Diaceutics Lab Diagnostics Dataset (Non-Genomic) Sample

The Diaceutics Lab Diagnostics Dataset provides structured, de-identified real-world data from over US based 600 laboratories, capturing diagnostic activity across both commonly ordered non-genomic tests and emerging lab tests, such as A1C, CBC, immunoassays, and clinical chemistry panels. Each record reflects a unique test event, including the test ordered (TEST_NAME), specimen collection date (SPECIMEN_COLLECTION_DATE), and the date results were reported (TEST_REPORT_DATE).

Test-level results are captured at the LOINC level with fields such as RESULT_NAME and RESULT_VALUE, alongside clinical context fields like RESULT_REFERENCE_RANGE and RESULT_UNITS_OF_MEASURE. Patient-level data includes a hashed patient ID (PATIENT_ID) and gender (GENDER). Ordering and referring provider behavior is captured through ORDERING_PROVIDER_NPI_NUMBER and REFERRING_PROVIDER_NPI_NUMBER.

This dataset enables users to define and analyze cohorts based on test name, LOINC, result thresholds, ordering provider, gender, and year of test. Diaceutics has the ability to support linkage (via Datavant tokens) to diagnosis codes or therapy exposures supports advanced stratification for real-world evidence (RWE) and health economics (HEOR) use cases. Common applications include diagnostic access planning, trial feasibility analysis, and test-defined patient segmentation.

Data is delivered through the Snowflake Marketplace under a contact-based access model. Diaceutics provides the dataset directly to your Snowflake environment with the ability to support deliveries as frequently as weekly.

**The 'Diaceutics Lab Diagnostics Dataset (Non-Genomic) Sample' listing is a 7-day sample dataset containing A1C data only.*

原始信息汇总

Diaceutics Lab Diagnostics Dataset (Non-Genomic) Sample

概述

• 数据提供方: Diaceutics Inc
• 访问权限: 免费，无限访问
• 数据内容: 包含2025-06-01至2025-06-08期间与A1C检测事件相关的实验室数据记录
• 数据来源: 美国600多家实验室的结构化、去标识化真实世界数据
• 数据类型: 非基因组测试（如A1C、CBC、免疫测定和临床化学面板）

关键字段

• 测试事件: TEST_NAME, SPECIMEN_COLLECTION_DATE, TEST_REPORT_DATE
• 测试结果: RESULT_NAME, RESULT_VALUE, RESULT_REFERENCE_RANGE, RESULT_UNITS_OF_MEASURE
• 患者数据: PATIENT_ID (哈希处理), GENDER
• 提供者行为: ORDERING_PROVIDER_NPI_NUMBER, REFERRING_PROVIDER_NPI_NUMBER

业务需求

1. 受众激活: 基于实时实验室和基因组测试行为定位HCP
2. 需求预测: 跟踪真实世界诊断需求（按测试、生物标志物或地理位置）
3. 生命科学商业化: 加速上市规划和市场执行
4. 患者360: 访问去标识化、实验室锚定的患者视图
5. 市场分析: 分析诊断市场份额、测试采用率和实验室覆盖范围
6. 真实世界数据(RWD): 解锁专注于实验室结果、基因组测试和生物标志物趋势的RWD

数据字典

• 未提供详细信息

使用示例

1. 患者分布: 按治疗领域分组统计独特患者数量
2. 测试患者数: 统计至少接受一次测试的独特患者数量
3. 测试医师数: 统计至少执行一次测试的独特医师数量
4. 高频测试: 识别最常执行的测试
5. 医师分布: 按治疗领域分组统计独特医师数量
6. 专科医师数: 按专科领域分组统计独特医师数量

技术细节

• 数据交付: 通过Snowflake Marketplace基于联系人的访问模型交付
• 更新频率: 支持每周交付
• 时间覆盖范围: 2025-06-01至2025-06-08（按天）
• 地理覆盖范围: 美国（所有州）
• 云区域可用性: AWS US East (N. Virginia), US East (Ohio)

联系方式

• 销售: [e-mail]
• 支持: [e-mail]

关于Diaceutics Inc

• 提供全球首个精准医学诊断商业化平台DXRX
• 整合来自全球实验室网络的真实世界诊断测试数据