Factors influencing prosthesis selection and variation: a survey of orthopaedic surgeons in Australia.

doi:10.21203/rs.3.rs-3439378/v1

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Research Article

Factors influencing prosthesis selection and variation: a survey of orthopaedic surgeons in Australia.

https://doi.org/10.21203/rs.3.rs-3439378/v1

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Background: There is increasing demand for knee and hip arthroplasties, with considerable health system cost implications. Despite much of the surgical costs relating to the particular prosthesis used, little is known about which factors are most influential for surgeon decision-making, nor is it clear what level of variation may be warranted for clinical reasons.

Materials and Methods: A three-stage study was conducted to address the dual objectives of: a) identify factors influencing prosthesis selection for total hip arthroplasty (THA) and total knee arthroplasty (TKA); and b) develop a working definition for what could be considered unwarranted variation in THA and TKA implant selection. A questionnaire was developed and piloted with input from orthopaedic surgeons. This cross-sectional survey was conducted with orthopaedic surgeons across Australia, followed by an expert panel to finalise the working definition.

Results: Revision rates, familiarity with implant, and implant quality, were factors considered a priority when choosing a prosthesis, whilst other factors including cost, were reported to have limited influence. Technological advancement and revision rates were influential for past changes of prosthesis, and strong clinical evidence for future changes. Consensus was reached on a working definition of unwarranted variation that focused on implants with revision rates of 20% or higher compared to published benchmarks. Use of multiple cost thresholds was recommended for defining both narrow and broad definitions of unwarranted variation.

Conclusion: Findings from this study provide valuable insights into the decision-making process for prosthesis selection, as well as what surgeons believe might constitute unwarranted variation. This information can be used to progress our understanding of the magnitude and impact of this variation through use of the suggested unwarranted variation definitions, as well as inform strategies to address unwarranted variation in prosthesis selection.

Level of evidence: Non-randomised cross-sectional survey – Level 3.

Trial registration: Not applicable.

Orthopedic Surgery

Prosthesis

Arthroplasty

unwarranted variation

surgeon

selection

decision-making

cost

The number of total hip arthroplasty (THA) and total knee arthroplasty (TKA) surgeries are increasing globally and particularly across OECD countries (1). High-income countries, including the United States, are currently experiencing very high incidence rates per 100,000 for both THA and TKA, while other high-income countries like Australia are expecting rates to double in the coming decades (2–4). In the Australian context, where the present study was conducted, projected costs are expected to reach $AUD1.38B for TKA, and $AUD953M for THA, respectively by the year 2030 (5), with the cost of the implant itself averaging approximately 60% of the total expenditure (6, 7).

In high-income countries, prosthesis selection is largely driven by orthopaedic surgeons, but little is known about what factors influence their decision making. A recent systematic review to identify the factors influencing surgeons’ prosthesis selections for knee and hip arthroplasty in high-income countries highlighted a range of factors including patient anatomy, familiarity with implant, implant quality, and even the friendliness of the sales representative are considered by surgeons (8). However, due to the small number and heterogeneity of studies on this topic, no strong conclusions about the relative importance of these factors were articulated.

Better understanding of factors influencing prosthesis selection is needed to support the development and implementation of strategies to improve patient outcomes and reduce unwarranted variation. Unwarranted variation that is unrelated to clinical need, evidence or patient preferences can lead to poorer outcomes for patients, or other detrimental effects, including higher cost or wasted healthcare resources (9, 10). The dual objectives for this study were to: a) identify factors influencing prosthesis selection by surgeons for THA and TKA; and b) develop a working definition for what could be considered unwarranted variation in implant selection for THA and TKA. This working definition will be used to inform an economic analysis of unwarranted variation.

Study design

Informed by our recently completed scoping review of factors influencing prosthesis selection (8), we undertook a three-stage mixed methods study to address the objectives. The first stage comprised i) interviews with orthopaedic surgeons to inform the questionnaire design, and ii) piloting the questionnaire. The second stage was conducting a cross-sectional survey with orthopaedic surgeons in Australia. The results of the survey were then reviewed by the expert panel in stage 3, to consolidate a working definition of unwarranted variation for implant selection for THA and TKA.

Stage 1: Development and pilot of questionnaire

Key informant interviews with three orthopaedic surgeons were used to explore the findings of the systematic review and develop a questionnaire for surgeons within the Australian context. Key informant sampling was used, with participants for the interviews and pilot recruited via email through existing professional networks. A semi-structured interview guide was used to explore factors influencing prosthesis selection and what constitutes unwarranted variation (Supplementary File 1). Online piloting of the questionnaire was undertaken to review question wording and structure to ensure clinical relevance, as well as user-friendliness for participants.

Analysis and question development

Initial interviews were audio recorded and transcribed. Framework analysis of the interview transcripts were undertaken using the seven-step process of transcription, familiarisation with the data, coding, framework development, applying the framework, charting the data, and interpreting the data for meaning (11). The initial framework was based on inductive coding and deductive coding relating to the factors derived from the systematic review. Codes were grouped to create themes, then used to formulate the questions. Multiple iterations of the draft questionnaire were shared, both electronically and in-person, with available interview participants and the research team to refine question content, phrasing, and structure of the questionnaire. To pilot the penultimate questionnaire, an orthopaedic surgeon, a health economist, and a healthcare administrator were emailed a link to the questionnaire, with feedback emailed to the study’s Chief Investigator.

Final questionnaire

The final questionnaire had six sections: respondent characteristics, level of autonomy, factors influencing prosthesis selection, changing prosthesis selection, registry results, and unwarranted variation. It contained between 15 to 28 questions, depending on responses. The questionnaire used branching, whereby the number and type of questions depended on whether participants indicated they were a consultant or a registrar; whether they undertook THA, TKA or ‘both’ surgeries; and whether they worked in a public hospital, private hospital, or both. For example, if a respondent indicated that they only conducted THA, then no subsequent questions relating to TKA would be shown. There were no required fields and respondents could choose to not answer any of the questions.

Section 1: Respondent characteristics

The questionnaire was built in Qualtrix and included several questions to describe respondent characteristics, including age and number and location of surgeries performed.

Section 2: Level of autonomy and knowledge of cost

Both the systematic review and the interviews highlighted that there needed to be questions relating to the level of autonomy that surgeons have in relation to prosthesis selection in their context, as well as their awareness of the cost of the prostheses they use, to support the interpretation of results, which were both added to the final survey.

Section 3: Factors influencing prostheses selection

Twelve factors derived from the systematic review and interviews were included in the questionnaire. Pilot and interview participants suggested selecting the top five factors influencing selection would be sufficient to gain useful insight, without being too onerous.

Section 4: Changing prosthesis selection

Interview participants discussed the likelihood that surgeons might select prostheses, and their associated suppliers, based on what they had been trained on. Therefore, questions were included around whether surgeons changed prosthesis in the past, the reasons for doing so, and potential reasons for future changes.

Section 5: Registry results

Australia has a national joint registry which publishes revision rates for implants and combinations of implants, including individual surgeon level data. Questions on the use of registry data were also included.

Section 6: Unwarranted variation

Three questions about unwarranted variation were included using 5-year and 10-year revision rates and cost thresholds informed by national reporting measures and interview data.

Stage 2: Survey of orthopaedic surgeons

Participants

A cross-sectional survey was conducted with:

(1) Orthopaedic surgeons who undertake hip and/or knee surgery in Australia and are registered on the email mailing list of the Arthroplasty Society of Australia, a subspecialty group of the Australian Orthopaedic Association.

(2) Orthopaedic registrars, both training and non-training.

Recruitment

Survey participants were contacted via email sent from the Arthroplasty Society of Australia that contained a link to the questionnaire. The Arthroplasty Society of Australia has 121 members on its mailing list. Twenty registrars were emailed a link to the questionnaire through informal clinical networks, with the request to share with other registrars, whether they were training or non-training. The questionnaire remained active for three months to allow time for completion.

Analysis

The questionnaire responses were analysed using descriptive statistics and use of a numerical score to identify the highest priority factor. For this prioritisation exercise, respondents were asked to select their top five factors from a list of 12 that they consider when selecting an implant. We assigned a numerical score ranging from 5 (highest priority) to 1 (fifth priority), with all other non-prioritised factors receiving a score of 0. We then calculated the mean score for each factor, with higher scores providing an indication of factors that were perceived to have greater importance. All free text comments provided, have been reported.

Survey Results

Respondent characteristics

The survey was completed by 59 participants (50 consultants and 9 registrars) with a response rate of 41% and 45% respectively. Respondent characteristics are outlined in Table 1, noting respondents from all Australian states and territories, except the Northern Territory, and a 75–25% split between those practicing in metropolitan compared to regional hospitals. Most respondents practiced in both public and private hospitals (56% n = 33), with the remainder split evenly between public only and private only. Over half the respondents noted that they were either 15–20 years (n = 12, 20%) or 20 + years (n = 20, 34%,) post orthopaedic specialisation training.

Table 1

Respondent Characteristics
Q1: Which state or territory do you primarily work in?
State or territory	# of responses	% of total (n = 59)
QLD	20	34%
NSW	19	32%
VIC	7	12%
SA	5	8%
TAS	4	7%
WA	2	3%
ACT	1	2%
NT	0	0%
Missing	1	2%
Q2: What setting do you primarily work in?
Setting	# of responses	% of total (n = 59)
Metropolitan	44	75%
Regional	15	25%
Rural or remote	0	0%
Q3: Are you currently a:
Professional role	# of responses	% of total (n = 59)
Consultant orthopaedic surgeon	50	85%
Fellow	0	0%
Non-training registrar	5	9%
Training registrar	4	7%
Q4: How many years post training?
Year range	# of responses	% of total (n = 59)
0-5years	11	19%
6–10 years	5	9%
11–15 years	2	3%
15-20years	12	20%
20 + years	20	34%
Missing	9	15%
Q5: What is your age group?
Age range	# of responses	% of total (n = 59)
20–34	9	15%
35–49	19	32%
50–64	26	44%
65+	4	7%
Prefer not to say	1	2%
Q6: Do you conduct (select all that apply):
Surgery type	# of responses	% of total (n = 59)
THA only	1	2%
TKA only	5	8%
Both THA and TKA	53	90%
Surgery type	# of responses	% of total (n = 59)
Total knee replacement*	58	98
Total hip replacement**	54	90
If selected include Q7 and enable Q15-18 *If selected include Q8, also enable Q19-21
Q7: How many total hip replacements do you carry out per year?
THR range	# of responses	% of total (n = 54)
Less than 20	11	20%
20–50	7	13%
50–100	18	33%
100+	18	33%
Q8: How many total knee replacements do you carry out per year?
TKR range	# of responses	% of total (n = 58)
Less than 20	8	14%
20–50	10	17%
50–100	20	34%
100+	20	34%
Q9: Do you practice in (select all that apply):
Hospital type	# of responses	% of total (n = 59)
Public only	13	22%
Private only	13	22%
Both public and private	33	56%
Hospital type	# of responses	% of total (n = 59)
Public hospital	46	78%
Private hospital	46	78%

Table 1: Respondent characteristics

Level of autonomy and knowledge of cost

For those practicing in private hospitals, all respondents noted full autonomy over prosthesis selection. Approximately half of the consultants practicing in public hospitals reported full autonomy (51%, n = 19), closely followed by departmental consensus (46%, n = 17), with a single participant noting limited input. When combined with registrar responses, departmental consensus became the most selected response overall (n = 21, 46%) for those practicing in public hospitals. Free text comments highlighted that several consultants with full autonomy in public hospitals noted some hospital processes to minimise variation (that were not enforced), whilst registrar choices were directed. Further, the majority of respondents (n = 51, 88%) either knew the cost of the implant/s they use most often (n = 19, 32%) or knew the approximate price range (+/- $1000) (n = 32, 54%).

Table 2: Level of autonomy and cost awareness

Table 2

Level of autonomy and knowledge of cost
Q10: In the public setting, what level of autonomy over choice of implant do you have?
Autonomy level	Consultant orthopaedic surgeon (n = 37)	Others (n = 9)		Total (n = 46)
Full autonomy	19 (51%)	0 (0.0%)		19 (41%)
Departmental consensus	17 (46%)	4 (44%)		21 (46%)
Limited input	1 (3%)	3 (33%)		4 (9%)
Other	0 (0.0%)	2 (22%)		2 (4%)
Free text responses: Full autonomy “Department attempts to use similar implants to reduce cost… but there is no pressure to use something else” “Full autonomy within [state] tender, which most companies are. Needs to be an implant with some track record, but essentially full autonomy”. “Full autonomy, but free to choose any prosthesis with a threshold price”. “Have not tested the boundaries on my full autonomy”. “Implant contract with one large company is threshold based. Although autonomous in choice as there is no pressure to switch to this company” Departmental consensus “Choice of two determined by departmental consensus”. “Patients over 75 have all cemented implant. Have departmental rules regarding over costs for implant” “[company] agreement in public for hip and knee arthroplasty” “No restrictions for revisions. Two primary THR and two primary TKR choices available for use” “Implant tender tied to robot use!!” Limited input/ Other “Do what I’m told” “Implant selected by consultant”
Q11: In the private setting, what level of autonomy over choice of implant do you have?
Autonomy level	# of responses	% of total (n = 46)
Full autonomy	46	100
Departmental consensus	0	0
Limited input	0	0
Free text responses: “Required to be in top 10% registry survivorship at minimum 5 years”
Q12: Do you know the cost of the implant/s you use most often?
Knowledge level		# of responses	% of total (n = 59)
Yes, I know the cost of the implant/s I use		19	32
I know the approximate price range (+/- $1000)		32	54
No, I am not really sure of the cost of the implant/s I use		3	5
Missing (none selected)		5	9

Factors influencing prostheses selection

The factor selected the most often as surgeons’ first priority was revision rate (n = 20). The most frequently “top 5” factors, regardless of position, were familiarity with implant and revision rates (selected 40 times each). When factor ratings were used to provide a relative indicator of perceived factor importance, the highest ranked factor was revision rate (3.6), followed by familiarity of implant (2.6) and implant quality (2.2). Cost, availability of implant at hospitals, and length of time in surgery were the lowest ranked factors. Prioritisation of factors is outlined in Table 3.

Table 3

Factor Ranking
Q13: Please select your top 5 factors you consider when selecting an implant. Click on the item and drag and drop into the boxes 1–5 (1 = top priority, 2 = second priority, etc).	Mean score Max = 5, Min = 0
Revision rate	3.6
Familiarity with implant	2.6
Implant quality	2.2
Patient post-op functionality	1.6
Ease of use in theatre	1.2
Education and support provided with implant	1
Patient age	0.9
Reason for replacement (e.g.) osteoarthritis, trauma, inflammatory arthritis	0.7
Relationship with the implant supplier/ company	0.6
Implant cost	0.5
Type/brand of implant available at the hospital where I work	0.2
Length of time in surgery	0.1

Table 3: Prosthesis selection factor ranking

Changes to prostheses selection

Questions related to changes in prosthesis selection were split into those who conduct THA (n = 44) and those who conduct TKA (n = 49), with some respondents answering questions in both categories. Factors influencing previous changes to implant selection and expected future reasons are summarised in Figs. 1 and 2, and Supplementary Table 1.

Total hip replacement (n = 44)

Post training, the number of different THA implants used had a mixed spread, with more than five different implants the most common response (25%, n = 11). Most (61%, n = 30) respondents had changed away from at least one of the implants they used during training. Technological advancement (67%, n = 18), followed by registry data (56%, n = 15) were the most commonly selected reasons, with the least selected being cheaper alternatives providing similar results (11%, n = 3). For future changes, of the 15 out of 53 THA respondents that answered the question, strong clinical evidence for or against (93%, n = 14) was the most commonly selected response.

Total knee replacement (n = 49)

Post training, the number of different TKA implants used was equally split by one or two implants respectively (22%, n = 11 each), followed by more than five different implants (18%, n = 9). 61% of respondents (n = 27) had changed away from at least one of the implants they used during training. Registry data (67%, n = 20) followed by technological advancement (60%, n = 18) were the most commonly selected, with cheaper alternatives providing similar results (7%, n = 2) the least common. For future changes, of the 17 out of 58 TKA respondents that answered the question, strong clinical evidence for or against (77%, n = 13) was chosen.

Figure 1: Factors influencing decision – THA

Figure 2: Factors influencing decision – TKA.

Registry results

Just over half of consultant participants checked their results once a year (54%, n = 27), with another 32% (n = 16) checking their own results multiple times each year. Two consultant respondents (4%) indicated that they had never checked registry results. When asked how important joint registry outcomes were to them, more than 75% of respondents indicated extremely or very important (extremely important 39% n = 23, very important 37.3% n = 22).

Table 4: Joint registry data use

Table 4

Joint Registry Use
Q24: How often do you check your individual registry results?*
Support		# of responses		% of total (n = 50)
Multiple times a year		16		32
Once a year		27		54
Once every 2–3 years		2		4
Once every 3–5 years		1		2
Once every 5 + years		0		0
Never		2		4
Missing		2		4
Q25: How important are joint registry outcomes to you?
Importance level	Consultant orthopaedic surgeon (n = 50)		Others (n = 9)		Total (n = 59)
Extremely important	19 (38%)		4 (44%)		23 (39%)
Very important	20 (40%)		2 (22%)		22 (37%)
Moderately	7 (14%)		0 (0%)		7 (12%)
Slightly important	2 (4%)		0 (0%)		2 (3%)
Not at all important	2 (4%)		0 (0%)		0 (0%)
Missing	19 (38%)		3 (33)		5 (9%)
*NB: Q24 was answered by those who selected consultant only.

Unwarranted variation

Cost of prostheses

Participants were asked about unwarranted variation in relation to prosthesis cost (Unwarranted variation summarised in Fig. 3 and supplementary Table 2). Answers were mixed, with 27% (n = 16) indicating that a prosthesis costing 20% more than an equivalent was unwarranted variation, but this was closely followed by 24% (n = 14) indicating that a prosthesis costing 10% more than an equivalent was unwarranted variation. This question was not answered by 14% (n = 8) of participants. The distribution of responses was broadly consistent between consultants and registrars.

Five-year revisions

Fifty-eight percent of respondents (n = 34) indicated that a ‘more than 20%’ increase in five-year revision rates compared to equivalent prostheses constitutes unwarranted variation. This option was selected by 62% (n = 31) of consultants and a third (33%) of registrars. However, nearly a third (29%, n = 17) of respondents selected a lower threshold. Of note, 13.6% of surgeons (n = 8) did not answer this question.

10-year revisions

More than 20% increase in 10-year revision rates was also the most commonly selected response for 10-year revision rates, with 59% (n = 35) selecting this overall, comprising 62% (n = 31) and 44% (n = 4) of consultants and registrars, respectively. Similar to the five-year revision rates, 27% (n = 16) of respondents selected a lower threshold, with the same number of respondents (n = 8) not selecting a threshold at all.

Figure 3: Unwarranted variation

Stage 3: Panel discussion to define unwarranted variation

Survey results were reviewed by a panel of two orthopaedic surgeons and a health economist with expertise in unwarranted variation to consolidate a working definition of unwarranted clinical variation. This definition will be used as part of an economic evaluation using current prosthesis use data. Key outcomes from the panel meeting are summarised below.

1. Revision rates are a key indicator, which should form part of the working definition.

2. Revision rates of 20% or higher than an agreed benchmark rate at 5-year and 10-year intervals were suitable for a working definition. It was noted by participants 20% is similar to international benchmarking.

3. Uncertainty would always be present in estimates of unwarranted variation, for example, if derived from registry data revision rates, confidence intervals could be used for defining conservative narrow and broad definitions of unwarranted variation.

4. Cost is a useful indicator of unwarranted variation. However, given the mixed response in the survey, the panel suggested that multiple cost thresholds, along with revision rates, should be used within the working definition.

5. There was some discussion about other potentially confounding factors, including cemented vs uncemented, or age of implant recipients, and how this ought to be accounted for in future studies investigating unwarranted variation in this field.

This study demonstrates that the most influential factors for surgeon decision making in relation to prosthesis selection include revision rate, familiarity with implant, and implant quality, while factors including cost have limited influence. Similarly, technological advancement and revision rates were influential for past changes of prosthesis, and strong clinical evidence was reported to be influential for future changes. A working definition of unwarranted variation was agreed upon, which focused on implants with revision rates of at least 20% higher than published benchmarks with multiple cost thresholds.

National registries in Australia and internationally provide comprehensive data on revision rates for both THA and TKA implants, yet there is continued use of implants with no long term data, or with considerably higher revision rates (12). Previous research has also demonstrated a large disparity in revision rates between public and private hospital rates in Australia (13). Higher revision rates in private hospitals were shown to be largely related to differences in implant selection, with revision rates equalising where data was restricted to high performing implants only (13). Given that revision rates were demonstrated in this study as the key deciding factor when selecting an implant, providing a working definition on what constitutes potential unwarranted variation that includes a threshold for revision rates is a key outcome that can be applied in future research.

Cost was not highlighted in this study as a major deciding factor for most surgeons. Given the majority of respondents perceived that they knew the cost or approximate cost of the implants they use most often, the minimal role played by cost in decision making does not appear to be related to cost awareness. This high level of cost awareness is similar to that found by Sharkey et al.(14), with the majority of respondents in both studies having a high level of control over their implant selection. The authors of that study also noted that surgeons are likely to continue selecting the same implant, even if there is a more affordable implant with acceptable clinical outcomes (14). Given our results and that of previous studies, future strategies to address unwarranted variation must move beyond mere awareness raising.

Our finding regarding familiarity with implant being a key driver of prosthesis selection warrants further investigation. Studies have demonstrated that surgical experience and familiarity with other members of the operating team can lead to reduction in theatre time (15, 16), length of stay and 30 day readmission rates (16). One study suggests that surgeons perceived that changing implants and the associated learning curve would adversely affect patients in the short term (14). Conversely, another study found that firm preferences for specific implants was a barrier to acquiring competency in a broader range of implants that would better align to the needs of patients (17). Our results further resonate with other research on unwarranted variation which have highlighted the influence of capacity (individual and organisational) and individual preferences (both patient and clinician), as potential reasons for underlying variation, both warranted and unwarranted (9, 18), and the need for further consideration of these factors.

Several considerations that have been reported in previous research, including surgeon’s relationships with implant companies (19, 20), technological aspects (14, 17, 19, 20), or patient fit (14, 17, 19, 20), did not feature as prominently in our study. This may be due to factors being described in more detail in the questionnaire, for example, patient age and reason for replacement are both aspects of patient fit, which may have ranked higher if they were combined. Technological advancement on the other hand was reported in this study as a factor that influenced past changes in prosthesis selection, but not in relation to current decision making. This may align with the perception that surgeons believe there are minimal differences among common prostheses, so improvements would need to be significant before change to an alternate prosthesis would be considered (17).

A strength of this study is the relatively representative sample of consultant orthopaedic surgeons across Australia. However, we did not have a large number of registrars in the sample, and their responses must be interpreted with caution. Despite piloting the questionnaire and aligning the top threshold with current reporting standards, some limitations remained, including a potential ceiling effect of using ‘20% and over’ as the top increment for the unwarranted variation questions (both cost and revision rate). This may have led to the missing data with several participants not selecting a threshold for unwarranted variation based on revision rates (n = 8), or this may be due to the lack of importance placed on this data by some, despite revision rates being the highest ranked factor for prosthesis selection in this study. Furthermore, we did not explicitly define departmental consensus or implant quality within the questionnaire tool itself, which may have resulted in variable interpretation among participants. Reasons for future changes to implant also had missing data for 66% and 65% for THR and TKR respondents respectively. It is unclear as to whether this related to a lack of willingness to consider changing implants in the future, or difficulty making a selection for future decisions. Directly observing revealed preferences for implant selection may provide different outcomes from this survey study, presenting a useful area for future research.

This study highlights several factors that are influential in surgeon decision making in relation to implant choice for THA and TKA. Further, it provides a working definition for unwarranted variation that can be applied in future research and health system strategies to improve patient outcomes and provide better value care.

AUD	Australian dollars
OECD	Organisation for Economic Co-operation and Development
THA	total hip arthroplasty
TKA	total knee arthroplasty

Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Acknowledgements

We would like to thank all those who piloted or completed the survey for your time and expertise.

Ethics approval and consent to participate

Ethical approval for this study was granted by the Queensland University of Technology Human Research Ethics Committee, reference number UHREC-2022-4255. Participant consent for participation in the interviews was obtained in writing. For the survey, consent was provided electronically by selecting ‘agree to consent’ prior to being given access to complete the questions. Consent for the expert panel was provided verbally and recorded with the audio recorder as part of the meeting.

Consent to Publication

Consent to publish was included in all the above consent procedures. All participants that consented to participate, also consented to publish.

Data and materials

The survey data used and/ or analysed during the current study are either provided within the manuscript or supplementary materials, or are available from the corresponding author on reasonable request that has ethical clearance. The transcripts and audio-recordings of the interviews and expert panel are not available in their raw form due to potential re-identifiability given the small sample size, however a summary of the data and further detail on coding is available on reasonable request.

Funding

This work was funded by an unencumbered gift to the Queensland University of Technology from the Medibank Foundation. There was no contribution by the funders to data analysis, interpretation, writing or publication of results.

Author contributions

All authors conceived and designed the study. MJA undertook the interviews and undertook initial coding of the transcripts. Consolidation of themes and development of survey questions was done by MJA, RC, and DB, with the online questionnaire created by SS. Survey data was analysed by SS with results reviewed by all authors. Initial draft was written by MJA and LE. Subsequent drafts were reviewed by all authors and significant intellectual contribution was provided by all. All authors reviewed and agreed on the final manuscript.

Author information

RC and IH are orthopaedic surgeons with extensive experience in hip and knee arthroscopy.

DB, SS, VM, SMM are health economists with an interest in value-based care.

MJA, LE, RH are health services researchers with implementation science, public health and health management background

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Factors influencing prosthesis selection and variation: a survey of orthopaedic surgeons in Australia.

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Abstract

Figures

Introduction

Materials and Methods

Study design

Stage 1: Development and pilot of questionnaire

Analysis and question development

Final questionnaire

Section 1: Respondent characteristics

Section 2: Level of autonomy and knowledge of cost

Section 3: Factors influencing prostheses selection

Section 4: Changing prosthesis selection

Section 5: Registry results

Section 6: Unwarranted variation

Stage 2: Survey of orthopaedic surgeons

Participants

Recruitment

Analysis

Survey Results

Respondent characteristics

Level of autonomy and knowledge of cost

Factors influencing prostheses selection

Total hip replacement (n = 44)

Total knee replacement (n = 49)

Registry results

Unwarranted variation

Cost of prostheses

Five-year revisions

10-year revisions

Stage 3: Panel discussion to define unwarranted variation

Discussion

Conclusion

Abbreviations

Declarations

References

Supplementary Files

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