1 / 46

Methodology

Methodology. Solution Outline Validation. Terminology Collaboration. Whitepaper. Organization, Roles, and Skills Methodology Standards Analysis Tool Evaluation. Business Case Goals and Objectives High-Level Requirements Architecture. Knowledge and Vocabulary Management.

omana
Download Presentation

Methodology

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. Methodology Solution Outline Validation Terminology Collaboration Whitepaper • Organization, Roles, and Skills • Methodology • Standards Analysis • Tool Evaluation • Business Case • Goals and Objectives • High-Level Requirements • Architecture Knowledge and Vocabulary Management Phased Implementation Business Plan • Process Design • Functional Requirements • Non-Functional Requirements • Infrastructure Deployment • System Configuration • Testing • Project Identification • Mission Effect Analysis • Financial Effect Analysis • Risk Analysis

  2. Data Standards Development

  3. Change Proposal Process

  4. Tools

  5. System Context

  6. System Context

  7. System Context

  8. System Context

  9. System Context

  10. System Context

  11. Terminology Management

  12. Why Terminology Management? • Expansion and growth • Localized decision making for system selection and configuration • Multiple versions of the electronic medical record • Fragmentation of patient information within the medical record, something that Dr. Plummer’s unified paper medical record was created to eliminate

  13. Why Terminology Management? • Differing medical records, clinical systems, and terminology have resulted in diverse clinical processes in the delivery of care. • Provides considerable challenge as we seek • Enterprise-wide improvements in outcomes and safety of care • Provision of the best of the entire Mayo Clinic for each patient • Efficiencies of operation and public reporting

  14. Why Terminology Management? Standardization of • Clinical Systems • Policies • Core Clinical Processes • Terminology Promote accuracy and Consistency of Patient Care Delivery Improve Patient Outcomes Decrease Costs Increase Access to Patient Data Develop and access standardized evidence-based protocols and guidelines

  15. Why Terminology Management? “…no matter where a patient is at Mayo Clinic, that patient should know all the Mayo Clinic resources are at his or her disposal.” “…a promise to our patients, staff, and other customers that we are organized and function as a system with a single purpose: our mission. And the mission, as we all know, is to provide the best care to every patient every day…” - Glenn Forbes, M.D.

  16. Clinical Examples

  17. Clinical Notes Document Naming • Problem • Many different ways to view clinical note documentation (nearly 10 systems!) • Standards are implemented at a site, not enterprise level • Record review is inefficient and complex • How do I navigate? • Do I have the entire record? • How do we aggregate data? Can we?

  18. Clinical Notes Document Naming • Scope • Develop enterprise naming standard for Clinical Notes Documents in EMR. • Develop standardized value sets for each component of naming standard

  19. Clinical Notes Document Naming

  20. Clinical Notes Document Naming

  21. Clinical Notes Document Naming

  22. Clinical Notes Document Naming

  23. Vital Signs • Need • Identify and apply best practices (policies, processes, and terminology) across Mayo Clinic to promote accuracy and consistency of care delivery

  24. Height and Weight Temperature Respiratory Rate Pulse Blood Pressure Oxygen Saturation Pain Score Body Mass Index, Body Surface Area Head Circumference Fetal heart tone/rate monitoring with qualifiers (OB patients) Central Venous Pressure plus monitored Vital Signs - Scope

  25. Vital Signs

  26. Nursing Assessments • Business Need • Identify standard value sets for use by EMR applications • Provide a semantic context for the value sets and align the model to the Enterprise Data Model • Document a gap analysis between existing and standard terminologies to identify areas for further work

  27. Business Information Model

  28. Enterprise Context Enterprise Context EDM Concept Unified Model New

  29. Unified Nursing Assessment Model EDM Concept Unified Model Problem Specific

  30. Problem-Specific Models Problem Specific Unified Model

  31. Data Model to Vocabulary Data Model Vocabulary

  32. Inpatient Pain Management • Problem • Inpatient pain service wanted to proactively find patients with unresolved pain, reduce dependency on manually generated referrals • Solution • Reported pain scores recorded in EMR • Data replicated into analytic databases • Nightly report was generated to identify patients whose reported pain scores did not fall below a specified value • Clinical guidelines were applied • Multi-disciplinary provides patient care (Clinical Nurse Specialists, Pharmacists, Pain Clinic)

  33. Inpatient Pain Management • Solution illustrates • Simple use of controlled terminology for patient focused data capture and inference (data) • Information delivered to multi-specialty practice team about a dynamic patient population (information) • Actions taken by multidisciplinary team (knowledge driven care)

  34. Problem List • Problem • ICD 9 standard (for billing) does not adequately meet the needs of the practice to define a clinical problem • Limits workflow and automated decision support • Would like to map terms to multiple standards • Approach • Enterprise data modeling • Process analysis and design • Data and system requirements

  35. Race and Ethnicity • Need for enterprise standardization • Research • Meet internal and external (e.g., funding agencies) research requirements • Education • Conform to The US Department of Education (USDOE) accreditation requirements • Practice • Collect the data necessary to assure diversity does not create disparities in care and every patient receives the best care at Mayo

  36. Laboratory

  37. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  38. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  39. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  40. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  41. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  42. Laboratory – System Integration Transactions to:RES Type:13ASTM From:MNL On:10/02/2001 TX Seq Transaction Data MSH|^~&\|Antrim|MNL|A7023328|MML|200110020001|C7023328|ORU^R01||P|2.2 PID|1|000133443|23660011|00041753443|HANSEN^JEANE M ||19251012|F|| |||1001:PD00011R|||| ORC|RE|K5863087 OBR|1|K5863087||9387^PTH Whole Molecule, |||200110011413|||C7023328^Immanuel-St Josephs Hosp^507-625-4031|N|||||^STOROLE Storvic||L4562352405|1001:PD00011R||||C|CH|A||^^^^^R~R OBX|1|ST|2238^Calcium^ROCLIS||8.9|mg/dL|8.9-10.1|N|||F|19960208||| NTE|1|N^|8.9-10.1 OBX|2|ST|7596^Calcium, S^ROCLIS||DNR|mmol/L|2.2-2.5|N|||F|19960208||| NTE|1|N^|2.2-2.5 (Females > or = 19 years) OBX|3|ST|2239^Creatinine^ROCLIS||5.8|mg/dL|0.6-0.9|h|||F|19890216||| NTE|1|N^|0.6-0.9 (Females > or = 9 years) OBX|4|ST|2240^Phosphorus^ROCLIS||3.9|mg/dL|2.5-4.5|N|||F|19890811||| NTE|1|N^|2.5-4.5

  43. Referral Optimization ProjectEnterprise Data Trust Institutional Appointment Reporting Categories

  44. Clinically Derived Knowledge Bases Vision Practice Based Evidence Data Inference Transactional Databases Analytic Data Repositories Replication and modeling Research, evaluation, & performance measurement Storage and Processing Terminology Patient Focused Data Capture Use of Terminology Consolidate with other evidence, other knowledge bases Point of care knowledge execution Knowledge Management Decision support Clinical Guidelines Expert Systems Inform Evidence Based Practice

  45. Questions?

More Related