Abstract
Background
Waiting time between GP referral and consultation by a specialist (known as ‘Wait 2’ time) has not previously been reported in the Australian Capital Territory (ACT), but in other states it can be prolonged. A Canberra Health Service (CHS) internal review in 2020, The Reboot Project, found 1,590 patients awaiting orthopaedic consultation at Canberra Hospital; after 2 years only 38% had been seen, with a mean wait time of 3.6 years. Yet there is excellent evidence, from the ACT and internationally, that advanced practice physiotherapists (APP) can provide an efficient and accurate diagnostic and screening service. This project was developed in collaboration between University of Canberra (UC), CHS and local and national stakeholders to translate the best evidence from research into clinical practice. In our project, we investigated how implementing strategies aligned with best practice care of knee osteoarthritis could impact the care pathways and wait time for patients referred to see an orthopaedic surgeon in the ACT public health system.
The aim of this project was to sustainably eradicate Wait 2 and ensure that public patients have access to best practice care, including shared decision-making and non-surgical interventions. To unravel and remove access barriers to best practice interventions, we needed to:
1. Use a systems approach to implement an expert review that was responsive, cost-effective and followed best practice interventions.
2. Establish strong collaboration between consumers, primary health care, public orthopaedic triage and surgeons, and across public and private sectors.
3. Develop pathways to ensure patients have knee replacement surgery at the right time.
Method
A knowledge translation approach was taken, including qualitative, quantitative and economic analyses. We gathered evidence to determine best practice and used collaborative strategies for decision-making guided by deliberative democratic principles. The governance model of this project included the project executive, whole of team meetings (investigators, project manager and Trauma and Orthopaedic Research Unit staff), a steering committee (including stakeholders and consumers) and working parties, variously including academic team members, CHS members, health professionals, stakeholders and consumers. Evaluation for the knowledge translation approach included quantitative, qualitative and economic analyses.
We gathered baseline data on waiting times and patient and stakeholder experiences to identify issues, barriers and enablers to implementation of best practice in March 2023. Waiting times were measured for patients with a new referral for knee osteoarthritis and those already waiting for a consultation between 1 March and 30 September for baseline capture in 2022, then each year’s cohort in 2023 and 2024. Characteristics of the cohorts, wait time and pathways – either seen by an APP, a surgeon or both – and the outcome of those visits were analysed for predictive factors.
Interviews, conducted by UC academic members Angie Fearon and Jennie Scarvell, were recorded, transcribed and de-identified. Member checking of emerging themes and quotes resulted in some requests for revision or redaction by participants. Four investigators used thematic analysis, based in phenomenology, against a framework to organise the findings based on the aims of the project: to understand what is working well, what needs improvement, what a model of care would look like, and the barriers and enablers to implementation of that model of care. Participants were drawn through purposive sampling, and included patients (n = 6), primary care practitioners in general practice (GPs) (n = 4) and other primary care (n = 3), surgeons and registrars (n = 6), physiotherapists in the community, acute service and private care (n = 5), and the CHS Executive (n = 5).
Changes to the healthcare service during the period included those implemented by CHS as part of the implementation working party discussions and those serendipitously occurring as part of IT improvements in CHS. Acute care physiotherapy increased resources to the APP clinic so that more patients with knee osteoarthritis could be seen (from 0.8 to 1.5 FTE), connections with community osteoarthritis and obesity programs were streamlined, CHS Community Care expanded the availability of the hip and knee osteoarthritis education and exercise program GLA:D (Good Living with osteoArthritis: Denmark) (Barton et al., 2021; Roos et al., 2018) and several stakeholder engagement activities were conducted. Serendipitously, EPIC Digital Health Record (DHR) was established in November 2022, the HealthLink e-referral system was upgraded, and CHS Quality and Safety initiated the Osteoarthritis of the Knee Clinical Care Standard for knee osteoarthritis.
We evaluated the wait times measured for the 2023 and 2024 cohorts and the pathways for patients. To evaluate project impact, we held further interviews and focus groups in 2023 and 2024. Participants were invited from patient (n = 9), GP (n = 4), physiotherapy (n = 5), surgeon and registrar (n = 5) and health executive groups (n = 5). Three researchers used thematic analysis, based in phenomenology, to derive themes against the questions outlined above, with the addition of ‘what changes have you noticed?’
To assess the economic impact of waiting, and the economic considerations and decisions that influence current and future decisions, we conducted three tasks:
1. To calculate the costs to patients of living with osteoarthritis, using the Canadian Cost to Patients Questionnaire, 16 participants collected data for 6 or 12 months on out-of-pocket costs incurred.
2. To evaluate the costs of the three different patient pathways and outcomes, we modelled them using a Markov chain. Patients could either be seen in the APP clinic; be seen in APP clinic and then referred to a surgeon; or wait to see a surgeon. Their outcomes could be discharge; referral to community programs; or total knee replacement. Costs and the likelihood of successful outcomes were built into the model.
3. To describe optimal pathways and decisions and to inform policy, we fed information from the Markov model and from GLA:D outcomes data into a general algebraic model of optimising pathways and decisions. This work will be reported at the end of 2025.
Key findings
Compared to 2022, wait times to see a surgeon were 0.14 times shorter in 2023 and 0.10 times shorter in 2024. The waiting time improved from 50% of patients seen within 114 days in 2022 to within 45 and 46 days in 2023 and 2024 respectively, and from 90% seen within 1,248 days to within 91 and 84 days respectively. The proportion of patients seen in the APP clinic increased from 20% in 2022 to 81% in 2023 and 76% in 2024. Patients seen in the APP clinic risked fewer delays than those seen only in the surgical clinic (APP clinic incidence rate ratio [IRR]: 0.55; 95%CI: 0.43, 0.72; and if seen in both APP and surgical clinics IRR: 0.54; 95%CI:0.41, 0.70). Patients in 2023 and 2024 had reduced risk of extended wait times to see a surgeon (adjusted odds ratio [AOR]: 0.11; 95% CI: 0.04, 0.31; AOR: 0.02; 95% CI: 0.004, 0.09). The number of patients referred to orthopaedics and listed for surgery fell from 46% in 2022 to 38% in 2023 and then to 35% in 2024. There was no difference between the year cohorts for people referred back to see a surgeon by their GP after APP consultation. The surgeons saw more patients ready for surgery, in that patients referred in 2023–2024 were 1.9 times more likely to be listed for surgery than a patient seen in the surgical clinic in 2022 (odds ratio 1.9, chi2 = 6.5, p = 0.011). Wait times analysis incorporated all of the changes that occurred to the health service during the period, since this is an ecological study.
The first round of interviews showed consistently that APP clinical assessment of patients is highly valued. Patients appreciated early advice and interventions; surgeons appreciated filtering of patients. The high quality of surgery was recognised, but all participants noted that waits were unacceptably long, especially for high-risk complex patients unsuitable for elective surgery outsourced to the private hospital and at risk of deterioration. A community-based program that provided assessment, advice and review was recommended. APPs were acknowledged as skilled and appropriate to conduct this clinic, working at top of scope. Mechanisms to escalate deteriorating patients were needed. Several funding models were proposed, but success was felt to depend on access to imaging, ability to refer directly to the orthopaedic list, and quick access to surgeon advice. Good communication with the community to promote allied health interventions prior to considering surgery and for prehabilitation was essential. Facilitating the right patients having responsive access to surgery was essential for an efficient system. Good communication and listening to stakeholder voices are essential effective drivers of practice change.
The second round of interviews evaluating the changes made was synthesised into themes as follows. A responsive system had empowered confidence in self-management for patients. APP clinics were highly regarded by patients and health professionals. An imperative has arisen to expand this model of care to patients with other orthopaedic conditions and to other specialist clinics across the health service. There has been a major improvement for those patients with knee osteoarthritis, and other patients now face inequity in access to care. Barriers to expanding the successful model include training sufficient APPs to resource APP clinics. The program for knee osteoarthritis relied on strong community allied health programs available as a non-surgical pathway, but such programs do not exist for problematic foot or shoulder conditions with long delays to consultation. Participants told us that community health services need resourcing to meet demand, particularly in podiatry and dietetics, where demand is great. Some quick wins were identified, such as utilising the DHR to send notifications to patients on the progress of their referral, and for tracking referrals. There is a widespread request for education in self-management for patients, particularly in pain management. Changes have improved patients’ experience and responsiveness of the system. Stakeholder engagement has been essential to the success of the project, to staying grounded in patient-centred decision-making, and to meeting demands within resource priorities and constraints.
Costs to patients, including only out-of-pocket costs, ranged from $5,329 to $83 in 6 months (median $1,355, mean $1,824, SD 1,421). Total costs per day ranged from $16.09 to $0.45 (median $7.42 per day, mean $7.98 per day, SD 4.63). Total costs comprised direct costs of $921 (median), and indirect costs of $233 (median) over 6 months. There were no relationships confirmed between financial stress and costs, income category or quality of life metrics. This study is limited by its small sample size, but given the absence of more recent data, this information provides cost estimates for subsequent economic modelling.
Economic evaluation using the Markov chain to model costs to the health sector and patients found that Wait 2 was a key determinant in the costs and benefits of knee osteoarthritis care for public patients. Policy changes to increase resources to the APP clinic and screen all patients with knee osteoarthritis will direct patients to care earlier. Reduced Wait 2 time and earlier direction to care pathways that exhaust conservative care for public patients with knee osteoarthritis decrease public healthcare costs by approximately 36% and indirect patient costs by 24%. It is reasonable to expect that such significant changes will affect the relative demand for, and supply of, knee osteoarthritis care in both the public and private sectors.
An optimisation modelling platform (GAMS, general algebraic modelling system) was used to find (solve for) optimal care solutions in response to a user-defined objective function. The objective function was set to maximise Knee Osteoarthritis Outcome Scores for patients, reflecting outcomes important to patients and their function. Final modelling will be available for the next report.
Conclusions
Very positive changes may be attributed to an increased proportion of people with knee osteoarthritis being seen by APPs, to DHRs reducing the risk of lost referrals, to the availability of community exercise and education programs and to compliance with the clinical standards for management of knee osteoarthritis. Care has improved for patients with these improved pathways.
There is now an urgent imperative to expand this model of care to patients with other conditions in orthopaedics and to other specialist clinics across CHS, where it has been identified that advanced clinical practitioners would benefit from patients’ elevated access to care.
Key recommendations
Recommendations arising from this project are based in the qualitative and quantitative evaluation of the project. The CHS is recommended to:
Monitor and report on wait times and the impact of waiting
1. Be accountable for wait times for patients. Wait times should be monitored and reported. Develop a report in EPIC-DHR that will report on wait times for specialist clinics.
2. Adopt the clinically recommended timeframes (AIHW, 2022) for specialist clinics.
3. Embed in EPIC-DHR patient-reported outcomes measures. Good planning for care is based in sound data, and to embed patient-centred principles both consumer engagement and patient-reported outcomes are required. Otherwise, the impact of changes is not measured.
Expand and resource the APP clinic concept, and monitor the efficacy of that expansion
4. Expand and resource the APP clinic to see patients with other conditions in orthopaedic clinics.
5. Adopt clinically recommended timeframes for APP clinics.
6. Support resourcing of APPs to see Category 2, not only Category 3 urgency patients.
7. Commit to exploring expanding the APP concept to other specialist clinics.
8. Develop agreements with specialists to mentor and communicate regularly with APPs.
Improve cross-sector communication
9. Carry out the planned review of the CHN Health Pathways for GPs to refer to Canberra Hospital orthopaedic clinics.
10. Provide information via CHN that will assist GPs to refer to CHS Community Care services.
Communicate with patients about wait times
11. Provide simple phone text communication with patients about their waiting position.
Expand the advanced clinical practitioner workforce
12. Train more advanced clinical practitioners.
13. Address gaps in training pathways for advanced clinical practitioners.
14. Address issues in recruitment of advanced clinical practitioners.
Provide CHS Community Care health services with sufficient resources
15. CHS Community Care services need increased resourcing to provide the services that will: (1) meet the demand of patients living with complex chronic conditions requiring allied health services, and (2) to take the strain from specialist clinics for treatment of those chronic conditions where evidence shows allied health interventions can be most effective.
16. Address barriers to GPs referring patients to Community Care. My Aged Care, Central Health Intake and long wait times all present barriers to GP referral.
17. Develop services in Community Care to meet emerging demand. This may include implementing needs assessment for conditions that impact on patient quality of life, and where management in the community is appropriate and keeps people living effectively in their communities.
18. Develop patient education programs for managing osteoarthritis. Patients clearly asked for education programs to train themselves in self-management. Education can effectively change belief systems for those with osteoarthritis to enable good self-care and less reliance on surgical solutions.
Waiting time between GP referral and consultation by a specialist (known as ‘Wait 2’ time) has not previously been reported in the Australian Capital Territory (ACT), but in other states it can be prolonged. A Canberra Health Service (CHS) internal review in 2020, The Reboot Project, found 1,590 patients awaiting orthopaedic consultation at Canberra Hospital; after 2 years only 38% had been seen, with a mean wait time of 3.6 years. Yet there is excellent evidence, from the ACT and internationally, that advanced practice physiotherapists (APP) can provide an efficient and accurate diagnostic and screening service. This project was developed in collaboration between University of Canberra (UC), CHS and local and national stakeholders to translate the best evidence from research into clinical practice. In our project, we investigated how implementing strategies aligned with best practice care of knee osteoarthritis could impact the care pathways and wait time for patients referred to see an orthopaedic surgeon in the ACT public health system.
The aim of this project was to sustainably eradicate Wait 2 and ensure that public patients have access to best practice care, including shared decision-making and non-surgical interventions. To unravel and remove access barriers to best practice interventions, we needed to:
1. Use a systems approach to implement an expert review that was responsive, cost-effective and followed best practice interventions.
2. Establish strong collaboration between consumers, primary health care, public orthopaedic triage and surgeons, and across public and private sectors.
3. Develop pathways to ensure patients have knee replacement surgery at the right time.
Method
A knowledge translation approach was taken, including qualitative, quantitative and economic analyses. We gathered evidence to determine best practice and used collaborative strategies for decision-making guided by deliberative democratic principles. The governance model of this project included the project executive, whole of team meetings (investigators, project manager and Trauma and Orthopaedic Research Unit staff), a steering committee (including stakeholders and consumers) and working parties, variously including academic team members, CHS members, health professionals, stakeholders and consumers. Evaluation for the knowledge translation approach included quantitative, qualitative and economic analyses.
We gathered baseline data on waiting times and patient and stakeholder experiences to identify issues, barriers and enablers to implementation of best practice in March 2023. Waiting times were measured for patients with a new referral for knee osteoarthritis and those already waiting for a consultation between 1 March and 30 September for baseline capture in 2022, then each year’s cohort in 2023 and 2024. Characteristics of the cohorts, wait time and pathways – either seen by an APP, a surgeon or both – and the outcome of those visits were analysed for predictive factors.
Interviews, conducted by UC academic members Angie Fearon and Jennie Scarvell, were recorded, transcribed and de-identified. Member checking of emerging themes and quotes resulted in some requests for revision or redaction by participants. Four investigators used thematic analysis, based in phenomenology, against a framework to organise the findings based on the aims of the project: to understand what is working well, what needs improvement, what a model of care would look like, and the barriers and enablers to implementation of that model of care. Participants were drawn through purposive sampling, and included patients (n = 6), primary care practitioners in general practice (GPs) (n = 4) and other primary care (n = 3), surgeons and registrars (n = 6), physiotherapists in the community, acute service and private care (n = 5), and the CHS Executive (n = 5).
Changes to the healthcare service during the period included those implemented by CHS as part of the implementation working party discussions and those serendipitously occurring as part of IT improvements in CHS. Acute care physiotherapy increased resources to the APP clinic so that more patients with knee osteoarthritis could be seen (from 0.8 to 1.5 FTE), connections with community osteoarthritis and obesity programs were streamlined, CHS Community Care expanded the availability of the hip and knee osteoarthritis education and exercise program GLA:D (Good Living with osteoArthritis: Denmark) (Barton et al., 2021; Roos et al., 2018) and several stakeholder engagement activities were conducted. Serendipitously, EPIC Digital Health Record (DHR) was established in November 2022, the HealthLink e-referral system was upgraded, and CHS Quality and Safety initiated the Osteoarthritis of the Knee Clinical Care Standard for knee osteoarthritis.
We evaluated the wait times measured for the 2023 and 2024 cohorts and the pathways for patients. To evaluate project impact, we held further interviews and focus groups in 2023 and 2024. Participants were invited from patient (n = 9), GP (n = 4), physiotherapy (n = 5), surgeon and registrar (n = 5) and health executive groups (n = 5). Three researchers used thematic analysis, based in phenomenology, to derive themes against the questions outlined above, with the addition of ‘what changes have you noticed?’
To assess the economic impact of waiting, and the economic considerations and decisions that influence current and future decisions, we conducted three tasks:
1. To calculate the costs to patients of living with osteoarthritis, using the Canadian Cost to Patients Questionnaire, 16 participants collected data for 6 or 12 months on out-of-pocket costs incurred.
2. To evaluate the costs of the three different patient pathways and outcomes, we modelled them using a Markov chain. Patients could either be seen in the APP clinic; be seen in APP clinic and then referred to a surgeon; or wait to see a surgeon. Their outcomes could be discharge; referral to community programs; or total knee replacement. Costs and the likelihood of successful outcomes were built into the model.
3. To describe optimal pathways and decisions and to inform policy, we fed information from the Markov model and from GLA:D outcomes data into a general algebraic model of optimising pathways and decisions. This work will be reported at the end of 2025.
Key findings
Compared to 2022, wait times to see a surgeon were 0.14 times shorter in 2023 and 0.10 times shorter in 2024. The waiting time improved from 50% of patients seen within 114 days in 2022 to within 45 and 46 days in 2023 and 2024 respectively, and from 90% seen within 1,248 days to within 91 and 84 days respectively. The proportion of patients seen in the APP clinic increased from 20% in 2022 to 81% in 2023 and 76% in 2024. Patients seen in the APP clinic risked fewer delays than those seen only in the surgical clinic (APP clinic incidence rate ratio [IRR]: 0.55; 95%CI: 0.43, 0.72; and if seen in both APP and surgical clinics IRR: 0.54; 95%CI:0.41, 0.70). Patients in 2023 and 2024 had reduced risk of extended wait times to see a surgeon (adjusted odds ratio [AOR]: 0.11; 95% CI: 0.04, 0.31; AOR: 0.02; 95% CI: 0.004, 0.09). The number of patients referred to orthopaedics and listed for surgery fell from 46% in 2022 to 38% in 2023 and then to 35% in 2024. There was no difference between the year cohorts for people referred back to see a surgeon by their GP after APP consultation. The surgeons saw more patients ready for surgery, in that patients referred in 2023–2024 were 1.9 times more likely to be listed for surgery than a patient seen in the surgical clinic in 2022 (odds ratio 1.9, chi2 = 6.5, p = 0.011). Wait times analysis incorporated all of the changes that occurred to the health service during the period, since this is an ecological study.
The first round of interviews showed consistently that APP clinical assessment of patients is highly valued. Patients appreciated early advice and interventions; surgeons appreciated filtering of patients. The high quality of surgery was recognised, but all participants noted that waits were unacceptably long, especially for high-risk complex patients unsuitable for elective surgery outsourced to the private hospital and at risk of deterioration. A community-based program that provided assessment, advice and review was recommended. APPs were acknowledged as skilled and appropriate to conduct this clinic, working at top of scope. Mechanisms to escalate deteriorating patients were needed. Several funding models were proposed, but success was felt to depend on access to imaging, ability to refer directly to the orthopaedic list, and quick access to surgeon advice. Good communication with the community to promote allied health interventions prior to considering surgery and for prehabilitation was essential. Facilitating the right patients having responsive access to surgery was essential for an efficient system. Good communication and listening to stakeholder voices are essential effective drivers of practice change.
The second round of interviews evaluating the changes made was synthesised into themes as follows. A responsive system had empowered confidence in self-management for patients. APP clinics were highly regarded by patients and health professionals. An imperative has arisen to expand this model of care to patients with other orthopaedic conditions and to other specialist clinics across the health service. There has been a major improvement for those patients with knee osteoarthritis, and other patients now face inequity in access to care. Barriers to expanding the successful model include training sufficient APPs to resource APP clinics. The program for knee osteoarthritis relied on strong community allied health programs available as a non-surgical pathway, but such programs do not exist for problematic foot or shoulder conditions with long delays to consultation. Participants told us that community health services need resourcing to meet demand, particularly in podiatry and dietetics, where demand is great. Some quick wins were identified, such as utilising the DHR to send notifications to patients on the progress of their referral, and for tracking referrals. There is a widespread request for education in self-management for patients, particularly in pain management. Changes have improved patients’ experience and responsiveness of the system. Stakeholder engagement has been essential to the success of the project, to staying grounded in patient-centred decision-making, and to meeting demands within resource priorities and constraints.
Costs to patients, including only out-of-pocket costs, ranged from $5,329 to $83 in 6 months (median $1,355, mean $1,824, SD 1,421). Total costs per day ranged from $16.09 to $0.45 (median $7.42 per day, mean $7.98 per day, SD 4.63). Total costs comprised direct costs of $921 (median), and indirect costs of $233 (median) over 6 months. There were no relationships confirmed between financial stress and costs, income category or quality of life metrics. This study is limited by its small sample size, but given the absence of more recent data, this information provides cost estimates for subsequent economic modelling.
Economic evaluation using the Markov chain to model costs to the health sector and patients found that Wait 2 was a key determinant in the costs and benefits of knee osteoarthritis care for public patients. Policy changes to increase resources to the APP clinic and screen all patients with knee osteoarthritis will direct patients to care earlier. Reduced Wait 2 time and earlier direction to care pathways that exhaust conservative care for public patients with knee osteoarthritis decrease public healthcare costs by approximately 36% and indirect patient costs by 24%. It is reasonable to expect that such significant changes will affect the relative demand for, and supply of, knee osteoarthritis care in both the public and private sectors.
An optimisation modelling platform (GAMS, general algebraic modelling system) was used to find (solve for) optimal care solutions in response to a user-defined objective function. The objective function was set to maximise Knee Osteoarthritis Outcome Scores for patients, reflecting outcomes important to patients and their function. Final modelling will be available for the next report.
Conclusions
Very positive changes may be attributed to an increased proportion of people with knee osteoarthritis being seen by APPs, to DHRs reducing the risk of lost referrals, to the availability of community exercise and education programs and to compliance with the clinical standards for management of knee osteoarthritis. Care has improved for patients with these improved pathways.
There is now an urgent imperative to expand this model of care to patients with other conditions in orthopaedics and to other specialist clinics across CHS, where it has been identified that advanced clinical practitioners would benefit from patients’ elevated access to care.
Key recommendations
Recommendations arising from this project are based in the qualitative and quantitative evaluation of the project. The CHS is recommended to:
Monitor and report on wait times and the impact of waiting
1. Be accountable for wait times for patients. Wait times should be monitored and reported. Develop a report in EPIC-DHR that will report on wait times for specialist clinics.
2. Adopt the clinically recommended timeframes (AIHW, 2022) for specialist clinics.
3. Embed in EPIC-DHR patient-reported outcomes measures. Good planning for care is based in sound data, and to embed patient-centred principles both consumer engagement and patient-reported outcomes are required. Otherwise, the impact of changes is not measured.
Expand and resource the APP clinic concept, and monitor the efficacy of that expansion
4. Expand and resource the APP clinic to see patients with other conditions in orthopaedic clinics.
5. Adopt clinically recommended timeframes for APP clinics.
6. Support resourcing of APPs to see Category 2, not only Category 3 urgency patients.
7. Commit to exploring expanding the APP concept to other specialist clinics.
8. Develop agreements with specialists to mentor and communicate regularly with APPs.
Improve cross-sector communication
9. Carry out the planned review of the CHN Health Pathways for GPs to refer to Canberra Hospital orthopaedic clinics.
10. Provide information via CHN that will assist GPs to refer to CHS Community Care services.
Communicate with patients about wait times
11. Provide simple phone text communication with patients about their waiting position.
Expand the advanced clinical practitioner workforce
12. Train more advanced clinical practitioners.
13. Address gaps in training pathways for advanced clinical practitioners.
14. Address issues in recruitment of advanced clinical practitioners.
Provide CHS Community Care health services with sufficient resources
15. CHS Community Care services need increased resourcing to provide the services that will: (1) meet the demand of patients living with complex chronic conditions requiring allied health services, and (2) to take the strain from specialist clinics for treatment of those chronic conditions where evidence shows allied health interventions can be most effective.
16. Address barriers to GPs referring patients to Community Care. My Aged Care, Central Health Intake and long wait times all present barriers to GP referral.
17. Develop services in Community Care to meet emerging demand. This may include implementing needs assessment for conditions that impact on patient quality of life, and where management in the community is appropriate and keeps people living effectively in their communities.
18. Develop patient education programs for managing osteoarthritis. Patients clearly asked for education programs to train themselves in self-management. Education can effectively change belief systems for those with osteoarthritis to enable good self-care and less reliance on surgical solutions.
| Original language | English |
|---|---|
| Place of Publication | Australia |
| Publisher | University of Canberra |
| Commissioning body | HCF Foundation Translation Grant |
| Number of pages | 205 |
| Publication status | Published - 27 Jun 2025 |
