In a report dated 24 September 2026, TechTarget said Oracle Health had announced five AI revenue cycle capabilities, including prior authorization and appeals management, to be embedded in its revenue cycle solutions in the coming months.
A study of one large insurer's Medicare Advantage claims found that denial rates varied by service and provider type, with the most denials for laboratory services and hospital outpatient providers (Health Affairs, 2022). This payer-side study concerns medical-necessity coverage denials, not hospital-wide initial-denial performance or the effectiveness of denial-prevention AI.
Make the baseline match the intervention
We would require a pilot proposal to specify which measure it intends to change. In our view, the evaluation should measure the claims an intervention is intended to affect, against an agreed comparison. Do not make the all-payer denial rate the sole test of success or include outcomes the intervention cannot plausibly change.
For each endpoint, require a written numerator, denominator and definition of a preventable denial. Specify whether the endpoint concerns initial denials, final unresolved denials, claim counts or dollars. Treat those choices as the local evaluation contract, rather than assuming that everyone means the same thing by “denial reduction.”
Keep the operational and financial decisions separate. Ask whether the intervention prevented the targeted denial, what staff work it required and what financial result finance can substantiate. We would not accept a change in denial counts as sufficient evidence of cash benefit, or an improvement in appeals recovery as the primary test of initial-denial prevention.
Require measurement before go-live, not a new project by default
We recommend approving go-live only after revenue cycle analytics and finance validate a baseline by payer, denial reason and service line, and agree a comparison plan that accounts for concurrent workflow and payer-policy changes. Use existing reports if they pass validation. Do not automatically commission a separate data-readiness project or require a comprehensive root-cause analysis before a bounded test. Do not require a new prospective observation period if historical data pass validation.
Validate the proposed baseline against underlying claims and remittance records. Reconcile totals with finance, document exclusions and check that historical and pilot cohorts use the same definitions and have comparable time for adjudication. Treat the initial historical window and reporting interval as practical starting points; adjust them for claim volume, adjudication time, baseline variability and the evaluation method.
Choose the comparison before exposure to the intervention. Consider a comparable, unexposed group or a justified trend-adjusted time-series design. A 2013 health care quality-improvement methods paper in Academic Pediatrics describes interrupted time series as a way to control for background trends, unlike a two-period before-and-after t test. We consider that principle applicable to denial evaluation because the comparison should distinguish a change after launch from a trend already under way.
For the time-series approach they describe, the authors identify a minimum of eight periods before and eight after the intervention to evaluate changes statistically, and list the availability of a suitable control population among its limitations (Academic Pediatrics, 2013). Ask the analyst to establish feasibility for the proposed claims-data series, rather than treating the source's minimum as a universal observation window. If neither design is credible, narrow or defer the live test.
The methods paper also identifies difficulty separating program components introduced close together. Record planned staffing, coding, authorization, EHR and payer-policy changes, with dates and affected claims, and agree how the analysis will handle them. Set review triggers against baseline variability, with named pause authority and evidence required for expansion.
If the intervention proposes coding or documentation changes, include review of output accuracy, clinically important omissions and staff correction burden alongside workflow measures. Faster claim handling or lower denial rates do not establish clinical safety. The trade-off is explicit: some preparation before go-live in exchange for a result leadership can interpret.
The strongest case for starting immediately
The strongest case for immediate launch is a bounded test where existing reporting is already validated for the targeted payer, denial reason and service line, and the comparison and review triggers are settled. Waiting for broader analysis could postpone operational learning and any financial benefit the test might deliver, while consuming staff effort on questions outside its scope. In that setting, we would start rather than commission an expansive readiness project.
Where those conditions are not met, we still favor closing the specific measurement gap before exposure. A bounded scope alone does not give leadership an interpretable result. Settle the primary endpoint, denominator and comparison without holding the test for secondary questions.
Where to start
Start these actions this week. Each owner should set a completion date; the approval outputs must be ready before go-live.
- Have the revenue cycle VP convene the pilot owner to draft the scope. The final specification should name the payer, denial reasons and service lines in scope, the intervention's intended function and the accountable operational owner.
- Ask revenue cycle analytics and finance to select an existing report and begin reconciliation. The final output is the validated baseline, with the endpoint definitions, exclusions and adjudication treatment attached. Identify specific gaps before commissioning broader work.
- Have the evaluation analyst inventory available reporting periods and candidate comparison populations. The final plan should justify the selected design, historical window and reporting interval, and state what would make the comparison uninformative.
- Ask operations and payer contracting to request planned-change lists from affected teams. Combine them into a dated change log before launch, with the analyst's proposed treatment of each change recorded alongside it.
- Have the operational owner and clinical documentation lead assign scorecard reviewers. Before launch, produce the operational and financial scorecard described above, including the coding or documentation safety checks where applicable, with a named reviewer for each measure.
- Have the CIO and revenue cycle VP schedule the go-live review and identify pause authority. The signed decision should confirm that the measurement requirements are met and document review triggers and expansion criteria. Otherwise, assign an owner to close the specific gap.