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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 4 of 4 Research Studies DisplayedShear K, Rice H, Garabedian PM
Management of fall risk among older adults in diverse primary care settings.
The purpose of this study was to describe how urban and rural primary care staff and older adults manage fall risk and factors relevant to the application of computerized clinical decision support (CCDS). METHODS: Interviews, contextual inquiries, and workflow observations were analyzed. The study found that participants valued fall prevention and described similar approaches. Variations in available resources existed between rural and urban locations. Participants wanted evidence-based guidance incorporated into workflows to bridge gaps in skills.
AHRQ-funded; HS027557.
Citation: Shear K, Rice H, Garabedian PM .
Management of fall risk among older adults in diverse primary care settings.
J Appl Gerontol 2023 Nov; 42(11):2219-32. doi: 10.1177/07334648231185757..
Keywords: Falls, Elderly, Primary Care, Rural Health, Rural/Inner-City Residents
Hekman DJ, Cochran AL, Maru AP
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
This article described a research protocol for evaluating the effectiveness of an automated screening and referral intervention tool for patients receiving falls risk intervention. The study will attempt to quantify the impact of a machine learning (ML) clinical decision support intervention on patient behavior and outcomes. The primary analysis will obtain referral completion rates from different emergency departments. The findings will inform ongoing discussion on the use of ML and artificial intelligence to augment medical decision-making.
AHRQ-funded; HS027735.
Citation: Hekman DJ, Cochran AL, Maru AP .
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
JMIR Res Protoc 2023 Aug 3; 12:e48128. doi: 10.2196/48128..
Keywords: Clinical Decision Support (CDS), Emergency Department, Health Information Technology (HIT), Elderly, Falls
Shear K, Rice H, Garabedian PM
Usability testing of an interoperable computerized clinical decision support tool for fall risk management in primary care.
The purpose of this study was to conduct usability testing of the ASPIRE fall risk management tool for use in divergent primary care clinics. Participants recruited from two sites with different electronic health records and clinical organizations used ASPIRE across two clinical scenarios; they rated ASPIRE usability as above average, based on usability benchmarks. Time spent on tasks decreased significantly between the first and second scenarios, indicating ease of learnability. The authors conclude that ASPIRE could be integrated into diverse organizations, since it allows a tailored implementation without the need to build a new system for each organization. ASPIRE is therefore well positioned to impact the challenge of falls at scale.
AHRQ-funded; HS027557.
Citation: Shear K, Rice H, Garabedian PM .
Usability testing of an interoperable computerized clinical decision support tool for fall risk management in primary care.
Appl Clin Inform 2023 Mar;14(2):212-26. doi: 10.1055/a-2006-4936.
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT), Falls, Primary Care, Risk, Prevention
Dykes PC, Curtin-Bowen M, Lipsitz S
Cost of inpatient falls and cost-benefit analysis of implementation of an evidence-based fall prevention program.
The financial implications of patient falls within healthcare settings, a primary cause of nonreimbursable negative incidents, have not been thoroughly investigated. The aim of this study was to determine the expenses related to inpatient falls and the potential cost savings achieved through the adoption of a proven fall prevention program. This economic assessment employed a matched case-control approach, utilizing results from an interrupted time series analysis that evaluated the alterations in fall rates after the introduction of an evidence-based fall prevention program to estimate inpatient fall expenses. Subsequently, an economic analysis was conducted to evaluate the cost advantages of implementing the program across two American healthcare systems from June 1, 2013, to August 31, 2019, in New York, New York, and Boston, Massachusetts. All adult patients admitted to the participating units were included in the analysis. Data analysis took place between October 2021 and November 2022. The fall prevention program, based on evidence, was introduced in 33 medical and surgical departments across eight hospitals. The primary outcome was the expense related to inpatient falls. Secondary outcomes included costs and savings linked to the evidence-based fall prevention program. The study found that the case-control study and economic analysis included 10,176 patients who experienced a fall event (with or without injury) and 29,161 matched controls without a fall event (51.9% aged 65-74 years, 67.1% White, and 53.6% male). Prior to the intervention, there were 2,503 falls and 900 injuries; following the intervention, there were 2,078 falls and 758 injuries. Based on a 19% decrease in falls and a 20% decrease in injury-causing falls from the beginning to the end of the post-intervention period, the economic analysis revealed that noninjurious and injurious falls led to cost increases of $35,365 and $36,776, respectively. The introduction of the evidence-based fall prevention program resulted in $14,600 in net avoided expenses for every 1000 patient-days.
AHRQ-funded; HS027557; HS025128
Citation: Dykes PC, Curtin-Bowen M, Lipsitz S .
Cost of inpatient falls and cost-benefit analysis of implementation of an evidence-based fall prevention program.
JAMA Health Forum 2023 Jan 6;4(1):e225125. doi: 10.1001/jamahealthforum.2022.5125.
Keywords: Falls, Healthcare Delivery, Evidence-Based Practice, Prevention