The Healthcare Cost and Utilization Project (HCUP) Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all payers and the uninsured. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in health care data - the lack of nationally representative information on hospital readmissions for all ages. Outcomes of interest include national readmission rates, reasons for returning to the hospital for care, and the hospital costs for discharges with and without readmissions. Unweighted, the NRD contains data from approximately 18 million discharges each year. Weighted, it estimates roughly 35 million discharges. Developed through a Federal-State-Industry partnership sponsored by the Agency for Healthcare Research and Quality, HCUP data inform decision making at the national, State, and community levels. The NRD is drawn from HCUP State Inpatient Databases (SID) containing verified patient linkage numbers that can be used to track a person across hospitals within a State, while adhering to strict privacy guidelines. The NRD is not designed to support regional, State-, or hospital-specific readmission analyses. The NRD contains more than 100 clinical and non-clinical data elements provided in a hospital discharge abstract. Data elements include but are not limited to: diagnoses, procedures, patient demographics (e.g., sex, age), expected source of payer, regardless of expected payer, including but not limited to Medicare, Medicaid, private insurance, self-pay, or those billed as ‘no charge, discharge month, quarter, and year, total charges, length of stay, and data elements essential to readmission analyses. The NIS excludes data elements that could directly or indirectly identify individuals. Restricted access data files are available with a data use agreement and brief online security training.

The Nationwide Readmissions Database (NRD) is a unique and powerful database designed to support various types of analyses of national readmission rates for all patients regardless of the expected payer for the hospital stay. The NRD includes discharges for patients with and without repeat hospital visits in a year and those who have died in the hospital. Repeat stays may or may not be related. The criteria to determine the relationship between hospital admissions is left to the analyst using the NRD. This database addresses a large gap in healthcare data - the lack of nationally representative information on hospital readmissions for all ages.

Characteristics and comorbidities of patients discharged alive after an index hospitalization for pneumonia between 2013–14 in the National Readmissions Database sample, overall and by age- group.

All numbers are percentages with SE in parenthesis unless specified otherwise.

BackgroundMedical management is recommended for uncomplicated type B aortic dissection (TBAD). However, data focused on sex differences in outcomes in TBAD patients managed medically are limited.MethodsHospitalizations of adults with TBAD were identified using the 2016–2019 Nationwide Readmissions Database. TBAD diagnosis was deduced by inclusion of thoracic or thoracoabdominal aorta dissection and exclusion of presumed type A aortic dissection. Hospitalizations associated with intervention were excluded. Multivariable logistic regression modeling was used to investigate the association of sex with in-hospital mortality. A Cox proportional hazards model was used to assess the association between sex and readmission rates.ResultsThere were 52,269 TBAD hospitalizations (58% male). Compared to men, women were older (72 vs. 65 years), had higher in-hospital mortality (11.5% vs. 8.5%), shorter median length of stay (3.95 vs. 4.23 days), and lower rates of elective admissions (6.4% vs. 8.2%) (all p 

Percentage of emergency admissions to any hospital in England occurring within 30 days of the last, previous discharge from hospital after admission: indirectly standardised by age, sex, method of admission and diagnosis/procedure. The indicator is broken down into the following demographic groups for reporting: ● All years and female only, male only and both male and female (persons). ● <16 years and female only, male only and both male and female (persons). ● 16+ years and female only, male only and both male and female (persons) ● 16-74 years and female only, male only and both male and female (persons) ● 75+ years and female only, male only and both male and female (persons) Results for each of these groups are also split by the following geographical and demographic breakdowns: ● Local authority of residence. ● Region. ● Area classification. ● NHS and private providers. ● NHS England regions. ● Deprivation (Index of Multiple Deprivation (IMD) Quintiles, 2019). ● Sustainability and Transformation Partnerships (STP) & Integrated Care Boards (ICB) from 2016/17. ● Clinical Commissioning Groups (CCG) & sub-Integrated Care Boards (sub-ICB). ● Treatment Functions. All annual trends are indirectly standardised against 2014/15.

HCUPnet is an on-line query system that provides free, instant access to the largest set of all-payer health care databases that are publicly available. Using HCUPnet's easy step-by-step query system, you can generate tables and graphs on statistics and trends for acute care hospitals in the U.S. HCUPnet provides:  National and regional estimates for inpatient stays and emergency department visits;  State counts of inpatient stays and emergency department visits for those states that agreed to participate;  National estimates on readmissions and readmission rates;  County-level statistics on hospital use and potentially preventable admissions, based on the AHRQ Quality Indicators (QIs)* For most queries, detailed information is available for conditions and procedures (by ICD-9-CM codes and Clinical Classification Software), and for diagnosis related groups (DRGs). HCUPnet allows easy access to information from datasets that are part of the Healthcare Cost and Utilization Project (HCUP); details on obtaining these datasets are also available in www.healthdata.gov

From 2007 through 2011, the national 30-day, all-cause, hospital readmission rate averaged 19 percent. During calendar year 2012, the readmission rate averaged 18.4 percent. Of the 306 HRRs, rates in 166 HRRs fell by between 1 and 5 percent, while rates dropped by more than 5 percent in 73 HRRs, with the largest reduction in Longview, Texas. Rates increased by more than 1 percent in only 30 HRRs, with the largest increase in Bloomington, Illinois. Readmission rates at hospitals participating in the P4P program have been, on average, consistently lower than the rates at non-participating hospitals within all size categories except for the very smallest and largest hospitals, but rates at both participant and non-participant hospitals fell in 2012.

● Region.

This dataset contains the statewide number and (unadjusted) rate for all-cause, unplanned, 30-day inpatient readmissions in California hospitals. Data are categorized by age, sex, race/ethnicity, expected payer and county.

Background There has been a relentless increase in emergency medical admissions in the UK over recent years. Many of these patients suffer with chronic conditions requiring continuing medical attention. We wished to determine whether conventional outpatient clinic follow up after discharge has any impact on the rate of readmission to hospital. Methods Two consultant general physicians with the same patient case-mix but markedly different outpatient follow-up practice were chosen. Of 1203 patients discharged, one consultant saw twice as many patients in the follow-up clinic than the other (Dr A 9.8% v Dr B 19.6%). The readmission rate in the twelve months following discharge was compared in a retrospective analysis of hospital activity data. Due to the specialisation of the admitting system, patients mainly had cardiovascular or cerebrovascular disease or had taken an overdose. Few had respiratory or infectious diseases. Outpatient follow-up was focussed on patients with cardiac disease. Results Risk of readmission increased significantly with age and length of stay of the original episode and was less for digestive system and musculo-skeletal disorders. 28.7% of patients discharged by Dr A and 31.5 % of those discharged by Dr B were readmitted at least once. Relative readmission risk was not significantly different between the consultants and there was no difference in the length of stay of readmissions. Conclusions Increasing the proportion of patients with this age- and case-mix who are followed up in a hospital general medical outpatient clinic is unlikely to reduce the demand for acute hospital beds.

Most statistically significant differences in readmitted and non-readmitted patients.

This indicator compares the odds of an emergency readmission within seven days for patients discharged on a particular day of the week to the odds of an emergency readmission within seven days for patients discharged on a Wednesday. Discharges with both emergency and non-emergency admission methods are included in the indicator. Results including only discharges where the patient was admitted in an emergency are also presented as contextual information. The results are presented as odds ratios, alongside the number of discharges, emergency readmissions and the crude readmission rate for each trust. The number of emergency readmissions is broken down into those where the readmission was to the same provider that the patient was discharged from and those where the readmission was to a different provider. From April 2020, the Department of Health and Social Care (DHSC) is no longer commissioning NHS Digital to produce these indicators. Therefore, no further publications in this series are planned. Notes: 1. There is a shortfall in the number of records for Tameside and Glossop Integrated Care NHS Foundation Trust (trust code RMP) and University College London Hospitals NHS Foundation Trust (trust code RRV) meaning that results for these trusts are based on incomplete data and should therefore be interpreted with caution. 2. From this publication onwards, the adjustment for deprivation uses the 2019 version of the Index of Multiple Deprivation (IMD). Previous releases of these indicators used the 2015 version. Further information is available in the statement of methodological changes (see Resources). 3. The following mergers took place on 1st October 2019: Cumbria Partnership NHS Foundation Trust (trust code RNN) merged with North Cumbria University Hospitals NHS Trust (trust code RNL). The new trust is called North Cumbria Integrated Care NHS Foundation Trust (trust code RNN). Aintree University Hospital NHS Foundation Trust (trust code REM) merged with Royal Liverpool and Broadgreen University Hospitals NHS Trust (trust code RQ6). The new trust is called Liverpool University Hospitals NHS Foundation Trust (trust code REM). Results are presented to reflect the updated organisational structure from this publication onwards. 4. Further information on data quality can be found in the Seven-day Services background quality report, which can be downloaded from the ‘Resources’ section of the publication page. Further guidance on the interpretation of the indicators is also available to download from that page.

Data source: Declaration data of medical service points of insurance medical service organizationNumerator: Number of non-planned readmission cases within 14 days after discharge from denominator cases.Denominator: Number of inpatient cases for childbirth at the same hospital in the same season.Calculation formula: (Numerator / Denominator) x 100%

Objective: This study utilized a large, national US database to explore the impact of CMV infection on hospital services utilization and costs during the first 100 days following allogeneic hematopoietic stem cell transplant (allo-HSCT). Methods: This retrospective, observational cohort study used data from the Premier Healthcare database to identify patients undergoing their first (index) allo-HSCT procedure between 1/1/2006 and 3/31/2015. Three subgroups were analyzed according to CMV-related readmissions during the 100-day follow-up (0, 1, or 2+ readmissions) to compare healthcare utilization and costs. Results: A total of 1,610 patients (mean age, 50.5 years; 56.9% male) from 52 US hospitals met the inclusion criteria. During follow-up, 212 (13.2%) patients had 1 (n = 161; 10.0%) or 2+ (n = 51; 3.2%) CMV-related readmissions. The mean ± SD number of all follow-up encounters (inpatient admissions and hospital-based outpatient visits) was similar for the no CMV (3.9 ± 3.9), 1 CMV (3.7 ± 3.9), and 2+ CMV (4.5 ± 3.8) readmission groups (P = 0.439). Mean total costs of hospital-based healthcare encounters (inpatient admissions and hospital-based outpatient visits) during follow-up were significantly greater in patients who had a CMV readmission ($111,729 [1 CMV readmission]; $184,021 [2+ CMV readmissions]) compared to those without a CMV readmission ($46,064; P Conclusions: This large, national database study revealed significantly higher healthcare utilization and costs, as well as mortality, among patients with CMV-related re-hospitalization during the first 100 days post-transplant as compared to patients without CMV-related hospitalization.

● Region.

The Hospital Compare dataset is part of a data repository maintained by the Centers for Medicare & Medicaid Services (CMS), focusing on the quality of care at over 4,500 Medicare-certified hospitals (including acute care hospitals, critical access hospitals (CAHs), children’s hospitals, and hospital outpatient departments) across the country. The dataset was created in collaboration with organizations representing consumers, doctors, hospitals, employers, accrediting organizations, and other federal agencies, as part of an overall effort to improve patient safety and care.

The Hospital Compare dataset on PolicyMap includes data on:

General information (Overall Rating, Mortality, Safety of Care, Readmission, Patient Experience, Effectiveness of Care, Timeliness of Care, Effective use of Medical Imaging): The overall hospital rating is given in stars from 1 to 5, while all other measures are designated as either being below, same, or above the national average. Data for these measures is compiled through the Inpatient/Outpatient Quality Reports and other programs mandatory for Medicare-certified hospitals. All comparisons on national average were standardized to ensure a common scale and direction for each measure. This implies that hospitals that perform above average on mortality or readmission comparison have a higher standardized z-score on these measures, based on lower mortality and readmission rates than the national average. The overall star rating in this section is intended primarily for acute care hospitals, due to which CMS may have omitted the measure for specialty hospitals. More details on the methodology for calculating overall ratings can be found here. Survey of patients’ experiences – (Ratings on Care transition, Cleanliness, Communication, Pain Management, Staff Responsiveness, Quietness, Discharge Information, and overall hospital ratings): All of these measures are assigned a star rating from 1 to 5. Data for these measures is compiled using the Hospital Consumer Assessment of Healthcare Providers and Systems survey [HCAHPS], which is administered to a random sample of adult inpatients after discharge. In order to receive HCAHPS Star Ratings, hospitals must have at least 100 completed HCAHPS surveys over a given four-quarter period. While all of the star ratings are based on direct patient responses, the summary star rating is calculated as a weighted measure using all categories of patient responses, including overall patient rating. More details on the methodology for calculating HCAHPS star ratings can be found here. Healthcare Associated Infections (HAI): HAI measures show how often patients in a particular hospital contract certain infections during the course of their medical treatment, when compared to like hospitals. These infections can often be prevented when healthcare facilities follow guidelines for safe care. Hospitals currently submit information on central line-associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), colon and abdominal hysterectomy surgical site infections (SSIs), MRSA Bacteremia, and C.difficile laboratory-identified events. More details on the methodology for calculating HCAHPS star ratings can be found here.

Reasons for exclusion of certain measures for a hospital may include when number of cases/patients is too few to report, results are based on a shorter time period than required, data suppressed by CMS for one or more quarters, results are not available for this reporting period, there were discrepancies in the data collection process, this result is not based on performance data; the hospital did not submit data and did not submit a waiver, data are shown only for hospitals that participate in the Inpatient Quality Reporting (IQR) and Outpatient Quality Reporting (OQR) programs.

More details on data collection and computation methodology for each dataset can be found here. This dataset is available on PolicyMap as point data based on hospital location, and can be viewed upon clicking each respective point. The CMS Hospital Compare data was joined by PolicyMap to hospital locations using data from HRSA. HRSA hospital location data can be found here.

ObjectivesWe evaluated the impact of a COPD discharge care bundle on readmission rates following hospitalisation with an acute exacerbation.DesignInterrupted time series analysis, comparing readmission rates for COPD exacerbations at nine trusts that introduced the bundle, to two comparison groups; (1) other NHS trusts in London and (2) all other NHS trusts in England. Care bundles were implemented at different times for different NHS trusts, ranging from October 2009 to April 2011.SettingNine NHS acute trusts in the London, England.ParticipantsPatients aged 45 years and older admitted to an NHS acute hospital in England for acute exacerbation of COPD. Data come from Hospital Episode Statistics, April 2002 to March 2012.Main Outcome MeasuresAnnual trend readmission rates (and in total bed days) within 7, 28 and 90 days, before and after implementation.ResultsIn hospitals introducing the bundle readmission rates were rising before implementation and falling afterwards (e.g. readmissions within 28 days +2.13% per annum (pa) pre and -5.32% pa post (p for difference in trends = 0.012)). Following implementation, readmission rates within 7 and 28 day were falling faster than among other trusts in London, although this was not statistically significant (e.g. readmissions within 28 days -4.6% pa vs. -3.2% pa, p = 0.44). Comparisons with a national control group were similar.ConclusionsThe COPD discharge care bundle appeared to be associated with a reduction in readmission rate among hospitals using it. The significance of this is unclear because of changes to background trends in London and nationally.

Percentage reduction of readmissions due to increase in pre-operative hematocrit.

Indirectly age and sex standardised ratio of unplanned readmissions to a mental health service within 30 days of a discharge from a mental health inpatient service in people aged 17 and over. The next release date for this indicator is to be confirmed. Legacy unique identifier: P01863