Clinical Therapeutics/Volume 39, Number 1, 2017
Determinants of Treatment Eligibility in Veterans With Hepatitis C Viral Infection Janice Taylor, PharmD, BCPS1; Sian Carr-Lopez, PharmD2,3; Amy Robinson, PharmD4; Robert Malmstrom, PharmD5; Karsten Duncan, PharmD2; Archana Maniar, MD2,6; A.C. Del Re, PhD7; and Jannet M. Carmichael, PharmD, BCPS, FCCP, FAPhA1 1
Veterans Affairs Sierra Pacific Network, Reno, Nevada; 2Veterans Affairs Northern California Healthcare System, Mather, California; 3University of the Pacific, Stockton, California; 4Veterans Affairs Sierra Pacific Network, Mountain View, California; 5Veterans Affairs Northern California Healthcare System, Martinez, California; 6University of California Healthcare System, Sacramento, California; and 7Center for Innovation Implementation Veterans Affairs Palo Alto Healthcare System, Menlo Park, California
ABSTRACT Purposes: The objective of this study was to determine the percentage of veterans with active hepatitis C virus (HCV) infection who were deemed to be candidates for treatment and to identify factors associated with treatment ineligibility. Methods: This was a multisite, retrospective cohort analysis of veterans with HCV infection within the Veteran Integrated Service Network 21. Patients evaluated between August and November 2015 who were viremic and not receiving HCV treatment were included in the analysis. Reasons for treatment exclusion were determined by an experienced clinician and recorded into a regional population management dashboard. Descriptive statistics were used to describe the population. The t test for normally distributed data, the Mann-Whitney rank sum test for data that failed normality testing, or the χ2 test were used to examine differences between the treatment eligible and ineligible cohorts. Generalized linear mixed-effects models were conducted to estimate patient outcomes relevant to various disease states and characteristics while controlling for interfacility variability. Findings: The cohort included 1,003 veterans within 5 medical centers; 988 (98.5%) were male, and 625 (62%) had a fibrosis 4 score 43.25, indicating the presence of ALD. According to clinician classification, 478 (48%) were considered HCV treatment candidates, whereas 525 (52%) were determined to be treatment ineligible. The most common reasons documented by clinicians for treatment ineligibility included unstable or uncontrolled comorbidities (n ¼ 118 [22.4%]), excessive alcohol use (n ¼ 116 [22.1%]), and treatment refusal by
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the patient (n ¼ 69 [13%]). On the basis of statistical modeling and reporting odds ratios (ORs) and 95% CIs, diagnoses of active alcohol use disorder (OR ¼ 0.68; 95% CI, 0.47–0.98; P ¼ 0.038), hepatocellular carcinoma (OR ¼ 0.24; 95% CI, 0.13–0.47; P o 0.001), and palliative care status (OR ¼ 0.21; 95% CI, 0.05–0.99; P ¼ 0.049) were statistically associated with treatment ineligibility, whereas posttraumatic stress disorder (OR ¼ 1.48; 95% CI, 1.01–2.18; P ¼ 0.046) was associated with treatment eligibility. There were no statistically significant differences found for other psychiatric diagnoses or an encounter for homelessness. Implications: Results of this study indicate that a high percentage of patients may not be considered treatment eligible at initial clinical review. Within this veteran population, the presence of uncontrolled comorbidities and excessive alcohol use were the most commonly reported reasons for treatment ineligibility. On the basis of this analysis, processes could be established to address modifiable barriers to treatment, thus expanding the number of individuals receiving potentially curative therapy for HCV infection. (Clin Ther. 2017;39:130–137) Published by Elsevier HS Journals, Inc. Key words: direct-acting antivirals, hepatitis C, population management, pretreatment assessment, treatment candidate.
Accepted for publication November 17, 2016. http://dx.doi.org/10.1016/j.clinthera.2016.11.019 0149-2918/$ - see front matter Published by Elsevier HS Journals, Inc.
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J. Taylor et al.
INTRODUCTION Hepatitis C continues to be a major public health concern, with an estimated 2.7 million to 3.9 million chronic cases within the United States.1 Within the Veterans Health Administration, hepatitis C virus (HCV) infection prevalence is noted to be 2 to 3 times that of the general US population.2,3 In 2014, a total of 164,889 veterans had active HCV nationwide, and 10,056 were within the Veterans’ Integrated Service Network (VISN) 21, which encompasses Veterans Affairs (VA) health care facilities within Northern and Central California, Nevada, and the Pacific Islands.4 National rates of HCV-related deaths continue to increase, and the comorbidities of HCV can be significant.1 Untreated HCV infection is a leading cause of liver disease, and many cases progress to cirrhosis, hepatocellular carcinoma, or other end-stage liver complications.5,6 These complications affect patients’ quality of life and health care costs. Estimated annual health care costs per patient associated with HCV triple as the degree of liver fibrosis progresses from early ($810) to advanced ($2575) stages.7 The direct health care costs in individuals with advanced liver disease (ALD) resulting in hepatocellular carcinoma are estimated at $176,455 per patient.8 In 2014, 19% of veterans within VISN 21 with active HCV were estimated to have ALD.9 The VA clinical guidelines published in 2015 emphasized treating special populations with HCV, including those with ALD or HIV coinfection, and suggested that the urgency of treatment be based on the risk of developing decompensated cirrhosis or dying from liver-related disease.10–12 However, the current approach is to treat all patients with active HCV.13 Despite the VA’s push for treatment, factors that may affect treatment rates include patient readiness and contraindications to treatment, along with finite resources, such as pharmaceutical budgets and clinic capacity. The estimated cost for a 12-week treatment with the most commonly prescribed medication is $94,500; however, the VA health system cost is based on a negotiated contract.7 Health care systems must carefully allocate resources because of significant upfront pharmaceutical costs. In a study performed by Cachay et al14 in a non-VA population of 562 patients coinfected with HIV and HCV, 303 were referred for treatment and 259 were not referred. The strongest predictor of not being referred for HCV
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treatment was the patient’s lack of engagement in care as defined by missed clinic visits and follow-up.14 Of the 303 referred for treatment, 88 (29%) started treatment. Primary reasons for not treating included ongoing drug or alcohol abuse, unwillingness to participate in the clinic protocol, uncontrolled neuropsychiatric disorders, or uncontrolled HIV disease in the context of ongoing drug or alcohol abuse. Within the VA, the high prevalence of these clinical issues suggests that not all veterans may be appropriate for treatment. This finding reinforces the need for clinical evaluation and assessment of barriers when determining treatment candidate status to ensure efficient use of resources.
PATIENTS AND METHODS This was a retrospective analysis of data from 5 medical centers located within the states of California, Nevada, and Hawaii. This project did not meet the criteria for human research and did not require approval by the VISN 21 Institutional Review Board.
Data Source The VISN 21 clinical HCV population management dashboard was developed in 2012 to identify HCV-positive patients and monitor them during and after treatment. In August 2015, a tracking tool was added to the dashboard in an effort to capture clinicians’ decisions and data about patient eligibility for treatment. Pharmacists and physicians with experience in treating HCV used the dashboard to review patients at high risk of progression, primarily those with ALD, to determine HCV treatment eligibility. Eligibility criteria were based on VA guidelines derived from the Infectious Disease Society of America. A standardized dropdown menu was used to document possible reasons a veteran may have not been a treatment candidate. All HCV treatment providers were provided instructions to record the treatment candidate status and reasons for treatment ineligibility. The VISN 21 DataMart and associated databases were used to obtain the pharmacy and demographic records used in this study. Automated data extraction routines capture pharmacy, diagnosis, laboratory, provider, and patient demographic data on a daily basis. Data were queried using Structured Query Language. Relevant disease states were identified
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Clinical Therapeutics through International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, Tenth Revision (ICD-10) inpatient or outpatient diagnoses that had been encountered for a given patient within 1 year from the date of patient evaluation for candidate status. Patient demographic characteristics and laboratory information, including a calculated liver Fibrosis 4 (Fib-4) score, were extracted from the database for these patients.
Study Eligibility Any VA patient with chronic HCV was a potential candidate for antiviral treatment unless a medical contraindication existed. The VA guideline exclusion criteria for treatment include patient refusal of treatment; life expectancy of o12 months without perceived benefit of HCV eradication; confirmed severe and irreversible cognitive impairment, such as a persistent vegetative state; presence of HCV strains that are resistant to all antiviral treatments; and presence of a Model for End-Stage Liver Disease score 430.11 The VA guidelines recommend that decisions regarding treatment candidates be made by experienced providers, taking into account comorbid conditions and assessing potential factors associated with poor adherence, including illicit substance use, alcohol use disorder, or mental health conditions. Factors that could affect adherence should be adequately addressed before initiating use of medications.11 The study population consisted of veterans aged Z18 years with a confirmed diagnosis of HCV who had detectable HCV RNA laboratory results and a documented clinical review performed between August and November 2015. The clinical review determined their treatment candidate status and the reason for treatment ineligibility, if applicable. Veterans evaluated or started on treatment before August 1, 2015, or those with incomplete data regarding their treatment candidate status were not included in the analysis. The primary outcome of this project was to determine the percentage of clinically evaluated patients determined to be treatment eligible and to establish the reason given for treatment ineligibility. Standardized reasons that patients were deemed ineligible for HCV treatment included the following: documented ongoing nonadherence with medication or missed clinic appointment, limited life expectancy,
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no medication option currently available (ie, failed nonstructural protein 5a inhibitors, hypersensitivity to drug, interaction with required drug), patient refusal of treatment, severe renal impairment, inability to contact patient (ie, incorrect address or telephone number), unstable or uncontrolled comorbidity that precludes treatment, excessive use of alcohol, actively using illicit substances (other than marijuana), no longer receiving care at a VA facility, or other. Patient demographic characteristics, clinical characteristics, and other factors were evaluated as secondary outcomes.
Statistical Analysis R Statistical Software (R version 3.2.5, The R Foundation for Statistical Computing, Vienna, Austria) was used in the analysis of disease state diagnoses and patient characteristics. Analyses were conducted using generalized linear mixed-effects models with a random effect for facility to account for the clustering of patients nested within facilities. The models controlled for variability in average facility outcome to give an overall estimate of patient outcome in the average facility. Odds ratios (ORs) were used to describe the results and likelihood of the binary outcome of being a treatment candidate given a diagnosed disease state or patient characteristic. An a priori significance threshold was set at 0.05 with a 95% CI. Descriptive statistics were used to examine the primary and secondary outcomes, with results expressed as percentages and means or medians. In each cohort, patients were categorized into those with platelet counts o150,000/mL and Fib-4 scores 43.25 as both laboratory thresholds are associated with advanced disease. Analysis of patient characteristics was conducted using the t test or Mann-Whitney rank sum test for differences in mean (normally distributed data) or median (data failing normality testing) values between treatment eligible and treatment ineligible cohorts. The χ2 was used to examine differences for patients in each cohort with platelet counts o150,000/mL or Z150,000/mL and Fib-4 scores r3.25 or 43.25.
RESULTS Between August and November 2015, a total of 1003 patients from 5 medical centers within VISN 21 were reviewed and included in this analysis. Patient
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J. Taylor et al. characteristics and demographics in the treatment and nontreatment candidate cohorts are summarized in Table I. The median FIB-4 score was significantly higher in the nontreatment candidate cohort compared with the treatment candidate cohort (4.4 vs 3.8, P o .001). In this predominately male population, 625 (62%) had a calculated FIB-4 score 43.25, indicating ALD. Significantly more patients with ALD were in the nontreatment candidate cohort (66% vs 59% P ¼ 0.0198). Other characteristics were not statistically significantly different between the treatment candidate and noncandidate cohorts. For the primary outcome, 478 (48%) patients were determined by clinical review to meet HCV treatment criteria. Of the 525 patients (52%) who were not eligible for treatment, the most common reasons for treatment ineligibility were unstable or uncontrolled comorbidity (n ¼ 118), excessive alcohol use (n ¼ 116), and patient refusal of treatment (n ¼ 69) (Table II). Generalized linear mixed-model output for potential predictors of treatment eligibility status are reported in Table III. Patient characteristics and pertinent diagnoses encountered within 1 year of candidate status determination were analyzed. The ORs that were o1 indicated an association with being treatment ineligible. The ORs that were 41 were
indicative of treatment eligibility. Diagnoses of active alcohol use disorder (OR ¼ 0.68; 95% CI, 0.47–0.98; P ¼ 0.038), hepatocellular carcinoma (OR ¼ 0.24; 95% CI, 0.13–0.47; P o 0.001), and a palliative care encounter (OR ¼ 0.21; 95% CI, 0.05–0.99; P ¼ 0.049) were statistically significant predictors of treatment ineligibility. A diagnosis of PTSD (OR ¼ 1.48; 95% CI, 1.01–2.18; P ¼ 0.046) was a statistically significant positive predictor of treatment eligibility. Other diagnoses, including HIV, depression, dementia, bipolar disorder, and schizophrenia, and a homelessness encounter were not statistically significant predictors. Because the median FIB-4 score was significantly higher in the nontreatment candidate cohort compared with the treatment candidate cohort, a second linear mixed model was developed that controlled for a FIB-4 score 43.25. In that model, hepatocellular carcinoma (OR ¼ 0.23; 95% CI, 0.11–0.50; P o 0.001) was the only predictor of treatment ineligibility.
DISCUSSION Previous studies characterizing treatment of veterans with HCV were performed before the approval of the directacting antivirals simeprevir/sofosbuvir, ledipasvir/sofosbuvir, and ombitasvir/paritaprevir/ritonavir/dasabuvir.
Table I. Patient demographic characteristics in the treatment candidate and nontreatment candidate cohorts. Characteristic Age, mean (range), y Male, No. (%) FIB-4 score, median (range)† FIB-4 score 43.25, No. (%)† MELD score, median (range) Platelet count, median (range), /mL (in thousands) Platelet count o150,000/mL, No. (%) Serum creatinine, median (range), mg/dL
Treatment Candidates (n ¼ 478)* 65 473 3.8 280 8.65 142
(46–93) (99) (1–35) (n ¼ 454) (59) (6–27) (n ¼ 281) (17–343) (n ¼ 457)
269 (57) 0.9 (0.5–10) (n ¼ 462)
Nontreatment Candidates (n ¼ 525)* 64 515 4.4 343 8.75 132
P
(39–95) (98) (1–20) (n ¼ 485) (66) (6–30) (n ¼ 314) (29–434) (n ¼ 487)
0.581 0.2571 o0.001 0.0198 0.166 0.127
306 (59) 0.9 (0.4–10) (n ¼ 490)
0.5723 0.448
FIB-4 ¼ Fibrosis 4; MELD ¼ Model for End-Stage Liver Disease. * Sample size is reported if characteristic data were missing. † Statistically significant P o 0.05.
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Table II. Reasons for treatment ineligibility reported by clinical provider. No. (%) of Veterans (n ¼ 525)
Identified Barrier to Treatment Unstable or uncontrolled comorbidity Excessive alcohol use Refusing treatment Further workup and evaluation pending No longer receiving care at Veterans Affairs medical center Active illicit substance use (excluding marijuana) Limited life expectancy Documented ongoing nonadherence Unable to contact Other comments No medication option currently available Severe renal impairment
118 116 69 38 35 33 31 28 23 17 14 3
(22) (22) (13) (7) (7) (6) (6) (5) (4) (3) (3) (1)
Table III. Predictors of treatment eligibility using generalized linear mixed model. ICD-9 or ICD-10 Codes for Encounters in Previous 12 Months No. of Veterans Predictors of treatment eligible and ineligible status Intercept Predictors of treatment ineligibility Palliative care encounter† Hepatocellular carcinoma† Alcohol abuse† Bipolar disorder Substance abuse Dementia Psychiatric disorder diagnosis (unspecified) Homelessness encounter Depression Predictors of treatment eligibility HCV treatment naïve Nicotine use PTSD diagnosis† Marijuana use Schizophrenia diagnosis HIV coinfection
1003
OR (95% CI)* 0.57 (0.08–3.86)
P 0.562
18 38 209 14 356 20 94 242 228
0.21 0.24 0.68 0.69 0.78 0.79 0.80 0.82 0.91
(0.05–0.99) 0.049 (0.13–0.47) o0.001 (0.47–0.98) 0.038 (0.35–1.37) 0.291 (0.54–1.13) 0.193 (0.32–1.95) 0.605 (0.48–1.33) 0.391 (0.58–1.14) 0.238 (0.63–1.29) 0.583
897 109 164 55 36 17
1.33 1.38 1.48 1.79 1.91 2.03
(0.85–2.10) (0.89–2.13) (1.01–2.18) (0.95–3.36) (0.93–3.93) (0.69–5.98)
0.214 0.149 0.046 0.071 0.080 0.200
HCV ¼ hepatitis C virus; ICD-9 ¼ International Classification of Diseases, Ninth Revision; ICD-10 ¼ International Classification of Diseases, Tenth Revision; OR ¼ odds ratio; PTSD ¼ posttraumatic stress disorder. * ORs 41 are predictive of treatment eligibility, and ORs o1 are predictive of treatment ineligibility. † Statistically significant P o 0.05.
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J. Taylor et al. A systematic review that examined prevalence and treatment of chronic HCV in veterans noted that up to 58% of VA patients had contraindications to the standard, peg-interferon regimens of that era.2 Although newer medications have greater efficacy and fewer contraindications, 4% of our population had no appropriate medication option because of severe renal dysfunction, contraindicated drug interaction, or resistant strains and are thus awaiting the availability of new therapies. Gundlapalli et al12 evaluated characteristics of a HCV veteran cohort between 2004 and 2009 and found lower rates of treatment were associated with age 450 years and history of drug abuse. The mean age in our analysis was 65 years, and no statistically significant effect of age was seen in treatment eligibility status. Gundlapalli also found the treatment rate in homeless veterans with HCV was reportedly low; untreated homeless veterans were more likely to have a diagnosis of alcoholism, drug abuse, tobacco use, or mental health–related condition, such as depression, anxiety, or psychosis.12 The US Department of Veterans Affairs State of Care for Veterans With Hepatitis C 2014 report noted an increase in the diagnosis of PTSD and depression by 33%, bipolar disorder by 30%, and anxiety by 28% in the HCVinfected veteran population between 2002 and 2013. History or presence of alcohol use disorder was also noted among 55% of HCV viremic veterans.3 Within our population, the presence of PTSD was positively correlated with treatment eligibility. It is conceivable that veterans with PTSD were more engaged with the health system or mental health services, which may affect treatment eligibility. No difference was seen in treatment eligibility for other mental health disorders or a status of homelessness; however, the study was not powered to evaluate these differences. Because of high medication costs, health systems, including the VA, initially focused on treating patients with higher levels of fibrosis. In our population, most had ALD defined by a FIB-4 score 43.25. Other means to identify ALD, including liver biopsy or transient elastography results, were not routinely available and thus not used in our analysis. The median FIB-4 scores were statistically significantly higher in the treatment-ineligible group (P o 0.001), possibly related to the presence of uncontrolled comorbidities, such as hepatocellular carcinoma, excessive alcohol use, and limited life expectancy present in that cohort. When controlling for FIB-4
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score 43.25, the linear mixed model did not identify palliative care or active alcohol use disorder as predictors of treatment ineligibility. Patients with active alcohol use disorder may be more likely to have elevated FIB-4 scores, which may explain the different results found by the 2 mixed linear models. Although patients with ALD were initially prioritized for treatment, current evidence supports the VA’s expansion of treatment to patients regardless of current fibrosis status.13 Cost-effectiveness evaluations have been conducted comparing the costs of treating all patients to treating only those with ALD. Chahal et al7 conducted a cost and health care outcome analysis using total medical costs, quality-adjusted life-years (QALYs), and incremental costeffectiveness ratios (ICERs) to compare treatment of all patients with HCV to treatment of patients with advanced fibrosis stages F3 and F4 using Metaanalysis of Histological Data in Viral Hepatitis. Treating all patients is associated with an ICER of $39,475 per QALY whereby an ICER of r$50,000 per QALY is considered highly cost-effective. In a separate analysis using Markov modeling in a Medicaid population, treating all patients compared with treating those with ALD resulted in cost savings in 93% of models attributable to mitigating complications, such as hepatocellular carcinoma and liver transplantation.15 Although the upfront cost of treating patients with hepatitis C is high, the potential to prevent long-term clinical problems and improve patients’ quality of life is justifiable. In our population, more than half were classified as ineligible to receive treatment on initial clinical review. When considering the types of barriers to treatment, it is important to distinguish those that may change over time. Some criteria for ineligibility, such as limited life expectancy, are unlikely to change. However, a large number of the patients identified as treatment ineligible may have barriers that could be resolved with appropriate management and resources. The most prevalent potentially reversible barrier in our cohort was ongoing excessive alcohol use, which has been noted as a patient factor for treatment ineligibility in previous studies.3,12,14 Along with substance use disorder, this may be a modifiable barrier addressed by establishing formalized referral processes to substance use disorder programs or mental health care providers.
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Clinical Therapeutics Other barriers, such as uncontrolled comorbid disease states, should also be further investigated and addressed if feasible. Treatment guidelines provide strategies to address common barriers to treatment, including counseling, education, referrals, and providing care in a multidisciplinary care setting. These guidelines clarify that prescreening for illicit drug or alcohol use is not useful in predicting successful completion of HCV therapy and will likely reduce consideration of these factors as barriers to treatment in the future.13,16
Limitations This analysis was dependent on the accuracy and completeness of documentation within the electronical medical record and on the HCV dashboard tracking tool. Although use of the VISN 21 HCV clinical dashboard is widely accepted within the network, its use is not a requirement for all providers. Thus, it is possible that documentation for all patients undergoing clinical evaluation was not captured. Multiple providers and multiple sites were responsible for making clinical determinations and for documentation; thus, reporting bias could exist because of lack of a standardized approach among all providers. Attempts to minimize variation included the development of a dropdown menu to categorize findings from the clinical review. This project analyzed clinical evaluation for treatment eligibility but did not conduct follow-up to see what percentage of treatment-eligible veterans received drug therapy. This project did not reevaluate veterans who were initially categorized as ineligible for HCV treatment to assess whether the candidate status changed. Thus, the number of veterans with potentially modifiable barriers to treatment likely overestimates the number who would actually be treated in the future. Lastly, this project did not conduct pharmacoeconomic analysis related to changes to treatment eligibility classification.
CONCLUSIONS Results of this study identified that a large percentage of HCV infected veterans, most of whom had ALD, may not be treatment eligible on initial clinical review. Within this population, the presence of other uncontrolled comorbidities and ongoing excessive alcohol use were the most commonly reported reasons for being treatment ineligible. On the basis of this
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analysis, resources should be focused on changing modifiable barriers to treatment to optimize the number of veterans receiving curative HCV medication.
ACKNOWLEDGMENTS We acknowledge Julio Lopez, PharmD, Chief of Pharmacy Services at the Northern California Veteran’s Affairs Healthcare System, for his contributions to the characteristic statistical analyses. We also extend acknowledgement to all the VISN 21 hepatitis C treatment teams who provide outstanding care to our veterans.
CONFLICTS OF INTEREST The authors have indicated that they have no conflicts of interest regarding the content of this article.
REFERENCES 1. Centers for Disease Control and Prevention. Disease burden from viral hepatitis A, B, and C, in the United States. 2013. http://www.cdc.gov/hepatitis/HCV/Statis ticsHCV.htm. Accessed September 1, 2015. 2. Beste L, Ioannou G. Prevalence and treatment of chronic hepatitis C virus infection in the US Department of Veterans Affairs. Epidemiol Rev. 2015;37:131–143. 3. U.S. Department of Veterans Affairs. State of Care for Veterans with Hepatitis C 2014. http://www.cdc.gov/ hepatitis/HCV/StatisticsHCV.htm. Accessed September 1, 2015. 4. United States Department of Veterans Affairs. HCV registry Veterans in VHA care in 2014, for the nation, by VISN and by station, May 2015. http://vaww.hepatitis.va. gov/data-reports/ccr2014/Demo-HCV3PopInCare-Jan15HCV-2014-All.asp. Accessed September 1, 2015. 5. Sebastiani G, Gkovatsos K, Pantopoulos K. Chronic hepatitis C and liver fibrosis. World J Gastroenterol. 2014;20:11033–11053. 6. World Health Organization. Hepatitis C key facts. July 2015. http://www.who.int/mediacentre/factsheets/fs164/en/. Accessed September 1, 2015. 7. Chahal H, Marseille E, Tice J, et al. Cost-effectiveness of early treatment of hepatitis c virus genotype 1 by stage of liver fibrosis in a US treatment-naïve population. JAMA Intern Med. 2016;176:65–73. 8. Tapper E, Catana A, Sethi N, et al. Direct costs of care for hepatocellular carcinoma in patients with hepatitis C cirrhosis. Cancer. 2016;122:852–858. 9. United States Department of Veterans Affairs. HCV viremic Veterans in VHA care in 2014 with first or ever
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VHA diagnosis of cirrhosis/ALD by ICD-9 in the year for the Nation, by VISN and by station. http://vaww. hepatitis.va.gov/dat a-r epor ts/ ccr2014/Cond-DxGrpFirstEverInCar e-Jan15-HCVVir-CCRALD-2014-All. asp. Accessed September 1, 2015. AASLD/IDSA/IAS–USA. Recommendations for testing, managing, and treating hepatitis C. http://www.hcvgui delines.org. Accessed September 1, 2015. United States Department of Veterans Affairs. Chronic hepatitis C virus (HCV) infection: treatment considerations from the Department of Veterans Affairs national hepatitis C resource center program and the Office of Public Health. http:// vaww.hepatitis.va.gov/pdf/treat ment-considerations-2015-07.pdf. Accessed on September 1, 2015. Gundlapalli A, Nelson R, Haroldsen C, et al. Correlates of initiation of treatment for chronic hepatitis C infection in United States Veterans, 2004-2009. PLoS ONE. 2015;10:e0132056. AASLD-IDSA. Recommendations for testing, managing, and treating hepatitis C. http://www.hcvguidelines. org. Accessed on August 1, 2016. Cachay E, Hill L, Wyles D, et al. The hepatitis C cascade of care among HIV infected patients: A call to address ongoing barriers to care. PLoS ONE. 2014;9:e102883. Chidi A, Bryce C, Donohue J, et al. Economic and public health impacts of policies restricting access to hepatitis C treatment for medicaid patients. Value Health. 2016 326–334. United States Department of Veterans Affairs. Chronic hepatitis C virus (HCV) infection: Treatment considerations from the Department of Veterans Affairs national hepatitis C resource center program and the Office of Patient Care Services. http://www.hepatitis.va.gov/pro vider/guidelines/hcv-treatment-consid erations.pdf. Accessed on August 1, 2016.
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Address correspondence to: Janice Taylor, PharmD, BCPS, 975 Kirman Avenue, Reno, NV 89502. E-mail:
[email protected]
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