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Epidemiology of arthritis, chronic back pain, gout, osteoporosis, spondyloarthropathies and rheumatoid arthritis among 1.5 million patients in Australian general practice: NPS MedicineWise MedicineInsight dataset.

ABSTRACT: Previous estimates for the prevalence of musculoskeletal conditions (MSK) and chronic pain in Australia have been based on self-report. We aimed to determine the prevalence and distribution of arthritis, chronic back pain, gout, osteoporosis, spondyloarthropathies and rheumatoid arthritis and current consultations for chronic pain among adults attending Australian general practice, and describe their distribution according to sociodemographic characteristics and presence of co-morbidities.We investigated 1,501,267 active adult patients (57.6% females; 22.5% ≥65y) evaluated between 2013 and 2016 and included in the MedicineInsight database (a National Prescribing Service MedicineWise program), a large general practice data program that extracts longitudinal de-identified electronic medical record data from 'active' patients in over 550 practices. Three main groups of outcomes were investigated: 1) "prevalence" of arthritis, chronic back pain, gout, osteoporosis, spondyloarthropathies, and/or rheumatoid arthritis between 2000 and 2016; 2) "current" diagnosis/encounter for the same conditions occurring between 2013 and 2016, and; 3) "current" consultations for chronic pain of any type occurring between 2013 and 2016.The combined "prevalence" of the investigated MSK (diagnosis between 2000 and 2016) among adults attending Australian general practice was 16.8% (95%CI 15.9;17.7) with 21.3% (95%CI 20.2;22.4) of the sample consulting for chronic pain between 2013 and 2016. The investigated MSK with the highest "prevalence" were arthritis (9.5%) and chronic back pain (6.7%). Patients with some of these MSK attended general practices more frequently than those without these conditions (median 2.0 and 1.0 contacts/year, respectively). The "prevalence" of the investigated MSK and "current" consultations for chronic pain increased with age, especially in women, but chronic pain remained stable at 22% for males aged > 40 years. The investigated MSK and chronic pain were more frequent among those in lower socioeconomic groups, veterans, Aboriginal and Torrent Strait Islanders, current and ex-smokers, and patients with chronic obstructive pulmonary disease or heart failure.The investigated MSK are more frequent among lower socioeconomic groups and the elderly. Based on information collected from adults attending Australian general practices, MedicineInsight provided similar estimates to those obtained from population-based studies, with the advantage of being based on medical diagnosis and including a national sample.

SUBMITTER: Gonzalez-Chica DA

PROVIDER: S-EPMC5774097 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ObjectivesTo assess changes in the frequency of vitamin D testing and detection of moderate/severe vitamin D deficiency (<30 nmol/L) among adults after the introduction of new Medicare Benefits Schedule (MBS) rebate criteria (November 2014), and their relationship to sociodemographic and clinical characteristics.DesignDynamic (open) cohort study SETTING: Primary care PARTICIPANTS: About 1.5 million 'active' patients aged 18+ years visiting a general practitioner and included in the National Prescribing Service MedicineInsight database.Outcome measuresThe frequency of vitamin D testing (per 1000 consultations) and moderate/severe vitamin D deficiency (%) recorded between October 2013 and March 2016, stratified by the release of the new MBS criteria for rebate.ResultsMore patients were female (57.7%) and 30.2% were aged 60+ years. Vitamin D testing decreased 47% (from 40.3 to 21.4 tests per 1000 consultations) after the new MBS criteria, while the proportion of tests with no indication for being performed increased from 71.3% to 76.5%. The proportion of patients identified as moderate/severe vitamin D deficient among those tested increased from 5.4% to 6.5%. Practices located in high socioeconomic areas continued to have the highest rates of testing, but moderate/severe vitamin D deficiency detection remained 90% more frequent in practices from low socioeconomic areas after the rebate change. Furthermore, the frequency of individuals being tested was reduced independent of the patients' sociodemographic or clinical condition, and the gap in the prevalence of vitamin D deficiency detection between those meeting or not meeting the criteria for being tested remained the same. Moderate/severe vitamin D deficiency detection decreased slightly among patients with hyperparathyroidism or chronic renal failure.ConclusionsAlthough the new criteria for rebate almost halved the frequency of vitamin D testing, it also lessened the frequency of testing among those at higher risk of deficiency, with only a small improvement in vitamin D deficiency detection.

Project description:BackgroundMedicineInsight is a database containing de-identified electronic health records (EHRs) from over 700 Australian general practices. It is one of the largest and most widely used primary health care EHR databases in Australia. This study examined the validity of algorithms that use information from various fields in the MedicineInsight data to indicate whether patients have specific health conditions. This study examined the validity of MedicineInsight algorithms for five common chronic conditions: anxiety, asthma, depression, osteoporosis and type 2 diabetes.MethodsPatients' disease status according to MedicineInsight algorithms was benchmarked against the recording of diagnoses in the original EHRs. Fifty general practices contributing data to MedicineInsight met the eligibility criteria regarding patient load and location. Five were randomly selected and four agreed to participate. Within each practice, 250 patients aged ≥ 40 years were randomly selected from the MedicineInsight database. Trained staff reviewed the original EHR for as many of the selected patients as possible within the time available for data collection in each practice.ResultsA total of 475 patients were included in the analysis. All the evaluated MedicineInsight algorithms had excellent specificity, positive predictive value, and negative predictive value (above 0.9) when benchmarked against the recording of diagnoses in the original EHR. The asthma and osteoporosis algorithms also had excellent sensitivity, while the algorithms for anxiety, depression and type 2 diabetes yielded sensitivities of 0.85, 0.89 and 0.89 respectively.ConclusionsThe MedicineInsight algorithms for asthma and osteoporosis have excellent accuracy and the algorithms for anxiety, depression and type 2 diabetes have good accuracy. This study provides support for the use of these algorithms when using MedicineInsight data for primary health care quality improvement activities, research and health system policymaking and planning.

Project description:Background: Hyperuricemia is the cause of gout. The antioxidant and neuroprotective effects of uric acid seem to benefit some patients with central nervous system injury. However, changes in the brain structure have not been discovered in patients with gout. Object: Clarify the changes in cortical thickness in patients with gout and the alteration of the structural covariance networks (SCNs) based on cortical thickness. Methods: We collected structural MRIs of 23 male gout patients and 23 age-matched healthy controls. After calculating and comparing the difference in cortical thickness between the two groups, we constructed and analyzed the cortical thickness covariance networks of the two groups, and we investigated for any changes in SCNs of gout patients. Results: Gout patients have thicker cortices in the left postcentral, left supramarginal, right medial temporal, and right medial orbitofrontal regions; and thinner cortices were found in the left insula, left superior frontal, right pericalcarine, and right precentral regions. In SCN analysis, between-group differences in global network measures showed that gout patients have a higher global efficiency. In regional network measures, more nodes in gout patients have increased centrality. In network hub analysis, we found that the transfer of the core hub area, rather than the change in number, may be the characteristic of the gout's cortical thickness covariance network. Conclusion: This is the first study on changes in brain cortical thickness and SCN based on graph theory in patients with gout. The present study found that, compared with healthy controls, gout patients show regional cortical thinning or thickening, and variation in the properties of the cortical thickness covariance network also changed. These alterations may be the combined effect of disease damage and physiological compensation. More research is needed to fully understand the complex underlying mechanisms of gout brain variation.

Dataset Information

Epidemiology of arthritis, chronic back pain, gout, osteoporosis, spondyloarthropathies and rheumatoid arthritis among 1.5 million patients in Australian general practice: NPS MedicineWise MedicineInsight dataset.

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