You and your clinical team work hard to provide excellent care. While each health plan offers different benefits and formularies, and assesses performance on different measure sets, you and your team treat everyone the same. You diligently document the patient’s story, enter information into the structured fields of the electronic health record, review clinical decision support prompts, and select the most appropriate ICD-10, E&M, and HCC codes. Maybe artificial intelligence is working in the background to surface buried information and suggestions, or maybe it’s ambient in your examination room. You and your team do everything you can to support your patients and be the professionals you intended to be when you started training.

Yet nobody is perfect. How can we be better? What if EHRs, population health platforms, and patient engagement applications could pull in more complete, high-quality clinical data from wherever a patient received care in near real time? And what if systems organized this data and presented context-sensitive insights to clinical teams and population health managers in an actionable format? Clear. Concise. Patient- or population-specific recommendations. Not quality gaps based on national measures used for value-based payment programs. Those accountability measures are typically retrospective and designed to determine what happened, not what should happen. They aren’t the measures that most clinical teams want or need to drive improvements in care. They also aren’t the measures patients and caregivers value most. 

The richness of clinical data collected during care delivery should be the foundation for better, more relevant clinical quality measures that clinical teams, patients, and caregivers can see driving improvements in health outcomes. While accountability measures focus on downstream outcomes, clinical teams need to focus on improvements that ultimately affect outcomes and value-based payments but are proximate to care delivery. 

Digital quality measures (dQMs) can be as complex or simple as desired. Measures can include clinical logic, calculations, and modularity to focus on different population segments and attribution models. Here are some examples:

• Calculate the average blood pressure (or glucose control) over time and determine the level of hypertension (or diabetes mellitus) control.
• Was treatment intensified or de-intensified based on blood pressure (or glucose) control results over time?
• Was an abnormal test (e.g., mammogram, cervical cancer screening, colorectal cancer screening, diabetic eye exam, kidney health evaluation) followed up within the recommended time frame? Was the recommended next test (or procedure) completed?
• Beyond contacting patients after emergency department encounters or hospital discharges, are their patient-specific needs met within a clinically relevant time period?
• Beyond identifying social needs or risks, are those issues addressed within a timely period?
• When polypharmacy occurs, are medications adjusted? Was a comprehensive medication management process initiated and completed?
• When inappropriate opioid use occurs, does the clinical team address the issue and refer or manage the patient to reduce opioid misuse?
• Measures of appropriate test/imaging in response to clinical situations where such guidance exists.
• Development of care plans for complex patients (based on ICD-10 diagnoses and other readily available information in the clinical record) and a companion measure reflecting whether care plans are reviewed/updated regularly.

These and similar measures require complete, accurate, and immediately accessible data from wherever care was received to be effective. This is where metadata-based clinical data exchange via Fast Healthcare Interoperability Resources (FHIR®) endpoints is unmatched in effectiveness and efficiency. Clinical teams will gain secure access to patient data from multiple sources (e.g., payer connections, referral networks, or patient-directed apps) without managing custom integrations or proprietary interfaces.

We’re at an inflection point. The need for better digital clinical quality measures to drive improvement at the point of care, reduce avoidable expenses, and help people achieve their maximum health has never been more pressing. To achieve the outcomes we seek, clinical teams, health systems, and payers need access to more and better clinical data to support these better measures. Payers are now using Velox’s Payer Enablement Platform to help identify and optimize data for their use cases. Velox’s next move is to facilitate secure, clinical data exchange among multiple parties, as seamless and fast as the internet and as reliable and secure as online banking.