Foundations for PsyberCare-CD Development

The hallmark of an effective outcomes management system is a strong foundation in theory and research. When assessment scales developed for some other purpose are pressed into service as an outcomes measure, the data may be useful to evaluate program effectiveness but are not clinically actionable. They have little or no value in enhancing treatment because they provide no information useful to the clinician working with a specific patient. PsyberCare-CD is the best example of an outcomes management system whose measures were designed explicitly to support clinical decision making.

PsyberCare-CD was created in response to research that has repeatedly documented high relapse rates following treatment, high probability of re-entry into treatment and high incidence of dropout. Ineffective treatment leads to enormous human suffering and medical costs.

An effective program must address key questions for each patient:

• What services are most cost-effective for this patient?

• Is his/her treatment “working”; i.e., is the patient’s progress satisfactory?

• Is this person at high risk for relapse, and, if so, how can he/she be helped to maintain recovery?

PsyberCare-CD helps treatment programs to answer these key questions, and to improve outcomes through patient-treatment matching, concurrent monitoring, and assessment of risk for dropout and relapse.

Patient-Treatment Matching

There have been numerous attempts to match substance abuse patients to treatment programs. In view of the wide variability among programs and patients, it seems reasonable to pose the question raised by the Institute of Medicine after its review of alcoholism research: "which kinds of individuals... are likely to respond to what kinds of treatments by achieving which kinds of goals" (10).

The findings from studies that have attempted to improve outcomes by matching patients to programs were equivocal, due to methodological limitations (16). Project Match, an elegantly designed and well-funded study, was initiated by NIAAA to provide a definitive test of the matching hypothesis for alcoholism. The national, multi-site, randomized clinical trial involved over 1700 patients and addressed the methodological limitations of prior studies. Its conclusions were encouraging in relation to treatment effectiveness (patients experienced gains in each of the three modalities studied) but discouraging in relation to matching: of the ten matching variables studied, only one (psychiatric severity) was useful in matching outpatients to treatments (21).

In contrast, a five year NIDA-sponsored study of matching conducted by PsyberMetrics staff in collaboration with the University of Pennsylvania's Center for Study of Addiction found that outcomes could be significantly improved by matching patients to services, rather than to programs (18). The researchers discovered that numerous limitations on treatment referral made it impractical to attempt to match patients to programs. Nearly two thirds (62%) of the 186 patients in the initial study cohort could not be referred to the program considered optimal by their evaluator: limitations in insurance or HMO coverage precluded placement; the preferred program did not have a treatment slot or bed available; the patient insisted upon referral to the program most convenient in relation to their home or work; or the patient viewed the program negatively due to prior experience or that of a friend/family member. Even if it were technically feasible, the value of patient-program matching would be limited due to these non-clinical factors in referral.

Switching their focus, the research team developed and tested a procedure for matching patients to services (not programs), on the basis of their composite scores on the family, psychiatric, and employment subscales of the Addiction Severity Index (ASI). Threshold scores were established for each subscale, and the experimental group patients were provided with special services in each area where their scores exceeded the threshold. For example, those with elevated scores on the Family subscale received treatment focused upon family issues. Control group patients received standard care in the same programs.
Patients matched to services using this procedure achieved impressive outcomes in relation to unmatched controls. They were more likely to complete treatment (93% vs. 81%). Outcomes reported on the follow-up ASI (six months post-treatment) were uniformly more positive for the matched group (e.g., 35% of the control group patients had re-entered treatment, versus 24% of the matched group).

In summary, patients who received treatment directed towards their specific problems experienced significantly more positive outcomes than similar patients, treated in the same programs by the same therapists, who were not matched to services (18). The "matching" procedure developed under this research has been incorporated into PsyberCare-CD.

Concurrent Monitoring

Following the initial (intake) patient assessment, PsyberCare-CD provides for monitoring of patient progress during treatment. Monitoring concurrent with treatment provides clinically actionable data to providers; helps to identify persons who should be monitored post-treatment (i.e., high risk cases); and introduces monitoring as a routine component of the treatment process to improve compliance with post-discharge monitoring procedures.

PsyberMetrics co-founder Kenneth Howard, Ph.D., and his team at Northwestern University pioneered the use of concurrent monitoring as a tool for continuous quality improvement. This work has shown that data collected concurrently with treatment has direct clinical value and can also be analyzed to determine the likelihood that the current treatment will be successful (8).

Finally, concurrent monitoring promotes an organizational culture that values outcomes management. Providing therapists with actionable information helps to secure their full cooperation with a measurement system, which in turn is essential to the establishment of an organizational "culture of measurement" (4,3)

Assessment of Risk for Dropout and Relapse


PsyberCare-CD includes more than a dozen questions which prior research have found to be predictive of dropout or relapse. This information can be used clinically to assess the need for interventions (e.g., Motivation Enhancement Therapy, or Relapse Prevention) designed to reduce negative outcomes. The predictive validity research demonstrates the effectiveness of the system in identifying high risk patients.