National Healthcare Quality and Disparities Report
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Topics
- Adverse Events (2)
- Care Coordination (1)
- Children/Adolescents (4)
- Diagnostic Safety and Quality (1)
- Elderly (3)
- Electronic Health Records (EHRs) (1)
- Healthcare Cost and Utilization Project (HCUP) (1)
- Health Information Technology (HIT) (1)
- (-) Hospital Readmissions (15)
- Hospitals (5)
- Intensive Care Unit (ICU) (1)
- Medicare (2)
- Mortality (1)
- Neonatal Intensive Care Unit (NICU) (1)
- Newborns/Infants (1)
- Patient Safety (1)
- Pneumonia (1)
- Provider Performance (1)
- Quality Improvement (2)
- (-) Quality Indicators (QIs) (15)
- Quality Measures (6)
- Quality of Care (8)
- Rehabilitation (1)
- Respiratory Conditions (1)
- Risk (2)
- Surgery (2)
- Transitions of Care (1)
AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 15 of 15 Research Studies DisplayedElysee G, Yu H, Herrin J
Association between 30-day readmission rates and health information technology capabilities in US hospitals.
A study was conducted to determine if there is an association of health information technology (HIT) adoption and a decrease in 30-day hospital readmission rates. Data was used from the 2013 American Hospital Association IT survey which included non-federal U.S. acute care hospitals with self-reported capabilities. A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis. A one-point increase in the hospital adoption of patient engagement capability latent scores generally leads to a 0.086% decrease in risk-standardized readmission rates (RSRRs). However, computerized hospital discharge and information exchange among clinicians did not seem as beneficial.
AHRQ-funded; HS022882.
Citation: Elysee G, Yu H, Herrin J .
Association between 30-day readmission rates and health information technology capabilities in US hospitals.
Medicine 2021 Feb 26;100(8):e24755. doi: 10.1097/md.0000000000024755..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Hospital Readmissions, Hospitals, Quality Indicators (QIs), Quality of Care
Nakamura MM, Toomey SL, Zaslavsky AM
Potential impact of initial clinical data on adjustment of pediatric readmission rates.
This study investigated whether the addition of adding initial clinical data to adjust for case-mix (differences in patient populations) improved prediction of pediatric readmissions. Thirty-day readmissions were examined using claims and electronic records for patients aged 18 and younger who were admitted to 3 children’s hospitals from February 2011 to February 2014. The Pediatric All-Condition Readmission Measure was used and started with a model including age, gender, chronic conditions, and primary diagnosis. Initial vital sign and laboratory data was added to see if it improved model performance. Greater readmission risk was found if there was a low red blood cell count and mean corpuscular hemoglobin concentration and high red cell distribution risk. However, it did not provide more than minimal improvement in performance.
AHRQ-funded; HS020513; HS025299.
Citation: Nakamura MM, Toomey SL, Zaslavsky AM .
Potential impact of initial clinical data on adjustment of pediatric readmission rates.
Acad Pediatr 2019 Jul;19(5):589-98. doi: 10.1016/j.acap.2018.09.006..
Keywords: Children/Adolescents, Hospital Readmissions, Risk, Quality Indicators (QIs), Quality Measures, Quality of Care
Gupta S, Zengul FD, Davlyatov GK
Reduction in hospitals' readmission rates: role of hospital-based skilled nursing facilities.
The purpose of this study was to examine the association between hospital-based skilled nursing facilities (HBSNFs) and hospitals' readmission rates. Data sources included the American Hospital Association Annual Survey, Area Health Resources Files, CMS Medicare cost reports and Hospital Compare. Results showed that the presence of HBSNFs was associated with lower readmission rates for acute myocardial infarction and pneumonia. Further, higher skilled nursing facilities to hospitals ratio were associated with lower readmission rates.
AHRQ-funded; HS023345.
Citation: Gupta S, Zengul FD, Davlyatov GK .
Reduction in hospitals' readmission rates: role of hospital-based skilled nursing facilities.
Inquiry 2019 Jan-Dec;56:46958018817994. doi: 10.1177/0046958018817994..
Keywords: Hospital Readmissions, Transitions of Care, Care Coordination, Hospitals, Quality Indicators (QIs), Quality Measures, Quality of Care
Kaiser SV, Lam R, Joseph GB
Limitations of using pediatric respiratory illness readmissions to compare hospital performance.
Researcher sought to determine if a National Quality Forum (NQF)-endorsed measure for pediatric lower respiratory illness (LRI) 30-day readmission rates can meaningfully identify high- and low-performing hospitals. Subjects were children with LRI (bronchiolitis, influenza, or pneumonia as primary diagnosis, or with an LRI as a secondary diagnosis with a primary diagnosis of respiratory failure, sepsis, bacteremia, or asthma) from all hospital admissions in California from 2012 to 2014. The researchers were unable to identify meaningful variation in hospital performance without broadening the metric definition and merging multiple years of data. They recommend that utilizers of pediatric-quality measures consider modifying metrics to better evaluate the quality of pediatric care at low-volume hospitals.
AHRQ-funded; HS024385; HS022835; HS024592; HS025297.
Citation: Kaiser SV, Lam R, Joseph GB .
Limitations of using pediatric respiratory illness readmissions to compare hospital performance.
J Hosp Med 2018 Nov;13(11):737-42. doi: 10.12788/jhm.2988..
Keywords: Children/Adolescents, Respiratory Conditions, Provider Performance, Hospital Readmissions, Hospitals, Quality Indicators (QIs), Quality Measures, Quality of Care, Quality Improvement
Goldberg EM, Morphis B, Youssef R
An analysis of diagnoses that drive readmission: what can we learn from the hospitals in Southern New England with the highest and lowest readmission performance?
This study examined the most common diagnoses driving readmissions among fee-for-service Medicare beneficiaries in the hospitals with the highest and lowest readmission performance in Southern New England from 2014 to 2016. It found that the lowest-performing hospitals readmitted higher percentages of patients for sepsis and complications of device, implant, or graft, compared to highest-performing hospitals.
AHRQ-funded; HS000011.
Citation: Goldberg EM, Morphis B, Youssef R .
An analysis of diagnoses that drive readmission: what can we learn from the hospitals in Southern New England with the highest and lowest readmission performance?
R I Med J 2017 Aug;100(8):23-28.
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Keywords: Adverse Events, Diagnostic Safety and Quality, Hospital Readmissions, Hospitals, Quality Indicators (QIs)
Hollis RH, Graham LA, Richman JS
Hospital readmissions after surgery: how important are hospital and specialty factors?
Researchers hypothesized that hospital readmission rates for procedures within specialties were more strongly correlated than rates across specialties within the same hospital. However, they found that hospital readmission rates for orthopaedic, vascular, and general surgery were not correlated between specialties; within each of the 3 specialties, modest correlations were found between 2 procedures within 2 of these specialties.
AHRQ-funded; HS013852.
Citation: Hollis RH, Graham LA, Richman JS .
Hospital readmissions after surgery: how important are hospital and specialty factors?
J Am Coll Surg 2017 Apr;224(4):515-23. doi: 10.1016/j.jamcollsurg.2016.12.034.
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Keywords: Surgery, Hospital Readmissions, Quality Indicators (QIs), Elderly
Campione JR, Smith SA, Mardon RE
Hospital-level factors related to 30-day readmission rates.
This study investigates the relationship between inpatient quality of care as measured by the Agency for Healthcare Research and Quality (AHRQ) patient safety indicator (PSI) composite and all-cause, hospital-wide, 30-day readmission rates. It concluded that inpatient quality of care appears to have less influence on hospital readmission rates than do clinical and socioeconomic factors.
AHRQ-funded; 290201200003I.
Citation: Campione JR, Smith SA, Mardon RE .
Hospital-level factors related to 30-day readmission rates.
Am J Med Qual 2017 Jan/Feb;32(1):48-57. doi: 10.1177/1062860615612158.
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Keywords: Quality of Care, Healthcare Cost and Utilization Project (HCUP), Hospital Readmissions, Quality Indicators (QIs), Quality Measures
Chin DL, Bang H, Manickam RN
Rethinking thirty-day hospital readmissions: shorter intervals might be better indicators of quality of care.
The researchers examined risk-standardized thirty-day risk of unplanned inpatient readmission at the hospital level for Medicare patients ages sixty-five and older in four states and for three conditions: acute myocardial infarction, heart failure, and pneumonia. The hospital-level quality signal captured in readmission risk was highest on the first day after discharge and declined rapidly until it reached a nadir at seven days, as indicated by a decreasing intracluster correlation coefficient.
AHRQ-funded; HS022236.
Citation: Chin DL, Bang H, Manickam RN .
Rethinking thirty-day hospital readmissions: shorter intervals might be better indicators of quality of care.
Health Aff 2016 Oct;35(10):1867-75. doi: 10.1377/hlthaff.2016.0205.
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Keywords: Hospital Readmissions, Quality of Care, Hospitals, Quality Indicators (QIs)
Rajaram R, Ju MH, Bilimoria KY
National evaluation of hospital readmission after pulmonary resection.
The study’s objectives were to (1) assess readmission rates and timing after pulmonary resection, (2) report the most common reasons for rehospitalization, and (3) identify risk factors for unplanned readmission after pulmonary resection. It found that experiencing a postoperative complication was strongly associated with unplanned readmission.
AHRQ-funded; HS000078.
Citation: Rajaram R, Ju MH, Bilimoria KY .
National evaluation of hospital readmission after pulmonary resection.
J Thorac Cardiovasc Surg 2015 Dec;150(6):1508-14.e2. doi: 10.1016/j.jtcvs.2015.05.047..
Keywords: Hospital Readmissions, Risk, Surgery, Quality Indicators (QIs), Adverse Events
Khan A, Nakamura MM, Zaslavsky AM
Same-hospital readmission rates as a measure of pediatric quality of care.
This study determined the prevalence of 30-day pediatric different hospital readmission (DHRs); to assess the effect of DHR on readmission performance; and to identify patient and hospital characteristics associated with DHR. It concluded that DHRs differentially affect hospitals’ pediatric readmission rates and anticipated performance, making same-hospital readmissions an incomplete surrogate for all-hospital readmissions—particularly for certain hospital types.
AHRQ-funded; HS000063; HS020513.
Citation: Khan A, Nakamura MM, Zaslavsky AM .
Same-hospital readmission rates as a measure of pediatric quality of care.
JAMA Pediatr 2015 Oct;169(10):905-12. doi: 10.1001/jamapediatrics.2015.1129..
Keywords: Children/Adolescents, Quality of Care, Hospital Readmissions, Quality Indicators (QIs), Children/Adolescents
Sjoding MW, Iwashyna TJ, Dimick JB
Gaming hospital-level pneumonia 30-day mortality and readmission measures by legitimate changes to diagnostic coding.
The researchers sought to determine the degree to which hospitals can game mortality or readmission measures and change their rankings by recoding patients with pneumonia. They concluded that hospitals can improve apparent pneumonia mortality and readmission rates by recoding pneumonia patients. Centers for Medicare and Medicaid Services should consider changes to their methods used to calculate hospital-level pneumonia outcome measures.
AHRQ-funded; HS020672.
Citation: Sjoding MW, Iwashyna TJ, Dimick JB .
Gaming hospital-level pneumonia 30-day mortality and readmission measures by legitimate changes to diagnostic coding.
Crit Care Med 2015 May;43(5):989-95. doi: 10.1097/ccm.0000000000000862..
Keywords: Elderly, Hospital Readmissions, Medicare, Mortality, Pneumonia, Quality Indicators (QIs)
Lorch SA, Passarella M, Zeigler A
Challenges to measuring variation in readmission rates of neonatal intensive care patients.
The authors examined the viability of a hospital readmission quality metric for infants requiring neonatal intensive care. They found that the California cohort showed significant variation in hospital-level readmission rates, supporting the premise that readmission rates of prematurely born infants may reflect care quality. However, state data did not include term and early term infants requiring neonatal intensive care, and there were extensive missing data in the few states with sufficient information on managed care patients to calculate state-level measures. They concluded that constructing a valid readmission measure for NICU care across diverse states and regions requires improved data collection.
AHRQ-funded; HS018661; HS020508.
Citation: Lorch SA, Passarella M, Zeigler A .
Challenges to measuring variation in readmission rates of neonatal intensive care patients.
Acad Pediatr 2014 Sep-Oct;14(5 Suppl):S47-53. doi: 10.1016/j.acap.2014.06.010.
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Keywords: Neonatal Intensive Care Unit (NICU), Newborns/Infants, Quality Indicators (QIs), Quality Measures, Hospital Readmissions
Nakamura MM, Toomey SL, Zaslavsky AM
Measuring pediatric hospital readmission rates to drive quality improvement.
The investigators sought to describe the importance of readmissions in children and the challenges of developing readmission quality measures. They found that the policy focus on readmissions has motivated widespread efforts by hospitals and outpatient providers to evaluate and reengineer care processes.
AHRQ-funded; HS020513; HS020508.
Citation: Nakamura MM, Toomey SL, Zaslavsky AM .
Measuring pediatric hospital readmission rates to drive quality improvement.
Acad Pediatr 2014 Sep-Oct;14(5 Suppl):S39-46. doi: 10.1016/j.acap.2014.06.012.
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Keywords: Children/Adolescents, Quality Improvement, Quality Indicators (QIs), Quality Measures, Hospital Readmissions
Brown SE, Ratcliffe SJ, Halpern SD
An empirical comparison of key statistical attributes among potential ICU quality indicators.
The researchers assessed the performance of candidate indicators of ICU quality based on face validity, relevance to patients, ability to be measured reliably, sufficient variability to identify poor performers, relative insensitivity to severity adjustment, and the ability to capture what providers do rather than patients' characteristics. They concluded that no indicator performed optimally across assessments and recommended that future research seek to define and operationalize quality in a way that is relevant to both patients and providers.
AHRQ-funded; HS018406.
Citation: Brown SE, Ratcliffe SJ, Halpern SD .
An empirical comparison of key statistical attributes among potential ICU quality indicators.
Crit Care Med 2014 Aug;42(8):1821-31. doi: 10.1097/ccm.0000000000000334.
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Keywords: Quality of Care, Intensive Care Unit (ICU), Patient Safety, Quality Indicators (QIs), Hospital Readmissions
Ottenbacher KJ, Karmarkar A, Graham JE
Thirty-day hospital readmission following discharge from postacute rehabilitation in fee-for-service Medicare patients.
This study sought to determine 30-day readmission rates and factors related to readmission for patients receiving postacute inpatient rehabilitation. It found that among postacute rehabilitation facilities providing services to Medicare fee-for-service beneficiaries, 30-day readmission rates ranged from 5.8 percent to 18.8 percent for selected impairment groups.
AHRQ-funded; HS022134.
Citation: Ottenbacher KJ, Karmarkar A, Graham JE .
Thirty-day hospital readmission following discharge from postacute rehabilitation in fee-for-service Medicare patients.
JAMA 2014 Feb 12;311(6):604-14. doi: 10.1001/jama.2014.8..
Keywords: Hospital Readmissions, Medicare, Rehabilitation, Elderly, Quality Indicators (QIs)