Observation and Classification

Kepler's First Law: Planets move in ellipses with the Sun at one focus.

Kepler's First Law has applied to space scientists and astronomers since it was discovered over 430 years ago. Yet, Johannes Kepler didn't gather much of the data upon which he based his discoveries. Kepler was nearly blinded by smallpox before he was five years old.

As the Imperial Mathematician to the Holy Roman Emporer, Kepler couldn't quite see the stars he decribed in his first book, Astronomia Nova (1609), but he had faith in the measurements and in the observations of Tycho Brahe, his first patron and the man who generated much of the data for Kepler's initial insights.


Because of his eyesight, Kepler relied on Tycho Brahe's measurements of the stars and was able to derive equations that described the motion of the planets around the Sun. Keplers' Laws of Planetary Motion still hold today and are used for planning rocket launches and managing satellites in orbit. The word 'satellite' was coined by Kepler. Kepler's work is held in such esteem that he rates a page on NASA's website.

Kepler used observation and insight to create The Laws of Planetary Motion in an age before probability and computerized computation. His planetary tables...

"...used logarithms, which he developed, and provided perpetual tables for calculating planetary positions for any past or future date."

Observation and insight have generated tremendous discoveries in science, indeed, the entire Scientific Method is based on intial observations, predictions, hypotheses, measurements and tests.

Observation in Physical Therapy

The temptation to adhere to observation as the basis for physical therapy discovery in patient care is strong. What can treatment-based classification (TBC) offer more than your clinical observation when you can see, hear, smell, touch, taste (?) and talk to the patient right in front of you?

Some classification predictor variables predict an outcome like spinal manipulation success with 95% confidence. But the predictor variables are themselves uncertain - derived by dumping plausible tests into a 'hopper' (derivation study) and seeing what 'falls out'.

How can these statistically derived variables compete with the observation that the patient who says "I hurt" can feel better from your hands-on care? Who gets to decide what treatment is most appropriate?

Physical therapists on Soma Simple Discussion Boards demonstrate some of the controversy around TBC.

Why is it no surprise that even accomplished physical therapists have trouble wrapping their arms around classification? Peter Huijbregts, PT talks about his struggles with this paradigm shift in the Journal of Manual and Manipulative Therapy (2007):

"The once predominant mechanism-based classification system that is based on the premise that impairments identified during examination are the cause of musculoskeletal pain and dysfunction is increasingly being replaced by treatment-based classification systems.

In the treatment-based system, a cluster of signs and symptoms from the patient history and physical examination is used to classify patients into subgroups with specific implications for management."

People have always been uncomfortable with probabilistic systems, even among scientists. Some examples of probabilistic systems that have excited controversy and generated debate in the time since Kepler include the following:

1. Wikipedia vs. Encyclopedia Britannica
2. Free Market Economics vs. Central Planning
3. The Theory of Evolution vs. Religiosity
4. Google vs. what?

Probability implies that we are never 100% certain that the measurement describes the patient or the outcome - we can only know our level of confidence across samples of patients.

The Wikipedia Phenomenon (from The Long Tail)

Wikipedia articles have been described as 'amateur' or 'inaccurate'. However, a study done by the journal Nature found that Wikipedia averages 3.86 errors per article compared to 2.92 errors per article for Encyclopedia Britannica . Wikipedia article are corrected daily - as soon as the error is spotted. Encyclopedia Britannica articles only get corrected at new, printed editions - about every ten years.

Wikipedia has 13 million articles - Encyclopedia Britannica has just over 250,000. The chances that you will find an up-to-date article about something interesting in Wikipedia are pretty good. The Wikipedia article on 'Physical Therapy' is 4,659 words long. The Encyclopedia Britannica article on 'Physical Therapy' doesn't exist.

Growth Rate of Wikipedia Articles

Wikipedia is a probabilistic device that succeeds because it is useful to most of the people, most of the time. Encyclopedia Brittanica is an authoritative device that, until now, was our only option for encyclopedic information.

Authoritative Decision Makers

We still need authoritative sources like Encyclopedia Britannica but their dominance in information search is over. I recommend starting your information searches with Wikipedia and finding more authoritative sources as you delve deeper into your studies.

The ability of scientists to find amazing discoveries based on obsevation and insight has waned and so too has the dominance of physical therapists who insist that their palpatory and visual findings are superior to probabilistic tools like TBC.

Prediction of Risk

Another type of prediction physical therapists use can be called 'risk-adjusted prediction' where baseline data such as...

1. age
2. impairments
3. self-report scores
4. co-morbid factors like fear

are used to predict an outcome such as...

1. self-report change scores
2. predicted total number of visits
3. predicted total duration of care

Risk predictions are made by comparing your patients' baseline data to millions of similar patients in a database - your patient, whose characteristics match some of those patients in the database, is 'predicted' to get better, in scope and rate, like the patients in the database.

Risk-adjustment is not as cold and calculating as it sounds. Physical therapist J.W. Matheson believes he is a better physical therapist by using this tool.

"I find great value in this information and believe that it helps improve my communication and care of my patients.

We spend time during the initial evaluation discussing aspects of their risk-adjusted outcome data, and psychosocial yellow flags can be identified immediately.

More efficient care and utilization of staff and services is the end result."
(IMPACT June 2009 PPS log-in required)

For the non-mathematician/statistician (I am a 'non') it may feel like we are being asked to cede our decision-making control to algorithms and databases on 'faith'. Faith in the science and the statistics behind classification is what we fellow 'nons' are asked to trust.

Johannes Kepler trusted Tycho Brahe's data because he couldn't see. But, Kepler used Brahe's data to create better tools that predicted the future pathways of planets and allowed future space scientists and astronomers to see further than ever before.

What future pathways will physical therapists predict using probabilistic tools?

Physical Therapy Insight

You are confronted by the patient with intractable chronic pain – you’re the therapist – What do you do? What do you decide?

Bulletproof Physical Therapy Decisions presents your decision as the ‘skilled’ component of the physical therapy encounter. And there are two types of decision you can make.

Physical therapy decisions are dichotomized into two domains to draw attention to insight decisions – decisions that occur in the blink of an eye and can’t always be explained by logic or supported by data. Physical therapists have, historically, based many treatment decisions on insight and many patients have benefited from these treatments.

Non-Insight Decisions

Recent years have seen an explosion in physical therapy research into clinically relevant tests and measures like self-report, performance and classification measures.

Tests and measures that generate patient data by self-report, performance testing, classification and even ‘old school’ impairment-level measures are ‘obvious’ decision support tools and most are far better than what I had when I graduated with a 4-year Bachelors in Health Science in 1992.

Back then, you could explain your choice of a spinal traction treatment by pointing to the evidence from your examination:

• Signs of nerve root compression in the leg or arm such as
1. altered sensation
2. asymmetric reflexes
3. segmental motor weakness
4. unilateral muscle atrophy.

Now, we have classification predictor variables that indicate which patients will ’probably’ get better with a lumbar manipulation.

My Insight

Insight decisions are difficult to explain, hard to teach and challenging to document – why not manipulate a lumbar patient with 4/5 positive predictor variables for manipulation? What is it about his presentation that gives me pause? Is the manipulation worth the risk?

This lumbar patient also had a positive sciatic tension test and a positive cross leg sciatic tension test – tests these are not predictor variables for any classification category, not even ‘contra-manipulation’. Yet, these tests are sensitive and specific for lumbar herniated nucleus pulposis. The patient also had a lateral shift – which is a predictor variable for a direction-specific classification.

So, I had some tests that clearly pointed out why I shouldn’t manipulate and some tests that indicated the patient belongs in a different classification but why did I bother to examine those items in the first place?

One of the promises of a classification approach to physical therapy is its reliance on a parsimonious data set of predictor variables – fewest data are better. Therapists can quickly gather data on complex patients and allocate their clinical resources (eg: time) to do the most good. Presumably ‘the most good’ means better patient satisfaction, lower costs or improved outcomes using standard self-report measures.

So, insight decisions are an important source of clinical wisdom that is difficult to quantify and write down. Nevertheless, we ought to listen to our insight and, more importantly, study how those decisions are made so we can improve our teaching and documentation.

A Puzzle

Before I go on, I’d like to present an example of an insight puzzle.

This example is taken from Malcolm Gladwell’s bestselling book on decision making, Blink.

A man and his son are in a serious car accident.
The father is killed and the son is rushed to the emergency room.
Upon arrival, the emergency room doctor looks at the patient and gasps, “This child is my son!”
Who is the doctor?

The doctor is the child’s mother.

Most of us assume that the emergency room doctor is a man. Not all doctors are men – of course. Since the emergency room doctors’ gender is not explicitly stated in the puzzle to get the right answer we need to use our insight.

The Problem with Insight

Bulletproof is about how physical therapists can make better decision, primarily with better data, but also through insight – and write down their decisions to show skill, progress and need.

However, the very act of writing down your thought impairs your insight into the problem!

Psychologist Jonathan Schooler studied people’s performance on insight puzzles by interrupting their work and asking them to describe their thought processes – how did they reach their conclusions? What steps did they take? Did they make mistakes and start over?

He then repeated the experiment but this time he asked the subject to stop and write how they arrived at their insights.

With both experiments Schooler found that his subjects were able to answer fewer insight problems (Schooler calls insight problems ‘non-reportable processes’) when they were interrupted and asked to describe, verbally or in writing, their thought processes.

Schooler’s control groups were also interrupted and asked to stop working on their insight problems for the exact amount of time the experimental groups were asked to describe their thought processes.

The experimental groups, both verbal and written, were able to solve 30% fewer insight problems than the control groups. Schooler call this effect verbal overshadowing 121.

Face recognition is another area of study by those, like Dr. Schooler, who study insight.

I’m going to ask you to picture the face of someone you know, but not personally, say a famous movie star like Brad Pitt. You probably have his face in your mind right now. You can see his eyes, his hair, his chin. But, how accurately could you describe him to another person? Would they recognize Brad Pitt from your description?



By verbalizing your insight into facial recognition you weaken your insight. Face recognition and insight word problems are just two areas where insight has been shown to be impaired by verbalizing and writing 121.

What Implications do Overshadowing Have for Physical Therapists?

Plenty.

If you are comfortable and conversant with the leading edge of physical therapy practice (as of the writing of this book) in areas like treatment-based classification (TBC), performance measurement, self-report measurement, electronic documentation, alternative payment systems and Medicare compliance then you should have no trouble generating a daily note and a chart that accurately describes your interventions, patient need, expected progress and your skill level, even your insight decisions.

In 2006, when I bought out my private practice partners I was only peripherally involved in these issues. I was very much dependant on clinical insight, pattern recognition, heuristics and ‘rules-of-thumb’ to make decisions. If you are like I was then you should take heed…

The future of physical therapy will become increasing dominated by the clinicians’ ability to generate meaningful numbers (data) that justify our skilled interventions.

What about insight?

So where does that leave insight?

What about the valuable contributions made by legions of clinicians who came before we had of all these new, powerful probabilistic and predictive tests?

What about the patient in the example I gave earlier who presented with 4/5 predictor variables for manipulation and negative imaging studies? Why didn’t I manipulate him?

I can’t say for sure (since I had to write down my findings in the chart) but I suspected that he had an acute, torn disc. I gave him a Straight Leg Raise Test and then, on the opposite leg, I gave him a Crossed Straight Leg Raise Test – both were positive. The combination of these two tests, in populations with suspected disc injuries, is both sensitive and specific for herniated nucleus pulposus. I called his doctor and asked for a Magnetic Resonance Image (MRI). The results were positive.

What if I had manipulated him? What if I had not listened to my insight?

Medicare Demands Data

The standard of care in physical therapy in the United States is increasingly being provided by doctors of physical therapy practicing evidence-based medicine using clinical algorithms, classification and all the other tools just mentioned.

The prudent physical therapist is wise to incorporate these tools into her clinical examination, daily notes and complete chart.

How then can we preserve our insight yet create complete, compliant charts?

Here are five strategies I use to create a Bulletproof decision for my daily note and my chart.

Take Measurements Daily

I was taught to take measurements weekly or at least monthly. Now, when a patient fails a performance test the test becomes a part of the plan of care. For example, the Sharpened Rhomberg Test is an evidence-based measure used to predict falls and future institutionalization in elderly people. The test is valid and reliable and responsive to your clinical interventions. Why not, instead of just doing the technique, write down the score daily? Then you can show need (based on future falls risk) and change (based on the Minimum Detectable Change (MDC)).

‘Trust but Verify’

Classification decision-making is based on a parsimonious data set – that is, no test is used unless it is predictive and only predictive tests are used. The danger of a parsimonious data set is that patients aren’t data points – patients can’t be fully described with five (or seven or ten) predictor variables. Treatment (or non-treatment) risk may not be fully encapsulated by predictor variables.

For example, lower back pain patients often suffer from complexities and co-morbid conditions such as obesity, a sedentary lifestyle, various diseases and fear of movement. These patient often benefit with interventions that emphasize ‘spine sparing’ techniques, abdominal bracing, spinal stabilization and activity modification to identify provocative and easing factors of the pain. Some clinicians might call this approach a ‘stabilization classification’ yet, anecdotally, I have noticed that many lower back pain sufferers are older, stiffer and present in various stages of acuity. In short, few older patients satisfy most of the predictor variables for the ‘stabilization classification’.

Just like the manipulation patient I described earlier I measure all the stabilization predictor variables and use the classification decision rule as one of my tools – I make the final decision.

Put Goals up Front

I used to write goals because I had to – as long as the patient felt better I felt like I had done a good job. I didn’t understand the motivating effect goals can have on patient satisfaction. I also didn’t understand how important meeting functional goals is for a Medicare audit.

Now, we put a paper copy of our goals list on the front of the chart to refer to every treatment session.

In my clinic we co-treat our patients. I routinely delegate treatment to Physical Therapy Assistants who implement my Plan of Care.

1. Up-front goals are essential when flipping through a paper chart during a busy day.
2. Up-front goals keep everyone focused on what’s important – function.
3. Up front goals encourage the PTA to take daily measurements (see above).
4. Up front goals send a message to the Medicare auditor when the chart is audited that goals are important.

Spend face time with the patient

1. Insights happen when you least expect them – that’s what makes them insightful.
2. Insights happen when you are talking or listening to your patient.
3. Insights happen when you are reviewing patient data in the chart.
4. Insights happen when you are laying in bed that night remembering what else you could have done for your patient.

Yet, these insights rarely happen if you aren’t thinking about your patient or don’t remember your patient or never knew enough about your patient in the first place to understand her condition. To know these things we must spend face time with our patients.

Face time is good for your Medicare compliance program also – much time and talk have transpired at meetings, electronic list-serves and blogs about the one-on-one (constant attendance) requirements.

Here is an example of a recent answer to many of the questions about constant attendance asked in these forums:

“In the same 15-minute time period, one therapist may bill for more than one therapy service occurring in the same 15-minute time period where "supervised modalities" are defined by CPT as untimed and unattended -- not requiring the presence of the therapist (CPT codes 97010 - 97028). One or more supervised modalities may be billed in the same 15-minute time period with any other CPT code, timed or untimed, requiring constant attendance or direct one-on-one patient contact. However, any actual time the therapist uses to attend one-on-one to a patient receiving a supervised modality cannot be counted for any other service provided by the therapist.”

Spending your clinical time face-to-face with your patient will improve your compliance and your insight.

Write for posterity

Assume you may come back to read your own notes – or worse, someone else will. I am amazed when I go back and read some of my notes from 10 years ago – not much data.

My notes from three years ago, however (when I started Bulletproof), contain valid, standardized tests and measures on impairments, performance and self-reports.

Many of the tests I use reveal persistent impairments in ROM, strength, physical function and important self-reported activities – I have monitored one of my running patients from initial presentation of ‘trochanteric bursitis’ to ‘I-T band syndrome’ to’ torn anterior hip labrum’ over eleven years – all the while coaching and treating him so he could continue to run his marathons. I also advise him to cross-train on the cycle and in the pool.

The point is that his numeric data are remarkably stable – his values for, say, hip internal rotation ROM don’t change all that much over eleven years. His stiff right hip from eleven years ago is still his stiff right hip today.

Physical therapy helps him maximize his activities and the data I generate help me make decisions.

The Bottom Line

There is still room for insight in physical therapy – actually, the need is even greater since patients are more complex, the workflow busier, the risk higher and the decisions harder.

Insight, however, needs to be the last piece of the puzzle, the bottom line of a page full of data.

Classifying Physical Therapy, Nuclear Submarines and Cardiac Care Beds

The United States Navy had a problem. It was the early 1970’s and the height of the Cold War.

US Navy submarines were playing cat-and-mouse submerged reconnaissance with Soviet submarines in every ocean around the world. Nuclear submarines ran quieter, faster and longer than older, diesel subs and could submerge to new, record-setting depths. US Navy submariners were among the best trained, most highly motivated military men in the world.

Submariners, however, still got chest pain at the same rate as ordinary civilians.

Navy doctors had to decide, based on clinical findings, if the submariner’s signs and symptoms were serious enough to consider aborting the mission and seeking a friendly port.(Blink - Malcolm Gladwell)

Underwater heart attacks didn’t fare well outside of a hospitals’ intensive care unit.

That’s where Dr. Lee Goldman came in. Dr. Goldman was studying statistical rules – algorithms – that predicted when people were having a heart attack. Dr. Goldman’s rules predicted the occurrence of a major cardiac event based on three predictor variables:

1. Is the patients’ pain unstable angina?
2. Do you hear rales above the base? (indicates fluid in the lungs)
3. Is the systolic blood pressure below 100mm Hg?

Combinations of these predictor variables indicated different treatment options:

1. surface and give away your submarine’s position to the enemy but save your submariner’s life
2. sit tight and monitor your submariner’s vital signs or
3. send your submariner back to work with a bottle of Pepto-Bismol.

Navy doctors studied these treatment algorithms and used them in the care of their sick submariners. At one point, military physical therapists led their civilian cousins using evidence-based medicine in decision making, ordering radiographs and making referrals to other health care professionals.

While the US military lead the way in the early 1970’s in using clinical prediction rules the American health care community responded to Dr. Goldman’s work with deafening silence. (Gladwell)

American Doctors Make a Decision

It wasn’t until 1995 that American doctors began to use decision rules to inform the care of their patients. The best example on record comes from Cook County Hospital in Chicago. (Gladwell)

This 700-bed urban teaching hospital is a century-old, publicly-funded institution that was seeing thirty new chest pain patients per day in its emergency room and 79% of them were getting a full work-up for chest pain.

Patients were admitted to one of two wards for hospitalized chest pain patients:
• eight coronary intensive care beds or
• twelve telemetry-monitored coronary beds.
The coronary intensive beds cost $2,000 per bed per day and the telemetry-monitored beds cost $1,000 per bed per day.

Ironically, only 5-10% of the patients admitted to the hospital suspected of having a heart attack progressed to a full-blown heart attack. The hospital’s problem was that they were spending expensive resources on patients who were not having a heart attack.

The hospital’s chairman of the Department of Medicine, Dr. Brendan Reilly, wasn’t worried about the quality of care – the quality was good. Dr. Reilly was worried about the cost of providing cardiac care to patients who weren’t having a heart attack. He began studying the decision-making processes used by the emergency room doctors caring for patients with chest pain.

Ironically, the initial response from the ER doctors was reluctance and resistance – how can Dr. Goldman’s algorithm allocate intensive care bed space better than ER doctors’ decisions? What about family history? What about weight, sex, race, smoking history, stress and many other factors considered important at the time in the diagnosis of heart attack?

What Dr. Reilly found out was that race, gender and lifestyle factors were less important than whether or not the doctors followed the algorithm. Not that these factors were unimportant in the overall care of the patient – just that the initial decision to allocate the expensive, intensive care bed was better made by adhering to the algorithm, not to the host of factors that, while important, were incidental to the initial decision.

Dr. Reilly studied the impact of using the Dr. Goldman’s CPR in the Cook County ER. He found that the efficiency, the rate at which patients not having a heart attack were sent to inexpensive observation or sent home, went from 21% to 36%. Dr. Reilly also found that safety, the rate at which patients having a heart attack were triaged to coronary intensive care, went from 89% to 94%.

Just as the submariner’s doctor had to make a quick, initial decision that balanced the risk of giving away the submarine’s position with the risk that the submariner would progress into a full-blown heart attack so too did the Cook County ER doctor have to make a decision that balanced the risk that Cook County would spend $2,000 per night for up to three nights on a patient with acid indigestion versus the risk that the patient was having a heart attack.

Classifying submariners was a clinical 'shortcut' that enabled the submarine to stay submerged in those cases that were not clearly a major event. Classifying chest pain patients in Cook County was a clinical 'shortcut' that prevented spending thousands of dollars on people with tummy gas.

Classification as a Resource Allocation Tool

Both the submarine and the cardiac beds examples treat classification as the solution to a resource allocation problem. Both scenarios were prompted by crises of scarcity. Dr. Reilly at Cook County finding fewer public funds to pay for critical care cardiac beds as emergency room admissions rose and the US Navy facing a trade-off between dying submariners and national security.

American health care is facing its own crisis of scarcity as rising rates of per-capita health care consumption, the tidal wave of aging baby boomers and budget constraints on increased health care spending impose resource allocation challenges on increasingly scarce physical therapy resources, like time and money.

Classification, however, is not the appropriate tool for every clinical decision faced by physical therapists. As noted, classification is probably appropriate only for the initial treatment assignment and may not describe the exact treatment to be used. For example, the spinal traction classification is useful in cases of non-centralizing leg pain of radicular origin but the decision rule does not give information as to the parameters of spinal traction: force, total time, ramp time, or patient position.

Classification is probably most useful when one or more discrete alternative treatment possibilities exist, eg: lumbar manipulation or stabilization. Presumably, not both. Classification is probably not helpful in straightforward PT decision-making such as an uncomplicated ankle sprain. There needs to be some risk that making the wrong choice will produce worse outcomes or a less efficient clinical process.

For example, if the Navy doctor incorrectly diagnoses a heart attack and the submarine captain decides to surface en route to a friendly seaport it reveals its position to enemy radar and US national security could be compromised.

The submarine and cardiac beds examples offer illustrations of risk that are far more clear-cut than physical therapists would typically encounter in the clinic. It seems obvious that clinical prediction rules developed by Dr. Goldman and others were utilized earlier in these environments because of increased risk and greater costs involved.

Classification as Diagnosis

The physical therapy profession is currently shifting towards Treatment Based Classification (TBC) using clinical prediction rules (CPR) for diagnostic and treatment decision-making.

Unlike the physician profession, the physical therapy community seems almost uniform in its acceptance and embrace of classification measures as an aid to clinical decision-making. (Gladwell, Groopman in How Doctors Think)

An understanding of probability is required to fully understand the use of statistically-derived predictor variables. For example, the Fear-Avoidance Beliefs Questionnaire (FABQ) is a predictor variable for the manipulation classification while plausible findings like pelvic landmarks and sacroiliac region pain are not predictor variables. How can this be?

The derivation studies that identified the original predictor variables tossed out biologically plausible tests and measures instead showing us the true predictors of patients likely to respond to lumbar spinal manipulation.

Not leg length inequality, not mechanism of onset, not MRI or x-ray findings, not pelvic landmarks or pelvic movement tests. Instead, some surprising findings turned out to show physical therapists who should be manipulated:
1. Time since onset (> 2 weeks)
2. Extent of distal leg pain (not past the knee)
3. Lumbar hypomobility
4. FABQ work sub-scale >19 points
5. No hip ROM asymmetry

If, on average, manipulating your patients is a coin flip (about 50% get better, 50% don’t get better), then application of the CPR improves your chances to 68% for patient who have any 3/5 of the predictor variables. Your chances improve to 95% if the patient has just one more of the predictor variables.

Classification as Probability

Probabilistic decision-making is consistent with the hypothetico-deductive model that is associated with physician decision-making, prescriptive medicine and the patient’s role emphasizing ‘compliance’ over ‘collaboration’. As such, classification seems to shift traditional physical therapist decision making way from its ‘collaborative’ roots.

Will this shift threaten the intimacy that physical therapists have come to treasure with our patients?

Is intimacy sacrificed when decisions are made quickly?

Will physical therapists continue to consider patient-centered factors such as culture, social class, age, experiences and goals when applying clinical prediction rules? Just like the Cook County ER doctors who felt that the chest pain CPR ignored too many important factors in the ongoing care of their patients so too can TBC ignore important aspects that impact the ultimate physical therapy outcome.

Will CPRs allow therapists to quickly deliver routine aspects of care that are best made by statistics, like initial group allocation? Then physical therapists can focus on face-to-face interactions that engage patients’ emotional involvement in their own care.

Classification Success

Nothing succeeds like success and classification has succeeded in capturing the imaginations of educators, researchers and clinicians within physical therapy because of clinical successes and because of several well-designed studies published in prestigious medical journals.

Classification of spinal pain patients has crystallized an incoherent field of data into five or fewer examination findings per group. Classification has revolutionized physical therapy education and empowered students and experienced clinicians to become better decision-makers.

Questions remain:
1. Can classification change physical therapist behavior?
2. Can classification change physical therapy outcomes?
3. Are classification groups mutually exclusive and exhaustive? 75
4. Are some manipulation patients also candidates for stabilization?
5. Can some findings be treated that are not measured by classification predictor variables?
6. Can one patient fit the criteria for more than one diagnostic label?

Is classification good for documentation?

Aside from the risk that classification will change the interaction of patient and physical therapist to a less intimate relationship that is more typical to that of patient and physician I have concerns that classification will be used as a panacea for documentation; the clinical ‘shortcut’ will become a note-writing shortcut that leaves the physical therapist exposed to a Medicare audit because she has not adequately expressed her skilled decision in writing at every follow-up visit.

The 'Old School' case for impairments

Call me 'old school'... (some folks have called me that, and more).

I still treat some impairments - it's how I was trained.

There is a certain amount of satisfaction in measuring a stiff joint, fixing it with my 'old school' physical therapy techniques and getting the patient better.

It makes sense.

Today, however, physical therapists measure patient characteristics that predict the treatment the patient should get.

We don't measure as many impairments anymore. Some of the measurement are not even 'physical' - now we measure 'fear of movement'.

These new measurements are better because they are predictive of the patient's ultimate outcome whereas impairments (eg: ROM, strength, etc.) generally aren't predictive of outcomes.

The new way makes sense, too.

Teaching an Old DogWell, this 'old dog' can still learn some new tricks, like...

• classification
• clinical prediction rules
• outcomes scales
• disablement models
• computer adaptive testing
• alternative payment systems

None of these concepts were taught in PT school in 1992 and, ironically, they weren't taught in any of my 'old school' continuing education courses at 'Marriott U.'

The New School

A new article in April's JOSPT shows, however, that some impairments are still worth measuring - BECAUSE they may be predictive of the patient's ultimate outcome.

Lentz, Barabas, Day, Bishop and George showed that the flexion ROM variable was the strongest contributor to shoulder function in a model that included variables such as...

• duration of symptoms
• sex
• age
• mechanism of injury
• average pain intensity
• flexion ROM
• Tampa Scale of Kinesiophobia

So, my 'old school' training may still be useful after all!

The Outcomes

While shoulder flexion ROM was the strongest contributor to shoulder (dys)function

"...the immediate clinical relevance of these findings was unclear."

In other words, does improving shoulder flexion ROM with my 'old school' PT techniques (stretching, joint mobs, manipulation, cranio-sacral (not), whatever...) lead to better outcomes?

Physical therapists are still looking for the most parsimonious measurements that will predict outcomes for patients.

Are impairments still on the list?

Is your physical therapy 'cookie cutter'?

I appears that a 'cookie cutter' approach to therapy services is not a unique problem to physical therapists.

This post by Kori E. Carson Dean, Ed.S states the problem of the 'one-size-fits-all' approach to therapy services as it applies to special education.

Apparently, Occuptional Therapy (OT) and special education services have 'rules, laws practices' that adhere to the philosophy of the Individuals with Disabilities Education Act.

These professionals also seem to approach professional autonomy in the same way that physical therapists approach the Doctor of Physical Therapy (DPT):

"The therapist is correct that a (medical) doctor cannot dictate the amount of service time the therapist is required to provide."

Since much of current physical therapy research is focusing on the question of classification and treatment group assignment I am inclined to ask:

"At what point do standardized 'treatment groups' become a 'cookie-cutter' approach?"

The Functional Classification of Neck Pain

Orthopedic physical therapists need to read this clinical practice guideline from the September 2008 issue of JOSPT.

In addition to using the International Classification of Functioning as the basis for clinical physical therapy decision-making the authors describe, in one place, many of the the tests and measures used to assess cervical impairments.

Especially useful is Table 4 which links subjective and evaluation data to interventions used during treatment.

Not only is Table 4 useful for clinical decision-making but could also be used to support 2 of the 3 criteria for Bulletproof Physical Therapy Charts and Notes

1. Medical Necessity for Physical Therapy
2. Skilled Physical Therapy (decision-making)

Written measurements of impairments are 'evidence' for a staff physical therapist to argue their case in the event of an unfavorable Medicare audit.

I recommend using high-quality, evidence-based guidelines such as this one to support not only excellent clinical decisions but also to support your Medicare compliance program.

For more information go to BulletproofPT.com.

The Physical Therapy Value Proposition

I've received notice that my value proposition is not as clear and logical as I thought it was.

My thanks to Larry Benz, PT Selena Horner, PT and Mark Schwall, PT for commenting on several of my last posts.

I'll try again.

Physical therapists measure patients:

• ROM
• strength
• extremity girth
• difficulty with activities (OPTIMAL)
• Fear-Avoidance Beliefs
• isometric lumbar extension strength
• the list goes on...

The measurements and the interpretation of these measurements is all that separates physical therapists from other professions that do many of the same interventions we do:

• specialized exercise by personal trainers
• massage by massage therapists
• spinal manipulation by chiropractors and osteopaths
• ultrasound and electric stimulation by athletic trainers
• splint and orthotic fabrication by orthotists and occupational therapists

Going forward, my recommendation is that physical therapists hang their hats on simple physical therapy measurements as the value proposition to the consumer.

Consumers like value.

Consumers include the following:

• Patients
• Insurance companies
• Medicare
• Industrial work places
• Schools
• Military

The value created in the exchange between the patient and the physical therapist is information.

Simple measurements create information which is valuable.

I'll give one example...

You measure a weak external rotator muscle and advise the patient that overhead lifting or throwing sports are risky because the likelihood of impingement and eventual tear is increased.

You have created new information that did not exist prior to your exchange with the patient.

You have demonstrated the medical necessity for physical therapy.

You have demonstrated skilled physical therapy.

Physical therapists need to take more measurements of their patients in order to create additional value during the exchange.

Outcomes are one type of measurement. The OPTIMAL is an outcome measure.

But measurements are also predictive. Measurements taken during the evaluation help the physical therapist select interventions and set long term goals.

Measurements allow physical therapists to classify patients.

Measurements allow the physical therapist to make a physical therapy diagnosis and, ultimately, a prognosis.

Without measurement there is no value in physical therapy.

APTA Endorses World Health Organization ICF Model

The American Physical Therapy Association (APTA) recently endorsed the new World Health Organization (WHO) International Classification of Functioning, Disability and Health (ICF) Model.

I doubt most physicians consider disability when making a physical therapy referral.

Most medical doctors consider pathology first.

The first line intervention for pathology is usually pharmaceuticals.

Disability , and the physical impairments that lead to disability, is better addressed through physical therapy interventions such as Therapeutic Exercise (CPT 97110), Manual Therapy (CPT 97140) and other active interventions.

In the new model Impairments are replaced with 'Body Function & Structure'.

Functional Limitations are replaced with 'Activities'.

Disabilties are replaced with Participation.

Physical therapists are usually pretty familiar with the concept of disablement.

Medicare, in the United States, specifically pays physical therapists to treat disability, not pain.

The Orthopedic Section of the APTA is using the new ICF model to "Develop Evidence-Based Practice Guidelines for Treatment of Common Musculoskeletal Conditions".

The 'potential benefits of the project are to identify appropriate outcome measures'.

Currently, Medicare recommends the OPTIMAL scale for outcomes in outpatient physical therapy.

Watch OPTIMAL videos to use it for Medicare long term goal setting.

Physical Therapy and the International Classification of Functioning and Disability

The Orthopedic Section of the APTA (and others, I assume) is attempting to link 'academic physical therapy' - typically viewed as too esoteric - with clinical physical therapy with a new model of describing common conditions seen in physical therapy patients.

The Orthopedic Section has a position statement on the following topic...

Use of the International Classification of Functioning and Disability (ICF) to Develop Evidence-Based Practice Guidelines for Treatment of Common Musculoskeletal Conditions

Joseph Godges, DPT, MA, OCS
Coordinator, ICF-Based Clinical Practice Guidelines

James J. Irrgang, PT, PhD, ATC
Orthopaedic Section President

The details are preliminary but the final goal is to guide physical therapy decision-making.

For example, how should a student physical therapist classify a patient with a physician's diagnosis of 'frozen shoulder? The ICF Shoulder Guidelines can instruct the new graduate how to perform the evaluation and diagnosis.

The ICF Lower Back Pain Guidelines are complicated and focus heavily on classification.

Physical Therapy Diagnosis can do much the same for lower back and lower quarter dysfunction using the SIMPLE system (details at www.SimpleScore.com).

If classification can guide daily treatment decisions then I encourage the new graduate and the 'old school' physical therapist to learn the ICF model.

The SIMPLE (Summary of Impairments of the Lumbar Spine and Extremities) system provides much the same in a more intuitive manner.

Link your measured impairments with the patients' self-reported functional limitations in order to improve your decision making.

More people will get 'more better' if you make it easy for them.

Physical therapy should be simple.