Dataset and Code for Risk-Informed Data Analytics for Sustainable Pharmaceutical Supply: A Governance Framework for Public Oncology Hospitals

This repository contains all raw operational data layers and reproducible code used in the study “Risk-Informed Data Analytics for Sustainable Pharmaceutical Supply: A Governance Framework for Public Oncology Hospitals.” The materials hosted here enable full transparency and end-to-end replication of the analyses, figures, and before–after inventory parameter tables presented in the manuscript. Contents The repository includes the following components: 1. Raw operational datasets (Excel) These files correspond to real institutional data from a public oncology hospital and cover multiple layers of the medication supply chain: ABC/XYZ classifications and institutional stock parameters (base sss, SSSSSS, QQQ) Monthly consumption data (2023–2024) Purchase lead times and arrival patterns by procurement channel Inventory levels and overstock valuations Stock maximum/replenishment settings (as defined by institutional governance) Item master data including price, formulation, and subunit Records of stockouts, mermas, and operational events when applicable All data are strictly operational and contain no patient-level or identifiable information. 2. Reproducible code A minimal, executable pipeline is provided to regenerate the preprocessing steps and the illustrative before–after table of the continuous-review inventory parameters (s,SS,Q)(s, SS, Q)(s,SS,Q) used in Module 7 of the manuscript. Contents include: zenodo_example_pipeline.py — main Python script for data harmonization, merging, prioritization, and computation of illustrative (snew,SSnew,Qnew)(s_{new}, SS_{new}, Q_{new})(snew,SSnew,Qnew). requirements.txt — exact dependencies (pandas, numpy, openpyxl). README_zenodo_example.md — instructions for executing the pipeline. Optional merging of user-supplied optimized parameters through Parámetros de stock.xlsx. The code is designed to be robust to inconsistent column names, missing optional files, and heterogeneous operational sources. 3. Documentation Additional notes explain: Expected schema of each dataset How the data layers interact How the code regenerates the tables reported in the paper How to extend or adapt the pipeline for alternative prioritizations or governance rules Purpose The goal of this repository is to support: Transparency of data-driven public-sector decision-making Reproducibility of the risk-informed analytical workflow Validation of the governance framework proposed in the manuscript Future methodological extensions in sustainable pharmaceutical supply chain management License and ethical considerations All files are released for scientific and academic use. The dataset contains administrative operational records only; no patient information is included.