National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Events (3)
- Blood Clots (1)
- Care Coordination (1)
- Care Management (1)
- Diagnostic Safety and Quality (2)
- Electronic Health Records (EHRs) (8)
- Emergency Department (1)
- Evidence-Based Practice (2)
- Healthcare-Associated Infections (HAIs) (1)
- (-) Health Information Technology (HIT) (12)
- Health Systems (1)
- Hospitalization (1)
- Hospitals (3)
- Implementation (1)
- Mortality (1)
- Outcomes (1)
- Patient-Centered Healthcare (1)
- Patient Safety (2)
- Payment (1)
- Prevention (1)
- Primary Care (2)
- Provider Performance (2)
- (-) Quality Improvement (12)
- Quality Indicators (QIs) (1)
- Quality Measures (1)
- (-) Quality of Care (12)
- Sepsis (1)
- Surgery (2)
- Vulnerable Populations (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 12 of 12 Research Studies DisplayedShi J, Hurdle JF, Johnson SA
Natural language processing for the surveillance of postoperative venous thromboembolism.
The objective of the study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes. The investigators concluded that accurate surveillance of postoperative venous thromboembolism may be achieved using natural language processing on clinical notes in 2 independent health care systems. They indicated that these findings suggest natural language processing may augment manual chart abstraction for large registries such as National Surgical Quality Improvement Program.
AHRQ-funded; HS025776.
Citation: Shi J, Hurdle JF, Johnson SA .
Natural language processing for the surveillance of postoperative venous thromboembolism.
Surgery 2021 Oct;170(4):1175-82. doi: 10.1016/j.surg.2021.04.027..
Keywords: Blood Clots, Health Information Technology (HIT), Quality Improvement, Quality of Care, Surgery, Adverse Events
Cifra CL, Sittig DF, Singh H
Bridging the feedback gap: a sociotechnical approach to informing clinicians of patients' subsequent clinical course and outcomes.
This paper discusses challenges to the development of systems for effective patient outcome feedback to improve diagnosis and proposes the application of a sociotechnical approach using health information technology (HIT) to support the implementation of such systems. It discusses current barriers to effective clinician feedback, reasons for them, and features of potential IT solutions. Evaluation and implementation of the feedback process within a sociotechnical health system are then discussed. The authors use an eight-dimension sociotechnical model for studying health IT by authors Sittig and Singh. The eight dimensions are hardware and software; clinical content; human–computer interface; people; workflow and communication; organisational policies and procedures; external rules, regulations and pressures; and system measurement and monitoring. A table is included that shows the potential considerations for each dimension.
AHRQ-funded; 33201500022I; HS027363.
Citation: Cifra CL, Sittig DF, Singh H .
Bridging the feedback gap: a sociotechnical approach to informing clinicians of patients' subsequent clinical course and outcomes.
BMJ Qual Saf 2021 Jul;30(7):591-97. doi: 10.1136/bmjqs-2020-012464..
Keywords: Health Information Technology (HIT), Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care
Zhu Y, Simon GJ, Wick EC
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. The purpose of the study was to understand the generalizability of a machine learning algorithm between sites; automated surgical site infection (SSI) detection algorithms developed at one center were tested at another distinct center.
AHRQ-funded; HS024532.
Citation: Zhu Y, Simon GJ, Wick EC .
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
J Am Coll Surg 2021 Jun;232(6):963-71.e1. doi: 10.1016/j.jamcollsurg.2021.03.026..
Keywords: Healthcare-Associated Infections (HAIs), Surgery, Adverse Events, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Dowding D, Merrill J, Russell D
Using feedback intervention theory to guide clinical dashboard design.
The provision of feedback to clinicians and organizations on the quality of care they provide is thought to influence clinician and organizational behavior leading to care improvements. Clinical Dashboards use data visualization techniques to provide feedback to individuals on their performance compared to quality metrics. In this paper the authors outline a theoretical approach to the design of a clinical dashboard; Feedback Intervention Theory (FIT).
AHRQ-funded; HS023855.
Citation: Dowding D, Merrill J, Russell D .
Using feedback intervention theory to guide clinical dashboard design.
AMIA Annu Symp Proc 2018 Dec 5;2018:395-403..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Provider Performance, Quality of Care, Quality Improvement
Kranz AM, Dalton S, Damberg C
Using health IT to coordinate care and improve quality in safety-net clinics.
Health centers provide care to vulnerable and high-need populations. Recent investments have promoted use of health information technology (HIT) capabilities for improving care coordination and quality of care in health centers. This study examined factors associated with use of these HIT capabilities and the association between these capabilities and quality of care in a census of health centers in the United States.
AHRQ-funded; HS024067.
Citation: Kranz AM, Dalton S, Damberg C .
Using health IT to coordinate care and improve quality in safety-net clinics.
Jt Comm J Qual Patient Saf 2018 Dec;44(12):731-40. doi: 10.1016/j.jcjq.2018.03.006..
Keywords: Health Information Technology (HIT), Care Coordination, Patient-Centered Healthcare, Quality Improvement, Quality of Care, Vulnerable Populations, Care Management
Colin NV, Cholan RA, Sachdeva B
Understanding the impact of variations in measurement period reporting for electronic clinical quality measures.
The purpose of the study was to understand the impact of varying measurement period on the calculation of electronic Clinical Quality Measures (eCQMs). Variations in measurement periods were associated with variation in performance between clinics for 3 of the 4 eCQMs, but did not have significant differences when calculated within clinics. Variations from standard measurement periods may reflect poor data quality and accuracy.
AHRQ-funded; HS023908.
Citation: Colin NV, Cholan RA, Sachdeva B .
Understanding the impact of variations in measurement period reporting for electronic clinical quality measures.
eGEMS 2018 Jul 19;6(1):17. doi: 10.5334/egems.235..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Measures, Quality Improvement, Quality of Care
Dowding D, Merrill JA
The development of heuristics for evaluation of dashboard visualizations.
Heuristic evaluation is used in human-computer interaction studies to assess the usability of information systems. This article develops a heuristic evaluation checklist that can be used to evaluate systems that produce information visualizations. The authors suggest that a checklist of usability heuristics for evaluating information visualization systems can contribute to assuring high quality in electronic data systems developed for health care.
AHRQ-funded; HS023855.
Citation: Dowding D, Merrill JA .
The development of heuristics for evaluation of dashboard visualizations.
Appl Clin Inform 2018 Jul;9(3):511-18. doi: 10.1055/s-0038-1666842..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Provider Performance, Quality of Care, Quality Improvement
Hemler JR, Hall JD, Cholan RA
Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: EvidenceNOW.
In this paper, the authors describe the strategies facilitators use to help practices perform quality improvement (QI) when complete or accurate performance data are not available. The investigators found facilitators faced practice-level EHR data challenges, such as a lack of clinical performance data, partial or incomplete clinical performance data, and inaccurate clinical performance data.
AHRQ-funded; HS023940.
Citation: Hemler JR, Hall JD, Cholan RA .
Practice facilitator strategies for addressing electronic health record data challenges for quality improvement: EvidenceNOW.
J Am Board Fam Med 2018 May-Jun;31(3):398-409. doi: 10.3122/jabfm.2018.03.170274..
Keywords: Electronic Health Records (EHRs), Quality Improvement, Evidence-Based Practice, Health Information Technology (HIT), Primary Care, Quality of Care
Austrian JS, Jamin CT, Doty GR
Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay.
The goal of this study was to determine if an electronic health record (EHR) based sepsis alert system could improve quality of care and clinical outcomes for patients with sepsis. A patient-level, interrupted time series study of emergency department patients with severe sepsis or septic shock was conducted, with an intervention introduced at the approximate mid-point--a system of interruptive sepsis alerts triggered by abnormal vital signs or laboratory results. Mean length of stay for patients with sepsis decreased significantly following the introduction of the alert, but the alert system had no effect on mortality or other clinical or process measures. The researchers conclude that a more sophisticated algorithm for sepsis identification is needed to improve outcomes.
AHRQ-funded; HS023683.
Citation: Austrian JS, Jamin CT, Doty GR .
Impact of an emergency department electronic sepsis surveillance system on patient mortality and length of stay.
J Am Med Inform Assoc 2018 May;25(5):523-29. doi: 10.1093/jamia/ocx072..
Keywords: Electronic Health Records (EHRs), Emergency Department, Health Information Technology (HIT), Hospitals, Mortality, Outcomes, Quality Improvement, Quality of Care, Sepsis
Cohen DJ, Dorr DA, Knierim K
Primary care practices' abilities and challenges in using electronic health record data for quality improvement.
Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. This study concluded that the current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.
AHRQ-funded; HS023940.
Citation: Cohen DJ, Dorr DA, Knierim K .
Primary care practices' abilities and challenges in using electronic health record data for quality improvement.
Health Aff 2018 Apr;37(4):635-43. doi: 10.1377/hlthaff.2017.1254.
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Keywords: Electronic Health Records (EHRs), Primary Care, Quality Improvement, Quality of Care, Health Information Technology (HIT), Payment
Bhise V, Sittig DF, Vaghani V
An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients.
Researchers refined the methods of the Institute of Healthcare Improvement's Global Trigger Tool application and leveraged electronic health record data to improve detection of preventable adverse events, including diagnostic errors. In the studied sample, preventable adverse events were identified, including adverse drug events, patient falls, procedure-related complications, and hospital-associated infections. The authors concluded that such e-triggers can help overcome limitations of currently available methods to detect preventable harm in hospitalized patients.
AHRQ-funded; HS022087; HS023602.
Citation: Bhise V, Sittig DF, Vaghani V .
An electronic trigger based on care escalation to identify preventable adverse events in hospitalised patients.
BMJ Qual Saf 2018 Mar;27(3):241-46. doi: 10.1136/bmjqs-2017-006975..
Keywords: Adverse Events, Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitalization, Hospitals, Patient Safety, Prevention, Quality of Care, Quality Improvement, Quality Indicators (QIs)
Rangachari P
Innovation implementation in the context of hospital QI: lessons learned and strategies for success.
This paper conducts an integrative review of the literature on "innovation implementation" in hospitals and health systems over the last decade, since the spotlight was cast on "innovation implementation failure" in health care organizations (HCOs). It summarizes the lessons learned from the literature, discusses the relevance of management research on innovation implementation in HCOs, and identifies future research avenues.
AHRQ-funded; HS024335.
Citation: Rangachari P .
Innovation implementation in the context of hospital QI: lessons learned and strategies for success.
Innov Entrep Health 2018;5:1-14. doi: 10.2147/ieh.s151040.
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Keywords: Evidence-Based Practice, Health Systems, Health Information Technology (HIT), Implementation, Quality Improvement, Hospitals, Quality of Care