Workflow Analysis
What Is a Workflow?
The work (clinical care, administration, facility operations, marketing, etc.) performed by healthcare organizations must be well-organized to ensure efficiency, profitability, and most importantly the best possible patient outcomes. The particular work processes performed by different divisions in the organization are based on workflows, or the progression of steps required to complete the process. In a sequential workflow, a step must be completed before the next one is begun. In parallel workflows, however, multiple steps may be underway simultaneously.
Value-added vs. Non-value-added
Value-added steps in a workflow are those which contribute in some meaningful way by streamlining, advancing, or enhancing the process. They add value by improving the process itself. Non-value-added steps, by contrast, do not directly contribute to or add value to the process and should be considered for elimination. Remember that some steps are mandated or required by regulations or accrediting organizations and need to remain in place whether they add value or not.
Diagramming a Workflow
The various steps, and direction in which the process flows toward completion, are depicted in a process map. For clear examples of different process maps and tips for creating them, consult Amanda Athuraliya's Easy Guide to Process Mapping.
Types of Process Map
There are several types of process map, each with a defined purpose. Swimlane maps, for example, assign individuals to lanes in the flowchart. The lanes clarify who performs what role, at any step or stage, in the larger work process. A value stream map helps identify non-value-added steps in a process. To learn more about them, read the short article "What Is Value Stream Mapping, and How Can It Help My Practice?" by Ziad Gellad and Theodore Day.
Aggregating Patient and Organizational Data
Electronic healthcare records [EHR] now exist for nearly every facet of service provided in developed countries like the United States. Combining these often isolated, or siloed, records into single databases, however, is still a work in progress. Ideally, the disparate records like those shown below are cleanly aggregated and integrated into a usable system allowing for more holistic treatment and understanding of a patient's needs.
Data warehouses allow healthcare institutions to perform data mining to learn more about populations, discover relationships and patterns to inform practice, and otherwise build the knowledge-base of the institution. These large repositories are mined for information using a database querying language, usually SQL. By writing scripts in SQL, researchers can retrieve very particular information from the database.
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