Tracking Patient Progress: Outcome Measures That Matter
Level 3, Clinical application
In brief
Meaningful outcome measurement in integrated practice combines clinical markers, validated patient reported outcome measures such as PHQ 9, GAD 7, the Insomnia Severity Index and MYMOP, simple functional tests such as sit to stand, gait speed and grip strength, and behavioural measures such as steps or food records. Measures should be chosen for the patient’s goals, recorded at baseline, repeated at planned intervals and interpreted against the minimal change that matters.
How does a practitioner know whether a plan is working? Patients often report feeling better or worse, but impressions are shaped by recent events and expectations. Laboratory tests show some changes but not others; a patient’s HbA1c may improve while their fatigue does not. Measuring outcomes systematically, using a small number of well chosen measures, gives practitioners and patients a clearer picture and supports better decisions.
4 kinds of measure
| Type | Examples | Strengths |
|---|---|---|
| Clinical biomarkers | HbA1c, lipids, blood pressure, ferritin, liver enzymes, hsCRP | Objective; linked to disease risk |
| Patient reported outcome measures | Symptom, mood, sleep, fatigue and quality of life questionnaires | Capture what the patient experiences |
| Functional measures | Walking speed, sit to stand, grip strength, walking distance | Reflect physical capacity and independence |
| Behavioural measures | Steps, food records, sleep diaries, goal checklists | Show whether the plan is being followed |
A good measurement plan usually includes at least one measure from the patient’s perspective, not only laboratory values.
Validated questionnaires
| Measure | What it assesses |
|---|---|
| PHQ 9 | Depression severity |
| GAD 7 | Anxiety severity |
| Perceived Stress Scale | Perceived stress |
| Insomnia Severity Index | Insomnia severity |
| Epworth Sleepiness Scale | Daytime sleepiness |
| IBS Symptom Severity Scale | Irritable bowel syndrome symptom severity |
| Chalder Fatigue Scale | Fatigue |
| EQ 5D and PROMIS measures | Health related quality of life and specific domains |
| MYMOP, Measure Yourself Medical Outcome Profile | Patient chosen symptoms and activities, scored over time |
Patient generated measures such as MYMOP are particularly suited to integrated practice. Patients choose the symptoms and activities that matter most to them and rate them at each visit, which keeps the focus on their priorities and works across many conditions.
Simple functional tests
- 30 second sit to stand: the number of times a person can rise from a chair without using their arms in 30 seconds; reflects lower body strength.
- Gait speed: walking speed over a short distance; a strong predictor of outcomes in older adults.
- Grip strength: measured with a dynamometer; associated with mortality and used in sarcopenia assessment.
- 6 minute walk: distance walked in 6 minutes; reflects functional exercise capacity.
- Waist circumference: a simple, informative metabolic measure.
Choosing measures
- Match measures to goals. A patient whose goal is to sleep better should have a sleep measure; one with prediabetes needs HbA1c.
- Keep it small. 2 to 4 measures are usually enough. Measurement burden reduces completion.
- Use validated tools where available, so that change can be interpreted.
- Include the patient’s perspective.
- Record a baseline before starting interventions.
- Plan when to repeat, aligned with when change is expected.
Interpreting change
Not every change is meaningful. Measures vary from day to day, and small changes may reflect noise. Many validated questionnaires have an established minimal clinically important difference, the smallest change that patients perceive as meaningful. Laboratory tests have analytical and biological variation. Interpreting change in light of these reduces the risk of over reacting to random fluctuation or missing genuine improvement.
Trends over several measurements are more informative than a single comparison. Graphing a patient’s scores over time often makes patterns clear to both practitioner and patient.
Using data with patients
Sharing measurements helps patients see progress they might otherwise overlook, particularly when improvement is gradual. It also makes setbacks visible and discussable. Measures should be presented as information for shared decision making, not as grades.
Measuring practice, not just patients
Aggregating anonymised outcomes across patients allows practitioners to evaluate their own practice: which approaches seem to help, which patients do less well and where changes are needed. This kind of audit is a foundation of quality improvement and of honest claims about the value of integrated care.
A worked measurement plan
A 58 year old man with type 2 diabetes, knee pain and poor sleep chooses his priorities: walking without pain, better sleep and avoiding insulin.
| Measure | Baseline | 12 weeks |
|---|---|---|
| MYMOP: knee pain when walking (0 to 6) | 5 | 2 |
| MYMOP: activity, walking to the shops (0 to 6) | 4 | 2 |
| Insomnia Severity Index | 17 | 9 |
| HbA1c (mmol/mol) | 62 | 53 |
| 30 second sit to stand | 8 | 12 |
| Average daily steps | 3,200 | 6,500 |
Each measure moved meaningfully, and the patient could see progress on the things that mattered to him as well as on his blood tests.
What gets measured gets understood
Outcome measurement need not be complicated. A few well chosen measures, recorded at baseline and repeated at planned intervals, turn impressions into evidence, keep care focused on what matters to patients and allow practitioners to learn from their own work.
Outcome measure questions
What are patient reported outcome measures?
What is MYMOP?
How many measures should be used?
References
- Paterson C. Measuring outcomes in primary care: a patient generated measure, MYMOP, compared with the SF 36 health survey. BMJ. 1996;312(7037).
- Kroenke K, Spitzer RL, Williams JBW. The PHQ 9: validity of a brief depression severity measure. Journal of General Internal Medicine. 2001;16(9).
- Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD 7. Archives of Internal Medicine. 2006;166(10).
- Bastien CH, Vallières A, Morin CM. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Medicine. 2001;2(4).
- European Working Group on Sarcopenia in Older People 2. Sarcopenia: revised European consensus on definition and diagnosis. Age and Ageing. 2019;48(1).
- Studenski S, Perera S, Patel K, et al. Gait speed and survival in older adults. JAMA. 2011;305(1).
Continue your learning
Measuring what matters to patients
Tracking outcomes that matter to patients is part of IIFM’s 6 month Functional Medicine and Clinical Nutrition program, supporting evidence informed practice and continuous improvement.
This article is for the education of healthcare professionals. It is not a substitute for individual medical advice, diagnosis or treatment, and does not change any practitioner’s scope of practice. Regulation and guidelines differ between countries.