008 Big Data in Healthcare – Real World Use Cases
1. Objective
1. 目标
This blog will take you through various use cases of Big Data in Healthcare. Understand how Big data is transforming healthcare and medical science and how big data bring revolution in the healthcare industry, we will understand the same using various real world case studies of big data and analytics in healthcare. How big data is changing healthcare and reducing the cost & improving outcome.
这篇博客将带你了解医疗保健领域大数据的各种用例.如何理解大数据大数据如何给医疗行业带来革命，我们将通过各种方法来理解这一点大数据与分析的真实案例研究在医疗保健领域大数据如何改变医疗保健、降低成本和改善结果.
Big Data in Healthcare – Real World Use Cases
2. What is Big Data?
2. 什么大的数据？
Big Data revolution is transforming the way we live. The last few years have seen a tremendous generation of data which impacts our day to day life and health care has also not been untouched by it. The healthcare industry has certainly lagged behind other industries such as banking, retail, etc. in the usage of Big Data. Other industries have embraced Big Data earlier and have reaped profits and greater customer satisfaction.
大数据革命正在改变我们的生活方式.在过去的几年里，影响我们日常生活和医疗保健的数据产生了巨大的变化.医疗保健行业肯定落后于银行等其他行业,零售,等在使用中大数据.其他行业更早地接受了大数据，并获得了利润和更大的客户满意度.
3. Big Data in Healthcare
3. 大数据的医疗保健
Healthcare industry generates huge data about every patient but accessing, managing and interpreting the data are critical to creating actionable insights for better care and efficiency. The American Healthcare expenses represent 17.6% of its GDP, which is far more than the expected benchmark. Clinical trends also play a role in the rise of Big Data in Healthcare. Earlier physicians used their judgments to make treatment decisions, but the last few years have seen a shift in the way these decisions are being taken. Physicians review the clinical data and make an informed decision about a patient’s treatment. Financial concerns, better insights into treatment, research, efficient practices contribute to the need of Big Data in Healthcare industry. As per prediction by IDC, 30 percent of providers will use cognitive analytics with patient data by 2018.
医疗保健行业为每一位患者生成大量数据，但是访问、管理和解释这些数据对于为更好的护理和效率创建可操作的见解至关重要.美国的医疗费用占其 GDP 的 17.6%，远远超过了预期的基准.临床趋势在医疗保健大数据的兴起中也发挥了作用.早期的医生使用他们的判断来做出治疗决定，但是在过去的几年里，这些决定的做出方式发生了变化.医生审查临床数据，并对患者的治疗做出明智的决定.财务问题、对治疗、研究的更好理解、有效的实践有助于满足以下需求大数据医疗保健行业.根据 IDC 的预测，到 2018年，30% 的提供商将使用认知分析和患者数据.
4. IOT and Big Data Analytics in Healthcare
4. IOT 和医疗领域的大数据分析
IOT adds a great value to the healthcare industry. Devices that generate data about a person’s health and send it to the cloud will lead to a plethora of insights about an individual’s heart rate, weight, blood pressure, lifestyle and much more. Big Data allows real-time monitoring of patients, which leads to proactive care. Sensors and wearable devices will collect patient health data even from home. This data is monitored by healthcare institutions to provide remote health alerts and lifesaving insights to their patients.
Smartphones have added a new dimension. The apps enable the smartphone to be used as a calorie counter to keep a track of calories; pedometers to keep a check on how much you walk in a day. All these have helped people live a healthier lifestyle. Moreover, this data could be shared with a doctor, which will help towards personalized care and treatment. Patients can make lifestyle choices to remain healthy.
物联网为医疗保健行业增加了巨大的价值.生成有关人的健康数据并将其发送到云会导致对一个人的心率、体重、血压、生活方式等的大量洞察.大数据允许对患者进行实时监控，从而实现主动护理.即使在家里，传感器和可穿戴设备也会收集病人的健康数据.医疗机构对这些数据进行监控，为患者提供远程健康警报和救生洞察.
智能手机增加了一个新的维度.这些应用程序使智能手机能够用作卡路里计数器来跟踪卡路里; 计步器可以检查你一天步行多少.所有这些都帮助人们过上了更健康的生活方式.此外，这些数据可以与医生分享，这将有助于个性化护理和治疗.为了保持健康，患者可以选择生活方式.
5. Big Data and Cancer
5. 大数据和癌症
Big Data aims to collect data from pre-treatment and pre-diagnosis data to the end stage. This data is aggregated with clinical and diagnostic data which makes predicting cancer more feasible. This predictive analysis helps to categorize different cancers and improves cancer treatment.
By leveraging historical data of patients with similar conditions, predictive algorithms can be developed using R and big data machine learning libraries to project patient trajectory.
96% of the potentially available data on patients with cancer is not yet analyzed. Based on this idea, Flatiron Health developed a service called Oncology Cloud. This service aims to gather data during diagnosis and treatment and make it available to clinicians to advance their study.
大数据的目标是从预处理和诊断前的数据收集到最终阶段的数据.这些数据与临床和诊断数据相结合，使得预测癌症变得更加可行.这种预测性分析有助于对不同的癌症进行分类，并改善癌症治疗.
通过利用相似患者的历史数据，可以使用 R 和机器学习大数据项目患者轨迹的图书馆.
96% 的癌症患者的潜在可用数据尚未分析.基于这个想法，Flatiron Health 开发了一项名为肿瘤云的服务.这项服务旨在收集诊断和治疗期间的数据，并让临床医生能够推进他们的研究.
6. Clinical Studies, Predictive Analysis, and Inventory Management
6. 临床研究、分析预测、和库存管理
Clinical studies can be performed in a much efficient manner. Researchers who conduct clinical studies can take a variety of factors combined with multiple statistics to attain higher precision in their studies. Genomic data is very important for the healthcare industry. The values of diagnostic tests are vital to the reduction in lab testing and genome analysis costs.
Socioeconomic data can play a significant role in **predictive **analysis. This data might show that people with certain zip code do not have access to cars (rural places) or other vehicles. Health systems thus identify patients in these areas and predict missed appointments, non-compliance with medications and more. The possibilities with predictive analysis with Big Data are endless.
There are many benefits of Big Data in Healthcare for managing the hospital inventory. It averages the supplies per treatment enabling Just in Time Inventory which reduces cost.
临床研究可以以非常有效的方式进行.进行临床研究的研究人员可以将多种因素与多种统计相结合，以获得更高的研究精度.基因组数据对于医疗保健行业非常重要.诊断测试的价值对于实验室测试和基因组分析成本的降低至关重要.
社会经济数据可以发挥重要作用预测性分析.这些数据可能表明，某些邮政编码的人无法使用汽车 (农村地区) 或其他车辆.因此，卫生系统识别这些领域的患者，并预测错过的约会、不遵守药物等情况.利用大数据进行预测分析的可能性是无穷无尽的.
大数据在医疗保健管理医院库存方面有很多好处.它平均每个处理的供应，能够及时库存，从而降低成本.
7. Big Data Helps Fight Ebola in Africa
7. 大数据有助于抗埃博拉病毒在非洲
Big Data helps predict the spread of epidemics. The mobile phone location data track population movements, which predict the spread of the virus. This gives insights about the most affected areas, which in turn leads to better planning of treatment centers and enforce movement restriction in those areas.
大数据有助于预测流行病的传播.手机位置数据可以追踪人口移动，从而预测病毒的传播.这让我们对受影响最严重的地区有了更深入的了解，这反过来又会导致更好地规划治疗中心，并在这些地区实施行动限制.
8. Big Data Innovations in Healthcare
8. 大数据创新的医疗保健
Big Data – Hadoop, Spark, Flink has been a source of innovation in healthcare. Some Big data case studies in Healthcare are as follows:
大数据-Hadoop, 火花, Flink一直是医疗保健领域创新的源泉.医疗保健领域的一些大数据案例研究如下:
a. Asthmapolis
A.Asthmapolis
It has developed a GPS-enabled tracker that records inhaler usage by asthmatics. The information is transferred to a centralized database and used to identify trends about individual, group and population. The data are then merged with information about asthma catalysts. This information helps physician offer personalized care and treatment to asthma patients.
它开发了一种 GPS 跟踪系统，可以记录哮喘患者的空气过滤器使用情况.这些信息被转移到一个集中的数据库中，用于确定个人、群体和人口的趋势.然后将数据与哮喘催化剂的信息合并.这些信息有助于医生为哮喘患者提供个性化的护理和治疗.
b. Ginger.io
B.姜.
It offers a mobile application which allows their patients to be tracked through their mobile phones to remotely deliver mental health treatments. The smartphone sensors are monitored and the information is used for behavioral health therapies.
它提供了一个移动应用程序，可以通过手机跟踪病人，远程提供心理健康治疗.智能手机传感器被监控，信息被用于行为健康治疗.
c. AiCure
C.AiCure
It uses mobile technologies, facial recognition technologies, and big data and Spark to examine if a patient is taking the right medications at the right time. This will help doctors to ensure that the patient is taking his medications properly and alert him if something goes wrong.
它使用移动技术、面部识别技术、大数据和火花检查患者是否在正确的时间服用了正确的药物.这将有助于医生确保患者正确服用药物，并在出现问题时提醒他.
d. United Healthcare
联合医疗保健
It is processing data inside a Hadoop big data framework to give them a complete view of its 85 million members individually and then using it for clinical improvements, financial analysis and fraud and waste monitoring.
This is just the beginning. With the development of technologies, new and better treatments and diagnoses will help in saving more lives by curing more diseases. The future of medical science is based on data analytics.
Refer Big data applications in various fields to understand Big data uses in various domains.
它在处理数据Hadoop大数据框架，让他们单独查看其 8500万名成员，然后将其用于临床改进、财务分析以及欺诈和废物监控.
这只是一个开始.随着技术的发展，新的更好的治疗和诊断将有助于通过治疗更多的疾病来拯救更多的生命.医学的未来是建立在数据分析.
参考各领域大数据应用了解大数据在各个领域的应用.
https://data-flair.training/blogs/big-data-healthcare-real-world-use-cases
