Over the next few years, reimbursements will be based on both value and quality initiatives. Instead of billing for the number of office visits and tests ordered, payments will be based on the value of care. Providers will have to measure compliance with clinical guidelines and achieve improved outcomes in order to secure reimbursements.
While practices can look for information from claims data, not all information will be available.
- How can you determine if a current urology patient has a history of diabetes or high blood pressure?
- How can you determine the level of your practice providers using eprescribing?
- How can you see if your providers are meeting benchmarks for clinical guidelines against other providers (and their deidentified data) who are treating the same diagnosis?
If a patient’s history was entered into the practice EHR, that information could be readily available when clinical analytics programs are linked. Meeting those clinical guidelines will be easier with improved patient data.
Pharmaceutical manufacturers and payers will also begin to require more data. Two recent pay-for-performance deals with national payers for Novartis’ cardiac drug Entresto and Amgen’s cholesterollowering drug Repatha will have an impact on how providers must supply the clinical data.
While the manufacturers and payers are working out the terms of the information needed for reimbursements, it is anticipated that practices will assume the burden of providing the data.
Drilling down into data beyond claims records will become increasingly important for practices to determine financial impacts. Practices will need to make business decisions based on more specific information. If a practice sees that it is becoming increasingly difficult to work with a particular payer in their area, analytics could show the negative impact on the business by not treating those specific patients.
Additional data can also help optimize additional revenue streams. If a practice is involved with clinical research studies, reports beyond what can be pulled from an Excel file could streamline processes. Clinical research inclusion and exclusion criteria could be easily detected within the EHR and reaching out to those patients for a clinical trial screening visit would take much less time by the clinical research coordinator.
This information was taken from a webinar on ClinIQ Analytics held in January 2016.
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