patient age was 45.4 (±0.11) years, and 73,941 (77.6%) subjects were female. There were 5,423 (5.7%) readmissions within the study period. Patients with hospitalizations of 3 days and more than 3 days were twice and four times as likely to be readmitted than those with hospitalizations of one day, respectively (P < .001).

CONCLUSION

Patients with longer postoperative hospitalizations were more likely to be readmitted after bariatric surgery. Early discharge does not appear to be associated with increased readmission rates.

Why do patients keep coming back? Results of a readmitted patient survey

Hospital readmissions can negatively impact cost and patient outcomes. Predictors of 30-day readmissions have been primarily identified using medical claims data. Reported here are results of a patient survey developed as part of regular hospital quality assurance activities. Two-thirds of patients reported good discharge experiences but were still readmitted. One-third of patients discharged had a post-discharge doctor appointment scheduled; half were readmitted before that scheduled appointment. Results suggest post-discharge experiences could be improved, especially the timing of follow up doctor appointments. Identified weaknesses in the survey process highlight need for engagement of survey methodologists in efforts to understand patient experiences.