Of Hunters and Fishermen NSCFP Family Medicine Assembly

Peir 21, October 2, 2015

Sam G CampbellMB BCh, FCFP(EM), Dip PEC(SA), FCCHL.

Chief, Department of Emergency MedicineCharles V Keating Emergency and Trauma Centre

Professor of Emergency MedicineDalhousie University, Halifax, Nova Scotia.

Faculty: Sam Campbell

Relationships with commercial interests:◦ Grants/Research Support: Shire, NSHA, Boehringer-

Ingelheim.◦ Speakers Bureau/Honoraria: Boehringer-Ingelheim, ◦ Other: Employee PraxES Medical Group

Faculty/Presenter Disclosure

CFPC CoI Templates: Slide 1

This program has received no financial nor in kind support from anyone

Potential for conflict(s) of interest:◦ Sam Campbell has received no payment/funding,

from any organization whose product(s) are being discussed in this program.

Disclosure of Commercial Support

CFPC CoI Templates: Slide 2

Active involvement in Choosing Wisely Canada

Dal Critical thinking group

Mitigating Potential Bias

CFPC CoI Templates: Slide 3

Remind people about Choosing wisely Basic concept of testing

◦ Why/How tests lie ◦ How should we use them?

Clinical Context/Bayesian approach

Overview

P.H, 54 yr old ‘Check up’ CBC, ‘lytes, BUN/Creat, LFTs, Lipids, TSH, Fe,

PSA, Vit B12, folate, Vit D. Transaminases mildly elevated Repeat in a month (still up) Heaptitis serology, ANA, Abd US. 3.5 cm lesion in rt kidney (?angiomyolipoma) CT – confirms AML

Rational test ordering in family medicine

Can Fam Phys 2015;61:535-7.

Lab: US and CT: Missed work Anxiety ++ Reassurance???

Cost?

Can Fam Phys 2015;61:535-7.

L.A.W.

Canadian Journal of Diagnosis (in press)

What we do is not benign …

What we ask may not be either…….

Choosing Wisely Canada (CWC)

- campaign to help physicians and patients engage in conversations about unnecessary tests, treatments and procedures, and to help physicians and patients make smart and effective choices to ensure high-quality care.

Lists of interventions of questionable value from different specialist organizations.

1970 1980 1990 2000 2008 20110

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4

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16

18

GermanyU.K.CanadaJapanU.S.

OECD, 2013

Total health expenditures as % of GDP (1970-2011)

IOM - 30% of health care spending wasteful, no added value to patient care

Inappropriate testing◦ > 50% of prescriptions for respiratory infections◦ 28 - 65% of lumbar spine MRIs inappropriate◦ 9 - 16% of head scans for headache◦ Bone density scans, Vit D levels, pre-operative

tests………..

Issue of medical overuse

Hunters vs. Fishermen:

This is a simplistic preliminary discussion of a complicated issue

Doctors,

They are just tools, each designed for a purpose

Tests are not bad!

Test variability may be related to:◦ the test◦ the interpreter ◦ duration of symptoms/stage of the illness ◦ lab equipment, reagents, procedure, or even lab

error.

Test results should never be◦ accepted at face value◦ interpreted without considering pre-test (clinical)

probability of disease.

Medical tests are seldom useful unless taken in the appropriate clinical context

Diagnostic tests are used to:◦to help establish diagnoses.

Clinical uncertainty

◦ Culture ‘more is better’◦ Relieve pressure from patients/family (Cyberchondria)

◦ To delay making a decision (Entertain the patient while we wait for something to declare itself)

◦ Consultant expectations◦ Save time explaining/examining◦ Perpetuate the myth of medical clarity◦ “Routine”

Screening just because it is what we do!

Diagnostic tests are sometimes used to:

I’m going order this test because I don’t have time to tell you why you don’t need it…

Diagnosis◦ Rule In vs. Rule Out◦ Treatment Threshold

From a clinical perspective

Out of sight – ethereal/magical Measured once and rarely challenged

The Lab

Presumption that the result will help your patient

Presumption of benefit exceeding risk◦ Phlebotomy risks◦ Risk of false results◦ Waste of time/money◦ Misinformation/misinterpretation

It goes without saying..

Don't "make" diagnoses; they supplement clinical judgement and reduce the level of diagnostic uncertainty.

Unless applied and interpreted carefully, tests can be misleading.

Diagnostic tests:

The premise of diagnostic testing is that there are 2 populations of people ◦ those with the disease◦ those without .....

who differ on at least one testable parameter.

Almost all tests lie!

Most tests can be ‘positive’ for several reasons Not everyone with (for example) pneumonia

has an infiltrate on x-ray and not everyone with an infiltrate has pneumonia.

Patient variability and test variability result in an overlap between the results for diseased and normal populations for virtually all tests

The real world, however....

Most objective tests assess a measurable parameter and classify the patient as "normal" or "abnormal."

"Normal" is typically established by determining test values in disease-free people and identifying the range in which 95% of this population lies.

‘Normal’ values

Normal range of results

Uric acid levels in healthy and diseased patients.

There is variability in the normal and in the diseased population, and overlap between the two groups.

Some levels are therefore compatible with health or disease.

Imagine a test that screens people for a disease. ◦ Each person taking the test either has or does not

have the disease. ◦ The test outcome can be positive (predicting that

the person has the disease) or negative (predicting that the person does not have the disease).

◦ The test results for each subject may or may not match the subject's actual status – i.e. The test may lie

All tests can lie....... The trick is to

know when and why they lie....

True positive: Sick people correctly diagnosed as sick

False positive: Healthy people incorrectly identified as sick

True negative: Healthy people correctly identified as healthy

False negative: Sick people incorrectly identified as healthy

Each test will have it’s own strengths and weaknesses, and we can describe these.

All tests can lie.......

Sensitivity: the ability to recognize (rule in) the thing being tested for

Specificity: Precise – if it says the quality is present, then it is- able to rule out the thing being tested for

Test characteristics:

Population of mostly healthy people – your job is to find out who is sick

Population of mostly healthy people

Perfect test

A perfect test would be described as 100% sensitive (i.e. predicting all people from the sick group as sick)

and 100% specific (i.e. not predicting anyone from the healthy group as sick)

Sensitive test

Highly sensitive tests don’t miss those who

have a disease. The trade off is they will be positive in people who don’t. These are false positive results

Sensitive test

Specific test

Highly specific tests won’t be positive in

the absence of disease. The price? Some who have it will escape detection. These are false negatives

Specific test

Sensitivity and Specificity are not independent. When you increase one, you often decrease the other.

False negatives delay diagnoses. False positives create them.

All testing is susceptible to both

Good at one usually means bad at the other!

Test results are categorized as: ◦ True or false positive, or true or false negative

all relative to a ‘gold standard’ (which may also be imperfect..)

If that wasn’t vague/confusing enough…

Gold standard is more accurate, but too slow, expensive or invasive to do as a first line test.

The false positive rate is not just a function of sensitivity and specificity.

It is dependent on the actual risks an individual has of having the disease and how common the disease itself is.

Pre-Test Probability

Thomas Bayes (1701 –1761)

What do you need the test to do?

10% of patients with acute MI fail to develop ST segment changes.

20-30% of ST↑ have no MI

Electrocardiogram (ECG)

N Engl J Med 2003;349:2128-35

‘Screening’ ECG He has ST elevation Should we send him to hospital at once?

20 yr old football player...

‘Monitoring’ ECG completely normal Cancel the cath?

70 yr old smoker in acute pain.

In CCU admitted for acute ischemia and waiting for a cath.....

What do you need the test to do?

~80% of cases will have a high WBC WBC is ↑ in up to 70 % of patients with

other causes of right lower quadrant pain

Only including ‘grey zone’ cases, it may perform less well than clinical judgement!

White blood cell count in diagnosing appendicitis

Fig. 1: Hypothetical probability density distributions of measured plasma brain natriuretic peptide (BNP) levels in 2 subgroups of a study population.

Victor M. Montori et al. CMAJ 2005;173:385-390

©2005 by Canadian Medical Association

Fig. 2: These hypothetical probability density distributions reflect a study population of middle-aged patients who all have recurrent asthma and chronic CHF. The patients whose

dyspnea is caused by asthma exacerbations look clinically similar to those whos...

Victor M. Montori et al. CMAJ 2005;173:385-390

©2005 by Canadian Medical Association

Your clinical assessment is still critical!

LR+ 2-5 LR+ 5-10 LR+ >10

LR- 0.5-0.2 LR- 0.1-0.2 LR- <0.1

Small changes Moderate changes Large changes

Small changes Moderate changes

Large changes

Likelihood Ratios (LR)Likelihood of a positive test result in a patient with the target disorder compared that in a patient without the disorder LR+ = Sensitivity/1- Specificity

LR-+ 1-sensitivity/Specificity

Victor M. Montori et al. CMAJ 2005;173:385-390

©2005 by Canadian Medical Association

Likelihood Ratios

The ‘power’ of the test /Likelihood ratios depends on what you thought in the first place.

Radiation/blood loss Unnecessary intervention Inappropriate reasurrance Confirmation bias Cost

Why is this a big deal?

‘one third of health care costs could be saved without depriving any patient of beneficial care’ Howard Brody, 10.1056/nejmp0911423 nejm.org

when should we not order

tests?

• When it doesn’t matter: Seasonal viral illness Prostate screening in >80 Surgical conditions in people not fit for surgery Minor facial fractures

When not to do tests

When pre-test probability is really low:◦ Clinical picture◦ Rare conditions and no risk factors

Spinning a coin to rule out malaria is a really sensitive test in Tuktoyaktuk

When pre-test probability is so low that any positive is more likely to be false than true…..

If you already know the answer◦ Repeating normal screens too early◦ OA in older patients

When not to do tests

When risk of investigation/treatment approaches risk of illness◦ Contrast medium◦ Radiation

When not to do tests

When the test can’t answer the question you need answered◦ CT scan for cerebellar disease◦ Lumbar/cervical spine x-ray for ‘sprains’◦ Sinus x-rays

When not to do tests

When the evidence recommends against it! e.g. 'Ottawa rules’

Evidence-based guidelines suggest that: ◦ We should tailor screening to individual patient

health profiles and move to "opportunistic" screening

• We should screen only for conditions that: Cause serious illness or functional difficulties, and only when an accurate test and effective treatments

are available.

http://www.cfhi-fcass.ca/publicationsandresources/Mythbusters/

Cadman D et al. JAMA 1984;251: 1580-1585.

Screening:

Forcing function: we should ask ourselves BEFORE ordering a test:

• What will I do if the result is •+ve?•-ve?

• Will it improve the management of my patient?• What is the benefit related to the cost?

Or,

Ask yourself if you are being…

‘I’m going to do a test to supplement my clinical impression’

‘I’ll just do all of the tests and see what you might have’

Discussion:

Discussion:

26 yr old female Dysuria, frequency, suprapubic discomfort Afebrile, no back pain, N/V. Has had previous UTI’s – pretty much the

same..

Our options:◦ Urine dip?◦ Microscopy?◦ Culture?◦ Empiric treatment?◦ Treat only if Positive test?

Example: Urinary tract Symptoms

Four symptoms and 1 sign increased the probability of UTI:◦ dysuria LR, 1.5 ◦ frequency LR, 1.8◦ hematuria LR, 2.0◦ back pain LR, 1.6◦ costovertebral angle tenderness LR, 1.7

Four symptoms and 1 sign decreased the probability of UTI: ◦ absence of dysuria negative LR, 0.5; ◦ absence of back pain NLR, 0.8; ◦ history of vaginal discharge NLR, 0.3◦ history of vaginal irritation NLR, 0.2◦ vaginal discharge on examination NLR, 0.7

Review in JAMA of the value of Hx and Physical exam to investigate UTI..

JAMA. 2002 May 22-29;287(20):2701-10.

2 most powerful signs/symptoms - history of vaginal discharge and history of vaginal irritation◦ Neg LR of UTI when present (LRs, 0.3 and 0.2,

respectively).

Using combinations of symptoms:◦ LRs 24.6 for the combination of dysuria and

frequency but no vaginal discharge or irritation.◦ In patients with recurrent UTI one study found

that self-diagnosis significantly increased the probability of UTI (LR, 4.0).

JAMA. 2002 May 22-29;287(20):2701-10.

Reasonable to rule in infection, but not better that clinical judgement.

Not good enough to rule it out.◦ 57-96% sensitive and 94-98% specific for

identifying pyuria

What about urine dip?

Emerg Med J. 2003 Jul;20(4):362-3. Am J Med. 2002 Jul 8;113 Suppl 1A:20S-28S.

Ann Emerg Med. 1989 May;18(5):560-3.

◦ In women who present with >1 symptoms of UTI, the probability of infection is ~ 50% Physical exam, and tests are not able to lower the

post-test probability to a level where a UTI can be ruled out

◦ Specific combinations of symptoms raise the probability to >90%, effectively ruling in the diagnosis based on history alone.

CONCLUSION (UTI):

JAMA. 2002 May 22-29;287(20):2701-10.