How can you leverage data while working to improve quality measures?

With the recent uptake of technologies and solutions, leveraging data—along with data that include patient self-reported sources—can help health care stakeholders assemble a clear picture of how to improve patient care. Meaningful data use falls into three components: intent, action and enablement. Let’s explore a few use cases, and some opportunities that support accurate monitoring and closing care gaps, which can result in improved care quality and performance while advancing, scaling and advancing efficient care delivery. 

Data collection and use cases 

Data timeliness, integrity and accuracy are common challenges to: 

· Internal and external reporting and performance monitoring. 

· HEDIS performance submission to payers. 

· EHR integration and continuity of care.

 · Coding and claims processing.

 · Payer-ACO (or other health care stakeholders) transmission data. 

· Network adequacy and community needs. 

Focusing on interoperability and standardization among systems that support these functions will enable efficient use of data as your organization works to engage patients in prioritizing and managing their health. 

Aligning patient engagement and quality gaps 

As you identify a target population, don’t forget to crosswalk clinical and social needs, the total cost of care and quality targets and program benchmarks, to reflect the notion of true patient-centeredness. How often do we send reports and wonder who’s using the data, and how? Aligning gaps and opportunities with your organization’s core competencies, with precise interventions across functional areas—practice operations, care management, patient engagement and so on—can strengthen and increase the impact of your initiatives. Developing a
methodology that looks at the broader picture, and then integrating it into your data warehouse, analytics platform or EHR, can enhance resource use and provide patients with the most relevant services and follow-ups.  

Driving patient engagement and improving care quality

Considering technology as a significant resource for advancing population health creates an opportunity to align reimbursement and documentation effors. With NCQA's recently released HEDIS measures in mind, which include accomodations for telehealth, here are some examples of downstream applications that encourage automation and scalability of clinical and operations process to improve quality:

· Patient self-management/coaching and outreach 

o Multi-channel engagement and preferences (telephonic, multimedia, SMS, chat…).

o Patient self-reported (e.g., screening, service acknowledgment) [something… data?]. 

o Medication use and dispensing. 

o Escalations and follow-ups. 

o Asking algorithm-devised questions to proactively identify the next action step. 

· Remote patient monitoring 

o Device-collected (e.g., labs, clinical values) data. 

o Patient self-reported [something]. 

o Care management data (if the approach includes back-end clinical support). 

o Continuous management of and engagement with patients, using patient/caregiver reported data. 

o Asking algorithm-devised questions to proactively identify the next action step. 

· Social determinants of health 

o Use public or acquired geodata to identify social and critical community needs. 

o Standard screening (patient self-reported) data. 

o Referring community-based organizations services inventories. 

When used together, these tools provide integrated care management and quality services that promote continuity of care while allowing more gaps to be addressed in the home and community, relieving taxed clinical resources and reducing readmissions and ED visits. 

Collecting data at various entry and collection points enables action when data are integrated into workflows, models and applications that align with an organization’s care delivery and wraparound services. Data use carries a significant impact when implemented functionality reflects an organization's vision, goals and objectives and prioritizes the needs of its population and portfolio of services. 

Do you agree? 

1. What challenges have you experienced when evaluating data use? 

2. Does your organization explore use cases relevant to your goals and objectives? 

3. What technology approach has been most successful at integrating data to drive quality
performance? 

Share your thoughts in the community forum .