Dataset Information

ADHD Treatment in Primary Care: Demographic Factors, Medication Trends, and Treatment Predictors.

ABSTRACT: The aim of this study is to determine the prevalence and characteristics of youth with attention-deficit hyperactivity disorder (ADHD) in Ontario, Canada, and to determine the predictors of psychotropic medication prescriptions in youth with ADHD.This is a cross-sectional retrospective chart abstraction of more than 250 000 medical records from youth aged 1 to 24 years in a large geographical region in Ontario, Canada, linked to population-based health administrative data. A total of 10 000 charts were randomly selected and manually reviewed using predetermined criteria for ADHD and comorbidities. Prevalence, comorbidities, demographic indicators, and health service utilization characteristics were calculated. Predictors of treatment characteristics were determined using logistic regression modelling.The prevalence of ADHD was 5.4% (7.9% males, 2.7% females). Youth with ADHD had significant psychiatric comorbidities. The majority (70.0%) of ADHD patients received prescriptions for stimulant or nonstimulant ADHD medication. Antipsychotic prescriptions were provided to 11.9% of ADHD patients versus 0.9% of patients without ADHD. Antidepressant prescriptions were provided to 19.8% versus 5.4% of patients with and without ADHD, respectively. Predictors of antidepressant prescriptions were increasing age (odds ratio [OR], 1.14; 95% confidence interval [CI], 1.07 to 1.21), psychiatric consultation (OR, 2.04; 95% CI, 1.16 to 3.58), and diagnoses of both anxiety and depression (OR, 18.4; 95% CI, 8.03 to 42.1), whereas the only predictor of antipsychotic prescriptions was psychiatric consultation (OR, 3.85; 95% CI, 2.11 to 7.02).Youth with ADHD have more psychiatric comorbidities than youth without ADHD. The majority of youth with ADHD received stimulant medications, and a significant number received additional psychotropic medications, with psychiatric consultation predicting medication use.

SUBMITTER: Hauck TS

PROVIDER: S-EPMC5455870 | biostudies-other | 2017 Jun

REPOSITORIES: biostudies-other

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ADHD Treatment in Primary Care: Demographic Factors, Medication Trends, and Treatment Predictors.

Hauck Tanya S TS Lau Cindy C Wing Laura Li Foa LLF Kurdyak Paul P Tu Karen K

Canadian journal of psychiatry. Revue canadienne de psychiatrie 20170119 6

<h4>Background</h4>The aim of this study is to determine the prevalence and characteristics of youth with attention-deficit hyperactivity disorder (ADHD) in Ontario, Canada, and to determine the predictors of psychotropic medication prescriptions in youth with ADHD.<h4>Method</h4>This is a cross-sectional retrospective chart abstraction of more than 250 000 medical records from youth aged 1 to 24 years in a large geographical region in Ontario, Canada, linked to population-based health administr ...[more]

PMID: 28103079

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Project description:BACKGROUND: Questions about the existence of supplier-induced demand emerge repeatedly in discussions about governing Swiss health care. This study therefore aimed to evaluate the interrelationship between structural factors of supply and the volume of services that are provided by primary care physicians in Switzerland. METHODS: The study was designed as a cross-sectional investigation, based on the complete claims data from all Swiss health care insurers for the year 2004, which covered information from 6087 primary care physicians and 4.7 million patients. Utilization-based health service areas were constructed and used as spatial units to analyze effects of density of supply. Hierarchical linear models were applied to analyze the data. RESULTS: The data showed that, within a service area, a higher density of primary care physicians was associated with higher mortality rates and specialist density but not with treatment intensity in primary care. Higher specialist density was weakly associated with higher mortality rates and with higher treatment intensity density of primary care physicians. Annual physician-level data indicate a disproportionate increase of supplied services irrespective of the size of the number of patients treated during the same year and, even in high volume practices, no rationing but a paradoxical inducement of consultations occurred. The results provide empirical evidence that higher densities of primary care physicians, specialists and the availability of out-patient hospital clinics in a given area are associated with higher volume of supplied services per patient in primary care practices. Analyses stratified by language regions showed differences that emphasize the effect of the cantonal based (fragmented) governance of Swiss health care. CONCLUSION: The study shows high volumes in Swiss primary care and provides evidence that the volume of supply is not driven by medical needs alone. Effects related to the competition for patients between primary care physicians, specialists and out-patient hospital clinics and an association with the system of reimbursing services on a fee-for-service basis can not be excluded.

Project description:Dengue has been a major public health concern in Australia. This study has explored the spatio-temporal trends of dengue and potential socio- demographic and ecological determinants in Australia. Data on dengue cases, socio-demographic, climatic and land use types for the period January 1999 to December 2010 were collected from Australian National Notifiable Diseases Surveillance System, Australian Bureau of Statistics, Australian Bureau of Meteorology, and Australian Bureau of Agricultural and Resource Economics and Sciences, respectively. Descriptive and linear regression analyses were performed to observe the spatio-temporal trends of dengue, socio-demographic and ecological factors in Australia. A total of 5,853 dengue cases (both local and overseas acquired) were recorded across Australia between January 1999 and December 2010. Most the cases (53.0%) were reported from Queensland, followed by New South Wales (16.5%). Dengue outbreak was highest (54.2%) during 2008-2010. A highest percentage of overseas arrivals (29.9%), households having rainwater tanks (33.9%), Indigenous population (27.2%), separate houses (26.5%), terrace house types (26.9%) and economically advantage people (42.8%) were also observed during 2008-2010. Regression analyses demonstrate that there was an increasing trend of dengue incidence, potential socio-ecological factors such as overseas arrivals, number of households having rainwater tanks, housing types and land use types (e.g. intensive uses and production from dryland agriculture). Spatial variation of socio-demographic factors was also observed in this study. In near future, significant increase of temperature was also projected across Australia. The projected increased temperature as well as increased socio-ecological trend may pose a future threat to the local transmission of dengue in other parts of Australia if Aedes mosquitoes are being established. Therefore, upgraded mosquito and disease surveillance at different ports should be in place to reduce the chance of mosquitoes and dengue cases being imported into all over Australia.

Project description:BackgroundAddressing the causes of low engagement in health care is a prerequisite for reducing health inequalities. People who miss multiple appointments are an under-researched group who might have substantial unmet health needs. Individual-level patterns of missed general practice appointments might thus provide a risk marker for vulnerability and poor health outcomes. We sought to ascertain the contributions of patient and practice factors to the likelihood of missing general practice appointments.MethodsFor this national retrospective cohort analysis, we extracted UK National Health Service general practice data that were routinely collected across Scotland between Sept 5, 2013, and Sept 5, 2016. We calculated the per-patient number of missed appointments from individual appointments and investigated the risk of missing a general practice appointment using a negative binomial model offset by number of appointments made. We then analysed the effect of patient-level factors (including age, sex, and socioeconomic status) and practice-level factors (including appointment availability and geographical location) on the risk of missing appointments.FindingsThe full dataset included information from 909 073 patients, of whom 550 083 were included in the analysis after processing. We observed that 104 461 (19·0%) patients missed more than two appointments in the 3 year study period. After controlling for the number of appointments made, patterns of non-attendance could be differentiated, with patients who were aged 16-30 years (relative risk ratio [RRR] 1·21, 95% CI 1·19-1·23) or older than 90 years (2·20, 2·09-2·29), and of low socioeconomic status (Scottish Index of Multiple Deprivation decile 1: RRR 2·27, 2·22-2·31) significantly more likely to miss multiple appointments. Men missed fewer appointments overall than women, but were somewhat more likely to miss appointments in the adjusted model (1·05, 1·04-1·06). Practice factors also substantially affected attendance patterns, with urban practices in affluent areas that typically have appointment waiting times of 2-3 days the most likely to have patients who serially miss appointments. The combination of both patient and practice factors to predict appointments missed gave a higher pseudo R2 value (0·66) than models using either group of factors separately (patients only R2=0·54; practice only R2=0·63).InterpretationThe findings that both patient and practice characteristics contribute to non-attendance of general practice appointments raise important questions for both the management of patients who miss multiple appointments and the effectiveness of existing strategies that aim to increase attendance. Addressing these issues should lead to improvements in provision of services and public health.FundingScottish Government Chief Scientist Office and Data Sharing and Linkage Service of the Scottish Government.

Project description:BackgroundAdults at high risk of fragility fracture should be offered pharmacological treatment when not contraindicated, however, under-treatment is common.ObjectiveThis study aimed to investigate factors associated with bone-health medication initiation in older patients attending primary care.DesignThis was a retrospective cohort study.SettingThe study used data from forty-four general practices in Ireland from 2011-2017.SubjectsThe study included adults aged ≥ 65 years who were naïve to bone-health medication for 12 months.MethodsOverall fracture-risk (based on QFracture) and individual fracture-risk factors were described for patients initiated and not initiated onto medication and compared using generalised linear model regression with the Poisson distribution.ResultsOf 36,799 patients (51% female, mean age 75.4 (SD = 8.4)) included, 8% (n = 2,992) were observed to initiate bone-health medication during the study. One-fifth of all patients (n = 8,193) had osteoporosis or had high fracture-risk but only 21% of them (n = 1,687) initiated on medication. Female sex, older age, state-funded health cover and osteoporosis were associated with initiation. Independently of osteoporosis and co-variates, high 5-year QFracture risk for hip (IRR = 1.33 (95% CI = 1.17-1.50), P < 0.01) and all fractures (IRR = 1.30 (95% CI = 1.17-1.44), P < 0.01) were associated with medication initiation. Previous fracture, rheumatoid arthritis and corticosteroid use were associated with initiation, while liver, kidney, cardiovascular disease, diabetes and oestrogen-only hormone replacement therapy showed an inverse association.ConclusionsBone-health medication initiation is targeted at patients at higher fracture-risk but much potential under-treatment remains, particularly in those >80 years and with co-morbidities. This may reflect clinical uncertainty in older multimorbid patients, and further research should explore decision-making in preventive bone medication prescribing.

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Dataset Information

ADHD Treatment in Primary Care: Demographic Factors, Medication Trends, and Treatment Predictors.

Publications

ADHD Treatment in Primary Care: Demographic Factors, Medication Trends, and Treatment Predictors.

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