A value network is a marketing concept that describes the social and technical resources (supply chain) within and between businesses. They account for the overall worth of products and services, including the collection of upstream suppliers, downstream channels to market, and ancillary services that support a common business model within an industry. The kind of value network that the healthcare system needs focuses on bringing increased value to healthcare patient (consumer) and reward providers for delivering high-value care.
- The green box refers to three types of data required to build the information and knowledge people need for increasing value across the supply chain. The education data refers to formal and informal ways that people share their knowledge, ideas, and experiences. Research data, on the other hand, is used in controlled clinical trials, outcomes and performance studies, various types of biosurveillance (e.g., post-market drug and device, public health), preferred clinical guideline development, and other types of research. Technology data refers to the date collected by EHRs and other health IT tools, as well as streamed through durable medical equipment.
- The five blue boxes refer the transformation of the data using a variety of HIT tools and clinical processes that promote the kinds of knowledge and understanding that fosters more effective and efficient care (services and products). They include (a) use of evidence-based guidelines, personalized care plans, decision support tools, and communication networks; (b) methods of information sharing and care coordination; and (c) patient empowerment. Each activity (process) in the blue boxes supports value by requiring quality handoffs and continuous measurement, assessment, feedback and acceptance at each breakpoint (the gap between each activity) to ensure value creation via continuous quality improvement (CQI).
- The red box on the bottom refers to the technological, psychological, economic, and regulatory factors that promote or inhibit value to patient by influencing (driving or impeding) the blue box processes. Some of the key influences are listed in the box.
- The purple box represents good patient outcomes; it is the desired result of using the data, tools and processes to increase value to the patient. The curved purple arrow pointing to the Data Types box indicates the need to provide data about the process, influences and outcomes of care across the entire supply chain via continuous feedback loops. The blue box activities and their related influences that help achieve the goal of higher quality at lower cost are reinforced; those that do not are modified or eliminated.
This CQI solution does not strive for zero defects (no errors of omission and commission) because perfection assumes infinite resources and knowledge, both of which are unrealistic. Instead, it is based on the Michael Porter’s value chain model, which assumes defects (errors) will occur and, therefore, we had better accept some reasonable level of tolerance, reconcile mistakes and poor outcomes, and strive to ensure ever-better outcomes at reasonable cost for a given condition.
Ensuring patient access to high-quality healthcare at reasonable cost through the value-driven CQI solution requires adherence to these critical process transformations:
- Supporting value for each primary activity through quality handoffs (the transfer of information, as well as authority and responsibility, during transitions in care across the continuum) along with ongoing measurement, assessment, feedback, and acceptance at each breakpoint (the gap between each primary activity).
- Assuring that all infrastructure or support activities (a) promote a seamless support relationship that benefits the primary activities, (b) avoid impeding the primary activities, and (c) follow CQI rules for each component across the entire healthcare spectrum.
- Operating with awareness of current healthcare system shortcomings that focuses on areas with quality improvement is warranted.
- Addressing the problems associated with defining quality in real time versus retrospective analysis, for both individual patient and aggregate data.
- Focusing on root cause identification to determine the factors preventing clinical outcome and cost improvement, instead of playing a “blame game,” which only exacerbates the problem.