National Healthcare Quality and Disparities Report
Latest available findings on quality of and access to health care
Data
- Data Infographics
- Data Visualizations
- Data Tools
- Data Innovations
- All-Payer Claims Database
- Healthcare Cost and Utilization Project (HCUP)
- Medical Expenditure Panel Survey (MEPS)
- AHRQ Quality Indicator Tools for Data Analytics
- State Snapshots
- United States Health Information Knowledgebase (USHIK)
- Data Sources Available from AHRQ
Search All Research Studies
AHRQ Research Studies Date
Topics
- Adverse Events (14)
- Ambulatory Care and Surgery (3)
- Arthritis (1)
- Behavioral Health (3)
- Blood Clots (4)
- Cancer (5)
- Cancer: Prostate Cancer (1)
- Cardiovascular Conditions (6)
- Care Coordination (3)
- Caregiving (1)
- Care Management (1)
- Children's Health Insurance Program (CHIP) (3)
- Children/Adolescents (21)
- Chronic Conditions (5)
- Clinical Decision Support (CDS) (1)
- Comparative Effectiveness (1)
- Consumer Assessment of Healthcare Providers and Systems (CAHPS) (5)
- Data (2)
- Dental and Oral Health (1)
- Depression (2)
- Diabetes (1)
- Diagnostic Safety and Quality (5)
- Disparities (6)
- Education: Continuing Medical Education (1)
- Education: Patient and Caregiver (2)
- Elderly (11)
- Electronic Health Records (EHRs) (10)
- Emergency Department (8)
- Emergency Medical Services (EMS) (1)
- Evidence-Based Practice (7)
- Falls (2)
- Guidelines (2)
- Healthcare-Associated Infections (HAIs) (4)
- Healthcare Cost and Utilization Project (HCUP) (10)
- Healthcare Costs (2)
- Healthcare Delivery (4)
- Healthcare Utilization (2)
- Health Information Exchange (HIE) (1)
- Health Information Technology (HIT) (10)
- Health Insurance (2)
- Health Literacy (1)
- Health Systems (2)
- Heart Disease and Health (3)
- Home Healthcare (2)
- Hospital Discharge (1)
- Hospitalization (9)
- Hospital Readmissions (15)
- Hospitals (32)
- Imaging (2)
- Injuries and Wounds (4)
- Inpatient Care (1)
- Intensive Care Unit (ICU) (2)
- Labor and Delivery (1)
- Long-Term Care (6)
- Medicaid (3)
- Medical Errors (1)
- Medicare (10)
- Medication (3)
- Mortality (4)
- Neonatal Intensive Care Unit (NICU) (2)
- Neurological Disorders (2)
- Newborns/Infants (3)
- Nursing (6)
- Nursing Homes (13)
- Obesity (1)
- Opioids (1)
- Organizational Change (1)
- Orthopedics (1)
- Outcomes (11)
- Palliative Care (2)
- Patient-Centered Healthcare (2)
- Patient-Centered Outcomes Research (12)
- Patient Experience (8)
- Patient Safety (30)
- Payment (6)
- Pneumonia (2)
- Policy (3)
- Practice Patterns (1)
- Pressure Ulcers (3)
- Prevention (7)
- Primary Care (8)
- Primary Care: Models of Care (1)
- Provider (3)
- Provider: Nurse (1)
- Provider: Physician (1)
- Provider Performance (25)
- Public Reporting (5)
- Quality Improvement (30)
- (-) Quality Indicators (QIs) (138)
- Quality Measures (68)
- Quality of Care (101)
- Quality of Life (1)
- Racial and Ethnic Minorities (6)
- Registries (1)
- Rehabilitation (2)
- Research Methodologies (4)
- Respiratory Conditions (3)
- Risk (4)
- Rural Health (1)
- Sepsis (2)
- Shared Decision Making (2)
- Skin Conditions (1)
- Social Determinants of Health (1)
- Stroke (1)
- Substance Abuse (1)
- Surgery (16)
- Surveys on Patient Safety Culture (1)
- Tools & Toolkits (1)
- Transitions of Care (1)
- Urban Health (1)
- Vulnerable Populations (1)
- Workforce (1)
AHRQ Research Studies
Sign up: AHRQ Research Studies Email updates
Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
101 to 125 of 138 Research Studies DisplayedMcConnell KJ, Lindrooth RC, Wholey DR
Modern management practices and hospital admissions.
The researchers investigated whether the modern management practices and publicly reported performance measures are associated with choice of hospital for patients with acute myocardial infarction (AMI). They found that, overall, a one standard deviation change in management practice scores is associated with an 8% increase in AMI admissions.
AHRQ-funded; HS018466.
Citation: McConnell KJ, Lindrooth RC, Wholey DR .
Modern management practices and hospital admissions.
Health Econ 2016 Apr;25(4):470-85. doi: 10.1002/hec.3171.
.
.
Keywords: Hospitals, Heart Disease and Health, Cardiovascular Conditions, Quality Indicators (QIs), Quality Measures, Quality of Care, Public Reporting, Provider Performance
Moghavem N, McDonald K, Ratliff JK
Performance measures in neurosurgical patient care: differing applications of patient safety indicators.
The researchers sought to determine how Patient Safety Indicator (PSI) rates and their impact on other outcomes in patients undergoing cranial neurosurgery compared with other surgeries.. They found that procedure indication was strongly associated with PSI development. The neurosurgical population had significantly higher risk-adjusted ratios of most PSIs evaluated compared with other surgical patients. Development of a PSI was strongly associated with increased length of stay and hospital cost.
AHRQ-funded; HS018558.
Citation: Moghavem N, McDonald K, Ratliff JK .
Performance measures in neurosurgical patient care: differing applications of patient safety indicators.
Med Care 2016 Apr;54(4):359-64. doi: 10.1097/mlr.0000000000000490.
.
.
Keywords: Quality Indicators (QIs), Surgery, Hospitalization, Outcomes, Quality of Care
Mukamel DB, Amin A, Weimer DL
When patients customize nursing home ratings, choices and rankings differ from the government's version.
Report cards currently published by the Centers for Medicare and Medicaid Services (CMS) offer composite quality measures, such as the one featured on the Nursing Home Compare website. Nursing Home Compare Plus is an alternative that allows patients and their families to create their own composite scores based on their own preferences and medical needs. When comparing Nursing Home Compare Plus to Medicare's five-star ratings, we found only minimal agreement on ranking of nursing homes.
AHRQ-funded; HS021844.
Citation: Mukamel DB, Amin A, Weimer DL .
When patients customize nursing home ratings, choices and rankings differ from the government's version.
Health Aff 2016 Apr;35(4):714-9. doi: 10.1377/hlthaff.2015.1340.
.
.
Keywords: Nursing Homes, Quality of Care, Quality Indicators (QIs), Patient Experience, Consumer Assessment of Healthcare Providers and Systems (CAHPS)
Chien AT, Schiavoni KH, Sprecher E
How accountable care organizations responded to pediatric incentives in the alternative quality contract.
The authors characterized the pediatric infrastructure of adult-oriented accountable care organizations (ACOs) and obtained leaders' perspectives on their ACOs' response to pediatric incentives. They found that most ACOs augmented their pediatric quality improvement and spending reduction efforts when faced with pediatric incentives.
AHRQ-funded; HS017146.
Citation: Chien AT, Schiavoni KH, Sprecher E .
How accountable care organizations responded to pediatric incentives in the alternative quality contract.
Acad Pediatr 2016 Mar;16(2):200-7. doi: 10.1016/j.acap.2015.10.008.
.
.
Keywords: Children/Adolescents, Health Insurance, Quality of Care, Payment, Quality Indicators (QIs)
Southern DA, Pincus HA, Romano PS
Enhanced capture of healthcare-related harms and injuries in the 11th revision of the International Classification of Diseases (ICD-11).
The authors presented recommendations made to the World Health Organization (WHO) by the ICD revision's Quality and Safety Topic Advisory Group (Q&S TAG) for a new conceptual approach to capturing healthcare-related harms and injuries in ICD-coded data. They concluded that this new framework for coding healthcare-related harm has great potential to improve the clinical detail of adverse event descriptions and the overall quality of coded health data.
AHRQ-funded; HS020543.
Citation: Southern DA, Pincus HA, Romano PS .
Enhanced capture of healthcare-related harms and injuries in the 11th revision of the International Classification of Diseases (ICD-11).
Int J Qual Health Care 2016 Feb;28(1):136-42. doi: 10.1093/intqhc/mzv099.
.
.
Keywords: Adverse Events, Quality of Care, Patient Safety, Quality Indicators (QIs)
Dy SM, Herr K, Bernacki RE
Methodological research priorities in palliative care and hospice quality measurement.
The authors describe three key priorities: 1) defining the population of interest for palliative care quality indicators, 2) developing methods to measure quality from different data sources, and 3) conducting research to advance the development of patient/family-reported indicators. They apply these concepts to the key quality domain of advance care planning and address relevance to implementation of indicators in improving care in order to facilitate improved quality measurement across all populations with serious illness and care for patients and families.
AHRQ-funded; HS023681.
Citation: Dy SM, Herr K, Bernacki RE .
Methodological research priorities in palliative care and hospice quality measurement.
J Pain Symptom Manage 2016 Feb;51(2):155-62. doi: 10.1016/j.jpainsymman.2015.10.019.
.
.
Keywords: Research Methodologies, Palliative Care, Quality Measures, Quality Indicators (QIs), Quality of Care
Southern DA, Hall M, White DE
Opportunities and challenges for quality and safety applications in ICD-11: an international survey of users of coded health data.
The authors identified opportunities and challenges in improving the utility of ICD-11 for quality and safety applications. The 246 online survey respondents specified desires for the ICD revision: more code content for adverse events/complications; a desire for code clustering mechanisms; the need for diagnosis timing information; and the addition of better code definitions to reference materials. The authors concluded that the World Health Organization's ICD revision process is addressing each of these desires.
AHRQ-funded; HS020543.
Citation: Southern DA, Hall M, White DE .
Opportunities and challenges for quality and safety applications in ICD-11: an international survey of users of coded health data.
Int J Qual Health Care 2016 Feb;28(1):129-35. doi: 10.1093/intqhc/mzv096.
.
.
Keywords: Quality of Care, Patient Safety, Quality Indicators (QIs)
Dresden SM, Feinglass JM, Kang R
Ambulatory care sensitive hospitalizations through the emergency department by payer: comparing 2003 and 2009.
This study compared rates of ED ambulatory care sensitive hospitalizations (ACSHs) for 2003 and 2009 among patients 18 to 64 years of age with private insurance, Medicaid, or no insurance.It found that an increase in the uninsured population was associated with an increase in the rate of ED ACSH for uninsured patients.
AHRQ-funded; HS000078.
Citation: Dresden SM, Feinglass JM, Kang R .
Ambulatory care sensitive hospitalizations through the emergency department by payer: comparing 2003 and 2009.
J Emerg Med 2016 Jan;50(1):135-42. doi: 10.1016/j.jemermed.2015.02.047.
.
.
Keywords: Healthcare Cost and Utilization Project (HCUP), Quality Indicators (QIs), Hospitalization, Emergency Medical Services (EMS)
Walkey AJ, Weinberg J, Wiener RS
Association of do-not-resuscitate orders and hospital mortality rate among patients with pneumonia.
The researchers evaluated the effect of analytic approaches accounting for do-not-resuscitate (DNR) status on risk-adjusted hospital mortality rates and performance rankings. They found that after accounting for patient DNR status and between-hospital variation in the association between DNR status and mortality, hospitals with higher DNR rates had lower mortality.
AHRQ-funded; HS020672.
Citation: Walkey AJ, Weinberg J, Wiener RS .
Association of do-not-resuscitate orders and hospital mortality rate among patients with pneumonia.
JAMA Intern Med 2016 Jan;176(1):97-104. doi: 10.1001/jamainternmed.2015.6324.
.
.
Keywords: Hospitals, Mortality, Quality of Care, Quality Indicators (QIs), Quality Measures, Pneumonia, Provider Performance, Respiratory Conditions
Kanzaria HK, Hall MK, Moore CL
Emergency department diagnostic imaging: the journey to quality.
The authors examine the current state of quality measurement as it pertains to ED imaging. They also review relevant policies and discuss both the associated challenges and the facilitators of using quality measures to help optimize ED imaging. Understanding such factors will help ensure the delivery of diagnostic imaging that is appropriate, high-quality, and patient-centered.
AHRQ-funded; HS023498.
Citation: Kanzaria HK, Hall MK, Moore CL .
Emergency department diagnostic imaging: the journey to quality.
Acad Emerg Med 2015 Dec;22(12):1380-4. doi: 10.1111/acem.12817.
.
.
Keywords: Emergency Department, Imaging, Quality Indicators (QIs), Quality of Care
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
Morgans AK, van Bommel AC, Stowell C
Development of a standardized set of patient-centered outcomes for advanced prostate cancer: an international effort for a unified approach.
The International Consortium for Health Outcomes Measurement assembled a multidisciplinary working group to develop a standard set of outcomes relevant to men with advanced prostate cancer to follow during routine clinical care. The international multidisciplinary group identified clinical data and patient-reported outcome measures that serve as a basis for international health outcome comparisons and quality-of-care assessments. The set will be revised annually.
AHRQ-funded; HS022990.
Citation: Morgans AK, van Bommel AC, Stowell C .
Development of a standardized set of patient-centered outcomes for advanced prostate cancer: an international effort for a unified approach.
Eur Urol 2015 Nov;68(5):891-8. doi: 10.1016/j.eururo.2015.06.007.
.
.
Keywords: Cancer: Prostate Cancer, Patient-Centered Outcomes Research, Quality of Life, Adverse Events, Quality Indicators (QIs)
Mukamel DB, Ladd H, Li Y
AHRQ Author: Ngo-Metzger Q
Have racial disparities in ambulatory care sensitive admissions abated over time?
The researchers evaluated whether disparities in quality of ambulatory care have abated during the decade of 2000 by asking whether there were there differences in ambulatory care sensitive hospital admissions rates by race? In 2003 the overall Prevention Quality Indicators (PQI) admission rates were higher for African Americans (around 16.5/1000) than for whites (around 15/1000). By 2009, the overall and the chronic PQI admission rates declined significantly for whites but not for African Americans.
AHRQ-authored.
Citation: Mukamel DB, Ladd H, Li Y .
Have racial disparities in ambulatory care sensitive admissions abated over time?
Med Care 2015 Nov;53(11):931-9. doi: 10.1097/mlr.0000000000000426..
Keywords: Healthcare Cost and Utilization Project (HCUP), Disparities, Quality Indicators (QIs), Racial and Ethnic Minorities, Quality of Care
Litvin CB, Ornstein SM, Wessell AM
"Meaningful" clinical quality measures for primary care physicians.
The authors systematically solicited recommendations from Meaningful Use (MU) exemplars to inform Stage 3 MU clinical quality measure (CQM) requirements. There was consensus that CQMs should be evidence-based and focus on high-priority conditions relevant to primary care providers. Participants thought the emphasis of CQMs should largely be on outcomes and that reporting of CQMs should limit the burden on providers.
AHRQ-funded; HS022701; HS018984.
Citation: Litvin CB, Ornstein SM, Wessell AM .
"Meaningful" clinical quality measures for primary care physicians.
Am J Manag Care 2015 Oct;21(10):e583-90..
Keywords: Quality Indicators (QIs), Quality Measures, Primary Care, Quality of Care
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
Mukamel DB, Ye Z, Glance LG
Does mandating nursing home participation in quality reporting make a difference? Evidence from Massachusetts.
This study investigated one of the mechanisms that may detract from the effectiveness of quality report cards: voluntary versus mandatory participation of nursing homes in public quality reporting. It found that once reporting became mandatory, nonvolunteers improved more than volunteers in all but 2 staffing measures.
AHRQ-funded; HS021844.
Citation: Mukamel DB, Ye Z, Glance LG .
Does mandating nursing home participation in quality reporting make a difference? Evidence from Massachusetts.
Med Care 2015 Aug;53(8):713-9. doi: 10.1097/mlr.0000000000000390..
Keywords: Nursing Homes, Long-Term Care, Public Reporting, Provider Performance, Quality Improvement, Quality of Care, Quality Indicators (QIs), Quality Measures, Elderly
Goldman LE, Chu PW, Bacchetti P
Effect of present-on-admission (POA) reporting accuracy on hospital performance assessments using risk-adjusted mortality.
This study evaluated how the accuracy of present-on-admission (POA) reporting affects hospital 30-day acute myocardial infarction (AMI) mortality assessments. It finds that the use of POA indicators in administrative data significantly alters risk-adjusted hospital assessments that do not incorporate a method for distinguishing between comorbidities and complications.
AHRQ-funded; HS018090.
Citation: Goldman LE, Chu PW, Bacchetti P .
Effect of present-on-admission (POA) reporting accuracy on hospital performance assessments using risk-adjusted mortality.
Health Serv Res 2015 Jun;50(3):922-38. doi: 10.1111/1475-6773.12239.
.
.
Keywords: Hospitals, Mortality, Heart Disease and Health, Quality Indicators (QIs)
Smith B, McDuff J, Naierman N
What consumers want to know about quality when choosing a hospice provider.
This study drew on focus group and survey data collected in 5 metropolitan areas to learn more about hospice quality data. The researchers found that participants placed top priority on measures related to pain and symptom management. The National Quality Forum-approved measures resonate well with consumers, who also appear to be ready for access to data on the quality of hospice providers.
AHRQ-funded; HS021870.
Citation: Smith B, McDuff J, Naierman N .
What consumers want to know about quality when choosing a hospice provider.
Am J Hosp Palliat Care 2015 Jun;32(4):393-400. doi: 10.1177/1049909114524475.
.
.
Keywords: Caregiving, Education: Patient and Caregiver, Shared Decision Making, Palliative Care, Provider Performance, Public Reporting, Quality of Care, Quality Indicators (QIs)
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)
Ornstein SM, Nemeth LS, Nietert PJ
Learning from primary care meaningful use exemplars.
This report presents the results of a multimethod study combining an EHR-based clinical quality measurements (CQM) performance assessment, a provider survey, and focus groups among high CQM performers. It concluded that purposeful use of EHR functionality coupled with staff education in a milieu where Quality Improvement is valued and supported is associated with higher performance on CQM.
AHRQ-funded; HS022701; HS018984.
Citation: Ornstein SM, Nemeth LS, Nietert PJ .
Learning from primary care meaningful use exemplars.
J Am Board Fam Med 2015 May-Jun;28(3):360-70. doi: 10.3122/jabfm.2015.03.140219..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Quality Indicators (QIs), Quality of Care
Chung JW, Ju MH, Kinnier CV
Postoperative venous thromboembolism outcomes measure: analytic exploration of potential misclassification of hospital quality due to surveillance bias.
The authors discuss problems associated with AHRQ’s Patient Safety Indicator (PS112), Postoperative Venous Thromboembolism such as identifying truly poor-quality hospitals from those that only seem to be poor-quality because of hospital-to-hospital variations in imaging rates for venous thromboembolism (VTE). They call for the development of administrative codes that enable reliable identification and exclusion of sub-clinical VTE from the measure numerator.
AHRQ-funded; HS021857
Citation: Chung JW, Ju MH, Kinnier CV .
Postoperative venous thromboembolism outcomes measure: analytic exploration of potential misclassification of hospital quality due to surveillance bias.
Ann Surg. 2015 Mar;261(3):443-4. doi: 10.1097/sla.0000000000000850..
Keywords: Quality Indicators (QIs), Blood Clots, Quality of Care, Adverse Events
Sentell TL, Juarez DT, Ahn HJ
Disparities in diabetes-related preventable hospitalizations among working-age Native Hawaiians and Asians in Hawai'i.
Elderly (65+) Native Hawaiian, Filipino, and Japanese men and Filipino women have a higher risk of diabetes-related potentially preventable hospitalizations than whites. The authors sought to determine if similar disparities are seen among the non-elderly (< 65). They found that preventable hospitalizations rates were significantly higher for Native Hawaiians males compared to whites, but significantly lower for Chinese men and women, Japanese men and women, and Filipino men and women. Rates for Native Hawaiian females did not differ significantly from Whites. Disparities in diabetes-related preventable hospitalizations were seen for working-age (18-64) Native Hawaiian men even when their higher population-level diabetes prevalence was considered.
AHRQ-funded; HS019990.
Citation: Sentell TL, Juarez DT, Ahn HJ .
Disparities in diabetes-related preventable hospitalizations among working-age Native Hawaiians and Asians in Hawai'i.
Hawaii J Med Public Health 2014 Dec;73(12 Suppl 3):8-13.
.
.
Keywords: Diabetes, Disparities, Hospitalization, Quality Indicators (QIs), Racial and Ethnic Minorities
Bailey LC, Mistry KB, Tinoco A
AHRQ Author: Mistry KB
Addressing electronic clinical information in the construction of quality measures.
The authors draw on the experience of Centers of Excellence to review both structural and pragmatic considerations in e-measurement. They suggest that addressing these challenges will require investment by vendors, researchers, and clinicians alike in developing better pediatric content for standard terminologies and data models, encouraging wider adoption of technical standards that support reliable quality measurement, better harmonizing data collection with clinical work flow in EHRs, and better understanding the behavior and potential of e-measures.
AHRQ-authored.
Citation: Bailey LC, Mistry KB, Tinoco A .
Addressing electronic clinical information in the construction of quality measures.
Acad Pediatr 2014 Sep-Oct;14(5 Suppl):S82-9. doi: 10.1016/j.acap.2014.06.006.
.
.
Keywords: Children's Health Insurance Program (CHIP), Electronic Health Records (EHRs), Quality Improvement, Quality Indicators (QIs), Quality Measures
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.
.
.
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.
.
.
Keywords: Children/Adolescents, Quality Improvement, Quality Indicators (QIs), Quality Measures, Hospital Readmissions