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IIR 07-111 – HSR Study

 
IIR 07-111
Quality of Care Among Patients with Chronic Hepatitis C Virus Infection
Fasiha Kanwal, MD MSHS
St. Louis VA Medical Center John Cochran Division, St. Louis, MO
St Louis, MO
Funding Period: April 2008 - March 2011
BACKGROUND/RATIONALE:
The quality of care for veterans with chronic hepatitis C virus (HCV) infection is unclear. Data show deficiencies in HCV care. As a result, quality improvement efforts are needed. Key tasks before such efforts can be initiated include development of a HCV quality assessment tool, and evaluation of the extent and sources of deviations from best practices.

OBJECTIVE(S):
The objectives were to: (1) operationalize expert panel derived HCV quality indicators (QIs) into electronic data algorithms; (2) determine the QI adherence rate in a cohort of HCV patients using the VA HCV Registry; (3) validate the adherence rate from the Registry against rates from chart reviews in 1200 patients; (4) identify predictors of QI adherence at patient, provider, and facility levels. We also examined the effect of integrated care on HCV processes and outcomes, as part of a project modification.


METHODS:
We defined the exclusion/inclusion criteria and identified data elements to derive 24 HCV-specific QIs measuring pre-treatment (n=7), treatment (n=10), and preventive/comorbid condition (n=7) care. We calculated the QI adherence rate in a cohort of HCV patients enrolled in the national VA HCV Clinical Case Registry between 2000 and 2006.

We reviewed the electronic medical record of a random sample of HCV patients seeking care in 4 VA medical centers, and compared the agreement between registry and medical record in correctly identifying eligible patients (denominator) and recipients of indicated care (numerator) for each measure. We also conducted a structured review of charts for cases who failed a QI to determine the proportion of patients who had a valid exception to the measure.

We conducted multivariable hierarchical regression models to determine patient, provider, and facility-level predictors of QI adherence. Patient factors included demographics (age, race), comorbidity (Deyo index, depression, alcohol and/or substance use disorder), and healthcare utilization (visits/quarter). We assigned each patient a primary provider with whom the patient was seen most frequently. We defined primary provider's HCV panel as the total number of HCV patients seen by the provider. We used a national VA Clinical Practice Organizational Survey to obtain information regarding facility-level factors including region, academic affiliation, presence of onsite specialists, proximity of primary care to specialty clinics, and facilities' emphasis on quality improvement in HCV as measured by the number of existing HCV-specific quality improvement efforts (none, 1-3, >4) at each of the VA facilities.

Last, we used the 2007 Clinician Survey to Assess Hepatitis C Care in VHA to obtain data on the level of integrated/comprehensive care. We classified the facilities into 4 levels of integrated/comprehensive care based on the number of on-site providers and services associated with the HCV clinics (the higher the level, the more comprehensive the care). We then examined the effect of integrated care on antiviral treatment receipt, treatment completion, and sustained virological response (SVR) in our cohort of patients with HCV

FINDINGS/RESULTS:
Our study included 122,744 patients with HCV enrolled in the registry between 2000 and 2006. The QI success rates varied. For example, 75% of eligible patients met HCV genotype testing, 28% met liver biopsy, 27% met antiviral treatment, and 16% met hepatitis A vaccination QI.

In a sample of 717 chart review patients, we found excellent agreement between the registry and medical records in all measures (agreement coefficients >0.75). However, exceptions to indicated care documented only in medical records were common for HCV genotype testing, liver biopsy, and antiviral treatment. After accounting for these exceptions, the QI rates increased from 75% to 93% for genotype testing, 28% to 49% for liver biopsy, and 27% to 62% for antiviral treatment in genotype 1 HCV patients. Treatment contraindications were the most common reasons for not meeting indicated care.

In the multivariable model, younger age, higher Deyo index, presence of depression, and greater healthcare utilization were associated with higher quality scores. In contrast, African American race and diagnosis of drug and/or alcohol use were associated with lower quality. Patients seen by primary providers with larger HCV panels received lower quality than those seen by providers with smaller panels. The odds of receiving better quality were 2-fold higher for patients who were seen in facilities with greater emphasis on HCV quality improvement than for patients seen at facilities with no emphasis. Compared to the patients seen in the South, those seen in the Mid-Atlantic region of the U.S. were less likely to receive higher quality care. Other facility-level factors were not associated with quality of HCV care.

We found no significant associations in the rates of antiviral treatment initiation, antiviral treatment completion, and SVR across the facilities with different levels of integrated care/comprehensiveness. For example, the rates of treatment initiation were 22% at facilities of level I, 25% at facilities of level II, 22% at facilities of level III, and 21% at facilities of level IV. In addition, the rates of SVR were 29% at facilities of level I, 34% at facilities of level II, 29% at facilities of level III, and 29% at facilities of level IV. These results did not change after accounting for patient demographic, clinical, and healthcare utilization factors

IMPACT:
We developed a structured quality assessment tool in HCV capturing relevant domains of HCV care. We have found that automated data sources alone appear to miss several exceptions to care that are documented only in providers' notes, thus underestimating certain HCV QIs. Efforts to measure quality of care in HCV will need to record exceptions in order to improve accuracy of such measurement in the VA. However, after accounting for automated data and medical record reviews, vaccinations, liver biopsy, and antiviral treatment rates in patients with genotype 1 HCV left room for improvement.

Our results support focusing quality improvement efforts on older and African American patients. We also found that a facility's emphasis on quality improvement in HCV was associated with higher-quality HCV care. However, integration of care was not associated with patient treatment outcomes in HCV, perhaps due to lack of a functioning collaborative relationship. This project also provided the foundation for developing interventions to increase the rate of hepatitis C confirmatory testing in the VA


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PUBLICATIONS:

None at this time.


DRA: Health Systems, Infectious Diseases
DRE: Epidemiology, Diagnosis
Keywords: Hepatitis C, Quality assessment, Utilization patterns
MeSH Terms: none

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