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 (6)
- Ambulatory Care and Surgery (2)
- Arthritis (3)
- Asthma (1)
- Behavioral Health (6)
- Blood Clots (3)
- Blood Pressure (2)
- Cancer (8)
- Cancer: Breast Cancer (1)
- Cancer: Colorectal Cancer (1)
- Cancer: Lung Cancer (1)
- Cancer: Prostate Cancer (3)
- Cardiovascular Conditions (9)
- Care Coordination (3)
- Caregiving (2)
- Case Study (1)
- Catheter-Associated Urinary Tract Infection (CAUTI) (3)
- Central Line-Associated Bloodstream Infections (CLABSI) (2)
- Children's Health Insurance Program (CHIP) (14)
- Children/Adolescents (46)
- Chronic Conditions (11)
- Clinical Decision Support (CDS) (3)
- Clinician-Patient Communication (1)
- Comparative Effectiveness (2)
- Comprehensive Unit-based Safety Program (CUSP) (1)
- Consumer Assessment of Healthcare Providers and Systems (CAHPS) (19)
- Critical Care (1)
- Data (2)
- Decision Making (1)
- Dementia (1)
- Dental and Oral Health (3)
- Depression (2)
- Diabetes (7)
- Diagnostic Safety and Quality (8)
- Digestive Disease and Health (1)
- Disparities (4)
- Education: Continuing Medical Education (1)
- Education: Patient and Caregiver (2)
- Elderly (12)
- Electronic Health Records (EHRs) (18)
- Emergency Department (11)
- Evidence-Based Practice (17)
- Falls (2)
- Guidelines (5)
- Healthcare-Associated Infections (HAIs) (8)
- Healthcare Cost and Utilization Project (HCUP) (6)
- Healthcare Costs (1)
- Healthcare Delivery (9)
- Healthcare Utilization (2)
- Health Information Exchange (HIE) (2)
- Health Information Technology (HIT) (21)
- Health Insurance (3)
- Health Literacy (1)
- Health Services Research (HSR) (7)
- Health Status (1)
- Health Systems (3)
- Heart Disease and Health (3)
- Home Healthcare (2)
- Hospital Discharge (2)
- Hospitalization (6)
- Hospital Readmissions (9)
- Hospitals (37)
- Human Immunodeficiency Virus (HIV) (2)
- Imaging (1)
- Implementation (6)
- Infectious Diseases (2)
- Injuries and Wounds (4)
- Inpatient Care (5)
- Intensive Care Unit (ICU) (1)
- Learning Health Systems (1)
- Long-Term Care (14)
- Maternal Care (2)
- Medicaid (8)
- Medical Errors (3)
- Medicare (12)
- Medication (9)
- Medication: Safety (1)
- Mortality (2)
- Neonatal Intensive Care Unit (NICU) (2)
- Neurological Disorders (2)
- Newborns/Infants (1)
- Nursing (4)
- Nursing Homes (22)
- Obesity (1)
- Obesity: Weight Management (1)
- Organizational Change (1)
- Outcomes (16)
- Pain (1)
- Palliative Care (7)
- Patient-Centered Healthcare (6)
- Patient-Centered Outcomes Research (17)
- Patient Adherence/Compliance (2)
- Patient and Family Engagement (1)
- Patient Experience (20)
- Patient Safety (28)
- Payment (2)
- Pneumonia (2)
- Policy (5)
- Practice Patterns (3)
- Pregnancy (1)
- Pressure Ulcers (4)
- Prevention (4)
- Primary Care (14)
- Provider (2)
- Provider: Nurse (1)
- Provider Performance (50)
- Public Reporting (7)
- Quality Improvement (57)
- Quality Indicators (QIs) (68)
- (-) Quality Measures (227)
- Quality of Care (170)
- Quality of Life (2)
- Racial and Ethnic Minorities (4)
- Registries (2)
- Rehabilitation (2)
- Research Methodologies (5)
- Respiratory Conditions (4)
- Risk (4)
- Rural Health (1)
- Screening (2)
- Sepsis (6)
- Sexual Health (1)
- Skin Conditions (2)
- Social Determinants of Health (1)
- Social Media (1)
- Surgery (21)
- Surveys on Patient Safety Culture (1)
- Telehealth (2)
- Tools & Toolkits (1)
- Transitions of Care (4)
- Urban Health (1)
- Urinary Tract Infection (UTI) (2)
- Vulnerable Populations (2)
- Web-Based (1)
- Women (3)
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
176 to 200 of 227 Research Studies DisplayedGartlehner G, Dobrescu A, Evans TS
The predictive validity of quality of evidence grades for the stability of effect estimates was low: a meta-epidemiological study.
This study sought to determine the predictive validity of the U.S. Evidence-based Practice Center (EPC) approach to GRADE (Grading of Recommendations Assessment, Development and Evaluation). It concluded that the limited predictive validity of the EPC approach to GRADE seems to reflect a mismatch between expected and observed changes in treatment effects as bodies of evidence advance from insufficient to high quality of evidence.
AHRQ-funded; 290201200008I.
Citation: Gartlehner G, Dobrescu A, Evans TS .
The predictive validity of quality of evidence grades for the stability of effect estimates was low: a meta-epidemiological study.
J Clin Epidemiol 2016 Feb;70:52-60. doi: 10.1016/j.jclinepi.2015.08.018.
.
.
Keywords: Evidence-Based Practice, Research Methodologies, Quality Measures
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
Moy E, Coffey RM, Moore BJ
AHRQ Author: Moy E
Length of stay in EDs: variation across classifications of clinical condition and patient discharge disposition.
The researchers used a census of one state's data to measure length of emergency departments stays by patients' conditions and dispositions and exlore differences between means and medians as quality metrics. For the 10 most common diagnoses, patients with relatively minor injuries typically required the shortest mean stay (3 hours or less); conditions resulting in admission or transfer tended to be more serious, resulting in longer stays.
AHRQ-authored.
Citation: Moy E, Coffey RM, Moore BJ .
Length of stay in EDs: variation across classifications of clinical condition and patient discharge disposition.
Am J Emerg Med 2016 Jan;34(1):83-7. doi: 10.1016/j.ajem.2015.09.031..
Keywords: Healthcare Cost and Utilization Project (HCUP), Emergency Department, Quality Measures, Hospitalization, Quality of Care
Yanes AF, McElroy LM, Abecassis ZA
Observation for assessment of clinician performance: a narrative review.
The authors summarized studies utilizing video recorded or in-person observations for assessing clinician performance in medicine and surgery. They found that observations are useful for the improvement of healthcare delivery through the identification of clinician lapses and weaknesses that affect quality and safety. Further, limitations of observations included the Hawthorne effect and the necessity of trained observers to capture and analyze the notes or videos.
AHRQ-funded; HS000078.
Citation: Yanes AF, McElroy LM, Abecassis ZA .
Observation for assessment of clinician performance: a narrative review.
BMJ Qual Saf 2016 Jan;25(1):46-55. doi: 10.1136/bmjqs-2015-004171.
.
.
Keywords: Healthcare Delivery, Quality of Care, Patient Safety, Quality Measures
Berkman ND, Lohr KN, Ansari MT, et al.
AHRQ Author: Chang S
Grading the strength of a body of evidence when assessing health care interventions: an EPC update.
The purpose of this article is to revise the 2010 guidance on grading the strength of evidence (SOE) of the effectiveness of drugs, devices, and other preventive and therapeutic interventions produced by AHRQ’s Evidence-based Practice Center program. It concluded that no single approach for grading SOE suits all reviews, but a more consistent and transparent approach to reporting summary information will make reviews more useful.
AHRQ authored; AHRQ-funded 290200710056I
Citation: Berkman ND, Lohr KN, Ansari MT, et al..
Grading the strength of a body of evidence when assessing health care interventions: an EPC update.
J Clin Epidemiol. 2015 Nov;68(11):1312-24. doi: 10.1016/j.jclinepi.2014.11.023..
Keywords: Comparative Effectiveness, Evidence-Based Practice, Research Methodologies, Quality Measures
Kamal AH, Kavalieratos D, Bull J
Usability and acceptability of the QDACT-PC, an electronic point-of-care system for standardized quality monitoring in palliative care.
The researchers performed usability testing of the Quality Data Collection Tool for Palliative Care (QDACT-PC), a novel, point-of-care quality monitoring tool for palliative care. They found that testing the QDACT-PC reveals equivalence with paper for data collection time, but with less burden overall for electronic methods across other domains of usability.
AHRQ-funded; HS022989.
Citation: Kamal AH, Kavalieratos D, Bull J .
Usability and acceptability of the QDACT-PC, an electronic point-of-care system for standardized quality monitoring in palliative care.
J Pain Symptom Manage 2015 Nov;50(5):615-21. doi: 10.1016/j.jpainsymman.2015.05.013.
.
.
Keywords: Healthcare Delivery, Quality of Care, Palliative Care, Patient-Centered Healthcare, Quality Measures
Ahmed S, Siegel CA, Melmed GY
Implementing quality measures for inflammatory bowel disease.
The author argues that implementation of quality measures may depend on the care setting and whether quality measurement and improvement can be incorporated into workflows and electronic medical records. He also asserts that collaborative networks, utilization of care pathways, and standardized treatment algorithms may represent avenues for wide-scale implementation of quality improvement.
AHRQ-funded; HS021747.
Citation: Ahmed S, Siegel CA, Melmed GY .
Implementing quality measures for inflammatory bowel disease.
Curr Gastroenterol Rep 2015 Apr;17(4):14. doi: 10.1007/s11894-015-0437-1..
Keywords: Quality Measures, Quality of Care, Quality Improvement, Electronic Health Records (EHRs), Health Information Technology (HIT)
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
Konetzka RT, Brauner DJ, Coca Perraillon M
The role of severe dementia in nursing home report cards.
This article examined the intended and unintended effects of quality reporting for nursing home residents with severe dementia relative to other residents, using a difference-in-differences design to examine selected reported and unreported quality measures. The results indicate that prior to public reporting, nursing home residents with severe dementia were at significantly higher risk of poor outcomes on most reported quality measures.
AHRQ-funded; HS018718.
Citation: Konetzka RT, Brauner DJ, Coca Perraillon M .
The role of severe dementia in nursing home report cards.
Med Care Res Rev 2015 Oct;72(5):562-79. doi: 10.1177/1077558715588436.
.
.
Keywords: Dementia, Nursing Homes, Long-Term Care, Quality Measures
Johnson SL, Bartels CM, Palta M
Biological and steroid use in relationship to quality measures in older patients with inflammatory bowel disease: a US Medicare cohort study.
The researchers examined the frequency and predictors of antitumour necrosis factor (TNF) use, among US patients with inflammatory bowel disease (IBD) aged 65 years and older prior to the publication of a new Medicare quality measure calling for the use of anti-TNFs and other steroid-sparing agents. They found that anti-TNF use was very low in this population of older patients with IBD.
AHRQ-funded; HS022786.
Citation: Johnson SL, Bartels CM, Palta M .
Biological and steroid use in relationship to quality measures in older patients with inflammatory bowel disease: a US Medicare cohort study.
BMJ Open 2015 Sep 07;5(9):e008597. doi: 10.1136/bmjopen-2015-008597.
.
.
Keywords: Elderly, Digestive Disease and Health, Medication, Quality Measures
Cassel CK, Kronick R
AHRQ Author: Kronick R
Learning from the past to measure the future.
The authors argue that paying for value will not work unless it can be measured. The ability to assess health care quality and health outcomes has significantly improved over the past several decades, and there are good examples in specific organizations or clinical areas.
AHRQ-authored.
Citation: Cassel CK, Kronick R .
Learning from the past to measure the future.
JAMA 2015 Sep;314(9):875-6. doi: 10.1001/jama.2015.9186..
Keywords: Quality of Care, Quality Measures, Outcomes
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
Singh H, Sittig DF
Setting the record straight on measuring diagnostic errors. Reply to: 'Bad assumptions on primary care diagnostic errors' by Dr Richard Young.
This letter responds to a letter by Dr. Richard Young who criticizes Singh’s article on measuring diagnostic error. Singh defends his systems-based approach to advancing the science of measuring diagnostic error and acknowledges some of the uncertainties and evolution in the diagnostic process that Dr. Young writes about.
AHRQ-funded; HS022087
Citation: Singh H, Sittig DF .
Setting the record straight on measuring diagnostic errors. Reply to: 'Bad assumptions on primary care diagnostic errors' by Dr Richard Young.
BMJ Qual Saf. 2015 May;24(5):345-8. doi: 10.1136/bmjqs-2015-004140..
Keywords: Diagnostic Safety and Quality, Medical Errors, Patient Safety, Primary Care, Quality Measures
Kamal AH
Signposts along the journey toward high-quality palliative care: the value of measuring what matters.
The author of this letter discusses the rationale behind and the usefulness of the group of palliative care measures that were chosen through the deliberations of a Technical Advisory Panel, a Clinical User Panel, and public comment. He states that the 10 measures chosen represent important signposts along the journey toward high quality palliative care and that this is the first iteration of this effort, with updates planned.
AHRQ-funded; HS022763.
Citation: Kamal AH .
Signposts along the journey toward high-quality palliative care: the value of measuring what matters.
J Pain Symptom Manage 2015 May;49(5):e1-2. doi: 10.1016/j.jpainsymman.2015.03.002..
Keywords: Palliative Care, Quality of Care, Patient Safety, Quality Measures
Bardach NS, Hibbard JH, Greaves F
Sources of traffic and visitors' preferences regarding online public reports of quality: web analytics and online survey results.
Online public reports of quality exist, but little is known about how visitors find reports or about their purpose in visiting. To address this gap,the researchers gathered website analytics data from a national group of online public reports of hospital or physician quality and surveyed real-time visitors to those websites. They found that consumers were frequently interested in using the information to choose providers or assess the quality of their provider.
AHRQ-funded; 290200600023I.
Citation: Bardach NS, Hibbard JH, Greaves F .
Sources of traffic and visitors' preferences regarding online public reports of quality: web analytics and online survey results.
J Med Internet Res 2015 May;17(5):e102. doi: 10.2196/jmir.3637.
.
.
Keywords: Web-Based, Public Reporting, Quality Measures, Education: Patient and Caregiver
Schmittdiel JA, Nichols GA, Dyer W
Health care system-level factors associated with performance on Medicare STAR adherence metrics in a large, integrated delivery system.
The researchers examined the association of Medicare STAR adherence metrics with system-wide factors for patients with diabetes. They found that the strongest predictor of achieving STAR-defined medication adherence for patients with diabetes was a greater days’ supply of medications. Other important factors were use of a mail order pharmacy, lower copayments and lower annual individual out-of-pocket maximums.
AHRQ-funded; HS019859
Citation: Schmittdiel JA, Nichols GA, Dyer W .
Health care system-level factors associated with performance on Medicare STAR adherence metrics in a large, integrated delivery system.
Med Care. 2015 Apr;53(4):332-7. doi: 10.1097/mlr.0000000000000328..
Keywords: Medicare, Diabetes, Patient Adherence/Compliance, Quality Measures
Magnan EM, Palta M, Johnson HM
The impact of a patient's concordant and discordant chronic conditions on diabetes care quality measures.
The researchers sought to determine the impact of the number of concordant and discordant chronic conditions on diabetes care quality. Their findings suggest that the patients most at risk for suboptimal diabetes care are the patients with the fewest comorbidities, especially the fewest concordant comorbidities.
AHRQ-funded; HS018368; HS021899.
Citation: Magnan EM, Palta M, Johnson HM .
The impact of a patient's concordant and discordant chronic conditions on diabetes care quality measures.
J Diabetes Complications 2015 Mar;29(2):288-94. doi: 10.1016/j.jdiacomp.2014.10.003..
Keywords: Quality Measures, Diabetes, Chronic Conditions
Singh H, Sittig DF
Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework.
The authors developed a multifaceted framework to advance the science of measuring diagnostic errors (The Safer Dx framework). They described how their framework serves as a conceptual foundation for system-wide safety measurement, monitoring, and improvement of diagnostic error. They posited that the Safer Dx framework can be used by a variety of stakeholders including researchers, clinicians, health care organizations, and policymakers, to stimulate both retrospective and more proactive measurement of diagnostic errors.
AHRQ-funded; HS022087.
Citation: Singh H, Sittig DF .
Advancing the science of measurement of diagnostic errors in healthcare: the Safer Dx framework.
BMJ Qual Saf 2015 Feb;24(2):103-10. doi: 10.1136/bmjqs-2014-003675.
.
.
Keywords: Diagnostic Safety and Quality, Health Information Technology (HIT), Medical Errors, Patient Safety, Quality Measures
Schmittdiel J, Raebel M, Dyer W
Medicare Star excludes diabetes patients with poor CVD risk factor control.
This study is designed to improve understanding of novel CMS quality measures (adherence to antihypertensives, antihyperlipidemics, and oral antihyperglycemics) by assessing the proportion of Medicare patients with diabetes who are excluded from the Medicare Star medication adherence metrics due to early nonadherence and insulin use. Medicare’s STAR measures are used to evaluate the performance of Medicare Advantage plans.
AHRQ-funded; HS019859
Citation: Schmittdiel J, Raebel M, Dyer W .
Medicare Star excludes diabetes patients with poor CVD risk factor control.
Am J Manag Care. 2014 Dec; 20(12):e573-81..
Keywords: Medicare, Diabetes, Quality Measures, Patient Adherence/Compliance
Einbinder J, Hebel E, Wright A
The number needed to remind: a measure for assessing CDS effectiveness.
The purpose of this paper is to provide a better understanding of population based clinical decision support (CDS) performance measurement, to identify best practices for designing and implementing CDS, and to introduce two new quality measures, titled Reminder Performance (RP) and the Number Needed to Remind (NNR) for evaluating the effectiveness of clinical reminders in the context of the CDS Dashboards.
AHRQ-funded; 290200810010.
Citation: Einbinder J, Hebel E, Wright A .
The number needed to remind: a measure for assessing CDS effectiveness.
AMIA Annu Symp Proc 2014 Nov 14;2014:506-15..
Keywords: Decision Making, Clinical Decision Support (CDS), Quality Measures, Quality of Care
Garg N, Kuperman G, Onyile A
Validating health information exchange (HIE) data for quality measurement across four hospitals.
The study objective was to validate the secondary use of HIE data for two emergency department (ED) quality measures: identification of frequent ED users and early (72-hour) ED returns in four hospitals. It found that there was no significant difference in the total counts for frequent ED users or early ED returns for any of the four hospitals.
AHRQ-funded; HS021261.
Citation: Garg N, Kuperman G, Onyile A .
Validating health information exchange (HIE) data for quality measurement across four hospitals.
AMIA Annu Symp Proc 2014 Nov 14;2014:573-9..
Keywords: Electronic Health Records (EHRs), Emergency Department, Quality of Care, Health Information Exchange (HIE), Quality Measures
Lucas JA, Chakravarty S, Bowblis JR
Antipsychotic medication use in nursing homes: a proposed measure of quality.
There is an important need for a more specific measure of quality related to antipsychotic medication (APM) use. This paper proposes such a measure, compares it with the APM quality measure introduced by CMS in 2012 and examines variation in these two measures across resident and facility characteristics using a multi-state case demonstration of long-stay NH residents.
AHRQ-funded; HS021112.
Citation: Lucas JA, Chakravarty S, Bowblis JR .
Antipsychotic medication use in nursing homes: a proposed measure of quality.
Int J Geriatr Psychiatry 2014 Oct;29(10):1049-61. doi: 10.1002/gps.4098..
Keywords: Medication, Nursing Homes, Elderly, Quality Measures, Quality Measures
Anhang Price R, Elliott MN, Zaslavsky AM
Examining the role of patient experience surveys in measuring health care quality.
The authors reviewed the literature on the association between patient experiences and other measures of health care quality. They concluded that patient experience measures that are collected using psychometrically sound instruments, employing recommended sample sizes and adjustment procedures, and implemented according to standard protocols are intrinsically meaningful and are appropriate complements for clinical process and outcome measures in public reporting and pay-for-performance programs.
AHRQ-funded; HS016980; HS016978.
Citation: Anhang Price R, Elliott MN, Zaslavsky AM .
Examining the role of patient experience surveys in measuring health care quality.
Med Care Res Rev 2014 Oct;71(5):522-54. doi: 10.1177/1077558714541480.
.
.
Keywords: Consumer Assessment of Healthcare Providers and Systems (CAHPS), Patient Experience, Quality of Care, Quality Improvement, Quality Measures
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
Mistry KB, Chesley F, Llanos K
AHRQ Author: Mistry KB, Chesley F, Dougherty D.
Advancing children's health care and outcomes through the pediatric quality measures program.
This article focuses on the Pediatric Quality Measures Program and provides an overview of the program's goals and related activities, lessons learned, and future opportunities.
AHRQ-authored.
Citation: Mistry KB, Chesley F, Llanos K .
Advancing children's health care and outcomes through the pediatric quality measures program.
Acad Pediatr 2014 Sep-Oct;14(5 Suppl):S19-26. doi: 10.1016/j.acap.2014.06.025.
.
.
Keywords: Children's Health Insurance Program (CHIP), Quality of Care, Health Services Research (HSR), Children/Adolescents, Quality Measures