I was recently in a conversation about the measurement tools used to determine a patient's functional ability. Mark Werneke shared an article that was published a few years ago to help me better understand the types of measurements available.
I've decided that when it comes to learning the outcomes of your care, you first need to know what it is that you plan on doing with the data.
Let's say you need to know what seems to improve quality of life more: surgical intervention or rehabilitation services? Or do you want to compare quality of life improvement of a community based program to an outpatient service? General health related quality of life measures will be your first choice. Now there is a down-side to this kind of measure. Based on the name of this measure, realize it is very general in nature. The improvement that you see through your services may not actually be fully captured by this type of measure. Typically this measure has multiple components of health. The measure may include physical function, mental status, social well-being, pain, co-morbidities and emotional status. In other words it considers aspects within the various entities defined in "health."
If you need to compare options based on what changes for the patient in terms of quality of life and the length of life, then you need a health utility measure. A health utility measure seems quite broad in nature and from my perspective provides a snap shot of the patient's life. It seems bare minimum when thinking about all the things a body can potentially do. In other words, it seems to focus on the bare minimum requirements of function. The goal of a health utility measure is to calculate the cost associated with various procedures and to compare the quality-adjusted life years from an economical perspective.
In the musculoskeletal world, you can choose an outcome measure for a defined joint. In the below article, the focus is on the shoulder. Although the article mentions the measurements as "general," to me they are joint specific measurements. The joint specific measurements mentioned are not wholely focused on functional ability. The measurements shared may include some objective examination findings along with capturing pain level and even satisfaction. Because these measurements include more than just a patient's self-report of function, the tools really aren't completely focused on functional ability. The measures are used to capture change. If you need an outcome measure to capture the change that occurred, when you choose the measure, you also need to know the psychometric properties. You want to know the validity, reliability and the responsiveness to change. Another important factor to know is the minimum clinically important difference (MCID). This is important because a change in score outside of the MCID indicates change that is relevant to the patient (positively or even negatively).
The last type of outcome measure to consider in the musculoskeletal world is a condition specific measure. Examples of condition specific measures for the knee are the Western Ontario and McMaster Universities Osteoarthritis Index and Lysholm Knee Scoring Scale. The abstract shares a few specific to the shoulder. The condition specific measures may not be completely focused on function. The condition specific measures may bring the special symptoms or patient complaints into the measure. It seems the majority of condition specific musculoskeletal measures were designed with surgeons in mind - to capture the before and after patient presentation. In other words, it seems to me the condition specific measures help answer the question of whether the surgical intervention resolved the patient's symptoms and complaints. I don't know if the measure is better than a joint specific measure or not.
The abstract introduced the concept of computer adaptive testing (CAT) as the final option. The example provided was Patient-Reported Outcomes Measurement Information System (PROMIS). You can try the PROMIS CAT here. Although the article mentions an upper extremity CAT, the demo page does not have that as an option and only has the physical function CAT. This CAT is a general CAT, meaning it is not joint specific and is focused on general physical function. Take the CAT and you'll see.
FOTO has research supporting its shoulder functional status items and computer adaptive testing. In 2006, the number of items originally tested was 60. Factor analysis only supported 42 of the items. The item pool was decreased to 37 items to fit the item response theory model. Pretend you have a shoulder problem and take FOTO's shoulder CAT. You can compare and see the difference between the general PROMIS CAT and the joint specific shoulder CAT that FOTO offers.
Below you will find a quick view of the abstract.
The effective evaluation and management of orthopaedic conditions including shoulder disorders relies upon understanding the level of disability created by the disease process. Validated outcome measures are critical to the evaluation process. Traditionally, outcome measures have been physician derived objective evaluations including range of motion and radiologic evaluations. However, these measures can marginalize a patient's perception of their disability or outcome. As a result of these limitations, patient self-reported outcomes measures have become popular over the last quarter century and are currently primary tools to evaluate outcomes of treatment. Patient reported outcomes measures can be general health related quality of life measures, health utility measures, region specific health related quality of life measures or condition specific measures. Several patients self-reported outcomes measures have been developed and validated for evaluating patients with shoulder disorders. Computer adaptive testing will likely play an important role in the arsenal of measures used to evaluate shoulder patients in the future. The purpose of this article is to review the general health related quality-of-life measures as well as the joint-specific and condition specific measures utilized in evaluating patients with shoulder conditions. Advances in computer adaptive testing as it relates to assessing dysfunction in shoulder conditions will also be reviewed.
World J Orthop. 2014 Nov 18;5(5):623-33. doi: 10.5312/wjo.v5.i5.623. eCollection 2014 Nov 18.