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Targeted Analytics: Using Core Measures to Jump-Start Enterprise Analytics

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How top healthcare organizations are realizing the benefits of data analytics in such core areas as core measures, clinical alerting, surgical analytics, service line profitability, diabetes management, revenue cycle management, claims management and utilization.

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Targeted Analytics: Using Core Measures to Jump-Start Enterprise Analytics

  1. 1. Targeted Analytics:Using Core Measures to Jump-Start Enterprise Analytics<br />
  2. 2. About Perficient<br />Perficient is a leading information technology consulting firm serving clients throughout North America. <br />We help clients implement business-driven technology solutions that integrate business processes, improve worker productivity, increase customer loyalty and create a more agile enterprise to better respond to new business opportunities. <br />
  3. 3. PRFT Profile<br /><ul><li>Founded in 1997
  4. 4. Public, NASDAQ: PRFT
  5. 5. 2010 Revenue of $215 million
  6. 6. 20 major market locations throughout North America
  7. 7. Atlanta, Austin, Charlotte, Chicago, Cincinnati, Cleveland, Columbus, Dallas, Denver, Detroit, Fairfax, Houston, Indianapolis, Minneapolis, New Orleans, Philadelphia, San Francisco, San Jose, St. Louis and Toronto
  8. 8. 1,500+ colleagues
  9. 9. Dedicated solution practices
  10. 10. 500+ enterpriseclients (2010) and 85% repeat business rate
  11. 11. Alliance partnerships with major technology vendors
  12. 12. Multiple vendor/industry technology and growth awards</li></li></ul><li>Business-Driven Solutions<br />Enterprise Portals<br />SOA and Business Process Management<br />Business Intelligence<br />User-Centered Custom Applications<br />CRM Solutions<br />Enterprise Performance Management<br />Customer Self-Service<br />eCommerce & Product Information Management<br />Enterprise Content Management<br />Industry-Specific Solutions<br />Mobile Technology<br />Security Assessments<br />Perficient Services<br /><ul><li>End-to-End Solution Delivery
  13. 13. IT Strategic Consulting
  14. 14. IT Architecture Planning
  15. 15. Business Process & Workflow Consulting
  16. 16. Usability and UI Consulting
  17. 17. Custom Application Development
  18. 18. Offshore Development
  19. 19. Package Selection, Implementation and Integration
  20. 20. Architecture & Application Migrations
  21. 21. Education</li></ul>Perficient brings deep solutions expertise and offers a complete set of flexible services to help clients implement business-driven IT solutions<br />Our Solutions Expertise & Services<br />
  22. 22. Our Speaker<br />Michael Faloney<br />Healthcare Director responsible for development and delivery of business intelligence and analytics solutions<br />Responsible for engagement delivery and improving data solutions for Perficient's healthcare clients<br />20+ years progressive professional experience across technology, business, and process domains<br />+18 years in the IT fields of data warehousing, business intelligence, project/technical management, and applications development<br />Significant experience in developing enterprise data strategies, data architecture, data governance, data quality, data integration, master data management, metadata management, reporting and analytics<br />Held technical and management positions focused on delivering data warehousing and business intelligence solutions to the healthcare, financial services, and telecommunications industries<br />
  23. 23. Today’s Agenda<br />The Case for Healthcare Business Intelligence<br />Options for Healthcare Business Intelligence<br />The Targeted Analytics Approach<br />Core Measures Example of Building an Enterprise Analytics Platform with Targeted Analytics<br />Next Steps<br />
  24. 24. The Case for Healthcare Business Intelligence<br />Regulatory Pressure:<br /><ul><li>Pay for Performance
  25. 25. Meaningful Use
  26. 26. ICD-10</li></ul>Cost Pressure:<br /><ul><li>Reduced Funding/ Reimbursements
  27. 27. Skill shortages
  28. 28. Procurement management</li></ul>Competitive Pressure:<br /><ul><li>Consumer choice
  29. 29. Specialist hospitals
  30. 30. Attracting the Insured dollar</li></ul>Quality of Care<br />Increasing internal & external pressures makes the ability to accurately analyze the organization’s data in a timely manner to make critical financial, clinical or operational decisions a requirement, not a “Nice to Have” <br />Innovative Research<br />Financial Effectiveness<br />Operational Efficiencies<br />Regulatory Compliance<br />Healthcare Business Intelligence<br />
  31. 31. Healthcare Analytics Examples<br /><ul><li>Clinical Alerts
  32. 32. Core Measure Analysis
  33. 33. Longitudinal Records
  34. 34. Outcome Tracking
  35. 35. Patient Safety
  36. 36. Diabetes Management
  37. 37. Clinical Pathways Analysis
  38. 38. Personalized Medicine
  39. 39. Clinical Trial Effectiveness Analysis
  40. 40. Population Studies
  41. 41. Surgical Analytics
  42. 42. Material Usage Analysis vs. Outcomes
  43. 43. Cost Management
  44. 44. Service Line Profitability
  45. 45. Scheduling Analysis
  46. 46. Inventory Control Analysis
  47. 47. Claims Management
  48. 48. Service Line Profitability
  49. 49. Meaningful Use
  50. 50. Expanded Granularity using ICD-10
  51. 51. State Reporting
  52. 52. Public Health Reporting</li></li></ul><li>Options for Healthcare Business Intelligence<br />There are many options for business intelligence in Healthcare<br /><ul><li>“Top-Down Approach”
  53. 53. More likely to have an enterprise view and support from the beginning
  54. 54. Potentially longer time-line to deliver capabilities
  55. 55. “Bottom-Up Approach”
  56. 56. More likely to have departmental view at the beginning
  57. 57. Potentially shorter-time to deliver capabilities
  58. 58. Potentially requires significant rework to move to an enterprise platform
  59. 59. Can have either a departmental or enterprise view
  60. 60. Pre-built components offer potential for accelerated delivery
  61. 61. Often more of an accelerator based approach vs. shrink-wrap
  62. 62. Often provides only part of the solution and forces users to fit their problem into the package solution
  63. 63. Either a pre-packaged or accelerator –based approach
  64. 64. Typically tied to vendor’s transaction system(s)
  65. 65. Potentially limited ability to work outside their platform
  66. 66. Often not technology independent</li></li></ul><li>What is the Targeted Analytics Approach?<br />Targeted analytics is a structured approach to building out an enterprise analytics platform through the implementation of a series of individual applications focused on solving business critical issues<br />
  67. 67. Targeted Analytics Framework<br />Governance Framework<br /><ul><li>The governance framework ensures an enterprise view is maintained as the targeted analytics applications are implemented</li></ul>Enterprise View<br />Strategic Direction<br />Data Stewardship<br />Data Ownership<br />Data Guardianship<br /><ul><li>The accelerator-based implementation framework:
  68. 68. Based on Perficient’s BI Enable Approach
  69. 69. Balances process, technology and organizational constructs
  70. 70. Heavily leverages the accelerator library
  71. 71. Provides project, functional and technical oversight
  72. 72. Heavily leverages prototyping as a design/development technique</li></ul>Accelerator-Based Implementation Framework<br />Project Management<br />Functional Expertise<br />Perficient BI Enable™ Approach<br />Accelerator/Reusable Component Library<br />Visualization<br />Components<br />Integration Components<br />Metadata Components<br />Data Model Components<br />Other Components<br /><ul><li>The enterprise architecture frameworkprovides the supporting technical vision for the required functional capabilities, as well as ensures the developed applications meets the appropriate standards</li></ul>Enterprise Architecture Framework<br />Architectural Vision<br />Technical Oversight<br />Standards<br />Technical Direction<br />
  73. 73. How Does Targeted Analytics Work?<br />GOVERNANCE<br />Enterprise View<br />Enterprise View<br />Strategic Direction<br />Strategic Direction<br />Data Stewardship<br />Data Ownership<br />Data Guardianship<br />ENTERPRISE ARCHITECTURE<br />Architectural Vision<br />Technical Oversight<br />Standards<br />Technical Direction<br />Cardiovascular<br />Diabetes<br />Implementation Efficiency<br />Architecture Vision<br />Business Capabilities<br />1<br />2<br />Develop <br />Initial <br />Application (SCIP Core Measures)<br />Populate Accelerator<br />Library<br />Pneumonia<br />Core Measures<br />Meaningful<br />Use<br />Clinical<br />Alerting<br />3<br />Develop Additional Applications<br />ACCELERATOR LIBRARY<br />Visualization<br />Components<br />Integration Components<br />Metadata Components<br />Data Model Components<br />Other Components<br />
  74. 74. Core Measures Example<br />Starting with SCIP Core Measures, you set the initial foundation of your analytics platform through the creation of enterprise level, re-usable components<br />PROCEDURE<br />DIAGNOSIS<br />SCIP VALUE<br />CORE MEASURE TYPE<br />CORE MEASURE DESC<br />PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Data Source<br />1<br />Data Source<br />2<br />
  75. 75. Core Measures Example<br />The development of the first analytical application provides a number of accelerators that can be reused in future analytical applications. The governance function provides the enterprise view to ensure the re-usability in future analytical applications. <br />ACCELERATOR COMPONENT LIBRARY<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  76. 76. Report Templates
  77. 77. Dashboard Framework
  78. 78. Dashboard Widgets</li></ul>PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  79. 79. Time
  80. 80. Patient
  81. 81. Diagnosis
  82. 82. Procedure
  83. 83. Physician
  84. 84. Core Measure Type
  85. 85. Core Measure Description
  86. 86. Metrics:
  87. 87. SCIP Value
  88. 88. Hierarchies
  89. 89. Descriptive Attributes</li></ul>SCIP VALUE<br />CORE MEASURE TYPE<br />CORE MEASURE DESC<br />DATA GOVERNANCE<br />Data Integration<br /><ul><li>Mappings
  90. 90. Transformations
  91. 91. Data Quality Rules
  92. 92. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Other<br /><ul><li>Security (ex. Roles)
  93. 93. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />2<br />
  94. 94. Core Measures Example<br />Using the base created with the first application, the implementation of another core measure area is significantly accelerated. The architecture function function provides structure and process for leveraging the accelerators for future application<br />ACCELERATOR COMPONENT LIBRARY<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  95. 95. Report Templates
  96. 96. Dashboard Framework
  97. 97. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  98. 98. Time
  99. 99. Patient
  100. 100. Diagnosis
  101. 101. Procedure
  102. 102. Physician
  103. 103. Core Measure Type
  104. 104. Core Measure Description
  105. 105. Metrics:
  106. 106. SCIP Value
  107. 107. Hierarchies
  108. 108. Descriptive Attributes</li></ul>CORE MEASURE DESC<br />CORE MEASURE TYPE<br />Data Integration<br /><ul><li>Mappings
  109. 109. Transformations
  110. 110. Data Quality Rules
  111. 111. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Other<br /><ul><li>Security (ex. Roles)
  112. 112. Automation Constructs</li></ul>Data Source<br />1<br />
  113. 113. Core Measures Example<br />Using the accelerators previously created as a based, additional functionality can be delivered in a more time-sensitive manner<br />ACCELERATOR COMPONENT LIBRARY<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  114. 114. Report Templates
  115. 115. Dashboard Framework
  116. 116. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />FACILITY<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  117. 117. Time
  118. 118. Patient
  119. 119. Diagnosis
  120. 120. Procedure
  121. 121. Physician
  122. 122. Core Measure Type
  123. 123. Core Measure Description
  124. 124. Metrics:
  125. 125. SCIP Value
  126. 126. Hierarchies
  127. 127. Descriptive Attributes</li></ul>CORE MEASURE DESC<br />CORE MEASURE TYPE<br />PNEUMONIA<br />METRICS<br />Data Integration<br /><ul><li>Mappings
  128. 128. Transformations
  129. 129. Data Quality Rules
  130. 130. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Other<br /><ul><li>Security (ex. Roles)
  131. 131. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />3<br />
  132. 132. Core Measures Example<br />Once the second application is developed, the accelerator library is populated with the additional re-usable components<br />ACCELERATOR COMPONENT LIBRARY<br />Presentation/Analytic Capabilities<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  133. 133. Report Templates
  134. 134. Data Visualization
  135. 135. Report Templates
  136. 136. Dashboard Framework
  137. 137. Dashboard Widgets
  138. 138. Dashboard Framework
  139. 139. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />FACILITY<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  140. 140. Time
  141. 141. Patient
  142. 142. Diagnosis
  143. 143. Procedure
  144. 144. Physician
  145. 145. Core Measure Type
  146. 146. Core Measure Description
  147. 147. Metrics:
  148. 148. SCIP Value
  149. 149. Hierarchies
  150. 150. Descriptive Attributes</li></ul>Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  151. 151. Time
  152. 152. Patient
  153. 153. Diagnosis
  154. 154. Procedure
  155. 155. Physician
  156. 156. Core Measure Type
  157. 157. Core Measure Description
  158. 158. Facility
  159. 159. Metrics:
  160. 160. SCIP Value
  161. 161. Pneumonia Metrics
  162. 162. Hierarchies
  163. 163. Descriptive Attributes</li></ul>CORE MEASURE TYPE<br />CORE MEASURE DESC<br />PNEUMONIA<br />METRICS<br />Data Integration<br /><ul><li>Mappings
  164. 164. Transformations
  165. 165. Data Quality Rules
  166. 166. ETL Components</li></ul>Data Integration<br /><ul><li>Mappings
  167. 167. Transformations
  168. 168. Data Quality Rules
  169. 169. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />DATA GOVERNANCE<br />Other<br /><ul><li>Security (ex. Roles)
  170. 170. Automation Constructs</li></ul>Other<br /><ul><li>Security (ex. Roles)
  171. 171. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />3<br />
  172. 172. Extending Past Core Measures<br />Once the second application is developed, the accelerator library is populated with the additional re-usable components<br />ACCELERATOR COMPONENT LIBRARY<br />Presentation/Analytic Capabilities<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  173. 173. Report Templates
  174. 174. Data Visualization
  175. 175. Report Templates
  176. 176. Dashboard Framework
  177. 177. Dashboard Widgets
  178. 178. Dashboard Framework
  179. 179. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />FACILITY<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  180. 180. Time
  181. 181. Patient
  182. 182. Diagnosis
  183. 183. Procedure
  184. 184. Physician
  185. 185. Core Measure Type
  186. 186. Core Measure Description
  187. 187. Metrics:
  188. 188. SCIP Value
  189. 189. Hierarchies
  190. 190. Descriptive Attributes</li></ul>Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  191. 191. Time
  192. 192. Patient
  193. 193. Diagnosis
  194. 194. Procedure
  195. 195. Physician
  196. 196. Core Measure Type
  197. 197. Core Measure Description
  198. 198. Facility
  199. 199. Metrics:
  200. 200. SCIP Value
  201. 201. Pneumonia Metrics
  202. 202. Hierarchies
  203. 203. Descriptive Attributes</li></ul>Data Integration<br /><ul><li>Mappings
  204. 204. Transformations
  205. 205. Data Quality Rules
  206. 206. ETL Components</li></ul>Data Integration<br /><ul><li>Mappings
  207. 207. Transformations
  208. 208. Data Quality Rules
  209. 209. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Other<br /><ul><li>Security (ex. Roles)
  210. 210. Automation Constructs</li></ul>Other<br /><ul><li>Security (ex. Roles)
  211. 211. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />3<br />
  212. 212. Extending Past Core Measures<br />Once the second application is developed, the accelerator library is populated with the additional re-usable components<br />ENTERPRISE ANALYIC PLATFORM<br />Presentation/Analytic Capabilities<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  213. 213. Report Templates
  214. 214. Data Visualization
  215. 215. Report Templates
  216. 216. Dashboard Framework
  217. 217. Dashboard Widgets
  218. 218. Dashboard Framework
  219. 219. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />FACILITY<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  220. 220. Time
  221. 221. Patient
  222. 222. Diagnosis
  223. 223. Procedure
  224. 224. Physician
  225. 225. Core Measure Type
  226. 226. Core Measure Description
  227. 227. Metrics:
  228. 228. SCIP Value
  229. 229. Hierarchies
  230. 230. Descriptive Attributes</li></ul>Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  231. 231. Time
  232. 232. Patient
  233. 233. Diagnosis
  234. 234. Procedure
  235. 235. Physician
  236. 236. Core Measure Type
  237. 237. Core Measure Description
  238. 238. Facility
  239. 239. Metrics:
  240. 240. SCIP Value
  241. 241. Pneumonia Metrics
  242. 242. Hierarchies
  243. 243. Descriptive Attributes</li></ul>NURSING UNIT<br />ENCOUNTER<br />Meaningful Use Metrics<br />DISCRETE MEASURE<br />ADMISSION DATE<br />DISCHARGE DATE<br />Data Integration<br /><ul><li>Mappings
  244. 244. Transformations
  245. 245. Data Quality Rules
  246. 246. ETL Components</li></ul>Data Integration<br /><ul><li>Mappings
  247. 247. Transformations
  248. 248. Data Quality Rules
  249. 249. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />Other<br /><ul><li>Security (ex. Roles)
  250. 250. Automation Constructs</li></ul>Other<br /><ul><li>Security (ex. Roles)
  251. 251. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />5<br />Data Source<br />3<br />Data Source<br />4<br />
  252. 252. Extending Past Core Measures<br />Once the second application is developed, the accelerator library is populated with the additional re-usable components<br />ENTERPRISE ANALYIC PLATFORM<br />Presentation/Analytic Capabilities<br />Presentation/Analytic Capabilities<br /><ul><li>Data Visualization
  253. 253. Report Templates
  254. 254. Data Visualization
  255. 255. Report Templates
  256. 256. Dashboard Framework
  257. 257. Dashboard Widgets
  258. 258. Dashboard Framework
  259. 259. Dashboard Widgets</li></ul>ENTERPRISE ARCHITECTURE<br />FACILITY<br />PROCEDURE<br />DIAGNOSIS<br />Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  260. 260. Time
  261. 261. Patient
  262. 262. Diagnosis
  263. 263. Procedure
  264. 264. Physician
  265. 265. Core Measure Type
  266. 266. Core Measure Description
  267. 267. Metrics:
  268. 268. SCIP Value
  269. 269. Hierarchies
  270. 270. Descriptive Attributes</li></ul>Metadata<br /><ul><li>Enterprise Definitions for Data Elements</li></ul>Data Model<br /><ul><li>Dimensions:
  271. 271. Metrics:
  272. 272. SCIP Value
  273. 273. Pneumonia Metrics
  274. 274. Meaningful Use Metrics
  275. 275. Hierarchies
  276. 276. Descriptive Attributes</li></ul>NURSING UNIT<br />ENCOUNTER<br />Meaningful Use Metrics<br />DISCRETE MEASURE<br />ADMISSION DATE<br />DISCHARGE DATE<br />Data Integration<br /><ul><li>Mappings
  277. 277. Transformations
  278. 278. Data Quality Rules
  279. 279. ETL Components</li></ul>Data Integration<br /><ul><li>Mappings
  280. 280. Transformations
  281. 281. Data Quality Rules
  282. 282. ETL Components</li></ul>PHYSICIAN<br />PATIENT<br />TIME<br />Data Integration<br />DATA GOVERNANCE<br />Other<br /><ul><li>Security (ex. Roles)
  283. 283. Automation Constructs</li></ul>Other<br /><ul><li>Security (ex. Roles)
  284. 284. Automation Constructs</li></ul>Data Source<br />1<br />Data Source<br />5<br />Data Source<br />3<br />Data Source<br />4<br />
  285. 285. In Summary<br />
  286. 286. Q & A<br />
  287. 287. Follow Perficient Online<br />Perficient.com/SocialMedia<br />Daily unique content about content management, user experience, portals and other enterprise information technology solutions across a variety of industries.<br />Twitter.com/Perficient<br />Facebook.com/Perficient<br />
  288. 288. Thank You!<br />

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