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1.
BMC Med Inform Decis Mak ; 21(1): 43, 2021 Feb 06.
Artigo em Inglês | MEDLINE | ID: mdl-33549087

RESUMO

BACKGROUND: Researchers developing prediction models are faced with numerous design choices that may impact model performance. One key decision is how to include patients who are lost to follow-up. In this paper we perform a large-scale empirical evaluation investigating the impact of this decision. In addition, we aim to provide guidelines for how to deal with loss to follow-up. METHODS: We generate a partially synthetic dataset with complete follow-up and simulate loss to follow-up based either on random selection or on selection based on comorbidity. In addition to our synthetic data study we investigate 21 real-world data prediction problems. We compare four simple strategies for developing models when using a cohort design that encounters loss to follow-up. Three strategies employ a binary classifier with data that: (1) include all patients (including those lost to follow-up), (2) exclude all patients lost to follow-up or (3) only exclude patients lost to follow-up who do not have the outcome before being lost to follow-up. The fourth strategy uses a survival model with data that include all patients. We empirically evaluate the discrimination and calibration performance. RESULTS: The partially synthetic data study results show that excluding patients who are lost to follow-up can introduce bias when loss to follow-up is common and does not occur at random. However, when loss to follow-up was completely at random, the choice of addressing it had negligible impact on model discrimination performance. Our empirical real-world data results showed that the four design choices investigated to deal with loss to follow-up resulted in comparable performance when the time-at-risk was 1-year but demonstrated differential bias when we looked into 3-year time-at-risk. Removing patients who are lost to follow-up before experiencing the outcome but keeping patients who are lost to follow-up after the outcome can bias a model and should be avoided. CONCLUSION: Based on this study we therefore recommend (1) developing models using data that includes patients that are lost to follow-up and (2) evaluate the discrimination and calibration of models twice: on a test set including patients lost to follow-up and a test set excluding patients lost to follow-up.

2.
Sr Care Pharm ; 36(1): 6-10, 2021 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-33384029

RESUMO

The Veterans' Medicines Advice and Therapeutics Education Services (MATES) program is a national data driven, behaviorally informed, health intervention to improve the use of medicines among Australian veterans. The program, which has been operating since 2004, has led the way in the use of government held data assets to generate evidenced-based health information, which, when provided to clinicians alongside educational materials, can make demonstrable improvements in health and promote practice change.


Assuntos
Saúde Pública , Austrália , Assistência à Saúde , Humanos
3.
Lancet Digit Health ; 3(2): e98-e114, 2021 02.
Artigo em Inglês | MEDLINE | ID: mdl-33342753

RESUMO

BACKGROUND: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) have been postulated to affect susceptibility to COVID-19. Observational studies so far have lacked rigorous ascertainment adjustment and international generalisability. We aimed to determine whether use of ACEIs or ARBs is associated with an increased susceptibility to COVID-19 in patients with hypertension. METHODS: In this international, open science, cohort analysis, we used electronic health records from Spain (Information Systems for Research in Primary Care [SIDIAP]) and the USA (Columbia University Irving Medical Center data warehouse [CUIMC] and Department of Veterans Affairs Observational Medical Outcomes Partnership [VA-OMOP]) to identify patients aged 18 years or older with at least one prescription for ACEIs and ARBs (target cohort) or calcium channel blockers (CCBs) and thiazide or thiazide-like diuretics (THZs; comparator cohort) between Nov 1, 2019, and Jan 31, 2020. Users were defined separately as receiving either monotherapy with these four drug classes, or monotherapy or combination therapy (combination use) with other antihypertensive medications. We assessed four outcomes: COVID-19 diagnosis; hospital admission with COVID-19; hospital admission with pneumonia; and hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis. We built large-scale propensity score methods derived through a data-driven approach and negative control experiments across ten pairwise comparisons, with results meta-analysed to generate 1280 study effects. For each study effect, we did negative control outcome experiments using a possible 123 controls identified through a data-rich algorithm. This process used a set of predefined baseline patient characteristics to provide the most accurate prediction of treatment and balance among patient cohorts across characteristics. The study is registered with the EU Post-Authorisation Studies register, EUPAS35296. FINDINGS: Among 1 355 349 antihypertensive users (363 785 ACEI or ARB monotherapy users, 248 915 CCB or THZ monotherapy users, 711 799 ACEI or ARB combination users, and 473 076 CCB or THZ combination users) included in analyses, no association was observed between COVID-19 diagnosis and exposure to ACEI or ARB monotherapy versus CCB or THZ monotherapy (calibrated hazard ratio [HR] 0·98, 95% CI 0·84-1·14) or combination use exposure (1·01, 0·90-1·15). ACEIs alone similarly showed no relative risk difference when compared with CCB or THZ monotherapy (HR 0·91, 95% CI 0·68-1·21; with heterogeneity of >40%) or combination use (0·95, 0·83-1·07). Directly comparing ACEIs with ARBs demonstrated a moderately lower risk with ACEIs, which was significant with combination use (HR 0·88, 95% CI 0·79-0·99) and non-significant for monotherapy (0·85, 0·69-1·05). We observed no significant difference between drug classes for risk of hospital admission with COVID-19, hospital admission with pneumonia, or hospital admission with pneumonia, acute respiratory distress syndrome, acute kidney injury, or sepsis across all comparisons. INTERPRETATION: No clinically significant increased risk of COVID-19 diagnosis or hospital admission-related outcomes associated with ACEI or ARB use was observed, suggesting users should not discontinue or change their treatment to decrease their risk of COVID-19. FUNDING: Wellcome Trust, UK National Institute for Health Research, US National Institutes of Health, US Department of Veterans Affairs, Janssen Research & Development, IQVIA, South Korean Ministry of Health and Welfare Republic, Australian National Health and Medical Research Council, and European Health Data and Evidence Network.

4.
Artigo em Inglês | MEDLINE | ID: mdl-33185773

RESUMO

It is known that younger patients treated with antipsychotics are at increased risk of metabolic events; however, it is unknown how this risk varies according to ethnicity, the class of antipsychotic and the specific product used, and by age group. We conducted a multinational sequence symmetry study in Asian populations (Hong Kong, Japan, Korea, Taiwan and Thailand) and non-Asian populations (Australia and Denmark) to evaluate the metabolic events associated with antipsychotics in both Asian and non-Asian populations, for typical and atypical antipsychotics, and by the subgroups of children and adolescents, and young adults. Patients aged 6-30 years newly initiating oral antipsychotic drugs were included. We defined a composite outcome for metabolic events which included dyslipidemia, hypertension and hyperglycemia. We calculated the sequence ratio (SR) by dividing the number of people for whom a medicine for one of the outcome events was initiated within a 12-month period after antipsychotic initiation by the number before antipsychotic initiation. This study included 346,904 antipsychotic initiators across seven countries. Antipsychotic use was associated with an increased risk of composite metabolic events with a pooled adjusted SR (ASR) of 1.22 (95% CI 1.00-1.50). Pooled ASRs were similar between Asian (ASR, 1.22; 95% CI 0.88-1.70) and non-Asian populations (ASR, 1.22; 95% CI 1.04-1.43). The pooled ASR for typical and atypical antipsychotics was 0.98 (95% CI 0.85-1.12) and 1.24 (95% CI 0.97-1.59), respectively. No difference was observed in the relative effect in children and adolescents compared to young adults. The risk of metabolic events associated with antipsychotics use was similar in magnitude in Asian and non-Asian populations despite the marked difference in drug utilization patterns.

5.
J Biomed Inform ; 112: 103603, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33153975

RESUMO

As a medicine safety issue, Drug-Drug Interaction (DDI) may become an unexpected threat for causing Adverse Drug Events (ADEs). There is a growing demand for computational methods to efficiently and effectively analyse large-scale data to detect signals of Adverse Drug-drug Interactions (ADDIs). In this paper, we aim to detect high-quality signals of ADDIs which are non-spurious and non-redundant. We propose a new method which employs the framework of Bayesian network to infer the direct associations between the target ADE and medicines, and uses domain knowledge to facilitate the learning of Bayesian network structures. To improve efficiency and avoid redundancy, we design a level-wise algorithm with pruning strategy to search for high-quality ADDI signals. We have applied the proposed method to the United States Food and Drug Administration's (FDA) Adverse Event Reporting System (FAERS) data. The result shows that 54.45% of detected signals are verified as known DDIs and 10.89% were evaluated as high-quality ADDI signals, demonstrating that the proposed method could be a promising tool for ADDI signal detection.

6.
BMJ Open ; 10(10): e038016, 2020 10 14.
Artigo em Inglês | MEDLINE | ID: mdl-33055116

RESUMO

OBJECTIVE: Educational, and audit and feedback interventions are effective in promoting health professional behaviour change and evidence adoption. However, we lack evidence to pinpoint which particular features make them most effective. Our objective is to identify determinants of quality in professional behaviour change interventions, as perceived by participants. DESIGN: We performed a comparative observational study using data from the Veterans' Medicines Advice and Therapeutics Education Services program, a nation-wide Australian Government Department of Veterans' Affairs funded program that provides medicines advice and promotes physician adoption of best practices by use of a multifaceted intervention (educational material and a feedback document containing individual patient information). SETTING: Primary care practices providing care to Australian veterans. PARTICIPANTS: General practitioners (GPs) targeted by 51 distinct behaviour change interventions, implemented between November 2004 and June 2018. PRIMARY AND SECONDARY OUTCOME MEASURES: We extracted features related to presentation (number of images, tables and characters), content (polarity and subjectivity using sentiment analysis, number of external links and medicine mentions) and the use of five behaviour change techniques (prompt/cues, goal setting, discrepancy between current behaviour and goal, information about health consequences, feedback on behaviour). The main outcome was perceived usefulness, extracted from postintervention survey. RESULTS: On average, each intervention was delivered to 9667 GPs. Prompt and goal setting strategies in the audit and feedback were independently correlated to perceived usefulness (p=0.030 and p=0.005, respectively). The number of distinct behaviour change techniques in the audit and feedback was correlated with improved usefulness (Pearson's coefficient 0.45 (0.19, 0.65), p=0.001). No presentation or content features in the educational material were correlated with perceived usefulness. CONCLUSIONS: The finding provides additional evidence encouraging the use of behaviour change techniques, in particular prompt and goal setting, in audit and feedback interventions.

7.
Artigo em Inglês | MEDLINE | ID: mdl-33105301

RESUMO

BACKGROUND: There is increasing interest in the development of statistical models that can be used to estimate risk of adverse patient outcomes after joint arthroplasty. Competing risk approaches have been recommended to estimate risk of longer-term revision, which is often likely to be precluded by the competing risk of death. However, a common approach is to ignore the competing risk by treating death as a censoring event and using standard survival models such as Cox regression. It is well-known that this approach can overestimate the event risk for population-level estimates, but the impact on the estimation of a patient's individualized risk after joint arthroplasty has not been explored. QUESTIONS/PURPOSES: We performed this study to (1) determine whether using a competing risk or noncompeting risk method affects the accuracy of predictive models for joint arthroplasty revision and (2) determine the magnitude of difference that using a competing risks versus noncompeting risks approach will make to predicted risks for individual patients. METHODS: The predictive performance of a standard Cox model, with competing risks treated as censoring events, was compared with the performance of two competing risks approaches, the cause-specific Cox model and Fine-Gray model. Models were trained and tested using data pertaining to 531,304 TKAs and 274,618 THAs recorded in the Australian Orthopaedic Association National Joint Replacement Registry between January 1, 2003 and December 31, 2017. The registry is a large database with near-complete capture and follow-up of all hip and knee joint arthroplasty in Australia from 2003 onwards, making it an ideal setting for this study. The performance of the three modeling approaches was compared in two different prediction settings: prediction of the 10-year risk of all-cause revision after TKA and prediction of revision for periprosthetic fracture after THA. The calibration and discrimination of each approach were compared using the concordance index, integrated Brier scores, and calibration plots. Calibration of 10-year risk estimates was further assessed within subgroups of age by comparing the observed and predicted proportion of events. Estimated 10-year risks from each model were also compared in three hypothetical patients with different risk profiles to determine whether differences in population-level performance metrics would translate into a meaningful difference for individual patient predictions. RESULTS: The standard Cox and two competing risks models showed near-identical ability to distinguish between high-risk and low-risk patients (c-index 0.64 [95% CI, 0.64 to 0.64] for all three modeling approaches for TKAs and 0.66 [95% CI 0.66 to 0.66] for THA). All models performed similarly in patients younger than 75 years, but for patients aged 75 years and older, the standard Cox model overestimated the risk of revision more than the cause-specific Cox and Fine-Gray model did. These results were echoed when predictions were made for hypothetical individual patients. For patients with a low competing risk of mortality, the 10-year predicted risks from the standard Cox, cause-specific Cox, and Fine-Gray models were similar for TKAs and THAs. However, a larger difference was observed for hypothetical 89-year-old patients with increased mortality risk. In TKAs, the revision risk for an 89-year-old patient was so low that this difference was negligible (0.83% from the cause-specific Cox model versus 1.1% from the standard Cox model). However, for THAs, where older age is a risk factor for both death and revision for periprosthetic fracture, a larger difference was observed in the 10-year predicted risks for a hypothetical 89-year-old patient (3.4% from the cause-specific Cox model versus 5.2% from the standard Cox model). CONCLUSIONS: When developing models to predict longer-term revision of joint arthroplasty, failing to use a competing risks modeling approach will result in overestimating the revision risk for patients with a high risk of mortality during the surveillance period. However, even in an extreme instance, where both the frequency of the event of interest and the competing risk of death are high, the largest absolute difference in predicted 10-year risk for an individual patient was just 1.8%, which may not be of consequence to an individual. Despite these findings, when developing or using risk prediction models, researchers and clinicians should be aware of how competing risks were handled in the modeling process, particularly if the model is intended for use populations where the mortality risk is high. LEVEL OF EVIDENCE: Level III, therapeutic study.

9.
BMJ Open ; 10(10): e039579, 2020 10 29.
Artigo em Inglês | MEDLINE | ID: mdl-33122320

RESUMO

OBJECTIVES: To evaluate the impact of a patient-specific national programme targeting older Australians and health professionals that aimed to increase use of emollient moisturisers to reduce to the risk of skin tears. DESIGN: A prospective cohort intervention. PARTICIPANTS: The intervention targeted 52 778 Australian Government's Department of Veterans' Affairs patients aged over 64 years who had risk factors for wound development, and their general practitioners (GPs) (n=14 178). OUTCOME MEASURES: An interrupted time series model compared the rate of dispensing of emollients in the targeted cohort before and up to 23 months after the intervention. Commitment questions were included in self-report forms. RESULTS: In the first month after the intervention, the rate of claims increased 6.3-fold (95% CI: 5.2 to 7.6, p<0.001) to 10 emollient dispensings per 1000 patients in the first month after the intervention. Overall, the intervention resulted in 10 905 additional patient-months of treatment. The increased rate of dispensing among patients who committed to talking to their GP about using an emollient was six times higher (rate ratio: 6.2, 95% CI: 4.4 to 8.7) than comparison groups. CONCLUSIONS: The intervention had a sustained effect over 23 months. Veterans who responded positively to commitment questions had higher uptake of emollients than those who did not.

10.
J Am Med Inform Assoc ; 27(8): 1331-1337, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32909033

RESUMO

Evidence derived from existing health-care data, such as administrative claims and electronic health records, can fill evidence gaps in medicine. However, many claim such data cannot be used to estimate causal treatment effects because of the potential for observational study bias; for example, due to residual confounding. Other concerns include P hacking and publication bias. In response, the Observational Health Data Sciences and Informatics international collaborative launched the Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) research initiative. Its mission is to generate evidence on the effects of medical interventions using observational health-care databases while addressing the aforementioned concerns by following a recently proposed paradigm. We define 10 principles of LEGEND that enshrine this new paradigm, prescribing the generation and dissemination of evidence on many research questions at once; for example, comparing all treatments for a disease for many outcomes, thus preventing publication bias. These questions are answered using a prespecified and systematic approach, avoiding P hacking. Best-practice statistical methods address measured confounding, and control questions (research questions where the answer is known) quantify potential residual bias. Finally, the evidence is generated in a network of databases to assess consistency by sharing open-source analytics code to enhance transparency and reproducibility, but without sharing patient-level information. Here we detail the LEGEND principles and provide a generic overview of a LEGEND study. Our companion paper highlights an example study on the effects of hypertension treatments, and evaluates the internal and external validity of the evidence we generate.

11.
J Am Med Inform Assoc ; 27(8): 1268-1277, 2020 Aug 01.
Artigo em Inglês | MEDLINE | ID: mdl-32827027

RESUMO

OBJECTIVES: To demonstrate the application of the Large-scale Evidence Generation and Evaluation across a Network of Databases (LEGEND) principles described in our companion article to hypertension treatments and assess internal and external validity of the generated evidence. MATERIALS AND METHODS: LEGEND defines a process for high-quality observational research based on 10 guiding principles. We demonstrate how this process, here implemented through large-scale propensity score modeling, negative and positive control questions, empirical calibration, and full transparency, can be applied to compare antihypertensive drug therapies. We assess internal validity through covariate balance, confidence-interval coverage, between-database heterogeneity, and transitivity of results. We assess external validity through comparison to direct meta-analyses of randomized controlled trials (RCTs). RESULTS: From 21.6 million unique antihypertensive new users, we generate 6 076 775 effect size estimates for 699 872 research questions on 12 946 treatment comparisons. Through propensity score matching, we achieve balance on all baseline patient characteristics for 75% of estimates, observe 95.7% coverage in our effect-estimate 95% confidence intervals, find high between-database consistency, and achieve transitivity in 84.8% of triplet hypotheses. Compared with meta-analyses of RCTs, our results are consistent with 28 of 30 comparisons while providing narrower confidence intervals. CONCLUSION: We find that these LEGEND results show high internal validity and are congruent with meta-analyses of RCTs. For these reasons we believe that evidence generated by LEGEND is of high quality and can inform medical decision-making where evidence is currently lacking. Subsequent publications will explore the clinical interpretations of this evidence.

12.
Br J Ophthalmol ; 2020 Jun 10.
Artigo em Inglês | MEDLINE | ID: mdl-32522792

RESUMO

AIMS: To identify the association between ranibizumab and risk of stroke and acute myocardial infarction (AMI) in patients with exudative age-related macular degeneration (AMD). METHODS: We identified patients aged ≥45 years who received ranibizumab for exudative AMD from the Korean National Health Insurance database. Of these, we selected patients suffering stroke or AMI for the self-controlled case series. We estimated incidence rate ratios (IRR) for stroke or AMI by comparing incidence rates of ranibizumab-exposed periods to that of baseline using conditional Poisson regression. The risks of haemorrhagic and ischaemic strokes were also calculated separately. RESULTS: Among 33 134 patients receiving ranibizumab, 2397 patients had stroke or AMI. The risk of stroke (IRR=0.83, 95% CI 0.75 to 0.91) was not increased during the overall exposed period; however, there was a marginally elevated risk in ≥57 days exposed period (IRR=1.14, 95% CI 1.001 to 1.31). When analysing by the types of stroke, no increased risks of haemorrhagic (IRR=1.01, 95% CI 0.80 to 1.26) and ischaemic stroke (IRR=0.78, 95% CI 0.71 to 0.86) were observed during the exposed period, although the risks of ischaemic and haemorrhagic stroke were slightly elevated during ≥57 days exposed period. We could not find an association between ranibizumab and AMI. CONCLUSIONS: Ranibizumab intravitreal injections did not increase the overall risk of stroke or AMI. Although the cardiovascular risk in patient receiving ranibizumab seems to be low, continuous monthly use of ranibizumab for high-risk patients should be judged carefully.

13.
Artif Intell Med ; 104: 101839, 2020 04.
Artigo em Inglês | MEDLINE | ID: mdl-32499007

RESUMO

Adverse drug events (ADEs) may occur and lead to severe consequences for the public, even though clinical trials are conducted in the stage of pre-market. Computational methods are still needed to fulfil the task of pharmacosurveillance. In post-market surveillance, the spontaneous reporting system (SRS) has been widely used to detect suspicious associations between medicines and ADEs. However, the passive mechanism of SRS leads to the hysteresis in ADE detection by SRS based methods, not mentioning the acknowledged problem of under-reporting and duplicate reporting in SRS. Therefore, there is a growing demand for other complementary methods utilising different types of healthcare data to assist with global pharmacosurveillance. Among those data sources, prescription data is of proved usefulness for pharmacosurveillance. However, few works have used prescription data for signalling ADEs. In this paper, we propose a data-driven method to discover medicines that are responsible for a given ADE purely from prescription data. Our method uses a logistic regression model to evaluate the associations between up to hundreds of suspected medicines and an ADE spontaneously and selects the medicines possessing the most significant associations via Lasso regularisation. To prepare data for training the logistic regression model, we adapt the design of the case-crossover study to construct case time and control time windows for the extraction of medicine use information. While the case time window can be readily determined, we propose several criteria to select the suitable control time windows providing the maximum power of comparisons. In order to address confounding situations, we have considered diverse factors in medicine utilisation in terms of the temporal effect of medicine and the frequency of prescription, as well as the individual effect of patients on the occurrence of an ADE. To assess the performance of the proposed method, we conducted a case study with a real-world prescription dataset. Validated by the existing domain knowledge, our method successfully traced a wide range of medicines that are potentially responsible for the ADE. Further experiments were also carried out according to a recognised gold standard, our method achieved a sensitivity of 65.9% and specificity of 96.2%.

14.
medRxiv ; 2020 Jun 12.
Artigo em Inglês | MEDLINE | ID: mdl-32587982

RESUMO

INTRODUCTION: Angiotensin converting enzyme inhibitors (ACEs) and angiotensin receptor blockers (ARBs) could influence infection risk of coronavirus disease (COVID-19). Observational studies to date lack pre-specification, transparency, rigorous ascertainment adjustment and international generalizability, with contradictory results. METHODS: Using electronic health records from Spain (SIDIAP) and the United States (Columbia University Irving Medical Center and Department of Veterans Affairs), we conducted a systematic cohort study with prevalent ACE, ARB, calcium channel blocker (CCB) and thiazide diuretic (THZ) use to determine relative risk of COVID-19 diagnosis and related hospitalization outcomes. The study addressed confounding through large-scale propensity score adjustment and negative control experiments. RESULTS: Following over 1.1 million antihypertensive users identified between November 2019 and January 2020, we observed no significant difference in relative COVID-19 diagnosis risk comparing ACE/ARB vs CCB/THZ monotherapy (hazard ratio: 0.98; 95% CI 0.84 - 1.14), nor any difference for mono/combination use (1.01; 0.90 - 1.15). ACE alone and ARB alone similarly showed no relative risk difference when compared to CCB/THZ monotherapy or mono/combination use. Directly comparing ACE vs. ARB demonstrated a moderately lower risk with ACE, non-significant for monotherapy (0.85; 0.69 - 1.05) and marginally significant for mono/combination users (0.88; 0.79 - 0.99). We observed, however, no significant difference between drug- classes for COVID-19 hospitalization or pneumonia risk across all comparisons. CONCLUSION: There is no clinically significant increased risk of COVID-19 diagnosis or hospitalization with ACE or ARB use. Users should not discontinue or change their treatment to avoid COVID-19.

15.
Drug Saf ; 43(8): 787-795, 2020 08.
Artigo em Inglês | MEDLINE | ID: mdl-32578157

RESUMO

INTRODUCTION: Medicine safety signal detection methods employed by the medicine regulator in Australia (Therapeutic Goods Administration [TGA], Department of Health) rely predominantly on analysis of spontaneous adverse event (AE) reports, sponsor notifications or information shared by international agencies. The limitations of these methods and the availability of large administrative health data sets has given rise to greater interest in the use of administrative health data to support pharmacovigilance (PV). OBJECTIVE: We explored whether prescription sequence symmetry analysis (PSSA) of Pharmaceutical Benefits Scheme (PBS) data can enhance signal detection by the TGA, using the AE, heart failure (HF) as a case study. METHODS: We applied the PSSA method to all single-ingredient medicines dispensed under the PBS between 2012 and 2016, using furosemide initiation as a proxy for new-onset HF. A signal was considered present if the lower limit of the 95% confidence interval for the adjusted sequence ratio was > 1. We excluded medicines known to cause HF, indicated for HF treatment or indicated for diseases that may contribute to HF. RESULTS: Of the 654 tested medicines, 26 potential new HF signals were detected by PSSA. Five signals had additional support for the possible association provided by biological plausibility, consistency and disproportionate reporting of cases of HF to the TGA and the World Health Organization; and clinical impact. CONCLUSION: PSSA was able to identify potential signals for further evaluation. With the increasing availability of different administrative health data sources, the strengths and weaknesses of methods used to analyse these data for the purpose of regulatory PV should be evaluated.

16.
Int J Drug Policy ; 81: 102767, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-32416524

RESUMO

BACKGROUND: The Australian medicines regulator, the Therapeutic Goods Administration (TGA), rescheduled all codeine-containing medicines to be available only on prescription on 1 February 2018. This study was conducted to determine whether use of analgesics changed following codeine re-scheduling to prescription only status, and whether there was a change in the use of codeine preparations and a therapeutic shift to stronger opioids or other analgesics in the Australian veteran population following the change. METHODS: Interrupted time series analysis using Repatriation Pharmaceutical Benefits Scheme (RPBS) claims data from the Australian Government Department of Veterans' Affairs (DVA) for clients with dispensing of opioid and non-opioid analgesics between January 2015 and April 2019. Trends in the monthly rate of analgesic dispensings (opioid and non-opioid) were compared for the period between January 2015 and January 2018 with the period February 2018 to April 2019. RESULTS: Paracetamol with codeine 8mg was the only analgesic with an increased rate of dispensing following the February 2018 codeine scheduling changes. Prior to codeine re-scheduling, the rate of dispensing of paracetamol with codeine 8mg was decreasing by 0.9% each month. Immediately after the scheduling changes, dispensing of paracetamol with codeine 8mg increased by 45% (95%CI=1.282-1.676, p<0.001) and in the fifteen month period thereafter (February 2018 to April 2019), the rate of dispensing increased by 4% each month (95%CI=1.027-1.054, p<0.001). Therapeutic shift from over-the-counter codeine products to other opioids was not observed, with no increase in the rate of dispensing of any of the other opioid (or non-opioid) analgesics following the codeine scheduling changes. CONCLUSION: A significant increase in prescription use of paracetamol with codeine 8mg was observed after the February 2018 codeine re-scheduling. Therapeutic shift to stronger opioid analgesics was not observed in the study population.

17.
Australas J Ageing ; 2020 May 20.
Artigo em Inglês | MEDLINE | ID: mdl-32436314

RESUMO

OBJECTIVE: To determine the access to and use of health-care services by people with dementia in the community. METHODS: A retrospective cross-sectional analysis of the Australian Government Department of Veterans' Affairs (DVA) administrative claims data was conducted. Veterans and their spouses with one or more dementia claims between 1 January 2000 and 30 June 2016, who were aged ≥45 years at the time of the claim and who were still alive and living in the community on 30 June 2017, were included. We assessed the proportions of people with dementia who received medical, pharmacy and medicines, allied health services, and home care supports from 1 July 2016 to 30 June 2017. RESULTS: A total of 10 171 people with dementia were included. They had a median age of 89 years, 60% were female, and 63% lived in a major city. Over the one-year study period, 98% visited the GP and 99% had medicines dispensed at a pharmacy. Eighty-two per cent saw a specialist, and 19% saw a geriatrician. Thirty-one per cent received a DVA-funded dose administration aid to support medication administration, and 19% received a home medicines review. Less than half had claims for occupational therapist services (48%), community nursing (48%), physiotherapists (41%) or dentist visits (33%). Fifty-eight per cent received home care supports, for example domestic assistance. CONCLUSIONS: Many people living with dementia in the community do not access all of the health-care or support services available to them. Ensuring that people with dementia and their carers are supported to access the services available to assist them live in the community setting for as long as possible is important.

18.
J Opioid Manag ; 16(2): 103-110, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32329885

RESUMO

INTRODUCTION AND AIMS: Mental health disorders and substance abuse are risk factors that both precede and follow chronic opioid use. We predicted that incident opioid users would have lower rates of mental health comorbidities than chronic opioid users, but that incident chronic opioid users would have lower rates of mental health comorbidities than prevalent chronic users. DESIGN AND METHODS: We used administrative health claims data to evaluate differences in lifetime mental health and substance abuse comorbidity profiles of people who were prevalent and incident chronic opioid users, as well as those who used opioids acutely. Results were stratified by age. RESULTS: Over 5,188 people were prevalent chronic opioid users at study entry. Of the 10,079 people who initiated opioids, 10.2 per-cent had a subsequent chronic episode (incident chronic) and the remainder stopped within 90 days (incident acute). In prevalent chronic users compared to incident chronic users, rates of depression and anxiety were higher across all age groups (odds ratio (OR) across age groups range from = 1.60, 95 percent confidence interval (CI) = 1.35,1.89, to OR = 6.66, 95 percent CI = 3.02, 14.69) and prevalence of alcohol abuse was higher in those aged 55 to 74 years (OR = 5.11, 95 percent CI = 1.83, 14.24, p = 0.002). Acute users were less likely than incident chronic users to have depression and anxiety in those aged over 74 years (depression OR = 0.82, 95 per-cent CI = 0.70, 0.95; anxiety OR = 0.82, 95% CI 0.70, 0.98). CONCLUSIONS: Mental health morbidities commonly associated with chronic opioid use increase in prevalence as chronic use continues.


Assuntos
Analgésicos Opioides , Transtornos Relacionados ao Uso de Opioides , Idoso , Austrália/epidemiologia , Comorbidade , Humanos , Pessoa de Meia-Idade , Transtornos Relacionados ao Uso de Opioides/complicações , Prevalência
19.
BMJ Open ; 10(4): e032851, 2020 04 22.
Artigo em Inglês | MEDLINE | ID: mdl-32327474

RESUMO

INTRODUCTION: Many medicines have adverse effects which are difficult to detect and frequently go unrecognised. Pharmacist monitoring of changes in signs and symptoms of these adverse effects, which we describe as medicine-induced deterioration, may reduce the risk of developing frailty. The aim of this trial is to determine the effectiveness of a 12-month pharmacist service compared with usual care in reducing medicine-induced deterioration, frailty and adverse reactions in older people living in aged-care facilities in Australia. METHODS AND ANALYSIS: The reducing medicine-induced deterioration and adverse reactions trial is a multicentre, open-label randomised controlled trial. Participants will be recruited from 39 facilities in South Australia and Tasmania. Residents will be included if they are using four or more medicines at the time of recruitment, or taking more than one medicine with anticholinergic or sedative properties. The intervention group will receive a pharmacist assessment which occurs every 8 weeks. The pharmacists will liaise with the participants' general practitioners when medicine-induced deterioration is evident or adverse events are considered serious. The primary outcome is a reduction in medicine-induced deterioration from baseline to 6 and 12 months, as measured by change in frailty index. The secondary outcomes are changes in cognition scores, 24-hour movement behaviour, grip strength, weight, percentage robust, pre-frail and frail classification, rate of adverse medicine events, health-related quality of life and health resource use. The statistical analysis will use mixed-models adjusted for baseline to account for repeated outcome measures. A health economic evaluation will be conducted following trial completion using data collected during the trial. ETHICS AND DISSEMINATION: Ethics approvals have been obtained from the Human Research Ethics Committee of University of South Australia (ID:0000036440) and University of Tasmania (ID:H0017022). A copy of the final report will be provided to the Australian Government Department of Health. TRIAL REGISTRATION NUMBER: Australian and New Zealand Trials Registry ACTRN12618000766213.

20.
JAMA Intern Med ; 180(4): 542-551, 2020 04 01.
Artigo em Inglês | MEDLINE | ID: mdl-32065600

RESUMO

Importance: Chlorthalidone is currently recommended as the preferred thiazide diuretic to treat hypertension, but no trials have directly compared risks and benefits. Objective: To compare the effectiveness and safety of chlorthalidone and hydrochlorothiazide as first-line therapies for hypertension in real-world practice. Design, Setting, and Participants: This is a Large-Scale Evidence Generation and Evaluation in a Network of Databases (LEGEND) observational comparative cohort study with large-scale propensity score stratification and negative-control and synthetic positive-control calibration on databases spanning January 2001 through December 2018. Outpatient and inpatient care episodes of first-time users of antihypertensive monotherapy in the United States based on 2 administrative claims databases and 1 collection of electronic health records were analyzed. Analysis began June 2018. Exposures: Chlorthalidone and hydrochlorothiazide. Main Outcomes and Measures: The primary outcomes were acute myocardial infarction, hospitalization for heart failure, ischemic or hemorrhagic stroke, and a composite cardiovascular disease outcome including the first 3 outcomes and sudden cardiac death. Fifty-one safety outcomes were measured. Results: Of 730 225 individuals (mean [SD] age, 51.5 [13.3] years; 450 100 women [61.6%]), 36 918 were dispensed or prescribed chlorthalidone and had 149 composite outcome events, and 693 337 were dispensed or prescribed hydrochlorothiazide and had 3089 composite outcome events. No significant difference was found in the associated risk of myocardial infarction, hospitalized heart failure, or stroke, with a calibrated hazard ratio for the composite cardiovascular outcome of 1.00 for chlorthalidone compared with hydrochlorothiazide (95% CI, 0.85-1.17). Chlorthalidone was associated with a significantly higher risk of hypokalemia (hazard ratio [HR], 2.72; 95% CI, 2.38-3.12), hyponatremia (HR, 1.31; 95% CI, 1.16-1.47), acute renal failure (HR, 1.37; 95% CI, 1.15-1.63), chronic kidney disease (HR, 1.24; 95% CI, 1.09-1.42), and type 2 diabetes mellitus (HR, 1.21; 95% CI, 1.12-1.30). Chlorthalidone was associated with a significantly lower risk of diagnosed abnormal weight gain (HR, 0.73; 95% CI, 0.61-0.86). Conclusions and Relevance: This study found that chlorthalidone use was not associated with significant cardiovascular benefits when compared with hydrochlorothiazide, while its use was associated with greater risk of renal and electrolyte abnormalities. These findings do not support current recommendations to prefer chlorthalidone vs hydrochlorothiazide for hypertension treatment in first-time users was found. We used advanced methods, sensitivity analyses, and diagnostics, but given the possibility of residual confounding and the limited length of observation periods, further study is warranted.


Assuntos
Anti-Hipertensivos/uso terapêutico , Clortalidona/uso terapêutico , Hidroclorotiazida/uso terapêutico , Hipertensão/tratamento farmacológico , Anti-Hipertensivos/efeitos adversos , Clortalidona/efeitos adversos , Feminino , Humanos , Hidroclorotiazida/efeitos adversos , Masculino , Pessoa de Meia-Idade , Estudos Retrospectivos
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