Decline In Readmission Rates Research Articles

Improving community care for patients discharged from hospital through zone-wide implementation of a seamless care transition policy.

BackgroundSeveral studies within the psychiatry literature have illustrated the importance of discharge planning and execution, as well as accessibility of outpatient follow-up post-discharge. We report the results of implementing a new seamless care transition policy to expedite post-discharge follow-up in the community Addiction and Mental Health (AMH) program in the Edmonton Zone, Alberta, Canada. The policy involved a distribution mechanism for assessment by a mental health therapist (MHT) within 7 days of discharge as well as a dedicated roster of community psychiatrists to accept newly discharged patients.ObjectiveOur aim was to assess the feasibility of this novel policy and to assess its effect on our outcome measures of wait time to first outpatient MHT assessment and re-admission rate to hospital.MethodsOur study involved a retrospective clinical audit with total sampling design and a comparison of data 1 year before (2015/2016 fiscal year) and 1 year after (2017/2018 fiscal year) the implementation of the seamless care policy within the Edmonton Zone. Extracted data were analyzed with simple descriptive statistics and presented as percentages, mean and median.ResultsOverall, with the enactment of this policy, follow-up volumes ultimately increased, while wait times for initial assessment decreased on average for patients discharged from the hospital. In the 2015/2016 fiscal year, MHT completed 128 assessments of post-discharge patients who were new to the community AMH program compared to 298 completed new assessments for the 2017/2018 fiscal year. The corresponding wait times for the new MHT assessments were 12.7 days (median of 12 days) and 7.8 days (median of 6 days), respectively. Similarly, psychiatrists completed only 59 assessments of post-discharge patients who were new to AMH compared to 133 new psychiatric assessments for the 2017/2018 fiscal year. The corresponding wait times for the new psychiatric assessments were 15.3 days (median of 14 days) and 8.8 days (median of 7 days), respectively. We correspondingly found a slight decline in readmission rates after the implementation of our model in the subsequent fiscal year.ConclusionWe envision that this policy will set a precedent with regard to streamlining post-discharge follow-up care for admitted inpatients, ultimately improving mental health outcomes for patients.

Retrospective Outcome Data for Transitional Care Management in the Hematologic Malignant Patient Population

Introduction In 2016, providers within an Academic Medical Center's Blood and Marrow Transplant (BMT) program recognized preventable readmissions related to missed opportunities in the hospital discharge process. In an effort to address discharge deficiencies and reduce readmissions, Transitional Care Management (TCM) was developed and implemented by BMT Transplant Coordinators in 2017. Methods Hospital discharge reports are generated in the electronic medical record (EMR). Communication within the EMR is sent to the clinical teams the business day following discharge with instruction to initiate a telephone encounter. The clinical team completes a telephone encounter in the EMR and documents review of discharge summary, medications, follow-up appointments, pertinent clinical trial review (if applicable), and symptoms following discharge. Results Retrospective analysis of readmission rates for patients with hematologic malignancies for the period of January 1, 2016, through December 31, 2018, show a decline in readmission rates since implementation of TCM. (30 day- 2016 25.11% vs 2018 23.89%, 14 day 18.14% vs 2018 16.39%, 7 day 2016-13.5% vs 2018 9.6%) Retrospective analysis of TCM completion by BMT coordinators for the period of January 1, 2017 through August 31, 2019, reveal a drastic improvement. Compliance of TCM documentation and completion averaged 88% in 2017, and 85% in 2018. Since utilization of EMR generated telephone encounter notification, 98% completion of the TCM process has been documented. Conclusion TCM has improved quality of care for patients with hematologic malignancies. BMT 30-day, 14-day and 7-day readmission rates have improved since TCM. Utilization of the transplant center's upgraded EMR improved functionality and increased compliance of the TCM documentation process.

Reducing 30-Day Readmissions Through Nursing Science: An Application of Transitions Theory With Best Practice Guidelines.

The Transition Management Model was developed by and for nurse care coordinators at an Independent Health Network to reduce Medicare and Medicaid 30-day readmission rates. Preimplementation assessment revealed the need for a nursing science framework to effectively reduce 30-day readmissions. The model was developed through thoughtful integration of transitions theory with best practice guidelines set forth by Project BOOST. Initial results of the Transition Management Model produced a decline in readmission rates by 11%. The Transition Management Model initiative can serve as an exemplar for the integration of transitions theory to best practice guidelines to effectively reduce 30-day readmissions.

Suboptimal Use of Inpatient Palliative Care Consultation May Lead to Higher Readmissions and Costs in End-Stage Liver Disease.

Background/Aims: Patients with end-stage liver disease (ESLD) have a high risk for readmission. We studied the role of palliative care consultation (PCC) in ESLD-related readmissions with a focus on health care resource utilization in the United States. Methods: We performed a retrospective longitudinal analysis on patients surviving hospitalizations with ESLD from January 2010 to September 2014 utilizing the Nationwide Readmissions Database with a 90-day follow-up after discharge. We analyzed annual trends in PCC among patients with ESLD. We matched PCC to no-PCC (1:1) using propensity scores to create a pseudorandomized clinical study. We estimated the impact of PCC on readmission rates (30- and 90-day), and length of stay (LOS) and cost during subsequent readmissions. Results: Of the 67,480 hospitalizations with ESLD, 3485 (5.3%) received PCC, with an annual increase from 3.6% to 6.7% (p for trend <0.01). The average 30- and 90-day annual readmission rates were 36.2% and 54.6%, respectively. PCC resulted in a lower risk for 30- and 90-day readmissions (hazard ratio: 0.42, 95% confidence interval [CI]: 0.38-0.47 and 0.38, 95% CI: 0.34-0.42, respectively). On subsequent 30- and 90-day readmissions, PCC was associated with decreased LOS (5.6- vs. 7.4 days and 5.7- vs. 6.9 days, p < 0.01) and cost (US $48,752 vs. US $75,810 and US $48,582 vs. US $69,035, p < 0.01). Conclusion: Inpatient utilization of PCC for ESLD is increasing annually, yet still remains low in the United States. More importantly, PCC was associated with a decline in readmission rates resulting in a lower burden on health care resource utilization and improvement in cost savings during subsequent readmissions.

Regression to the Mean in the Medicare Hospital Readmissions Reduction Program

Excess 30-day readmissions have declined substantially in hospitals initially penalized for high readmission rates under the Medicare Hospital Readmissions Reduction Program (HRRP). Although a possible explanation is that the policy incentivized penalized hospitals to improve care processes, another is regression to the mean (RTM), a statistical phenomenon that predicts entities farther from the mean in one period are likely to fall closer to the mean in subsequent (or preceding) periods owing to random chance. To quantify the contribution of RTM to declining readmission rates at hospitals initially penalized under the HRRP. This study analyzed data from Medicare Provider and Analysis Review files to assess changes in readmissions going forward and backward in time at hospitals with high and low readmission rates during the measurement window for the first year of the HRRP (fiscal year [FY] 2013) and for a measurement window that predated the FY 2013 measurement window for the HRRP among hospitals participating in the HRRP. Hospital characteristics are based on the 2012 survey by the American Hospital Association. The analysis included fee-for-service Medicare beneficiaries 65 years or older with an index hospitalization for 1 of the 3 target conditions of heart failure, acute myocardial infarction, or pneumonia or chronic obstructive pulmonary disease and who were discharged alive from February 1, 2006, through June 30, 2014, with follow-up completed by July 30, 2014. Data were analyzed from January 23, 2018, through March 29, 2019. Hospital Readmission Reduction Program penalties. The excess readmission ratio (ERR), calculated as the ratio of a hospital's readmissions to the readmissions that would be expected based on an average hospital with similar patients. Hospitals with ERRs of greater than 1.0 were penalized. A total of 3258 hospitals were included in the study. For the 3 target conditions, hospitals with ERRs of greater than 1.0 during the FY 2013 measurement window exhibited decreases in ERRs in the subsequent 3 years, whereas hospitals with ERRs of no greater than 1.0 exhibited increases. For example, for patients with heart failure, mean ERRs declined from 1.086 to 1.038 (-0.048; 95% CI, -0.053 to -0.043; P < .001) at hospitals with ERRs of greater than 1.0 and increased from 0.917 to 0.957 (0.040; 95% CI, 0.036-0.044; P < .001) at hospitals with ERRs of no greater than 1.0. The same results, with ERR changes of similar magnitude, were found when the analyses were repeated using an alternate measurement window that predated the HRRP and followed up hospitals for 3 years (for patients with heart failure, mean ERRs declined from 1.089 to 1.044 [-0.045; 95% CI, -0.050 to -0.040; P < .001] at hospitals with below-mean performance and increased from 0.915 to 0.948 [0.033; 95% CI, 0.029 to 0.037; P < .001] at hospitals with above-mean performance). By comparing actual changes in ERRs with expected changes due to RTM, 74.3% to 86.5% of the improvement in ERRs for penalized hospitals was explained by RTM. Most of the decline in readmission rates in hospitals with high rates during the measurement window for the first year of the HRRP appeared to be due to RTM. These findings seem to call into question the notion of an HRRP policy effect on readmissions.

Trends in Hospital Admissions for and Readmissions After Cardiac Implantable Electronic Device Procedures in the United States: An Analysis From 2010 to 2014 Using the National Readmission Database

ObjectiveTo evaluate inpatient trends in de novo complete cardiac implantable electronic device (CIED) procedures and subsequent all-cause 30-day readmissions in the United States. Patients and MethodsWe accessed the National Readmission Database to identify CIED implantation-related hospitalizations between January 1, 2010, and December 31, 2014, using International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes. In-hospital mortality and postprocedure all-cause 30-day readmissions were also analyzed. ResultsDuring the study period, a total of 800,250 CIED implantation hospitalizations were identified across the United States, with an in-hospital mortality rate of 0.9% (7423 of 800,250) and a 29% decrease in CIED-related index hospitalizations (188,086 in 2010 vs 134,276 in 2014). The all-cause 30-day readmission rate for the entire cohort was 13% (106,505 of 800,250), decreasing from 14% (26,134 of 188,085) in 2010 to only 13% (17,154 of 134,276) by 2014. Dual-chamber pacemakers were the most frequently implanted in-hospital CIEDs (473,615 of 800,250 [59%]). The most common cause for readmission was heart failure exacerbation, which remained unchanged over the study period. ConclusionOur data reveal a steady decline in overall in-hospital CIED implantations and only a modest decline in readmission rates. The cause for this decline may be an impact of medical and regulatory changes guiding CIED implantations, but it deserves further investigation.

Trends in unplanned readmissions over 15 years: a regional Australian perspective.

Objective The aim of this study was to assess 15-year trends in unplanned readmissions in an Australian regional health service. Methods Drawing on data held in the Illawarra Health Information Platform (IHIP), this longitudinal retrospective study of adults admitted to hospital between 2001-02 and 2015-16 assessed rates of unplanned all-cause readmissions within 30 days ('early') and 1-6 months ('late') following discharge. Rates were compared over time and between patient groups. Results Age-adjusted early readmission rates declined over the 15 years by an average of 1.3% per annum, whereas late readmission rates increased by an average of 0.6% per annum. Together, there was an overall decline in readmission rates. The entire decline in early readmission rates and a reversal of the increasing trend in late readmission rates occurred since 2010-11. Similar trends occurred across age groups, but were most pronounced among those aged ≥75 years. Conclusions The decline in readmissions since 2010-11 suggests that the region has achieved improvements in discharge planning and in continuity between hospitals and community-based care. These improvements have occurred across broad patient groups. The longitudinal and linked data held in the IHIP provides a unique opportunity to examine patterns of service utilisation at a regional level. What is known about the topic? Published reports of longitudinal trends in readmissions are typically limited by short study periods and narrow criteria used to define study populations and readmissions. Australian longitudinal data suggest rates of early readmission have remained relatively unchanged in recent years, despite the focus on readmission rates as a metric to assess the quality and continuity of care. What does this paper add? This unique longitudinal study reports on long-term readmission trends over 15 years to hospitals within a single geographic area, with trends reported for both early (30-day) and late (1- to 6-month) readmissions by age group and major diagnostic categories. The findings reflect more complex patterns than are typically reported in cross-sectional and more limited longitudinal studies. What are the implications for practitioners? The results suggest improvements at a regional level that may be associated with care during the initial hospitalisation and discharge (reflected particularly in early readmissions) and in the community (reflected particularly in late readmissions). Future investigations will explore specific patient groups and the effects of specific initiatives, services and models of care to better predict those at risk of readmission and to inform translation locally and further afield. The relationship between readmissions and the use of ambulatory services (primary care, emergency department and out-patient) also warrants further investigation.

Frequency of 30-Day Readmission and Its Causes After Endovascular Aneurysm Intervention of Abdominal Aortic Aneurysm (from the Nationwide Readmission Database)

Endovascular aneurysm intervention (EVAI) is one of the most commonly performed vascular interventions for abdominal aortic aneurysm (AAA). Data regarding 30-day readmission rates after EVAI are poorly reported in the literature. We used the United States Nationwide Readmission Database from 2010 to 2014 to identify all patients ≥18 years who were readmitted within 30 days after a hospital discharge for EVAI of the AAA. Incidence, etiologies, predictors of 30-day readmission, and trends of readmission rates were analyzed. In 138,014 patients who survived to discharge after an EVAI procedure for AAA, 14,146 (10.24%) were readmitted within 30 days. Median time to readmission was 11 days. Cardiac causes (16.34%) followed by infections (15.40%) and vascular complications (12.86%) were common etiologies of readmission. Greater patient age, female sex, coexisting co-morbidities such as heart failure, atrial fibrillation, peripheral vascular disease, lung disease, and chronic kidney disease were independent predictors of 30-day readmission. In-hospital complications during an index admission such as major bleeding or vascular complications were also predictive of 30-day readmission. Trend analysis showed a progressive decline in readmission rates from 11.3% in 2010 to 9.6% in 2014 (ptrend <0.0001), 20% lower odds in 2014 compared with 2010 (odds ratio 0.80, 95% confidence interval 0.72 to 0.87, p <0.0001). In this contemporary study of EVAI for AAA, nearly 1 in 10 patients was readmitted within 30 days of discharge after an index admission. Cardiac complications and infections were common causes of readmission within 30 days.

Long-term trends of use of health service among heart failure patients.

We aimed to identify subgroups in the patient population with different trajectories of long-term readmission rates. The study also aimed to assess common causes and their sequences of readmissions for each subgroup. Patients with a primary diagnosis of heart failure (HF) in the period 2008-09 were identified using nationally representative primary care data linked to national hospital data, which contain information on 10.5 million patients. Heart failure patients were followed up for 5 years. Group-based trajectory models and sequence analysis were applied. The model categorised the HF population (n = 9466) into five subgroups: low-impact (66.9%); two intermediate ones (27.4%); chronic high-impact (2.3%) with steady high annual readmission rates; and short-term high-impact (3.4%) with rapid decline in readmission rates. The groups were defined by their trends of yearly number of readmissions. The all-cause 5-year mortality was highest in the short-term high-impact group (n = 185, 72.8%), followed by Group 2 (intermediate users) (n = 744, 58.8%), low-impact (n = 4244, 56.9%), chronic high-impact (n = 88, 37.6%), and Group 1 (intermediate users) (n = 401, 30.3%) (P < 0.01). Compared with low-impact users, high-impact users were associated with higher mortality, bereavement episodes, and more out-of-hours general practitioner visits. The chronic high-impact users had distinct sequences of causes of emergency admissions most often consisting of chest infection, ischaemic heart disease, and cardio-pulmonary signs and/or symptoms. Chronic high-impact users constitute a small proportion of total patients, but they have increasingly high use of healthcare services. Short-term high-impact users represent largely end of life patients. They require prompt involvement of the palliative care team to reduce unnecessary readmissions to hospital.

Temporal Trends in Incidence, Sepsis-Related Mortality, and Hospital-Based Acute Care After Sepsis.

A growing number of patients survive sepsis hospitalizations each year and are at high risk for readmission. However, little is known about temporal trends in hospital-based acute care (emergency department treat-and-release visits and hospital readmission) after sepsis. Our primary objective was to measure temporal trends in sepsis survivorship and hospital-based acute care use in sepsis survivors. In addition, because readmissions after pneumonia are subject to penalty under the national readmission reduction program, we examined whether readmission rates declined after sepsis hospitalizations related to pneumonia. Retrospective, observational cohort study conducted within an academic healthcare system from 2010 to 2015. We used three validated, claims-based approaches to identify 17,256 sepsis or severe sepsis hospitalizations to examine trends in hospital-based acute care after sepsis. None. From 2010 to 2015, sepsis as a proportion of medical and surgical admissions increased from 3.9% to 9.4%, whereas in-hospital mortality rate for sepsis hospitalizations declined from 24.1% to 14.8%. As a result, the proportion of medical and surgical discharges at-risk for hospital readmission after sepsis increased from 2.7% to 7.8%. Over 6 years, 30-day hospital readmission rates declined modestly, from 26.4% in 2010 to 23.1% in 2015, driven largely by a decline in readmission rates among survivors of nonsevere sepsis, and nonpneumonia sepsis specifically, as the readmission rate of severe sepsis survivors was stable. The modest decline in 30-day readmission rates was offset by an increase in emergency department treat-and-release visits, from 2.8% in 2010 to a peak of 5.4% in 2014. Owing to increasing incidence and declining mortality, the number of sepsis survivors at risk for hospital readmission rose significantly between 2010 and 2015. The 30-day hospital readmission rates for sepsis declined modestly but were offset by a rise in emergency department treat-and-release visits.

Descriptive analysis of 30-day readmission after inpatient surgery discharge in the Veterans Health Administration.

For the first time to our knowledge, this study analyzes and reports the 30-day all-cause readmission rates for surgical procedures performed in the Veterans Health Administration (VHA). To analyze and report 30-day all-cause readmission rates following discharge from 9 surgical specialties in the VHA for a 10-year period. In a retrospective observational study, Veterans Affairs Surgical Quality Improvement Program data for surgery records and VHA administrative discharge data were linked to evaluate all-cause readmission within 30 days of discharge from the surgical inpatient stay. The study population represents 9 surgical specialty groups: general, urology, neurosurgery, orthopedic, otolaryngology, plastic, thoracic, peripheral vascular, and cardiac. Trends of postoperative hospital admission rates for each surgery were investigated using 10 years (fiscal years 2001-2010; N = 894,943) of linked data. All-cause 30-day readmission after surgery for each specialty. During the 10-year period, the overall 30-day all-cause readmission rate following inpatient surgery discharge significantly decreased from 12.9% to 12.2% (P < .001). Unadjusted readmission rates varied by surgical specialty: general, 12.5%; urology, 9.0%; neurosurgery, 10.5%; orthopedic, 9.6%; otolaryngology, 9.5%; plastic, 12.2%; thoracic, 14.4%; peripheral vascular, 16.0%; and cardiac, 16.6%. The following specialties were found to have a significant decline in readmission rates: orthopedic (P = .004), otolaryngology (P = .005), plastic (P = .02), thoracic (P = .04), peripheral vascular (P < .001), and cardiac (P = .003). Postoperative hospital length of stay in individual specialties decreased during this period (each P < .05) except for thoracic and cardiac surgery, which remained unchanged. Readmission diagnoses varied by specialty; postoperative infection was the most common readmission diagnosis in 7 specialties and the second most common in the other 2 specialties (urology and thoracic). Urinary tract infection and digestive system complications were also common readmission diagnoses. This retrospective observational study showed decreasing 30-day readmission rates associated with a decline in postoperative hospital length of stay for 9 surgical specialties in the VHA during a 10-year period. Further study will be required to capture data from patients who had surgery at a VHA facility but were readmitted in the private sector.