We recognized the need, both in our field and in healthcare in general, for a robust, practical, and effective system to standardize care and to gather, analyze, and act on relevant clinical data in a flexible and continuous way. We hypothesized that a new kind of tool was required for this purpose, as no existing tool was well suited for these needs. In designing this tool, we made the following assumptions:
- There is a need to reduce practice variability, optimize resource utilization, and enhance patient care
- The assertion that "best practice" can be defined is misleading, as it ignores the continual changes in medical knowledge, therapeutic options, and patient populations, and discourages both clinical acumen and innovation
- Any standardization of care must therefore be based on principles of "sound practice," which represent a synthesis of current medical knowledge and best clinical judgment, and are imperfect in ways yet to be determined
- Guidelines to standardize care cannot be static or stand-alone, as many CPGs have been designed to be; rather, guidelines must be flexible and must be used to create a medical learning system that can collect, analyze, and learn from relevant data to allow continuous revision and improvement
- Data gathering must be selective and, based on prior medical understanding, be targeted towards relevant clinical findings in order to optimize the data burden and signal-to-noise ratio. It must readily accommodate economic analyses for cost-effectiveness studies as well
- Any solution is more likely to succeed if it is designed and implemented by caregivers themselves, such that they are owners of the process rather than passive recipients
- Finally, certain cherished characteristics of medical practice - the ability to discover and innovate, to train the next generation to the highest standards, and to provide truly outstanding healthcare - must be maintained
With these considerations in mind, Standardized Clinical Assessment and Management Plans (SCAMPs) were created.
How do SCAMPs work?
A SCAMP is a quality improvement initiative that aims to optimize care delivery for patients iteratively over time. Each SCAMP outlines a sound, standardized care pathway for a somewhat diverse patient population with a particular diagnosis or condition. It is accompanied by a systematic and robust, but also selective data collection process, allowing measurable differences in outcomes to emerge based on clinical heterogeneity. One distinguishing feature of the SCAMPs process is active invitation and capturing of knowledge-based clinician deviations from the standard management plans, which are perceived to be a rich source of information and innovation. Based upon periodic review of the collected data and deviations, a SCAMP undergoes iterative and progressive modification of its care-delivery algorithm. The development of a SCAMP is carried out by a multi-disciplinary group of physician and nursing experts on a particular disorder, and can be summarized by the following six-step process.
- Establish a foundation for "sound" clinical practice on a particular disorder through a thorough literature review to compose a background position paper and, if necessary, a focused retrospective study to analyze the results of current practice
- Formulate several (generally eight to twelve) plausible outcomes, or questions that address known gaps in knowledge regarding management of the disorder, which become the focus of targeted data collection
- Arrive at expert consensus on the entry criteria, assessment recommendations, and management algorithms (decision trees) for the SCAMP
- Develop data forms and computer-based tools that facilitate the implementation of the SCAMP and the targeted collection of data on SCAMP use, deviations, and patient outcomes
- Perform periodic analysis of SCAMP data using frequentist and Bayesian statistical approaches to assess the effectiveness of recommendations from both a clinical and cost-effectiveness perspective
- Revise and improve the SCAMP based on this analysis, best clinical judgment, and relevant updates from the medical literature