Singh M Sullivan K 8 21 Dt


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Singh M Sullivan K 8 21 Dt

  1. 1. Winning Trust, Minimizing IT Resources: Key to Forming RHIOs The SEMRHIO Experience Mark Singh MD, President, Clinicore Kathleen Sullivan MPH, CEO, Salient Health
  2. 2. Introduction • Hospitals: Greater demand for electronic data delivery: EMRs interfaces, Portals • Physicians: Clinical data from multiple disparate sources • RHIOs: a solution – Significant Barriers: Trust/Security, Cost • Hospital buy-in: Need to overcome these barriers
  3. 3. Our Experience in forming SEMRHIO • South Eastern Massachusetts Regional Healthcare Information Organization Milton Hospital Jordan Hospital Quincy Medical Center
  4. 4. Overcoming Barriers • Developed a model: – Gain Trust – Minimize Hospital IT infrastructure • lower cost of entry • Won Approval from Hospital Leadership – SEMRHIO
  5. 5. Problems Addressed • Need to support EMR adoption, electronic data delivery, interfaces to hospital systems – Immediate problem which needs a solution within next 2-3 years • Health care delivery is distributed through out community – Challenge to have the appropriate data available in order to provide safe patient care – Trying to keep; up with fax machines: tough
  6. 6. EMR Adoption • More doctors implementing EMRs • Hospitals being asked to provide interfaces – Need to serve small and large practices – Can this this be done more efficiently by hospitals as a “group”: RHIO?
  7. 7. Care Delivered at Multiple Sites Patient Doctor’s offices Imaging Hospital Labs Center Surgi-center
  8. 8. Clinical Data is spread out • When taking care of a patient, need to have access to data from all the other sites – Care delivered in Physician's offices (multiple specialists, PCP) – Hospitals/Emergency Rooms – Nursing Homes
  9. 9. Need to Solve: • How do we deliver clinical data electronically? • How to consolidate clinical data set in real from disparate healthcare entities in order to care for patients?
  10. 10. Solving these Problems • RHIO seems to makes sense: – multi-stakeholder organization – Allow shared costs of common IT infrastructure • Economies of scale – Framework for data sharing among competing organizations
  11. 11. RHIO: Challenges and Barriers • Perceived Negatives regarding RHIOs – Too costly, Lack of sustainability models – Too many security and trust issues among Competing entities. • uncomfortable with concept of “Sharing” clinical data
  12. 12. “California RHIO closes amid cost, privacy concerns” The closure of the Santa Barbara Co. Care Data Exchange eHealth SmartBrief | 07/11/2007
  13. 13. Given these significant barriers, how do we get community based, independent, competing hospitals to form a RHIO?
  14. 14. Need to Address Potential Barriers • Cost and Security issues: – Lack of IT Infrastructure and Resources • Hospitals have more immediate pressing issues: – i.e., CPOE , eMAR – Trust among disparate organizations
  15. 15. Trust in Forming a RHIO • Issue of Architecture, business process – When thinking about RHIOs, we consider classic approach for RHIO architectures – Classic Model is a “federated”, “Pull” based architecture using a Record Locator Service (RLS)
  16. 16. “PULL” based Model Pull Based RHIO Model Return only permitted data Return data but exclude: Drug Addiction Patient data with “HIV”, “Substance Hx 2 has CAD, Abuse”, “Mental Health” CHF. Hospital-A Sodium 135, Cholestero l 187, Glucose Patient has CAD, CHF. Aso HIV. Patient hasNaus 3 ea Aso H Hospital-B h/o HIV. Patient has CAD, CHF. AIDS 1 RLS User requests records on patient Hospital-C Get John Doe’s Mental data Health Hx Search for John Doe’s data across User not entitled to receive data hospitals containing mental health, HIV, substance abuse information
  17. 17. Pull Model Complicates Trust issues • Pull may work very well in a multi-site, single- organization • Has problems in a multi-organizational setting- Problematic – Introduces new Trust issues – Each hospital (source) needs to determine what data each user can access – Model opens up a “can of worms” – Can be a “show stopper” in forming RHIOs
  18. 18. “Best to automate an existing business process and trust relationship” “The RHIO experience in Massachusetts” John Halamka D. MD, CEO MA-SHARE May 4, 2007
  19. 19. How do we build Trust ? Use an existing Trust relationship Use an existing Business Process
  20. 20. Existing Business Process and Trust Relationship “PUSH” model The directed delivery of clinical data from to provider Push Healthcare entity
  21. 21. PUSH Model for Exchange PUSH Based Health Information Interchange Had h/o fall. Felt Sodium Patientdizzine 135, has CAD, ss. Sodium Cholestero CHF. Aso 135, l 187, h/o HIV. CholesteroGlucose Sodium 130 PUSH to 135, l 187, Glucose Cholestero Sodium 187, 130 Authorized l 135,Glucose Cholestero 130 Recipient l 187, Glucose Patient 130 hasNaus ea Aso h/o HIV. Patient has CAD, InBox CHF. Aso h. Building Trust: quot;pushquot; model—A doctor or healthcare entity decides what data to send to another doctor or Patient has CAD, CHF. Aso entity. h/o HIV.
  22. 22. Proposed Model • Adopt conservative approach: Don’t change the current arrangement – Hospital to send data to the legal recipient (“ordering”, “primary” doctors) via RHIO (instead of fax/mail) • Once received by doctor, ownership of data goes to doctor • Data sharing among doctors: “…for treatment, payment, and healthcare operations” per HIPAA guidelines.
  23. 23. SEMRHIO Security Model Doctors can exchange reports Hospitals securely with Exchange Doctors Hospital A Confidential Data via secure RHIO consulting and primary care physicians Dr Good Doctor may have their only share own Dr Health data with secure Hospital B another account Local RHIO doctor for Data for data Exchange Dr Livelong “Treatment sent to and Hospital C them by Dr Luck payment” the per HIPAA hospitals Local RHIO guidelines connects to State RHIO Mega Medical Group STATE WIDE RHIO Mega EMR Confidential Clinical Data Exchange via Local RHIO which reflects the local culture, physician relationships
  24. 24. IT Infrastructure Issues • Hospitals wanted to commit minimal resources • Major Component of the RHIO: Hospital Information System (HIS) Integration – Need for HL7 Interface Engine – Involved increased cost and complexity
  25. 25. Onsite Integration Onsite setup and maintenance required Specialized staff to manage interface HL7 $ Engine HL71 HL72 HL7c Integration HL7 $ Engine Engine HL73 HL7 $ HL7 RHIO Software Engine
  26. 26. Is there an easier solution? – Studied other possibilities • Extract desired data in near-real time, delimited text format, using HIS query /reporting utility • Proposed Model: – Local: Extract hospital data using existing the HIS query/reporting utility – Central: Conversion to HL7 centrally using BizTalk.
  27. 27. Hosted Integration “Zero” local foot-print Move HL7 integration infrastructure centrally Flat file BizTalk based RHIO Software $ HL7 Integration Flat file Engine Flat file
  28. 28. Advantages of Hosted Services Model • Move infrastructure to the other side of the “Cloud”. – Simplify/minimize onsite infrastructure – Existing Local IT staff able to manage onsite needs without additional training needed – Centralize interface management – Allow hospitals to share in economies of scale
  29. 29. Hosted Services • Evolving Model: SOA ,SaaS • Trend towards Hosted services – i.e.,, Google, Postini – Hosted email – Many Hospitals outsource their IT infrastructure and support: e.g., Perot systems
  30. 30. Hosted Integration • Minimizing IT resources • There was also a desire by hospitals to commit minimal resources • Reluctance to install additional software/hardware locally. • We studied the existing hospital IT infrastructure and developed a centralized “Hosted-Integration” model using BizTalk server. • This was a “zero” local foot print implementation model which did not require any additional software/hardware locally, and was implemented using basic IT personal.
  31. 31. The Process • Extract data from HIS use existing built-in reporting/query utility • Hosted BizTalk integration server – BizTalk receive data at input ports – Delimited data mapped to HL7 2.x, • The disparate data is mapped to a standard terminology. • Final data is stored in SQL 2005 for delivery to the recipient physicians.
  32. 32. Source Lab data: Flat file ~delimited convert to HL7 v2x-XML • <ns1:ORU_R01_231_GLO_DEF xmlns:ns2=quot;AM.HL7.Schemas.Tablesquot; xmlns:ns0=quot;AM.HL7.Schemas.Segmentsquot; • 12222 ~01364999 ~000-00-0000 xmlns:ns1=quot;AM.HL7.Schemasquot; ~Doe,John ~11/30/39~67 xmlns:ns3=quot;AM.HL7.Schemas.DataTypesquot;> ~F~3N ~367 ~ADM IN • - <Sequence> ~00966001~LITTLE ~RICHARD • - <PID_PatientIdentificationSegment> ~LITTLE,RICHARD M.D. • - <PID.2_PatientId> ~1204:C00078R ~SODIUM – <CX.0_Id>064166</CX.0_Id> ~T~BASIC METABOLIC PANEL • </PID.2_PatientId> ~CPT 4 ~84295 ~12/04/06~0717~12/04/06~0818~COMP • - <PID.3_PatientIdentifierList> ~136 ~135-145 ~mmol/L ~ • ~ <CX.4_IdentifierTypeCode>MR</CX.4_IdentifierTypeCode > • 12222 ~01364999 ~ 000-00-0000 ~Doe,John ~11/30/39~67 Map FF to HL7 xml • • </PID.3_PatientIdentifierList> - <PID.3_PatientIdentifierList> ~F~3N ~367 ~ADM IN ~00966001~LITTLE ~RICHARD • <CX.4_IdentifierTypeCode>MR</CX.4_Identifi ~LITTLE,RICHARD M.D. erTypeCode> ~1204:C00078R ~POTASSIUM ~T~BASIC METABOLIC PANEL • </PID.3_PatientIdentifierList> ~CPT 4 ~84132 • - <PID.3_PatientIdentifierList> ~12/04/06~0717~12/04/06~0818~COMP • <CX.0_Id>000-00-0000</CX.0_Id> ~4.2 ~3.7-5.2 ~mmol/L ~ • ~ <CX.4_IdentifierTypeCode>MR</CX.4_Identifi erTypeCode> • </PID.3_PatientIdentifierList> • - <PID.5_PatientName> • - <XPN.0_FamilyLastName> • <XPN.0.0_FamilyName>Doe</XPN.0.0_Family Name> • </XPN.0_FamilyLastName> • <XPN.1_GivenName>John</XPN.1_GivenNa me> • </PID.5_PatientName> • <PID.7_DateTimeOfBirth>20331122</PID.7_DateTimeOf Birth> • <PID.8_Sex>F</PID.8_Sex> • - <PID.18_PatientAccountNumber> • <CX.0_Id>49717259</CX.0_Id>
  33. 33. Mapping Flat file to HL7 2x
  34. 34. BizTalk Orchestration
  35. 35. Clinical Results Viewer • Labs • Radiology • Clinical Reports An “EMR-Lite” client application to view the data was built using .NET and Microsoft’s “Composite Application Block”.
  36. 36. Clinical Events Viewer Keeps track of patient events: -Hospital, ER admissions discharges - Bed Census
  37. 37. Conclusion: • By using a “push” model and a BizTalk based “Hosted-Integration-Services” model: – Able to gain trust and minimize hospital IT resources • Demonstrated how: – competing community hospitals can succeed in winning approval for forming a RHIO by their hospital leadership.
  38. 38. Microsoft Technologies used: – BizTalk 2006 – Visual Studio 2005 – SQL 2005 – Composite Application Block
  39. 39. Technical Team Hospital • Mike Cosgrave IT Infrastructure • Brian Allen • Ed Powers, GlobalNet Solutions – • Anne Baker • Jean Fernandez • Crowley, Sheryl BizTalk Eric Stott, Information Architect, Clinicore
  40. 40. Thanks! For more information: Mark Singh MD msingh at semrhio dot org