Medicine, Dentistry & Health Sciences Collected Works - Research Publications
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ItemDeveloping and internally validating a prediction model for total knee replacement surgery in patients with osteoarthritis.(Elsevier BV, 2022-09)OBJECTIVE: The objective of this study was to develop and internally validate a clinical algorithm for use in general practice that predicts the probability of total knee replacement (TKR) surgery within the next five years for patients with osteoarthritis. The purpose of the model is to encourage early uptake of first-line treatment strategies in patients likely to undergo TKR and to provide a cohort for the development and testing of novel interventions that prevent or delay the progression to TKR. METHOD: Electronic health records (EHRs) from 201,462 patients with osteoarthritis aged 45 years and over from 483 general practices across Australia were linked with records from the Australian Orthopaedic Association National Joint Replacement Registry and the National Death Index. A Fine and Gray competing risk prediction model was developed using these data to predict the risk of TKR within the next five years. RESULTS: During a follow-up time of 5 years, 15,979 (7.9%) patients underwent TKR and 13,873 (6.9%) died. Predictors included in the final algorithm were age, previous knee replacement, knee surgery (other than TKR), prescribing of osteoarthritis medication in the 12 months prior, comorbidity count and diagnosis of a mental health condition. Optimism corrected model discrimination was 0.67 (95% CI: 0.66 to 0.67) and model calibration acceptable. CONCLUSION: The model has the potential to reduce some of the economic burden associated with TKR in Australia. External validation and further optimisation of the algorithm will be carried out prior to implementation within Australian general practice EHR systems.
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ItemNo Preview AvailableLink-me: Protocol for a randomised controlled trial of a systematic approach to stepped mental health care in primary care(ELSEVIER SCIENCE INC, 2019-03)Primary care in Australia is undergoing significant reform, with a particular focus on cost-effective tailoring of mental health care to individual needs. Link-me is testing whether a patient-completed Decision Support Tool (DST), which predicts future severity of depression and anxiety symptoms and triages individuals into care accordingly, is clinically effective and cost-effective relative to usual care. The trial is set in general practices, with English-speaking patients invited to complete eligibility screening in their general practitioner's waiting room. Eligible and consenting patients will then complete the DST assessment and are randomised and stratified according to predicted symptom severity. Participants allocated to the intervention arm will receive feedback on DST responses, select treatment priorities, assess motivation to change, and receive a severity-matched treatment recommendation (information about and links to low intensity services for those with mild symptoms, or assistance from a specially trained health professional (care navigator) for those with severe symptoms). All patients allocated to the comparison arm will receive usual GP care plus attention control. Primary (psychological distress) and secondary (depression, anxiety, quality of life, days out of role) outcomes will be assessed at 6 and 12 months. Differences in outcome means between trial arms both across and within symptom severity group will be examined using intention-to-treat analyses. Within trial and modelled economic evaluations will be conducted to determine the value for money of credentials of Link-me. Findings will be reported to the Federal Government to inform how mental health services across Australia are funded and delivered in the future.
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ItemTarget-D: a stratified individually randomized controlled trial of the diamond clinical prediction tool to triage and target treatment for depressive symptoms in general practice: study protocol for a randomized controlled trial(BMC, 2017-07-20)BACKGROUND: Depression is a highly prevalent and costly disorder. Effective treatments are available but are not always delivered to the right person at the right time, with both under- and over-treatment a problem. Up to half the patients presenting to general practice report symptoms of depression, but general practitioners have no systematic way of efficiently identifying level of need and allocating treatment accordingly. Therefore, our team developed a new clinical prediction tool (CPT) to assist with this task. The CPT predicts depressive symptom severity in three months' time and based on these scores classifies individuals into three groups (minimal/mild, moderate, severe), then provides a matched treatment recommendation. This study aims to test whether using the CPT reduces depressive symptoms at three months compared with usual care. METHODS: The Target-D study is an individually randomized controlled trial. Participants will be 1320 general practice patients with depressive symptoms who will be approached in the practice waiting room by a research assistant and invited to complete eligibility screening on an iPad. Eligible patients will provide informed consent and complete the CPT on a purpose-built website. A computer-generated allocation sequence stratified by practice and depressive symptom severity group, will randomly assign participants to intervention (treatment recommendation matched to predicted depressive symptom severity group) or comparison (usual care plus Target-D attention control) arms. Follow-up assessments will be completed online at three and 12 months. The primary outcome is depressive symptom severity at three months. Secondary outcomes include anxiety, mental health self-efficacy, quality of life, and cost-effectiveness. Intention-to-treat analyses will test for differences in outcome means between study arms overall and by depressive symptom severity group. DISCUSSION: To our knowledge, this is the first depressive symptom stratification tool designed for primary care which takes a prognosis-based approach to provide a tailored treatment recommendation. If shown to be effective, this tool could be used to assist general practitioners to implement stepped mental-healthcare models and contribute to a more efficient and effective mental health system. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR 12616000537459 ). Retrospectively registered on 27 April 2016. See Additional file 1 for trial registration data.
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ItemCorrection.(BMJ, 2015-07-14)