"Are you watching this month's numbers?" — a single question from a manager reshapes how a rep structures the next day's physician visits. Sales targets, market share, end-of-quarter close rates. The numerical gravity bearing down on pharmaceutical reps every day competes with the weight of approved scientific evidence — and over time, it wins. A hint implying off-label use. A suggestion on how to sidestep a prescription restriction. A scheme to avoid insurance audit. None of these begin with malice. They begin with the conviction that "this drug can help this patient." This article examines the psychological architecture behind that conviction, anchored to real incidents on record.

So What / So Why — The Core of This Issue

The central problem with numerical gravity is that deviations do not start from bad intent. When a rep suggests an off-label use to a physician, the internal experience is usually a belief: "This drug genuinely works. Patients aren't getting the treatment they need." Whether that belief is correct is beside the point. The damaging pattern is the order of operations: the conclusion comes first, then the rep selects supporting data and dismisses contradicting data. That sequence distorts judgment.

Why is this fatal? Regulatory approval is a government certification that "efficacy and safety have been confirmed for this specific dosage regimen and indication." Outside that boundary lies territory where evidence is absent or insufficient. Directing patients into that territory is equivalent to placing them outside the net of post-marketing safety surveillance. The moment a rep tells a physician "this dosage won't trigger an insurance audit," any adverse events arising from that prescription go unrecorded, and the safety information in the package insert never accumulates. Regulation is not bureaucratic friction — it is the information-collection mechanism itself.

What makes numerical gravity dangerous is that the entry point is a morally correct motive: the patient's benefit. If prescriptions rise, the company grows, R&D investment continues, and the next drug gets made — reps who believe that chain of logic tend to experience a missed target not merely as personal failure but as a failure to contribute to medicine. That feeling pushes them one step further at the next visit.

The Structure of Pressure — Who, What Deadline, What Numbers

Multiple actors exert pressure on pharmaceutical reps. The direct manager (district manager) reviews visit counts, prescription volumes, and market share weekly and monthly. District managers are evaluated quarterly by regional headquarters, and those evaluations directly determine rep bonuses and promotions. The metrics typically combine product-level sales attainment rates, market share, new prescriber acquisition counts, and formulary retention at targeted hospitals.

Deadlines amplify the pressure. End-of-quarter periods — especially March and September — create organization-wide awareness that "this is when we build the numbers." Newly launched products face demands for fast early results because "the prescription record established in the launch phase determines future share." Pre-patent-expiry originator products face pressure to maximize volume before generic entry. For products with pending indication expansions, the temptation to "build physician awareness before approval" is structurally built in.

KOL (Key Opinion Leader) relationships carry their own gravity. Speaker invitations, honoraria, and symposium sponsorship create a sense of reciprocity between reps and KOLs — a mutual feeling of debts and obligations. When a KOL presents an off-label use at a conference, the rep can shelter under the authority of "the doctor said so" — a direct link to the responsibility externalization mechanism discussed below.

Internal politics and manager oversight add another layer. Multiple monitoring reports document cases in which reps made exaggerated claims during presentations attended by their own managers. If an organization's culture makes it impossible to say "honestly, we won't hit the target," deviations in the field become the performance that management implicitly demands.

The Internal Reconstruction — Beliefs, Emotions, Deep Psychology

Beliefs — What the person took to be true

Many reps caught in numerical gravity held the belief that "I haven't been able to convey this drug's value to physicians correctly." They felt the approved dosage regimen was excessively conservative. Secondhand accounts — "there are physicians at other hospitals who use it that way" — were accepted as practical clinical wisdom. Pre-approval indication data was shared out of a sense of duty: "I want physicians to know about this as early as possible, for patients' sake." Even knowing the regulation existed, a self-constructed interpretation had solidified: "The spirit of the rule is patient benefit, and exceptions are acceptable when patient benefit requires it."

Emotions — What was felt in the moment

The night before a monthly report, staring at 70% of target while reviewing the next morning's visit list. The anxiety that last week's presentation failed to land. The low-grade shame of being asked by a manager "what's missing." Watching a peer celebrate hitting quota at the end of the quarter. These emotions do not directly instruct anyone to deviate. But they lower the threshold for the judgment: "Maybe I should bring up that use we haven't discussed before."

Deep Psychology — How Four Drivers Operated

① Motivated reasoning. As psychologist Ziva Kunda demonstrated in 1990, when people are motivated to reach a desired conclusion, they selectively seek out evidence that supports it. If "this drug helps patients" is the predetermined conclusion, only favorable data enters the field of vision. A single overseas paper supporting off-label use overwrites the meaning of the drug being off-label.

② Local rationalization. "I prefaced it with 'this is off-label, but'" functions as a self-issued permission slip. Showing one extra slide, answering because the physician asked, framing it as a general observation — each act is processed as a "small exception," but in aggregate they constitute a clear deviation.

③ Omission bias. Rather than "proposing" a workaround to a prescription restriction, the rep positions themselves as passively responding — "the physician asked, so I answered." Not mentioning safety information because "they didn't ask" is processed similarly. Because the act is not perceived as active, the guilt threshold is far lower.

④ Responsibility externalization. "The KOL said so at a lecture." "My manager was there and didn't stop it." "The physician said they wanted to use it, so I provided information." The person who acted places themselves in the role of messenger or intermediary, attributing the decision to external parties. In a lecture-meeting case recorded in the March Reiwa 7 (2025) report, the company's failure to contradict the presenting physician was itself evaluated as amounting to co-promotion (author's characterization).

The Underlying Real Incidents

The three cases below show how the combination of numerical gravity and deep psychology produced actual deviations. Full details are in Analysis Vol. 04: "Presenting Unapproved Indications and Dosage Regimens."

Case 1: Dyslipidemia Drug (March Heisei 31 / 2019 Report) — Engineering Single-Agent Prescribing to Avoid Insurance Audit

Medium / setting: Verbal explanation by MR (individual physician visit)

What happened: Approval conditions for the drug required co-administration with another agent. The rep explained: "If you prescribe a cheap drug like a generic alongside it and tell the patient they don't need to take it, you can avoid the insurance audit and effectively use this as a single agent. Some physicians are already prescribing it that way."

Trace of numerical gravity: This explanation was designed to reduce physician resistance and increase prescription volume. The co-administration requirement adds prescribing complexity and drug cost burden — barriers to selection. The proposal was structured to eliminate those barriers.

Deep psychology: Motivated reasoning came first: "This drug genuinely works, but systemic constraints are keeping it from patients." Gaming the insurance system was then locally rationalized as "practical clinical wisdom for patients." The secondhand claim that "other physicians are doing it" served as social proof, lowering the psychological barrier to action.

Case 2: SGLT2 Inhibitor (March Reiwa 4 / 2022 Report) — Expanding Prescriptions by Attaching a CKD Diagnosis

Medium / setting: Face-to-face explanation by MR (stated in a context the healthcare professional had not requested)

What happened: HFpEF (heart failure with preserved ejection fraction) was not an approved indication for the drug. The rep stated: "Physicians are saying it has become easier to prescribe for HFpEF patients by attaching a chronic kidney disease diagnosis." The cited literature was data for a competitor's product.

Trace of numerical gravity: SGLT2 inhibitors were undergoing rapid indication expansions, with companies competing to widen the prescribing population. Widening it through "diagnostic adjustment" was faster than waiting for approval. The expectation of an indication expansion structurally generates the temptation to prepare physicians before the approval arrives.

Deep psychology: Responsibility externalization appeared in its clearest form. By using the structure "physicians are saying," the rep positioned themselves as a transmitter of information, not its originator. Omission bias compounded this: passing along the information without flagging the problem with diagnostic manipulation became, in practice, a recommendation.

Case 3: Insomnia Drug (March Reiwa 3 / 2021 Report) — Proposing a Workaround to Long-Term Prescription Restrictions

Medium / setting: Verbal explanation by MR

What happened: The product was a new drug within its first year post-approval, subject to long-term prescription restrictions. The rep proposed: "If you prescribe half the dose as two tablets for fourteen days, you can effectively give a twenty-eight-day supply."

Trace of numerical gravity: Long-term prescription restrictions directly affect the prescription volume that accumulates during the launch period. Once restrictions lift, prescription counts jump. The organizational pressure to build volume during the restricted period — even incrementally — generated this proposal.

Deep psychology: The rep understood the rationale for new-drug prescription restrictions — to rapidly accumulate safety data in the early post-marketing period and confirm real-world use patterns. And yet actively proposed the workaround. Local rationalization was at work: "I'm only prescribing a dosage that is individually within approved parameters" served as a self-issued permission that destroyed the regulatory purpose while framing it as ingenuity.

Inside the Creator ── The Psychology Behind Deviations ── Map of 10 chapters

  1. Part 1: A Map of Pressure — How Good Intentions Bend
  2. Part 2: The Creed Trap — "I Want to Help Patients" as the Entry Point
  3. Part 3: Conclusion First, Data Second — Motivated Reasoning
  4. Part 4: "Just One Slide" — Local Rationalization
  5. Part 5: The Choice Not to Speak — The Sin of Omission
  6. Part 6: Structures That Let You Blame Someone Else — Externalizing Responsibility
  7. Part 7 (this chapter): The Gravity of Numbers — Quotas and the Psychology of Incentives
  8. Part 8: The Anxiety of Competition — How Panic Becomes Disparagement
  9. Part 9: The Silent Organization — Conformity Pressure, Hollow Audits, and the Self That Won't Disclose
  10. Part 10: Redesigning Pressure — Individual Psychology and Organizational Systems
Key Points
  1. Quota pressure produces deviations not through malice but through conviction. When a rep facing a sales target takes one step further, it is usually because they believe they are doing the right thing. The "motivated reasoning" that constructs that conviction is the deepest threat to safety management.
  2. Avoiding an insurance audit is a different matter from medical appropriateness. Suggestions like "this dosage won't be audited" or "attach this diagnosis and you can prescribe it" may raise prescription counts, but they make it impossible to record adverse event causality. This is the path by which numerical pressure destroys the regulatory purpose itself.
  3. "Other physicians are doing it. " "The doctor asked me, so I answered." "My manager was there." Responsibility externalization converts the actor into a messenger and dissolves guilt. As long as that self-reframing is in place, education and punishment have limited deterrent effect. The question that matters is not who made the decision — it is what happened to the patient.
References
  1. Guidelines on Sales Information Activities for Ethical Drugs (Ministry of Health, Labour and Welfare, Yakuseikaima-hatsu 0925 No. 1, September 25, 2019)
  2. Advertising Activity Monitoring Project for Ethical Drugs — Report (March Heisei 31 / 2019) (MHLW Commissioned Project)
  3. Sales Information Provision Monitoring Project for Ethical Drugs — Report (March Reiwa 3 / 2021) (MHLW Commissioned Project)
  4. Sales Information Provision Monitoring Project for Ethical Drugs — Report (March Reiwa 4 / 2022) (MHLW Commissioned Project)
  5. Sales Information Provision Survey Project for Ethical Drugs — Report (March Reiwa 7 / 2025) (MHLW Commissioned Project)
  6. Standards for Appropriate Advertising of Pharmaceuticals, etc. (Ministry of Health, Labour and Welfare)
  7. Guidelines for Preparing Product Information Compendiums for Ethical Drugs (Japan Pharmaceutical Manufacturers Association)
  8. Kunda, Z. (1990). The Case for Motivated Reasoning. Psychological Bulletin, 108(3), 480–498.
  9. Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
  10. Ariely, D. (2012). The (Honest) Truth About Dishonesty: How We Lie to Everyone — Especially Ourselves. HarperCollins.
  11. Cialdini, R. B. (2001). Influence: Science and Practice (4th ed.). Allyn & Bacon.
  12. Shirakami M. et al. (2016). Analysis of pharmaceutical industry compliance violations in drug-related regulations and proposed recurrence-prevention measures based on their background. FY Heisei 27 MHLW Health and Labour Sciences Research Grant — Regulatory Science Policy Research on Pharmaceuticals and Medical Devices: Summary and Divisional Research Report.