Value Based Pay for Performance (VBP4P) Stakeholders. From: Lindsay Erickson, Director, Value Based P4P, Integrated Healthcare Association

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1 To: Value Based Pay for Performance (VBP4P) Stakeholders From: Lindsay Erickson, Director, Value Based P4P, Integrated Healthcare Association Subject: Measurement Years 2017 & 2018 Proposed Changes to the VBP4P Program 2017 Value Based P4P Public Comment Period September 1 September 29, 2017 Value Based P4P staff is inviting public comment on the following: 1. IHA Performance Measurement Changes IHA seeks comment on proposed timeline, process, and measurement changes. 2. Measurement Year 2017 (MY 2017) The changes outlined reflect the proposed process and guidelines for collecting the results, measures identified for testing, and the incorporation of updates to the specifications of existing VBP4P measures to align with measure steward s specifications for the same period (e.g., HEDIS 2018 and VBP4P MY 2017 measure the same time period). As a reminder, the MY 2017 Measure Set was finalized in 2016; all changes reflect specification updates, not measure additions or removals. 3. Measurement Year 2018 (MY 2018) The changes outlined reflect the measures that are proposed for payment and public reporting for MY 2018; results will reflect the care provided to members in calendar year 2018 and be collected and reported during calendar year Specifications are provided for any measures that are not already included in the VBP4P manual. 4. General Feedback on VBP4P Program and Measure Sets Value Based P4P staff welcome general comments on the VBP4P program and measure sets. Comments are due by 5 p.m. PDT on Friday, September 29, 2017 to the Public Comment website at the following link: Page 1 of 36

2 Public Comment Login Instructions: Access the Public Comment System Step 1: The public comment system is integrated with NCQA s single sign-on platform. If you have access to any of the systems below you can use the same credentials to login and submit your comments: Interactive Data Submission System (IDSS) Health Organization Questionnaire (HOQ) Download Center Recognition Program Online Application Quality Compass (QC) Policy/Program Clarification Support (PCS) Note: Use the Forgot Password button if you are unsure of your password. By using this feature you are changing your password for any NCQA system to which you have access. Step 2: If you do not have access to any of the systems from step 1, click the Create an Account button and complete the entire form. Please retain the password for your records. Submit a Comment NCQA and IHA will not accept comments submitted outside of the system. Step 1: Begin by selecting a Product. Step 2: Click on the Instructions link to view public comment materials including instructions, proposed specifications and measures. Step 3: Select a Topic and Element (if applicable) Step 4: Select a Support Type Step 5: Complete the Comments box. Note: the character limit for all comments is 2500 characters. Step 6: If you are submitting more than one comment, use the Submit and Return button. When finished submitting all comments, use the Submit and Logout button to receive an e- mail notification with all submitted comments. Page 2 of 36

3 Introduction All comments received during the Public Comment period will be reviewed by the VBP4P Technical Measurement or Technical Payment Committee, and responses, including applicable changes, will be approved by the VBP4P Governance Committee before being incorporated where appropriate. IHA Performance Measurement Changes New Timeline to Support Consolidation of VBP4P & Atlas Health Plan Data Submission One of the takeaways from VBP4P participant feedback, bolstered by market research IHA conducted in 2017, is that IHA should take steps to increase operational efficiencies and strengthen data capabilities to reduce reporting burden on stakeholders and increase the meaningfulness of the information and reports we produce. There was support to enhance the services and products we already provide, rather than expanding information and reports produced. As one step toward this end, and in concert with recent data vendor re-procurement efforts, IHA plans to consolidate the VBP4P and Atlas data submissions from health plans in To support a successful transition to a consolidated process, the proposed MY 2017 reporting timeline has been pushed out. The current VBP4P reporting timelines for resource use and cost are not realistic, as evidenced by the frequent delays due to health plan data issues each year. As such, the reporting timeline for 2018 has been adjusted to allow more time to get clean, useable data. See pages 6-7 of the draft MY 2017 VBP4P Manual for the updated timeline. Specialty Pharmacy Measure Development Generic Prescribing has been a VBP4P resource use measure since Over time, participating physician organizations have driven substantial gains in the generic prescribing rates statewide. Over the same period, the drug pipeline has shifted and new cost drivers beyond branded drugs, including specialty and biologic drugs, have emerged. Together these changes translate to less opportunity for physician organization improvement and less impact on overall pharmacy spend. The VBP4P committees have identified the desire to establish a replacement measure or measures that targets the current opportunities to impact pharmacy spend. Doing so will help support more meaningful incentives across all VBP4P participating POs. There is not an obvious candidate measure to replace generic prescribing, so a workgroup of health plan and physician organization pharmacy management staff will be convened later this Fall to take up the issue. In preparation, IHA is seeking stakeholder input that may contribute to this effort. Measurement Year 2017 (MY 2017) MY 2017 VBP4P Measure Specification Updates Align to Measure Steward Specifications As a reminder, the MY 2017 VBP4P Measure Set was finalized in calendar year VBP4P intends to align with all HEDIS 2018 measure specification updates to ensure measure alignment and reduce reporting burden for participating physician organizations and health plans. Changes to the MY 2017 VBP4P Measure Set reflect alignment with HEDIS specification changes made in HEDIS A Page 3 of 36

4 summary of measure specification changes is listed at the beginning of each measure specification, and a complete Summary of Changes can be found in Appendix 1 of the draft MY 2017 VBP4P Manual. The MY 2017 Measure Set can be referenced online in full in Appendix B. Please note that the Breast Cancer Screening and Immunizations for Adolescents: HPV Vaccine for Adolescents include notable updates as part of NCQA s continuous monitoring process for HEDIS, and that an update has been made to the non-hedis Controlling Blood Pressure for People with Hypertension measure to better align with the intent of the HEDIS Controlling Blood Pressure measure. Align to Standard Specifications for Inpatient & Emergency Department Resource Use In addition to increasing data collection efficiency and alignment, efforts underway to consolidate health plan data submissions and update our vendor contracts afford the opportunity to increase measurement efficiency and alignment. Optimally, any changes would be implemented in measurement year 2017, as IHA executes a new contract with a data aggregation vendor. Towards this end, IHA is considering replacing the specifications for current Inpatient Utilization, Inpatient Bed Days, and Emergency Department Visits and aligning with the current HEDIS utilization (Inpatient Utilization General Hospital/Acute Care and Ambulatory Care) and risk-adjusted utilization measures (Inpatient Hospital Utilization and Emergency Department Utilization). One of the guiding principles of the VBP4P program has been to align with standard specifications. When VBP4P first tested the risk-adjusted resource use measures, there were not standardized, riskadjusted measures available. Within the last year, HEDIS has added standard specifications for riskadjusted inpatient discharge and ED utilization. These new HEDIS measures incorporate a transparent, public domain HCC-based risk adjustment methodology, which is similar to the approach used for All-Cause Readmissions. Complete HEDIS specifications for these measures are available in Appendix A. Please note that this measure will only be generated by the IHA data aggregation vendor from claims data submitted by health plans. Like other appropriate resource use measures, these measures will not be self-reported by physician organizations. Aligning to standard specifications will affect the trending of these measures. To support consistency and trending, IHA will work with its data aggregation vendor to provide updated MY 2016 and MY 2017 results to participants in reporting year Align to Standard Specifications for Total Cost of Care In addition to increasing data collection efficiency and alignment, efforts underway to consolidate health plan data submissions and update our vendor contracts afford the opportunity to increase measurement efficiency and alignment. Optimally, any changes would be implemented in measurement year 2017, as IHA executes a new contract with a data aggregation vendor. Towards this end, there is now an NQF endorsed national standard total cost of care measure (and companion total resource use measure) that was not available when IHA started developing and measuring total cost of care. The NQF measure has had significant uptake, and is currently in use in 37 states and the District of Columbia. It is very similar to IHA s total cost of care measure. In addition to aligning to a national standard, the use of the NQF measure would also address a Page 4 of 36

5 methodological challenge that has continued to affect the timeliness of producing IHA s total cost of care results. The endorsed specifications are available here. This measure will only be generated by the IHA data aggregation vendor from data submitted by health plans and will not be self-reported by physician organizations. Please note that changing the total cost of care specifications will affect the trending of results between years. To support consistency and trending, IHA will work with its vendor to provide updated MY 2016 and MY 2017 results to participants in MY 2017 Commercial VBP4P - Testing Measures The VBP4P committees continuously evaluate approaches for measuring the commercial HMO/POS population to ensure a targeted, highly aligned measure set that meets the needs of VBP4P participating physician organizations and health plans. To this end, the Committees have recommended testing three new measures in MY 2017: Comprehensive Diabetes Care - Eye Exam, Use of Opioids at High Dosage, and Concurrent Use of Opioids and Benzodiazepines. Measures tested in MY 2017 will be reviewed in reporting year 2018 and considered for addition to the IHA measure set for future years (e.g., baseline in MY 2018 and recommended for payment/public reporting as early as MY 2019). All participating health plans and self-reporting physician organizations are encouraged to submit data for these testing measure in MY Comprehensive Diabetes Care: Eye Exam (CDC) The Committees reevaluated the Comprehensive Diabetes Care (CDC) measures to review opportunities to increase alignment. Toward greater consistency with NCQA s health plan accreditation standards as well as Medicare Advantage Stars measurement, they have recommended testing this measure in the VBP4P commercial HMO/POS product line for MY Please refer to the draft MY 2017 VBP4P Manual for full measure specifications. CDC: Eye Exam measures the percentage of members years of age with diabetes (type 1 and type 2) who had an eye exam. Use of Opioids at High Dosage (UOD) Lowering opioid-related morbidity and mortality has emerged as a focus area for many providers, health plans, purchasers, and policymakers in California and is now a national priority. Reducing the overuse of opioids is also one of three focus areas for Smart Care California, a multi-stakeholder effort to promote safe, affordable care led by California s three largest state purchasers. An important aspect of reducing opioid overuse is identifying patients who are at highest risk of opioid overdose, such as patients on high doses of opioids, and working with patients to taper them to safer doses. Measuring high dose opioid use will support understanding of the scope of high dose opioid use in the Commercial population and provide valuable information to health plans and physician organizations. Use of Opioids at High Dosage measures the rate per 1,000 members 18 years and older, receiving prescription opioids for 15 days during the measurement year who are prescribed opioids at high dosage MED >120 mg. Please refer to the draft MY 2017 VBP4P Page 5 of 36

6 Manual for full measure specifications. The VBP4P Committees recognize that high dose opioid use is a focus area for providers, health plans, purchasers, and policymakers. Please note that due to anticipated programming complexity of the measure specifications, this measure will only be submitted by participating health plans. Concurrent Use of Opioids and Benzodiazepines (COB) Smart Care California has identified opioid overuse as a focus area, with monitoring of high-risk regimens (such as opioids and benzodiazepines) of particular importance. Studies of fatal opioid overdose deaths found evidence of concurrent benzodiazepine use in 31% 61% of decedents 1, and CDC guidelines for prescribing opioids for chronic pain recommend avoiding concurrent opioid and benzodiazepine prescribing 2. Concurrent Use of Opioids and Benzodiazepines measures the percentage of individuals 18 years and older with concurrent use of prescription opioids and benzodiazepines. Please refer to the draft MY 2017 VBP4P Manual for full measure specifications. Please note that due to anticipated programming complexity of the measure specifications, this measure will only be submitted by participating health plans. MY 2017 Medicare Advantage - Baseline Measure Additions These measures will be added as baseline measures (reported by participating health plans and selfreporting physician organizations) in an effort to align with CMS Medicare Advantage Star measurement. Please refer to the draft MY 2017 VBP4P Manual for full measure specifications. Statin Therapy for Patients with Cardiovascular Disease (SPC) Statin Therapy for Patients with Cardiovascular Disease assesses the percentage of males years of age and females years of age during the measurement year, who were identified as having clinical atherosclerotic cardiovascular disease (ASCVD) and met the required criteria. Two rates are reported: 1. Received Statin Therapy - Members who were dispensed at least one high or moderateintensity statin medication during the measurement year 2. Statin Adherence 80%. Members who remained on a high or moderate-intensity statin medication for at least 80% of the treatment period. Statin Use in Persons with Diabetes (SUPD) Statin Use in Persons with Diabetes measures the percentage of patients ages years who were dispensed a medication for diabetes that receive a statin medication. 1 Dowell D, Haegerich TM, Chou R. CDC Guideline for Prescribing Opioids for Chronic Pain United States, MMWR Recomm Rep 2016;65(No. RR-1):1 49. DOI: Page 6 of 36

7 Measurement Year 2018 (MY 2018) MY 2018 Commercial VBP4P - Measure Removals The MY 2018 Measure Set is available in full online and in Appendix C. Annual Monitoring of Patients on Persistent Medications (MPM) Due to high performance as well as low variation amongst the VBP4P commercial HMO/POS population, the VBP4P Committees have recommended retirement of Annual Monitoring of Patients on Persistent Medications beginning in MY Diabetes Care: Two HbA1c Tests (CDC) The VBP4P Committees have recommended retirement of Diabetes Care: Two HbA1c Tests in Measurement Year 2018 to increase focus on a more meaningful outcomes measure (CDC: HbA1c Control <8%). Additionally, the HbA1c screening is no longer part of NCQA health plan accreditation and the two test version of the screening measure is not broadly used. Please note that due to the retirement of this measure, the Optimal Diabetes Care Combination Rate (an all-or-none rate which includes: HbA1c Control <8%, Two HbA1c Tests, Blood Pressure Control, and Medical Attention for Nephropathy) will become a baseline measure in MY 2018 to ensure trending in future years. Page 7 of 36

8 Inpatient Utilization General Hospital/Acute Care 1 Inpatient Utilization General Hospital/Acute Care (IPU) SUMMARY OF CHANGES TO HEDIS 2018 Revised the data elements tables to indicate that rates are calculated for the Discharges/1,000 Member Months/Years in the unknown category. Description This measure summarizes utilization of acute inpatient care and services in the following categories: Total inpatient. Maternity. Surgery. Medicine. Calculations Note: Members in hospice are excluded from this measure. Refer to General Guideline 20: Members in Hospice. Product lines Member months Report the following tables for each applicable product line: Table IPU-1a Total Medicaid. Table IPU-1b Medicaid/Medicare Dual-Eligibles. Table IPU-1c Medicaid Disabled. Table IPU-1d Medicaid Other Low Income. Table IPU-2 Commercial by Product or Combined HMO/POS. Table IPU-3 Medicare. For each product line and table, report all member months for the measurement year. IDSS automatically produces member years data for the commercial and Medicare product lines. Refer to Specific Instructions for Utilization Tables for more information. Maternity rates are reported per 1,000 male and per 1,000 female total member months in order to capture deliveries as a percentage of the total inpatient discharges. Days ALOS Count all days associated with the identified discharges. Report days for total inpatient, maternity, surgery and medicine. Refer to Specific Instructions for Utilization Tables for the formula. Calculate average length of stay for total inpatient, maternity, surgery and medicine. Page 8 of 36

9 Inpatient Utilization General Hospital/Acute Care 2 Use the following steps to identify and categorize inpatient discharges. Step 1 Identify all acute inpatient discharges on or between January 1 and December 31 of the measurement year. To identify acute inpatient discharges: 1. Identify all acute and nonacute inpatient stays (Inpatient Stay Value Set). 2. Exclude nonacute inpatient stays (Nonacute Inpatient Stay Value Set). 3. Identify the discharge date for the stay. Step 2 Exclude discharges with a principal diagnosis of mental health or chemical dependency (Mental and Behavioral Disorders Value Set), or an MS-DRG for mental health, chemical dependency or rehabilitation (IPU Exclusions MS-DRG Value Set). Exclude newborn care rendered from birth to discharge home from delivery (only include care rendered during subsequent rehospitalizations after the delivery discharge). Identify newborn care by a principal diagnosis of live-born infant (Deliveries Infant Record Value Set) or the presence of a code from the Newborn/Neonates MS-DRG Value Set. Organizations must develop methods to differentiate between the mother s claim and the newborn s claim, if needed. Step 3 Report total inpatient, using all discharges identified after completing steps 1 and 2. Step 4 Report maternity, surgery and medicine using MS-DRGs. For organizations that use DRGs, categorize each discharge as maternity, surgery or medicine. Maternity (Maternity MS-DRG Value Set). A delivery is not required for inclusion in the Maternity category; any maternity-related stay is included. Include birthing center deliveries and count them as one day of stay. Surgery (Surgery MS-DRG Value Set). Medicine: Medicine MS-DRG Value Set. Newborns/Neonates MS-DRG Value Set. Do not include newborn care rendered from birth to discharge home from delivery; only report newborn care rendered if the baby is discharged home from delivery and is subsequently rehospitalized. Note: If reporting using MS-DRGs, Total Inpatient will not equal the sum of Maternity, Surgery and Medicine because DRGs for Principal Diagnosis Invalid as Discharge Diagnosis and Ungroupable are included in Total Inpatient, but are not included in maternity, surgery or medicine. If the organization does not use MS-DRGs, follow steps 5 7 to categorize discharges. Step 5 Report maternity. A delivery is not required for inclusion in the Maternity category; any maternity-related stay is included. Include birthing center deliveries and count them as one day of stay. Starting with all discharges identified in step 3, identify maternity using either of the following: A maternity-related principal diagnosis (Maternity Diagnosis Value Set). A maternity-related stay (Maternity Value Set). Step 6 Step 7 Report surgery. From discharges remaining after removing maternity (identified in step 5) from total inpatient (identified in step 3), identify surgery (Surgery Value Set). Report medicine. Categorize as medicine the discharges remaining after removing maternity (identified in step 5) and surgery (identified in step 6) from total inpatient (identified in step 3). Page 9 of 36

10 Inpatient Utilization General Hospital/Acute Care 3 Table IPU-1: Inpatient Utilization General Hospital/Acute Care Age Member Months < Unknown Total Discharges/1,000 Member Months Days/1,000 Member Months Average Length of Stay Age Discharges Days Total Inpatient < Unknown Total Maternity* Unknown Total Surgery < Unknown Total *The Maternity category is calculated using member months for members years. Page 10 of 36

11 Inpatient Utilization General Hospital/Acute Care 4 Age Medicine Discharges Discharges/1,000 Member Months Days Days/1,000 Member Months Average Length of Stay < Unknown Total Table IPU-2/3: Inpatient Utilization General Hospital/Acute Care Age Member Months < Unknown Total Age Total Inpatient Discharges Discharges/ 1,000 Member Years Days Days/ 1,000 Member Years Average Length of Stay < Unknown Total Page 11 of 36

12 Inpatient Utilization General Hospital/Acute Care 5 Age Maternity* Discharges Discharges/ 1,000 Member Years Days Days/ 1,000 Member Years Average Length of Stay Unknown Surgery Total < Unknown Medicine Total < Unknown Total *The Maternity category is calculated using member months for members years. Page 12 of 36

13 Ambulatory Care 1 Ambulatory Care (AMB) SUMMARY OF CHANGES TO HEDIS 2018 Clarified how to identify an ED visit that resulted in an inpatient stay. Removed the AOD Rehab and Detox Value Set from the required exclusions (exclusions will be identified based on a principal diagnosis of chemical dependency). Revised the data elements tables to indicate that rates are calculated for the Visits/1,000 Member Months/ Years in the unknown category. Description This measure summarizes utilization of ambulatory care in the following categories: Outpatient Visits. ED Visits. Calculations Note: Members in hospice are excluded from this measure. Refer to General Guideline 20: Members in Hospice. Product lines Member months Counting multiple services Outpatient visits Report the following tables for each applicable product line: Table AMB-1a Total Medicaid. Table AMB-1b Medicaid/Medicare Dual-Eligibles. Table AMB-1c Medicaid Disabled. Table AMB-1d Medicaid Other Low Income. Table AMB-2 Table AMB-3 Commercial by Product or Combined HMO/POS. Medicare. For each product line and table, report all member months for the measurement year. IDSS automatically produces member years data for the commercial and Medicare product lines. Refer to Specific Instructions for Utilization Tables for more information. For combinations of multiple ambulatory services falling in different categories on the same day, report each service that meets the criteria in the appropriate category. Outpatient visits (Ambulatory Outpatient Visits Value Set). Count multiple codes with the same practitioner on the same date of service as a single visit. Count visits with different practitioners separately (count visits with different providers on the same date of service as different visits). Report services without regard to practitioner type, training or licensing. Page 13 of 36

14 Ambulatory Care 2 ED visits Count each visit to an ED once, regardless of the intensity or duration of the visit. Count multiple ED visits on the same date of service as one visit. Identify ED visits using either of the following: An ED visit (ED Value Set). A procedure code (ED Procedure Code Value Set) with an ED place of service code (ED POS Value Set). Exclusions (required) Do not include ED visits that result in an inpatient stay (Inpatient Stay Value Set). When an ED visit and an inpatient stay are billed on separate claims, the visit results in an inpatient stay when the admission date for the inpatient stay occurs on the ED date of service or one calendar day after. An ED visit billed on the same claim as an inpatient stay is considered a visit that resulted in an inpatient stay. The measure does not include mental health or chemical dependency services. Exclude claims and encounters that indicate the encounter was for mental health or chemical dependency. Any of the following meet criteria: A principal diagnosis of mental health or chemical dependency (Mental and Behavioral Disorders Value Set). Psychiatry (Psychiatry Value Set). Electroconvulsive therapy (Electroconvulsive Therapy Value Set). Note This measure provides a reasonable proxy for professional ambulatory encounters. It is neither a strict accounting of all ambulatory resources nor an effort to be all-inclusive. Page 14 of 36

15 Ambulatory Care 3 Table AMB-1: Ambulatory Care Age Member Months < Unknown Total OUTPATIENT VISITS ED VISITS Visits/1,000 Visits/1,000 Member Age Visits Months Visits Member Months < Unknown Total Page 15 of 36

16 Ambulatory Care 4 Table AMB-2/3: Ambulatory Care Age Member Months < Unknown Total OUTPATIENT VISITS ED VISITS Visits/1,000 Visits/1,000 Age Visits Member Years Visits Member Years < Unknown Total Page 16 of 36

17 Inpatient Hospital Utilization 1 Inpatient Hospital Utilization (IHU) SUMMARY OF CHANGES TO HEDIS 2018 Added a note to clarify that Total Inpatient will not equal Surgery and Medicine sum if reporting using MS-DRGs. Clarified to round to ten decimal places using the.5 rule during the intermediate calculations of Expected events. Added steps 5 and 6 to the calculation of the PUCD risk weights to calculate covariance and total variance for each category. Removed the Risk Adjustment Weighting Process diagram. Added Total Variance as a data elements to Table IHU-B-2/3, Table IHU-C-2/3 and Table IHU-D-2/3. Description For members 18 years of age and older, the risk-adjusted ratio of observed to expected acute inpatient discharges during the measurement year reported by Surgery, Medicine and Total. Definitions Classification period PPD PUCD The year prior to the measurement year. Predicted probability of discharge. The predicted probability of a member having any discharge in the measurement year. Predicted unconditional count of discharge. The predicted unconditional count of discharges for members during the measurement year. Eligible Population Note: Members in hospice are excluded from the eligible population. Refer to General Guideline 20: Members in Hospice. Product lines Ages Continuous enrollment Allowable gap Anchor date Benefit Event/diagnosis Commercial, Medicare (report each product line separately). 18 and older as of December 31 of the measurement year. The measurement year and the year prior to the measurement year. No more than one gap in enrollment of up to 45 days during each year of continuous enrollment. December 31 of the measurement year. Medical. None. Page 17 of 36

18 Inpatient Hospital Utilization 2 Calculation of Observed Events Use the following steps to identify and categorize inpatient discharges. Step 1 Step 2 Identify all acute inpatient discharges during the measurement year. To identify acute inpatient discharges: 1. Identify all acute and nonacute inpatient stays (Inpatient Stay Value Set). 2. Exclude nonacute inpatient stays (Nonacute Inpatient Stay Value Set). 3. Identify the discharge date for the stay. Exclude discharges with: A principal diagnosis of mental health or chemical dependency (Mental and Behavioral Disorders Value Set). A principal diagnosis of live-born infant (Deliveries Infant Record Value Set). A maternity-related principal diagnosis (Maternity Diagnosis Value Set). A maternity-related stay (Maternity Value Set; Maternity MS-DRG Value Set). A mental health, chemical dependency or rehabilitation related stay (IPU Exclusions MS- DRG Value Set). Newborn care (Newborns/Neonates MS-DRG Value Set). Inpatient stays with a discharge for death. Step 3 Calculate total inpatient using all discharges identified after completing steps 1 and 2. Step 4 Identify surgery and medicine using MS-DRGs. For organizations that use DRGs, categorize each discharge as surgery or medicine. Surgery (Surgery MS-DRG Value Set). Medicine (Medicine MS-DRG Value Set). Note: If reporting using MS-DRGs, Total Inpatient will not equal the sum of Surgery and Medicine because DRGs for Principal Diagnosis Invalid as Discharge Diagnosis and Ungroupable are included in Total Inpatient, but are not included in surgery or medicine. If the organization does not use MS-DRGs, follow steps 5 6 to categorize discharges. Step 5 Step 6 Calculate surgery. Identify the surgery discharges (Surgery Value Set) from the total inpatient discharges (step 3). Calculate medicine. Categorize as medicine the discharges remaining after removing surgery (step 5) from total inpatient (step 3). Risk Adjustment Determination For each member in the eligible population, use the steps in the Utilization Risk Adjustment Determination section in the Guidelines for Risk Adjusted Utilization Measures to identify risk adjustment categories based on presence of comorbidities. Page 18 of 36

19 Inpatient Hospital Utilization 3 Risk Adjustment Weighting and Calculation of Expected Events Calculation of risk-adjusted outcomes (counts of discharges) uses predetermined risk weights generated by two separate regression models. Weights from each model are combined to predict how many discharges each member may have during the measurement year, given age, gender and presence or absence of a comorbid condition. Refer to the Risk Adjustment Weight Process diagram for an overview of the process. For each member in the eligible population, assign Predicted Probability of Discharge (PPD) risk weights. Calculate the PPD for each service utilization category: Surgery, Medicine, Total. Step 1 For each member with a comorbidity HCC category, link the PPD weights. For the Medicare product line, use the following tables: For Surgery: Use Table IHUS-MA-PPD-ComorbidHCC. For Medicine: Use Table IHUM-MA-PPD-ComorbidHCC. For Total: Use Table IHUT-MA-PPD-ComorbidHCC. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PPD-ComorbidHCC. For Medicine: Use Table IHUM-Comm-PPD-ComorbidHCC. For Total: Use Table IHUT-Comm-PPD-ComorbidHCC. Step 2 Link the age-gender PPD weights for each member. For the Medicare product line, use the following tables: For Surgery: Use Table IHUS-MA-PPD. For Medicine: Use Table IHUM-MA-PPD. For Total: Use Table IHUT-MA-PPD. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PPD. For Medicine: Use Table IHUM-Comm-PPD. For Total: Use Table IHUT-Comm-PPD. Step 3 Identify the base PPD risk weight for each member. For the Medicare product line, use the following tables: For Surgery: Use Table IHUS-MA-PPD. For Medicine: Use Table IHUM-MA-PPD. For Total: Use Table IHUT-MA-PPD. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PPD. For Medicine: Use Table IHUM-Comm-PPD. For Total: Use Table IHUT-Comm-PPD. Step 4 Step 5 Sum all PPD weights (HCC, age, gender, base weight) associated with the member for each category (Medicine, Surgery, Total). Calculate the predicted probability of having at least one discharge in the measurement year based on the sum of the weights for each member, for each category (Surgery, Medicine, Total), using the formula below. PPD = e ( PPD WeightsForEachMember) 1+e ( PPD WeightsForEachMember) Note: The risk adjustment tables will be released on November 1, 2017, and posted to Page 19 of 36

20 Inpatient Hospital Utilization 4 For each member in the eligible population, assign Predicted Unconditional Count of Discharge (PUCD) risk weights. Step 1 For each member with a comorbidity HCC Category, link the PUCD weights. If a member does not have any comorbidities to which a weight could be linked, assign a weight of 1. For Medicare product line, use the following tables: For Surgery: Use Table IHUS-MA-PUCD-ComorbidHCC. For Medicine: Use Table IHUM-MA-PUCD-ComorbidHCC. For Total: Use Table IHUT-MA-PUCD-ComorbidHCC. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PUCD-ComorbidHCC. For Medicine: Use Table IHUM-Comm-PUCD-ComorbidHCC. For Total: Use Table IHUT-Comm-PUCD-ComorbidHCC. Step 2 Link the PUCD age-gender weights for each member. For Medicare product line, use the following tables: For Surgery: Use Table IHUS-MA-PUCD. For Medicine: Use Table IHUM-MA-PUCD. For Total: Use Table IHUT-MA-PUCD. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PUCD. For Medicine: Use Table IHUM-Comm-PUCD. For Total: Use Table IHUT-Comm-PUCD. Step 3 Identify the base PUCD risk weight. For Medicare product line use the following tables: For Surgery: Use Table IHUS-MA-PUCD. For Medicine: Use Table IHUM-MA-PUCD. For Total: Use Table IHUT-MA-PUCD. For the commercial product line, use the following tables: For Surgery: Use Table IHUS-Comm-PUCD. For Medicine: Use Table IHUM-Comm-PUCD. For Total: Use Table IHUT-Comm-PUCD. Step 4 Calculate the predicted unconditional count of discharges in the measurement year, by multiplying all PUCD weights (HCC, age, gender and base weight) associated with the member for each category (Surgery, Medicine, Total). Use the following formula: PUCD = Base Weight * Age/gender Weight * HCC Weight Note: Multiply by each HCC associated with the member. For example, assume a member with HCC-2, HCC-10, HCC-47. The formula would be: PUCD = Base Weight * Age/gender Weight * HCC-2 * HCC-10 * HCC-47 Round intermediate calculations to 10 decimal places using the.5 rule. Page 20 of 36

21 Inpatient Hospital Utilization 5 Expected count of hospitalization Step 5 Step 6 Report the final member-level expected count of discharges for each category using the formula below. Round to four decimal places using the.5 rule and enter these values into the reporting table. Expected Count of Discharges = PPD x PUCD Use the formula below to calculate the covariance of the predicted outcomes for each category (i.e., gender, age group and type of hospital stay). CCCCCC = nn ii=1(pppppp mmmmmmmm(pppppp)) (PPPPPPPP mmmmmmmm(pppppppp)) nn 1 Use the formula below to calculate the variance for each category. nn TTTTTTTTTT VVVVVVVVVVVVVVVV = (PPPPPP PPPPPPPP) (1 PPPPPP) 2 2 CCCCCC + PPPPPP PPPPPPPP ii=1 Reporting: Number of Members in the Eligible Population The number of members in the eligible population for each age and gender group and the overall total. Enter these values into the reporting table (Table IHU-A-2/3). Reporting: Number of Observed Events The number of observed discharges within each age and gender group and the overall total for each category (Surgery, Medicine, Total). Reporting: Observed Discharges per 1,000 Members The number of observed discharges divided by the number of members in the eligible population, multiplied by 1,000 within each age and gender group and the overall total for each category (Surgery, Medicine, Total). Reporting: Number of Expected Events The number of expected inpatient discharges within each age and gender group and the overall total for each category (Surgery, Medicine, Total). Reporting: Expected Discharges per 1,000 Members The number of expected inpatient discharges divided by the number of members in the eligible population, multiplied by 1,000 within each age and gender group and the overall total for each category (Surgery, Medicine, Total). Reporting: Total Variance The variance (from Risk Adjustment Weighting and Calculation of Expected Events, PUCD, step 6) within each age and gender group and the overall total for each category (i.e., Surgery, Medicine and Total Inpatient). Page 21 of 36

22 Inpatient Hospital Utilization 6 Table IHU-A-2/3: Number of Members in the Eligible Population Age Sex Members Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male 85+ Female Total Male Total Female Total Page 22 of 36

23 Inpatient Hospital Utilization 7 Table IHU-B-2/3: Inpatient Discharges by Age and Risk Adjustment: Surgery Age Total Sex Observed Inpatient Discharges Observed Inpatient Discharges/ 1,000 Members Expected Inpatient Discharges Expected Inpatient Discharges/ 1,000 Members Total Variance (O/E) O/E Ratio (Observed Discharges/ Expected Discharges) Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Page 23 of 36

24 Inpatient Hospital Utilization 8 Table IHU-C-2/3: Inpatient Discharges by Age and Risk Adjustment: Medicine Age Total Sex Observed Inpatient Discharges Observed Inpatient Discharges/ 1,000 Members Expected Inpatient Discharges Expected Inpatient Discharges/ 1,000 Members Total Variance (O/E) O/E Ratio (Observed Discharges/ Expected Discharges) Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Page 24 of 36

25 Inpatient Hospital Utilization 9 Table IHU-D-2/3: Inpatient Discharges by Age and Risk Adjustment: Total Inpatient Age Total Sex Observed Inpatient Discharges Observed Inpatient Discharges/ 1,000 Members Expected Inpatient Discharges Expected Inpatient Discharges/ 1,000 Members Total Variance (O/E) O/E Ratio (Observed Discharges/ Expected Discharges) Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Page 25 of 36

26 Emergency Department Utilization 1 Emergency Department Utilization (EDU) SUMMARY OF CHANGES TO HEDIS 2018 Clarified how to identify an ED visit that resulted in an inpatient stay. Removed the AOD Rehab and Detox Value Set from the required exclusions (claims and encounters with a principal diagnosis of chemical dependency are excluded from the measure). Clarified to round to 10 decimal places using the.5 rule during the intermediate calculations of Expected events. Added steps 5 and 6 to the calculation of the PUCV risk weights to calculate covariance and total variance for each category. Removed the Risk Adjustment Weighting Process diagram. Added Total Variance as a data element to Table EDU-B-2/3. Description For members 18 years of age and older, the risk-adjusted ratio of observed to expected emergency department (ED) visits during the measurement year. Definitions Classification period PPV PUCV The year prior to the measurement year. Predicted probability of a visit. The predicted probability of a member having an emergency department visit in the measurement year. Predicted unconditional count of visits. The unconditional count of emergency department visits for members during the measurement year. Eligible Population Note: Members in hospice are excluded from the eligible population. Refer to General Guideline 20: Members in Hospice. Product lines Ages Continuous enrollment Allowable gap Anchor date Benefit Event/diagnosis Commercial, Medicare (report each product line separately). 18 and older as of December 31 of the measurement year. The measurement year and the year prior to the measurement year. No more than one gap in enrollment of up to 45 days during each year of continuous enrollment. December 31 of the measurement year. Medical. None. HEDIS 2018, Volume 2 Page 26 of 36

27 Emergency Department Utilization 2 Calculation of Observed Events Step 1 Count each visit to an ED once, regardless of the intensity or duration of the visit. Count multiple ED visits on the same date of service as one visit. Identify all ED visits during the measurement year using either of the following: An ED Visit (ED Value Set). A procedure code (ED Procedure Code Value Set) with an ED place of service code (ED POS Value Set). Do not include ED visits that result in an inpatient stay (Inpatient Stay Value Set). When an ED visit and an inpatient stay are billed on separate claims, the visit results in an inpatient stay when the admission date for the inpatient stay occurs on the ED date of service or one calendar day after. An ED visit billed on the same claim as an inpatient stay is considered a visit that resulted in an inpatient stay. Step 2 Exclude encounters with any of the following: A principal diagnosis of mental health or chemical dependency (Mental and Behavioral Disorders Value Set). Psychiatry (Psychiatry Value Set). Electroconvulsive therapy (Electroconvulsive Therapy Value Set). Risk Adjustment Determination For each member in the eligible population, use the steps in the Utilization Risk Adjustment Determination section in the Guidelines for Risk Adjusted Utilization Measures to identify risk adjustment categories based on presence of comorbidities. Risk Adjustment Weighting and Calculation of Expected Events Calculation of risk-adjusted outcomes (counts of ED visits) uses predetermined risk weights generated by two separate regression models. Weights from each model are combined to predict how many visits each member may have during the measurement year. Refer to the Risk Adjustment Weight Process diagram for an overview of the process. For each member in the eligible population, assign Predicted Probability of a Visit (PPV) risk weights. Step 1 Step 2 Step 3 Step 4 For each member with a comorbidity HCC Category, link the PPV weights. For the Medicare product line: Use Table EDU-MA-PPV-ComorbidHCC. For the commercial product line: Use Table EDU-Comm-PPV-ComorbidHCC. Link the age-gender PPV weights for each member using the following tables. For the Medicare product line: Use Table EDU-MA-PPV. For the commercial product line: Use Table EDU-Comm-PPV. Identify the base PPV risk weight for each member using the following tables. For the Medicare product line: Use Table EDU-MA-PPV. For the commercial product line: Use Table EDU-Comm-PPV. Sum all PPV weights associated with the member (HCC, age, gender, base weight). HEDIS 2018, Volume 2 Page 27 of 36

28 Emergency Department Utilization 3 Step 5 Calculate the predicted probability of each member having at least one visit based on the sum of the weights for each member using the formula below. PPV = ee ( PPV WeightsForEachMember) 1+ee ( PPV WeightsForEachMember) Note: The risk adjustment tables will be released on November 1, 2017, and posted to For each member in the eligible population, assign Predicted Unconditional Count of Visits (PUCV) risk weights. Step 1 Step 2 Step 3 Step 4 For each member with a comorbidity HCC Category, link the PUCV weights. If a member does not have any comorbidities to which weights can be linked, assign a weight of 1. For the Medicare product line: Use Table EDU-MA-PUCV-ComorbidHCC. For the commercial product line: Use Table EDU-Comm-PUCV- ComorbidHCC. Link the PUCV age-gender weights for each member using the following tables. For the Medicare product line: Use Table EDU-MA-PUCV. For the commercial product line: Use Table EDU-Comm-PUCV. Identify the base PUCV risk weight for each member using the following tables. For the Medicare product line: Use Table EDU-MA-PUCV. For the commercial product line: Use Table EDU-Comm-PUCV. Calculate the predicted unconditional count of visits in the measurement year, by multiplying all PUCV weights (HCC, age, gender and base weight). Use the following formula: PUCV = Base Weight * Age/gender Weight * HCC Weight Note: Multiply by each HCC associated with the member. For example, assume a member with HCC-2, HCC-10, HCC-47. The formula would be: PUCV = Base Weight * Age/gender Weight * HCC-2 * HCC-10 * HCC-47 Note: Round intermediate calculations to 10 decimal places using the.5 rule. Expected count of hospitalization Step 5 Step 6 Report the final member-level expected count of ED visits for each category using the formula below. Round to four decimal places using the.5 rule and enter these values into the reporting table. Expected Count of ED Visits = PPV x PUCV Use the formula below to calculate to calculate the covariance of the predicted outcomes for each category (i.e., gender and age group). CCCCCC = nn ii=1(pppppp mmmmmmmm(pppppp)) (PPPPPPPP mmmmmmmm(pppppppp)) nn 1 Use the formula below to calculate the variance for each category. nn TTTTTTTTTT VVVVVVVVVVVVVVVV = (PPPPPP PPPPPPPP) (1 PPPPPP) CCCCCC PPPPPP PPPPPPPP ii=1 HEDIS 2018, Volume 2 Page 28 of 36

29 Emergency Department Utilization 4 Reporting: Number of Members in the Eligible Population The number of members in the eligible population for each age and gender combination and enter these values into the reporting table (Table EDU-A-2/3). Reporting: Number of Observed Events The number of observed ED visits within each age and gender group and the overall total. Reporting: Observed Visits per 1,000 Members The number of observed ED visits divided by the number of members in the eligible population, multiplied by 1,000 within each age and gender group and the overall total. Reporting: Number of Expected Events The number of expected ED visits within each age and gender group and the overall total. Reporting: Expected Visits per 1,000 Members The number of expected ED visits divided by the number of members in the eligible population, multiplied by 1,000 within each age and gender group and the overall total. Reporting: Total Variance The variance (from Risk Adjustment Weighting and Calculation of Expected Events, PUCD, step 6) within each age and gender group and the overall total. Table EDU-A-2/3: Number of Members in the Eligible Population Age Sex Members Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male 85+ Female Total Male Total Female Total HEDIS 2018, Volume 2 Page 29 of 36

30 Emergency Department Utilization 5 Table EDU-B-2/3: Number of ED visits by Age and Risk Adjustment Age Total Sex Observed ED Visits Observed ED Visits/ 1,000 Members Expected ED Visits Expected ED Visits/ 1,000 Members Total Variance (O/E) O/E Ratio (Observed ED Visits/Expected ED Visits) Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total Male Female Total HEDIS 2018, Volume 2 Page 30 of 36

31 APPENDIX B Recommended VBP4P Measure Set for Measurement Year 2017 RED - Proposed MY 2017 changes compared to final MY 2016 measure set Commercial Value Based P4P Clinical Domain NQF# Approved Measurement Year 2017/ Reporting Year 2018 Measures Cardiovascular 2371 Annual Monitoring for Patients on Persistent Medications: ACEI/ARB, 1. Digoxin, and Diuretics 0541 Proportion of Days Covered by Medications: Renin Angiotensin 2. System (RAS) Antagonists Recommended for Public Payment Reporting* X X¹ Clinical Submission X Clinical Submission Proportion of Days Covered by Medications: Statins X Clinical Submission N/A 4. Statin Therapy for Patients With Cardiovascular Disease X X Clinical Submission Controlling Blood Pressure for People with Hypertension X X¹ Clinical Submission Diabetes Diabetes Care: Blood Pressure Control <140/90 mm Hg X X Clinical Submission Diabetes Care: HbA1c Control < 8.0% X X Clinical Submission N/A 8. Diabetes Care: Two HbA1c Tests X X Clinical Submission Diabetes Care: HbA1c Poor Control > 9.0% X X Clinical Submission Diabetes Care: Medical Attention for Nephropathy X X Clinical Submission N/A 11. Optimal Diabetes Care - Combination X X¹ Clinical Submission 0541 Proportion of Days Covered by Medications: Oral Diabetes 12. Medications X Clinical Submission N/A 13. Statin Therapy for Patients With Diabetes X X Clinical Submission Diabetes Care: Eye Exam Testing Testing Clinical Submission Musculoskeletal Use of Imaging Studies for Low Back Pain X X¹ Clinical Submission Prevention & Screening Breast Cancer Screening X X Clinical Submission Chlamydia Screening in Women X X Clinical Submission Childhood Immunization Status: Combination 10 X X Clinical Submission Colorectal Cancer Screening X X Clinical Submission Cervical Cancer Screening X X Clinical Submission N/A 21. Cervical Cancer Overscreening X X Clinical Submission Human Papillomavirus Vaccine for Female Adolescents Human Papillomavirus Vaccine for Male Adolescents Immunizations for Adolescents: Combination 2 (meningococcal, Tdap, 22. HPV for Adolescents) X X Clinical Submission Respiratory Asthma Medication Ratio X X Clinical Submission Appropriate Testing for Children With Pharyngitis X X Clinical Submission Appropriate Treatment for Children with Upper Respiratory Infection Data Source Avoidance of Antibiotic Treatment of Adults with Acute Bronchitis X X¹ Clinical Submission September 2017 Page 31 of 36

32 APPENDIX B Clinical Domain (Continued) Advancing Care Information Domain Value Based P4P Patient Experience Domain Value Based P4P Resource Use Domain Payment Baseline Testing Recommended VBP4P Measure Set for Measurement Year 2017 NQF# RED - Proposed MY 2017 changes compared to final MY 2016 measure set Approved Measurement Year 2017/ Reporting Year 2018 Measures Recommended for Public Payment Reporting* Data Source Behavioral Health & Substance Use N/A 26. Use of Opioids at High Dosage Testing Testing HP Clinical Submission N/A 27. Concurrent Use of Opioids and Benzodiazepines Testing Testing HP Clinical Submission Other N/A 28. Encounter Rate by Service Type Info Only HP Clinical Submission Clinical Domain Weighting 60% N/A 29. Controlling High Blood Pressure e-measure X PO Clinical Submission 30. Screening for Clinical Depression and Follow-up e-measure X PO Clinical Submission Advancing Care Information Domain Weighting 10% N/A 31. Provider Communication Composite X N/A PAS N/A 32. Access Composite X N/A PAS N/A 33. Care Coordination Composite X N/A PAS N/A 34. Office Staff Composite X N/A PAS N/A Overall Ratings of Care Composite (Rating of Doctor & Rating of All 35. Healthcare) X N/A PAS Patient Experience Domain Weighting 30% All-Cause Readmissions X X¹ HP Clinical Submission N/A Inpatient Utilization: Acute Care Discharges, Bed Days, Average Length 37. of Stay X HP Submission N/A 38. Maternity Discharges, Average Length of Stay Info Only HP Submission N/A 39. Emergency Department Visits X HP Submission N/A 40. Outpatient Procedures Utilization - Percent Done in Preferred Facility X HP Submission Generic Prescribing: Overall and Antidepressants, Antimigraine, Anti- Ulcer, Cardiac - Hypertension and Cardiovascular, Nasal Steroids, N/A 41. Statins, Diabetes, Anxiety/Sedation - Sleep Aids N/A 42. Frequency of Selected Procedures - Angioplasty, Back Surgery, Bariatric Weight Loss Surgery, Cardiac Catheterization, Carotid Endarterectomy, CABG, Total Hip Replacement, Total Knee Replacement, Hysterectomy, Tonsillectomy, Cholecystectomy, Prostatectomy, Mastectomy, Lumpectomy X HP Submission HP Submission N/A 43. Total Cost of Care X X HP Submission Resource Use Domain Weighting Info Only Value Based P4P / Shared Savings = Indicates that the measure is in its first year of reporting and will not be used for payment this year (because it is not possible to assess relative improvement). It is intended for payment next year. = Indicates that the measure is being tested with the intent of adding it to the measure set next year, but will not be used for payment or public reporting this year. Public Reporting * 1 N/A = In general, The Office of the Patient Advocate (OPA) reports all measures that are available for public reporting; final decisions are made when baseline data becomes available for analysis. For measures in baseline year, OPA will not publicly report the measure but will consider whether the measure will be included in the following year's public reporting and whether it will be included in the star ratings or as a stand-alone measure. = Indicates the measure is reported on the OPA Report Card but not included in a topic star rating or the Medical Group Provides Recommended Care star rating. = The Patient Experience questions are collected and administered by California Healthcare Performance Information System (CHPI), including decisions about public reporting. Data Source Clinical Submission PAS HP Submission = Self-reporting POs and health plans submit audited files of numerator, denominator, and rate for these measures unless otherwise specified. = The Patient Assessment Survey is a CG-CAHPs survey administered by CHPI. = Health plans submit eligibility, claims/encounter, and cost data to Truven Health Analytics to run these measures. September 2017 Page 32 of 36

33 APPENDIX B Medicare Stars Measure Set for Measurement Year 2017 RED - Proposed MY 2017 changes compared to final MY 2016 measure set Medicare Stars Measures Data Source Clinical Submission Info Only NQF # Recommended for Public Payment Reporting Cardiovascular 0541 Proportion of Days Covered by Medications: Renin Angiotensin 1. System (RAS) Antagonists X Clinical Submission Proportion of Days Covered by Medications: Statins X Clinical Submission N/A 3. Statin Therapy for Patients with Cardiovascular Disease Baseline Clinical Submission Diabetes Diabetes Care: HbA1c Poor Control > 9.0% X Clinical Submission Diabetes Care: Medical Attention for Nephropathy X Clinical Submission Diabetes Care: Eye Exam X Clinical Submission 0541 Proportion of Days Covered by Medications: Oral Diabetes 7. Medications X Clinical Submission Statin Use in Persons with Diabetes Baseline Clinical Submission Musculoskeletal 0054 Disease Modifying Anti-Rheumatic Drug Therapy for Rheumatoid 9. Arthritis X Clinical Submission Osteoporosis Management in Women Who Had a Fracture X Clinical Submission Prevention N/A 11. Adult BMI Assessment X Clinical Submission Breast Cancer Screening: Ages X Clinical Submission Colorectal Cancer Screening: Ages X Clinical Submission N/A 14. High Risk Medication Info Only Clinical Submission Appropriate Resource Use All-Cause Readmissions X HP Clinical Submission Other Approved Measurement Year 2017/ Reporting Year 2018 Measures Data Source N/A 16. Encounter Rate by Service Type Info Only Clinical Submission = Self-reporting POs and health plans submit audited files of numerator, denominator, and rate for these measures. The All-Cause Readmission measure is only submitted by health plans. = CMS cut points required for calculating star ratings not available September 2017 Page 33 of 36

34 APPENDIX C Recommended VBP4P Measure Set for Measurement Year 2018 RED - Proposed MY 2018 changes compared to final MY 2017 measure set Commercial Value Based P4P Clinical Domain NQF# Approved Measurement Year 2018/ Reporting Year 2019 Measures Cardiovascular Annual Monitoring of Persistent Medications Proportion of Days Covered by Medications: Renin Angiotensin System (RAS) Antagonists Recommended for Public Payment Reporting* Data Source X X Clinical Submission Proportion of Days Covered by Medications: Statins X X Clinical Submission N/A 3. Statin Therapy for Patients With Cardiovascular Disease X X Clinical Submission Controlling Blood Pressure for People with Hypertension X X¹ Clinical Submission Diabetes Diabetes Care: Blood Pressure Control <140/90 mm Hg X X Clinical Submission Diabetes Care: HbA1c Control < 8.0% X Clinical Submission Diabetes Care: Two HbA1c Tests Diabetes Care: HbA1c Poor Control > 9.0% X X Clinical Submission Diabetes Care: Medical Attention for Nephropathy X X Clinical Submission Diabetes Care: Eye Exam Baseline Baseline Clinical Submission Optimal Diabetes Care: Combination (Hba1c Control, 2 HbA1c tests, BP Control, Med Attn. Nephropathy) Baseline Baseline 0541 Proportion of Days Covered by Medications: Oral Diabetes 10. Medications X X Clinical Submission N/A 11. Statin Therapy for Patients With Diabetes X X Clinical Submission Musculoskeletal Use of Imaging Studies for Low Back Pain X X¹ Clinical Submission Prevention & Screening Breast Cancer Screening X X Clinical Submission Chlamydia Screening in Women X X Clinical Submission Childhood Immunization Status: Combination 10 X X Clinical Submission Colorectal Cancer Screening X X Clinical Submission Cervical Cancer Screening X X Clinical Submission N/A 18. Cervical Cancer Overscreening X X Clinical Submission 1407 Immunizations for Adolescents: Combination 2 (meningococcal, Tdap, 19. HPV for Adolescents) X X Clinical Submission Respiratory Asthma Medication Ratio X X Clinical Submission Appropriate Testing for Children With Pharyngitis X X Clinical Submission Avoidance of Antibiotic Treatment of Adults with Acute Bronchitis X X¹ Clinical Submission September 2017 Page 34 of 36

35 APPENDIX C Clinical Domain (Continued) Advancing Care Information Domain Value Based P4P Patient Experience Domain Value Based P4P Resource Use Domain Payment Baseline Testing Recommended VBP4P Measure Set for Measurement Year 2018 NQF# RED - Proposed MY 2018 changes compared to final MY 2017 measure set Approved Measurement Year 2018/ Reporting Year 2019 Measures Recommended for Public Payment Reporting* Data Source Behavioral Health & Substance Use N/A 23. Use of Opioids at High Dosage Baseline Baseline HP Clinical Submission N/A 24. Concurrent Use of Opioids and Benzodiazepines Baseline Baseline HP Clinical Submission Other N/A 25. Encounter Rate by Service Type Info Only HP Clinical Submission Clinical Domain Weighting 60% N/A 26. Controlling High Blood Pressure e-measure X PO Clinical Submission Screening for Clinical Depression and Follow-up e-measure X PO Clinical Submission Advancing Care Information Domain Weighting 10% N/A 28. Provider Communication Composite X N/A PAS N/A 29. Access Composite X N/A PAS N/A 30. Care Coordination Composite X N/A PAS N/A 31. Office Staff Composite X N/A PAS N/A Overall Ratings of Care Composite 32. (Rating of Doctor & Rating of All Healthcare) X N/A PAS Patient Experience Domain Weighting 30% All-Cause Readmissions X X¹ HP Clinical Submission N/A Inpatient Utilization: Acute Care Discharges, Bed Days, Average Length 34. of Stay X HP Submission N/A 35. Maternity Discharges, Average Length of Stay Info Only HP Submission N/A 36. Emergency Department Visits X HP Submission N/A 37. Outpatient Procedures Utilization - Percent Done in Preferred Facility X HP Submission N/A 38. Specialty Pharmacy TBD Under consideration HP Submission Generic Prescribing: Overall and Antidepressants, Antimigraine, Anti- 39. Ulcer, Cardiac - Hypertension and Cardiovascular, Nasal Steroids, X HP Submission Statins, Diabetes N/A Frequency of Selected Procedures - Angioplasty, Back Surgery, Bariatric Weight Loss Surgery, Cardiac Catheterization, Carotid 40. Endarterectomy, CABG, Total Hip Replacement, Total Knee Replacement, Hysterectomy, Tonsillectomy, Cholecystectomy, Prostatectomy, Mastectomy, Lumpectomy Info Only HP Submission N/A 41. Total Cost of Care (incl. service categories) X X (overall TCC only) HP Submission Resource Use Domain Weighting Value Based P4P / Shared Savings = Indicates that the measure is in its first year of reporting and will not be used for payment this year (because it is not possible to assess relative improvement). It is intended for payment next year. = Indicates that the measure is being tested with the intent of adding it to the measure set next year, but will not be used for payment or public reporting this year. Public Reporting * 1 N/A = In general, The Office of the Patient Advocate (OPA) reports all measures that are available for public reporting; final decisions are made when baseline data becomes available for analysis. For measures in baseline year, OPA will not publicly report the measure but will consider whether the measure will be included in the following year's public reporting and whether it will be included in the star ratings or as a stand-alone measure. = Indicates the measure is reported on the OPA Report Card but not included in a topic star rating or the Medical Group Provides Recommended Care star rating. = The Patient Experience questions are collected and administered by California Healthcare Performance Information System (CHPI), including decisions about public reporting. Data Source Clinical Submission PAS HP Submission = Self-reporting POs and health plans submit audited files of numerator, denominator, and rate for these measures unless otherwise specified. = The Patient Assessment Survey is a CG-CAHPs survey administered by CHPI. = Health plans submit eligibility, claims/encounter, and cost data to Truven Health Analytics to run these measures. September 2017 Page 35 of 36