Psychiatric Annals

Editorial 

What We Need Is “Living Treatment Algorithms”

Jan Fawcett, MD

Abstract

This month's edition of Psychiatric Annals, guest edited by Jonathan Davidson and Kenneth Jobson, focuses on treatment algorithms and posttraumatic stress disorder (PTSD). It is both fitting and ironic that PTSD is selected as the subject of a treatment algorithm for this discussion. It is fitting because the ongoing war, the threat of terrorist attacks around the world and on our own soil, and the recent occurrence of natural disasters have increased the focus on the treatment of this condition in both military and civilian populations. It is ironic because the very nature of PTSD, with its chronic course and high comorbidity, makes it a particularly complicated condition to treat, with a wide array of target symptoms and related life problems.

This issue deals with one of the common problems in yielding benefit from treatment algorithms — getting clinicians to follow them and use them to increase the benefits of treatment. The apparent value of learning-based psychotherapies such as cognitive-behavior therapy and prolonged exposure therapy in the treatment of PTSD when the number of clinicians fully trained in these techniques is limited is a further barrier to the full application of the treatment algorithm. Other attempts to develop and use treatment algorithms in depression, mania and schizophrenia, such as the Texas Medication Algorithm Project, have found some difficulties in getting clinicians to use the recommended algorithm, despite some evidence for an increase in treatment effectiveness when the algorithms are followed. The problems of introducing new, evidence-based treatments are discussed by Dr. Ruzek in this issue.

One of the values of treatment algorithms is their ability to rapidly expose the lack of evidence and measured outcomes after patients have failed to respond to the first two to three recommended treatments. For example, in the PTSD algorithm in this issue, after initiating a selective serotonin reputake inhibitor, the dose is then increased to the maximum suggested dose. It is then suggested that for insomnia or nightmares, prazosin, trazodone, or low-dose amitriptyline be added. In Node 7, the authors state that most trials with medication for PTSD have tested the efficacy of monotherapy and, with the exception of atypical antipsychotics and prazosin, no trials have systematically evaluated the relative effectiveness of different augmentation strategies. This is true for many other algorithms in the area of depression and bipolar disorder. We look toward large studies currently under way to produce empirical evidence to support future treatment algorithms.

At this point, the clinician frequently finds the algorithm has run out of data-based recommendations for many patients. It is important to note that the treatment algorithm specifies the treatment duration required to evaluate the treatment effects and does make suggestions based on expert consensus. These treatment algorithms serve the purpose of driving the process of obtaining more outcome data on the use of augmentation tactics so that we can look forward to more advanced treatment sequence recommendations for many of the treatment-resistant disorders we treat.

Once the system creates enough pressure to obtain the data we need, which will require updating as new data becomes available, our treatment algorithms will become increasingly important for up-to-date effective practice and will become a clear benefit for our patients. We look forward to the day when the availability of treatment data yields “Living Treatment Algorithms” that we can access online to help us inform our treatments. Let's hope that the research will get done to allow this to happen soon.…

This month's edition of Psychiatric Annals, guest edited by Jonathan Davidson and Kenneth Jobson, focuses on treatment algorithms and posttraumatic stress disorder (PTSD). It is both fitting and ironic that PTSD is selected as the subject of a treatment algorithm for this discussion. It is fitting because the ongoing war, the threat of terrorist attacks around the world and on our own soil, and the recent occurrence of natural disasters have increased the focus on the treatment of this condition in both military and civilian populations. It is ironic because the very nature of PTSD, with its chronic course and high comorbidity, makes it a particularly complicated condition to treat, with a wide array of target symptoms and related life problems.

This issue deals with one of the common problems in yielding benefit from treatment algorithms — getting clinicians to follow them and use them to increase the benefits of treatment. The apparent value of learning-based psychotherapies such as cognitive-behavior therapy and prolonged exposure therapy in the treatment of PTSD when the number of clinicians fully trained in these techniques is limited is a further barrier to the full application of the treatment algorithm. Other attempts to develop and use treatment algorithms in depression, mania and schizophrenia, such as the Texas Medication Algorithm Project, have found some difficulties in getting clinicians to use the recommended algorithm, despite some evidence for an increase in treatment effectiveness when the algorithms are followed. The problems of introducing new, evidence-based treatments are discussed by Dr. Ruzek in this issue.

One of the values of treatment algorithms is their ability to rapidly expose the lack of evidence and measured outcomes after patients have failed to respond to the first two to three recommended treatments. For example, in the PTSD algorithm in this issue, after initiating a selective serotonin reputake inhibitor, the dose is then increased to the maximum suggested dose. It is then suggested that for insomnia or nightmares, prazosin, trazodone, or low-dose amitriptyline be added. In Node 7, the authors state that most trials with medication for PTSD have tested the efficacy of monotherapy and, with the exception of atypical antipsychotics and prazosin, no trials have systematically evaluated the relative effectiveness of different augmentation strategies. This is true for many other algorithms in the area of depression and bipolar disorder. We look toward large studies currently under way to produce empirical evidence to support future treatment algorithms.

At this point, the clinician frequently finds the algorithm has run out of data-based recommendations for many patients. It is important to note that the treatment algorithm specifies the treatment duration required to evaluate the treatment effects and does make suggestions based on expert consensus. These treatment algorithms serve the purpose of driving the process of obtaining more outcome data on the use of augmentation tactics so that we can look forward to more advanced treatment sequence recommendations for many of the treatment-resistant disorders we treat.

Once the system creates enough pressure to obtain the data we need, which will require updating as new data becomes available, our treatment algorithms will become increasingly important for up-to-date effective practice and will become a clear benefit for our patients. We look forward to the day when the availability of treatment data yields “Living Treatment Algorithms” that we can access online to help us inform our treatments. Let's hope that the research will get done to allow this to happen soon.

Authors

10.3928/00485713-20051101-01

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