National Healthcare Quality and Disparities Report
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Topics
- Adverse Drug Events (ADE) (4)
- Adverse Events (5)
- Antimicrobial Stewardship (1)
- Asthma (1)
- Autism (1)
- Care Management (1)
- Catheter-Associated Urinary Tract Infection (CAUTI) (1)
- Children/Adolescents (9)
- Chronic Conditions (1)
- (-) Clinical Decision Support (CDS) (45)
- Clinician-Patient Communication (1)
- Communication (1)
- Comparative Effectiveness (1)
- Data (2)
- Decision Making (11)
- Diagnostic Safety and Quality (5)
- Digestive Disease and Health (1)
- Disabilities (1)
- Ear Infections (1)
- Electronic Health Records (EHRs) (15)
- Electronic Prescribing (E-Prescribing) (1)
- Emergency Medical Services (EMS) (1)
- Evidence-Based Practice (2)
- Genetics (1)
- Guidelines (1)
- Healthcare-Associated Infections (HAIs) (1)
- Healthcare Costs (1)
- Health Information Exchange (HIE) (1)
- Health Information Technology (HIT) (25)
- Health Services Research (HSR) (1)
- Heart Disease and Health (2)
- Hepatitis (1)
- Home Healthcare (1)
- Hospitals (1)
- Human Immunodeficiency Virus (HIV) (1)
- Imaging (1)
- Kidney Disease and Health (1)
- Long-Term Care (1)
- Medical Errors (3)
- Medication (9)
- Newborns/Infants (1)
- Nursing (1)
- Nursing Homes (2)
- Nutrition (1)
- Obesity (2)
- Obesity: Weight Management (1)
- Outcomes (1)
- Patient-Centered Healthcare (1)
- Patient-Centered Outcomes Research (4)
- Patient Adherence/Compliance (1)
- Patient Safety (7)
- Patient Self-Management (1)
- Practice Patterns (4)
- Pressure Ulcers (1)
- Prevention (2)
- Primary Care (6)
- Public Reporting (1)
- Quality Improvement (1)
- Quality Measures (1)
- Quality of Care (1)
- Risk (1)
- Sepsis (1)
- Transplantation (2)
- Urinary Tract Infection (UTI) (1)
- Workflow (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 25 of 45 Research Studies DisplayedGoldstein SL
Automated/integrated real-time clinical decision support in acute kidney injury.
The author argues that early, real-time identification and notification to healthcare providers of patients at risk for, or with, acute or chronic kidney disease can drive simple interventions to reduce harm. Similarly, he believes that screening patients at risk for acute kidney injury with these platforms to alert research personnel will lead to improve study subject recruitment.
AHRQ-funded; HS023763; HS021114.
Citation: Goldstein SL .
Automated/integrated real-time clinical decision support in acute kidney injury.
Curr Opin Crit Care 2015 Dec;21(6):485-9. doi: 10.1097/mcc.0000000000000250.
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Keywords: Clinical Decision Support (CDS), Kidney Disease and Health, Electronic Health Records (EHRs), Patient-Centered Outcomes Research, Diagnostic Safety and Quality
Almario CV, Chey WD, Iriana S
Computer versus physician identification of gastrointestinal alarm features.
This study's objective was to compare the number of alarms documented by physicians during usual care vs. that collected by a computer algorithm called Automated Evaluation of Gastrointestinal Symptoms (AEGIS). AEGIS identified more patients with positive alarm features compared to physicians and also documented more positive alarms. Moreover, clinicians documented only 30% of the positive alarms self-reported by patients through AEGIS.
AHRQ-funded; HS000046.
Citation: Almario CV, Chey WD, Iriana S .
Computer versus physician identification of gastrointestinal alarm features.
Int J Med Inform 2015 Dec;84(12):1111-7. doi: 10.1016/j.ijmedinf.2015.07.006.
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Keywords: Clinical Decision Support (CDS), Diagnostic Safety and Quality, Digestive Disease and Health, Electronic Health Records (EHRs), Patient Safety
Liang C, Gong Y
Enhancing patient safety event reporting by K-nearest neighbor classifier.
The debate on structured or unstructured data entry reveals not only a trade-off problem among data accuracy, completeness, and timeliness, but also a technical gap on text mining. The reesarchers suggested a text classification method for predicting subject categories. Their results demonstrated the feasibility of their system and indicated the advantage of such an application to raise data quality and clinical decision support in reporting patient safety events.
AHRQ-funded; HS022895.
Citation: Liang C, Gong Y .
Enhancing patient safety event reporting by K-nearest neighbor classifier.
Stud Health Technol Inform 2015;218:40603.
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Keywords: Adverse Events, Medical Errors, Patient Safety, Public Reporting, Clinical Decision Support (CDS), Health Information Technology (HIT), Data
Lo Re V, 3rd, Haynes K, Forde KA
Risk of acute liver failure in patients with drug-induced liver injury: evaluation of Hy's Law and a new prognostic model.
The researchers aimed to develop a highly sensitive model to identify drug-induced liver injury (DILI) patients at increased risk of acute liver failure (ALF). negative predictive value (0.99), but low level of sensitivity (0.68) and positive predictive value (0.02). Their model, comprising data on platelet count and total bilirubin level, identified patients with ALF with a C statistic of 0.87 and enabled calculation of a risk score (Drug-Induced Liver Toxicity ALF Score).
AHRQ-funded; HS018372.
Citation: Lo Re V, 3rd, Haynes K, Forde KA .
Risk of acute liver failure in patients with drug-induced liver injury: evaluation of Hy's Law and a new prognostic model.
Clin Gastroenterol Hepatol 2015 Dec;13(13):2360-8. doi: 10.1016/j.cgh.2015.06.020.
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Keywords: Antimicrobial Stewardship, Medication, Chronic Conditions, Adverse Drug Events (ADE), Clinical Decision Support (CDS)
Panahiazar M, Taslimitehrani V, Pereira NL
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
The authors developed a multidimensional patient similarity assessment technique that leverages multiple types of information from the electronic health records and predicts a medication plan for each new patient based on prior knowledge and data from similar patients.Their findings suggest that it is feasible to harness population-based information for an individual patient-specific assessment.
AHRQ-funded; HS023077.
Citation: Panahiazar M, Taslimitehrani V, Pereira NL .
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
Stud Health Technol Inform 2015;210:369-73.
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Keywords: Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare
Islam R, Weir CR, Jones M
Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.
The purpose of the study was to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment. The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety.
AHRQ-funded; HS023349.
Citation: Islam R, Weir CR, Jones M .
Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.
BMC Med Inform Decis Mak 2015 Nov 30;15:101. doi: 10.1186/s12911-015-0221-z.
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Keywords: Clinical Decision Support (CDS), Health Services Research (HSR), Practice Patterns
Wright A, Sittig DF, Ash JS
Lessons learned from implementing service-oriented clinical decision support at four sites: a qualitative study.
This study identified challenges, lessons learned and best practices for service-oriented clinical decision support, based on the results of the Clinical Decision Support Consortium, a multi-site study which developed, implemented and evaluated clinical decision support services in a diverse range of electronic health records. Based on the challenges and lessons learned, there were eight best practices for developers and implementers of service-oriented clinical decision support.
AHRQ-funded; 290200810010.
Citation: Wright A, Sittig DF, Ash JS .
Lessons learned from implementing service-oriented clinical decision support at four sites: a qualitative study.
Int J Med Inform 2015 Nov;84(11):901-11. doi: 10.1016/j.ijmedinf.2015.08.008.
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Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Decision Making, Health Information Technology (HIT)
Gephart S, Carrington JM, Finley B
A systematic review of nurses' experiences with unintended consequences when using the electronic health record.
The purpose of this article is to present the state of the science on nurses' experiences with unintended consequences of electronic health records (EHRs). Findings demonstrate that nurses experience changes to workflow, must continually adapt to meet patient's needs in the context of imperfect EHR systems, and have difficulty accessing the information they need to make patient care decisions. Implications for nurse administrators include the need for continual engagement with nurses along the continuum of EHR design, as well as the need to encourage nurses to speak up and acknowledge workflow changes that threaten patient safety or do not support work efficiency.
AHRQ-funded; HS021074.
Citation: Gephart S, Carrington JM, Finley B .
A systematic review of nurses' experiences with unintended consequences when using the electronic health record.
Nurs Adm Q 2015 Oct-Dec;39(4):345-56. doi: 10.1097/naq.0000000000000119.
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Keywords: Adverse Events, Clinical Decision Support (CDS), Electronic Health Records (EHRs), Nursing, Workflow
Fumo DE, Kapoor V, Reece LJ
Historical matching strategies in kidney paired donation: the 7-year evolution of a web-based virtual matching system.
Failure to convert computer-identified possible kidney paired donation (KPD) exchanges into transplants has prohibited KPD from reaching its full potential. This study analyzes the progress of exchanges in moving from "offers" to completed transplants. The "offer" and 1-way success rates were 21.9 and 15.5 percent, respectively. Three reasons for failure were found that could be prospectively prevented by changes in protocol or software.
AHRQ-funded; HS020610.
Citation: Fumo DE, Kapoor V, Reece LJ .
Historical matching strategies in kidney paired donation: the 7-year evolution of a web-based virtual matching system.
Am J Transplant 2015 Oct;15(10):2646-54. doi: 10.1111/ajt.13337.
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Keywords: Health Information Technology (HIT), Transplantation, Decision Making, Clinical Decision Support (CDS)
Bray M, Wang W, Song PX
Planning for uncertainty and fallbacks can increase the number of transplants in a kidney-paired donation program.
The researchers outlined and examined, through example and by simulation, four schemes for selecting potential matches in a realistic model of a kidney-paired donation system. Their proposed schemes take account of probabilities that chosen transplants may not be completed as well as allowing for contingency plans when the optimal solution fails.
AHRQ-funded; HS020610.
Citation: Bray M, Wang W, Song PX .
Planning for uncertainty and fallbacks can increase the number of transplants in a kidney-paired donation program.
Am J Transplant 2015 Oct;15(10):2636-45. doi: 10.1111/ajt.13413.
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Keywords: Transplantation, Clinical Decision Support (CDS), Health Information Technology (HIT)
Dugan TM, Mukhopadhyay S, Carroll A
Machine learning techniques for prediction of early childhood obesity.
This study aimed to predict childhood obesity after age two, using only data collected prior to the second birthday by a clinical decision support system called CHICA. It demonstrated that data from a production clinical decision support system can be used to build an accurate machine learning model to predict obesity in children after age two.
AHRQ-funded; HS020640; HS018453; HS017939.
Citation: Dugan TM, Mukhopadhyay S, Carroll A .
Machine learning techniques for prediction of early childhood obesity.
Appl Clin Inform 2015 Aug 12;6(3):506-20. doi: 10.4338/aci-2015-03-ra-0036.
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Keywords: Children/Adolescents, Obesity, Health Information Technology (HIT), Clinical Decision Support (CDS), Children/Adolescents
El-Jawahri A, Mitchell SL, Paasche-Orlow MK
A randomized controlled trial of a CPR and intubation video decision support tool for hospitalized patients.
The researchers examined the impact of a video decision tool for CPR and intubation on patients’ choices, knowledge, medical orders, and discussions with providers. They found that seriously ill patients who viewed a video about CPR and intubation were more likely not to want these treatments, be better informed about their options, have orders to forgo CPR/ intubation, and discuss preferences with providers.
AHRQ-funded; HS018780.
Citation: El-Jawahri A, Mitchell SL, Paasche-Orlow MK .
A randomized controlled trial of a CPR and intubation video decision support tool for hospitalized patients.
J Gen Intern Med 2015 Aug;30(8):1071-80. doi: 10.1007/s11606-015-3200-2..
Keywords: Patient-Centered Outcomes Research, Clinical Decision Support (CDS), Decision Making, Clinician-Patient Communication
Pho MT, Jensen DM, Meltzer DO
Clinical impact of treatment timing for chronic hepatitis C infection: a decision model.
The researchers developed a decision model to quantify the trade-offs between immediate, interferon-containing therapy and delayed, interferon-free therapy for patients with chronic, genotype 1 HCV infection. They found that compared to one-time immediate treatment with the interferon-containing regimen, delayed treatment with the interferon-free regimen in 1 year resulted in longer life expectancy.
AHRQ-funded; HS022433.
Citation: Pho MT, Jensen DM, Meltzer DO .
Clinical impact of treatment timing for chronic hepatitis C infection: a decision model.
J Viral Hepat 2015 Aug;22(8):630-8. doi: 10.1111/jvh.12412..
Keywords: Clinical Decision Support (CDS), Decision Making, Hepatitis, Medication, Outcomes
Nuckols TK, Asch SM, Patel V
Implementing Computerized Provider Order Entry In Acute Care Hospitals in the United States could generate substantial savings to society.
This study was conducted to evaluate from the societal perspective the cost-utility of implementing computerized physician order entry (CPOE) in acute care hospitals in the United States. It found that relative to paper ordering and using typical estimates of implementation costs, CPOE had, on average, a 99 percent probability of yielding savings to society and improving health.
AHRQ-funded; HS017954.
Citation: Nuckols TK, Asch SM, Patel V .
Implementing Computerized Provider Order Entry In Acute Care Hospitals in the United States could generate substantial savings to society.
Jt Comm J Qual Patient Saf 2015 Aug;41(8):341-50..
Keywords: Health Information Technology (HIT), Hospitals, Clinical Decision Support (CDS), Healthcare Costs
Bauer NS, Carroll AE, Saha C
Computer decision support changes physician practice but not knowledge regarding autism spectrum disorders.
This study examined whether adding an autism module promoting adherence to clinical guidelines to an existing computer decision support system (CDSS) changed physician knowledge and self-reported clinical practice. It found that a CDSS module to improve primary care management of ASD in pediatric practice led to significant improvements in physician-reported use of validated screening tools to screen for ASDs.
AHRQ-funded; HS018453.
Citation: Bauer NS, Carroll AE, Saha C .
Computer decision support changes physician practice but not knowledge regarding autism spectrum disorders.
Appl Clin Inform 2015;6(3):454-65. doi: 10.4338/aci-2014-09-ra-0084.
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Keywords: Health Information Technology (HIT), Practice Patterns, Clinical Decision Support (CDS), Children/Adolescents, Autism
Melnick ER, Keegan J, Taylor RA
Redefining overuse to include costs: a decision analysis for computed tomography in minor head injury.
This study was conducted to (1) determine the testing threshold for head computed tomography (CT) in minor head injury in the emergency department using decision analysis with and without costs included in the analysis. If only effectiveness is considered, current clinical decision rules might not provide a sufficient degree of certainty to ensure identification of all patients for whom the benefits of CT outweigh its risks.
AHRQ-funded; HS021271.
Citation: Melnick ER, Keegan J, Taylor RA .
Redefining overuse to include costs: a decision analysis for computed tomography in minor head injury.
Jt Comm J Qual Patient Saf 2015 Jul;41(7):313-22..
Keywords: Clinical Decision Support (CDS), Decision Making, Imaging, Emergency Medical Services (EMS)
Makam AN, Nguyen OK, Auerbach AD
Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: a systematic review.
This review aimed to determine whether automated real-time electronic sepsis alerts can: (1) accurately identify sepsis and (2) improve process measures and outcomes. It found that automated sepsis alerts derived from electronic health data may improve care processes but tend to have poor positive predictive value and do not improve mortality or length of stay.
AHRQ-funded; HS022418.
Citation: Makam AN, Nguyen OK, Auerbach AD .
Diagnostic accuracy and effectiveness of automated electronic sepsis alert systems: a systematic review.
J Hosp Med 2015 Jun;10(6):396-402. doi: 10.1002/jhm.2347..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Sepsis, Diagnostic Safety and Quality, Patient-Centered Outcomes Research
Overby CL, Devine EB, Abernethy N
Making pharmacogenomic-based prescribing alerts more effective: a scenario-based pilot study with physicians.
This pilot study explored the communication effectiveness and clinical impact of using a prototype clinical decision support (CDS) system embedded in an electronic health record (EHR) to deliver pharmacogenomic (PGx) information to physicians. The proportion of physicians that saw a relative advantage to using PGx-CDS was 83 percent at the start and 94 percent at the conclusion of our study.
AHRQ-funded; HS014739.
Citation: Overby CL, Devine EB, Abernethy N .
Making pharmacogenomic-based prescribing alerts more effective: a scenario-based pilot study with physicians.
J Biomed Inform 2015 Jun;55:249-59. doi: 10.1016/j.jbi.2015.04.011..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Patient Safety
McDonald MV, Feldman PH, Barron-Vaya Y
Outcomes of clinical decision support (CDS) and correlates of CDS use for home care patients with high medication regimen complexity: a randomized trial.
The researchers assessed the outcomes of a clinical decision support (CDS) intervention designed for home care patients with high medication regimen complexity (MRC) and examined correlates of CDS use. They found that eighty-two percent of intervention nurses used the CDS but for only 42 percent of their patients. Among intervention patients, CDS use (vs. non-use) was associated with reduced MRC and hospitalization.
AHRQ-funded; HS017837.
Citation: McDonald MV, Feldman PH, Barron-Vaya Y .
Outcomes of clinical decision support (CDS) and correlates of CDS use for home care patients with high medication regimen complexity: a randomized trial.
J Eval Clin Pract 2015 May 26;22(1):10-19. doi: 10.1111/jep.12383.
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Keywords: Clinical Decision Support (CDS), Home Healthcare, Medication, Risk
Moss J, Berner ES
Evaluating clinical decision support tools for medication administration safety in a simulated environment.
This study aimed to develop a methodology and tools for the design of clinical decision support systems to decrease the incidence of medication administration errors. Nurses’ evaluation of the medication administration decision support tools as well as their actual performance revealed a tendency to underestimate their need for support. Their preferences were for decision support that was short, color coded, and easily accessed.
AHRQ-funded; HS016660.
Citation: Moss J, Berner ES .
Evaluating clinical decision support tools for medication administration safety in a simulated environment.
Int J Med Inform 2015 May;84(5):308-18. doi: 10.1016/j.ijmedinf.2015.01.018..
Keywords: Patient Safety, Clinical Decision Support (CDS), Medication, Adverse Drug Events (ADE)
Kuhn L, Reeves K, Taylor Y
Planning for action: the impact of an asthma action plan decision support tool integrated into an electronic health record (EHR) at a large health care system.
This project aimed to embed an electronic asthma action plan decision support tool (eAAP) into the medical record to streamline evidence-based guidelines for providers at the point of care, create individualized patient handouts, and evaluate effects on disease outcomes. Its findings supports existing evidence that patient self-management plays an important role in reducing asthma exacerbations.
AHRQ-funded; HS019946.
Citation: Kuhn L, Reeves K, Taylor Y .
Planning for action: the impact of an asthma action plan decision support tool integrated into an electronic health record (EHR) at a large health care system.
J Am Board Fam Med 2015 May-Jun;28(3):382-93. doi: 10.3122/jabfm.2015.03.140248..
Keywords: Electronic Health Records (EHRs), Clinical Decision Support (CDS), Asthma, Patient Self-Management, Evidence-Based Practice
Ash JS, Sittig DF, McMullen CK
Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations.
The purpose of this study was to discover how the views of clinical stakeholders, clinical decision support (CDS) content vendors, and EHR vendors are alike or different with respect to challenges in the development, management, and use of CDS. The groups share views on the importance of appropriate manpower, careful knowledge management, CDS that fits user workflow, and the need for communication among the groups.
AHRQ-funded; 290200810010.
Citation: Ash JS, Sittig DF, McMullen CK .
Multiple perspectives on clinical decision support: a qualitative study of fifteen clinical and vendor organizations.
BMC Med Inform Decis Mak 2015 Apr 24;15:35. doi: 10.1186/s12911-015-0156-4..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT)
Fiks AG, Zhang P, Localio AR
Adoption of electronic medical record-based decision support for otitis media in children.
The authors characterized adoption of an otitis media clinical decision support (CDS) system, the impact of performance feedback on adoption, and the effects of adoption on guideline adherence. The performance feedback increased CDS adoption, but additional strategies are needed to integrate CDS into primary care workflows.
AHRQ-funded; HS017042
Citation: Fiks AG, Zhang P, Localio AR .
Adoption of electronic medical record-based decision support for otitis media in children.
Health Serv Res. 2015 Apr;50(2):489-513. doi: 10.1111/1475-6773.12240..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Ear Infections, Electronic Health Records (EHRs), Health Information Technology (HIT)
Tannenbaum D, Doctor JN, Persell SD
Nudging physician prescription decisions by partitioning the order set: results of a vignette-based study.
The purpose of this study was to examine whether the grouping of menu items systematically affects prescribing practices among primary care providers. It found that provider treatment choice appears to be influenced by the grouping of menu options, suggesting that the layout of EHR order sets is not an arbitrary exercise.
AHRQ-funded; RC4 AG039115 (NIA/AHRQ).
Citation: Tannenbaum D, Doctor JN, Persell SD .
Nudging physician prescription decisions by partitioning the order set: results of a vignette-based study.
J Gen Intern Med 2015 Mar;30(3):298-304. doi: 10.1007/s11606-014-3051-2..
Keywords: Electronic Health Records (EHRs), Primary Care, Clinical Decision Support (CDS), Health Information Technology (HIT), Medication
Hendrix KS, Downs SM, Carroll AE
Pediatricians' responses to printed clinical reminders: does highlighting prompts improve responsiveness?
The authors tested whether selectively highlighting clinical decision support prompts in yellow would improve physicians' responsiveness. They found that highlighting reminder prompts did not increase physicians' responsiveness. They suggested possible explanations and offer alternative strategies to increasing physician responsiveness to prompts.
AHRQ-funded; HS020640; HS018453; HS017939.
Citation: Hendrix KS, Downs SM, Carroll AE .
Pediatricians' responses to printed clinical reminders: does highlighting prompts improve responsiveness?
Acad Pediatr 2015 Mar-Apr;15(2):158-64. doi: 10.1016/j.acap.2014.10.009.
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Keywords: Clinical Decision Support (CDS), Children/Adolescents, Primary Care, Practice Patterns, Quality Improvement