The clinical case for GLP-1 receptor agonists in obesity management is no longer a debate. Randomized controlled trials have demonstrated sustained weight reduction of 15 to 22 percent of body weight, meaningful improvements in cardiovascular outcomes, and reductions in obesity related comorbidities including type 2 diabetes and sleep apnea. The American Association of Clinical Endocrinology, the American Gastroenterological Association, and major cardiology societies have all updated their guidelines to reflect this evidence. Clinically, the question of whether these medications work has been settled.
The question that has not been settled — and that is quietly determining who actually receives this care — is whether the health IT infrastructure supporting access to these therapies is adequate. It is not. The prior authorization systems, formulary management platforms, and electronic health record integrations that sit between a clinician’s prescribing decision and a patient filling a prescription were not designed for a drug class of this complexity, this volume, or this clinical significance. They are failing, and patients are the ones absorbing the cost.
Consider what the prior authorization workflow actually demands for a GLP-1 prescription. A clinician must document body mass index thresholds, the presence or absence of specific comorbidities, prior treatment attempts with qualifying agents, and often a formal dietary counseling attestation — all formatted to the exacting and frequently idiosyncratic requirements of a given payer’s criteria. The American Medical Association’s 2023 Prior Authorization Physician Survey found that 93 percent of physicians report delays in patient care due to prior authorization, and 82 percent report that the process sometimes leads patients to abandon recommended treatment altogether. For GLP-1 therapies, initial denial rates from commercial payers have been reported as high as 30 to 50 percent, with successful appeals requiring weeks of additional documentation exchange.
The technology layer underneath this process is strikingly outdated. Despite the existence of the NCPDP SCRIPT ePA standard and CMS mandates encouraging electronic prior authorization adoption, a substantial share of PA requests for specialty medications — including GLP-1 agents — still travel by fax. Where electronic portals exist, they are rarely integrated with the EHR workflow. The physician’s team must manually re enter clinical data that already lives in structured fields inside the patient’s chart: the BMI from the last visit, the A1C trend from the lab panel, the documented counseling session from six months ago. That redundant data entry is not merely inefficient. It introduces transcription error, consumes clinical staff time, and extends turnaround. For a drug class where early treatment initiation correlates with better long term adherence, a two to four week authorization delay is not a paperwork inconvenience — it is a clinical access barrier.
This is the distinction that health IT leaders and policymakers must internalize: a plan can technically cover a GLP-1 agent while its prior authorization infrastructure functions as a de facto denial mechanism. Coverage on paper means nothing if the administrative pathway to that coverage is inaccessible to the average primary care practice without a dedicated authorization team. Small practices, rural practices, and practices serving Medicaid populations are disproportionately affected. The burden does not fall equally, and the disparity is in large part a technology gap.
There is a secondary technology failure worth naming. GLP-1 therapies are expensive, and payers are understandably interested in outcomes data to support value based contracting arrangements. But the data pipelines that would enable that kind of outcomes measurement — connecting prescription fill data, lab trends, weight trajectories, and downstream utilization across plan years — largely do not exist in integrated form. EHR data remains siloed from claims data. Real-world outcomes that could justify formulary placement or tiered cost sharing go unmeasured because no one has built the infrastructure to capture them systematically. The irony is that the same payers resisting broad access on cost grounds are also failing to invest in the outcomes tracking architecture that would let them evaluate whether their cost concerns are justified.
What would better health IT infrastructure look like? At minimum, it would mean true EHR integrated ePA — not a portal that clinicians open in a separate browser window, but a workflow embedded in the prescribing interface that automatically populates payer criteria from structured chart data and returns a real time eligibility determination. It would mean formulary APIs that surface coverage status and prior authorization requirements at the point of prescribing, before a prescription is sent to the pharmacy. It would mean standardized outcomes data schemas that allow participating practices to contribute deidentified longitudinal data to payer provider value arrangements. The technical standards for most of this — HL7 FHIR, the Da Vinci Prior Authorization Support implementation guide, NCPDP SCRIPT — already exist. The gap is not innovation. It is implementation.
The GLP-1 revolution is real. But its benefits will remain inequitably distributed as long as the administrative and IT infrastructure surrounding access lags this far behind the clinical evidence. Health IT professionals, EHR vendors, payer technology teams, and standards bodies have a specific and tractable problem in front of them. The patients who could benefit from this drug class are waiting on a prior authorization queue, not a clinical trial. The tools to fix this already exist. The will to deploy them is the variable that still needs to change.
About Dr. Quoc N. Dang, DO
Dr. Quoc N. Dang, DO, is a Medical Director specializing in obesity medicine and GLP-1 therapy.
