Diabetes

Chronic Condition Clinical Advisory Group
Value Based Payment Recommendation Report

  • Report is also available in Portable Document Format (PDF)

NYS Medicaid Value Based Payment

September 2016


Contents
Introduction
  • Delivery System Reform Incentive Payment (DSRIP) Program and Value Based Payment (VBP) Overview
Diabetes Clinical Advisory Group (CAG)
  • CAG Overview
Recommendation Report Overview and Components
  • Diabetes Playbook
  • Diabetes Outcome Measure Summary
Diabetes Playbook
Playbook Overview – Diabetes
Attachment A: Glossary
Attachment B: Workbooks with Codes for the Diabetes Episode
Diabetes Clinical Advisory Group (CAG)
  • Quality Measure Recommendations
Diabetes Quality Measure Summary
Introduction
  • Selecting Quality Measures: Criteria used to Consider Relevance
Categorizing and Prioritizing Quality Measures
Diabetes CAG Recommended Quality Measures – Category 1 and 2
CAG Categorization and Discussion of Measures
Appendix A:
  • Meeting Schedule

Introduction

Delivery System Reform Incentive Payment (DSRIP) Program and Value Based Payment (VBP) Overview

The New York State (NYS or the State) DSRIP program aims to fundamentally restructure New York State´s healthcare delivery system, reducing avoidable hospital use by 25%, and improving the financial sustainability of New York State´s safety net.

To further stimulate and sustain this delivery reform, at least 80 - 90% of all payments made from Managed Care Organizations (MCOs) to providers will be captured within VBP arrangements by 2020. The goal of converting to VBP arrangements is to develop a sustainable system, which incentivizes value over volume. The Centers for Medicare & Medicaid Services (CMS) has approved the State´s multiyear VBP Roadmap, which details the menu of options and different levels of VBP that the MCOs and providers can select.

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Diabetes Episode Clinical Advisory Group (CAG)

CAG Overview

For many VBP arrangements, a subpopulation or defined set of conditions may be contracted on an episodic/bundle basis. Clinical Advisory Groups (CAGs) have been formed to review and facilitate the development of each subpopulation or bundle. Each CAG comprises leading experts and key stakeholders from throughout New York State, often including representatives from providers, universities, State agencies, medical societies, and clinical experts from health plans.

The Diabetes Episode CAG held a series of two meetings throughout the State and discussed key components of the Diabetes Episode VBP arrangement, including bundle definition, risk adjustment, and the Diabetes Episode bundle outcome measures. In order to help ensure a comprehensive discussion that captured unique attributes specific to Diabetes Episode and as well as areas of overlap with chronic heart disease, key stakeholders in the area of Diabetes Episode leveraged the chronic heart disease CAG to continue the discussion focusing on diabetes. For a full list of meeting dates, and an overview of discussions, please see the Appendix A at the end of the Quality Measure Summary.

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Recommendation Report Overview & Components

The following report contains two key components:

Diabetes Episode Playbook

  1. The playbook provides an overview of the episode definition and clinical descriptions, including ICD-9 and ICD-10 codes.

Diabetes Episode Outcome Measure Summary

  1. The outcome measure summary provides a description of the criteria used to determine relevancy, categorization, and prioritization of outcome measures, as well as a listing of the recommended outcome measures.
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Diabetes Playbook

Diabetes Episode Definition


Playbook Overview – Diabetes

New York State´s VBP Roadmap1 describes how the State will transition 80 – 90% of all payments from MCOs to providers from Fee for Service (FFS) to Value Based Payments. "Bundles" or "episodes"2 group together the wide range of services performed for a patient with a specific condition. Episodes only include those services that are relevant to the condition, including services that are routine and typical for the care of the condition. The episode also takes into account services that are required to manage complications that could potentially occur during the course and care of the condition. Episodes open with a claim carrying a "trigger code." Sometimes a confirmatory claim is required in addition to the initial trigger code to confirm an episode exists. Once the episode is opened, it creates a time window where all relevant claims are attributed. Thus, an episode of care is patient–centered and time–delimited. It can be considered as a unit of accounting for budgeting purposes, unit of care for contracting purposes, and a unit for accountability for quality measurement purposes.

New York State uses the HCI3 (Prometheus)–bundled payment methodology, including the standard episode definitions to maximize compatibility and consistency within the State and nationally. More information on how the episodes are developed is available on HCI3´s Web site.3 The HCI3–bundled payment methodology is also referred to as "the grouper."

This playbook describes the Diabetes Episode (Asthma Episode and COPD Episode). The table below provides an overview of the sections in this playbook.

Section Short Description
Description of Episode Details on the Diabetes Episode, including episode triggers and time lines, covered services, exclusions, and potentially avoidable complications
Attachment A: Glossary List of all important definitions
Attachment B: Workbooks with Codes for the Diabetes Episode Overview of all diabetes specific ICD–9 codes as well as their cross–walk to ICD–10 codes
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Description of Episode – Diabetes

This episode targets Medicaid–only members who have diabetes.

How is a Diabetes Episode triggered?

trigger

The Diabetes Episode is initially triggered by either (1) an inpatient claim with diabetes as the principal diagnosis, or (2) an outpatient or professional billing claim with an evaluation and management (E&M) service listing diabetes as the diagnosis. The confirming trigger must adhere to the same parameters as the initial trigger and follow at least 30 days after the initial trigger.4

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Which services are included in the Diabetes Episode?

The Diabetes Episode included all services (inpatient services, outpatient services, ancillary, laboratory, radiology, pharmacy, and professional billing services) related to the care for diabetes.4 The visual below provides an example of the services that are/are not included in an episode. The episode includes all care related to that episode, while it excludes encounters where services are provided for unrelated care as defined by the diagnoses (see crossed out services in the example below).

clinical logic for diabetes
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What are the exclusion criteria for the Diabetes Episode?

Some episodes have specific exclusion criteria; these are either exclusions from the episode based on clinical reasons or exclusions from eligibility for Medicaid. Episodes might be excluded from analysis if they are incomplete due to:

  • Administrative Exclusion: Incomplete set of claims within the episode time window due to coverage/enrollment gap or lack of episode completion.
  • Age: The Diabetes Episode excludes Medicaid members who are younger than 5 or are 65 years and older.
  • Cost Upper and Lower Limit: To create adequate risk models, individual episodes where the episode cost is below the first percentile or higher than the ninety–ninth percentile are excluded.
  • Coverage Gap: For the Diabetes Episode, continuous member/patient enrollment eligibility is checked for the episode period. If a patient has any enrollment gap during an episode with an episode window 90 days or less or a gap greater than 30 days during episodes with episode window greater than 90 days, then the episode is flagged as not meeting the coverage/enrollment gap criteria.
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What is the timeline for a Diabetes Episode?

Starting from the moment the episode is triggered, there is a 30–day look–back period for care related to diabetes. As diabetes are a chronic episodes, the episodes can be open until the patient is deceased. For reporting purposes, the episode can be assessed on a yearly rolling basis. However, if there are no services related to this episode in a given year, then the episode will not be triggered. If the patient becomes deceased, the date of death marks the end of the episode.

trigger
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Which potentially avoidable complications (PACs) are related to the Diabetes Episode?

The services within an episode are assigned as either typical or as potentially avoidable complications. In order to be considered a potentially avoidable complication, or PAC, services must include complication diagnosis codes that either (1) directly relate to the index condition or (2) indicate a failure in patient safety. PACs can occur as hospitalizations, emergency room visits, and professional services related to these hospitalizations, but they can also occur in outpatient settings. As the term indicates, a PAC does not mean that something has gone wrong: it means that a type of care was delivered related to a clinical event that may have been preventable. As such, the goal is not to reduce PACs to zero, but to reduce PACs as much as possible, and to benchmark the risk-adjusted occurrences of these PACs between VBP contractors and MCOs.

Additionally, from a quality perspective, PACs can be identified by failure to comply with patient safety guidelines, such as HACs (CMS defined Hospital–Acquired Conditions) and PSIs (Agency for Healthcare Research and Quality (AHRQ) defined Patient Safety Indicators). Likewise, failure to avoid other situations related to patient safety (e.g. avoidable infection or drug interaction) may also be considered a PAC.

The top 10 PACs (based on cost) related to diabetes in NYS Medicaid are:

  1. Diabetes, poor control
  2. HAC: Manifestations of poor glycemic control
  3. Sepsis
  4. Cellulitis, skin infection
  5. Stroke
  6. Pneumonia
  7. Urinary tract infection
  8. Acute myocardial infarction
  9. Hypotension/syncope
  10. Acute pancreatitis, Pseudocyst
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Which episodes roll up under the Diabetes Episode?

The HCI3 grouper looks at episodes at different levels. At level 1, all episodes are analyzed individually. At higher levels (2 to 5), different episodes are rolled up under one specific episode as PACs.

Which episodes roll up under the Diabetes Episode?
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Which subtypes of the Diabetes Episode exist?

"Subtypes" are subgroupings that could help stratify a population for analytic purposes and are used for functions such as risk adjustment.

A few examples of common subtypes for the diabetes episode are:

  • Diabetes mellitus with neurologic manifestations
  • Diabetes mellitus with ophthalmic manifestations
  • Diabetes mellitus with peripheral circulatory disorders
  • Diabetes mellitus with renal manifestations
  • Type I diabetes

The overview of all subtypes of the diabetes episode can be found in Attachment B.

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How is the risk adjustment of the Diabetes Episode done?

Separate risk adjustment models are created for "typical" services and for PACs. Risk factors that are taken into account include patient demographics, pre–existing co–morbidities, and subtypes.5 Using these factors, the episode grouper calculates an "expected" total cost that is unique for every individual patient. The difference between the actual cost and the expected cost determines the savings/losses incurred in the care for that individual patient. 6

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Attachment A: Glossary

  • Complication Code: These are ICD–9 and ICD–10 diagnosis codes, which are used to identify a Potentially Avoidable Complication (PAC) services during the episode time window.
  • Diagnosis Codes: These are unique codes based on ICD–9 (or ICD–10) that are used to group and categorize diseases, disorders, symptoms, etc. These identify clinically–related inpatient, outpatient, and professional typical services to be included in the episode in conjunction with the relevant procedure codes. These may include trigger codes, signs and symptoms and other related conditions and are used to steer services into an open episode.
  • Episode: An episode of medical care that spans a predefined period of time for a particular payer–provider–patient triad, as informed by clinical practice guidelines and/or expert opinion. The episode starts after there is a confirmed trigger for that episode (e.g. a diagnosis).
  • Episode Type: Episodes are grouped into four main categories:
    • Chronic Condition – care for a chronic medical condition.
    • Acute Condition – care for an acute medical condition.
    • Procedural (Inpatient (IP) or Outpatient (OP)) – a surgical procedure and its follow–up care; the procedure may treat a chronic or acute condition.
    • Other Condition – care for pregnancy and cancer episodes.
  • In addition, there is one generic episode type included:
    • System–Related Failures – inpatient and follow–up care for a condition caused by a systemic patient–safety failure.
  • Exclusions: Some episodes have specific exclusion criteria, which are either based on clinical or administrative (eligibility/coverage) criteria.
  • ICD–10 Codes: The ICD–9 diagnosis codes and the ICD–9 procedure codes for the above categories of codes have been cross–walked to ICD–10 codes leveraging the open–source GEM (Generalized Equivalence mapping) tables published by CMS.
  • Index Condition: The index condition refers to the specific episode that the PAC relates to.
  • Initial and Confirming Triggers: An initial trigger initiates an episode based on diagnosis and / or procedure codes found on institutional or non–institutional claims. For many episodes, a second trigger, the confirming trigger, is necessary to actually trigger the episode. Sometimes an episode itself could serve as a trigger for another episode, e.g., pregnancy episode in delivery episode.
  • Clinical Association: HCI3´s PROMETHEUS Analytics© allows episodes to be connected to one another based on clinical relevance. For any individual patient, conditions and treatments, all of which trigger different episodes, are often related to one another from a clinical perspective. Episodes can be linked together for the analysis of their costs as either typical or complication.
  • Look–Back & Look–Forward: From the point at which an episode is triggered, episode costs / volume are evaluated within the associated time window for a predetermined number of days before and after the trigger date. Costs, volume, and other episode components that fall within this range are captured within the episode.
  • Pharmacy Codes: These are codes used to identify relevant pharmacy claims to be included in the episode. HCI3´s PROMETHEUS Analytics© groups pharmacy NDC codes into higher categories using the National Library of Medicine´s open–source RxNorm system of drug classification.
  • Potentially Avoidable Complication (PAC): An episode contains services that are assigned as either typical or as potentially avoidable complications. In order to be considered a potentially avoidable complication, or PAC, services must include complication diagnosis codes that either (1) directly relate to the index condition or (2) indicate a failure in patient safety. PACs can occur as hospitalizations, emergency room visits, and professional services related to these hospitalizations, but they can also occur in outpatient settings. As the term indicates, a PAC does not mean that something has gone wrong: it means that a type of care was delivered related to a clinical event that may have been preventable. As such, the goal is never to reduce PACs to zero, but to reduce PACs as much as possible, and to benchmark the risk–adjusted occurrences of these PACs between VBP contractors and MCOs.

    Additionally, PACs can be identified by failure to comply with patient safety guidelines, such as HACs (CMS defined Hospital–Acquired Conditions) and PSIs (Agency for Healthcare Research and Quality (AHRQ) defined Patient Safety Indicators). Likewise, failure to avoid other situations related to patient safety (e.g. avoidable infection or drug interaction) may also be considered a PAC.
  • Procedure Codes: These are codes used to identify clinically–related services to be included in the episode in conjunction with the typical diagnosis codes. These include CPT, HCPCS, and ICD–9 and ICD–10 procedure codes.
  • Roll–Ups: Some episodes are associated with each other through HCI3´s PROMETHEUS Analytics© clinical logic and grouped under an ´umbrella´ episode, including the grouped episode´s costs/volume.
  • Subtypes (code): Episodes often have subtypes or variants, which are useful to adjust for the severity of that episode, and reduce the need to have multiple episodes of the same type.
  • Time–Window: This defines the time that an episode is open. It includes the trigger event, a look–back period and a look–forward period and could be extended based on rules and criteria.
  • Trigger Code: A trigger code is the diagnosis or procedure code indicating the condition in question is present or procedure in question has occurred. Trigger codes are used to open new episodes and assign a time window for the start and end dates of each episode (depending on the episode type). Trigger codes can be ICD–9 or ICD–10 diagnosis or procedure codes, CPT or HCPCS codes, and could be present on an inpatient facility, outpatient facility, or professional claim.
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Attachment B: Workbook with Codes for the Diabetes Episode

The file below includes all ICD–9 diabetes specific codes

Diabetes: ICD–9 codes

The files below include all ICD–10 diabetes specific codes.

(Coming Soon)

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Diabetes Quality Measure Summary


Diabetes Clinical Advisory Group (CAG)

Quality Measure Recommendations

Introduction

Over the course of two meetings, the Diabetes Episode CAG reviewed, discussed, and provided feedback on the proposed Diabetes Episode Episodes (diabetes) to be used to inform VBP contracting for levels one through three. Both episodes concern lung–related conditions and include significant overlap of quality measures that are relevant for several conditions simultaneously. To help ensure a comprehensive discussion that captured both unique attributes specific to each bundle as well as areas of overlap (such as quality measures), one Diabetes Episode CAG was assembled and the outcomes are included here within one comprehensive document.

A key element of these discussions was the review of current, existing, and new quality measures used to measure the quality of care related to the diabetes bundle. The chronic heart and diabetes joint CAG discussed clinically relevant and feasible quality measures for diabetes. This document summarizes the discussion of the CAG and their categorization of quality measures.7

Selecting quality measures: Criteria used to consider relevance:8

In reviewing potential quality measures for utilization as part of a VBP arrangement, a number of key criteria have been applied across all Medicaid member subpopulations and disease bundles. These criteria, and examples of their specific implications for the Diabetes Episode VBP arrangement, are the following:

Clinical relevance

Focused on key outcomes of integrated care process
i.e. outcome measures (postpartum depression) are preferred over process measures (screening for postpartum depression); outcomes of the total care process are preferred over outcomes of a single component of the care process (e.g. the quality of one type of professional´s care)

For process measures: crucial evidence–based steps in integrated care process that may not be reflected in the patient outcomes measured
i.e. focus on postpartum contraceptive care is key but will not be captured in outcomes of current maternity episode

Existing variability in performance and/or possibility for improvement
i.e. blood pressure measurement during pregnancy is unlikely to be lower than >95% throughout the State

Reliability and validity

Measure is well established by reputable organization
By focusing on established measures (owned by e.g. NYS Office of Patient Quality and Safety (OQPS), endorsed by the National Quality Forum (NQF), Healthcare Effectiveness Data and Information Set (HEDIS) measures and/or measures owned by organizations such as the Joint Commission), the validity and reliability of measures can be assumed to be acceptable.

Outcome measures are adequately risk–adjusted
i.e. measuring ´% preterm births´ without adequate risk adjustment makes it impossible to compare outcomes between providers

Feasibility

Claims–based measures are preferred over non–claims based measures (clinical data, surveys)
i.e. ease of data collection data is important and measure information should not add unnecessary burden for data collection

When clinical data or surveys are required, existing sources must be available
i.e. the vital statistics repository (based on birth certificates) is an acceptable source, especially because OQPS has already created the link between the Medicaid claims data and this clinical registry

Data sources preferably are patient–level data
Measures that require random samples (e.g. sampling patient records or using surveys) are less ideal because they do not allow drill–down to patient level and/or adequate risk–adjustment, and may add to the burden of data collection. An exception is made for such measures that are part of DSRIP/QARR.

Data sources must be available without significant delay
i.e. data sources should not have a lag longer than the claims–based measures (which have a lag of six months). This is an issue with the vital statistics repository, for example, which have a one year lag (at least for the NYC data).

Meaningful and actionable to provider improvement in general

Measures should not only be related to the goals of care, but also something the provider can impact or use to change care.

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Categorizing and prioritizing quality measures

Based on the above criteria, the CAG discussed the quality measures in the framework of three categories:

  • Category 1 – Category 1 comprises approved quality measures that are felt to be clinically relevant, reliable, valid, and feasible.
  • Category 2 – Category 2 quality measures were felt to be clinically relevant, valid, and probably reliable, but where the feasibility could be problematic. These quality measures will likely be investigated during the 2016 or 2017 pilots but would likely not be implementable in the immediate future.
  • Category 3 – Category 3 measures were decided to be insufficiently relevant, valid, reliable, and/or feasible.

Ultimately, the use of these measures, particularly in Category 1 and 2 will be developed and further refined during the 2016 (and possibly 2017 pilots). The CAG will be re-assembled on a yearly basis during at least 2016 and 2017 to further refine the Category 1 and 2 measures.

The HCI3 grouper creates condition–specific scores for Potentially Avoidable Complications (PACs) for each condition. The ´percentage of total episode costs that are PACs is a useful measure to look for potential improvements; it cannot be interpreted as a quality measure. PAC counts however, can be considered clinically relevant and feasible outcome measures.

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Diabetes CAG Recommended Quality Measures – Category 1 and 2

  # Measure Measure Steward/Source
Category 1 1 Comprehensive Diabetes Care: Blood Pressure Control (<140/90 mm Hg)* National Committee for Quality Assurance
2 Comprehensive Diabetes Care: Medical Attention for Nephropathy* National Committee for Quality Assurance
3 Comprehensive Diabetes Care: Hemoglobin A1c (HbA1c) Control (<8.0%)* National Committee for Quality Assurance
4 Comprehensive Diabetes Care: Hemoglobin A1c (HbA1c) Poor Control (>9.0%)* National Committee for Quality Assurance
5 Comprehensive Diabetes Care: Eye Exam (retinal) performed* National Committee for Quality Assurance
6 Diabetes: Foot Exam* National Committee for Quality Assurance
7 Smoking Cessation discussed and documented American Diabetes Association
8 Depression screening (PHQ2 or 9) annually American Diabetes Association
9 Comprehensive Diabetes screening – All Four Tests

(HbA1c, lipid profile, dilated eye exam, nephropathy monitor)
National Committee for Quality Assurance
10 Diabetes Short–Term Complications Admission Rate (PQI 01) Agency for Healthcare Research and Quality
Category 2 11 Optimal Diabetes Care (Composite Measure) Minnesota Community Measurement
12 BMI/Nutrition Counseling American Diabetes Association
13 Adherence to Statins for Individuals with Diabetes Mellitus* Centers for Medicare & Medicaid Services
14 On ACEI/ARB if hypertension or nephropathy American Diabetes Association
15 Proportion of patients with a chronic condition that have a potentially avoidable complication during a calendar year* Bridges to Excellence
16 Rate of Lower–Extremity Amputation Among Patients With Diabetes (PQI 16) * Agency for Healthcare Research and Quality
*= NQF Endorsed
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CAG categorization and discussion of measures

Topic # Quality Measure (* = NQF Endorsed) Type of Measure Measure Steward/ Source DSRIP QARR HEDIS Data Required Quality Measure Categorization & Notes
Medicaid Claims Data Clinical Data 9 Category Notes
Prevention 1 Comprehensive Diabetes Care: Blood Pressure Control (<140/90 mm Hg) * Outcome National Committee for Quality Assurance   X X Yes Yes 1 The CAG members agreed that this is an essential measure. This is a chart review measure but is already being used by QARR and can be captured with current procedural terminology (CPT) codes. According to NCQA policy update, related to diabetes and blood pressure control < 140/90 mm Hg, CPT codes exist for this measure and should exist in claims data.

http://www.ncqa.org/portals/0/PolicyUpdates/HEDIS%20Technical%20Updates/09_CD C_Spec.pdf
Prevention 2 Comprehensive Diabetes Care: Medical Attention for Nephropathy* Process National Committee for Quality Assurance     X Yes Yes 1 This is a comprehensive measure that uses multiple factors for screening, including urine screening, ACEI/ARBs (angiotensin– converting enzyme inhibitor/angiotensin–receptor blocker) use, or referral to a nephrologist.
Prevention 3 Comprehensive Diabetes Care: Hemoglobin A1c (HbA1c) Control (<8.0%)* Outcome National Committee for Quality Assurance   X X Yes Yes 1 The CAG members believe that an HbA1c of less than 7.0% as seen in measure #4 is too aggressive. It has the potential to negatively categorize a practice that has a disproportionally large group of patients with comorbidities. They would be unable to realistically achieve the goal of an A1C of less than 7%. The CAG members feel that an HbA1c of less than 8% is a more reasonable measure to use instead of less than 7%.
Prevention 4 Hemoglobin A1c Control (HbA1c), (<7.0%) Outcome American Diabetes Association       Yes Yes 3 Discussed in measure #3.
Prevention 5 Comprehensive Diabetes Care: Hemoglobin A1c (HbA1c) Poor Control (>9.0%)* Outcome National Committee for Quality Assurance X X X Yes Yes 1 The CAG members believe that this measure combined with measure #3 (A1c of less than 8%) provides a balance of controlling diabetes without being too aggressive. It also identifies greater than 9%, which is poorly controlled and unacceptable standards.
Prevention 6 Comprehensive Diabetes Care: Hemoglobin A1c (HbA1c) testing* Process National Committee for Quality Assurance   X X Yes Yes 3 This measure is not necessary with measures #3 and #5.
Prevention 7 Comprehensive Diabetes Care: Eye Exam (retinal) performed* Process National Committee for Quality Assurance   X X Yes Yes 1 CAG members believe that this is essential to diabetes care. The measure can be measured through claims data.
Prevention 8 Comprehensive diabetes care: LDL–c control (<100mg/dL) * Process National Committee for Quality Assurance X     Yes Yes 3 The NCQA no longer uses this measure. Furthermore the use of statins, rather than an LDL target goal, is more important. An associated and more relevant quality measure is captured in measure #20, (Adherence to Statins for Individuals with Diabetes Mellitus) –– which is a Category 2 measure.
Prevention 9 Comprehensive Diabetes screening – All Four Tests (HbA1c, lipid profile, dilated eye exam, nephropathy monitor) Process National Committee for Quality Assurance X     Yes Yes 1 The CAG believes that this composite measure is important to include as it truly represents a patient centered focus. The results of this measure speak to how the patient is doing (as reflected in compliance with all 4 measure components on a per patient basis).
Prevention 10 Optimal Diabetes Care (Composite Measure)* Process Minnesota Community Measurement       Yes Yes 2 The CAG believes that the threshold for compliance of the different components of this measure are low. Therefore, compliance with this measure is a challenge and may not be reasonable to hold providers accountable. Therefore, the CAG believes that this measure should likely be included in the pilot phase to be further evaluated.
Prevention 11 Diabetic Retinopathy: Communication with the Physician Managing Ongoing Diabetes Care* Process American Medical Association (AMA)– convened Physician Consortium for Performance Improvement       Yes Yes 3 The CAG advises against including this measure due to the difficulty of obtaining testing reports from the eye exam provider. The CAG discussed that this information can be collected through claims data. However, it is felt by the CAG that there is a discrepancy in the communication between the eye exam provider and the Medicaid members´ physician. For example, many Medicaid members obtain eye exams through vision care programs that are independent of a referring provider, and these reports may never be received by the member´s physician.
Prevention 12 Diabetic Retinopathy: Documentation of Presence or Absence of Macular Edema and Level of Severity of Retinopathy* Process AMA–convened Physician Consortium for Performance Improvement       Yes Yes 3 Similar to measure #11, the CAG is concerned about the difficulty of obtaining eye exam reports and advises against including this measure.
Prevention 13 Diabetes: Foot Exam* Process National Committee for Quality Assurance       Yes Yes 1 The CAG believes an annual foot exam is essential for diabetes care.
Prevention 14 Diabetic Foot and Ankle Care, Ulcer Prevention – Evaluation of Footwear* Process American College of Cardiology       Yes Yes 3 An annual foot exam is included in this measure; however, the CAG does not believe that it is feasible for the Medicaid member´s primary provider to evaluate for proper footwear. Physicians are not trained to do so; therefore, the analysis may be too subjective.
Prevention 15 Smoking Cessation discussed and documented Process American Diabetes Association       No Yes 1 The CAG advises to include this measure. However, there is a concern about the completeness of the data. CAG members suggest it might be possible to use CPT codes for counselling for claims analysis.
Prevention 16 BMI/Nutrition Counseling Process American Diabetes Association       No Yes 2 The CAG advises to include this measure. This is a Category 2 because the issue of how to capture nutritional counseling will need to be addressed in the pilot phase.
Prevention 17 Depression screening (PHQ2 or 9) annually Process American Diabetes Association       Yes Yes 1 The CAG advises to include this measure. CPT codes for counseling can be used for claims analysis. Data could also be obtained via EMR.
Medication 18 Adherence to ACEIs/ARBs for Individuals with Diabetes Mellitus* Process Centers for Medicare & Medicaid Services       Yes Yes 3 The CAG does not feel strongly about holding a physician responsible for medication adherence; medication compliance is low (especially within the Medicaid population) despite physicians encouraging patients, or even giving patients medication to go home with.
Medication 19 Adherence to Oral Diabetes Agents for Individuals with Diabetes Mellitus* Process Centers for Medicare & Medicaid Services       Yes Yes 3 Same as measure #19.
Medication 20 Adherence to Statins for Individuals with Diabetes Mellitus* Process Centers for Medicare & Medicaid Services       Yes Yes 2 Similar to measures #18 and #19; however, the CAG feels that there is currently mixed opinions on statin use and would like to test this measure in the pilot phase.
Medication 21 Glycemic Control – Hyperglycemia* Outcome Centers for Medicare & Medicaid Services       No Yes 3 The CAG feels that many patients who are hospitalized with primary diagnoses other than diabetes often have hyperglycemia. This leads to a positively skewed view of hyperglycemia and, therefore, does not properly reflect how well the diabetic population is being controlled.
Medication 22 Glycemic Control – Hypoglycemia* Outcome Centers for Medicare & Medicaid Services       No Yes 3 Hypoglycemia (blood sugar of less than 40) would require clinical records to capture data, and the CAG feels that the value gained is not worth the effort since the rate of hypoglycemic events is low.
Medication 23 Proportion of Days Covered (PDC): 3 rates by therapeutic category (% of patients who met the PDC threshold of 80% during the measurement year (at least 91 days) for RAS antagonists, diabetes medication, or statins)* Process American Diabetes Association       Yes Yes 3 Similar to measures #18 and #19, this measure covers statins, diabetes medications, and ACE/ARBS for at least two prescriptions filled annually.
Medication 24 On ACEI/ARB if hypertension or nephropathy Process American Diabetes Association       Yes Yes 3 This is already included in measure #2.
Treatment 25 Proportion of patients with a chronic condition that have a PAC during a calendar year* Outcome Bridges to Excellence       Yes No 2 The CAG believes that no matter how good the provider´s treatment is, due to the long–term multiple organ effects of diabetes disease and the issue of patients who are noncompliant, it is difficult to hold providers and plans accountable. However, this measure is helpful to analyze aggregate level data and to see the medication member population as a whole. The CAG would like to test it in the pilot phase.
Treatment 26 Diabetes Short–Term Complications Admission Rate (PQI 01)* Outcome Agency for Healthcare Research and Quality X     Yes No 1 The CAG feels that this measure would be helpful since the providers have a greater impact on short–term complication rates as opposed to long–term complication rates (long–term complication rate discussed in measure #27).
Treatment 27 Diabetes Long–Term Complications Admission Rate (PQI 03)* Outcome Agency for Healthcare Research and Quality       Yes No 3 The CAG feels that providers should not be accountable for this measure. The variability of long–term extent of diabetes is high, and the CAG feels that the provider may inherit patients with significant uncontrollable disease that they should not be financially responsible for.
Treatment 28 Uncontrolled Diabetes Admission Rate (PQI 14)* Outcome Agency for Healthcare Research and Quality       Yes No 3 The CAG discussed that most hospital admissions do not occur as a result of uncontrolled diabetes, and therefore, this measure is not applicable.
Treatment 29 Rate of Lower–Extremity Amputation Among Patients With Diabetes (PQI 16)* Outcome Agency for Healthcare Research and Quality       Yes No 2 The CAG would like to test this measure in the pilot phase to see if better controlled diabetes can slow down the amputation rate.
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Appendix A:

Meeting Schedule

  Date Agenda
CAG #1
(Webinar)
10/14/2015 Part I
  1. Clinical Advisory Group Roles and Responsibilities
  2. Introduction to Value Based Payment
  3. Contracting Chronic Care: the Different Options
  4. HCI3 – Understanding the HCI3 Grouper and Development of Care Episodes
Part II
  1. Introduction to Quality Measures.
CAG #2 10/20/2015
  1. Diabetes Episode Definition
  2. Diabetes Quality Measures
  3. Closing this Series of CAG Sessions and Next Steps

______________________________________________________

1. https://www.health.ny.gov/health_care/medicaid/redesign/dsrip/docs/vbp_roadmap_final.pdf1
2. The terms can be used interchangeably. Sometimes, the term "bundle" is used to refer to a combination of individual episodes. 2
3. http://www.hci3.org/content/online–courses 3
4. Attachment B lists all codes for the Asthma Episode and COPD Episode.  4
5. For details on risk adjustment, visit the HCI3 Web site (http://www.hci3.org/content/online–courses)  5
6. The overall total savings/losses per bundle are calculated by adding all these savings/losses at the individual episode level.  6
7. The following sources were used to establish the list of measures to evaluate: existing DSRIP/QARR measures; AHRQ PQI/IQI/PSI/PDI measures; CMS Medicaid Core set measures; other existing statewide measures; NQF endorsed measures; measures suggested by the CAG.  7
8. After the Measurement Evaluation Criteria established by the National Quality Forum (NQF),  8
9. Clinical data refers to non–claims data and is information that is often captured on a patient´s individual chart or record.  9

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