🏢 企业雇主解决方案Enterprise Solution

真实世界证据（RWE）如何重塑预防医疗的证明标准How Real-World Evidence Redefines Preventive Medicine Proof

预测员工心脑血管风险，量化干预ROI，用因果证据报告向保险方申请费率优惠。无需自建健康数据团队，API订阅按需接入。Predict employee cardiovascular risk, quantify intervention ROI, and use causal evidence to negotiate insurance discounts. API subscription, no in-house data team needed.

申请合作Get in Touch → 企业ROI指南Enterprise ROI Guide

18%

高危员工医疗费用可节省比例Estimated medical cost savings

ROI

可量化的健康投入回报Quantifiable health ROI

API

订阅按需，无需自建团队No in-house team needed

<2周

HR系统接入周期HR system integration

核心挑战Core Challenges

员工健康管理的三个结构性困境Three Structural Barriers in Employee Health Management

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健康投入无法量化ROIUnquantifiable Health ROI

企业每年在员工健康福利上投入大量资源，但无法向管理层证明这些投入真实降低了多少医疗费用——健康福利永远是"软性"支出。Enterprises invest heavily in employee health benefits but cannot prove ROI to management. Health benefits remain "soft" expenditure.

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保险费率无差异化No Differentiated Insurance Rates

企业无论是否积极推行员工健康管理，保险公司的团体险费率差异有限。没有因果证据，险企无法为主动健康管理的企业提供合理的费率优惠。Without causal evidence, insurers cannot justify premium discounts for employers who invest in health management.

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高危员工识别盲区High-Risk Employee Blind Spots

传统体检无法实时监测员工健康状态，等到高危员工出现症状时，干预窗口已经关闭，企业和员工都付出了更高代价。Traditional checkups cannot monitor employee health in real time. By the time symptoms appear, the intervention window has closed.

典型价值数据Typical Value Metrics

企业健康管理的可量化收益Quantifiable Returns from Employee Health Management

18%

高危员工医疗费用可节省比例（干预后预估）Estimated medical cost savings for high-risk employees post-intervention

1.8天

每位高危员工年均减少心血管相关缺勤天数Avg reduction in cardiovascular-related absences per high-risk employee per year

正ROI

基于典型企业规模的干预投入产出比（PSM因果证据支撑）Positive ROI based on typical enterprise scale, supported by PSM causal evidence

解决方案Solution

四步打通企业健康管理ROI闭环Four Steps to Close the Enterprise Health ROI Loop

员工群体风险画像Employee Group Risk Profiling

基于16个临床特征，对员工群体进行心脑血管风险分层，识别极高、高、中、低风险四类人群。支持按部门、年龄段、岗位类型的交叉分析，精准确定优先干预对象。16 clinical features for cardiovascular risk stratification. Cross-analysis by department, age group, and job type to precisely identify priority intervention targets.

群体风险分层Group Stratification高危识别High-Risk ID多维分析Multi-Dimensional

个性化干预方案推送Personalized Intervention Delivery

针对高危员工自动生成个性化干预建议，推送至员工终端（企业健康App或微信）。干预方案覆盖生活方式改善、数字健康工具、定期随访提醒，并记录完整干预轨迹。Auto-generate personalized interventions for high-risk employees, delivered to their devices. Covers lifestyle, digital health tools, and follow-up reminders with full tracking.

个性化Personalized终端推送Push Delivery轨迹记录Tracking

PSM因果归因——量化干预ROIPSM Attribution — Quantify Intervention ROI

通过倾向评分匹配量化干预对医疗费用节省的真实因果效应，输出ATT效应量和置信区间。帮助企业向管理层汇报健康投入的财务回报，将健康福利从"员工关怀"转化为可量化的财务决策。PSM quantifies the true causal effect of interventions on medical cost savings. Helps HR report health investment ROI to management as a quantifiable financial decision.

PSMROI量化 Quantification管理层报告Management Report

因果证据报告——向险企申请费率优惠Causal Evidence — Negotiate Insurance Discounts

生成标准化因果证据报告，企业可将其提交给商业保险公司，证明员工健康管理项目真实降低了风险，支持申请团体险费率优惠。同时可用于年度健康管理报告和ESG披露。Submit standardized causal evidence to insurers to prove risk reduction, supporting group insurance premium discounts. Also usable for annual health reports and ESG disclosure.

费率优惠申请Premium DiscountESG管理报告Management Report

常见问题FAQ

企业合作常见问题Enterprise Partnership FAQ

企业如何用ReHealth Core向保险方申请费率优惠？How can enterprises use ReHealth Core to negotiate insurance discounts?

ReHealth Core生成PSM因果归因报告，证明企业健康管理项目真实降低了员工心血管风险。企业将该报告提交给商业保险公司，作为申请团体险费率优惠的证据依据。ReHealth Core generates PSM causal attribution reports proving that the enterprise's health management program genuinely reduced employee cardiovascular risk. Enterprises submit this to insurers as evidence for group insurance premium discounts.

员工隐私如何保障？How is employee privacy protected?

所有员工个人数据在本地脱敏处理后方可进入分析流程。企业管理层只能看到群体层面的风险分析，无法识别具体个人的健康数据。满足《个人信息保护法》员工数据处理相关要求。All employee data is de-identified locally before entering the analysis pipeline. Management can only see group-level risk analysis, not individual health data. Compliant with PIPL employee data processing requirements.

适合多大规模的企业？What company size is optimal?

PSM因果归因建议干预组至少100人，对照组候选池3-5倍于此。因此500人以上的企业效果最佳。小于500人的企业可选择跨企业联合分析方案（数据不出企业，联邦计算）。PSM attribution requires at least 100 in the intervention group with 3-5x the control pool. Optimal for companies with 500+ employees. Smaller companies can use cross-enterprise federated analysis (data stays on-premise).

准备好了解更多？Ready to Learn More?

联系我们，了解ReHealth Core如何帮助您的企业量化员工健康投入的真实价值。Contact us to learn how ReHealth Core can quantify the real value of your employee health investment.

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