Preventable Hospital Readmissions Research Articles

Preventing Readmissions in Children: How Do We Do That?

It is frankly unbelievable that we know so little about preventing hospital readmissions in children despite (1) 60 years of readmission study and discussion across the world1; (2) national endorsement of measurement and reduction of readmissions by esteemed entities such as the National Quality Forum, the Centers for Medicare and Medicare Services, and the Agency for Healthcare Research and Quality2–4; (3) computer software designed to measure preventable readmissions5; and (4) financial penalties to hospitals (including children’s hospitals) with too many readmissions.6–8 There has been tremendous fervor about readmissions in adult patients, but this fervor does not sizzle at the same amplitude in children. To begin with, children (in general) have lower readmission rates than adults.9–12 Furthermore, in children, there is neither a wealth of data correlating quality of discharge care with readmission nor a clear understanding of best practices to prevent readmissions.13–15 So what’s the big deal with readmissions in children? Should we even care about them? Of course we should. First, many children do have a problem with discharge care (eg, incorrect dosing of a medication) that negatively affects their health after discharge. The burden placed on a family (and the accompanying stress) to remedy problems and issues regarding a child’s health after discharge can be devastating. The experience of worsening health after discharge and returning for another hospitalization is always an unwelcome occurrence in the life of a child. Readmissions, like all hospitalizations, are expensive, and they expose children to the dangers of the hospital environment (eg, nosocomial pathogens, adverse events). Finally, some children, especially those with medical complexity, have readmission rates that are as high as or higher than those for adult patients.10 Central to the issue of readmissions …

Preventing Hospital Readmissions and Limiting the Complications Associated With Total Joint Arthroplasty.

Total joint arthroplasty is a highly successful surgical procedure for patients with painful arthritic joints. The increasing prevalence of the procedure is generating significant expenditures in the American healthcare system. Healthcare payers, specifically the Center for Medicare and Medicaid Services, currently target total joint arthroplasty as an area for healthcare cost-savings initiatives, resulting in increased scrutiny surrounding orthopaedic care, health resource utilization, and hospital readmissions. Identifying the complications associated with total hip and total knee arthroplasty that result in readmissions will be critically important for predictive modeling and for decreasing the number of readmissions following total joint arthroplasty. Additionally, improving perioperative optimization, providing seamless episodic care, and intensifying posthospital coordination of care may result in a decreasing number of unnecessary hospital readmissions. Identified modifiable risk factors that significantly contribute to poor clinical outcome following total joint arthroplasty include morbid obesity; poorly controlled diabetes and nutritional deficiencies; Staphylococcus aureus colonization; tobacco use; venous thromboembolic disease; cardiovascular disease; neurocognitive, psychological, and behavioral problems; and physical deconditioning and fall risk. Both clinical practice and research will be enhanced if there is standardization of defined total joint arthroplasty complications and utilization of stratification schemes to identify high-risk patients. Subsequently, clinical intervention would be warranted to address modifiable risk factors before proceeding with total joint arthroplasty.

Prognostic Value of Estimated Plasma Volume in Heart Failure

ObjectivesThe purpose of this study was to assess the prognostic value of the estimation of plasma volume or of its variation beyond clinical examination in a post-hoc analysis of EPHESUS (Eplerenone Post-Acute Myocardial Infarction Heart Failure Efficacy and Survival Study). BackgroundAssessing congestion after discharge is challenging but of paramount importance to optimize patient management and to prevent hospital readmissions. MethodsThe present analysis was performed in a subset of 4,957 patients with available data (within a full dataset of 6,632 patients). The study endpoint was cardiovascular death or hospitalization for heart failure (HF) between months 1 and 3 after post-acute myocardial infarction HF. Estimated plasma volume variation (ΔePVS) between baseline and month 1 was estimated by the Strauss formula, which includes hemoglobin and hematocrit ratios. Other potential predictors, including congestion surrogates, hemodynamic and renal variables, and medical history variables, were tested. An instantaneous estimation of plasma volume at month 1 was defined and also tested. ResultsMultivariate analysis was performed with stepwise logistic regression. ΔePVS was selected in the model (odds ratio: 1.01; p = 0.004). The corresponding prognostic gain measured by integrated discrimination improvement was significant (7.57%; p = 0.01). Nevertheless, instantaneous estimation of plasma volume at month 1 was found to be a better predictor than ΔePVS. ConclusionsIn HF complicating myocardial infarction, congestion as assessed by the Strauss formula and an instantaneous derived measurement of plasma volume provided a predictive value of early cardiovascular events beyond routine clinical assessment. Prospective trials to assess congestion management guided by this simple tool to monitor plasma volume are warranted.

High utilization of inpatient detoxification: predictors among US veterans

ABSTRACTBackground: Readmissions are among the most problematic and expensive problems in the treatment of substance use disorders. Objective: To evaluate the characteristics associated with four or more inpatient medically managed detoxification admissions in FY 2012, when all had post-discharge appointments within 7 days. Methods: A retrospective case control study. A total of 38 (6.0%) of 623 unique veterans had four or more detoxification admissions (high utilizers). A random sample of 42 was selected from the remaining 585 people (comparison group). In all, 264 detoxification and 70 hospital admissions for other reasons were reviewed. Results: The high utilizers had more alcohol use disorder (AUD, 82% versus 59%, p = 0.03) of significantly longer duration (mean 28.9 years [SD = 17] vs. 19.6 [SD = 13.4], p = 0.01). AUD increased the odds of being a high utilizer three-fold [OR = 3.0, 95% CI 1.1, 8.4], and every additional year of AUD, increased the number of admissions 1.3%, p = 0.0006. The high utilizers did not differ from the comparison group with regards to either number of hospitalizations for other reasons (mean 1.2 [SD = 1.9] vs. 0.57 [SD = 0.8], p = 0.06) or rate of 7 day post discharge appointments kept (46.9% vs. 49.3%, p = 0.82). Conclusions: High utilizers were a small percentage of patients (6.0%) who accounted for a disproportionate number (23%) of 977 detoxification admissions. They had greater disease severity as manifest by more years of AUD. They were not more likely to have hospitalizations for other reasons or less likely to keep post discharge appointments. These patients may warrant different services tailored to prevent hospital readmissions for detoxification.

Características diferenciales de los pacientes del Grupo Relacionado con el Diagnóstico (GRD) 541 que reingresan

ObjectiveHospital readmission is considered an adverse outcome, and the hospital readmission ratio is an indicator of health care quality. Published studies show a wide variability and heterogeneity, with large groups of patients with different diagnoses and prognoses. The aim of the study was to analyse the differences between patients readmitted and those who were not, in patients grouped into the diagnosis related group (DRG) 541. Material and methodA retrospective observational study was conducted on DRG 541 patients discharged in 2010. Readmission is defined as any admission into any hospital department, and for any reason at ≤30 days from discharge. An analysis was performed that included age, sex, day of discharge, month of discharge, number of diagnoses and drugs at discharge, respiratory depressant drugs, length of stay, requests for consultations/referrals, Charlson comorbidity index, feeding method, hospitalisations in the previous 6 months, albumin and haemoglobin levels and medical examinations within 30 days after discharge. ResultsOf the 985 patients included in the study, 189 were readmitted. On multivariate analysis, significant variables were: Haemoglobin -0.6g/dl (95% confidence interval [95%CI] −0.9 to −0.3), gastrostomy feeding odds ratio (OR) 5.6 (95%CI: 1.5 to 21.6), hospitalisations in previous 6 months OR 1.9 (95%CI: 1.3 to 2.8), visits to emergency department OR 17.4 (95%CI: 11.3 to 26.8), medical checks after discharge OR 0.4 (95%CI: 0.2 to 0.8). ConclusionsDRG 541 readmitting patients have some distinctive features that could allow early detection and prevent hospital readmission.

Acute electroconvulsive therapy followed by maintenance electroconvulsive therapy decreases hospital re-admission rates of older patients with severe mental illness.

Electroconvulsive therapy (ECT) is a highly effective treatment for patients with severe mental illness (SMI). Maintenance ECT (M-ECT) is required for many elderly patients experiencing severe recurrent forms of mood disorders, whereas M-ECT for schizophrenia patients is a poorly studied treatment. We report on the outcomes in aged patients with SMI: schizophrenia and severe affective disorders treated by M-ECT of varying duration to prevent relapse after a successful course of acute ECT. The study measured the effectiveness of M-ECT in preventing hospital readmissions and reducing admission days. A retrospective chart review of 42 consecutive patients comparing the number and length of psychiatric admissions before and after the start of M-ECT was used. We analyzed diagnoses, previous ECT treatments, number of ECT treatments, and number and length of psychiatric admissions before and after M-ECT. Mean age in our sample was 71.5 (6.9) years. Twenty-two (52%) patients experienced severe affective disorders and 20 (48%) experienced schizophrenia. Patients were administered 92.8 (85.9) M-ECT treatments. Average duration of the M-ECT course was 34 (29.8) months. There were on average 1.88 admissions before M-ECT and only 0.38 admissions in the M-ECT period (P < 0.001). Duration of mean hospitalization stay decreased from 215.9 to 12.4 days during the M-ECT (P < 0.01). Our findings suggest that acute ECT followed by M-ECT is highly effective in selected elderly patients with SMIs.

Using Disruptive Innovation to Improve Patient Care

Using Disruptive Innovation to Improve Patient Care

Predictive modeling of hospital readmissions using metaheuristics and data mining

This research studies the risk prediction of hospital readmissions using metaheuristic and data mining approaches. This is a critical issue in the U.S. healthcare system because a large percentage of preventable hospital readmissions derive from a low quality of care during patients’ stays in the hospital as well as poor arrangement of the discharge process. To reduce the number of hospital readmissions, the Centers for Medicare and Medicaid Services has launched a readmission penalty program in which hospitals receive reduced reimbursement for high readmission rates for Medicare beneficiaries. In the current practice, patient readmission risk is widely assessed by evaluating a LACE score including length of stay (L), acuity level of admission (A), comorbidity condition (C), and use of emergency rooms (E). However, the LACE threshold classifying high- and low-risk readmitted patients is set up by clinic practitioners based on specific circumstances and experiences. This research proposed various data mining approaches to identify the risk group of a particular patient, including neural network model, random forest (RF) algorithm, and the hybrid model of swarm intelligence heuristic and support vector machine (SVM). The proposed neural network algorithm, the RF and the SVM classifiers are used to model patients’ characteristics, such as their ages, insurance payers, medication risks, etc. Experiments are conducted to compare the performance of the proposed models with previous research. Experimental results indicate that the proposed prediction SVM model with particle swarm parameter tuning outperforms other algorithms and achieves 78.4% on overall prediction accuracy, 97.3% on sensitivity. The high sensitivity shows its strength in correctly identifying readmitted patients. The outcome of this research will help reduce overall hospital readmission rates and allow hospitals to utilize their resources more efficiently to enhance interventions for high-risk patients.

Implementation of transitions-of-care services through acute care and outpatient pharmacy collaboration.

The implementation of a practice model designed to reduce hospital readmissions through optimal deployment of pharmacy staff on multidisciplinary care collaboration teams is described. In response to Affordable Care Act provisions aimed at reducing preventable hospital readmissions, the pharmacy department at The Johns Hopkins Hospital (JHH) led the implementation of a new pharmacy services model spanning both inpatient and outpatient settings. Key components of the model include (1) increased pharmacist participation in multidisciplinary rounds, (2) targeted medication reconciliation and patient education, (3) postdischarge phone monitoring of selected patients, and (4) bedside discharge medication delivery performed by a "transitions pharmacist extender." Incorporation of care coordination activities into the daily workflow has increased the rate of patient education on high-risk medications and allowed for affordable and effective medication regimens to be designed and prescriptions to be filled prior to patient discharge. The ultimate goal is enhanced multidisciplinary collaboration to decrease hospital readmissions by increasing medication adherence and patients' understanding of medications. The inpatient and outpatient pharmacy teams at JHH collaborated to improve their understanding of patients' medication use prior to admission through targeted medication reconciliation, education of patients on high-risk medications initiated during admission, and development of affordable and practical medication regimens that patients would receive in hand on discharge. A pharmacy team model was developed to ensure that these services are adequately provided and enhance patient understanding of the importance of medications for acute and chronic disease state management.

Risk Factors Associated with Unplanned Hospital Readmissions in Adults with Cancer.

To identify risk factors associated with 30-day unplanned hospital readmissions in adults with cancer. Case-control study. A teaching hospital in an urban center in the Mid-Atlantic region of the United States. 302 adults with solid tumors. The Conceptual Model of Re-Hospitalization was used as a theoretic framework. Univariate logistic regression and multivariate logistic regression were conducted to identify risk factors for hospital readmission. Risk factors included patient, clinical, hospitalization, and discharge-planning characteristics. From November 2011 to November 2012, 29% of patients were readmitted within 30 days after discharge, and a higher percentage of those readmissions occurred within the first week of discharge. Several predictors for hospital readmission were identified in the univariate logistic analysis, but the most relevant in the final multivariate logistic model were moderate to high risk for falls and advanced stage disease (metastatic). Hospital readmission is an indicator of quality care. Learning about risk factors allows opportunities to prevent hospital readmission by identifying those at high risk and implementing optimal discharge-planning systems and early referrals to palliative care. Oncology nurses are best positioned to develop strategic plans aimed at improving discharge planning and transitions of care that will decrease unplanned hospital readmissions.

New Drugs You Are Going to Read About: Serelaxin, Ularitide, TRV027.

Nitrovasodilators have long been used as first-line treatment for hypertensive acute heart failure (AHF). Although effective for BP control and symptom alleviation, this class of agents has never been shown to improve mortality or prevent hospital readmissions. Consequently, there has been tremendous interest in development of newer vasodilators with more beneficial therapeutic profiles. In this review, we focus on three of the most promising agents currently being studied: serelaxin, ularitide, and TRV027. While regulatory approval has yet to be obtained, should they prove beneficial in on-going trials, we are looking at a new era of drug therapy that could supplant more conventional treatments and broaden the horizon for management of patients with AHF.

A Model Home-Delivered Meals Program to Support Transitions from Hospital to Home

Meals On Wheels, Inc. of Tarrant County (MOWI) collaborated with local community-based organizations and hospitals to provide home-delivered meals and an evidence-based medication management intervention as a care transition service. The model program was designed to address risk factors commonly associated with preventable hospital readmissions. MOWI staff provided meals to 121 patients recently discharged from an inpatient hospitalization or emergency department visit from March 2013 through March 2014. A total of 18,010 meals were delivered to the 121 clients. On average, clients received 6.25 meals per week with meal delivery starting, on average, 8.95 days postdischarge. Ninety-three of the 121 clients also elected to receive the HomeMeds program. Client self-report of health care utilization (e.g., hospital readmission) at three months and six months was lower than expected given client characteristics. Positive changes in the Emergent Care Assessment and resolution of medication alerts provide additional evidence of a positive effect of the home-delivered meals program. More research is needed to document the benefits of home-based care supports following hospitalization.

576 Relationship Between Hospital Facility Characteristics and End-Stage Liver Disease Readmission Rates in California

infection on/during admission while 70% remained infection-free. During index hospitalization,77 died or went to hospice & 20 were transplanted. Therefore, 481 pts (age 56 yrs, 53% men,37% HCV) were available for analysis. Three month outcomes of these 481; 77% were alive without transplant, 11% were transplanted while 12% died. Readmissions: 50% of patients were readmitted at least once within 3 months; 56% had 1 readmission, 28% had 2, and 16% had ≥3 readmissions. Readmission rates were similar between those admitted with/without an infection (51% vs 50%,p=0.8) during the index hospitalization. Most readmissions were infection related (40%) followed by liver-related complications (17% anasarca, 11% GI bleed, 9% TIPS, 7% AKI, 5% HE) & 11% others. Two regression models were created; Model using index hospitalization day of admission values: A high MELD score (OR 1.1, p=0.001), lactulose use (corollary for HE; OR 1.6, p=0.05) & male gender (OR 1.6, p=0.05) predicted readmission while high serum albumin was protective (OR 0.57, p= 0.004). Infection as the reason for index admission, diabetes or admission WBC count did not impact 3-month readmissions. Model using index hospitalization discharge values: The only predictors of 3-month readmissions on discharge were MELD score (OR 1.1, p=0.002) and SBP prophylaxis use (OR 1.95, p=0.05). Nosocomial infections, diabetes, infections on admission and other medications were not significantly predictive. Conclusions: Readmissions occurred in 50% of hospitalized cirrhotics within 3 months of hospital discharge in this prospective multi-center study regardless of infections as their cause for index hospitalization. Without intervention, admitted cirrhotics are likely to require readmission, most commonly for infection related complications. Strategies to prevent hospital readmissions are urgently needed, especially in higher MELD patients with encephalopathy who have lower serum albumin and are on SBP prophylaxis.

Implementing a transitional care program to reduce hospital readmissions among older adults.

This research examines the early implementation of an evidence-based intervention, adapted from the Coleman Care Transitions Intervention and community-based models, aimed at reducing preventable hospital readmissions among older adults. To better understand program implementation, we conducted and analyzed in-depth interviews on the basis of the Promoting Action on Research Implementation in Health Services conceptual framework. Contextual factors, evidence support for the intervention, and facilitation techniques should be taken into account when implementing transitional care programs.

Process Evaluation of a Quality Improvement Project to Decrease Hospital Readmissions From Skilled Nursing Facilities

ObjectiveTo describe and evaluate the impact of quality improvement (QI) support provided to skilled nursing facilities (SNFs) by a Quality Improvement Organization (QIO). DesignRetrospective, mixed-method, process evaluation of a QI project intended to decrease preventable hospital readmissions from SNFs. SettingFive SNFs in Connecticut. ParticipantsSNF Administrators, Directors of Nursing, Assistant Directors of Nursing, Admissions Coordinators, Registered Nurses, Certified Nursing Assistants, Receptionists, QIO Quality Improvement Consultant. InterventionQIO staff provided training and technical assistance to SNF administrative and clinical staff to establish or enhance QI infrastructure and implement an established set of QI tools [Interventions to Reduce Acute Care Transfers (INTERACT) tools]. MeasurementsBaseline SNF demographic, staffing, and hospital readmission data; baseline and follow-up SNF QI structure (QI Committee), processes (general and use of INTERACT tools), and outcome (30-day all-cause hospital readmission rates); details of QIO-provided training and technical assistance; QIO-perceived barriers to quality improvement; SNF leadership-perceived barriers, accomplishments, and suggestions for improvement of QIO support. ResultsSuccess occurred in establishing QI Committees and targeting preventable hospital readmissions, as well as implementing INTERACT tools in all SNFs; however, hospital readmission rates decreased in only 2 facilities. QIO staff and SNF leaders noted the ongoing challenge of engaging already busy SNF staff and leadership in QI activities. SNF leaders reported that they appreciated the training and technical assistance that their institutions received, although most noted that additional support was needed to bring about improvement in readmission rates. ConclusionThis process evaluation documented mixed clinical results but successfully identified opportunities to improve recruitment of and provision of technical support to participating SNFs. Recommendations are offered for others who wish to conduct similar projects.

Providing patients with ISMP consumer leaflets can help prevent hospital readmissions.

Providing patients with ISMP consumer leaflets can help prevent hospital readmissions.

Preventing hospital readmissions: roll over or attack?

Preventing hospital readmissions: roll over or attack?

Abstract T P382: Urgent Primary Care Physician Follow up is Associated with Reduced Stroke Readmission after Acute Ischemic Stroke Hospitalization

Introduction: Readmission after acute ischemic stroke is common and costly, with an average rate of 14.8% within 30 days of discharge1. In 2010, as part of a hospital performance improvement strategy, ischemic stroke patients who were discharged to home had an urgent (within 7 days) appointment with Primary Care Physician (PCP) scheduled. We compared 30-day readmission rates for those who kept and did not keep their appointment. Methods: Data from an electronic medical record system was retrospectively evaluated. The cohort included all patients with hospital admission for ICD 9 diagnosis of ischemic stroke (433, 434, 435) during the years 2010 - 2013. Only those with a discharge disposition of home were included. Group 1 included patients discharged to home who kept follow up appointment. Group 2 included those who did not keep their scheduled appointment. Significant predictors of readmission such as age, heart failure, diabetes, LACE score were compared. Fisher’s Exact test was used for categorical variables. Results: A total of 349 ischemic stroke patients were discharged to home during the study period. Of these, 250 had appointments scheduled, and 167 (66.8%) kept these appointments (Group 1). The average age was 69.2 and 68.3 with average LACE of 9.7 and 9.5 for groups 1 and 2 respectively. There was no significant difference in rates of diabetes or heart failure between groups. There were 7 (3.6%) readmissions in group 1 and 19 of 83 (22.9%) in group 2. Five patients were readmitted prior to appointment time in group 2, so were not entered into final calculation; this left readmission rate of 14/83 (16%); p =0.004. Conclusion: Urgent follow up with PCP may prevent hospital readmission in those with mild strokes. Reverse causation, from missing appointment due to hospital readmission did not account for these results. Although NIHSS was not compared, our cohort consisted of those with mild symptoms, given home disposition. Further study is needed to determine which elements of the PCP follow up visit are most effective in reducing hospital readmission. Reference: 1. Lichtman, JH. Leifheit-Limson, EC. Predictors of Hospital Readmission after Stroke: A Systematic Review Stroke. 2010; 41(11): 2525-2533.

Aging in rural America.

For older Americans, accessing high-quality care can be a challenge. For those in rural communities, it's even harder.

Using a Small Workgroup to Jump-start a Community-Wide Coalition to Reduce Preventable Hospital Readmissions.

Unplanned hospital readmissions are common and often preventable. A review of Medicare discharge data identified a geographical area with higher than expected readmission rates. The state Medicare quality improvement organization (QIO) used community organizing techniques to assess provider engagement and hypothesized that a small workgroup of high impact providers could address some root causes for preventable readmissions, achieve quick wins, and reinvigorate the broader community-wide coalition. Seven of the eight facilities targeted by the QIO actively engaged and began rapid cycle initiatives to improve the patient transfer process between providers. Monthly, 2-hr structured meetings were supplemented by additional ad hoc meetings convened by participants. Effectiveness of the intervention was measured by workgroup functioning, the implementation of multiple initiatives spread from the small workgroup to the broader provider coalition, and reductions in readmissions to the anchor hospital system from the participating skilled nursing facilities. The community impact of the workgroup initiative is shown by a decline in community readmission rates for Medicare beneficiaries.