Abstract
Objectives
In 2013, American Society of Addiction Medicine (ASAM) approved their Standards of Care for the Addiction Specialist Physician. Subsequently, an ASAM Performance Measures Panel identified and prioritized the standards to be operationalized into performance measures. The goal of this paper is to describe the process of operationalizing three of these standards into quality measures, and to present the initial measure specifications and results of pilot testing these measures in a large health care system. By presenting the process rather than just the end results, we hope to shed light on the measure development process in order to educate, as well as stimulate debate about the decisions that were made.
Methods
Each measure was decomposed into major concepts. Then each concept was operationalized using commonly available administrative data sources. Alternative specifications examined and sensitivity analyses were conducted to inform decisions that balanced accuracy, clinical nuance, and simplicity. Using data from the US Veterans Health Administration (VHA), overall performance and variation in performance across 119 VHA facilities were calculated.
Results
Three measures were operationalized and pilot tested: pharmacotherapy for alcohol use disorder, pharmacotherapy for opioid use disorder, and timely follow-up after medically managed withdrawal (aka detoxification). Each measure was calculable with available data, showed ample room for improvement (no ceiling effects) and wide facility-level variability.
Conclusions
Next steps include conducting feasibility and pilot testing in other health care systems and other contexts such as standalone addiction treatment programs, as well as to study the specification and predictive validity of these measures.
Keywords: Quality Measurement, Standards of Care, Treatment Processes
Introduction
To help health care systems, medical specialty certification boards, quality managers, and individual physicians monitor quality and performance, as well as to support quality improvement efforts, the Board of Directors of the American Society of Addiction Medicine (ASAM) convened a Practice Improvement and Performance Measurement Action Group (PIPMAG). PIPMAG was comprised of a Steering Committee, a Standards and Outcomes of Care Panel, and a Performance Measures Panel. Using a consensus process, the Standards Expert Panel developed, and the ASAM Board of Directors approved, the Standards of Care for the Addiction Specialist Physician (The Standards) in 2013. (American Society of Addiction Medicine, 2014) The Standards outline the minimum aspects of care that an addiction specialist physician should consider for, and when appropriate provide to, a person with an addictive disorder, especially substance use disorder (SUD). Then, the Performance Measures Panel, comprised of individuals conducting research and clinical work in diverse settings, was tasked with determining which of the standards could feasibly be operationalized into performance measures using administrative data, which should be prioritized for specification and pilot testing, and to identify areas for future research and development.
The report from the Performance Measures Panel describes its process as well the rationale for the measures selected for initial specification and pilot testing.(American Society of Addiction Medicine, 2015) The mission of the Performance Measures Panel was to propose and develop measures that would operationalize elements of The Standards, and to prioritize measures that would be most likely to improve patients’ health, and promote high-quality, cost-efficient health care for addictive disorders. Thus, initial measure selection was based on a number of factors, based on criteria used by the National Quality Forum, and used by other measure developers (National Quality Forum, 2013; Thomas et al., 2011): clinical importance, scientific evidence, reliability and validity, usability, risk of unintended consequences, and, as is always the case with performance measure development, feasibility given available data. Although the initial intention was to develop physician-level measures, the challenges of operationalizing such measures (e.g., small numbers of patients, assigning patients to individual physicians vs. care team or systems of care), and the importance and influence of organizational and payer structures led the Performance Measures Panel to scope the measures to settings (e.g., program, facility or system-level) that usually have more than one clinician or provider.
Of the nine standards that were recommended for measure development (see report for details), three were identified as highest priority for measure specification and pilot testing, primarily based on the existence of supporting scientific evidence, earlier models for measurement and specification, and the availability of relevant data elements.
Measure 1
Percent of patients receiving a medication for alcohol use disorder (AUD).
Measure 2
Percent of patients receiving a medication for opioid use disorder (OUD).
Measure 3
Percent of withdrawal management episodes with outpatient follow-up within 7 days
Although not often appreciated, specifying quality measures is a process that involves making scores of more or less satisfying decisions about how to operationalize the major concepts given available data. Each measurement concept needs to be decomposed into elemental concepts, which then need to be operationalized using data that often exist for billing rather than quality measurement purposes. The goal of this paper is to describe the decision making process the Performance Measures Panel undertook in operationalizing and pilot testing these three measures, as well as to present the initial measure specifications. By presenting the process rather than just the end result, we hope to shed light on the “black box” of measure development in order to educate, as well as stimulate debate about the decisions that were made. This study protocol was approved by the Institutional Review Board of Stanford University and the VA Palo Alto Healthcare System.
Methods and Results
Specifying Measure 1: Percent of patients prescribed a medication for alcohol use disorder (AUD)
The two major concepts for this measure are “AUD medications” and “Patients with AUD”. The Performance Measures Panel operationalized all major concepts with International Classification of Disease – Version 9 (ICD-9) and ICD-10 diagnostic codes, as well as Common Procedure Terminology (CPT), Healthcare Common Procedure Coding System (HCPCS), and ICD-9 CM and ICD-10 CM procedure codes. Other concepts and decisions include the timing and sequence of the diagnosis and medication, medication persistence, and lead-in and follow-up period durations. We describe each below.
Patients with AUD
The FDA has approved four medications for the treatment of alcohol dependence rather than all alcohol use disorders, including abuse. However the abuse/dependence distinction has been abandoned in the American Psychiatric Association Diagnostic and statistical manual of mental disorders (DSM-5)(American Psychiatric Association, 2013). Thus, the Performance Measures Panel included all ICD alcohol abuse and dependence codes, except in-remission diagnoses. The rationale for excluding in-remission codes is that those are intended to signify that a patient's symptoms are not in need of current treatment. (American Psychiatric Association, 2013) In addition to the abuse and dependence codes, the Performance Measures Panel also included alcohol-related medical condition codes, such as ICD-9 291.98 Alcohol Related Sleep Disorders and 425.5 Alcoholic Cardiomyopathy, if there was not an AUD in-remission code recorded on the same day. The rationale for including these codes is that they would rarely be used in the absence of a diagnosable, but perhaps undiagnosed, AUD. Future validation work should confirm this assumption.
Finally, it is not uncommon for patients to receive medications for AUD without having an AUD diagnosis documented in the medical record. The Performance Measures Panel deliberated whether to include undiagnosed patients in the denominator (and numerator) if they were receiving AUD medications, but ultimately decided to only include patients who had a qualifying AUD diagnosis documented in the medical record. The rationale for this decision was two-fold: First, high quality care includes both documenting and treating disorders, not just treating them. Second, naltrexone and topiramate in particular have other indications, thus including patients without a documented AUD might erroneously include many patients without disordered drinking. Tables 1 and 2 present the ICD-9 and ICD-10 codes that have been included and excluded based on these decisions.
Table 1.
Concept | ICD-9 Codes Included | ICD-9 Codes Excluded | ||
---|---|---|---|---|
Alcohol Use Disorder | 303 | Acute alcoholic intoxication in alcoholism, unspecified | 303.03 | Acute alcoholic intoxication in alcoholism, in remission |
303.01 | Acute alcoholic intoxication in alcoholism, continuous | |||
303.02 | Acute alcoholic intoxication in alcoholism, episodic | 303.93 | Other and unspecified alcohol dependence, in remission | |
303.9 | Other and unspecified alcohol dependence, unspecified | 305.03 | Alcohol abuse, in remission | |
303.91 | Other and unspecified alcohol dependence, continuous | |||
303.92 | Other and unspecified alcohol dependence, episodic | V11.3 | History of alcoholism | |
305 | Alcohol abuse, unspecified | |||
305.01 | Alcohol abuse, continuous | |||
305.02 | Alcohol abuse, episodic | |||
291 | Alcohol withdrawal delirium | |||
291.1 | Alcohol-induced persisting amnestic disorder | |||
291.2 | Alcohol-induced persisting dementia | |||
291.3 | Alcohol-induced psychotic disorder with hallucinations | |||
291.5 | Alcohol-induced psychotic disorder with delusions | |||
291.81 | Alcohol withdrawal | |||
291.82 | Alcohol induced sleep disorders | |||
291.89 | Other alcohol-induced mental disorders | |||
291.9 | Unspecified alcohol-induced mental disorders | |||
357.5 | Alcoholic polyneuropathy | |||
425.5 | Alcoholic cardiomyopathy | |||
535.30 | Alcoholic gastritis, without mention of hemorrhage | |||
535.31 | Alcoholic gastritis, with hemorrhage | |||
571.0 | Alcoholic fatty liver | |||
571.1 | Acute alcoholic hepatitis | |||
571.2 | Alcoholic cirrhosis of liver | |||
571.3 | Alcoholic liver damage, unspecified | |||
Medications for AUD | Naltrexone (oral and IM) | |||
Acamprosate | ||||
Disulfiram | ||||
Topiramate | ||||
Opioid Use Disorder | 304.00 | Opioid type dependence, unspecified | ||
304.01 | Opioid type dependence, continuous | |||
304.02 | Opioid type dependence, episodic | |||
305.50 | Opioid abuse, unspecified | |||
305.51 | Opioid abuse, continuous | |||
305.52 | Opioid abuse, episodic | |||
Medications for OUD | Suboxone | |||
Naltrexone (oral and IM) | ||||
Buprenorphine excluding patches AND IV medications | ||||
Subutex | ||||
Detoxification Procedures | 94.62 | Alcohol detoxification | ||
94.63 | Alcohol rehabilitation and detoxification | |||
94.65 | Drug detoxification | |||
94.66 | Drug rehabilitation and detoxification | |||
94.68 | Combined alcohol and drug detoxification | |||
94.69 | Combined alcohol and drug rehabilitation and detoxification | |||
H0008 | Alcohol and/or drug services; sub-acute detoxification (hospital inpatient) | |||
H0009 | Alcohol and/or drug services; acute detoxification (hospital inpatient) | |||
H0010 | Alcohol and/or drug services; sub-acute detoxification (residential addiction program inpatient) | |||
H0011 | Alcohol and/or drug services; acute detoxification (residential addiction program inpatient) | |||
H0012 | Alcohol and/or drug services; sub-acute detoxification (residential addiction program outpatient) | |||
H0013 | Alcohol and/or drug services; acute detoxification (residential addiction program outpatient) | |||
H0014 | Alcohol and/or drug services; ambulatory detoxification |
Table 2.
Concept | ICD-10 Codes Included | ICD-10 Codes Excluded | ||
---|---|---|---|---|
Alcohol Use Disorder | F10.229 | Alcohol dependence with intoxication, unspecified | F10.21 | Alcohol dependence, in remission |
F10.129 | Alcohol abuse with intoxication, unspecified | F10.929 | Alcohol use, unspecified with intoxication, unspecified | |
F10.220 | Alcohol dependence with intoxication, uncomplicated | |||
F10.221 | Alcohol dependence with intoxication delirium | F10.920 | Alcohol use, unspecified with intoxication, uncomplicated | |
F10.20 | Alcohol dependence, uncomplicated | |||
F10.10 | Alcohol abuse, uncomplicated | F10.921 | Alcohol use, unspecified with intoxication delirium | |
F10.230 | Alcohol dependence with withdrawal, uncomplicated | |||
F10.239 | Alcohol dependence with withdrawal, unspecified | F10.981 | Alcohol use, unspecified with alcohol-induced sexual dysfunction | |
F10.231 | Alcohol dependence with withdrawal delirium | |||
F10.232 | Alcohol dependence with withdrawal with perceptual disturbance | R78.0 | Finding of alcohol in blood | |
F10.96 | Alcohol use, unspecified with alcohol-induced persisting amnestic disorder | Y90 |
Evidence of alcohol involvement determined by blood alcohol level | |
F10.97 | Alcohol use, unspecified with alcohol-induced persisting dementia | T51.0X1A | Toxic effect of ethanol, accidental (unintentional), initial encounter | |
F10.27 | Alcohol dependence with alcohol-induced persisting dementia | T51.91X1A | Toxic effect of unspecified alcohol, accidental (unintentional), initial encounter | |
F10.951 | Alcohol use, unspecified with alcohol-induced psychotic disorder with hallucinations | |||
K099.310-315 | Alcohol use complicating pregnancy, childbirth, and the puerperium | |||
F10.950 | Alcohol use, unspecified with alcohol-induced psychotic disorder with delusions | |||
F10.239 | Alcohol dependence with withdrawal, unspecified | |||
F10.232 | Alcohol dependence with withdrawal with perceptual disturbance | |||
F10.182 | Alcohol abuse with alcohol-induced sleep disorder | |||
F10.282 | Alcohol dependence with alcohol-induced sleep disorder | |||
F10.982 | Alcohol use, unspecified with alcohol-induced sleep disorder | |||
F10.159 | Alcohol abuse with alcohol-induced psychotic disorder, unspecified | |||
F10.180 | Alcohol abuse with alcohol-induced anxiety disorder | |||
F10.181 | Alcohol abuse with alcohol-induced sexual dysfunction | |||
F10.188 | Alcohol abuse with other alcohol-induced disorder | |||
F10.250 | Alcohol dependence with alcohol-induced psychotic disorder, with delusions | |||
F10.251 | Alcohol dependence with alcohol-induced psychotic disorder, hallucinations | |||
F10.259 | Alcohol dependence with alcohol-induced psychotic disorder, unspecified | |||
F10.280 | Alcohol dependence with alcohol-induced anxiety disorder | |||
F10.281 | Alcohol dependence with alcohol-induced sexual dysfunction | |||
F10.288 | Alcohol dependence with other alcohol-induced disorder | |||
F10.29 | Alcohol dependence with unspecified alcohol-induced disorder | |||
F10.994 | Alcohol use, unspecified with alcohol-induced mood disorder | |||
F10.959 | Alcohol use, unspecified with alcohol-induced psychotic disorder, unspecified | |||
F10.980 | Alcohol use, unspecified with alcohol-induced anxiety disorder | |||
F10.988 | Alcohol use, unspecified with other alcohol-induced disorder | |||
F10.19 | Alcohol abuse with unspecified alcohol-induced disorder | |||
F10.120 | Alcohol abuse with intoxication, uncomplicated | |||
F10.121 | Alcohol abuse with intoxication delirium | |||
F10.122 | Alcohol abuse with intoxication, unspecified | |||
F10.14 | Alcohol abuse with alcohol-induced mood disorder | |||
F10.150 | Alcohol abuse with alcohol-induced psychotic disorder with delusions | |||
F10.151 | Alcohol abuse with alcohol-induced psychotic disorder, unspecified | |||
F10.24 | Alcohol dependence with alcohol-induced mood disorder | |||
F10.26 | Alcohol dependence with alcohol-induced persisting amnestic disorder | |||
F10.99 | Alcohol use, unspecified with unspecified alcohol-induced disorder | |||
G62.1 | Alcoholic polyneuropathy | |||
I42.6 | Alcoyholic cardiomyopathy | |||
K29.20 | Alcoholic gastritis without bleeding | |||
K29.21 | Alcoholic gastritis with bleeding | |||
K70.0 | Alcoholic fatty liver | |||
K70.10 | Alcoholic hepatitis without ascites | |||
K70.11 | Alcoholic hepatitis with ascites | |||
K70.2 | Alcoholic fibrosis and sclerosis of liver | |||
K70.30 | Alcoholic cirrhosis of liver without ascites | |||
K70.31 | Alcoholic cirrhosis of liver with ascites | |||
K70.40 | Alcoholic hepatic failure without coma | |||
K70.41 | Alcoholic hepatic failure with coma | |||
K70.9 | Alcoholic liver disease, unspecified | |||
K85.2 | Alcohol-induced acute pancreatitis | |||
K86.0 | Alcohol-induced chronic pancreatitis | |||
E24.4 | Alcohol-induced pseudo-Cushing's syndrome | |||
G31.2 | Degeneration of the nervous system due to alcohol | |||
G72.1 | Alcoholic myopathy | |||
Medications for AUD | Naltrexone (oral and IM) | |||
Acamprosate | ||||
Disulfiram | ||||
Topiramate | ||||
Opioid Use Disorder | F11.20 | Opioid dependence, uncomplicated | F11.21 | Opioid dependence, in remission |
F11.10 | Opioid abuse, uncomplicated | |||
F11.10 | F11.922 | Opioid use, unspecified with intoxication with perceptual disturbance | ||
F11.122 | Opioid abuse with intoxication with perceptual disturbance | |||
F11.929 | Opioid use, unspecified with intoxication, unspecified | |||
F11.222 | Opioid dependence with intoxication with perceptual disturbance | |||
F11.120 | Opioid abuse with intoxication, uncomplicated | |||
F11.129 | Opioid abuse with intoxication, unspecified | |||
F11.229 | Opioid dependence with intoxication, unspecified | |||
F11.23 | Opioid dependence with withdrawal | |||
F11.99 | Opioid use, unspecified with unspecified opioid-induced disorder | |||
F11.14 | Opioid abuse with opioid-induced mood disorder | |||
F11.188 | Opioid abuse with other opioid-induced disorder | |||
F11.159 | Opioid abuse with opioid-induced psychotic disorder, unspecified | |||
F11.150 | Opioid abuse with opioid-induced psychotic disorder with delusions | |||
F11.151 | Opioid abuse with opioid-induced psychotic disorder with hallucinations | |||
F11.181 | Opioid abuse with opioid-induced sexual dysfunction | |||
F11.182 | Opioid abuse with opioid-induced sleep disorder | |||
F11.19 | Opioid abuse with unspecified opioid-induced disorder | |||
Medications for AUD | Suboxone | |||
Naltrexone (oral and IM) | ||||
Buprenorphine excluding patches AND IV medications | ||||
Subutex | ||||
Detoxification Procedures | HZ2ZZZZ | Detoxification Services for Substance Abuse Treatment |
Medications for AUD
Many medications have been studied for the treatment of AUD, many with varied or equivocal evidence of effectiveness. (Jonas et al., 2014; Maisel, Blodgett, Wilbourne, et al, 2013) The Performance Measures Panel strove to develop criteria that could be used not only to select which medications to include in the measure specifications, but also to add or subtract medications as new evidence emerges. The panel decided that medications should be included if they meet at least one of the following criteria: 1) The FDA has approved the medication for AUD (or alcohol dependence); 2) Effectiveness of the medication for AUD is supported by high-quality meta-analytic studies. Using these criteria, the following medications are included in the measure specifications: Naltrexone (oral and injectable), acamprosate, disulfiram, and topiramate. (Blodgett, Del Re, Maisel, et al, 2014; Jonas et al., 2014; Maisel et al., 2013; Skinner, Lahmek, Pham, et al, 2014) The Performance Measures Panel decided that other commonly used or perhaps promising medications such as gabapentin and baclofen, sometimes being used in practice, did not meet these criteria.
Other Measure Design Decisions
In order to operationalize these concepts into a measure, the Performance Measures Panel needed to decide what time period to use for denominator qualification and then what time period to use for the numerator qualification. There are many possibilities with varying complexity, all with dissatisfying aspects. The simplest version includes all patients who had at least one documented AUD diagnosis in any setting (e.g., inpatient, outpatient, primary care, addiction treatment program) any time during a measurement year, and determine which of these qualified patients received at least one of the medications at any time during the measurement year. This version provides a simple, administratively feasible, snapshot of AUD pharmacotherapy access at a program, facility, or system level.
Potential problems with this version are that patients can get the medication before they get the documented diagnosis, and patients who get diagnosed late in the year have less time to receive medications that satisfy the measure criteria. A major test of whether differences in measure specification are consequential is whether the overall level and rank order of performance changes substantially when different specifications are used.(Fernandes-Taylor & Harris, 2012; Harris, Rubinsky, & Hoggatt, 2015) To test some of the alternatives in sensitivity analyses, Performance Measures Panel limited the qualification period to the first 9 months of the measurement year in order to give all patients at least 3 months to receive medication after diagnoses. Another version was tested that only counted medications received after the index diagnosis. Although these more complicated versions predictably shifted the level of measured performance slightly (~1%) lower, the change in relative performance of facilities was minimal. Therefore, the panel decided to adopt the simple version: Proportion of patients who get an AUD diagnoses during the measurement year who also fill a prescription for one of the medications at any time during the measurement year.
The Performance Measures Panel decided to rely on receipt of medication as determined through pharmacy records rather than the provision of a prescription, as data on the latter is not as commonly accessible. Finally, the panel decided to focus on initiation/access rather than persistence/adequate course of medications because lack of access is the most immediate problem. Further, there is no consensus on what constitutes an adequate course of these medications as well as some evidence of efficacy for as-needed (PRN) use, (Heinala et al., 2001) making persistence a more difficult concept to operationalize.
Pilot Testing Measure 1
In order to pilot test these specifications, the measures were calculated using Fiscal Year 2013 (FY13) inpatient and outpatient clinical and pharmacy data from the Veterans Health Administration (VHA). These data cover VHA's 119 major health care systems, each including large medical centers as well as smaller community clinics. The pilot testing was accomplished using the ICD-9 specifications. The target medications were identified using the “Drug Name” variable in VA pharmacy datasets.
In FY13, 356,116 patients had at least one clinical encounter with an AUD diagnosis which qualified them for the measure denominator, of which 21,093 (5.92%) filled at least one prescription for at least one of the medications. Facility-level descriptive statistics for the measure are presented in Table 3. Substantial facility-level variability existed, ranging from 1%-19%.
Table 3.
Measure | Mean | Minimum | 25th %tile | 50th %tile | 75th %tile | Maximum |
---|---|---|---|---|---|---|
Pharmacotherapy for AUD (N = 119) | 6.05 | 1.16 | 4.16 | 5.48 | 7.12 | 19.25 |
Pharmacotherapy for OUD v1 (N = 119) | 21.63 | 0.23 | 11.50 | 19.97 | 29.73 | 62.23 |
Pharmacotherapy for OUD v2 (N = 119) | 27.55 | 0.23 | 15.38 | 28.28 | 38.39 | 62.96 |
Follow-up after Detox (N = 116)* | 34.67 | 5.55 | 25.97 | 35.29 | 42.23 | 59.40 |
excluding facilities with less than 5 detoxification episodes in the measurement year
Other Details and Sensitivity Analyses
Of qualifying patients, 3.8% (13,683) qualified by having an alcohol-related medical condition and no concurrent in-remission diagnosis or other AUD diagnosis, of which 1.50% received medication. Among patients who did not meet the qualifying criteria, 55,912 patients had in-remission AUD codes only (i.e., no active AUD diagnoses) and 1,980 of these in-remission patients (3.5%) received a medication. Furthermore, there were patients who received the medications without a qualifying diagnoses: 118 with Acamprosate; 1352 with oral naltrexone; 521 with disulfiram; 34 with injectable naltrexone; and 49,904 with topiramate. Note that naltrexone and, to a greater extent, topiramate have other indications than AUD. It is more likely that those getting disulfiram and acamprosate are getting treated for AUD without a properly documented diagnosis.
Specifying Measure 2: Percent of patients prescribed a medication for opioid use disorder (OUD)
The two major concepts for this measure are “OUD medications” and “Patients with OUD”. Other concepts and decisions include the timing and sequence of the diagnosis and medication, medication persistence, and lead-in and follow-up period durations. We describe each below.
Patients with OUD
Using the same rationale as Measure 1, the Performance Measures Panel included all OUD's not in-remission. Unlike alcohol, there are no opioid-related mental health or medical conditions to consider. Tables 1 and 2 present the ICD-9 and ICD-10 codes that have been included and excluded based on these decisions.
Medications for OUD
Using the same criteria for inclusion as Measure 1, the performance measure panel determined that three medications are FDA-approved and have meta-analytic support for the treatment of OUD: Buprenorphine (Suboxone, Subutex; excluding buprenorphine patches and IV medications, which are primarily used for pain), naltrexone (oral and injectable), and methadone.
Because methadone for OUD must be dispensed by a licensed Opioid Treatment Program (OTP), and is usually not recorded in the pharmacy data, data elements to capture methadone, if they exist at all, vary from system to system. For example, VA operates many OTPs that generate clinical encounter codes when providing services, even though no specific data exist on the methadone dispensed. When a patient has a recorded encounter in an OTP (clinic stop 523), an OUD diagnose, but not currently receiving buprenorphine or naltrexone, it is assumed they are receiving methadone treatment. However, some VA facilities have no OTP but pay for these services through a contract provider. Patient data on these services are not available, so its looks like patients from these facilities do not have access to methadone. Due to this potential data problem and undercounting of services in many locations, it is even more important than usual to understand the context of the facilities and systems being assessed. In particular, although this measure will be useful for within-system quality assurance and improvement, using this measure for between-system comparisons, especially public reporting, could be very problematic.
Pilot Testing Measure 2
As mentioned, VA provides methadone in OTP's and buprenorphine and naltrexone for OUD in OTP's and other settings. Here we present results from two versions of the measure: Version 1 (v1) that includes naltrexone and buprenorphine but not methadone, and Version 2 (v2) that includes all three medications.
In FY13, 51,655 patients had at least one clinical encounter with an OUD documented, thereby qualifying them for the measure denominator, of which 11,065 (21.8%) filled at least one prescription for naltrexone or buprenorphine (v1), and 16,316 (32.2%) had at least one visit to an OTP with an OUD diagnosis or filled at least one prescription for naltrexone or buprenorphine (v2). Facility-level descriptive statistics for both versions of the measure are presented in Table 3. Substantial facility-level variability existed, ranging from 0.2%-62% for v1 and 0.2%-63% for v2.
Other Details and Sensitivity Analyses
Among patients who did not meet the qualifying criteria, 4,926 patients had in-remission OUD codes only (i.e., no active OUD diagnoses) of which 457 (9.2%) received either buprenorphine or naltrexone. The Performance Measures Panel excluded “Combinations of opioid type drug” diagnosis codes (304.70, 304.71, 304.72). Among the 1,264 patients with these codes and no other active OUD, 106 (8.4%) received medications. Furthermore, there were 799 patients who received buprenorphine without a qualifying diagnoses. There were 1573 patients with a 523 clinic stop without a OUD diagnosis, which we know from previous validation work were mostly patients getting counseling treatment for other addictive disorders, not methadone or other medications for OUD.
Specifying Measure 3: Percent of withdrawal management episodes with outpatient follow-up within 7 days
The major concepts for this measure are “Withdrawal Management Episode”, i.e. detoxification, and “Follow-up”. Other concepts and decisions include the timing and nature of the follow-up. We describe each below.
Withdrawal Management (i.e., Detoxification)
The denominator for this measure is composed of detoxification episodes, which were operationalized using the procedure codes presented in Tables 1 and 2. At first, an attempt was made to develop separate versions of this measure for inpatient and ambulatory detoxification episodes. However, at least in VA data, it was impossible to be certain if a detoxification episode occurred in an inpatient or outpatient setting. For example, the code H0009 (Alcohol and/or drug services; acute detoxification (hospital inpatient)) occurred frequently in the VA outpatient files. For this reason, and for overall simplicity, the Performance Measures Panel decided to construct one combined measure to capture information about follow-up from detoxification episodes regardless of the clinical context (inpatient or outpatient).
An attempt was made to capture information about detoxification episodes that were not coded with one of the procedure codes by looking for short-term courses of medications typically used for medically managed withdrawal. When paired with a diagnosis of AUD or OUD, this method identified about ten percent more patients than the method only using procedure codes. However, due to the added complexity and very cursory validation of this method, it was not included in the measure specifications.
Finally, some patients have what appeared to be, but may not be, multiple closely spaced outpatient detoxification episodes. The panel considered a denominator composed of unique patients rather than episodes to partially address this problem. Because making the distinction between possibly separate detoxification episodes was more difficult in the outpatient setting, the Performance Measures Panel decided to include only the last ambulatory detoxification episode for each patient in the measurement year. Additionally, each inpatient detoxification with a unique discharge day was included. Thus, each patient might contribute at most one outpatient detoxification but perhaps many inpatients detoxifications to the denominator.
Outpatient Follow-up
The main concept for the measure numerator is outpatient follow-up care for SUD within 7 days after detoxification. The Performance Measures Panel entertained various windows besides 7 days for the follow-up to occur, including 3 and 10 days. The general consensus was that 3 days would be clinically more conservative but was perhaps too stringent in some contexts. Pilot testing the different follow-up lengths revealed that although the overall level of performance increased with longer follow-up windows, the relative performance of facilities did not appreciably change. Therefore, the 7-day window was chosen as a compromise and because some evidence exists for the predictive validity of this time period. (Harris et al., 2013) For outpatients, the follow-up window is 7 days starting the day after the last documented detoxification code. For inpatients, the follow-up is 7 days starting the day after discharge.
Clearly, one visit is not adequate treatment for SUD after a detoxification episode, but it is a necessary and critical first step. Completion of the first visit is an indicator that proper coordination and communication may exist. Future work by the Performance Measures Panel will develop a measure of SUD treatment engagement after detoxification.
Even though detoxification is almost always for AUD or OUD, the Performance Measures Panel decided that follow-up would be defined consistent with the HEDIS Initiation and Engagement measures’ specifications for any outpatient SUD treatment.(National Committee for Quality Assurance, 2014) According to the HEDIS specifications, any health care encounter with combinations of specific diagnosis and procedure codes are consider SUD treatment, including encounters outside of SUD programs (e.g., primary care). (Harris et al., 2015; Harris, et al, 2011; National Committee for Quality Assurance, 2014)
Pilot Testing Measure 3
In FY13, 38,514 detoxification episodes were recorded per the measure specifications, of which 876 were outpatient and 37,638 were inpatient services. Overall, 35.3% (13,594) were followed within 7 days with an outpatient SUD treatment encounter per HEDIS specifications. For outpatient and inpatient detoxification episodes, 60.7% and 34.7% respectively were followed within 7 days with outpatient SUD treatment. Facility-level descriptive statistics for the measure are presented in Table 3. Substantial facility-level variability existed, ranging from 5.5%-59.4%.
Other Details and Sensitivity Analyses
For outpatient detoxification episodes, 43.3% had an outpatient follow-up visit within 3 days and 63.9% had an outpatient follow-up visit within 10 days. For inpatient detoxification episodes, 20.1% had an outpatient follow-up visit within 3 days and 39.4% had an outpatient follow-up visit within 10 days.
Discussion
The purpose of this paper is to describe the decision making process that the Performance Measures Panel undertook in operationalizing and pilot testing these three measures. By transparently presenting the process rather than just the end results, we hope to shed light inside of the measure development process in order to stimulate debate about the decisions that were made. The analyses presented in this paper demonstrate that the measure specifications can be used in a large health care system that has a robust electronic medical record system to produce quality data to describe the overall level and variation in the underlying standards of care. It is worth noting that systems or programs that lack comparable data systems will be challenged to implement these measures.
Next steps include conducting feasibility and pilot testing in other health care systems and other contexts such as standalone addiction treatment programs, as well as to study the specification and predictive validity of these measures. To ease future implementation, pilot testing in other systems should also include the development of a list of National Drug Codes relevant to these measures. With the switch to ICD-10 in 2016, these measures should also be pilot tested with the new codes and compared to the values obtained using ICD-9. Also, the Performance Measures Panel still needs to specify and pilot test the other measures proposed for later development.
Acknowledgments
Funding: This work was funded in part by Substance Abuse and Mental Health Services Administration (SAMHSA), a Cooperative Research and Development Agreement between ASAM and the Palo Alto Veterans Institute for Research, and a VA Research Career Scientist Award to Dr. Harris (RCS-14-232). We also acknowledge other members of the Performance Measures Panel including Corey Waller, MD, MS (Chair), Melinda Campopiano, MD (SAMHSA Liaison), Rhonda Robinson-Beale, MD, and Sarah Duffy (NIDA). The views expressed are the authors’ not those of the Department of Veterans Affairs or other organizations.
References
- American Psychiatric Association . Diagnostic and statistical manual of mental disorders: DSM-5. 5th ed. Author; Washington, DC: 2013. [Google Scholar]
- American Society of Addiction Medicine . Standards of Care: For the Addiction Specialist Physician. Author; Chevy Chase, MD: 2014. [Google Scholar]
- American Society of Addiction Medicine . Performance Measures for the Addiction Specialist Physician. Author; Chevy Chase, MD: 2015. [Google Scholar]
- Blodgett JC, Del Re AC, Maisel NC, Finney JW. A meta-analysis of topiramate's effects for individuals with alcohol use disorders. Alcohol Clin Exp Res. 2014;38:1481–1488. doi: 10.1111/acer.12411. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fernandes-Taylor S, Harris AH. Comparing alternative specifications of quality measures: access to pharmacotherapy for alcohol use disorders. J Subst Abuse Treat. 2012;42:102–107. doi: 10.1016/j.jsat.2011.07.005. [DOI] [PubMed] [Google Scholar]
- Harris AHS, Finney J, Asch S, et al. Validating New Measures of Addiction Treatment Quality.. Paper presented at the 2013 AcademyHealth Annual Research Meeting; Baltimore MD.. [Google Scholar]
- Harris AHS, Ellerbe L, Phelps TE, et al. Examining the Specification Validity of the HEDIS Quality Measures for Substance Use Disorders. J Subst Abuse Treat. 2015;53:16–21. doi: 10.1016/j.jsat.2015.01.002. [DOI] [PubMed] [Google Scholar]
- Harris AHS, Reeder RN, Ellerbe LS, Bowe TR. Validation of the treatment identification strategy of the HEDIS addiction quality measures: concordance with medical record review. BMC Health Serv Res. 2011;2011;11:73. doi: 10.1186/1472-6963-11-73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Harris AHS, Rubinsky AD, Hoggatt KJ. Possible Alternatives to Diagnosis-based Denominators for Addiction Treatment Quality Measures. J Subst Abuse Treat. 2015;58:62–66. doi: 10.1016/j.jsat.2015.06.004. [DOI] [PubMed] [Google Scholar]
- Heinala P, Alho H, Kiianmaa K, Lonnqvist J, Kuoppasalmi K, Sinclair JD. Targeted use of naltrexone without prior detoxification in the treatment of alcohol dependence: a factorial double-blind, placebo-controlled trial. J Clin Psychopharmacol. 2001;21:287–292. doi: 10.1097/00004714-200106000-00006. [DOI] [PubMed] [Google Scholar]
- Jonas DE, Amick HR, Feltner C, et al. Pharmacotherapy for adults with alcohol use disorders in outpatient settings: a systematic review and meta-analysis. JAMA. 2014;311:1889–1900. doi: 10.1001/jama.2014.3628. [DOI] [PubMed] [Google Scholar]
- Maisel NC, Blodgett JC, Wilbourne PL, Humphreys K, Finney JW. Meta-analysis of naltrexone and acamprosate for treating alcohol use disorders: when are these medications most helpful? Addiction. 2013;108:275–293. doi: 10.1111/j.1360-0443.2012.04054.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- National Committee for Quality Assurance . HEDIS 2014 Volume 2: Technical Specifications. Author; Washington, DC: 2014. [Google Scholar]
- National Quality Forum . Review and Update of Guidance for Evaluating Evidence and Measure Testing – Technical Report. Author; Washington, DC: 2013. [Google Scholar]
- Skinner MD, Lahmek P, Pham H, Aubin HJ. Disulfiram efficacy in the treatment of alcohol dependence: a meta-analysis. PLoS One. 2014;9:e87366. doi: 10.1371/journal.pone.0087366. [DOI] [PMC free article] [PubMed] [Google Scholar]
- Thomas CP, Garnick DW, Horgan CM, McCorry F, et al. Advancing performance measures for use of medications in substance abuse treatment. J Subst Abuse Treat. 2011;40:35–43. doi: 10.1016/j.jsat.2010.08.005. [DOI] [PMC free article] [PubMed] [Google Scholar]