Diaceutics Severely Uncontrolled Diabetes Dataset

The Diaceutics Severely Uncontrolled Diabetes Dataset provides structured, de-identified real-world data from over 600 U.S.-based laboratories, focusing on diagnostic activity related to poor glycemic control. This dataset specifically identifies patients with severely uncontrolled diabetes, defined by Hemoglobin A1c (HbA1c) levels exceeding 8.1%, a threshold associated with elevated risk for diabetes-related complications and suboptimal disease management.

Each record represents a unique laboratory test event, with the TEST_DATE field indicating when results were reported. Test-level data is standardized using LOINC codes, and includes fields such as RESULT_NAME, RESULT_VALUE, RESULT_REFERENCE_RANGE, and RESULT_UNITS_OF_MEASURE.

Patient-level information includes a hashed PATIENT_ID and GENDER, while the ordering physician is identified via PHYSICIAN_NPI. This structure enables cohort definition and analysis based on test name, LOINC, result thresholds (e.g., HbA1c >8.1%), physician, gender, and year of birth.

Diaceutics supports advanced linkage capabilities via Datavant tokens, enabling integration with diagnosis codes or therapy exposures for enhanced stratification in real-world evidence (RWE) and health economics and outcomes research (HEOR) applications. Common use cases include:

- Identifying high-risk patient populations
- Evaluating gaps in diabetes management
- Supporting trial feasibility and intervention targeting

Data is delivered through the Snowflake Marketplace under a contract-based access model, with flexible delivery frequencies, including weekly updates.

HbA1c is a critical biomarker for assessing long-term glucose regulation. It reflects the average blood glucose concentration over the prior 2-3 months by measuring the percentage of glycated hemoglobin in red blood cells. Elevated HbA1c levels (>8.1%) are indicative of poor glycemic control, and are associated with increased risk for complications such as neuropathy, nephropathy, retinopathy, and cardiovascular disease.

In clinical practice, HbA1c is used to:

- Monitor the effectiveness of diabetes management strategies
- Identify patients at risk for adverse outcomes
- Guide therapeutic adjustments and care planning

原始信息汇总

Diaceutics Severely Uncontrolled Diabetes Dataset

数据集概述

包含过去12个月内严重未控制糖尿病检测事件相关的实验室数据记录，重点关注糖化血红蛋白（HbA1c）水平超过8.1%的患者群体。

数据来源与覆盖范围

• 数据来源：来自600多家美国实验室的结构化、去标识化真实世界数据
• 时间覆盖：过去12个月
• 地理覆盖：美国所有州
• 数据更新频率：每周更新

数据内容与结构

患者信息

• PATIENT_ID：哈希处理的患者标识符
• GENDER：性别
• YEAR_OF_BIRTH：出生年份

医生信息

• PHYSICIAN_NPI：医生NPI标识符
• PHYSICIAN_SPECIALTY：医生专业

检测信息

• TEST_ID：检测标识符
• TEST_DATE：检测报告日期
• LOINC_NAME：LOINC检测名称
• LOINC_CODE：LOINC代码
• TEST_NAME：检测名称

结果信息

• RESULT_ID：结果标识符
• RESULT_NAME：结果名称
• RESULT_VALUE：结果数值
• RESULT_REFERENCE_RANGE：结果参考范围
• RESULT_UNITS_OF_MEASURE：结果测量单位

主要特征

• 专门识别严重未控制糖尿病患者（HbA1c > 8.1%）
• 使用LOINC代码进行检测级数据标准化
• 支持通过Datavant令牌进行高级链接功能
• 支持基于检测名称、LOINC、结果阈值、医生、性别和出生年份的队列定义和分析

应用场景

业务需求

• 受众激活：基于实时实验室检测行为定位医疗专业人员
• 需求预测：按检测、生物标志物或地理位置跟踪真实世界诊断需求
• 生命科学商业化：加速上市规划和市场执行
• 患者360：访问去标识化的实验室锚定患者视图
• 市场分析：分析诊断市场份额和检测采用情况
• 真实世界数据：解锁专注于实验室结果和生物标志物趋势的策划数据

常见用例

• 识别高风险患者群体
• 评估糖尿病管理差距
• 支持试验可行性和干预目标确定

数据交付

• 交付平台：Snowflake Marketplace
• 访问模式：基于合同的访问模式
• 交付频率：灵活的交付频率，包括每周更新

技术说明

• 数据表名称：MARKETPLACE_SEVERELY_UNCONTROLLED_DIABETES_12M
• 支持与外部索赔和EHR来源集成
• 适用于真实世界证据和健康经济学与结果研究应用