Time to rethink the design of shared decision making tools to include diagnostic probabilities?
We were delighted to read Berger and colleagues’ analysis of shared decision making (SDM) for diagnostic decisions, an important issue in this era of overdiagnosis and overuse [1]. We agree with the authors that diagnostic decisions represent a unique decisional process before deciding about treatment options [2]. However, we also believe that integrating diagnostic information in SDM tools is essential.
The rationale behind this suggestion is that the probabilistic nature of diagnosis is by itself the first step before guiding patients into treatment decision making. For example, surgery for the knee meniscal tears is increasingly recognized as an overused low-value option for degenerative knee pain [3]. The first step leading to an orthopedic consultation is often a magnetic resonance imaging to diagnose a meniscal tear. Yet, almost one third of all adults will have evidence of a meniscal tear on this imaging test, most of which are asymptomatic and certainly do not require surgery [4]. This is applicable to musculoskeletal disorders like knee, shoulder and low back pain.
Presenting diagnostic information to patients in an understandable manner is one of the most challenging parts of the SDM clinical pathway. In our current studies aiming to foster SDM in the context of prenatal screening for chromosomal abnormalities and fetal infections, we are providing diagnostic probabilities to couples along with screening options [5-8]. This work will provide data on the best ways to improve patients’ knowledge concerning diagnostic probabilities while guiding subsequent treatment decisions. Presenting diagnostic probabilities to patients may strengthen the overall treatment decision making process leading to successful SDM interventions. Only then will we be able to observe that no decisions about oneself is made without oneself!
1. Berger, Z.D., et al., Patient centred diagnosis: sharing diagnostic decisions with patients in clinical practice. BMJ, 2017. 359: p. j4218.
2. Stacey, D., et al., Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev, 2017. 4: p. CD001431.
3. Siemieniuk, R.A.C., et al., Arthroscopic surgery for degenerative knee arthritis and meniscal tears: a clinical practice guideline. BMJ, 2017. 357: p. j1982.
4. Katz, J.N., et al., The Value of History, Physical Examination, and Radiographic Findings in the Diagnosis of Symptomatic Meniscal Tear among Middle-Age Subjects with Knee Pain. Arthritis Care Res (Hoboken), 2016.
5. Portocarrero, M.E., et al., Use of a patient decision aid for prenatal screening for Down syndrome: what do pregnant women say? BMC Pregnancy Childbirth, 2017. 17(1): p. 90.
6. Lepine, J., et al., What factors influence health professionals to use decision aids for Down syndrome prenatal screening? BMC Pregnancy Childbirth, 2016. 16: p. 262.
7. Leiva Portocarrero, M.E., et al., Decision aids that support decisions about prenatal testing for Down syndrome: an environmental scan. BMC Med Inform Decis Mak, 2015. 15: p. 76.
8. http://www.decision.chaire.fmed.ulaval.ca/en/research/projects/pegasus/.
Competing interests:
No competing interests
15 November 2017
Simon Décary
Post-doctoral fellow
Samira Abbasgholizadeh Rahimi
Université Laval
2525, chemin de la Canardière Québec (Québec) G1J 0A4
Rapid Response:
Time to rethink the design of shared decision making tools to include diagnostic probabilities?
We were delighted to read Berger and colleagues’ analysis of shared decision making (SDM) for diagnostic decisions, an important issue in this era of overdiagnosis and overuse [1]. We agree with the authors that diagnostic decisions represent a unique decisional process before deciding about treatment options [2]. However, we also believe that integrating diagnostic information in SDM tools is essential.
The rationale behind this suggestion is that the probabilistic nature of diagnosis is by itself the first step before guiding patients into treatment decision making. For example, surgery for the knee meniscal tears is increasingly recognized as an overused low-value option for degenerative knee pain [3]. The first step leading to an orthopedic consultation is often a magnetic resonance imaging to diagnose a meniscal tear. Yet, almost one third of all adults will have evidence of a meniscal tear on this imaging test, most of which are asymptomatic and certainly do not require surgery [4]. This is applicable to musculoskeletal disorders like knee, shoulder and low back pain.
Presenting diagnostic information to patients in an understandable manner is one of the most challenging parts of the SDM clinical pathway. In our current studies aiming to foster SDM in the context of prenatal screening for chromosomal abnormalities and fetal infections, we are providing diagnostic probabilities to couples along with screening options [5-8]. This work will provide data on the best ways to improve patients’ knowledge concerning diagnostic probabilities while guiding subsequent treatment decisions. Presenting diagnostic probabilities to patients may strengthen the overall treatment decision making process leading to successful SDM interventions. Only then will we be able to observe that no decisions about oneself is made without oneself!
1. Berger, Z.D., et al., Patient centred diagnosis: sharing diagnostic decisions with patients in clinical practice. BMJ, 2017. 359: p. j4218.
2. Stacey, D., et al., Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev, 2017. 4: p. CD001431.
3. Siemieniuk, R.A.C., et al., Arthroscopic surgery for degenerative knee arthritis and meniscal tears: a clinical practice guideline. BMJ, 2017. 357: p. j1982.
4. Katz, J.N., et al., The Value of History, Physical Examination, and Radiographic Findings in the Diagnosis of Symptomatic Meniscal Tear among Middle-Age Subjects with Knee Pain. Arthritis Care Res (Hoboken), 2016.
5. Portocarrero, M.E., et al., Use of a patient decision aid for prenatal screening for Down syndrome: what do pregnant women say? BMC Pregnancy Childbirth, 2017. 17(1): p. 90.
6. Lepine, J., et al., What factors influence health professionals to use decision aids for Down syndrome prenatal screening? BMC Pregnancy Childbirth, 2016. 16: p. 262.
7. Leiva Portocarrero, M.E., et al., Decision aids that support decisions about prenatal testing for Down syndrome: an environmental scan. BMC Med Inform Decis Mak, 2015. 15: p. 76.
8. http://www.decision.chaire.fmed.ulaval.ca/en/research/projects/pegasus/.
Competing interests: No competing interests