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- Diagnostic Safety and Quality (1)
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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.
Results
1 to 4 of 4 Research Studies DisplayedLozano PM, Lane-Fall M, Franklin PD
AHRQ Author: Chesley FD
Training the next generation of learning health system scientists.
The purpose of this paper was to describe the approaches developed by 11 Agency for Healthcare Research and Quality (AHRQ)- and Patient-Centered Outcomes Research Institute- funded Centers of Excellence (COEs) to grow the number of learning health systems (LHS) scientists. Program directors for each COE have provided descriptive program data since 2018. The authors found that since the program began, the 11 COEs have partnered with health systems to train 110 scholars. Nine programs partner with a Veterans Affairs health system and 9 partner with safety net providers. Clinically trained scholars include 70 physicians and 17 scholars in other clinical disciplines. Non-clinicians represent diverse fields, with most representing population health sciences. Challenges include guiding scholars through issues that can disrupt or delay projects during already-limited program time, such as delays in accessing data, organizational changes, pandemic impacts and others. The researchers concluded that the program documentation provides evidence of scholars' academic accomplishments and career-trajectory achievements.
AHRQ-authored; AHRQ-funded; HS026369; HS026370; HS026372; HS026379; HS026383; HS026385; HS026390; HS026393; HS026395; HS026396; HS026407
Citation: Lozano PM, Lane-Fall M, Franklin PD .
Training the next generation of learning health system scientists.
Learn Health Syst 2022 Oct;6(4):e10342. doi: 10.1002/lrh2.10342..
Keywords: Learning Health Systems, Health Systems, Patient-Centered Outcomes Research, Evidence-Based Practice, Training, Workforce
Dukhanin V, Feeser S, Berkowitz SA
Who represents me? A patient-derived model of patient engagement via patient and family advisory councils (PFACs).
This study examined what expectations would be from patients who are not patient and family advisory council (PFAC) members of PFACs. Patients and caregivers from the Johns Hopkins Medical Alliance for Patients, LLC were recruited in 2014. This Medicare accountable care organization has an established PFAC, the Beneficiary Advisory Council. Five focus groups with 42 patients and caregivers participated. Most participants were not aware of PFACs and wanted to know more about representation, what they could do and expected that patients could communicate with PFACs if desired.
AHRQ-funded; HS023684.
Citation: Dukhanin V, Feeser S, Berkowitz SA .
Who represents me? A patient-derived model of patient engagement via patient and family advisory councils (PFACs).
Health Expect 2020 Feb;23(1):148-58. doi: 10.1111/hex.12983..
Keywords: Patient and Family Engagement, Patient-Centered Outcomes Research, Patient-Centered Healthcare, Healthcare Delivery, Health Systems
White CM, Coleman CI, Jackman K
AHRQ series on improving translation of evidence: linking evidence reports and performance measures to help learning health systems use new information for improvement.
This paper analyzed ways to enhance usability of AHRQ’s Evidence-based Practice Center (EPC) reports. The reports are often lengthy and difficult for users to navigate. A quality measure index was created to allow health systems to more efficiently access relevant information. A test was created where two tables were embedded in an EPC report. The first identified quality measures covered by the report descriptively. The second contained page numbers in the executive summary which hyperlinked to those pages with the quality measures. An exercise with two health system-targeted scenarios was then created. The participants were timed how long it took to find answers to scenario questions and gave feedback. It was found that it took 63.4% less time to find quality measure information with the hyperlinked indexing tables than without. The participants felt that the tables were easy to use and more user friendly to health systems.
Jt Comm J Qual Patient Saf 2019 Oct;45(10):706-10. doi: 10.1016/j.jcjq.2019.05.002.
Citation: White CM, Coleman CI, Jackman K .
AHRQ series on improving translation of evidence: linking evidence reports and performance measures to help learning health systems use new information for improvement.
Jt Comm J Qual Patient Saf 2019 Oct;45(10):706-10. doi: 10.1016/j.jcjq.2019.05.002..
Keywords: Implementation, Evidence-Based Practice, Health Systems, Learning Health Systems, Patient-Centered Outcomes Research, Provider Performance, Quality Measures, Quality Improvement, Quality of Care
Pantalone KM, Hobbs TM, Chagin KM
Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.
The purpose of the study was to determine the prevalence of obesity and its related comorbidities among patients being actively managed at a US academic medical centre, and to examine the frequency of a formal diagnosis of obesity. This cross-sectional summary from a large US integrated health system found that three out of every four patients had overweight or obesity based on BMI. Less than half of patients who were identified as having obesity according to BMI received a formal diagnosis via ICD-9 documentation.
AHRQ-funded; HS024128.
Citation: Pantalone KM, Hobbs TM, Chagin KM .
Prevalence and recognition of obesity and its associated comorbidities: cross-sectional analysis of electronic health record data from a large US integrated health system.
BMJ Open 2017 Nov 16;7(11):e017583. doi: 10.1136/bmjopen-2017-017583..
Keywords: Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Systems, Obesity, Patient-Centered Outcomes Research