Evidence-based guidelines are recognized as the standard of care to improve outcomes for the 6.5 million people in the United States affected by heart failure (HF).1 The current HF guidelines were developed and endorsed by multiple national organizations including the Heart Failure Society of America (HFSA), American College of Cardiology (ACC), and the American Heart Association (AHA).2,3 The AHA also launched Get With The Guidelines-Heart Failure (GWTG-HF), a voluntary, hospital-based initiative in 2005. This initiative uses a national data registry and benchmarking program to promote guideline adoption.2 More recently, guideline-directed management and therapy (GDMT) entered the lexicon to promote optimal therapies for adults with HF based on the current evidence. Medication optimization is a prominent part of GDMT.4 Health behaviors have received less attention, namely, exercise to improve HF outcomes.
Multiple large clinical trials support the safety and efficacy of exercise to prevent or slow HF progression, translating to improved health-related quality of life.2 Despite the benefits, there is a lack of implementation of guideline-directed exercise recommendations for HF patients. The objective of this pre-implementation investigation was to assess the feasibility of engaging the Greater Plains Collaborative,5 an integrated digital network of 12 leading health systems across 10 states in the Midwestern United States to support a future implementation study and improve adoption of exercise guideline recommendations for HF patients. The specific aims were 1) Determine the number of patients with a diagnosis of HF treated at each of the 12 leading health systems in the network; and 2) Assess the status of PRO measure accessibility in the EHR systems across the network. The following research questions were also addressed: Q1) Can the information needed from the health systems across the collaborative be effectively accessed and reported? Q2) Is centralized facilitation of the network efficient in extracting data in a timely manner?
Implementation science includes the methods needed for implementation, evaluation, and maintenance of guideline-directed recommendations.6,7 The literature indicates that passive approaches to guideline implementation are largely ineffective8 as uptake does not occur spontaneously or naturally.9 Comprehensive multilevel approaches are more effective10 when they involve stakeholder involvement11-13 and are tailored to a specific audience.14 Identification of unique approaches to implementation is needed beginning in the early developmental stages to maximize uptake of guideline-directed therapies and emphasize feasibility and sustainability while minimizing cost and disparities.15,16
The uptake of guideline-directed therapies informed by implementation science gives reason to a practice,17 and promotes meaningful patient outcomes.18 To assist the development of an implementation intervention for exercise in HF patients, implementation mapping followed this pre-implementation query. Implementation mapping involved a systematic approach, combining implementation science and intervention mapping to plan intervention techniques and strategies.19 Implementation mapping promoted consistent use of concepts and constructs that aligned with the study objectives. The implementation mapping process also helped to identify theory-based behavior change strategies and techniques advantageous for promoting guideline uptake.
Multiple health systems were queried across an existing integrated digital network to determine the feasibility of leveraging this network for a future implementation study. The standard of care for adults with HF is defined by Guideline-Directed Evaluation and Management (GDEM) based on the current state-of-the science. A key behavioral factor in the HF guidelines that is often overlooked is exercise. Adults with HF experience poorer quality of life outcomes compared to patients with other chronic conditions attributed to symptoms of dyspnea, fatigue, and limitations in exercise tolerance.20 Exercise is safe and effective for adults with HF, a recommendation supported by the highest level of evidence.2 Implementation science is key to accelerating the uptake of this guideline recommendation. This project explored the potential to engage the integrated digital network to accelerate the implementation of guideline-directed exercise in adults with HF.
The integrated digital network or collaborative is an established infrastructure led by our University health system, a regional referral center for adults with HF in the Midwest. The collaborative represents a diverse set of patients and institutions ranging from cutting-edge academic medical centers to local community health clinics. These connections allow research to be conducted and have expanded to allow the infrastructure necessary for multi-site research. The health systems throughout the network comprise 430 clinics, 1,800 primary care providers, and 7,600 specialist providers and continue to grow.21 This infrastructure contains data for specialty populations, such as adults with HF to contribute to the creation of new knowledge. The sites have teams with extensive expertise with electronic health record (EHR) systems and terminology standardization.
The model or structure for the data used across the collaborative is referred to as the Common Data Model (CDM). Standardization is necessary across systems for data sharing and to be useful in research. The network health systems incorporate the CDM for electronic health record and billing data.22 A field is included in the CDM that contains a patient reported outcomes measure. While these measures are included in the CDM, the degree of accessibility and ease of use in the EHRs at each health system across the collaborative was unknown. This information was needed for future implementation research primarily to scale and sustain an implementation intervention.
Patient reported outcomes traditionally included symptoms routinely assessed during clinic encounters with HF patients. The defining clinical symptoms of HF are dyspnea, fatigue, and limitations in exercise tolerance; however, the experience of patients with HF extends beyond these symptoms to include a range of physical, mental, and social effects.23 Assessment is generally limited to standard measures of biological or physiological symptoms to identify condition deterioration in HF.24
There is growing recognition of the need for evaluation of HF symptoms using validated, standardized measures from the patient’s perspective, such as the Patient Reported Outcome Measures Information System (PROMIS).25 The PROMIS measures include general health items and multiple condition specific subscales to assess physical, mental, and social health, and overall health-related quality of life. Without consideration of the patient’s perspective, the role of the patient’s physical, mental and social health and attitudinal factors in HF may go unrecognized.26 The degree of integration of patient reported outcomes in the electronic health record (EHR) systems across the digital network was unknown.