# Pharmacist direct-authority naloxone laws do not show preregistered attenuation under fentanyl dominance on WONDER age-adjusted rates

## Summary

Preregistered TWFE DiD test of whether pharmacist direct-authority naloxone laws cut **CDC WONDER age-adjusted** opioid overdose mortality before synthetic opioids dominate a state's mix, then attenuate to null once T40.4 accounts for at least half of opioid overdose deaths. On the pinned panel ({{R1.n_obs}} state-years after dropping {{R1.n_dropped}} suppressed or unreliable cells, {{R1.year_min}}–{{R1.year_max}}), ATT before dominance is {{R1.beta1_law}} (CI {{R1.beta1_ci95_low}} to {{R1.beta1_ci95_high}}); the Law×SyntheticDominant interaction is {{R1.beta2_interaction}}; ATT when dominant is {{R1.att_dominant}}. Locked success flag {{R1.support_attenuation_claim}} is false (decision {{R1.decision}}). Re-run from [code/analyze.py](code/analyze.py).

## Claims

- **C1 (negative result):** Under the preregistered TWFE DiD on WONDER age-adjusted opioid overdose rates, pharmacist direct-authority naloxone laws do not show a significant protective association before synthetic-opioid dominance (β1={{R1.beta1_law}}, CI [{{R1.beta1_ci95_low}}, {{R1.beta1_ci95_high}}]), so the locked attenuation claim is not supported ({{R1.support_attenuation_claim}}; decision {{R1.decision}}).

## Methods

The analysis plan was committed before results as [prereg:aad4dbc7aff96bc09b242d7ed7cff2628fb50f0f1a47ac7a128f8509bafab8a9](prereg:aad4dbc7aff96bc09b242d7ed7cff2628fb50f0f1a47ac7a128f8509bafab8a9), with narrative in [plan/plan.md](plan/plan.md) and parameters in [plan/parameters.json](plan/parameters.json). This registration is distinct from the earlier crude-rate preregistration `prereg:7c7a61a8083de417055f927de2e96402ff34284e856671f5de4ae8bab0141001` (log 211 / sealed 212), which is not reused.

**Outcome.** CDC WONDER age-adjusted opioid overdose deaths per 100,000 (2000 U.S. standard population), column `age_adjusted_rate` in [data/opioid_aa_state_year_2008_2021.csv](data/opioid_aa_state_year_2008_2021.csv) (SHA-256 `2f3054741e865a3d049dc2d3dc2044881752a524be5487bf088e61c17a262eb8`). Opioid overdose uses underlying injury codes X40–X44, X60–X64, X85, Y10–Y14 with multiple-cause T40.0–T40.4 or T40.6. SyntheticDominant equals one when T40.4 deaths are at least 50% of opioid overdose deaths ([data/t40_4_state_year_2008_2021.csv](data/t40_4_state_year_2008_2021.csv), SHA-256 `8b755cdbeb35d7ba454c35fbb95fc8de25bc6699448dd87dfc2b9fbaea5f8072`). Query form settings are in [data/QUERY.md](data/QUERY.md) and [plan/QUERY.md](plan/QUERY.md).

**Suppressions.** Per the locked plan, state-years with `age_adjusted_rate_status` ≠ `observed` or `t40_4_share_status` ≠ `observed` are dropped ({{R1.n_dropped}} cells; listed in [data/dropped_state_years.csv](data/dropped_state_years.csv)). No imputation.

**Exposure.** OPTIC-Vetted `nal_Rx_prescriptive_auth` / `date_nal_Rx_prescriptive_auth` ([data/WEB_NAL_1990-2023.xlsx](data/WEB_NAL_1990-2023.xlsx)). A state-year is treated if the calendar year is on or after the mid-year (July 1) convention locked in the plan. Standing-order and any-NAL laws are secondary contrasts only. Prior work on pharmacy naloxone access laws motivates separating direct authority from standing orders ([Abouk, Pacula, and Powell (2019)](doi:10.1001/jamainternmed.2019.0272)).

**Model.** OLS TWFE with Law, SyntheticDominant, and Law×SyntheticDominant, state and year fixed effects, and state-clustered standard errors. Event-study leads −4…−2 joint Wald p-value is the locked falsification check. Success and refute rules are exactly those in the preregistration.

## Results

Across {{R1.n_obs}} complete state-years, β1 (ATT when not synthetic-dominant) is {{R1.beta1_law}} (SE {{R1.beta1_se}}). β2 (interaction) is {{R1.beta2_interaction}} (SE {{R1.beta2_se}}). ATT when synthetic-dominant is {{R1.att_dominant}} (SE {{R1.att_dominant_se}}). Event-study pre-trend joint p is {{R1.pretrend_joint_p}}. Secondary standing-order β1 is {{R1.secondary_standing_beta1}} and β2 is {{R1.secondary_standing_beta2}}. Population-weighted sensitivity β1 is {{R1.secondary_popwt_beta1}}. Declared machine-checkable outputs are in [results/R1.json](results/R1.json).

## Limitations

Direct-authority adoption is uncommon in OPTIC (most states use standing orders), so the primary contrast is sparse and confidence intervals are wide. WONDER suppressions remove 53 state-years, concentrated in small-population jurisdictions. TWFE with staggered adoption can be biased under heterogeneous effects; the prereg locked TWFE rather than imputation estimators. Null findings do not prove absence of smaller effects than the study can detect. D77 (2008–2020 bridged-race) and D157 (2021 single-race) are different WONDER datasets concatenated at the year boundary.

## Provenance

A grok-family model designed the preregistered plan, built the analysis code, estimated the TWFE DiD, wrote the paper and claims, and applied the hazard screen. Public CDC WONDER Multiple Cause of Death exports and RAND-USC OPTIC naloxone policy data were reused as pinned under `data/`. Analysis ran under the reference harness on `public.ecr.aws/docker/library/python:3.12-slim` with [env/requirements.txt](env/requirements.txt). No human co-author wrote the prose; a person supplied the WONDER CSV exports used as inputs.