Coming down from overload and identifying actionable information
Care coordination is the intricate process that involves organizing all of the care and activities between the patient and each caregiver responsible for the various aspects of the patient’s healthcare services. Today, care coordination mostly focuses on managing patient problem lists, reconciling medications, coordinating and scheduling appointments, transitioning patients between care levels, following up on care gaps, and providing much-needed psychological and social support.
Many healthcare professionals and technology systems are necessary to ensure that patient care and information are delivered in an efficient and timely manner. However, with the ever-increasing amount of data being collected from different sources, the diversity of applications aggregating the information, caregiver time constraints, plus the shift in focus to value-based care, it’s easy to see why our healthcare teams are overloaded.
The healthcare data map
Payers, health systems, and accountable care organizations use proprietary risk stratification applications to identify high-risk patients for care management. Their analysis is mainly based on available administrative data (medical claims, pharmacy data, and even clinical data in some cases). However, it’s the socioeconomic, behavioral, cultural, lifestyle, and environmental factors, usually uncovered by care managers, that are critical for improving outcomes and for managing and prioritizing patient care. Collecting, analyzing, and sharing this nonclinical data is quite challenging. New technologies capable of deciphering this data should play a major role in care management initiatives.
Care coordinators usually engage with multiple caregivers and information systems. Conflicting results, data gaps and delays, structured vs. unstructured information, and different coding systems make managing a complex patient even harder. The following are some simple strategies to help care coordination teams understand the sea of data they try to swim in:
Pay attention to dates and data sources
Check the update dates for the diagnoses or conditions. This will help manage and confirm active problem lists. Match update dates on complementary data. For example, does the medication reconciliation date match the discharge date?
Sort out multiple providers. Most complex patients have multiple providers. It is challenging to see which provider is responsible for the patient’s diagnosis, or who ordered a particular lab or imaging study. Based on his or her specialty, one provider may play more of a role in managing a condition. When possible, check the EMR audit logs to see who the caregiver is and when that person looked at the patient’s record, and to see who is responsible for the primary diagnosis.
Find the best path to medication adherence. Improving medication adherence is a key goal for many care coordinators and has been shown to have the highest association with improving clinical outcomes. Obtaining medication fill information from payer claims, pharmacy benefit managers, or pharmacy aggregators (e.g., Surescripts) can take between 30 and 120 days. Hospital medication fill information, however, is processed more quickly. Take this into account when looking at this metric and other outcomes dependent on medications and vaccinations.
Be a detective. For EMRs with a longitudinal patient record, pay attention to trends, but be mindful that the EMR may not include all the data. Check for gaps between provider visits within the same specialty. This is also the quickest way to check if patients with chronic diseases are getting their labs drawn or following up on care at consistent intervals. Investigate the gaps because they may represent much more than a patient changing providers or using out-of-network ancillary services.
Look at the details when identifying care gaps Finally, for laboratory-based or clinical outcome measures (Hba1c, hypertension control, BMI), divide noncompliant patients into two groups: those who have values outside the normal range and are truly noncompliant for the measure, and those who don’t have a result for the measure-specific time frame.
If no results are available, check if the test was ordered, or if the patient had a recent provider encounter. If either of these is the case, the result may not be available because the patient may have had the test at an out-of-network lab, or there may be processing delays or translation/mapping issues. Also, aggregate and analyze patient-specific disease-based outcome quality measures.
Combine this with utilization data (provider or ER visits) and patient location, race, or ethnicity (the nonclinical data most likely to be available) to help stratify your population.
To learn more about Understanding Data that Drives Care Coordination and download our brochure on Risk Discovery, click here.