National Healthcare Quality and Disparities Report
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- Adverse Events (5)
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- Antimicrobial Stewardship (1)
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- Diabetes (4)
- Diagnostic Safety and Quality (5)
- (-) Electronic Health Records (EHRs) (59)
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- Healthcare-Associated Infections (HAIs) (3)
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- Health Information Technology (HIT) (49)
- Health Services Research (HSR) (2)
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- Heart Disease and Health (1)
- Hospitalization (1)
- Hospital Readmissions (1)
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- Imaging (1)
- Implementation (1)
- Injuries and Wounds (2)
- Intensive Care Unit (ICU) (1)
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- Obesity: Weight Management (1)
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- Provider (1)
- Provider: Nurse (1)
- Provider Performance (6)
- Quality Improvement (30)
- Quality Indicators (QIs) (7)
- Quality Measures (10)
- (-) Quality of Care (59)
- Registries (1)
- Respiratory Conditions (1)
- Sepsis (2)
- Surgery (5)
- Teams (1)
- Tools & Toolkits (2)
- Training (1)
- Trauma (1)
- Urinary Tract Infection (UTI) (1)
- Web-Based (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 59 Research Studies DisplayedBradford A, Shofer M, Singh H
AHRQ Author: Shofer M, Singh H
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
This paper discusses Measure Dx, a new AHRQ resource that translates knowledge from diagnostic measurement research into actionable recommendations. This resource guides healthcare organizations to detect, analyze, and learn from diagnostic safety events as part of a continuous learning and feedback cycle. The goal of Measure Dx is to advance new frontiers in reducing preventable diagnostic harm to patients.
AHRQ-authored; AHRQ-funded; 233201500022I; HS027363.
Citation: Bradford A, Shofer M, Singh H .
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
Int J Qual Health Care 2022 Sep 10;34(3). doi: 10.1093/intqhc/mzac068..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Systems, Learning Health Systems
Huo T, Li Q, Cardel MI
AHRQ Author: Mistry K
Enhancing quality measurement with clinical information: a use case of body mass index change among children taking second generation antipsychotics.
The authors sought to examine the extent to which body mass index (BMI) was available in electronic health records for Florida Medicaid recipients aged 5 to 18 years taking Second-Generation Antipsychotics (SGAP). They concluded that meeting the 2030 CMS goal of digital monitoring of quality of care will require continuing expansion of clinical encounter data capture to provide the data needed for digital quality monitoring. Using linked electronic health records and claims data allows identifying children at higher risk for SGAP-induced weight gain.
AHRQ-authored; AHRQ-funded; HS025298.
Citation: Huo T, Li Q, Cardel MI .
Enhancing quality measurement with clinical information: a use case of body mass index change among children taking second generation antipsychotics.
Acad Pediatr 2022 Apr;22(3S):S140-S49. doi: 10.1016/j.acap.2021.11.012..
Keywords: Children/Adolescents, Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Obesity, Obesity: Weight Management, Quality Measures, Quality of Care
Richardson JE, Rasmussen LV, Dorr DA
Generating and reporting electronic clinical quality measures from electronic health records: strategies from EvidenceNOW cooperatives.
This study’s goal was to characterize strategies that seven regional cooperatives participating in the EvidenceNOW initiative developed to generate and report electronic health record (EHR)-based electronic clinical quality measures (eCQMs) for quality improvement (QI) in small-to-medium-sized practices. Findings showed that cooperatives ultimately generated and reported eCQMs using hybrid strategies because they determined that neither EHRs alone nor centralized sources alone could operationalize eCQMs for QI. In order to attain this goal, cooperatives needed to devise solutions and utilize resources that often are unavailable to typical small-to-medium-sized practices.
AHRQ-funded; HS023921.
Citation: Richardson JE, Rasmussen LV, Dorr DA .
Generating and reporting electronic clinical quality measures from electronic health records: strategies from EvidenceNOW cooperatives.
Appl Clin Inform 2022 Mar;13(2):485-94. doi: 10.1055/s-0042-1748145..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Indicators (QIs), Quality Measures, Quality of Care, Evidence-Based Practice, Primary Care
Holmgren AJ, Kuznetsova M, Classen D
Assessing hospital electronic health record vendor performance across publicly reported quality measures.
The authors measured hospital performance, stratified by electronic health record (EHR) vendor, across 4 quality metrics. They found that no EHR vendor was associated with higher quality across all measures, and the 2 largest vendors were not associated with the highest scores. Only a small fraction of quality variation was explained by EHR vendor choice. They concluded that top performance on quality measures can be achieved with any EHR vendor, as much of quality performance is driven by the hospital and how it uses the EHR.
AHRQ-funded; HS023696.
Citation: Holmgren AJ, Kuznetsova M, Classen D .
Assessing hospital electronic health record vendor performance across publicly reported quality measures.
J Am Med Inform Assoc 2021 Sep 18;28(10):2101-07. doi: 10.1093/jamia/ocab120..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Indicators (QIs), Quality Measures, Hospitals, Quality of Care, Provider Performance
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
Shekelle PG, Pane JD, Agniel D
Assessment of variation in electronic health record capabilities and reported clinical quality performance in ambulatory care clinics, 2014-2017.
This study’s objective was to assess the association between electronic health records (EHRs) with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care. This cross-sectional and longitudinal study was conducted using survey responses from 1141 ambulatory clinics in Minnesota, Washington, and Wisconsin affiliated with a health system and reported performance measures in 2014 to 2017. A composite measure of EHR capability that considered 50 EHR capabilities was created using 7 functional domains: no functional EHR, EHR underuser, EHR, neither underuser nor superuser, and EHR superuser; as well as a standardized composite of ambulatory clinical measures that included a median of 13 individual measures (3 to 25). The proportion of clinics that were EHR superusers increased from 51% in 2014 to 61% in 2017. In all survey years EHR superusers had better clinical quality performance than other clinics. This difference in scores translated into an approximately 9% difference in a clinic’s rank order in clinical quality.
AHRQ-funded; HS024067.
Citation: Shekelle PG, Pane JD, Agniel D .
Assessment of variation in electronic health record capabilities and reported clinical quality performance in ambulatory care clinics, 2014-2017.
JAMA Netw Open 2021 Apr;4(4):e217476. doi: 10.1001/jamanetworkopen.2021.7476..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Ambulatory Care and Surgery, Provider Performance, Quality of Care
Elysee G, Yu H, Herrin J
Association between 30-day readmission rates and health information technology capabilities in US hospitals.
A study was conducted to determine if there is an association of health information technology (HIT) adoption and a decrease in 30-day hospital readmission rates. Data was used from the 2013 American Hospital Association IT survey which included non-federal U.S. acute care hospitals with self-reported capabilities. A 54-indicator 7-factor structure of hospital health IT capabilities was identified by exploratory factor analysis. A one-point increase in the hospital adoption of patient engagement capability latent scores generally leads to a 0.086% decrease in risk-standardized readmission rates (RSRRs). However, computerized hospital discharge and information exchange among clinicians did not seem as beneficial.
AHRQ-funded; HS022882.
Citation: Elysee G, Yu H, Herrin J .
Association between 30-day readmission rates and health information technology capabilities in US hospitals.
Medicine 2021 Feb 26;100(8):e24755. doi: 10.1097/md.0000000000024755..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Hospital Readmissions, Hospitals, Quality Indicators (QIs), Quality of Care
Griffey RT, Schneider RM, Todorov AA
The emergency department trigger tool: validation and testing to optimize yield.
Researchers validated the emergency department trigger tool (EDTT) in an independent sample and compared record selection approaches to optimize yield for quality improvement. In this single-site study of the EDTT, they observed high levels of validity in trigger selection, yield, and representativeness of adverse events, with yields that are superior to estimates for traditional approaches to adverse event detection. Record selection using weighted triggers outperformed a trigger count threshold approach and far outperformed random sampling from records with at least one trigger. They concluded that the EDTT is a promising efficient and high-yield approach for detecting all-cause harm to guide quality improvement efforts in the emergency department.
AHRQ-funded; HS025052.
Citation: Griffey RT, Schneider RM, Todorov AA .
The emergency department trigger tool: validation and testing to optimize yield.
Acad Emerg Med 2020 Dec;27(12):1279-90. doi: 10.1111/acem.14101..
Keywords: Emergency Department, Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Adverse Events, Patient Safety, Quality Improvement, Quality of Care
Scott HF, Brilli RJ, Paul R
Evaluating pediatric sepsis definitions designed for electronic health record extraction and multicenter quality improvement.
The purpose of this study was to describe the Children's Hospital Association's Improving Pediatric Sepsis Outcomes sepsis definitions and to evaluate the definition using a published framework. The investigators concluded that the Improving Pediatric Sepsis Outcomes Sepsis definitions demonstrated feasibility for large-scale data abstraction. When operationalized, these definitions enabled multicenter identification and data aggregation, indicating practical utility for quality improvement.
AHRQ-funded; HS025696.
Citation: Scott HF, Brilli RJ, Paul R .
Evaluating pediatric sepsis definitions designed for electronic health record extraction and multicenter quality improvement.
Crit Care Med 2020 Oct;48(10):e916-e26. doi: 10.1097/ccm.0000000000004505..
Keywords: Children/Adolescents, Electronic Health Records (EHRs), Health Information Technology (HIT), Sepsis, Quality Improvement, Quality of Care
Bucher BT, Shi J, Ferraro JP
Portable automated surveillance of surgical site infections using natural language processing: development and validation.
The authors presented the development and validation of a portable natural language processing (NLP) approach for automated surveillance of surgical site infections (SSIs). Patient clinical text notes from EHRs following surgical procedures from two independent healthcare systems were abstracted. The authors found that automated surveillance of SSIs can be achieved using NLP of clinical notes with high sensitivity and specificity.
AHRQ-funded; HS025776.
Citation: Bucher BT, Shi J, Ferraro JP .
Portable automated surveillance of surgical site infections using natural language processing: development and validation.
Ann Surg 2020 Oct;272(4):629-36. doi: 10.1097/sla.0000000000004133..
Keywords: Surgery, Healthcare-Associated Infections (HAIs), Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Bronsert M, Singh AB, Henderson WG
Identification of postoperative complications using electronic health record data and machine learning.
Investigators developed a machine learning algorithm for identifying patients with one or more complications using data from the electronic health record (EHR). They concluded that using machine learning on EHR postoperative data linked to American College of Surgeons National Surgical Quality Improvement Program outcomes data, a model with 163 predictors from the EHR identified complications well at their institution.
AHRQ-funded; HS026019.
Citation: Bronsert M, Singh AB, Henderson WG .
Identification of postoperative complications using electronic health record data and machine learning.
Am J Surg 2020 Jul;220(1):114-19. doi: 10.1016/j.amjsurg.2019.10.009..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Surgery, Quality Improvement, Quality of Care, Diagnostic Safety and Quality
Homco J, Carabin H, Nagykaldi Z
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
The purpose of this study was to compare observed performance scores measured using 2 imperfect reference standard data sources with misclassification-adjusted performance scores obtained using bayesian latent class analysis. Using aspirin, blood pressure, and smoking performance data from the Healthy Hearts for Oklahoma Project, researchers found that extracting information for the same individuals using different data sources generated different performance score estimates. Recommendations included further research to identify the sources of these differences.
AHRQ-funded; HS023919.
Citation: Homco J, Carabin H, Nagykaldi Z .
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
JAMA Netw Open 2020 Jul;3(7):e209411. doi: 10.1001/jamanetworkopen.2020.9411..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Cardiovascular Conditions, Quality Measures, Quality of Care, Primary Care, Provider Performance, Evidence-Based Practice
Rudin RS, Friedberg MW, Shekelle P
Getting value from electronic health records: research needed to improve practice.
Electronic health records (EHRs) are now widely adopted in the United States, but health systems have barely begun using them to deliver high-value care. This article describes 4 potential benefits of EHR-based research: improving clinical decisions, supporting triage decisions, enabling collaboration among the care team (including patients), and increasing productivity via automation of tasks.
AHRQ-funded; HS024067.
Citation: Rudin RS, Friedberg MW, Shekelle P .
Getting value from electronic health records: research needed to improve practice.
Ann Intern Med 2020 Jun 2;172(11 Suppl):S130-s36. doi: 10.7326/m19-0878..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care, Healthcare Delivery
Tignanelli CJ, Silverman GM, Lindemann EA
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize treatment appropriateness. Natural language processing (NLP) methods present a novel approach to bridge this gap. In this study, the investigators sought to evaluate the efficacy of a novel and automated NLP pipeline to determine treatment appropriateness from a sample of prehospital EMS motor vehicle crash records.
AHRQ-funded; HS026379.
Citation: Tignanelli CJ, Silverman GM, Lindemann EA .
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
J Trauma Acute Care Surg 2020 May;88(5):607-14. doi: 10.1097/ta.0000000000002598.
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Keywords: Trauma, Injuries and Wounds, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Businger AC, Fuller TE, Schnipper JL
Lessons learned implementing a complex and innovative patient safety learning laboratory project in a large academic medical center.
This paper describes the challenges, recommendations and lessons learned while developing and implementing a Patient Safety Learning Laboratory (PSLL) project, which is comprised of a suite of HIT tools integrated with a newly implemented Electronic Health Record (EHR) vendor system in the acute care setting of a large academic medical center. The PSLL Administrative Core engaged stakeholders and study personnel throughout all phases of the project. Challenges to implementation included stakeholder engagement, project scope and complexity, technology and governance, and team structure. Some changes were implemented during the trial and others were labeled as lessons learned for future iterative interventions. A willingness to think outside of current workflows and processes to change health system culture around adverse event prevention was one of the keys to success.
AHRQ-funded; HS023535.
Citation: Businger AC, Fuller TE, Schnipper JL .
Lessons learned implementing a complex and innovative patient safety learning laboratory project in a large academic medical center.
J Am Med Inform Assoc 2020 Feb;27(2):301-07. doi: 10.1093/jamia/ocz193.
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Keywords: Patient Safety, Implementation, Health Information Technology (HIT), Quality Improvement, Quality of Care, Patient-Centered Healthcare, Electronic Health Records (EHRs), Evidence-Based Practice
Gandrup J, Li J, Izadi Z
Three quality improvement initiatives and performance of rheumatoid arthritis disease activity measures in electronic health records: results from an interrupted time series study.
This study evaluated the effect of 3 HIT initiatives on the performance of rheumatoid arthritis (RA) disease activity measures and outcomes in an academic rheumatology clinic. The three initiatives implemented to facilitate performance of the Clinical Disease Activity Index (CDAI) were: 1) an EHR flowsheet to input scores, 2) peer performance reports, and 3) an EHR Smartform including a CDAI calculator. Data from 995 patients with 8,040 encounters between 2012 and 2017 was included. Electronic capture of CDAI scores increased from 0% to 64%. Peer performance reporting and the SmartForm kept performance stable. Physician satisfaction increased after SmartForm implementation.
AHRQ-funded; HS025638.
Citation: Gandrup J, Li J, Izadi Z .
Three quality improvement initiatives and performance of rheumatoid arthritis disease activity measures in electronic health records: results from an interrupted time series study.
Arthritis Care Res 2020 Feb;72(2):283-91. doi: 10.1002/acr.23848..
Keywords: Arthritis, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Liss DT, Peprah YA, Brown T
Using electronic health records to measure quality improvement efforts: findings from a large practice facilitation initiative.
This study described primary care practices' ability to obtain measures with reporting periods aligning with a large quality improvement initiative. Facilitators reported barriers to data collection such as practices lacking optional EHR features, and EHRs' inability to produce reporting periods across two calendar years. The authors conclude that EHR vendors' compliance with federal reporting requirements is not necessarily sufficient to support real-world quality improvement work. They recommended improvements in the flexibility and usability of EHRs' quality measurement functions, particularly for smaller practices.
AHRQ-funded; HS023921.
Citation: Liss DT, Peprah YA, Brown T .
Using electronic health records to measure quality improvement efforts: findings from a large practice facilitation initiative.
Jt Comm J Qual Patient Saf 2020 Jan;46(1):11-17. doi: 10.1016/j.jcjq.2019.09.006..
Keywords: Patient-Centered Outcomes Research, Evidence-Based Practice, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Kang SK, Garry K, Chung R
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
The authors developed natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations using the electronic health records for patients who underwent chest CT before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. They concluded that NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management.
AHRQ-funded; HS024376.
Citation: Kang SK, Garry K, Chung R .
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
J Am Coll Radiol 2019 Nov;16(11):1587-94. doi: 10.1016/j.jacr.2019.04.026..
Keywords: Imaging, Diagnostic Safety and Quality, Health Information Technology (HIT), Electronic Health Records (EHRs), Quality Improvement, Quality of Care
Knierim KE, Hall TL, Dickinson LM
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
The objective of this study was to determine how quickly primary care practices can report electronic clinical quality measures (eCQMs) and to identify the practice characteristics associated with faster reporting. Examining the EvidenceNOW Southwest initiative, the researchers’ results showed that the time to report eCQMs varied by measure and practice type, with very few practices reporting quickly. Additional support for practices to succeed in new programs that require eCQM reporting was recommended.
AHRQ-funded; HS023904.
Citation: Knierim KE, Hall TL, Dickinson LM .
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
JAMA Netw Open 2019 Aug 2;2(8):e198569. doi: 10.1001/jamanetworkopen.2019.8569..
Keywords: Primary Care, Quality Indicators (QIs), Quality Measures, Quality Improvement, Quality of Care, Heart Disease and Health, Cardiovascular Conditions, Patient-Centered Outcomes Research, Evidence-Based Practice, Electronic Health Records (EHRs), Health Information Technology (HIT)
Dalal AK, Fuller T, Garabedian P
Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.
This study examined systems engineering and human factors support of a system of novel electronic health record (EHR)-integrated tools for patient safety in the hospital. The authors established a Patient Safety Learning Laboratory of 2 core and 3 individual project teams to introduce a suite of digital health tools integrated with their EHR to identify, assess, and mitigate threats to patient safety. They identified 7 themes regarding use of 12 systems engineering and human factors over the 4-year project.
AHRQ-funded; HS023535.
Citation: Dalal AK, Fuller T, Garabedian P .
Systems engineering and human factors support of a system of novel EHR-integrated tools to prevent harm in the hospital.
J Am Med Inform Assoc 2019 Jun;26(6):553-60. doi: 10.1093/jamia/ocz002..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Hospitals, Quality Improvement, Quality of Care
Larsen E, Hoffman D, Rivera C
Continuing patient care during electronic health record downtime.
This study examined the impact of electronic health record (EHR) downtime in hospitals on patient care. Two mid-Atlantic hospitals where the EHR system was either fully or partially unavailable were used to document the problems using historic performance data and semistructured interviews. A total of 17 hospital employees were interviewed. Laboratory test results were delayed an average of 62% during downtime events. Paper documentation created during the downtime period was often incomplete or incorrect. The authors provided recommendations to improve downtime contingency plans based on their findings.
AHRQ-funded; HS024350.
Citation: Larsen E, Hoffman D, Rivera C .
Continuing patient care during electronic health record downtime.
Appl Clin Inform 2019 May;10(3):495-504. doi: 10.1055/s-0039-1692678..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Hospitals, Quality of Care
Althoff KN, Wong C, Hogan B
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Under the hypothesis that use of electronic health records in health research may lead to false assumptions of complete event ascertainment, the authors of this article estimated "observation windows" (OWs) as a quality-control approach to reduce the likelihood of false assumption. The impact of OWs on estimating rates of type II diabetes mellitus from HIV clinical cohorts are demonstrated. Data from 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence. The authors conclude that OWs have utility as a quality-control approach to complete event ascertainment and help to improve the accuracy of estimates.
AHRQ-funded; 90047713.
Citation: Althoff KN, Wong C, Hogan B .
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Ann Epidemiol 2019 May;33:54-63. doi: 10.1016/j.annepidem.2019.01.015..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR), Quality of Care
Wu SS, Chan KS, Bae J
Electronic clinical reminder and quality of primary diabetes care.
The goal of this retrospective cohort study was to examine the association of EMR's clinical reminder use with a comprehensive set of diabetes quality metrics in office-based physicians and within solo- versus multi-physician practices. Data on visits made by adults with diabetes were identified from the National Ambulatory Medical Care Survey and a multiple logistic regression was used to test for associations between clinical reminder use and recommended services by the American Diabetes Association. The researchers found no statistically significant relationship that suggests clinical reminder use improves diabetes process guidelines for solo practices, and they conclude that other resource efforts are needed to reduce gaps in primary diabetes care.
AHRQ-funded; HS000029.
Citation: Wu SS, Chan KS, Bae J .
Electronic clinical reminder and quality of primary diabetes care.
Prim Care Diabetes 2019 Apr;13(2):150-57. doi: 10.1016/j.pcd.2018.08.007..
Keywords: Care Management, Chronic Conditions, Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Quality of Care
Colborn KL, Bronsert M, Hammermeister K
Identification of urinary tract infections using electronic health record data.
Using the American College of Surgeons National Surgical Quality Improvement Program UTI status of patients who underwent an operation at the University of Colorado Hospital, the investigators sought to develop an algorithm for identifying UTIs using data from the electronic health record. The investigators concluded that a model with 14 predictors from the electronic health record identifies UTIs well, and it could be used to scale up UTI surveillance or to estimate the impact of large-scale interventions on UTI rates.
AHRQ-funded; HS026019.
Citation: Colborn KL, Bronsert M, Hammermeister K .
Identification of urinary tract infections using electronic health record data.
Am J Infect Control 2019 Apr;47(4):371-75. doi: 10.1016/j.ajic.2018.10.009..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Quality of Care, Quality Improvement, Surgery, Urinary Tract Infection (UTI)
Simon KC, Yucus C, Castle J
Building of EMR tools to support quality and research in a memory disorders clinic.
This article describes the development of a customized EMR toolkit that standardizes patient data collection with hundreds of discrete fields, supports Best Practices for treating patients with memory disorders, and also supports practice-based research. The toolkit was successfully implemented to support Best Practices in the care of patients with memory disorders. Applications are also discussed. Data collection is ongoing, but the authors anticipate that the toolkit will generate data that allows for descriptive and hypothesis-driven research as well as quality improvement among patients seen in memory clinics.
AHRQ-funded; HS024057.
Citation: Simon KC, Yucus C, Castle J .
Building of EMR tools to support quality and research in a memory disorders clinic.
Front Neurol 2019 Mar 7;10:161. doi: 10.3389/fneur.2019.00161..
Keywords: Dementia, Electronic Health Records (EHRs), Health Information Technology (HIT), Neurological Disorders, Quality of Care, Quality Improvement, Tools & Toolkits