National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (4)
- Adverse Events (4)
- Antimicrobial Stewardship (1)
- Asthma (1)
- Autism (1)
- Care Management (1)
- Children/Adolescents (6)
- Chronic Conditions (1)
- (-) Clinical Decision Support (CDS) (38)
- Clinician-Patient Communication (1)
- Communication (1)
- Comparative Effectiveness (1)
- Critical Care (1)
- Data (2)
- Diagnostic Safety and Quality (5)
- Digestive Disease and Health (1)
- Ear Infections (1)
- Electronic Health Records (EHRs) (13)
- Emergency Medical Services (EMS) (1)
- Evidence-Based Practice (3)
- Falls (1)
- Guidelines (2)
- Healthcare Costs (1)
- Health Information Technology (HIT) (18)
- Health Services Research (HSR) (1)
- Heart Disease and Health (1)
- Hepatitis (1)
- Home Healthcare (1)
- Hospitalization (1)
- Hospitals (3)
- Imaging (1)
- Infectious Diseases (1)
- Injuries and Wounds (1)
- Inpatient Care (3)
- Kidney Disease and Health (1)
- Medical Errors (2)
- Medication (8)
- Nursing (2)
- Obesity (2)
- Obesity: Weight Management (1)
- Outcomes (1)
- Patient-Centered Healthcare (1)
- Patient-Centered Outcomes Research (3)
- Patient Safety (11)
- Patient Self-Management (1)
- Practice Patterns (3)
- Pressure Ulcers (1)
- Prevention (2)
- Primary Care (2)
- Provider (1)
- Provider: Nurse (1)
- Provider: Physician (1)
- Public Reporting (1)
- Quality Improvement (1)
- Risk (3)
- Sepsis (2)
- Shared Decision Making (9)
- Tools & Toolkits (1)
- Transplantation (2)
- 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 38 Research Studies DisplayedWang J, Gong Y
Potential of decision support in preventing pressure ulcers in hospitals.
The development of hospital-acquired pressure ulcers signals low quality of care. To meet the challenges of consistently translating best practices into effective clinical practices and promote effective teamwork communication and interprofessional collaboration, the authors consider the failure of consistent care delivery as loss of information and reveal the opportunities of informatics methods to reinforce information delivery, evidenced by typical cases. They then explain and summarize information-related issues existing at the initial assessment upon hospital admission, routine treatments, and team communication.
AHRQ-funded; HS022895.
Citation: Wang J, Gong Y .
Potential of decision support in preventing pressure ulcers in hospitals.
Stud Health Technol Inform 2017;241:15-20.
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Keywords: Clinical Decision Support (CDS), Shared Decision Making, Hospitals, Patient Safety, Pressure Ulcers, Prevention
Dykes PC, Duckworth M, Cunningham S
Pilot testing Fall TIPS (Tailoring Interventions for Patient Safety): a patient-centered fall prevention toolkit.
Patient falls during an acute hospitalization cause injury, reduced mobility, and increased costs. The laminated paper Fall TIPS Toolkit (Fall TIPS) provides clinical decision support at the bedside by linking each patient's fall risk assessment with evidence-based interventions. The investigators examined strategies to integrate this evidence into clinical practice. They concluded that engaging hospital and clinical leadership is critical in translating evidence-based care into clinical practice. They address and detail barriers to adoption of the protocol to provide guidance for spread to other institutions.
AHRQ-funded; HS025128.
Citation: Dykes PC, Duckworth M, Cunningham S .
Pilot testing Fall TIPS (Tailoring Interventions for Patient Safety): a patient-centered fall prevention toolkit.
Jt Comm J Qual Patient Saf 2017 Aug;43(8):403-13. doi: 10.1016/j.jcjq.2017.05.002..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Evidence-Based Practice, Falls, Hospitals, Injuries and Wounds, Inpatient Care, Patient Safety, Prevention, Risk, Tools & Toolkits
Roosan D, Weir C, Samore M
Identifying complexity in infectious diseases inpatient settings: an observation study.
This study sought to identify specific complexity-contributing factors in the infectious disease domain and the relationship with the complexity perceived by clinicians. Its factor analysis revealed three factors explaining 47 percent of total variance, namely task interaction and goals, urgency and acuity, and psychosocial behavior. A linear regression analysis showed no statistically significant association between complexity perceived by the physicians and objective complexity.
AHRQ-funded; HS023349.
Citation: Roosan D, Weir C, Samore M .
Identifying complexity in infectious diseases inpatient settings: an observation study.
J Biomed Inform 2017 Jul;71s:S13-s21. doi: 10.1016/j.jbi.2016.10.018.
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Keywords: Clinical Decision Support (CDS), Infectious Diseases, Inpatient Care, Patient Safety
Le P, Martinez KA, Pappas MA
A decision model to estimate a risk threshold for venous thromboembolism prophylaxis in hospitalized medical patients.
To determine a threshold for prophylaxis based on risk of venous thromboembolism, the researchers constructed a decision model with a decision-tree following patients for 3 months after hospitalization, and a lifetime Markov model with 3-month cycles. They found that the prophylaxis threshold was relatively insensitive to low-molecular-weight heparin cost and bleeding risk, but very sensitive to patient age and life expectancy.
AHRQ-funded; HS022883.
Citation: Le P, Martinez KA, Pappas MA .
A decision model to estimate a risk threshold for venous thromboembolism prophylaxis in hospitalized medical patients.
J Thromb Haemost 2017 Jun;15(6):1132-41. doi: 10.1111/jth.13687.
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Keywords: Adverse Events, Clinical Decision Support (CDS), Inpatient Care, Patient Safety, Risk
Ancker JS, Edwards A, Nosal S
Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.
In this study, the investigators tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time. The investigators found that clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert.
AHRQ-funded; HS021531.
Citation: Ancker JS, Edwards A, Nosal S .
Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.
BMC Med Inform Decis Mak 2017 Apr 10;17(1):1-9. doi: 10.1186/s12911-017-0430-8..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Provider, Provider: Nurse, Provider: Physician
Bhattacharjee P, Edelson DP, Churpek MM
Identifying patients with sepsis on the hospital wards.
The goal of this review was to discuss recent advances in the detection of sepsis in patients on the hospital wards. The investigators discuss data highlighting the benefits and limitations of the systemic inflammatory response syndrome (SIRS) criteria for screening patients with sepsis, such as its low specificity, as well as newly described scoring systems, including the proposed role of the quick sepsis-related organ failure assessment (qSOFA) score.
AHRQ-funded; HS000078.
Citation: Bhattacharjee P, Edelson DP, Churpek MM .
Identifying patients with sepsis on the hospital wards.
Chest 2017 Apr;151(4):898-907. doi: 10.1016/j.chest.2016.06.020..
Keywords: Clinical Decision Support (CDS), Diagnostic Safety and Quality, Hospitalization, Sepsis
Dunn Lopez K, Gephart SM, Raszewski R
Integrative review of clinical decision support for registered nurses in acute care settings.
To report on the state of the science of clinical decision support (CDS) for hospital bedside nurses, the researchers performed an integrative review of qualitative and quantitative peer-reviewed original research studies. They concluded that clinical support systems targeting bedside nurses have positive effects on outcomes and hold promise for improving care quality.
AHRQ-funded; HS022908.
Citation: Dunn Lopez K, Gephart SM, Raszewski R .
Integrative review of clinical decision support for registered nurses in acute care settings.
J Am Med Inform Assoc 2017 Mar 1;24(2):441-50. doi: 10.1093/jamia/ocw084.
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Keywords: Critical Care, Clinical Decision Support (CDS), Health Information Technology (HIT), Nursing, Patient Safety
Romagnoli KM, Nelson SD, Hines L
Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.
To better understand the information needs and work practices of specialists who search and synthesize potential drug-drug interactions (PDDIs) evidence for drug information resources, the researchers conducted an inquiry that combined a thematic analysis of published literature with unstructured interviews. Their review of 92 papers and 10 interviews identified 56 categories of information needs related to the interpretation of PDDI information including drug and interaction information, study design and evidence including clinical details.
AHRQ-funded; HS019461.
Citation: Romagnoli KM, Nelson SD, Hines L .
Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.
BMC Med Inform Decis Mak 2017 Feb 22;17(1):21. doi: 10.1186/s12911-017-0419-3.
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Keywords: Guidelines, Clinical Decision Support (CDS), Medication, Adverse Drug Events (ADE)
Horsky J, Aarts J, Verheul L
Clinical reasoning in the context of active decision support during medication prescribing.
The purpose of this study was to describe and analyze reasoning patterns of clinicians responding to drug-drug interaction alerts in order to understand the role of patient-specific information in the decision-making process about the risks and benefits of medication therapy. The investigators found that declining an alert suggestion was preceded by sometimes brief but often complex reasoning, prioritizing different aspects of care quality and safety, especially when the perceived risk was higher.
AHRQ-funded; HS021094.
Citation: Horsky J, Aarts J, Verheul L .
Clinical reasoning in the context of active decision support during medication prescribing.
Int J Med Inform 2017 Jan;97:1-11. doi: 10.1016/j.ijmedinf.2016.09.004..
Keywords: Adverse Drug Events (ADE), Adverse Events, Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Medication, Patient Safety
Goldstein 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), Shared 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, Shared 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), Shared 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), Shared 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), Shared Decision Making, Imaging, Emergency Medical Services (EMS)