  {"id":29157,"date":"2018-11-13T17:21:00","date_gmt":"2018-11-13T22:21:00","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/can-computers-make-healthcare-affordable\/"},"modified":"2018-11-13T17:21:00","modified_gmt":"2018-11-13T22:21:00","slug":"can-the-maker-of-post-it-notes-solve-healthcare-pricing","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/can-the-maker-of-post-it-notes-solve-healthcare-pricing\/","title":{"rendered":"Can the maker of Post-it notes solve healthcare pricing?"},"content":{"rendered":"<h2>3M in the healthcare space<\/h2>\n<p>Of the many divisions in 3M, a multinational conglomerate known the world over for their iconic Post-it sticky notes, there is one in particular on a mission to improve healthcare. For years, 3M&#8217;s healthcare division has produced the software that helps hospitals across America &#8220;code&#8221; their patients&#8217; conditions into an appropriate diagnosis-related grouping (or &#8220;DRG&#8221;), that tells the hospital what a likely treatment plan and costs to expect, and tells insurers what a reasonable payment will be for treatment.<\/p>\n<figure id=\"attachment_29173\" aria-describedby=\"caption-attachment-29173\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/0_p4XEHwzzqPFnRvj5-1.png\"><img loading=\"lazy\" decoding=\"async\" class=\"size-full wp-image-29173\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/0_p4XEHwzzqPFnRvj5-1.png\" alt=\"\" width=\"640\" height=\"333\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/0_p4XEHwzzqPFnRvj5-1.png 640w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/0_p4XEHwzzqPFnRvj5-1-300x156.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/0_p4XEHwzzqPFnRvj5-1-600x312.png 600w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-29173\" class=\"wp-caption-text\">An example processing pipeline used by HBI Solutions (https:\/\/www.hospitalemrandehr.com\/2016\/12\/12\/using-nlp-with-machine-learning-for-predictive-analytics-in-healthcare\/)<\/figcaption><\/figure>\n<p>This system of identifying the &#8220;product&#8221; code that an incoming patient will receive covers every treatment, from hip replacements to &#8220;bitten by pig, initial encounter&#8221;. Critics have suggested that this system of paying providers based on the procedures they carry out incentivizes providers to exaggerate diagnoses, and perform unnecessary and costly procedures while focusing too little on patient outcomes.<\/p>\n<h2>Learning from the data<\/h2>\n<p>In the face of this old system, 3M announced in 2016 a partnership with Verily (the healthcare arm of Alphabet), to build the 3M Performance Matrix [1] &#8211; a platform that would allow hospitals to synthesize their data from diverse sources such as insurance claims, patient electronic health records, hospital billing platforms, and lab and pharmacy data to compare their operations against larger industry averages, and identify at-risk and underperforming areas of their care delivery cycle.<\/p>\n<p>Instead of merely processing claims, 3M&#8217;s new platform would iteratively learn from patients who received similar diagnoses but received different care plans, and begin to suggest to hospitals which care plans were more effective at responding to and preventing complications.<\/p>\n<p>In both the short and longer term, 3M plans to leverage a few growing trends in the healthcare industry to transition from merely recording claims, to helping hospitals reduce and optimize them:<\/p>\n<ul>\n<li style=\"font-weight: 400\"><strong>Population health management<\/strong><span style=\"font-weight: 400\">\u00a0algorithms synthesize and combine disparate data sources (EHRs, billing platforms, medical claims, labs and pharmacies), to provide a unified and more accurate picture of a patient&#8217;s total lifetime of care and results.\u00a0 3M uses this unified view to better identify avoidable complications, and correlation between interventions earlier in life and reduced disease later.<\/span><\/li>\n<li style=\"font-weight: 400\"><b>Value-based (also called &#8220;accountable care&#8221;) reimbursement<\/b><span style=\"font-weight: 400\">\u00a0modules enable payers (insurance companies) to track and pay providers (hospitals) for outcomes instead of procedures by setting and measuring how much acute care was\u00a0<em>not<\/em> needed.\u00a0 The performance matrix learns and identifies preventive services that shift\u00a0hospitals\u2019 focus from costly reactive procedures in order to reduce future needs for hospital visits or chronic care management [2]<\/span><span style=\"font-weight: 400\">.<\/span><\/li>\n<li style=\"font-weight: 400\"><span style=\"font-weight: 400\"><strong>Big data sources<\/strong> are getting better and easier to manage. In addition to internal data (claims data, lab data), publicly derived data (e.g. census data), and device data (e.g. smart watches, smart scales) are now allowing insight into populations at a much more granular level [3].<\/span><\/li>\n<\/ul>\n<figure id=\"attachment_30845\" aria-describedby=\"caption-attachment-30845\" style=\"width: 640px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery.png\"><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-30845 size-large\" src=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery-1024x796.png\" alt=\"\" width=\"640\" height=\"498\" srcset=\"https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery-1024x796.png 1024w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery-300x233.png 300w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery-768x597.png 768w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery-600x466.png 600w, https:\/\/d3.harvard.edu\/platform-rctom\/wp-content\/uploads\/sites\/4\/2018\/11\/Example-discovery.png 1107w\" sizes=\"auto, (max-width: 640px) 100vw, 640px\" \/><\/a><figcaption id=\"caption-attachment-30845\" class=\"wp-caption-text\">An example of a root cause analysis on hospital inefficiency, provided by the 3M Performance Matrix. (Source: 3M.com)<\/figcaption><\/figure>\n<p>3M brought the data, and Verily brought the machine learning expertise &#8211; within a year, the company debuted the Performance Matrix at the\u00a0Healthcare Information and Management Systems Society conference that was capable of parsing diverse data sources in a hospital to identify unusually long stays, patients whose treatment deviated from expected, and conditions with atypically high readmission rates so that administrators could focus on root causes [4].<\/p>\n<h2>What&#8217;s missing?<\/h2>\n<p>3M and its contemporaries might well be served to defend their turf: competition has arrived in the Population Health management space.\u00a0 IBM and Siemens have partnered to build software for hospitals in the space [5], and recently Amazon announced a partnership with JPMorgan and Berkshire Hathaway to tackle the same problems, starting with their own employee base [6].<\/p>\n<p>In the short term, this competition should encourage 3M to double down on their competitive advantage &#8211; enormous historical claims processing databases &#8211; and go &#8220;deep&#8221; in developing machine learning techniques to learn from those data. In the longer term, the Performance Matrix would benefit from diversifying the data sources it can integrate into its analysis &#8211; go &#8220;wide&#8221; as competitors begin to mature, to provide the most holistic view.<\/p>\n<h2>Outstanding questions as 3M looks to the future of healthcare<\/h2>\n<ul>\n<li><strong>In the immediate term<\/strong>, a shift from fee-for-service to fee-for-value pricing will cut into short-term profits. How can payers help providers embrace the new paradigm in the face of tightening budgets?<\/li>\n<li><strong>In the longer term<\/strong>, how will 3M differentiate its product as major technology players enter the space and tap into the same data sources they do?<\/li>\n<\/ul>\n<div class=\"mceTemp\"><\/div>\n<p>&nbsp;<\/p>\n<p>(Word Count: 757)<\/p>\n<p>&nbsp;<\/p>\n<hr \/>\n<p><span style=\"text-decoration: underline\"><strong>Sources<\/strong><\/span><\/p>\n<p class=\"p1\"><span class=\"s1\">[1]\u00a0Neil Versel, \u201c3M, Google\u2019s Verily team up on population health management technology\u201d, Oct 12 2016. <a href=\"https:\/\/medcitynews.com\/2016\/10\/3m-verily-population-health\/\"><span class=\"s2\">https:\/\/medcitynews.com\/2016\/10\/3m-verily-population-health\/<\/span><\/a>, accessed Nov 2018<\/span><\/p>\n<p class=\"p2\"><span class=\"s1\">[2] NEJM Catalyst, \u201cWhat Is Value-Based Healthcare?\u201d, January 1 2017. https:\/\/catalyst.nejm.org\/what-is-value-based-healthcare\/, accessed Nov 2018.<\/span><\/p>\n<p class=\"p2\"><span class=\"s1\">[3] Dan Addyson, &#8220;Population Health Methods: How patient risk scoring works&#8221;, March 7 2018.\u00a0 <a href=\"https:\/\/towardsdatascience.com\/population-health-methods-how-patient-risk-scoring-works-70061ba327d2\"><span class=\"s2\">https:\/\/towardsdatascience.com\/population-health-methods-how-patient-risk-scoring-works-70061ba327d2<\/span><\/a>, accessed Nov 2018.<\/span><\/p>\n<p class=\"p2\"><span class=\"s1\">[4]\u00a0Susan Morse, \u201c3M, Verily, to unveil performance matrix at HIMSS18\u201d, Feb 23 2018. <a href=\"https:\/\/www.healthcareitnews.com\/news\/3m-verily-unveil-performance-matrix-himss18\"><span class=\"s3\">https:\/\/www.healthcareitnews.com\/news\/3m-verily-unveil-performance-matrix-himss18<\/span><\/a>, accessed Nov 2018.<\/span><\/p>\n<p class=\"p2\"><span class=\"s1\">[5] Neil Versel, \u201cIBM Watson gets \u201960 Minutes\u2019 love, then teams with Siemens\u201d, Oct 11 2016. <a href=\"https:\/\/medcitynews.com\/2016\/10\/ibm-watson-60-minutes-siemens\/\"><span class=\"s3\">https:\/\/medcitynews.com\/2016\/10\/ibm-watson-60-minutes-siemens\/<\/span><\/a>, accessed Nov 2018.<\/span><\/p>\n<p class=\"p2\"><span class=\"s1\">[6]\u00a0Angelica LaVito, Amazon, Berkshire Hathaway, and JPMorgan Chase to partner on US employee health care, Jan 30 2018. \u00a0<a href=\"https:\/\/www.cnbc.com\/2018\/01\/30\/amazon-berkshire-hathaway-and-jpmorgan-chase-to-partner-on-us-employee-health-care.html\"><span class=\"s3\">https:\/\/www.cnbc.com\/2018\/01\/30\/amazon-berkshire-hathaway-and-jpmorgan-chase-to-partner-on-us-employee-health-care.html<\/span><\/a>, accessed Nov 2018.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>3M and Google&#8217;s Verily team up to beat healthcare costs with machine learning<\/p>\n","protected":false},"author":11440,"featured_media":33851,"comment_status":"open","ping_status":"closed","template":"","categories":[346],"class_list":["post-29157","hck-submission","type-hck-submission","status-publish","has-post-thumbnail","hentry","category-machine-learning","hck-taxonomy-industry-health","hck-taxonomy-country-united-states"],"connected_submission_link":"https:\/\/d3.harvard.edu\/platform-rctom\/assignment\/rc-tom-challenge-2018\/","yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Can the maker of Post-it notes solve healthcare pricing? 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