Keywords
shoulder - diagnosis - history
Musculoskeletal disorders are the most prevalent chronic health condition in Canada,
being both the leading cause of disability and cause the greatest use of health care
resources in Canada.[1] Shoulder complaints are the third most common musculoskeletal problem in the general
population, second to knee referrals to orthopaedic surgery or primary care sports
medicine clinics.[2] Shoulder pain and disability pose a challenge for physicians owing to the numerous
etiologies and the potential for multiple disorders existing in the same patient.
A thorough history and clinical evaluation of the entire shoulder girdle, along with
clinical tests and imaging may be necessary to make a diagnosis. More invasive tests,
including magnetic resonance imaging (MRI) and arthroscopic exam, are often felt necessary,
as a clinical evaluation alone can frequently lead to misdiagnoses.
Although most physicians rely on these modalities to arrive at a definitive diagnosis,
patient history may be sufficient to predict pathologies associated with the shoulder.
Over a half century ago, Platt claimed that in most general medical cases, a diagnosis
can be made with a history alone.[3] Hampton et al[4] evaluated the importance of the medical history in the diagnosis of general medical
outpatients and found that in 83% of their patients, the diagnosis following the history
agreed with the final diagnosis. Similarly, Peterson et al[5] found that the history led to a correct diagnosis in 76% of their general medical
outpatients. Although this phenomenon has been demonstrated in many patient populations,
few studies have evaluated the accuracy of the history as a diagnostic test for shoulder
pathology.
Litaker et al[6] demonstrated that age older than or equal to 65 years, and night pain, were the
most predictive of rotator cuff tears. Holtby and Razmjou[7] found that 76% of their patients referred for surgery had night pain. Michener et
al[8] examined history of trauma, sudden onset of pain, and history of popping, clicking,
or catching, and demonstrated that none of these items had diagnostic utility for
superior labrum anterior to posterior (SLAP) lesions.
Primary care physicians often misdirect referrals of musculoskeletal conditions to
orthopaedic surgeons when nonsurgical intervention is most appropriate.[9] This reduces the efficiency of these services and can potentially affect quality
of care. Thus, having a tool to assist with the practice of triage can streamline
the care of patients. To this end, Stiell et al[10] developed a clinical decision rule, the Ottawa ankle rules, to guide the assessment
of ankle injuries. The Ottawa ankle rules provide a high level of diagnostic confidence
and has reduced the number of radiographs ordered by emergency departments.[11]
[12] Applying the same principle to the shoulder population could reduce the number of
patients being referred for further diagnostic tests, thus, improving the efficiency
of these services for others.
The purpose of this article is to determine whether patient-reported history items
are predictive of shoulder pathology. We will assess whether a clinical decision rule
can be developed that could effectively triage patients with shoulder pathology to
orthopaedic outpatient clinics.
Methods
Patient Population
Using a consecutive sampling strategy, we recruited all participants presenting for
their first consultation for shoulder pain or disability between May 2007 and November
2008, within two tertiary care centers that specialize in orthopaedics. We excluded
patients with adhesive capsulitis or glenohumeral arthritis. A total of 193 patients
participated in this study. All patients gave informed consent, and the study was
approved by each center's Research Ethics Board.
Identification of History Items
We conducted a review of the diagnostic literature for shoulder pathology to identify
common items used in a typical clinician history. A list of items was compiled for
the most common pathology (rotator cuff pathology, labral pathology, acromioclavicular
abnormalities, and instability) and circulated to expert orthopaedic surgeons with
a specialty in shoulder disorders for review. In a round-table discussion, each item
was reviewed individually by the clinicians and they selected whether to include or
exclude the item. Any discrepancies were re-examined until a consensus was reached.
Clinical Examination Testing
Prior to seeing the clinician, patients completed a detailed questionnaire asking
questions in regard to their referred painful/disabled shoulder, which included the
items identified by clinicians. These elicited demographic information, symptoms,
mechanism of injury, and history of their disease. The clinician was not provided
with the completed questionnaire. Instead, the clinician took the patient's history
as usual. Following the history, the clinician recorded their primary diagnosis and
any secondary diagnoses, then rated their confidence with each diagnosis on a visual
analog scale (VAS) ranging from 0 to 100% confidence. The clinician then performed
the physical examination maneuvers for any disease suspected to contribute to the
patient's symptoms. The clinician was then asked (again) to indicate their primary
and any secondary diagnoses and to indicate their confidence in these diagnoses. The
results of the physical examination maneuvers are reported elsewhere.[13]
[14]
Reference Standard
Arthroscopic examination and MRI arthrogram were the main reference standards. We
developed a standardized arthroscopic examination and reporting protocol to minimize
differences between surgeons in diagnoses due to variations in methods of examination.
The clinicians were to look specifically at the subacromial space, rotator cuff tendons,
glenoid labrum, acromioclavicular joint, biceps tendon, and cartilage.
Although the majority of patients went on to have surgery, some did not require surgery,
or opted out of recommended surgery. These patients underwent a standardized MRI arthrogram
as the reference standard. Since the literature has shown that MRI alone is not as
accurate for diagnosing SLAP tears, with reported sensitivities for MRI ranging from
43 to 75%,[15]
[16]
[17]
[18]
[19] and specificities between 58 and 70%,[15]
[18]
[19] we included the arthrogram. There is good evidence to suggest that MRI arthrogram
is a comparable reference standard to arthroscopy. MRI arthrogram has been shown to
be highly sensitive (100 and 82%) and specific (88 and 100%) for detecting SLAP injuries.[20]
[21]
Plan for Statistical Analysis
Sensitivity and specificity were calculated for each history item including 95% confidence
intervals. These values were used to calculate positive and negative likelihood ratios
(LRs). LRs greater than 1 increase the probability that the test result is associated
with the disease, whereas LRs less than 1 indicate that the test result is associated
with the absence of disease.
We calculated the proportion of diagnoses that agreed following the patient history
and the physical examination. Among those that agreed, we calculated the proportion
that was accurate according to the gold standard. For these patients, we also calculated
the change in confidence in the diagnosis following the physical examination. For
those patients in whom a discrepancy was noted between the primary diagnosis after
the physical examination and the primary diagnosis following the history, we determined
the proportion of primary diagnoses that were switched with the secondary diagnosis
after the physical examination, and the proportion of primary diagnosis that changed
entirely following the physical examination. Of these cases, we calculated the proportion
of diagnosis that the history identified correctly and that the physical examination
identified correctly according to the gold standard.
We used the LRs to generate a clinical decision rule. The item with the highest LR
was selected as the first question in the decision algorithm. All patients who answered
“yes” to this question were removed from subsequent analyses, and the measurement
properties were recalculated with the new sample. This process was repeated until
the remaining history items produced LRs that would not change the clinician's impression
of the probability of the target disorder (i.e., the LR was less than 2).
For any disease in which the history items would not change the clinicians impression
(LR less than 2), we calculated the prevalence of disease at that step in the algorithm
and used this value as the pretest probability. We calculated the 95% confidence interval
around this probability. Using the literature on the diagnostic validity of MRI arthrogram,
we calculated the LR for MRI arthrogram for any disease that the history items could
not diagnose. Using the pretest probability and LR, we calculated the posttest probability
of these disorders if an MRI arthrogram was ordered. This value was calculated for
the lower and upper 95% confidence interval of the prevalence.
Results
The clinicians selected 32 items to be included in the patient history questionnaire.
The questionnaire consisted of items for anterior instability, posterior instability,
multidirectional instability, SLAP lesions, tendinosis, subscapularis disease, rotator
cuff disease, and acromioclavicular abnormalities ([Table 1]).
Table 1
Patient-reported history questionnaire items
|
Q1: Did you try any new activities in the days preceding the onset of pain?
Q2: Do you experience pain when performing overhead activities?
Q3: Do you feel pain in your shoulder during rest?
Q4: Do you have difficulty lifting objects?
Q5: At the time of injury, did you feel a snap/tear in your shoulder?
Q6: Did the onset of pain in your shoulder occur after a motor vehicle accident (while
wearing a seatbelt)?
Q7: Do you have weakness in your shoulder when doing up your seatbelt?
Q8: Do you have weakness when throwing an object overhand?
Q9: Does your occupation or hobbies require elevation of the arm above the level of
the shoulder?
Q10: Has your shoulder pain been longstanding (> 6 mo)?
Q11: Do you experience pain at night while lying on the injured shoulder?
Q12: Does pain at night awaken you from your sleep?
Q13: Is the pain worsened by participating in activities where the elbow is level
with the shoulder?
Q14: Do you have a feeling of clicking, clunking, or grinding with use of your arm
overhead?
Q15: Do you feel weakness in your shoulder without any pain?
Q16: Is the pain in your shoulder worsened by the position of your neck?
Q17: Do you have numbness/tingling in your hand?
Q18: Does your shoulder pain radiate to your hand?
Q19: At the time of injury, did you feel a sudden pull on your arm (e.g., waterskiing,
grabbing onto something when falling, sudden pull when losing hold of a heavy object)?
Q20: Do you participate regularly in overhead sports (e.g., tennis, baseball, squash,
etc.)?
Q21: Do you experience a catching, locking, popping, or grinding along with pain in
your injured shoulder?
Q22: Do you ever experience the feeling of your arm coming out of the socket?
Q23: Has your shoulder ever dislocated from its socket?
Q24: Does your shoulder feel unstable toward the back of your body?
Q25: Did your shoulder become painful after a traumatic event (e.g., motor vehicle
accident)?
Q26: At the time of injury, was your arm driven backward (e.g., car accident while
holding the wheel, taking a hit from the front)?
Q27: Are you extremely flexible?
Q28: Can you make your shoulder come out?
Q29: Does your shoulder come out with daily activities?
Q30: Do you experience discomfort while doing weight lifting, push-ups, or dips?
Q31: Do you feel like your collar bone moves when raising your arm?
|
Of the 193 enrolled patients, 15 patients refused to undergo one of the reference
standard tests, or canceled their scheduled test; therefore, the remaining 178 patients
composed the study sample. There were 127 males and 51 females with an average age
of 41.8 (standard deviation = 17.5) years.
The diagnostic validity measures for all of the history items are presented in [Table 2]. The majority of questions intended to diagnose rotator cuff disease were highly
sensitive, but their LRs suggested that they are not clinically useful. The results
were similar for subscapularis tears and SLAP tears, but Question 5 (“At the time
of injury, did you feel a snap/tear in your shoulder?”) had a LR approaching three
for full-thickness tears of the subscapularis. If the history items for subscapularis
were assessed in combination, adding Question 8 (“Do you have weakness when throwing
an object overhand?”) improved this LR to over three. The majority of history items
for posterior instability had poor diagnostic ability, but Question 26 (“At the time
of injury, was your arm driven backward?”) and Question 29 (“Does your shoulder come
out with daily activities?”) had LRs over two. All of the items for anterior instability
were good indicators of disease, with LRs over three.
Table 2
Diagnostic validity measures for patient-reported history items
|
Item
|
Sensitivity
|
95% CI
|
Specificity
|
95% CI
|
Positive LR
|
Negative LR
|
|
Rotator cuff disease[a]
|
|
Q1
|
|
All disease
|
13.6
|
8.0–22.3
|
80.0
|
70.6–87.0
|
0.68
|
1.08
|
|
All tears
|
12.5
|
6.7–22.1
|
80.2
|
71.6–86.7
|
0.63
|
1.09
|
|
FT tears
|
11.1
|
5.5–21.2
|
81.2
|
73.3–87.1
|
0.59
|
1.10
|
|
Tendinosis
|
18.8
|
6.6–43.0
|
83.3
|
76.8–88.3
|
1.13
|
0.98
|
|
Q2
|
|
All disease
|
95.5
|
88.9–98.2
|
13.3
|
7.8–21.9
|
1.10
|
0.34
|
|
All tears
|
97.2
|
90.4–99.2
|
13.2
|
8.0–21.0
|
1.12
|
0.21
|
|
FT tears
|
96.4
|
87.9–99.0
|
11.5
|
7.0–18.3
|
1.09
|
0.31
|
|
Tendinosis
|
87.5
|
64.0–96.5
|
8.6
|
5.2–14.0
|
1.45
|
0.66
|
|
Q3
|
|
All disease
|
86.4
|
77.7–92.0
|
34.4
|
25.5–44.7
|
1.32
|
0.40
|
|
All tears
|
88.9
|
79.6–94.3
|
33.0
|
24.8–42.4
|
1.33
|
0.34
|
|
FT tears
|
87.5
|
76.4–93.8
|
29.5
|
22.1–38.1
|
1.24
|
0.42
|
|
Tendinosis
|
75.0
|
50.5–89.8
|
24.1
|
18.1–31.2
|
0.99
|
1.04
|
|
Q4
|
|
All disease
|
83.9
|
74.8–90.2
|
28.9
|
20.5–39.0
|
1.18
|
0.56
|
|
All tears
|
84.5
|
74.4–91.1
|
27.4
|
19.8–36.5
|
1.16
|
0.57
|
|
FT tears
|
85.5
|
73.8–92.4
|
26.2
|
19.2–34.7
|
1.16
|
0.56
|
|
Tendinosis
|
81.3
|
57.0–93.4
|
23.0
|
17.2–30.1
|
1.06
|
0.82
|
|
Q8
|
|
All disease
|
89.8
|
81.7–94.5
|
23.5
|
15.8–33.6
|
1.17
|
0.44
|
|
All tears
|
90.3
|
81.3–95.2
|
21.8
|
14.9–30.1
|
1.15
|
0.45
|
|
FT tears
|
92.6
|
82.5–97.1
|
21.0
|
14.7–29.2
|
1.17
|
0.35
|
|
Tendinosis
|
87.5
|
64.0–96.5
|
17.2
|
12.1–23.9
|
1.06
|
0.73
|
|
Q9
|
|
All disease
|
74.7
|
64.7–82.7
|
20.0
|
13.0–29.4
|
0.93
|
1.26
|
|
All tears
|
77.5
|
66.5–85.6
|
22.6
|
15.7–31.5
|
1.00
|
0.99
|
|
FT tears
|
78.2
|
65.6–87.1
|
23.0
|
16.4–31.2
|
1.02
|
0.95
|
|
Tendinosis
|
62.5
|
38.6–81.5
|
21.1
|
15.5–28.1
|
0.79
|
1.78
|
|
Q10
|
|
All disease
|
87.5
|
79.0–92.9
|
17.8
|
11.3–26.9
|
1.06
|
0.70
|
|
All tears
|
86.1
|
76.3–92.3
|
16.0
|
10.3–24.2
|
1.03
|
0.87
|
|
FT tears
|
83.9
|
72.2–91.3
|
14.8
|
9.5–22.1
|
0.99
|
1.09
|
|
Tendinosis
|
93.8
|
71.7–98.9
|
16.1
|
11.2–22.5
|
1.12
|
0.39
|
|
Q11
|
|
All disease
|
92.0
|
84.3–96.1
|
26.7
|
18.6–36.6
|
1.25
|
0.30
|
|
All tears
|
94.4
|
86.4–97.8
|
25.5
|
18.1–34.5
|
1.27
|
0.22
|
|
FT tears
|
94.6
|
85.2–98.1
|
23.0
|
16.4–31.1
|
1.23
|
0.24
|
|
Tendinosis
|
81.3
|
57.0–93.4
|
17.4
|
12.3–24.0
|
0.98
|
1.08
|
|
Q12
|
|
All disease
|
79.6
|
70.0–86.7
|
53.3
|
43.1–63.3
|
1.71
|
0.38
|
|
All tears
|
80.6
|
70.0–88.1
|
49.1
|
39.7–58.4
|
1.58
|
0.40
|
|
FT tears
|
83.9
|
72.2–91.3
|
46.7
|
38.1–55.5
|
1.56
|
0.34
|
|
Tendinosis
|
75.0
|
50.5–89.8
|
38.3
|
31.1–46.0
|
1.22
|
0.65
|
|
Q13
|
|
All disease
|
88.6
|
80.3–93.7
|
18.9
|
12.1–28.2
|
1.09
|
0.60
|
|
All tears
|
90.3
|
81.3–95.2
|
18.9
|
12.6–27.4
|
1.11
|
0.52
|
|
FT tears
|
91.1
|
80.7–96.1
|
18.0
|
12.2–25.8
|
1.11
|
0.50
|
|
Tendinosis
|
81.3
|
57.0–93.4
|
14.8
|
10.2–21.1
|
0.95
|
1.27
|
|
Q14
|
|
All disease
|
69.0
|
58.6–77.7
|
26.7
|
18.6–36.6
|
0.94
|
1.16
|
|
All tears
|
70.8
|
59.5–80.1
|
28.6
|
20.8–37.9
|
0.99
|
1.02
|
|
FT tears
|
69.6
|
56.7–80.1
|
28.1
|
20.9–36.7
|
0.97
|
1.08
|
|
Tendinosis
|
60.0
|
35.8–80.2
|
27.8
|
21.5–35.1
|
0.83
|
1.44
|
|
Q15
|
|
All disease
|
56.8
|
46.4–66.7
|
33.0
|
24.0–43.3
|
0.85
|
1.31
|
|
All tears
|
56.2
|
44.8–67.0
|
34.0
|
25.6–43.6
|
0.85
|
1.29
|
|
FT tears
|
54.6
|
41.5–67.0
|
34.7
|
26.8–43.6
|
0.84
|
1.31
|
|
Tendinosis
|
60.0
|
35.8–80.2
|
37.9
|
30.8–45.6
|
0.97
|
1.06
|
|
Subscapularis tears
|
|
Q5
|
|
All disease
|
44.7
|
30.2–60.3
|
66.2
|
57.8–73.7
|
1.32
|
0.84
|
|
All tears
|
57.9
|
36.3–76.9
|
66.5
|
58.6–73.5
|
1.73
|
0.63
|
|
FT tears
|
87.5
|
52.9–97.8
|
66.3
|
58.7–73.1
|
2.59
|
0.19
|
|
Tendinosis
|
31.6
|
15.4–54.0
|
77.8
|
72.3–82.5
|
1.42
|
0.88
|
|
Q6
|
|
All disease
|
2.4
|
0.4–12.6
|
96.4
|
91.7–98.4
|
0.67
|
1.01
|
|
All tears
|
0.0
|
0.0–15.5
|
96.2
|
91.9–98.2
|
0.0
|
1.04
|
|
FT tears
|
0.0
|
0.0–32.4
|
96.5
|
92.5–98.4
|
0.0
|
1.04
|
|
Tendinosis
|
5.0
|
0.9–23.6
|
96.8
|
92.8–98.6
|
1.58
|
0.98
|
|
Q7
|
|
All disease
|
51.2
|
36.5–65.8
|
65.0
|
56.7–72.5
|
1.46
|
0.75
|
|
All tears
|
57.1
|
36.6–75.5
|
63.7
|
55.9–70.8
|
1.57
|
0.67
|
|
FT tears
|
37.5
|
13.7–69.4
|
61.2
|
53.7–68.2
|
0.97
|
1.02
|
|
Tendinosis
|
45.0
|
25.8–65.8
|
62.0
|
54.3–69.2
|
1.19
|
0.89
|
|
Q8
|
|
All disease
|
94.7
|
82.7–98.5
|
20.0
|
14.1–27.5
|
1.18
|
0.26
|
|
All tears
|
100.0
|
83.2–100
|
18.8
|
13.4–25.7
|
1.23
|
|
|
FT tears
|
100.0
|
64.6–100
|
17.5
|
12.5–24.0
|
1.21
|
|
|
Tendinosis
|
89.5
|
68.6–97.1
|
17.5
|
12.3–24.3
|
1.09
|
0.60
|
|
Superior posterior labral complex
|
|
Q19
|
|
All SLAP tears
|
37.7
|
25.9–51.2
|
69.1
|
60.5–76.6
|
1.22
|
1.89
|
|
Types II–V
|
54.2
|
35.1–72.1
|
70.4
|
62.7–77.1
|
1.83
|
0.65
|
|
Q20
|
|
All SLAP tears
|
51.9
|
38.9–64.6
|
57.4
|
48.5–65.8
|
1.22
|
0.84
|
|
Types II–V
|
15.6
|
9.2–25.3
|
31.3
|
23.0–41.0
|
0.23
|
2.70
|
|
Q21
|
|
All SLAP tears
|
59.3
|
46.0–71.3
|
32.8
|
25.1–41.5
|
0.88
|
1.24
|
|
Types II–V
|
75.0
|
55.1–88.0
|
36.8
|
29.6–44.8
|
1.19
|
0.68
|
|
Anterior instability
|
|
Q22
|
70.0
|
56.3–80.9
|
68.5
|
60.0–75.9
|
2.22
|
0.44
|
|
Q23
|
76.0
|
62.6–85.7
|
81.3
|
73.6–87.1
|
4.05
|
0.30
|
|
Q29
|
30.0
|
19.1–43.8
|
94.5
|
89.1–97.3
|
5.44
|
0.74
|
|
Posterior instability
|
|
Q22
|
54.6
|
28.0–78.7
|
58.4
|
50.8–65.7
|
1.31
|
0.78
|
|
Q23
|
36.4
|
15.2–64.6
|
66.5
|
58.9–73.2
|
1.08
|
0.96
|
|
Q24
|
63.6
|
35.4–84.8
|
58.3
|
50.6–65.6
|
1.53
|
0.62
|
|
Q25
|
72.7
|
43.4–90.3
|
41.6
|
34.3–49.2
|
1.25
|
0.66
|
|
Q26
|
63.6
|
35.4–84.8
|
76.7
|
69.6–82.5
|
2.73
|
0.47
|
|
Q29
|
27.3
|
9.8–56.6
|
88.6
|
82.8–92.6
|
2.38
|
0.82
|
|
Acromioclavicular joint arthritis
|
|
Q30
|
87.0
|
75.6–93.6
|
12.1
|
7.3–19.2
|
0.99
|
1.07
|
Abbreviations: CI, confidence interval; FT, full thickness; LR, likelihood ratio;
PT, partial thickness; SLAP, superior labrum anterior to posterior.
a All disease refers to any pathology affecting the supraspinatus tendon. This includes
tendinosis, PT tears, and FT tears. All tears refer to both PT and FT tears.
The primary diagnoses following the physical examination agreed with the diagnoses
made by the history in 74.6% of cases. Sixty-nine percent of these were correct according
to the gold standard. The confidence change following physical examination was minimal
on the VAS scale (2.69 ± 18.7). For those patients who the primary diagnosis after
the history agreed with the diagnosis following the physical examination, only 10%
did not correlate with the gold standard diagnosis. Seventeen percent of the primary
and secondary diagnoses after the history were switched following the physical examination.
Of these, 45% were identified correctly by the history, 23% by the physical examination,
and the remaining were not identified by either the physical examination or history.
The primary diagnosis changed entirely following the physical examination in 16.6%
of cases. Of these, 47% were identified correctly with the history, 24% with the physical
examination, and the remaining were not identified by either.
The diagnostic decision algorithm is presented in [Fig. 1]. Question 23 (“Has your shoulder ever dislocated from its socket?”) had the best
combination of measurement properties and was therefore selected as the first question
in the diagnostic algorithm. Of those who answered “yes” to this question, 38 had
anterior labral tears, 6 had a degenerative labrum, and 15 had another disorder. Of
those with another disorder, six had another type of instability (posterior, multidirectional,
or atraumatic instability). Since these disorders could also present with shoulder
dislocations, we assessed whether other questions could differentiate these diseases
at this stage. Question 26 was found to have moderate diagnostic utility (LR = 1.93)
for posterior instability, and Question 28 (“Can you make your shoulder come out?”)
was able to differentiate multidirectional instability (LR = 2.67). For those patients
who answered “no” to Question 23, analysis revealed that posterior instability could
be predicted with Question 26 (LR = 3.60). Analysis with the remaining patients demonstrated
that a combination of Questions 5 and 8 was diagnostic for full-thickness subscapularis
tears (LR = 4.14). At this stage of the clinical decision algorithm, we found that
the history items could not predict rotator cuff tears or SLAP lesions. We calculated
a LR of an MRI arthrogram for rotator cuff tears[22] to be 86.7 and for SLAP lesions[21] to be 41. Using these LRs, we determined that the posttest probability of rotator
cuff tear following an MRI arthrogram would be 98.15% (96.8–98.8%) and for SLAP lesions
83.67% (55.9–90%).
Fig. 1 Diagnostic clinical decision algorithm using patient-reported history items for shoulder
pathology.
Discussion
Diagnosis of shoulder pathology is one of the most challenging areas in orthopaedics
as the clinical manifestations vary widely and pathologies often coexist. Our study
demonstrates that the patient-reported history items for shoulder pathology are predictive
of disease and can be useful in the diagnostic process. In particular, history items
were good diagnostic indicators of anterior instability (Question 23), posterior instability
(Question 26), and full-thickness subscapularis tears (Questions 5 and 8). History
items for SLAP injuries and rotator cuff tears could not change the clinical impression
of disease as their LRs were close to one. Physical examination changed the primary
diagnosis made by the history in only 25% of cases, and of these, only 23% changed
the diagnosis correctly, in 47%, the history was correct, and in the remaining cases
neither the history nor physical examination was correct. We assessed whether MRI
arthrogram could improve the ability to predict these disorders and found that the
probability of disease could be improved to 83.7 and 93.2% for SLAP lesions and rotator
cuff tears, respectively.
Several studies have established that a substantial portion of referrals to orthopaedic
specialists are inappropriate.[9]
[23]
[24]
[25] Roland et al[25] found that 43% of referrals to their orthopaedic clinic could have been avoided.
Similarly, Speed and Crisp[9] showed that only 42% of their referred sample was listed for a surgical intervention
following orthopaedic consultation. Both concluded that referral guidelines might
help make more efficient use of orthopaedic services and optimize patient care. A
more efficient referral process could reduce the number of unsuitable patients being
seen by the specialist and consequently reduce wait times and improve management of
patients who require a specialist.
The use of triage systems to ensure referrals reach the most appropriate destination
is a popular concept. This triage process begins with a referral sent by a primary
care clinician and upon its arrival is directed by a gatekeeper.[9] Several pitfalls in the current system suggest a need for an improved triage system.
First, general and primary care clinicians often have low levels of confidence in
diagnosing and managing musculoskeletal disorders often referring patients when it
is inappropriate or sending them for clinical tests that are not warranted.[25]
[26] In addition, this system is limited by the lack of information that is provided
in the referral letter, and consequently, gatekeepers may have difficulty deciding
where the referral should be sent to. We were able to construct a clinical decision
algorithm that has the potential for implementation in the orthopaedic referral process.
The algorithm is formatted as a decision tree whereby if a patient were to answer
“no” to a question they would advance to the next, if they were to answer “yes” then
the process would end and the patient would be referred to the appropriate management.
If a patient were to get through the entire algorithm without responding “yes” to
any question, we would recommend the patient be referred for a more invasive clinical
test (MRI arthrogram) to assist in confirming a diagnosis before being referred to
an orthopaedic specialist.
This algorithm has several advantages. First, only patients who answered “yes” to
any item in the algorithm would be referred to an orthopaedic surgeon. This has the
potential to reduce the number of unsuitable patients being seen by a specialist.
In our study, if this algorithm was in place, the potential reduction in the number
of patients seen by the surgeon would have been 37%. Second, this algorithm has the
potential to reduce the number of costly or invasive tests that patients get referred
for. Many patients who get referred to orthopaedic specialists have undergone at least
one type of imaging modality, including X-ray, ultrasonography, and MRI. Our study
found that patients do not have to undergo these examinations unless they proceed
through the decision algorithm without a diagnosis. Using our algorithm, only 37%
of patients would have been referred for an MRI arthrogram. Primary care clinicians
need to be informed that musculoskeletal patients do not need to be sent for these
modalities as part of their work-up prior to referral. This has the potential to reduce
the cost to health care resources, as only a fraction of musculoskeletal referrals
will be sent for costly examinations. Third, as a health care specialist is not needed
to collect the data required for our algorithm, this system may lend itself to electronic
administration. In an era of ever-advancing technology, paperless charting, electronic
access to patient care guidelines, and computerized decision tools promise to improve
patient care. Electronic methods of triaging have been assessed in an emergency department
setting and were found to improve allocation of patients compared with traditional
triaging methods.[27] Future research efforts could assess whether such an instrument can be utilized
in the referral process electronically in this orthopaedic population.
Although this decision tool has the potential to improve the efficiency of orthopaedic
services, it is necessary to validate this tool in the orthopaedic shoulder population.
Future research should focus on determining if this triage system can successfully
allocate patients. This research would inform us whether this tool is useful in a
clinical setting.
Limitations
A limitation of our study is that patients enrolled in our study were referred to
a tertiary care orthopaedic clinic; therefore, the results should be generalized to
only those types of patients. Although the generalizability is limited, the strengths
of this study include its large sample size, which enable us to provide precise measures
of the specificity, sensitivity, and LRs of the history items. In addition, this study
involves four surgeons in two different cities in Ontario, Canada, which increases
the applicability of the results. Consequently, there is enormous potential for knowledge
transfer, in that our results will be used to guide practice, teach medical students,
residents, and fellows, and will create a more research friendly atmosphere.
Conclusion
Based on these study results, we found that the patient-reported history is able to
diagnose anterior instability, posterior instability, and subscapularis tears. In
fact, the physical examination and history agreed in 75% of cases. Of those that did
not agree, the physical examination misdirected the diagnosis in 47% of our cases.
We can conclude that these have the potential to assist in the triage process. In
addition, patients should not be sent for diagnostic imaging without first triaging;
moreover, if the patient gets to the end of the decision tree without a diagnosis,
MRI arthrogram is an appropriate imaging modality to distinguish both rotator cuff
tears and SLAP lesions.
