1 / 32

Is Healthcare the Most Complex IT Industry ?

Is Healthcare the Most Complex IT Industry ?. Skip Valusek Quality Engineer, Director Performance Improvement Children’s Hospitals & Clinics Minneapolis/St Paul The content of this presentation and discussion is solely that of the presenter. skip.valusek@childrenshc.org 612 813-5876.

kaia
Télécharger la présentation

Is Healthcare the Most Complex IT Industry ?

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Is Healthcare the Most Complex IT Industry ? Skip Valusek Quality Engineer, Director Performance Improvement Children’s Hospitals & Clinics Minneapolis/St Paul The content of this presentation and discussion is solely that of the presenter. skip.valusek@childrenshc.org 612 813-5876 MN-DAMA Feb 2003

  2. Exercise: What Makes IT Complex ? • Identify three dimensions of complexity 2. Pick the dimension you feel is the most important contributor to IT complexity MN-DAMA Feb 2003

  3. Complexity Components MN-DAMA Feb 2003

  4. AGENDA • Very Brief Review of IT Technical Dimensions of Complexity • Brief discussion of “DSS: A Paradigm Addition” • Inter-active discussion of business dimensions of complexity MN-DAMA Feb 2003

  5. Very brief: IT Technical Dimensions • Interfacing/Networking requirements • Information security requirements • Bandwidth • Database requirements • Structural fit • Flat file • Hierarchical ? • Relational? • Object ? • Standardizing definitions • Identifying acceptable values • Application requirements • Breadth • Depth • Volatility MN-DAMA Feb 2003

  6. End-users as a dimension of complexity • Number • Types • Range of End-User: • PC Maturity • Expectations • Rate of change of all the above MN-DAMA Feb 2003

  7. Technology change • Rate • Impact on transaction processes • Impact on decision processes MN-DAMA Feb 2003

  8. Information Management Premise • The purpose of managing information and knowledge is to improve decision making capability. • More effective information/knowledge management requires a paradigm ADDITION for both IT and user communities. MN-DAMA Feb 2003

  9. Machine • Military Command & Control The new, emerging metaphor of the decision paradigm: • Biological or Living Systems (complex adaptive systems) Predominant Metaphors Used in Organizations: MN-DAMA Feb 2003

  10. ? Decision-Making • Decisions commit resources through judgment and choice processes • There is process in decision-making: • Opportunity/Problem Detection & Explanation • Alternative Generation • Analysis (value & probability judgments) • Selection among alternatives • Implementation • Can we model this process? • Judgments (Value & Likelihood) • Choices MN-DAMA Feb 2003

  11. Demographic C U R R E N T H I S T O R Y “Source” Systems “ “ “ Data Warehouse Decision Categories RETROSPECTIVE / ANALYTICAL TACTICAL & STRATEGIC DECISIONS CONCURRENT CLINICAL & OPERATIONAL DECISIONS • RESEARCH & ANALYSIS • ‘across’ • accounts, customers, patients, • channels, practices • markets, • periods, day of week, time of day • Unstructured (little or no process) • Find key variables • Collaboration & sharing. • Design & Refine protocols/pathways • ‘Quick Look’JUDGMENTS & CHOICES • ‘within’ • a PATIENT: view WHAM • a PROVIDER: rounding list • a DEPARTMENT: staff scheduling • a MARKET: assess event impacts • Empower employees (within limits) • Semi-structured process • Apply protocols/pathways/guidelines MN-DAMA Feb 2003

  12. STAR (MUMPS) ORYX 6-digit coding Pharmacy Radiology Lab Med Staff Inpatient Pharmacy (STAR) SYSTEMS/DATA USERS ADAC Lab database (Fortran) Quality Indicators Outpatient Pharmacy Pxyis STAR Lab Radiology (STAR) HDM (B-trieve) Sungard (Oracle) OB database External/Regulatory Relations Eclipsys (Sybase ?) Neuro database? Oncology EXTERNAL SOURCE SYSTEMS OR Navicare Ortho Medline MN Hospital Assoc OB/ Womencare SurgiServer b-trieve Care-effective Cost Payor Relations CV Lab Abaton (Oracle) Micromedex (drug info) OLAP Analytical Decision Processes Neuro MICC database CV IT MODELS Provider Relations Allina KnowledgeQuest CV MicroMedical Behavioral Health Transaction Process (ERD; DFD) OLTP USER’S DECISION WORLD Logician (MedicaLogic) (Oracle) Patient Relations Ortho Database Demographic C U R R E N T H I T O R Y S ED OR Outpatient/ Ambulatory Cactus (credentialing) Warehouse (Oracle) Quality Patient Safety Picker (local) DISC Operational/Clinical Decision Process Storyboards Complaints RisKey (AREV) MediPac Medica Claims Additional Bridges Required MN-DAMA Feb 2003

  13. ANALYSIS REPORTING ANALYSIS REPORTING DATA QUALITY DATA QUALITY Transition to Decision Support • Opportunity/Problem Detection & Explanation • Alternative Generation • Analysis (Cost/Benefit judgments) • Selection among alternatives • Implementation FUTURE Explanation: “Why is it happening?” “What’s the best action ?” TODAY Detection: “What’s Going On?” MN-DAMA Feb 2003

  14. “FINAL” “PILOT” Project Internal Measures External Measures Projects & Measures of the Business: • Start Small & Grow: The Decision Support Paradigm • Healthcare: PDSA Rapid Cycle model for change MN-DAMA Feb 2003

  15. Time Time Time Time Measure Measure Measure Measure Time Time Measure Measure Groupings Groupings Groupings Groupings Groupings Groupings System Evolution 20 36 52 72 88 104 120 Managing Evolutionary Design & Development User Requirements Evolution Time (weeks) MN-DAMA Feb 2003

  16. Managing Evolutionary Design & Development:Obtaining & Sustaining Business Sponsorship • Instill a sense of urgency (level of pain) • A critical success factor of organizational change • Manage expectations • Provide and retain funding • Recruit and retain skills MN-DAMA Feb 2003

  17. AGENDA • Very Brief Review of IT Technical Dimensions of Complexity • Brief discussion of “DSS: A Paradigm Addition” • Inter-active discussion of business dimensions of complexity MN-DAMA Feb 2003

  18. IT Complexity Framework: Assess Business Processes in Four Categories Transaction (I-P-O) Decision (Judgments & Choices) Real-Time/ Operational Retrospective/ Analytical MN-DAMA Feb 2003

  19. Providers Physician(s) Practice(s) Hospital & Staff Payment made “Coding” & Appropriate bills prepared • Payors contract(s) • Individual DRGs, CPT Payors Real-time “Transaction”: Financial Billing complexity Customer (patient) presents Services provided Discrepancies resolved time MN-DAMA Feb 2003

  20. Real-time decision complexity: Safety • Operational/Clinical • Number of front-line employees with decision responsibility • Number of judgment and choice processes for each participant • Number of processes requiring communication • Number of potential failure points MN-DAMA Feb 2003

  21. One sample judgment process: Right “customer” ? Complete record ? • What are the customer expectations regarding a “complete” knowledge of their relationship ? • Difficulty creating a complete customer record for accurate customer decisions. • Who has the master patient record? MN-DAMA Feb 2003

  22. ? Real time decision: patient placement/flow DEMAND SUPPLY Infection Control Nurse Staffing Historical Forecast Ancillary Services External Events Housekeeping Staffing Scheduling & Admissions Forecast Homecare ER Short Stay ER Isolation Beds Family Needs OR BEDS Referring Physicians Discharge Forecast & Status Consulting & Admitting Physicians Sister Hospital Status Children’s Physician Network Other Hospital Status Physician Referral Telephone Line Interpreter Services MN-DAMA Feb 2003

  23. Real-time decision: Financial • EMTALA doesn’t allow financial considerations to enter the initial real-time decision process. Those who “present” to the ER must be assessed regardless of ability to pay. • Forces the problem to the retrospective domain MN-DAMA Feb 2003

  24. Real-time decision complexity: Satisfaction • What are “customer” dis-satisfiers? • Parking • Food • Delays in treatment; waiting time • Double rooms • Staffing • Communication • Poor transitions • Inability to reach consulting physician • Who’s in charge? MN-DAMA Feb 2003

  25. Accuity/ Severity Case Mix LOS Clinical Outcomes Charges Patient Days Census Medication Usage Blood Usage Delays Retrospective Decision: Dimensions for analysis Patient Date/Time Day Employer DRG or APR ICD-9 Plans/ Payors CPT-4 Facility Practice & Provider Department/ Unit • Example attributes of importance: • Age appropriate • Culturally appropriate (44 languages/cultures) MN-DAMA Feb 2003

  26. Measurement of Quality/Evaluation of Success • Balanced Scorecard Components • Safety • Access • Finance • Experience • Stakeholders • Patients • Families • Physicians • Nurses • Ancillary Services • Payers • Regulators MN-DAMA Feb 2003

  27. Retrospective Analysis: Transaction • Safety • Labeling of specimens • Labeling of medications • Waiting time • Access • Length of stay • Time to turn a room • Waiting time • Experience • Billing • Waiting time MN-DAMA Feb 2003

  28. Difficulty properly attributing provider/servicer • Team of service vs individual • Practices (“coverage”) • Roles • PCP • Attending • Procedure • Consult • Resident • Team services MN-DAMA Feb 2003

  29. Retrospective Analysis: Relationships Schools Community Efforts & Action Groups Children’s Services & Provider Network Community-based advocacy groups Hospitals Physician Groups Families Employers Local State National Governments Clinics Social Service Providers • MHHP, • NACHRI, • AAP, • MCHP, • CDF Local State Public Health Managed Care Payers MN-DAMA Feb 2003

  30. Supreme Court Federal Circuit Courts Departmental Congress Appeals Administrators Office HCFA OIG Health Care FInancing Administration MIPS State Survey & PRRB Survey Certification Regional Offices Intermediaries Carriers PRO's State & Local Governments JCAHO DMERC State Health State Medical Boards Boards Regional Home Health Intermediaries HIPAA State Medicaid EMTALA HHS/OCR HHS/NIOSH Leapfrog HHS/OMH CLAS HHS/HRSA HOSPITALS State Licensure FDA DOT OSHA Labor/Justice ADA DOL/ Employment OPO'S DOJ NRC SEC IRS EPA FTC FCC FBI CDC CARF NCQA Regulatory/Compliance/Accreditation (Number of regulators & Information intensity) MN-DAMA Feb 2003

  31. Rate of content knowledge creationImpact on real-time and retrospective decisions Transaction (I-P-O) Decision (Judgments & Choices) Real-Time/ Operational Retrospective/ Analytical MN-DAMA Feb 2003

  32. Review of Healthcare Complexity: Change Process Real-Time/ Operational Retrospective/ Analytical Ability to achieve agreement (across & within stakeholder groups) Transaction (I-P-O) Decision Intensity (Judgments & Choices) MN-DAMA Feb 2003

More Related