Revenue Cycle Management (RCM) analytics can provide a wealth of information to healthcare organizations or single providers. Data is the key to understanding financial performance but also allows an organization to streamline operations and enhance patient services. Here’s a snapshot at some of the various types of data and insights that can be gained through RCM analytics:

Patient Financial Data 

This includes information related to patient payments, insurance coverage, and outstanding balances. Analytics can provide insights into trends in patient payment behavior and the effectiveness of collection strategies.

Example insight

An analysis might show that a significant number of patients delay payments beyond 30 days. As a response, the healthcare provider could introduce early payment incentives to improve collection times.

Claim Denial and Underpayment Data

Data from claims analytics can provide information on common reasons for denied claims, which departments or procedures are most affected, and the financial impact of these denials. Additionally, claims analytics can provide detail on what claims are underpaid. 

Example insight

If data reveals that a high percentage of spine surgery claims are denied due to coding errors, the organization will want to initiate additional training for the coding team or even consider adopting a computer-assisted coding solution.‍

Payer Performance Data

This encompasses data related to the performance of different insurance payers, such as denial rates, payment timeliness, underpayments, and contract adherence.

Example insight

If an insurance company consistently underpays compared to the contracted rate, an organization could use this data to renegotiate the contract or decide whether to continue partnering with that payer or potentially seek reimbursement on any penalties that may be allowed.

Coding and Billing Data

Data on coding accuracy, charge capture, and billing practices can be used to identify areas of revenue leakage or inefficiencies in the billing process.

Example insight

If an analysis at an organization uncovers recurrent missed charges in the emergency department, the organization could implement a charge capture tool to ensure all services rendered are being billed appropriately. This could also identify areas of system issues, human error, etc.

Operational Data

This includes data on the efficiency of different revenue cycle processes, such as the time taken for claims processing, collection times, and staff productivity.

Example insight

If the data shows that the average days in accounts receivable (A/R) is rising, the billing department might need to re-evaluate its follow-up processes with payers, identify areas where RPA processes may be effective, or AI solutions could assist.

Patient Access Data

This involves data related to patient registration, insurance verification, and benefit eligibility. This can help identify issues in the patient access process that may lead to claim denials or delays in payment.

Example insight

If a significant number of claims are denied due to insurance eligibility issues, the organization might automate the insurance verification process at the time of patient registration in addition to pre-billing verification to confirm continued eligibility, especially in an in-patient setting.

Contract Management Data

Data on payer contracts can help organizations understand the financial implications of different contracts and identify opportunities for renegotiation.

Example insight

If an analytics tool shows certain payer contracts consistently result in lower payments, the healthcare provider could use this data during contract renegotiation to argue for more favorable terms.

Medical Practice Success has worked with several vendors who have tools that can assist your organization with obtaining the clarity that they need from patient collections to payer contract performance; you can quickly identify opportunities for revenue recovery. Reach out to us today and let’s discuss your specific needs.