01 / DATA TRUST
Can we rely on the numbers?
Data quality, reconciliation, consistent definitions, and governance that make analytics credible.
Healthcare revenue cycle intelligence
DataTrust RCM explores how healthcare leaders can connect trusted data, analytics, and AI with better revenue cycle decisions.
By Christopher Scott Benefield · Publication date to be announced
Concept cover
The book
Healthcare organizations have no shortage of data. The challenge is knowing whether it can be trusted, what it means, and what action should follow.
I’m writing DataTrust RCM to explore that connection: from claims and reimbursement data to meaningful performance measures, stronger operational conversations, and practical uses of analytics and AI.
The book draws on my experience leading healthcare revenue cycle operations, technology programs, and analytics teams.
Inside DataTrust RCM
These are the core themes guiding the manuscript.
01 / DATA TRUST
Data quality, reconciliation, consistent definitions, and governance that make analytics credible.
02 / REVENUE CYCLE VISIBILITY
Connecting claims, payments, denials, and accounts receivable to reveal gaps and recovery priorities.
03 / ACTIONABLE INTELLIGENCE
Moving from dashboard metrics to clear priorities, accountable owners, and measurable follow-through.
04 / PREDICTIVE ANALYTICS
Exploring how forecasting and risk signals can support earlier intervention and more informed planning.
05 / AI & AUTOMATION
Identifying opportunities for automation while keeping validation, human review, and oversight in place.
06 / OPERATING DISCIPLINE
Building a repeatable rhythm for performance reviews, stakeholder decisions, and tracking results.
From insight to action
The manuscript is built around practical approaches to four recurring revenue cycle challenges.
Establish consistent definitions for denial rates, AR days, and collection performance so teams can work from the same numbers.
Connect claims, remittances, and expected reimbursement to identify payment variances and focus recovery efforts.
Use recurring denial patterns to identify upstream issues in eligibility, authorization, and claim preparation.
Translate analysis into an action, an accountable owner, and a measure of whether performance improved.
“Having data and having actionable business intelligence are two very different things.”CHRIS BENEFIELD
A few details
Not yet. I am still writing DataTrust RCM. Publication timing and availability will be shared here when they are confirmed.
Healthcare executives, revenue cycle leaders, and analytics and technology teams looking to connect trusted data with practical business decisions.
Yes. Use the email link below to contact Chris about the book, a question, or a relevant revenue cycle challenge.
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