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.本仓库包含研究《风险导向数据分析助力可持续药品供应链：公立肿瘤医院治理框架》中使用的全部原始运营数据层与可复现代码。本仓库托管的材料可实现论文中呈现的分析、图表以及库存参数前后对比表的全透明与端到端复现。 内容 本仓库包含以下组件： 1. 原始运营数据集（Excel格式） 这些文件来自某公立肿瘤医院的真实机构数据，覆盖药品供应链的多个环节： - ABC/XYZ分类与机构库存参数（基础参数ss、SSSSSS、QQQ） - 2023年至2024年的月度消耗数据 - 不同采购渠道下的采购提前期与到货模式 - 库存水平与超额库存估值 - 库存上限/补货设置（遵循机构治理规范） - 包含价格、剂型与单位拆分的物料主数据 - 适用场景下的缺货、库存损耗与运营事件记录 所有数据均为严格的运营数据，不包含任何患者层面的可识别信息。 2. 可复现代码 本仓库提供了极简可执行流程，用于重新生成论文模块7中使用的连续盘点库存参数(s, SS, Q)的预处理步骤与示例前后对比表。具体内容包括： - zenodo_example_pipeline.py：用于数据协调、合并、优先级排序以及计算示例(s_new, SS_new, Q_new)的主Python脚本。 - requirements.txt：精确依赖项（pandas、numpy、openpyxl）。 - README_zenodo_example.md：流程执行说明文档。 - 支持通过Parámetros de stock.xlsx合并用户提供的优化参数。 本代码设计为可兼容不一致的列名、缺失的可选文件以及异构运营数据源。 3. 文档 附加说明文档涵盖以下内容： - 各数据集的预期数据架构 - 各数据层间的交互逻辑 - 代码如何重新生成论文中报告的表格 - 如何针对替代优先级排序或治理规则扩展或适配该流程 目标 本仓库旨在支持以下工作： - 数据驱动的公共部门决策透明度 - 风险导向分析工作流的可复现性 - 验证论文中提出的治理框架 - 可持续药品供应链管理领域的未来方法学扩展 许可与伦理考量 所有文件均开放用于科学与学术用途。本数据集仅包含行政运营记录，未包含任何患者信息。