Table 3 Illustrative examples of the use of DSF for different types of interventions

Clinical guidelines for pharmacotherapy

• Clinical guidelines for pharmacotherapy to treat a range of chronic diseases have been developed, implemented and refined as new compounds have reached the market and new evidence has been gathered about the relative benefit of different medications.

• The influences on prescribing practices exist at the patient level (preferences and predictors of response), clinician level (practice patterns, level of training), system level (formulary design, insurance coverage, adherence monitoring).

• Each influence will impact guideline implementation and overall benefit of care for patients served within the health system.

• Assessing appropriate fit between guidelines and the care setting will require analysis of multiple streams of data, including administrative, clinical, organizational and epidemiologic.

• The DSF suggests that collecting benchmarks over time on patient outcomes, adaptations in algorithms used, available evidence (from the literature, healthcare systems and patient populations), and contextual factors could result in improvements to the guidelines, to the capacity of the health system to more seamlessly integrate the guidelines, to the ecological system that could improve access, quality and health outcomes.

Psychotherapy for mood disorders

• Manualized evidence-based psychotherapies for mood disorders have been tested in numerous studies.

• Many of these therapies are designed to be delivered by specific providers, over a set number of sessions, with a clear step-by-step approach.

• Given variation in access to therapy (e.g., number of sessions covered, availability of therapists, time), limited predictive ability of response (how many sessions are needed, what are active ingredients, who should deliver therapy?), emergent options for mode of delivery (web-based, face-to-face, self-guided, asynchronous), optimizing psychotherapy for individuals and systems is still beyond our current knowledge base.

• The DSF suggests manualized psychotherapy could be improved by tracking variation in use and therapeutic response of patients, contextual characteristics that influence delivery, and additional interventions that affect clinical and functional outcomes.

• Systems could track how patients respond to varying doses of therapy, modes of delivery, and clinician characteristics. Over time, decision-makers could align available care to the needs of patient populations, and clinicians could adapt practice patterns to data on patient preferences and outcomes, and general needs of the patient population.

• By assessing the fit of psychotherapy delivery with patients, the service setting and the broader ecological system, the DSF hypothesizes that new insights about psychotherapy optimization could drive improvements in patient care.

Care management for chronic diseases

• Studies have shown the effectiveness of care management strategies to assess, intervene and monitor for a range of chronic conditions.

• Typical strategies involve initial screening, assessment, treatment planning, care and self-management strategies, and follow-up.

• While general care management approaches seem to be durable, specific approaches can have difficulty being implemented across many clinical and community settings, because of limitations in resources (both monetary and staffing), information systems, financing processes, and other barriers.

• With new technologies, additional evidence about treatment and preventive interventions, and reconfiguration of care systems, care management for chronic diseases can be sustained and improved in a large variety of care settings.

• Care management is influenced by drivers at patient, provider, organization and system levels.

• Care management requires coordination among multiple people, organizational supports and capital resources, all of which will likely shift over time.

• Therefore, care management cannot be sustained without continual assessment of fit within the local setting and the support of the components of the model.

The DSF hypothesizes that attention to local adaptations made by healthcare and community settings to fit the model; and feedback on staffing levels, intensity of care management, emerging interventions and patient outcomes could enhance long-term sustainability and model improvement.

• Evidence about who benefits most from different variants of care management, who is an ideal care manager, and what are the best ways of coordinating across primary care and specialty practice could lead to better uptake and improve patient health.