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      Patterns and trends of potentially inappropriate high-density lipoprotein cholesterol testing in Australian adults at high risk of cardiovascular disease from 2008 to 2014: analysis of linked individual patient data from the Australian Medicare Benefits Schedule and Pharmaceutical Benefits Scheme

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          Abstract

          Objectives

          We examine the extent to which the adult Australian population on lipid-lowering medications receives the level of high-density lipoprotein cholesterol (HDL-C) testing recommended by national guidelines.

          Data

          We analysed records from 7 years (2008–2014) of the 10% publicly available sample of deidentified, individual level, linked Medicare Benefits Schedule (MBS) and Pharmaceutical Benefits Scheme (PBS) electronic databases of Australia.

          Methods

          The PBS data were used to identify individuals on stable prescriptions of lipid-lowering treatment. The MBS data were used to estimate the annual frequency of HDL-C testing. We developed a methodology to address the issue of ‘episode coning’ in the MBS data, which causes an undercounting of pathology tests. We used a published figure on the proportion of unreported HDL-C tests to correct for the undercounting and estimate the probability that an HDL-C test was performed. We judged appropriateness of testing frequency by comparing the HDL-C testing rate to guidelines’ recommendations of annual testing for people at high risk for cardiovascular disease.

          Results

          We estimated that approximately 49% of the population on stable lipid-lowering treatment did not receive any HDL-C test in a given year. We also found that approximately 19% of the same population received two or more HDL-C tests within the year. These levels of underutilisation and overutilisation have been changing at an average rate of 2% and −4% a year, respectively, since 2009. The yearly expenditure associated with test overutilisation was approximately $A4.3 million during the study period, while the cost averted because of test underutilisation was approximately $A11.3 million a year.

          Conclusions

          We found that approximately half of Australians on stable lipid-lowering treatment may be having fewer HDL-C testing than recommended by national guidelines, while nearly one-fifth are having more tests than recommended.

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          Most cited references19

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          Cardiovascular disease risk profiles.

          This article presents prediction equations for several cardiovascular disease endpoints, which are based on measurements of several known risk factors. Subjects (n = 5573) were original and offspring subjects in the Framingham Heart Study, aged 30 to 74 years, and initially free of cardiovascular disease. Equations to predict risk for the following were developed: myocardial infarction, coronary heart disease (CHD), death from CHD, stroke, cardiovascular disease, and death from cardiovascular disease. The equations demonstrated the potential importance of controlling multiple risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, glucose intolerance, and left ventricular hypertrophy) as opposed to focusing on one single risk factor. The parametric model used was seen to have several advantages over existing standard regression models. Unlike logistic regression, it can provide predictions for different lengths of time, and probabilities can be expressed in a more straightforward way than the Cox proportional hazards model.
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            The Landscape of Inappropriate Laboratory Testing: A 15-Year Meta-Analysis

            Background Laboratory testing is the single highest-volume medical activity and drives clinical decision-making across medicine. However, the overall landscape of inappropriate testing, which is thought to be dominated by repeat testing, is unclear. Systematic differences in initial vs. repeat testing, measurement criteria, and other factors would suggest new priorities for improving laboratory testing. Methods A multi-database systematic review was performed on published studies from 1997–2012 using strict inclusion and exclusion criteria. Over- vs. underutilization, initial vs. repeat testing, low- vs. high-volume testing, subjective vs. objective appropriateness criteria, and restrictive vs. permissive appropriateness criteria, among other factors, were assessed. Results Overall mean rates of over- and underutilization were 20.6% (95% CI 16.2–24.9%) and 44.8% (95% CI 33.8–55.8%). Overutilization during initial testing (43.9%; 95% CI 35.4–52.5%) was six times higher than during repeat testing (7.4%; 95% CI 2.5–12.3%; P for stratum difference <0.001). Overutilization of low-volume tests (32.2%; 95% CI 25.0–39.4%) was three times that of high-volume tests (10.2%; 95% CI 2.6–17.7%; P<0.001). Overutilization measured according to restrictive criteria (44.2%; 95% CI 36.8–51.6%) was three times higher than for permissive criteria (12.0%; 95% CI 8.0–16.0%; P<0.001). Overutilization measured using subjective criteria (29.0%; 95% CI 21.9–36.1%) was nearly twice as high as for objective criteria (16.1%; 95% CI 11.0–21.2%; P = 0.004). Together, these factors explained over half (54%) of the overall variability in overutilization. There were no statistically significant differences between studies from the United States vs. elsewhere (P = 0.38) or among chemistry, hematology, microbiology, and molecular tests (P = 0.05–0.65) and no robust statistically significant trends over time. Conclusions The landscape of overutilization varies systematically by clinical setting (initial vs. repeat), test volume, and measurement criteria. Underutilization is also widespread, but understudied. Expanding the current focus on reducing repeat testing to include ordering the right test during initial evaluation may lead to fewer errors and better care.
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              Monitoring in chronic disease: a rational approach.

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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                8 March 2018
                : 8
                : 3
                : e019041
                Affiliations
                [1 ] departmentTranslational Health Research Institute , Western Sydney University , Penrith, New South Wales, Australia
                [2 ] Capital Markets CRC , Sydney, New South Wales, Australia
                [3 ] departmentSchool of Nursing and Midwifery , Western Sydney University , Penrith, New South Wales, Australia
                [4 ] departmentSchool of Medicine , University of Adelaide , Adelaide, South Australia, Australia
                [5 ] departmentSchool of Public Health , University of Sydney , Sydney, New South Wales, Australia
                Author notes
                [Correspondence to ] Professor Federico Girosi; f.girosi@ 123456westernsydney.edu.au
                Author information
                http://orcid.org/0000-0002-0137-3218
                http://orcid.org/0000-0003-3937-2285
                Article
                bmjopen-2017-019041
                10.1136/bmjopen-2017-019041
                5855213
                29523561
                404f525a-5cc3-4cd0-b018-bbace513eb36
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 09 August 2017
                : 18 January 2018
                : 31 January 2018
                Categories
                Health Services Research
                Research
                1506
                1704
                655
                Custom metadata
                unlocked

                Medicine
                epidemiology,cardiac epidemiology,chemical pathology,primary care
                Medicine
                epidemiology, cardiac epidemiology, chemical pathology, primary care

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