1271953

research-article2024

JPCXXX10.1177/21501319241271953Journal of Primary Care & Community HealthEubank et al

Advancing Practice in Primary and Community Care—Original Research Article

Development of a Soft Tissue Knee
Clinical Decision-Making Tool for Patients
Presenting to Primary Point-of-Care
Providers in Alberta, Canada

Journal of Primary Care & Community Health
Volume 15: 1–28
© The Author(s) 2024
Article reuse guidelines:
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https://doi.org/10.1177/21501319241271953
DOI: 10.1177/21501319241271953
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Breda H. F. Eubank1 , Tim Takahashi2,3,4, Ryan Shields2,5, Jason Martyn6,
Rachel Xurong Zhao7, Sebastian W. Lackey8, Mel Slomp2,6, Jason R. Werle2,9,
Jill Robert2,6, and Catherine Hui2,10

Abstract
Several barriers exist in Alberta, Canada to providing accurate and accessible diagnoses for patients presenting with acute
knee injuries and chronic knee problems. In efforts to improve quality of care for these patients, an evidence-informed
clinical decision-making tool was developed. Forty-five expert panelists were purposively chosen to represent stakeholder
groups, various expertise, and each of Alberta Health Services’ 5 geographical health regions. A systematic rapid review and
modified Delphi approach were executed with the intention of developing standardized clinical decision-making processes
for acute knee injuries, atraumatic/overuse conditions, knee arthritis, and degenerative meniscus. Standardized criteria
for screening, history-taking, physical examination, diagnostic imaging, timelines, and treatment were developed. This tool
standardizes and optimizes assessment and diagnosis of acute knee injuries and chronic knee problems in Alberta. This
project was a highly collaborative, province-wide effort led by Alberta Health Services’ Bone and Joint Health Strategic
Clinical Network (BJH SCN) and the Alberta Bone and Joint Health Institute (ABJHI).
Keywords
algorithm, clinical care pathway, clinical decision-making, Delphi consensus, soft tissue knee injuries
Dates received: 29 May 2024; revised: 25 June 2024; accepted: 26 June 2024.

Introduction
An estimated 45 000 acute knee injuries occur each year and
require access to primary point-of-care and surgical screening services. Within this group, there are approximately
2500 Albertans who tear the anterior cruciate ligament
(ACL) of their knee each year based on an estimated nominal incidence rate of 30 to 80 injuries per 100 000 persons.1
As such, evidence-informed clinical assessment and management should be initiated within days to weeks after the
injury.2 Several challenges exist in Alberta, Canada, however, to providing accurate and accessible diagnoses in the
traditional medical model.3 First, there is a serious labour
shortage in the health workforce coupled with a high
demand for services.1 The current ratio for patient to provider in Canada is 247 primary care physicians and 3.5
orthopedic surgeons per 100 000 people, respectively.4,5
Combined with the backlog and demands placed on our

health system resulting from the COVID-19 pandemic, subsequent delays in assessment and surgery have resulted.

1

Mount Royal University, Calgary, AB, Canada
Bone & Joint Health Strategic Clinical Network, Edmonton, AB, Canada
3
University of Lethbridge, Lethbridge, AB, Canada
4
Rebound Health Centre Ltd, Lethbridge, AB, Canada
5
University of Calgary Sport Medicine Centre, Calgary, AB, Canada
6
Alberta Health Services Corporate Office, Edmonton, AB, Canada
7
Library Services, Calgary, AB, Canada
8
Alberta Bone and Joint Health Institute, Calgary, AB, Canada
9
University of Calgary, Calgary, AB, Canada
10
University of Alberta, Edmonton, AB, Canada
2

Corresponding Author:
Breda H. F. Eubank, Department of Health & Physical Education, Faculty
of Health, Community, & Education, Mount Royal University, 4825
Mount Royal Gate SW, Calgary, AB T3E 6K6, Canada.
Email: beubank@mtroyal.ca

Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons
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reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open
Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).

2
Second, primary care physicians have limited training in
musculoskeletal (MSK) medicine, whereby the Canadian
medical curriculum dedicates roughly ~3% to MSK education.6,7 Primary care physicians are required to provide a
wide range of services across multiple health conditions
with minimal resources. They have a heavy workload with
high levels of clinical responsibility. Further, lack of confidence and training also exist in other primary care providers
groups that lead to missed or incorrect diagnoses.1,8,9 Studies
have estimated that 1 out of 5 patients presenting to primary
care with a medical condition are misdiagnosed.10,11
Additionally, many primary care providers do not employ
evidence-based guidelines or appropriate use criteria when
ordering diagnostic imaging or referring for surgery.12
Although between 30%13 and 88%14 of Albertans will
receive magnetic resonance imaging (MRI) for their knee
pain, some of these may not be indicated. Moreover,
approximately 1/3 of patients presenting with knee pain are
referred to an orthopedic surgeon, many of whom could be
managed successfully with non-operative treatment (eg,
non-steroidal anti-inflammatory drugs, active exercise therapy).15 In addition to waiting months for MRI, patients suffer an additional average wait time of 3 to 7 months in
Alberta before appropriate diagnoses and secondary nonoperative care measures are received.16,17
Clinical decision-making tools incorporate evidenceinformed recommendations designed to optimize patient
care, wayfinding, and outcomes. This includes establishing appropriate decisions and services involved in treating
a condition and recommending appropriate timing and
integration of interventions. Adherence to clinical decision-making tools standardize care and reduce unacceptable variations in practice.18 In Alberta, Canada, the Bone
and Joint Health Strategic Clinical Network (BJHSCN)
has created clinical decision-making tools for hip and
knee osteoarthritis and hip fractures in response to the
need for quality improvement.16,19 These tools have
resulted in wait time reductions to assessment and surgery,
improved efficiency of healthcare resources, and improved
patient outcomes.16,19
As part of the MSK-Transformation Initiative, the
BJHSCN has engaged province-wide stakeholder groups
(ie, administrators, physicians, allied health providers,
researchers, and patient advisors) to transform the quality of
care for patients presenting with acute knee injuries and
chronic knee problems.20 In partnership with the Alberta
Bone and Joint Health Institute, the BJHSCN has set out to
transform the way MSK care is delivered in Alberta. Several
initiatives are underway to standardize care, improve management of waitlists, increase effectiveness in delivering
care, and support innovative models of care that shifts the
burden of care and dollars from downstream management
(ie, surgery) toward prevention, early detection, and appropriate community management.20 Therefore, the aim of this

Journal of Primary Care & Community Health 
project is to develop a clinical tool to facilitate clinical decision-making and uptake of evidence-based assessment,
diagnosis, and treatment criteria for patients presenting
with acute knee injuries and chronic knee problems. Acute
injuries include fractures, dislocations, and injuries to the
cruciate ligaments, collateral ligaments, tendons, and cartilage. Chronic knee problems include arthritis and degenerative disease. The development of the knee clinical
decision-making tool occurred over 4 phases: (1) a systematic rapid review to identify existing decision-making tools;
(2) grading of the evidence; (3) development of a Knee
Delphi Questionnaire; and (4) a modified Delphi approach.

Methods
Leadership Team
The development of this tool was guided by a BJHSCN
Knee Leadership Team. The Knee Leadership Team was
comprised of 8 members from 3 stakeholder groups (administrative leaders, researchers, and clinicians) represented by
a BJHSCN executive director, BJHSCN medical director,
ABJHI quality improvement manager, guideline methodologist, provincial physical therapist practice lead, orthopedic
surgeon, sport medicine physician, and athletic therapist.
Each member was assigned to a different role depending on
expertise and previous experience. The Knee Leadership
Team provided project management and quality control
over all 4 phases of the project, including drafting the knee
clinical decision-making tool. Institutional ethical approval
was received from the University of Calgary Ethics
Committee (REB22-0249) on April 22, 2022.

Delphi Expert Panel
Forty-five experts were chosen to form the Delphi expert
panel. To serve on the Panel, experts must have possessed
clinical expertise in knee injury assessment and/or management. Experts were purposefully chosen across all 5 provincial health zones and to include representation from a wide
range of disciplines including emergency medicine, family
medicine, sports medicine, radiology, orthopedic surgery,
athletic therapy, physical therapy, chiropractic, nursing,
public policy, and healthcare administration. Table 1 presents the distribution of experts by geographical location and
discipline.

Rapid Review
The rapid review utilized systematic review methods and
was conducted according to the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses (PRISMA)
guidelines.21 Rapid reviews are recommended for promptly
evaluating a large body of evidence.22 The literature was

Eubank et al
Table 1.

3

Expert Panel Demographic Profile.

Category
Occupation
Physicians
  Orthopaedic surgeon
  Sport medicine
  Family/general practitioner
  Emergency physician
  Radiologist
  Physiatrist
Allied health practitioner
  Physiotherapist
  Athletic therapist
  Chiropractor
Demographic
Physicians
  Calgary
  Edmonton
  North
  Central
  South
Allied health practitioner
  Calgary
  Edmonton
  North
  Central
  South

Baseline
(n=45)

Round 1
(n=42)

Round 2
(n=40)

Round 3
(n=31)

Round
(n=35)

27
10
10
2
2
1
2
18
12
4
2

25
10
9
1
2
1
2
17
11
4
2

23
9
8
1
2
1
2
17
11
4
2

19
7
8
1
0
1
2
12
6
4
2

21
6
9
1
2
1
2
14
8
4
2

27
8
11
2
3
3
18
6
9
0
1
2

25
8
11
2
2
2
17
6
8
0
1
2

23
7
10
2
2
2
17
6
8
0
1
2

19
6
8
1
2
2
12
5
4
0
1
2

21
7
10
0
2
2
14
6
5
0
1
2

searched for protocols, patient flow charts, algorithms,
appropriate use criteria, and clinical practice guidelines for
the following: cruciate ligamentous injuries (anterior cruciate ligament, posterior cruciate ligament); collateral ligamentous injuries (medial collateral, lateral collateral);
patellofemoral joint injuries (including medial patellofemoral ligament, patellar ligament injuries); osteochondral injuries; meniscal injuries; fractures (patella, distal femoral,
proximal tibial, proximal fibula); other muscle injuries
(hamstring and quadriceps group, popliteus); other tendon
injuries (distal hamstring, quadriceps tendon, iliotibial
band, and popliteal tendon); neurological injuries; and vascular injuries. Supplemental Material File 1 presents the
inclusion and exclusion search criteria.
Medline, EMBASE, and CINAHL were searched from
inception to December 2020. The search strategy incorporated a combination of Medical Subject Headings (MeSHs),
text words by means of “wild cards,” and Boolean operators, and was developed in consultation with a health services library scientist within the Knowledge Management
Department of Alberta Health Services. Only English articles and human studies were included in the final synthesis.

Supplemental Material File 2 outlines the search strategy.
Articles were also identified by screening the reference lists
of relevant articles. Citations were imported into Mendeley
Reference Manager Platform for organization and to remove
duplicates. Citations were then exported into a Microsoft
Excel worksheet designed for title and abstract screening.
Titles and abstracts were independently screened by 2
reviewers (BE and CH). Both reviewers first screened a
random sample of 50 titles and abstracts (K = 0.65, 95% CI
0.50, 0.80) to improve consistently in screening. Once the
title and abstract screening was completed, both reviewers
met to discuss and resolve disagreements. Full texts were
screened by BE and CH. BE performed data extraction and
evidence quality appraisal, which was ratified by the Knee
Leadership Group. Each article was graded according to the
Oxford Centre of Evidence-Based Medicine (OCEBM)
200923 model. The quality appraisal worksheet can be found
in Supplemental Material File 3. Data extraction included
author, publication year, study aim, design, population, and
one of the following: protocols, patient flow charts, algorithms, appropriate use criteria, and clinical practice
guidelines.

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Delphi Questionnaire Development
The search results were used to generate evidence-based
statements for the Knee Delphi Questionnaire to create clinical definitions for acute knee injuries and chronic knee
problems and to inform 6 clinical domains: screening indicators, history-taking, physical examination, timelines,
investigations, and treatment. Research Electronic Data
Capture (REDCap) software was used to distribute the
Knee Delphi Questionnaire and consisted of 161 statements.24,25 Experts were given 2 weeks to complete the
Questionnaire before a reminder email was sent.

Modified Delphi Approach
Between March and August 2022, a 4-round modified
Delphi approach was carried out according to the process
outlined in Nasa et al26 for Delphi methodology in healthcare research. However, this modified Delphi approach
deviated slightly with the inclusion of a virtual “face-toface” meeting in Round 3 facilitated using Zoom Video
Communications (version 5.14.2). This deviation allowed
participants to seek clarification, provide constructive feedback, and revise the tool. Voting in rounds 1, 2, and 4 were
completed via REDCap’s survey distribution tools. Voting
in Round 3 was facilitated using Mentimeter’s interactive
polling platform27 to allow for anonymity during the faceto-face meeting. To ensure content validity, 80% was chosen a priori as an appropriate cut off point based on work by
Lynn.28 Participants were asked to select “yes” or “no” for
each statement to indicate whether the evidence should be
included (ie, yes) or not included (ie, no) in the final clinical
tool. Only statements that reached 80% consensus, where
participants voted “yes,” were included in the final clinical
decision-making tool. Those that did not meet consensus,
were revised using participant feedback, and redistributed
for voting. Round 4 was used to circulate the revised clinical decision-making tool to the entire expert panel for a
final round of voting.

Results
Rapid Review and Grading of the Evidence
The search strategy identified 9867 articles. After removing
167 internal and 2118 external duplicates, a total of 7585
citations were included for title and abstract screening.
Three additional articles were retrieved after searching the
reference lists of studies that met the inclusion criteria.
Eight hundred and eighty-six articles were selected for fulltext review, of which 109 articles were included in the final
narrative synthesis. The levels of evidence ranged from

Journal of Primary Care & Community Health 
Level 1b: Prospective cohort study to Level 5: Literature
Review. The majority of studies were categorized as Level
5 evidence. Study characteristics are presented in
Supplemental Material File 3. Figure 1 illustrates the
PRISMA-P flow diagram of the study identification
process.

Modified Delphi Approach
Round 1. Forty-two experts participated in Round 1; 3
experts were lost to follow-up resulting in a response rate of
93%. One hundred and thirty-one of 181 statements reached
consensus: 1 of 2 definitions; 14 of 20 clinical presentations; 17 of 28 screening questions; 33 of 36 history-taking
questions; 22 of 26 physical examination criteria; 15 of 30
diagnostic imaging criteria; and 29 of 39 treatment recommendations. Feedback provided by the expert group was
used to revise the remaining content. New questions were
also created to fill in gaps identified throughout all 6 clinical domains.
Round 2. Forty experts participated in Round 2 resulting in
a response rate of 89%. A revised Delphi Questionnaire was
circulated to the expert group consisting of 76 statements,
in which 49 met consensus: 4 of 4 definitions; 11 of 11 clinical presentations; 12 of 14 screening questions; 6 of 7 history-taking questions; 2 of 11 physical examination criteria;
9 of 15 diagnostic imaging criteria; and 5 of 14 treatment
recommendations. Twenty-seven statements failed to reach
consensus after 2 rounds and were not retained for Round 3.
Round 3. Statements reaching consensus in Rounds 1 and 2
were used to draft the knee clinical decision-making tool.
The draft knee tool was circulated to the expert group prior
to the 2-hour meeting, which also included 41 discussion
points. Thirty-one experts attended the virtual discussion
(response rate = 74%). The meeting was used to seek consensus for each discussion point and review all steps within
the knee clinical decision-making tool, including optimal
sequencing and timing of interventions. During the meeting, 33 discussion points reached consensus. Subsequently,
conversations surrounding each discussion point were used
to inform revisions for the remaining 8 discussion points.
After the meeting, these revisions were carried out, and an
updated version was circulated to the entire expert group
(n = 42). Figure 2 illustrates the results of the Delphi
approach.
Round 4. Thirty-five experts participated in Round 4 voting, resulting in a response rate of 83%. All revisions
reached consensus resulting in the final knee clinical decision-making tool as presented in Figures 3 to 20.

Eubank et al

5

Figure 1. PRISMA-P flow diagram of the identified studies.

A Clinical Decision-Making Tool for Soft Tissue
Knee Injuries
The clinical decision-making tool for patients presenting
with acute knee injuries and chronic knee problems to primary care reached consensus using an expert panel representing various health disciplines and geographical regions
across the province. This tool serves as a reference standard
for primary care providers practicing in both public and private sectors. The clinical examination is a 4-step initial
assessment process with the mandate of initiating early,
non-operative treatment for suitable patients; reducing
unnecessary diagnostic imaging; increasing the

appropriateness of surgical referrals; and reducing waiting
lists for surgical consult for suitable patients (Figure 3). The
knee clinical-decision making tool also consists of screening criteria for medical red and yellow flags (Figure 4);
history-taking and diagnostic questions (Figure 5); physical
examination criteria (Figure 6); an MRI knee appropriateness checklist (Figure 7); 1 pathway selection algorithm
(Figure 8), and 6 differential diagnoses aids and associated
clinical decision-making algorithms (Figures 9-20).
Clinical scope. The knee clinical decision-making tool has
been developed for point-of-care providers (ie, primary care
and allied health) who are managing patients with acute

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Figure 2. Summary of the modified delphi process.

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Figure 3. A step-wise clinical examination process.

7

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Figure 4. Screening criteria for medical red and yellow flags.

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Figure 5. History-taking and diagnostic questions.

9

10

Figure 6. Physical examination criteria.

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Figure 7. MRI knee appropriateness checklist.

11

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Figure 8. Pathway selection algorithm.

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Figure 9. Acute knee injury differential diagnosis.

13

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Figure 10. Acute knee injury pathway.

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Figure 11. Acute intra-articular knee ligament injury differential diagnosis.

15

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Figure 12. Acute intra-articular knee ligament injury pathway.

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Figure 13. Acute extra-articular knee ligament injury differential diagnosis.

17

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Figure 14. Acute extra-articular knee ligament injury pathway.

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Figure 15. Acute patellar instability differential diagnosis.

19

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Figure 16. Acute patellar instability pathway.

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Figure 17. Chronic knee injury differential diagnosis.

21

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Figure 18. Chronic knee pathway.

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Figure 19. Knee arthritis and degenerative meniscus differential diagnosis.

23

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Figure 20. Knee arthritis and degenerative meniscus pathway.

knee injuries and chronic knee problems. In conjunction
with sound clinical judgment, this tool will provide evidence-based, goal-oriented management while identifying
triggers for investigations and referrals. We acknowledge
that this tool is not comprehensive but serves as a helpful
guide for managing common conditions of the knee.

This tool is suitable for adult men and women (≥18 years
old) presenting with acute knee injuries and chronic knee
problems. Children and young adults (<18 years old) and
patients presenting concomitant symptomatic pathologies
(eg, malignancy, inflammatory arthropathy) pose additional
concerns that require a different standard of care. This

Eubank et al
population of patients are likely to require alternative or
collaborative management pathways.
Step 1: Initial assessment. Step 1 comprises of 4 components
in the initial assessment process: (1) perform a focused history-taking; (2) perform a physical examination; (3) identify red flags; and (4) identify yellow flags. The intent is to
guide the appropriateness of the focused history-taking and
physical examination. The focused history-taking comprises of 16 questions (Figure 5) to assist in differential
diagnosis of acute knee injuries and chronic knee problems,
and screening for red and yellow flags. If red or yellow
flags are identified, Figure 4 suggests additional resources
and referral pathways that should be activated to manage
these patients.
Step 1 also outlines 6 components to include in the physical examination (Figure 6). Clinicians should assess lower
limb alignment and perform a gait analysis to assess gait
pattern. The affected side should be assessed and compared
to the contralateral side. Inspection should include effusion,
bruising, deformities, atrophy, prior scars, and lacerations.
The patellar borders, joint lines, and pes anserine should be
palpated to identify the point of maximum tenderness.
Clinicians should also perform bilateral active and passive
knee flexion and extension, and strength testing. Pain or
neurological symptoms originating from the hip, ankle, or
lumbar spine can be ruled out by performing active rangeof-motion, dermatomes, myotomes, and reflexes if indicated. If pain and symptoms are reproduced during this
screening process, additional resources may be required to
help manage the patient, which may include referral to other
health care professionals. Orthopedic special tests were not
prescribed due inherent challenges to validity and reliability
when performed at the primary care level.29 However, primary care providers are not precluded from performing special tests if they confidently possess additional orthopedic
assessment skills or training.
Step 2: Pathway assessment. Step 2 directs providers to a
pathway selection algorithm (Figure 8) to help triage
patients into appropriate care pathways, including referral
of emergent conditions to the Emergency Department for
acute care. Figures 9 and 10 aid in assessment and management for acute knee injuries. The complex nature of
acute knee injuries motivated the development of 3 additional differential diagnosis aids and respective algorithms to manage acute intra-articular knee ligament
injuries (Figures 11 and 12), acute extra-articular knee
ligament injuries (Figures 13 and 14), and acute patellar
instability (Figures 15 and 16). Figures 17 and 18 aid in
assessment and management chronic knee problems,
while Figures 19 and 20 pertain to knee arthritis/degenerative menisci.

25
Step 3: Follow selected pathway. Findings from Step 1: Initial
Assessment inform decision points within each algorithm
including appropriate criteria for diagnostic imaging, surgical referral, and benchmark timelines. Each differential
diagnosis aid corresponds to a specific algorithm and
includes main findings from the focused history-taking,
physical examination, and orthopedic special tests.
Step 4: MRI Knee Appropriate Checklist. Step 4 comprises of
an MRI Knee Appropriate Checklist (Figure 7) to inform
MRI decision-making and highlights that MRI should be
reserved for when unique conditions are suspected (ie, postero-medial lesion of the medial collateral ligament) after
expert orthopedic assessment and in planning for surgery by
an orthopedic surgeon. The tool advises against ordering
MRI at the primary care level. This document has adopted
The Choosing Wisely Canada Orthopaedic Recommendations30 and serves as a central message for clinicians against
routine MRI of patients with acute knee injuries and chronic
knee problems.

Discussion
Acute knee injuries and chronic knee problems are complex
due to the abundance of injury mechanisms and resultant
spectrum of injuries that exist. Even experienced medical
professionals often have difficulties making appropriate
diagnoses.31 A clinical decision-making tool can help to
support difficulties in decision-making, while aiding
patients and clinicians in navigating the complexities of the
health system. It is also difficult to plan treatment without
an accurate diagnosis.32 Prompt identification and triage of
non-surgical and surgically treatable acute knee injuries
enables early intervention, which reduces the risk of secondary injury to other knee tissues.33 Delays can result in a
sixfold increased risk of osteoarthritis (OA) development at
11-year,34 with a sixfold risk of requiring arthroplasty.35
ACL tears are particularly burdensome as they primarily
occur in young persons aged 16 to 35 years, resulting in
greater years lived with disability.17,36
Additionally, there is a high rate of ordering MRI at the
primary care level before orthopedic consultation. This is
largely influenced and not limited to: an overreliance of
MRI for diagnosing acute knee injuries and chronic knee
problems; pressures placed on primary care physicians by
patients; and a misconstrued notion that MRI is a necessary component prior to referring to specialist care or surgical screening.37 Approximately 17 500 patients in
Alberta will receive MRI for their knee problem each year,
where the primary intent is to help with diagnosing injuries.3 This amounts to ~10% of all MRIs performed in the
province.3 Additionally, the estimated wait time for an
MRI in Alberta is 27 to 32 weeks,23 where unnecessary

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Journal of Primary Care & Community Health 

MRI delays diagnosis and subsequent treatment of patients
in which MRI is indicated. Conversely, this also delays
appropriate treatment for patients in which MRI was
unwarranted. At approximately $400 for Albertans and
$800 for out-of-province patients per knee scanned, overreliance of MRI has the potential to cost the province
between $2 and $6 million each year. This estimate does
not include capital costs. This has significant health system implications, whereby a reduction in MRI would
allow more patient care to be provided with the same budgetary constraints.
The goal of this project was to guide clinical decisionmaking for primary care physicians and allied healthcare
professionals in Alberta, Canada. Adoption of the knee clinical decision-making tool may standardize care and provide
logic and flow to clinical practice, which has the potential to
improve quality of care and patient outcomes. It also has the
potential to guide and improve diagnostic accuracy of acute
knee injuries and chronic knee problems, which leads to earlier intervention and reduces the risk of secondary injury to
other knee tissues.15 This reduces the risk of re-injury and
additional irreparable damage to the knee, while mitigating
degenerative changes and delaying OA onset.15 The development of the knee tool was guided by evidence-based best
practice in collaboration with a diverse clinical stakeholder
group, which included professionals from a range of disciplines, expertise, and geographic health regions across
Alberta to ensure generalizability of the tool. This purposive
recruitment strategy was carried out to maximize integration
and uptake of the knee tool into local health care settings
across the province. Collaboration and engagement between
all stakeholder groups was a key aspect of this project.

It will serve as a useful guidance document and starting
point for other regions to borrow or adapt.
Finally, the COVID-19 pandemic had a dramatic effect
on workforce and workplace productivity, which delayed
completion, development, and publication of the knee clinical decision-making tool. It is possible that new studies possessing high levels of evidence have emerged since the
original systematic search was completed in December
2020. However, as the tool is a dynamic document, the
Knee Leadership Team has been mandated to update the
document every 5 years.

Limitations

Declaration of Conflicting Interests

Although a thorough and systematic search was conducted
to gather the best available evidence, recommendations
were limited by the availability of high-grade evidence in
the literature. Therefore, the Delphi expert group was used
to fill in gaps and recommend best practices to enable practicality and acceptability within our local clinical settings.
This practice has been accepted and is often used by health
systems to create an integrated care environment that is
appropriate for the population it serves.38
Additionally, the knee clinical decision-making tool
should only be used as a reference standard in conjunction
with sound clinical judgment. Tools are most valid and reliable when utilized in the context and setting in which it was
developed. Therefore, the impact of this tool on healthcare
providers outside of Alberta, Canada will vary accordingly.
However, the knee clinical decision-making tool provides a
systematic approach, best-evidence synthesis, and standardized criteria for screening, history-taking, physical
examination, diagnostic imaging, timelines, and treatment.

Conclusion
The knee clinical decision-making tool was developed
through a multi-phase process involving evidence synthesis
and provincial expert consultation. The result was a clinical
decision support tool with implications for patients, providers, healthcare administrators, and policy makers. This tool
aims to improve clinical uncertainty with respect to knee
assessment, treatment, diagnostic imaging, and community
management. To ensure the tool retains accuracy and appropriateness, periodic updates of this tool will be carried out
as part of ongoing BJHSCN quality improvement initiatives. Next steps will also aim to evaluate the clinical effectiveness of this tool within the Alberta health system
setting.
Acknowledgments
The authors would like to thank the members of the Consensus
Expert Delphi Group who contributed to the development of the
knee clinical decision-making tool.

The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.

Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.

ORCID iD
Breda H. F. Eubank

https://orcid.org/0000-0003-1735-8642

Supplemental Material
Supplemental material for this article is available online.

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