{"id":3535,"date":"2020-05-25T03:22:12","date_gmt":"2020-05-25T03:22:12","guid":{"rendered":"http:\/\/orionhealth-blog.local\/?p=3535"},"modified":"2025-03-28T01:05:28","modified_gmt":"2025-03-28T01:05:28","slug":"how-big-data-is-shaping-healthcare-delivery","status":"publish","type":"post","link":"https:\/\/orionhealth.com\/au\/blog\/how-big-data-is-shaping-healthcare-delivery\/","title":{"rendered":"How Big Data is shaping healthcare delivery"},"content":{"rendered":"<p>The term \u201cbig data\u201d refers to the management of massive volumes of data, both structured and unstructured,&nbsp;that it is difficult to process using traditional means.&nbsp;<strong>\u202f<\/strong>&nbsp;<\/p>\n\n\n\n<p>In healthcare,&nbsp;we typically find large volumes of data when looking in-depth at the health of an entire population.&nbsp;These&nbsp;large healthcare data sets managed correctly, can help address some major problems that have been&nbsp;intractable&nbsp;in the past. Such problems include\u202f prediction of high-risk situations and the spread of epidemics, improved care coordination and optimal management of chronic disease cohorts.&nbsp;&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Aggregate and analyse with AI and machine learning<\/strong><\/h4>\n\n\n\n<p>\u202fTo achieve the potential of big data in healthcare, we first require the ability to aggregate large volumes of data and then analyse them.&nbsp;&nbsp;\u201cAnalysis\u201d includes both traditional analytic tools and emerging tools including&nbsp;artificial&nbsp;intelligence and&nbsp;machine&nbsp;learning.\u202f&nbsp;&nbsp;<\/p>\n\n\n\n<p>Big data is already showing promising results in healthcare by offering solutions that \u202fimprove individual patient care and the generation of value at the level of the whole population.\u202f&nbsp;&nbsp;<\/p>\n\n\n\n<p>An important aspect is the ability to work with data of all types\u202ffrom all manner of sources to bring a more complete picture of the patient.\u202f&nbsp;&nbsp;<\/p>\n\n\n\n<p>Relevant data types in population health include traditional clinical data, claims data, social determinants of health data, patient-generated data, device data, environmental data and genomic data.&nbsp;&nbsp;<\/p>\n\n\n\n<p><strong>Let\u2019s review a few applications of big data to population health and see how it\u2019s shaping healthcare delivery.&nbsp;<\/strong><\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Applications of big data in healthcare&nbsp;<\/strong>&nbsp;<\/h4>\n\n\n\n<p>Analysis of Big Data sets allows healthcare providers to identify high-risk populations (cohorts) prone to high cost,&nbsp;high importance diseases and clinical situations such as high-risk pregnancy.&nbsp;&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Early detection and management of patients at high risk within a population&nbsp;<\/strong><\/h4>\n\n\n\n<p>Identifying such populations allows healthcare providers to make data-driven decisions, targeting patients for interventions that will deliver the maximum&nbsp;benefit at the lowest cost.\u202fThis is especially important in patients with complex histories and those suffering from multiple\u202f chronic conditions.\u202f&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>The Right Care at the Right Time and the Right Place&nbsp;<\/strong><\/h4>\n\n\n\n<p>Analysis of&nbsp;big&nbsp;data in healthcare populations provides new insights into diseases&nbsp;and an&nbsp;understanding&nbsp;of&nbsp;whether specific interventions deliver benefits at realistic levels of expenditure.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Big&nbsp;data&nbsp;approaches enable clinician end-users and population-level managers to analyse and review data drawn from&nbsp;real-world&nbsp;experiences of real patients.&nbsp;This is a big improvement when previously information was gained from clinical trials, which were frequently very idealised.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Real-world&nbsp;data improves the ability of care management teams to target patients most likely to benefit and&nbsp;prioritise&nbsp;those patients over others with less pressing needs or&nbsp;a&nbsp;lower likelihood of&nbsp;a&nbsp;successful intervention.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\">&nbsp;Avoiding unnecessary hospitalisation&nbsp;<\/h4>\n\n\n\n<p>Today, with a growth in digital devices such as smartphones, wireless devices, and wearables, virtual care has&nbsp;become an integral part of many clinical situations.&nbsp;Clinicians use virtual care to provide personalised treatment plans and prevent hospitalisation or re-admission.&nbsp;&nbsp;<\/p>\n\n\n\n<p>\u202fBy keeping patients out of hospitals, virtual care can help reduce workload pressures on healthcare providers&nbsp;whilst gaining&nbsp;a huge amount of information about each patient.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Most times,&nbsp;virtual care means patients can avoid long waiting times at the hospital or clinics.&nbsp;This reduction in consultation wait times means&nbsp;that&nbsp;patients with high priority&nbsp;health issues can see their clinicians face to face. Patients with low risk can be managed by their clinician remotely through virtual care.&nbsp;<\/p>\n\n\n\n<h4 class=\"wp-block-heading\"><strong>Population health exploration&nbsp;<\/strong><\/h4>\n\n\n\n<p>Once the infrastructure for&nbsp;big&nbsp;data has&nbsp;been established&nbsp;and real-time high volume data is available,&nbsp;healthcare providers&nbsp;can explore the data&nbsp;for meaningful insights, such as gaps in care.&nbsp;&nbsp;<\/p>\n\n\n\n<p>Big Data is inherent to population health in the 21<sup>st<\/sup>&nbsp;century as it enables a much better understanding of that population and the ability to target interventions where patients are most likely to benefit.\u202f&nbsp;&nbsp;<\/p>\n\n\n\n<p>Combined with emerging funding models such as value-based care, big data can make major contributions to the improvement of healthcare sustainably.&nbsp;&nbsp;&nbsp;<\/p>\n\n\n\n<p>Combined with emerging funding models such as&nbsp;value-based&nbsp;care,&nbsp;Big Data is poised&nbsp;to&nbsp;make a major contribution&nbsp;to the improvement of healthcare delivery and the sustainability of the health system.&nbsp;<\/p>\n\n\n\n<p><strong><a href=\"https:\/\/orionhealth.com\/au\/white-papers\/unlocking-the-power-of-machine-learning-in-health\/\" target=\"_blank\" rel=\"noreferrer noopener\">See our whitepaper on how big data coupled with machine learning can provide the right patient with the right care at the right place and time.<\/a><\/strong><\/p>\n\n\n\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/orionhealth.com\/au\/contact\/\">Contact an expert<\/a><\/div>","protected":false},"excerpt":{"rendered":"<p>The term \u201cbig data\u201d refers to the management of massive volumes of data, both structured and unstructured,&nbsp;that it is difficult to process using traditional means.&nbsp;\u202f&nbsp; In healthcare,&nbsp;we typically find large volumes of data when looking in-depth at the health of an entire population.&nbsp;These&nbsp;large healthcare data sets managed correctly, can help address some major problems that [&hellip;]<\/p>\n","protected":false},"author":35,"featured_media":3536,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[1],"tags":[],"region":[25,23],"class_list":["post-3535","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","region-au","region-global"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - 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