National Healthcare Quality and Disparities Report
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
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1 to 2 of 2 Research Studies DisplayedBronsert 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
Shetty KD, Robbins M, Aragaki D
The quality of electrodiagnostic tests for carpal tunnel syndrome: Implications for surgery, outcomes, and expenditures.
The quality of electrodiagnostic tests may influence treatment decisions, particularly regarding surgery, affecting health outcomes and health-care expenditures. In this study, the investigators evaluated test quality among 338 adults with workers' compensation claims for carpal tunnel syndrome. The investigators found that in simulations, suboptimal quality tests rendered surgery inappropriate for 99 of 309 patients (+32 percentage points). They also found that test quality was not associated with overall health, actual receipt of surgery, or expenditures.
AHRQ-funded; HS018982.
Citation: Shetty KD, Robbins M, Aragaki D .
The quality of electrodiagnostic tests for carpal tunnel syndrome: Implications for surgery, outcomes, and expenditures.
Muscle Nerve 2020 Jul;62(1):60-69. doi: 10.1002/mus.26874..
Keywords: Diagnostic Safety and Quality, Neurological Disorders, Surgery, Quality Indicators (QIs), Quality Measures, Quality of Care