Big data and the Healthcare Sector


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Big data and the Healthcare Sector

  1. 1. Big Data and theHealthcare SectorJonathan HannahsDavid HewittChris Groves
  2. 2. What is Big Data?0 Global data is going to grow by 40%this year. McKinsey & Company0 Big data is data that exceeds theprocessing capacity of conventionaldatabase systems. O’Reilly Media0 The ability to spot trends andpatterns in large and diverse datasets has been in the hands of largecorporations for many years.
  3. 3. Wannamaker’s Dilemma0 John Wannamaker was a DepartmentStore magnet during the 30’s and 40’s.0 “I know that half of my advertisingdoesn’t work. The problem is that Idon’t know which half.” - JohnWannamaker0 Because of Google AdWords and the useof Big Data Analytics, the question ofwhich part of the advertising is effectivehas been answered and caused arevolution in the advertising business.0 Currently, doctors recommend patientcare centered on the “standards of care”treatment and on their own intuitionand training0 Big data promises to answer forhealthcare what it did for advertising,which treatments work and whichtreatments don’t.
  4. 4. Currently the U.S. spends $2.6 trillion on healthcare everyyear and $600 billion of that spending is on variations intreatment (treatments that do not work).- O’Reilly Media
  5. 5. Characteristics of Big Data inHealthcare - Data Silos0 Pharmaceutical R&D Data0 Clinical Data0 Activity (claims) and CostData0 Patient Behavior andSentiment Data
  6. 6. 4 Key Attributes of Big Data0 Volume: The amount of data beingprocessed is much greater than processesin the past.0 Variety: In the healthcare sector,unstructured data, combined withtraditional structured data, can offer thesector a wealth of undiscoveredinformation.0 Velocity: With data changing by the day,hour, or minute, this is the speed at whichyou can process data and make decisionsbased on that data.0 Veracity: Data uncertainty and planningfor the uncertainty is a uniquecharacteristic of big data that sets it apartof traditional structured data.(Source: Analytics: The Real World Use of Big Data)
  7. 7. Characteristics of Big Data inHealthcare - Top 51. A greater scope ofinformation.2. New kinds of data analysis.3. Real time Information.4. Data influx from newtechnologies.5. Non-traditional forms ofdata.
  8. 8. Healthcare & Big DataDrivers of Adoption0 Implementation of theAffordable Care Act.0 Growing costs for new,revolutionary technologiescombined with shrinkingreimbursements.0 Ability for New Big DataSystems to ProcessUnstructured and StructuredData.
  9. 9. 5 Ways Big Data Will Enable HealthcareQuality Improvement and Cost Cutting1. Right Living: Big data can help patients take an activerole in treating their current ailments but also inpreventing future issues by encouraging them to eatright, exercise, and adhere to medication.2. Right Care: Integration and application of big datatools will promote evidence-based care that will bepersonalized to the patient.3. Right Provider: Big data can help the healthcaresector match patients with specific providers based onoutcomes and the patients past history.4. Right Value: Big data tools can help drive down costby helping to eliminate fraud, waste, and abuse andassist with implementing an outcome-based paymentsystem.5. Right Innovation: Big data tools will help improvespecific therapies and care and also help in theinnovation of research and development of new caretechniques.(Source: The Big Data Revolution in Healthcare)
  10. 10. Challenges to Big Data Adoption0 Silos of Informationwithin the HealthcareSector0 Patient Privacy andGovernment Regulation0 Provider Trust in DataAnalysis Over Instincts
  11. 11. Big Data Top CompaniesIBM, a leader in the big data field, haspartnered with Memorial Sloan-Kettering Cancer Center to introducetheir “Watson” technology to the clinicalsetting. Watson isn’t only a searchengine but relies on probabilisticalgorithms to analyze millions of pagesof unstructured data in patient recordsand the medical literature to make adiagnosis and answer treatment relatedquestions.
  12. 12. Big Data Top CompaniesHumedica is a private company based inBoston that offers a cloud-based population-wide analytics platform. Humedica’s systemconnects patient information across themedical setting and time period to enableproviders to get a holistic view of patientcare.Over 25 Million Patients
  13. 13. Big Data Top CompaniesExplorys is a privately heldcompany based in Cleveland, Ohio.Explorys is a spinoff company of theCleveland Clinic.The Explorys platform enablesproviders to do the following:0 Complete searches across patientpopulations and care venues tohelp identify disease trends.0 Coordinate rules-driven patientregistries.0 View performance matrix.
  14. 14. Big Data in HealthcareCase Study – SuccessSharp Community Medical Group (San Diego, Ca)0 Partnered with IBM0 Created a system to capture and utilize datagenerated by its customers and staff.0 Helps doctors see trends in SCMG patientpopulations0 How many people have uncontrolleddiabetes.0 How many women havent had theirmammography screening0 Considering using natural-language processingto record and store data.
  15. 15. Big Data in HealthcareCase Study – SuccessCamden Coalition of Health Care Providers (Camden, NJ)0 Collect and analyze data to improve preventative carefor the city.0 Created a map of medical “hot-spots” that showed thatthere were areas of the city where a disproportionatelyhigh level of calls for an ambulance.0 Data showed that these residents did not receiveeffective preventative care.0 Demonstrated that 80% of the city’s medical costscould be attributed to 13% of the patients0 A sample of 36 patients that were given preventativecare brought the group’s monthly average of 62hospital visits down to 37 and reduced the patients’hospital costs by 56%
  16. 16. Big Data in HealthcareCase Study – SuccessReasons for Success of Case Studies0 Buy in- In both cases, the organizationin the SCMG case and the medicalcommunity in the Camden case,supported fully the implementation ofbig data solutions.0 Measurable results – In both cases,the data stored and analyzed resultedin improvement.0 Adaptive to operational need – Bothorganizations tailored their big datasolution to the needs of the peoplewho need it and are adapting thesolution as circumstances change.
  17. 17. Big Data in HealthcareCase Study – FailureCanadian research group led by Dr.Damian Cruse and an American researchgroup led by Dr. Andrew Goldfine0 Both research groups were studyingelectrical activity in the brains ofpatients in a vegetative state.0 Goldfine found that the Canadian groupdid not rely on standard statistical testsin their research. They used a computerprogram based on machine learning tocomb through tens of thousands of datapoints.0 “Big Data” solution recorded allelectrical fluctuations in the EEG andmay have recorded artifacts as brainimpulses.0 Big data tools very subject to falsepositivesReasons for this failure in this caseinclude:0 Using an unproven datacollection method- The methodused to collect the data was adeparture from the norm and wasuntested.0 No data quality oversight- Theresearches for the Canadian groupdid not double check the computeroperated system to make sure thedata being collected was accurate.0 Uneducated operators- TheCanadian researches did notfamiliarize themselves with thedata collection method beforetrusting it implicitly.
  18. 18. The Ohio Lottery Commission0 State’s only legally operating seller of lotterygames0 Operated more like a business than a stateagency0 Goal is to deliver a cost effectiveentertaining product to the public with allbottom line revenue being transferred to theLottery Profits for Education Fund0 Since the OLC relies heavily on licensedretail agents to sell the product, making surethat product is on hand in the locations andprominently displayed at key sale points isessential to the success0 OLC’s sales reached a record last year of$2.78 billion
  19. 19. Ohio Lottery & Big Data0 OLC has been using big dataapplications since 2007.0 Currently in place are data warehousesand reporting tools for human capitalmanagement and financial functions.0 The State of Ohio uses two mainapplications for compiling anddistribution of data.0 Oracle’s PeopleSoft application -Enterprise PeopleTools 8.46 is usedfor data entry.0 IBM’s Cognos software is used forreporting and analytics.0 OLC could benefit from more specificbig data functions.
  20. 20. Potential Applications of BigData Tools at the Ohio Lottery0 3 departments generate usable data on a dailybasis that if properly utilized could build a greatercompetitive advantage; the Lottery Call Center,Sales, and Marketing.0 Currently, the three departments operate onseparate systems.0 A single data warehouse to store all theinformation from all departments would improvetimes for resolution of customer and retailerrequests.0 Sharing information in real time would be a greatbenefit to the organization.0 Sales representatives in the field would havebetter information regarding call center data.0 Call center agents would have better data of whatis happening in the field which will lead to moreaccurate resolutions over the phone.0 Marketing would have a better picture of wherepromotions are needed.
  21. 21. The Ohio Lottery & Big DataManagement Challenges0 Management of Information – TheOLC will need to first build amanagement team to design andmanage the new system.0 Building Infrastructure – To makethis system truly beneficial to allusers, it will need to be accessible byall users.0 Building employee trust in data - Ifa data driven solutions are to growand thrive in the agency, allemployees involved need to be onboard.
  22. 22. Big Data and Competitiveness@ The Ohio Lottery0 Big data would have an impact on theability of the OLC to anticipate customerdesires and react to changes.0 Competing for discretionary dollar putsOLC products in direct competition witha wide variety of products at the sameprice point (i.e. Snack foods, beverages,tobacco products, etc.)0 OLC specific data shared acrossdepartments will allow the more formore effective sales and marketingsolutions at the majority of retaillocations.
  23. 23. Big Data and Competitiveness@ The Ohio Lottery0 Opening up of the state to casino gamingoffers the OLC an opportunity to expandtheir reach into a new market segment.0 The OLC has begun to partner with Ohiohorse racing tracks to create a new entityin the state’s gaming/gamblingindustry, the Racino.0 The analysis of data from Video LotteryTerminals at Racinos will assist the OLCto uncover many ways to improve profits.
  24. 24. Questions?