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      Development of a clinical decision support tool for diagnostic imaging use in patients with low back pain: a study protocol

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          Abstract

          Background

          Low back pain is one of the most common and disabling health problems in Canada and internationally. In most cases, low back pain is a benign, self-limiting condition that can be managed with little diagnostic investigation or treatment. Yet contrary to clinical practice guideline recommendations, diagnostic imaging (here meaning X-ray, MRI, CT) is commonly used in the assessment of low back pain. Diagnostic imaging is of limited value in most cases, exposing patients to unnecessary radiation and leading to increased health services use and worse patient health outcomes. The Choosing Wisely campaign has highlighted the need to reduce diagnostic imaging for low back pain; however, no clinical decision rules are available.

          Methods

          This project will develop a clinical decision support tool for appropriate use of diagnostic imaging for patients with low back pain in the emergency department. We will conduct a prospective cohort study at five Canadian emergency departments. The study will follow recommendations for prediction model development and testing. The study population will be 4000 patients presenting to the emergency department with low back pain. We will assess potential clinical indications of emergent-cause (i.e., “red flag” items), including clinical characteristics and past history. Our outcome, emergent-cause for low back pain such as fracture, cancer, infection, or cauda equina syndrome, will be assessed at discharge and at 1-, 3-, and 12-month follow-up periods using information from self-report and health administrative data. We will construct and assess the performance of a multivariable prediction model that has strong measurement properties, presented as a clinical decision support tool acceptable to knowledge users.

          Discussion

          Practice guidelines describe “red flags” for which diagnostic imaging is likely appropriate. However, recommendations across guidelines are discordant, and few studies have evaluated these criteria to determine which characteristics best predict emergent etiology that warrant diagnostic imaging. A clinical decision support tool, that recommends diagnostic imaging where appropriate, has the potential to improve clinical care and patient outcomes and reduce costs associated with managing low back pain patients.

          Electronic supplementary material

          The online version of this article (10.1186/s41512-019-0047-8) contains supplementary material, which is available to authorized users.

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          Most cited references30

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

          The Lancet, 380(9859), 2224-2260
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            Expenditures and health status among adults with back and neck problems.

            Back and neck problems are among the symptoms most commonly encountered in clinical practice. However, few studies have examined national trends in expenditures for back and neck problems or related these trends to health status measures. To estimate inpatient, outpatient, emergency department, and pharmacy expenditures related to back and neck problems in the United States from 1997 through 2005 and to examine associated trends in health status. Age- and sex-adjusted analysis of the nationally representative Medical Expenditure Panel Survey (MEPS) from 1997 to 2005 using complex survey regression methods. The MEPS is a household survey of medical expenditures weighted to represent national estimates. Respondents were US adults (> 17 years) who self-reported back and neck problems (referred to as "spine problems" based on MEPS descriptions and International Classification of Diseases, Ninth Revision, Clinical Modification definitions). Spine-related expenditures for health services (inflation-adjusted); annual surveys of self-reported health status. National estimates were based on annual samples of survey respondents with and without self-reported spine problems from 1997 through 2005. A total of 23 045 respondents were sampled in 1997, including 3139 who reported spine problems. In 2005, the sample included 22 258 respondents, including 3187 who reported spine problems. In 1997, the mean age- and sex-adjusted medical costs for respondents with spine problems was $4695 (95% confidence interval [CI], $4181-$5209), compared with $2731 (95% CI, $2557-$2904) among those without spine problems (inflation-adjusted to 2005 dollars). In 2005, the mean age- and sex- adjusted medical expenditure among respondents with spine problems was $6096 (95% CI, $5670-$6522), compared with $3516 (95% CI, $3266-$3765) among those without spine problems. Total estimated expenditures among respondents with spine problems increased 65% (adjusted for inflation) from 1997 to 2005, more rapidly than overall health expenditures. The estimated proportion of persons with back or neck problems who self-reported physical functioning limitations increased from 20.7% (95% CI, 19.9%-21.4%) to 24.7% (95% CI, 23.7%-25.6%) from 1997 to 2005. Age- and sex-adjusted self-reported measures of mental health, physical functioning, work or school limitations, and social limitations among adults with spine problems were worse in 2005 than in 1997. In this survey population, self-reported back and neck problems accounted for a large proportion of health care expenditures. These spine-related expenditures have increased substantially from 1997 to 2005, without evidence of corresponding improvement in self-assessed health status.
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              Effect of clinical decision-support systems: a systematic review.

              Despite increasing emphasis on the role of clinical decision-support systems (CDSSs) for improving care and reducing costs, evidence to support widespread use is lacking. To evaluate the effect of CDSSs on clinical outcomes, health care processes, workload and efficiency, patient satisfaction, cost, and provider use and implementation. MEDLINE, CINAHL, PsycINFO, and Web of Science through January 2011. Investigators independently screened reports to identify randomized trials published in English of electronic CDSSs that were implemented in clinical settings; used by providers to aid decision making at the point of care; and reported clinical, health care process, workload, relationship-centered, economic, or provider use outcomes. Investigators extracted data about study design, participant characteristics, interventions, outcomes, and quality. 148 randomized, controlled trials were included. A total of 128 (86%) assessed health care process measures, 29 (20%) assessed clinical outcomes, and 22 (15%) measured costs. Both commercially and locally developed CDSSs improved health care process measures related to performing preventive services (n= 25; odds ratio [OR], 1.42 [95% CI, 1.27 to 1.58]), ordering clinical studies (n= 20; OR, 1.72 [CI, 1.47 to 2.00]), and prescribing therapies (n= 46; OR, 1.57 [CI, 1.35 to 1.82]). Few studies measured potential unintended consequences or adverse effects. Studies were heterogeneous in interventions, populations, settings, and outcomes. Publication bias and selective reporting cannot be excluded. Both commercially and locally developed CDSSs are effective at improving health care process measures across diverse settings, but evidence for clinical, economic, workload, and efficiency outcomes remains sparse. This review expands knowledge in the field by demonstrating the benefits of CDSSs outside of experienced academic centers. Agency for Healthcare Research and Quality.
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                Author and article information

                Contributors
                jhayden@dal.ca
                rachel.ogilvie@dal.ca
                Sam.Stewart@dal.ca
                simon.french@mq.edu.au
                samuel.campbell@nshealth.ca
                kirk.magee@dal.ca
                Patrick.Slipp@Dal.Ca
                gawells@ottawaheart.ca
                istiell@ohri.ca
                Journal
                Diagn Progn Res
                Diagn Progn Res
                Diagnostic and Prognostic Research
                BioMed Central (London )
                2397-7523
                14 January 2019
                14 January 2019
                2019
                : 3
                : 1
                Affiliations
                [1 ]ISNI 0000 0004 1936 8200, GRID grid.55602.34, Department Community Health and Epidemiology, , Dalhousie University, ; 5790 University Avenue, Halifax, NS B3H 1V7 Canada
                [2 ]ISNI 0000 0004 1936 8331, GRID grid.410356.5, School of Rehabilitation Therapy, , Queen’s University, ; Louise D. Acton Building, 31 George St, Kingston, ON K7L 3N6 Canada
                [3 ]ISNI 0000 0001 2158 5405, GRID grid.1004.5, Department of Chiropractic, , Macquarie University, ; Sydney, NSW 2109 Australia
                [4 ]ISNI 0000 0004 1936 8200, GRID grid.55602.34, Department of Emergency Medicine, , Dalhousie University, Emergency Medicine, Nova Scotia Health Authority, QEII Health Sciences Centre, ; Suite 355, 1796 Summer Street, Halifax, NS B3H 3A7 Canada
                [5 ]ISNI 0000 0004 0407 789X, GRID grid.413292.f, Department of Radiology, , Nova Scotia Health Authority, QEII Health Sciences Centre, ; Suite 355, 1796 Summer Street, Halifax, NS B3H 3A7 Canada
                [6 ]ISNI 0000 0001 2182 2255, GRID grid.28046.38, Epidemiology and Community Medicine, , University of Ottawa, Cardiovascular Research Methods Centre, University of Ottawa Heart Institute, ; 40 Ruskin Street, Ottawa, ON K1Y 4W7 Canada
                [7 ]ISNI 0000 0001 2182 2255, GRID grid.28046.38, Department of Emergency Medicine, Ottawa Hospital Research Institute, , University of Ottawa, ; 1053 Carling Avenue, Ottawa, ON K1Y 4E9 Canada
                Article
                47
                10.1186/s41512-019-0047-8
                6460553
                31093571
                4be5c51e-4a03-4e3c-a3b0-17cb5508dd54
                © The Author(s) 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 27 July 2018
                : 4 January 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;
                Award ID: 374823
                Award Recipient :
                Categories
                Protocol
                Custom metadata
                © The Author(s) 2019

                low back pain,diagnostic imaging,red flags,clinical decision support tool,prediction model,knowledge translation

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