梅斯医学荣获2021中国·常州"江南农商行"杯健康医疗数据开放创新应用大赛二等奖,精准预测宏观,专病,以及个体医疗费用

2022-05-24 MedSci原创 MedSci原创

“2021中国常州江南农商行杯健康医疗数据开放创新应用大赛(以下简称“大赛”)”已圆满结束,经过项目初赛、决赛、项目答辩、评审阶段,最终智慧医疗 赛道、

“2021中国常州江南农商行杯健康医疗数据开放创新应用大赛(以下简称“大赛”)”已圆满结束,经过项目初赛、决赛、项目答辩、评审阶段,最终智慧医疗 赛道、产业服务赛道、辅助决策赛道及高校赛道共产生24个获奖队伍,梅斯医学荣获二等奖。

此次常州市的大赛,依托常州市全域的全量医疗数据(2016-2020年)进行建模分析。梅斯参赛的项目是《基于AI的医疗费用预测模型》,应用先进的深度学习、机器学习、统计学及时间序列等算法, 构建了三大类模型:模型1:宏观费用预测模型:学习医保基金近5年历史支出规律,精准预测未来5~10年费用开支;模型2:专病费用预测模型:对人次及费用较高的疾病,通过主流机器学习方法Catboost、LGM等方法构建专病住院费用预测模型;模型3:个人未来医疗费用预测模型:根据个人历史费用开支情况,依托先进深度学习(DNN、BI-LSTM)和机器学习算法(XGB、LR),构建了个人未来一年费用开支预测模型。

这三大类模型具有极高的通用性,既能通过宏观数据分析,了解未来数年的医保支出的变化,从而做到精准管理与决策。进一步针对专病的预测,可以有效控制专病的治疗费用,指导临床,降低医疗费用,同时发现医疗中一些不合理的医疗行为。通过个人的未来预测,有助于精准指导个人的医疗费用支出,对医疗保险,尤其是商业保险的决策,起到关键性作用。

首先,在宏观费用预测模型方面,通过2016-2019年四年的结果,精准预测了2020年医保费用状况,有极高的吻合度,与实际发生费用仅相差1.5%。进一步还预测了到2026年医保费用的总支出状况,并精确到具体的月份。

进一步进行专病费用预测模型测试集表现,系统费用预测的重点是识别高费用人群,通过事前预测,可将有限的医疗资源更多的投入到高费用患者,降低不必要的医疗开支。 利用了XGB、CatBoost、LGB、RF等主流集成学习方法对2018-2019年数据集进行训练,在2020年数据集上进行测试: 主要结果:最高AUROC达0.89,为CatBoost和LGB模型,AUPRC达到0.8以上,测试集上的混淆矩阵(概率阈值为0.3,大于 0.3为正样本,小于为负样本)。同时,基于博弈论的SHAP模型解释方法,黑盒变白盒,使得数据表现能得到医学上很好地解释。

最后针对个人治疗费用进行预测,时序相关的模型和时序无关的模型,时序相关的主要考虑个人疾病疾病的进展,可以更加精准预测未来的花费,主要采用BI-LSTM,同时也采用了时序无关的模型,DNN、XGB及LR模型进行综合比对与分析

通过未来一年个人医疗费用支出等价于罹患某种疾病,通过预测费用开支,可有效预防疾病(治未病)的发生或延缓疾病进展,提升个人生存质量,同时有针对性进行健康管理,从而降低医疗成本的支出。

通过预测结果显示,AUC达到0.84,具有极高的吻合性。能极其出色地预测每一个个体未来一年的医疗费用支出状况,从而做出精准地决策。这项研究成果对于医疗保险,商业保险的精准决策和动态保费预算,均具有重要的意义与价值。

附获奖名单:

一等奖  3名

蓝软宇影智能医疗科技(常州)有限公司 (智慧医疗赛道)
中国银行股份有限公司常州分行  (产业服务赛道)
北京大数医达科技有限公司 (辅助决策赛道)

二等奖  6名

上海梅斯医药科技有限公司 (辅助决策赛道)

青岛海信医疗设备股份有限公司 (智慧医疗赛道)

联仁健康医疗大数据科技股份有限公司 (智慧医疗赛道)

医渡科技有限公司 (产业服务赛道)

天津康鼎科技有限公司 (产业服务赛道)

华信咨询设计研究院有限公司&浙江邦盛科技有限公司 (辅助决策赛道)

三等奖  8名

江苏任务网络科技有限公司(智慧医疗赛道)

上海中医药大学&上海医药集团&上海迷达适数据科技中心(智慧医疗赛道)

中国电信股份有限公司常州分公司&中电鸿信信息科技有限公司常州分公司
(智慧医疗赛道)

中信银行股份有限公司常州分行(产业服务赛道) 

江苏任务网络科技有限公司(产业服务赛道)

中国太平洋人寿保险股份有限公司&太保金融科技有限公司 (辅助决策赛道)

江苏理工学院(辅助决策赛道)

天津中医药大学&联想北京有限公司(辅助决策赛道)

高校赛道  7名

特等奖常州大学(医云一医学数据智能平台)

优胜奖常州大学(心安项目)

优胜奖常州大学(慧医项目)

创新奖常州大学(疾病未来趋势预测)

创新奖常州大学(糖尿病规范管理与防治)

创新奖常州大学(医疗智慧大屏)

创新奖常州大学(基于医保数据的慢性病人群就医与用费研究)

关于梅斯医学

梅斯医学是面向医生的综合互联网平台,应用大数据和人工智能技术链接医生、患者、药械企业等,提供精准数字化医学传播解决方案,赋能医疗生态,改善医疗质量,共创美好健康生活。

梅斯医学主要产品包括平台解决方案、数字化医学传播解决方案、数字化临床研究解决方案,涵盖临床研究、医生职业成长、多渠道学术传播等类别。在数字化临床研究层面,提供临床研究整体解决方案,通过数字化技术降低成本,提升质量;在数字化医学传播方面,提供数字化的专业医学内容和精准、整合的传播方案,将疾病知识和药械产品信息精准地传递给目标医生,更早更快地惠及更多的目标患者。同时,梅斯积极利用人工智能与大数据等技术,在患者管理、医保决策、药物经济学和创新支付、数字治疗等领域不断拓展新的业务类型和创新的产品。

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    2022-05-26 一闲
  3. [GetPortalCommentsPageByObjectIdResponse(id=1677627, encodeId=95d816e76273a, content=<a href='/topic/show?id=51162e76305' target=_blank style='color:#2F92EE;'>#健康医疗#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=34, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=27763, encryptionId=51162e76305, topicName=健康医疗)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=b2fd27558420, createdName=jiadan198791, createdTime=Tue Jul 26 16:44:55 CST 2022, time=2022-07-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1277337, encodeId=dafa12e7337e9, content=<a href='/topic/show?id=bde16242956' target=_blank style='color:#2F92EE;'>#梅斯#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=32, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=62429, encryptionId=bde16242956, topicName=梅斯)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=18fc139, createdName=一闲, createdTime=Thu May 26 01:44:55 CST 2022, time=2022-05-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1286111, encodeId=14931286111ce, content=<a href='/topic/show?id=77903209422' target=_blank style='color:#2F92EE;'>#创新#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=32, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=32094, encryptionId=77903209422, topicName=创新)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=512a199, createdName=lilianxiang, createdTime=Thu May 26 01:44:55 CST 2022, time=2022-05-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1403598, encodeId=fdcb140359859, content=<a href='/topic/show?id=ebbde6353be' target=_blank style='color:#2F92EE;'>#精准#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=40, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=76353, encryptionId=ebbde6353be, topicName=精准)], attachment=null, authenticateStatus=null, createdAvatar=https://thirdwx.qlogo.cn/mmopen/vi_32/DYAIOgq83epQX9hfEIBiaPg0e9KvLYVBCSGYydH6K6OQxBh3RaOC0TYP9HYy2v0XdHib1LFnZNU5Siak0P8oh8Aqw/132, createdBy=acd92440184, createdName=shijzhiewnjhch, createdTime=Thu May 26 01:44:55 CST 2022, time=2022-05-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1457947, encodeId=cb72145e947be, content=<a href='/topic/show?id=e604351e60d' target=_blank style='color:#2F92EE;'>#医疗费用#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=35176, encryptionId=e604351e60d, topicName=医疗费用)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=16bd5999183, createdName=wangyang7960, createdTime=Thu May 26 01:44:55 CST 2022, time=2022-05-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1591621, encodeId=da7a1591621ab, content=<a href='/topic/show?id=85213500260' target=_blank style='color:#2F92EE;'>#医疗数据#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=26, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=35002, encryptionId=85213500260, topicName=医疗数据)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=eded17951306, createdName=yzh405, createdTime=Thu May 26 01:44:55 CST 2022, time=2022-05-26, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1222053, encodeId=ba6d12220538a, content=👍🏻🐮, beContent=null, objectType=article, channel=null, level=null, likeNumber=46, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmhead/Q3auHgzwzM62hhmdZXtt9qxlVvXIXPHdENG7pbGbrNUUT9kYOl7QSA/0, createdBy=7d4a2077155, createdName=chenzhaolin, createdTime=Tue May 24 12:17:49 CST 2022, time=2022-05-24, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1221960, encodeId=f55e1221960c6, content=<a href='/topic/show?id=148562431a3' target=_blank style='color:#2F92EE;'>#梅斯医学#</a><a href='/topic/show?id=d3a024808e0' target=_blank style='color:#2F92EE;'>#人工智能#</a><a href='/topic/show?id=e85c33804e5' target=_blank style='color:#2F92EE;'>#医保#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=106, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=62431, encryptionId=148562431a3, topicName=梅斯医学), TopicDto(id=24808, encryptionId=d3a024808e0, topicName=人工智能), TopicDto(id=33804, encryptionId=e85c33804e5, topicName=医保)], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220519/c2ab253484ee4527a2d4e9589a4821ac/45de9bf494a54becb2ea4369c9d11e85.jpg, createdBy=7a3710, createdName=清风徐来2022, createdTime=Tue May 24 11:04:48 CST 2022, time=2022-05-24, status=1, ipAttribution=)]
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    2022-05-24 chenzhaolin

    👍🏻🐮

    0

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