Payment Integrity: Nigeria’s Fastest Path to Better Healthcare

By Tosin Clegg

Nigeria’s health system sits at a difficult intersection: public funding is tight, out‑of‑pocket spending remains high, and service quality is uneven across states. In that context, every naira lost to preventable leakage—fraud, waste, abuse, or simple process error—is a clinic left understaffed, a ward left without medicines, or a primary health centre that cannot keep the lights on. Prevention is not a slogan; it is the only sustainable financing strategy. Over my career, from managing credit control for a 50‑million‑subscriber telecommunications operator to building revenue‑integrity frameworks across sectors, the same lesson has kept resurfacing: disciplined data, verified identity, and proactive risk management consistently outperform after‑the‑fact firefighting.

Improper payments in Nigerian healthcare are not mysteries; they are patterns. Duplicate and phantom claims flourish when enrolment and eligibility checks are weak, while upcoding and unbundling thrive where tariff governance is opaque and claims review is inconsistent. Capitation misuse grows when panel management is lax and outcomes are not monitored, and “paper friction” multiplies—miskeyed tariffs, mismatched codes, lost pre‑authorizations—when facilities must depend on patchy connectivity or manual back‑and‑forth with multiple HMOs and schemes. These are not harmless administrative quirks; they are direct transfers from scarce health budgets into avoidable losses, and they undermine public confidence in a sector that can least afford it. The good news is that Nigeria already has the rails to change this story. When every claim is tied to a verified identity—NIN and NHIA ID for beneficiaries, BVN and corporate RC for provider entities—ghost enrolments evaporate and duplicate submissions lose their oxygen. Real‑time eligibility checks, delivered through simple USSD flows or offline‑first tablets that sync intermittently, can stop many bad claims at the door without punishing honest providers. Standards help too, but they must be pragmatic: a lean HL7/FHIR profile, trimmed to a dozen or so essential fields that every scheme can collect and every provider can supply, is far more valuable than a perfect but unattainable data model. Clean, comparable data is the precondition for everything that follows.

Once identity and basic data discipline are in place, risk‑based controls become transformative. Lightweight anomaly detection—simple rules and basic machine learning trained on Nigerian patterns—can flag improbable combinations, same‑day multi‑facility encounters for the same person, and “zero‑day” inpatient stays that never pass a plausibility test. The point is not to replace adjudicators, but to aim them. In prior roles, this approach lifted recoveries and reduced processing error rates because scarce human attention went to the riskiest items first, and that logic translates perfectly to claims triage: put the highest‑risk claims at the top of the queue, require a bit more documentation where the numbers look wrong, and let clean claims sail through faster.

Pricing and authorization must also reflect local realities. Instant pre‑authorization for high‑value procedures, issued as one‑time tokens by SMS or USSD, can curb unnecessary escalations without slowing down care. For large tertiary centres, bundled payments—DRGs for common inpatient episodes—help realign incentives away from item‑by‑item inflation and toward outcomes. This does not require a big‑bang reform; it requires a handful of high‑volume procedures, clear documentation rules, and a willingness to iterate, keeping fee‑for‑service where tariffs are mature and clinical variation is real, and introducing bundles where variation is low and volume is high.

All of this only works if we close the loop. Monthly feedback—what was denied, what was paid, why it was denied, and how often denials were sustained on appeal—must return to providers in a form they can use. A simple dashboard that shows clean‑claim rates, average turnaround time, and the most common errors does not shame facilities; it empowers them. When providers see first‑pass acceptance rising and appeals falling, they are more likely to invest in the data discipline the system needs, and when schemes see that most confirmed improper claims were flagged before payment, they gain the confidence to pay clean claims faster. That is what integrity looks like in practice: fewer disputes, quicker cash flow, and more care delivered per naira.This shift can happen faster than many assume. In the first month, schemes and HMOs can agree on a common data dictionary, switch on eligibility checks at encounter creation, and block exact duplicates at intake. Over the next two months, a pilot in two states and one federal teaching hospital can introduce a first‑cut risk score, pre‑authorization tokens for the small set of high‑value procedures that drive spend, and a provider portal that standardizes denial reasons and reduces email ping‑pong. By the end of a quarter, clean‑claim rates can rise materially, duplicate submissions can drop significantly, and average processing time can shrink without starving providers of cash—results that mirror gains in other high‑volume Nigerian businesses when identity, data hygiene, and risk‑based workflows were introduced with discipline.

For business leaders and policymakers, the core metric is credibility. If, within six months, most confirmed improper claims are captured before payment, average turnaround time has fallen by a third, and denial decisions are sustained on appeal more often than not, the system earns the right to move to the next stage—bundles for additional service lines, integrity‑linked capitation, and transparent publication of scheme‑level performance. Credibility changes behaviour: providers spend less time chasing payments and more time delivering care, beneficiaries meet fewer surprise bills, schemes shift spend from administration to medicines, diagnostics, and workforce retention, and the public begins to believe that contributions—whether through taxes, premiums, or donor funds—actually translate into better services.

There will be objections. Connectivity is patchy in many local government areas, some facilities lack the hardware to run slick portals, and data skills are uneven. That is why the design must be offline‑first, the standards minimal, and the training hands‑on. A USSD flow works where fibre does not; a tablet that syncs once a day works where always‑on broadband is a fantasy; and a slim form with 15 clean fields beats a perfect, unusable form with 150. Nigeria does not need a Scandinavian data lake to stop paying the same claim twice.

Payment integrity, ultimately, is not just about protecting balance sheets; it is a patient‑protection strategy. It keeps premiums and public allocations focused on care rather than leakage, smooths cash flow for honest providers already operating on thin margins, and helps restore trust in a system that has suffered too long from opacity. The blueprint is simple: verify identity, standardize the minimum data that matters, aim human review using risk signals that reflect local reality, and learn visibly every month. Start with two states and one teaching hospital; publish the results; iterate. The future of Nigerian healthcare will not be decided by how much we say we spend, but by how wisely we manage what we already have. Payment integrity is the fastest, fairest way to buy real capacity—more drugs on the shelf, more diagnostics that work, more health workers staying on the job. In a scarce environment, prevention is the highest‑return investment Nigeria can make.

Tolulope Abolude is a financial operations professional with a track record of financial recoveries, operational loss reduction, and payment‑integrity implementations across healthcare, telecommunications, and financial services