The concept of phenoconversion is central to the argument. A patient’s genotype predicts how their drug-metabolizing enzymes should work, but the clinical phenotype, meaning the enzyme’s actual functional activity, can diverge sharply from that prediction. Drug-drug-gene interactions, inflammation, and organ dysfunction can all shift a person from a normal metabolizer to a poor metabolizer, or the reverse. The cytochrome P-450 enzyme CYP2D6 is especially consequential here because several widely prescribed opioids depend on it. Codeine and tramadol are true prodrugs requiring CYP2D6 activity to be converted into morphine and o-desmethyltramadol respectively. Hydrocodone is partially dependent on the enzyme for conversion to hydromorphone, while oxycodone’s analgesic effect is enhanced by CYP2D6-mediated formation of oxymorphone. When inhibitors such as the antidepressants fluoxetine or bupropion are on board, enzyme-dependent opioids may simply fail to relieve pain. When the inhibitors are withdrawn, the opposite can happen, and opioid potency can surge.

The authors illustrate both directions of this seesaw with composite clinical cases, drawn from observations across multiple patients rather than empirical validation of a population-level effect. In the first case, a 68-year-old farmer with hypertension, diabetes, chronic kidney disease, and depression treated with fluoxetine fell from his tractor and fractured his hip. After surgical fixation, his pain was severe and unrelenting despite escalating doses of hydrocodone and then oxycodone, forcing his transfer to inpatient rehabilitation. On admission, a physician recognized that fluoxetine, a strong CYP2D6 inhibitor, was effectively blocking activation of the enzyme-dependent opioids through phenoconversion. He was switched to morphine, which bypasses CYP2D6, and within 24 hours achieved sustained analgesia on a total of 22.5 milligrams per day, a fraction of the roughly 90 morphine milligram equivalents of oxycodone that had done nothing.

The second case shows the mechanism working in reverse, with near-fatal consequences. A 72-year-old woman on long-term oxycodone for chronic spine-related pain was admitted with pneumonia and agitation, and her inpatient team stopped her bupropion, another strong CYP2D6 inhibitor, suspecting it was worsening her confusion. Her oxycodone dose was left unchanged. Six days later, after transfer to a rehabilitation facility, she suffered sudden respiratory collapse requiring three doses of naloxone. The abrupt discontinuation of bupropion, with its short half-life, had reversed her enzyme inhibition, restoring CYP2D6 activity and accelerating conversion of oxycodone into its more potent metabolite oxymorphone. The authors note that had she been taking fluoxetine, which lingers far longer in the body, the metabolic shift could have occurred after discharge, at home and unmonitored, where fatal apnea would have been a real possibility.

Both cases also carry a message about how such risks surface during transitions of care, the very points where medication changes, discontinuations, and formulary substitutions are routine. Rural older adults frequently move between acute care hospitals, inpatient rehabilitation, and long-term care, each with different levels of geriatric expertise. Without two-way communication, interdisciplinary training, and careful medication reconciliation across settings, unrecognized metabolic shifts can translate into analgesic failure, delirium misdiagnosed as behavioral disturbance, or life-threatening toxicity. The authors suggest that metabolic awareness deserves a place in delirium evaluation itself, since opioid toxicity or abrupt metabolic change can manifest as agitation that is easily misattributed to cognitive impairment or multimorbidity.

Why single out rural communities? The structural context matters enormously. Rural Health Clinics serve as essential access points for medically underserved populations but operate under reimbursement and workflow constraints that limit adoption of anything beyond what fits existing visit types. Pain specialists, geriatricians, behavioral health clinicians, and pharmacists with pharmacogenomics expertise are persistently scarce in rural areas, even though rural residents are more often exposed to medications with pharmacogenomic prescribing guidance. Rurality is correlated with higher rates of opioid prescribing, and geographic isolation plus transportation barriers delay escalation of care, while digital inequities constrain telehealth. Add multimorbidity, polypharmacy, potentially inappropriate medications, and age-related changes in pharmacokinetics and pharmacodynamics, and the conditions for phenoconversion-related harm become more concentrated precisely where the tools to detect it are least available.

The authors are careful about the limits of their claim. Phenoconversion itself is clinically well established, but its contribution to rural pain inequities remains a plausible yet incompletely characterized pathway, and the composite cases cannot establish causality or generalizability. The article frames its proposal explicitly as an implementation-focused roadmap rather than a validated solution. That honesty matters, because the corollary risk is real: precision health interventions introduced unevenly, favoring clinics with integrated electronic health records and embedded specialists, could inadvertently widen the very gaps they aim to close. The authors therefore build low-technology alternatives into their framework, including the Agency for Healthcare Research and Quality’s electronic care plan tools and the PharmDOG drug optimization guidance resource, for clinics lacking genomic modules, reliable internet, or embedded pharmacists.

The roadmap rests on four pillars intended to work in combination. First, clinical decision support infrastructure: routine medication reconciliation, electronic health record-integrated pharmacogenomic results, and alerts that progress from drug-drug interactions to drug-gene interactions and ultimately to drug-drug-gene alerts prioritizing opioids, with interoperability ensured through Health Information Exchange using the FHIR standard so that alerts follow patients across care settings. Second, telehealth-enabled specialty access, including tele-pain and tele-pharmacy consultation pathways, virtual case reviews for complex regimens, and remote pharmacogenomic interpretation. Third, workforce development through case-based learning on phenoconversion, shared decision-making tools, and precision prescribing training spanning primary, acute, rehabilitation, and long-term care. Fourth, system-level support covering reimbursement for pharmacogenomic testing and pharmacist services, broadband expansion, digital literacy support, and state policy levers such as Medicaid coverage of biomarker testing, which Florida has already enacted.

The proposal is grounded in a working example. Archer Family Health Care, a rural health clinic in Archer, Florida, where roughly one in 4.3 adults is over 65, piloted an interdisciplinary precision prescribing model built on the Epic electronic health record’s genomics module. Pharmacists used integrated medication records to generate personalized recommendations in patient-friendly educational formats, and where pharmacogenomic results were available, best-practice alerts provided real-time reminders to clinicians. Early clinician impressions, explicitly framed as quality-improvement experience rather than formally evaluated outcomes, suggested that older adults valued individualized explanations of their medications and that providers grew more confident applying precision principles in a busy primary care setting. The clinic’s reliance on pre-existing digital infrastructure, the authors concede, is an advantage not universally shared.

What emerges is a vision that treats the biology and the structure of rural health care as inseparable. Older adults are not a homogenous group; they differ in genetics, epigenetic changes shaped by life-course exposures, frailty, comorbidity burden, coping strategies, and social context, all of which shape analgesic effectiveness and risk. Precision medicine, combined with shared decision making that brings patient goals, caregiver perspectives, and functional priorities into every medication decision, offers a way to honor that heterogeneity. But as the authors emphasize, translating that promise into equity will require coordinated action across clinical, system, and policy domains, and evidence will be needed to evaluate whether these approaches actually reduce disparities at scale. If they do, the humble rural health clinic may prove to be the unexpected catalyst for a transformation in geriatric pain care, one in which a routine medication change no longer carries the hidden power to rescue or endanger a patient without anyone knowing why.

Subject of Research: Phenoconversion and precision medicine approaches to reduce rural pain management inequities in older adults

Article Title: Phenoconversion and rural pain inequities: a precision-informed roadmap to advance equity for rural older adults

Article References: Hall, A. K., Cicali, E. J., Schentrup, D., & Dubin, A. H. (2026). Phenoconversion and rural pain inequities: a precision-informed roadmap to advance equity for rural older adults. Frontiers in Pain Research, 7, Article 1883083. https://doi.org/10.3389/fpain.2026.1883083

Image Credits: AI Generated

DOI: 10.3389/fpain.2026.1883083

Keywords: phenoconversion, CYP2D6, pharmacogenomics, rural health, geriatric pain, opioids, precision medicine, health equity, polypharmacy, telehealth, clinical decision support, shared decision making