Table 3.

Optimize and Target Therapies

1.	Data systems need to link clinical, pharmacy and encounter data, and data science needs to be applied to develop algorithms that can be applied to care in real time that identify patients for whom there are opportunities to intervene to improve care and outcomes, including health status.
2.	A set of clearly outlined treatment pathways (at an institutional level) should encourage providers and patients to think about high-value activities throughout encounters. The information should include consideration of diagnostic procedures, medical therapies, device therapies and lifestyle changes.
3.	Imaging software and electronic health records must require field coding of summary LVEF measurement (just as a systolic blood pressure or serum creatinine is recorded), which can then be used to identify certain patients and trigger appropriate care.
4.	Apply data science to develop risk models that can be automatically calculated and presented in electronic health records that in turn foster clear communication about prognosis and care considerations.
5.	Launch a targeted campaign aimed to educate providers who care for patients with HF, including cardiologists, primary care doctors and hospitalists about signs of progressing from Stage C to D.
6.	Data science should be applied to develop algorithms that can be incorporated into EHRs to facilitate identification of patients with a worsening trajectory who should be referred to a HF specialist for consideration of advanced therapies.
7.	Within networks of care, create different levels of expertise and coordination so that patients receive the appropriate level of care.