Clinical Quality and Policy

Transcription

1 Clinical Quality and Policy A DEEP DIVE BEFORE AN AERIAL VIEW

2 Our Mission 1. Understand the technical framework 2. Testing 3. Programs and performance 4. Governance 5. Data- and Workflow 6. Integration and Interoperability 7. Making Quality Meaningful

3 Understanding the Technical Framework 1. QDM to CQL 2. CDA to FHIR, Smart on FHIR apps 3. Terminology 4. VSAC 5. Cimi on FHIR

4 Understanding a Measure: (Example title and number)

5 emeasure (or ecqm) The electronic format for quality measures using: the Quality Data Model to define clinical concepts (Lego brick specifications) and the Healthcare Quality Measure Format to define quality measures (instructions constraining the use of Lego blocks to create meaningful structures). Barnes I. Making the Move to Electronic Clinical Quality Measurement. Epic 2015 Expert User Group Meeting. Verona, WI. March 17,

6 The Quality Data Model An information model intended to clearly and consistently define concepts used in quality measures in a standardized format. The QDM includes: criteria for data elements, relationships for relating data element criteria to each other, and functions for filtering criteria to the subset of data elements that are of interest.

7 Quality Data Model (QDM) Barnes I. Making the Move to Electronic Clinical Quality Measurement. Epic 2015 Expert User Group Meeting. Verona, WI. March 17,

8 QUALITY DATA ELEMENT HOW DO WE DESCRIBE A PROBLEM FOR ELECTRONIC QUALITY MEASUREMENT? Category: consists of a single clinical concept identified by a value set Medication, Laboratory Test Data Type: The context in which each category is used to describe a part of the clinical care process Laboratory Test, Order Laboratory Test, Performed Attribute: provides specific detail about a QDM element Laboratory Test, Performed: (result) Value Set: used to define the set of codes that can possibly be found in a patient record for a particular concept. 10 Barnes I. Making the Move to Electronic Clinical Quality Measurement. Epic 2015 Expert User Group Meeting. Verona, WI. March 17, 2015

9 Health Quality Measures Format (HQMF) A Health Level Seven International (HL7) standard for documenting the content and structure of a quality measure. It includes: Metadata describing the quality measure Human readable narrative description, data criteria, and measure population Machine readable translation of the measure. 11 Barnes I. Making the Move to Electronic Clinical Quality Measurement. Epic 2015 Expert User Group Meeting. Verona, WI. March 17, 2015

10 2018 Standards Evolution for CMS ecqm Specifications Public comment on ecqms open until Nov. 10! 10

11 Future Standards Need to be Interoperable Across Each Other to Allow Flexibility Clinical Quality Language (CQL) Authors use CQL to produce libraries containing humanreadable yet precise logic. Expression Logical Model (ELM) ELM XML documents contain machine-friendly rendering of the CQL logic. This is the intended mechanism for distribution of libraries. Native Java Script Drools SQL Implementation environments will either directly execute the ELM, or perform translation from ELM to their target environment language.

12 Evolving ecqm Standards Now Near Term HQMF (Metadata, Population Structure QDM (Logic) QDM (Data Model) HQMF (Metadata, Population Structure) CQL (Logic) QDM (Data Model) Definitions: HQMF Health Quality Measure Format CQL Clinical Quality Language QDM Quality Data Model

13 Differences Between the Quality Data Model (QDM) Now and When using Clinical Quality Language (CQL) QDM Now QDM with CQL Data Model and Logic are both in the QDM The Data Model will continue to exist as the QDM CQL will provide the logic expressions and will replace that function currently in the QDM

14 Clinical Quality Language Originated from need to harmonize decision support and quality measurement Author-friendly and human-readable language Computable and implementable Standard for Trial Use (STU) CQL provides the ability to express logic that is human readable yet structured enough for processing a query electronically

15 Limitations of a QDM Logic Model QDM can t express comparisons needed to evaluate outcomes of care e.g., change in depression scale (PHQ-9) results over time for a single patient, or for each patient in a cohort QDM can t use mathematical expressions to derive results e.g., patients who have a PHQ-9 Follow-Up Score = ½(Baseline PHQ-9 Score) QDM can t identify components of an assessment, examination or test procedure e.g., assure the systolic and diastolic blood pressure results are from the same blood pressure reading QDM logic model only works with QDM data model

16 Benefits of CQL **

17 Measure Authoring Tool Narrative Measure Specification Measure Authoring Tool Measure Package

18 MAT Measure Package Export Measures encoded and packaged in the MAT output 4 measure artifacts 1. Human Readable HTML 2. CQL Library information 3. ELM (machine-friendly representation of XML) 4. HQMF XML file consumable by an EHR

19 Measure Authoring Tool: Clause Library

20 Standards Improvement and Harmonization: Clinical Quality Measurement and Clinical Decision Support CQM Specific Standards HQMF QRDA Category-1 QRDA Category-3 QDM Common Metadata Standard Common Data Model Standard (QI Core/FHIR)* Common Expression Logic Standard (CQL)** CDS Specific Standards HeD vmr * Quality Improvement and Clinical Knowledge ** Clinical Quality Language Common Clinical Data Elements (CIMI/FHIR)

21 Advanced Next Generation Standards for Clinical Quality Improvement Allowed in QPP now proposed support in future QPP reporting API 21

22 Next Generation Standards for Clinical Quality: FHIR Clinical Reasoning: FHIR 22

23 HSPC: Healthcare Services Platform Consortium The iphone Approach 23

24 Terminology

25 The problem Huge amounts of clinical data being generated both within and outside clinical care settings Tremendous potential Primary use i.e., clinical care Secondary use e.g., quality measures, public health, rare diseases research But potential can only be realized if the data are stored and exchanged using common data and messaging standards

26 Data versus messaging standards Data standards provide a consistent definition for a given concept across systems Messaging standards provide a common structure by which to exchange data between systems

27 Data vs messaging standards Need both common data and messaging standards for successful interoperability ios Messaging standard ios Messaging standard Android Data standard

28 Data standards LOINC laboratory and clinical observations Urine sodium, Systolic blood pressure, Ankle MRI SNOMED CT findings/values Hypernatremia, Hypotension, Streptococcus pneumoniae bacteremia RxNORM clinical drugs Penicillin, Infliximab IEEE observables for medical devices Ventilator breath rate setting, EEG burst rate ICD-10-CM diagnoses (for billing) CPT procedures (for billing)

29 Messaging standards HL7 (Health Level 7) Version 2 Version 3/CDA FHIR DICOM (Digital Imaging and Communications in Medicine)

30 LOINC in an HL7 message MSH ^~\& ORU^R01 PID ^9^M11 Smith^John^J OBR ^Blood pressure panel^ln OBX CE ^Body position^ln ^Sitting^SCT OBX NM ^Systolic blood pressure^ln 138 mmhg OBX NM ^Diastolic blood pressure^ln 85 mmhg

31 LOINC in XML message (e.g., HL7 CDA) <Observation>... <component> <code> <coding> <system value=" /> <code value= "1975-2" /> <display value="bilirubin.total [Mass/ volume] in Serum or Plasma" /> </coding> </code> <valuequantity> <value value="0.8" /> <unit value="mg/dl" /> <system value=" /> <code value="mg/dl" /> </valuequantity> </component>

32 Data vs messaging standards Need both common data and messaging standards for successful interoperability Personal health record Messaging standard OBX 1 Data type Test code Result Units Hospital EHR Messaging standard OBX 1 Data type Test code Result Units CMS Systolic blood pressure 138 mmhg Medication name + identifier 2193 Ceftriaxone RxCUI Body position with respect to gravity Sitting SNOMED CT Data standards

33 LOINC basics Logical Observation Identifiers Names and Codes Standard terminology to identify lab tests, clinical measurements, documents, surveys, and more Used in 170+ countries, mandated in nearly 30 Maintained by Regenstrief Institute, Inc. Supported by the National Library of Medicine And it s free!

34 Brief history of LOINC Organized in 1994 by Clement McDonald, MD Needed a universal language for observation identifiers Began with laboratory observations Expanded to clinical observations in 1996 Currently includes 4 major categories Laboratory LOINC Clinical LOINC HIPAA attachments Standardized survey instruments

35 LOINC grows because you ask

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37 How to access LOINC Twice-yearly releases in June and December June 2017 (v2.61) release had >85,000 terms Find codes using Regenstrief LOINC mapping assistant (RELMA) desktop application Multiple download formats New files in v2.61, including LOINC Parts, Answers, and Groups

38 Value Set Authority Center (VSAC)

39 Where can I find value sets? The Value Set Authority Center (VSAC) publishes updated ecqm value sets annually. The Downloadable Resource Table provides prepackaged downloads for the most recently updated and released ecqm value sets, as well as for previously released versions.

40 VSAC Value Sets: Downloadables Download value sets by measure, value set name, or quality data model category

41 Value Set Authority Center (VSAC)

42 Clinical Information Interoperability Council CIIC is a broad stakeholder-based group of clinical and technical stakeholder organizations who are seeking to fill in the gaps needed to reach a shared set of interoperability data elements for clinical care Has adopted the CIMI detailed clinical model approach with the physical CDEs translated to FHIR Targets gaps including: clinician organization engagement and education, governance processes, resourcing, and tooling

43 Graphic of a CIMI Detailed Clinical Model SystolicBPObs SystolicBP data quals 138 mmhg LOINC BodyLocation BodyLocation data Right Arm PatientPosition PatientPosition SNOMED CT data Sitting 43

44 FHIR Data Element Resource 44

45 Discussion: Standards

46 Why MACRA? Medicare Access and CHIP Reauthorization Act of 2015 Program started 2017, timelines continue to shift and payment adjustments lag by 2 years CMS prefers term QPP Beginning in 2019, all current Medicare payment, including incentive programs, will be combined into one Merit-Based Incentive Payment System (MIPS), replacing all Medicare reimbursement for eligible professionals. Still on hold The MIPS program will use four performance measures to determine reimbursement, which will begin in 2019: Quality; Resource use; Clinical practice improvement activities; and Now just Improvement Activities (IA) Meaningful use of certified EHR technology (Advancing Care Information) Privacy and security including HIPAA are also requirements and failure to adhere to required standards results in penalties 46

47 QPP Builds on Prior Existing CMS Programs and Requirements Many providers say that the expansion of quality programs has distracted from, rather than added to the focus on providing quality care Need for alignment with non-federal programs has been recognized but not addressed 47

48 APMs & MIPS Paying for Performance Alternative Payment Model Clinicians who receive a substantial portion of their revenues (at least 25% of Medicare revenue in but threshold will increase over time) from qualifying alternative payment mechanisms will not be subject to MIPS. While the definition of a qualifying APM has yet to be determined, MACRA outlines criteria which includes but is not limited to: Quality Measures (APM) Risk-sharing Advancing Care Information Merit-Based Incentive Payment System (MIPS) Adjustments based on the composite performance score of each eligible physician or other health professional on a point scale based on the following performance measures. All scores noted below are for the first MIPS year and are subject to adjustment. Additional positive adjustment available for exceptional performance. Quality (60% of MIPS score 1 st year) Resource Use (0% 1 st year) Clinical Practice Improvement Activities (15%) Advancing Care Information (25%) 48

49 MIPS/QPP Weighting: 2017 and 2018 Majority of program weight lies on quality measures with contributions from Improvement Activities and Advancing Care Information; aligning all three of these activities allows a reporter to maximize value and staff engagement while minimizing investment. In 2018, the proposed rule does not change the mix of weighted activities. Cost will be measured and feedback will be provided in 2018; however, it will not be used to calculate performance. Therefore, considering cost starting in 2018 will position reporters ideally for future years in which cost will begin to take on greater weight for scoring. 49

50 Cost (AKA Resource Use ) CMS will calculate the Medicare Spending Per Beneficiary (MSPB) and total per capita cost measures for feedback purposes. Do not include previous episode-based measures but new ones are in development. Improvement scoring will be based on statistically significant changes at the measure level. Why think about cost now? Improvement scoring with CMS Future episode-based cost measures Move to APM or other cost-sharing arrangement (not just with CMS) Your own bottom line (+ making the C-suite happy) 50

51 More on QPP Scoring SOURCE: CMS, 51

52 More on QPP Scoring Really, 0-14? 52 SOURCE: CMS,

53 HEDIS

54 About HEDIS It all starts with HEDIS H ealthcare Health care s most-used tool for improving performance Asks how often insurers provide evidence-based care to support more than 70 aspects of health E D I S ffectiveness ata nformation et 54

55 184 million 57 % of population HEDIS shines a light on health plans' quality 55

56 About HEDIS It all starts with HEDIS

57 About HEDIS Administrative/Claims Data Medical Record Data Survey Data 57

58 HEDIS in LOINC Since 2009, NCQA and Regenstrief have worked together to maintain HEDIS value sets in LOINC Updated every fall for the following year For value sets that have not changed, dates are updated Otherwise new panels are created

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61 TJC

62 2017/2018 ORYX Performance Measurement Reporting Requirements Updated: 8/15/2017

63 2017/2018 ORYX Performance Measurement Reporting Requirements Updated: 8/15/2017

64 Discussion

65 LUNCH

66 Understanding the Big Picture

67 Governance and Strategy Start by aligning your quality strategy to your business goals Build a team of multidisciplinary experts and thought leaders Create an overview of all your programmatic and regulatory requirements Develop a coherent approach that minimizes rework, mapping, and validation Automate and test test test Celebrate your successes and build on them

68 Infrastructure for Successful ecqm Implementation Health IT/Data Governance Successful ecqms Quality Team Effort

69 Overview: ecqm Implementation Process Get content Gap analysis Data capture and workflow design Data extraction and ecqm calculation Validation Downstream uses of ecqm results A Study of the Impact of Meaningful Use Clinical Quality Measures. Eisenberg et al.,

70 ecqm Implementation is Iterative and Collaborative A Study of the Impact of Meaningful Use Clinical Quality Measures. Eisenberg et al.,

71 Workflow Analysis Definitions of workflow vary: The flow of work through space and time, where work is comprised of three components: inputs are transformed into outputs. [1] The activities, tools, and processes needed to produce or modify work, products, or services. More specifically, clinical workflow encompasses all of the 1) activities, 2) technologies, 3) environments, 4) people, and 5) organizations engaged in providing and promoting health care. [2] 1. Carayon P, Karsh, BT. Workflow toolkit and lessons in user-centered design. Paper presented at the AHRQ Annual Health IT Grantee and Contractor Meeting; 2010 June 2-4; Washington, DC. 2. Niazkhani Z, van der Sijs H, Pirnejad H, Redekop W, Aarts J. Same system, different outcomes: Comparing the transitions from two paper-based systems to the same computerized physician order entry system. International Journal of Medical Informatics 2009; 78(3): Agency for Healthcare Research and Quality. What Is Workflow. Rockville MD. October

72 Dataflow: What is it?

73 Dataflow and Workflow Redesign Data Capture New query build Interface to bring data from disparate application into certified electronic health record technology (CEHRT) Deploy alerts, reminders, and order sets judiciously Workflow redesign Work with subject matter experts to determine where/how data should be captured (e.g., cardiovascular services) Evaluate aspects of care coordination or transitions of care

74 Workflow Analysis Process Step 1: Decide what processes to examine Step 2: Create a preliminary flowchart Step 3: Add detail to the flowchart Step 4: Determine who you need to observe and interview Step 5: Do the observations and interviews

75 Is workflow just the sequence of steps of a process? Not exactly Workflow is the sequence of physical and mental tasks performed by various people over time and through space It can occur at different and/or multiple levels (e.g., one person, between people, or across organizations) It can occur sequentially or simultaneously Agency for Healthcare Research and Quality. What Is Workflow. Rockville MD. October

76 Goals of a flowchart Shows how processes really happen, as opposed to how they are supposed to happen or how we expect they will happen Allows a better understanding of what contributes to different types of flows for the same processes Helps to identify ways to improve the flows Can illustrate ways that health IT will affect workflows Agency for Healthcare Research and Quality. What Is Workflow. Rockville MD. October

77 Example: Detailed Flowcharts Both flowcharts show the workflow of patient check-in Both are accurate descriptions of the same process at a particular clinic, but only the figure on the right (#2) shows the details of what the workflow really is The details of the workflow will change when you implement health IT If you don t understand the details, you cannot plan for the changes that will come. Agency for Healthcare Research and Quality. What Is Workflow. Rockville MD. October

78 Example: Swim Lane Diagram, Before Population Implementing Shared Formulary and E-based Medication Order Review to Create "Closed Loop" Medication Process in Critical Access Hospitals (Text Version). December Agency for Healthcare Research and Quality, Rockville, MD.

79 Example: Swim Lane Diagram, After Population Implementing Shared Formulary and E-based Medication Order Review to Create "Closed Loop" Medication Process in Critical Access Hospitals (Text Version). December Agency for Healthcare Research and Quality, Rockville, MD.

80 The Layers of Workflow Interactions Clinic-level workflow: the flow of information, in paper or electronic formats, among people at a practice or clinic. Intra-visit workflow: workflow during a patient visit Inter-organizational workflow: workflow between healthcare organizations Cognitive workflow: the workflow in the mind Agency for Healthcare Research and Quality. What Is Workflow. Rockville MD. October

81 Data and Workflow Process for Updates Compare measures Consider reporting modification or quality improvement Challenges to data identification and collection: Unstructured data Data latency Discordant data

82 Data Extraction and ecqm Calculation Once data are available, move forward with data extraction and calculation Continue iterative process of validation Additional tweaks to data capture and/or workflow may be necessary after validation Remember to modify tracking documentation

83 Workflow Assessment:

84 Capturing Data as Part of Workflow Depression Care Example

85 Patient with Depression Has current depression diagnosis Taking antidepressant Receiving psychotherapy Care team includes PCP, nurse case manager, consulting psychiatrist, pharmacist Symptoms routinely assessed using PHQ-9 Health Questionnaire (recent score indicates moderate depression) Goes to visit with PCP

86 Historical Data Patient history in PCP s EHR Diagnoses Visits Referrals Medications Patient completes PHQ-9 on patient portal mobile app and at visits

87 Workflow for Patient Visit Patient Check-in Updates personal info Completes PHQ-9 on tablet Rooming RN assessment Weight Blood Pressure PCP Exam PCP assessment Adjusts treatment Follow-up with RN Case Manager

88 Data Capture in Real Time Patient Check-in Updates personal info Completes PHQ-9 on tablet Rooming RN assessment Weight Blood Pressure PCP Exam PCP assessment Adjusts treatment Follow-up with RN Case Manager

89 Data for Quality Measurement Structured By-product of workflow Captured and used in real time (supports measurement-based care) In this example: Denominator = Patient with active depression diagnosis and visit Numerator = PHQ-9 administered to monitor symptoms

90 Common Clinical DataSet (CCDS) Required for transitions of care in 2014 and 2015 Editions of Certification Describes a minimum set of data with variable level of specification generally minimum requirement is a terminology binding Alone does not guarantee interoperability because metadata and other form and manner vary However, it is a good starting place to look for requirements that will be widely available

91 Common Clinical Data Set Renamed the Common MU Data Set. This does not impact 2014 Edition certification. Includes key health data that should be accessible and available for exchange. Data must conform with specified vocabulary standards and code sets, as applicable. Patient name Sex Date of birth Race Ethnicity Preferred language Problems Smoking Status Medications Medication allergies Lab tests Lab values/results Vital signs (changed from proposed rule) Procedures Care team members Immunizations Unique device identifiers for implantable devices Assessment and plan of treatment Goals Health concerns ONC Interoperability Roadmap Goal Send, receive, find and use priority data domains to improve health and health quality Red = New data added to data set (+ standards for immunizations) Blue = Only new standards for data 91

92 Data Mapping:

93 Mapping Mapping is the process of matching a concept in one system to the equivalent concept in another system For example, laboratory code to LOINC ICD-10-CM code to SNOMED CT NDC code to RxNorm Best to assign the standard code as close to the origin of the data as possible to prevent loss of information The more times the data is mapped from one system to another, the higher the chance for errors

94 Mapping principles Map to the most specific code based on the available information Do not overspecify, i.e., do not map to a concept that has more information than what you have available by making assumptions about your data

95 Choose codes to fit your purpose Laboratory in most cases a single LOINC represents a single assay Acute clinical care need granular codes that accurately reflect what is being measured Invasive Systolic blood pressure Noninvasive Systolic blood pressure

96 Choose codes to fit your purpose (cont.) If comparing two methodologies for measuring an analyte, need to find the exact LOINC codes that represent those two assays Example comparing Zika IgM immunoassay to Zika IgM immunofluorescence assay Zika virus IgM Ab [Presence] in Serum by Immunoassay Zika virus IgM Ab [Presence] in Serum by Immunofluorescence If doing a study on how many pregnant women were tested for Zika virus infection over a certain time period, need to use all Zika LOINC codes to find the correct data

97 Searching principles Searches should be tailored for the purpose i.e., looking for very specific data (Zika IgM by IF or IA) versus broader use For specific searches, use all available information to narrow down the results Searching for Zika IgM IF returns 1 LOINC code Searching for Zika CSF returns 8 codes For broad use, keep the search broad Searching for Zika returns 30 records

98 Mapping examples Major laboratories have LOINC mappings published on their websites

99 Mapping examples

100 Mapping examples

101 Customizing a HIT Installation: Impacts Often EHR and HIT systems will allow the implementer to make many customizations to the system being implemented The level of effectiveness of a customization varies based on the: Guidance offered by the developer Knowledge of the informatics team involved in the implementation Data already available in the system Knowledge and alignment of the existing system database Knowledge and alignment of export requirements for reporting and exchange

102 The Impact of Customization: Pro/Con Pros: Allows the system to reflect specialized requirements Gives local terms and providers a place in the system Cons: Generally the more customization the bigger the barrier to interoperability The more customization the more the cost of mapping and maintenance The more customization the more likely things are to break

103 How to Position Yourself on the Leading Edge: Clinical Quality Programs: 1. Look at scoring and bonus point opportunities 2. Consider reorienting your practice into groups. Or practice groups 3. Consider creating or using measures that are more meaningful: 1. Outcomes and risk adjustment 2. Special populations*, specialty measures 3. Multidimensional interventions 4. Integrating workflow and process changes thinking about cost 1. Care plans and coordination (count for IA) 2. Sophisticated risk assessment* and targeted intervention 5. Evaluate changes in reporting options 6. New standards and technology 103

104 Discussion