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The American Journal of Managed Care August 2018
Impact of a Medical Home Model on Costs and Utilization Among Comorbid HIV-Positive Medicaid Patients
Paul Crits-Christoph, PhD; Robert Gallop, PhD; Elizabeth Noll, PhD; Aileen Rothbard, ScD; Caroline K. Diehl, BS; Mary Beth Connolly Gibbons, PhD; Robert Gross, MD, MSCE; and Karin V. Rhodes, MD, MS
Choosing Wisely Clinical Decision Support Adherence and Associated Inpatient Outcomes
Andrew M. Heekin, PhD; John Kontor, MD; Harry C. Sax, MD; Michelle S. Keller, MPH; Anne Wellington, BA; and Scott Weingarten, MD
Precision Medicine and Sharing Medical Data in Real Time: Opportunities and Barriers
Y. Tony Yang, ScD, and Brian Chen, PhD, JD
Levers to Reduce Use of Unnecessary Services: Creating Needed Headroom to Enhance Spending on Evidence-Based Care
Michael Budros, MPH, MPP, and A. Mark Fendrick, MD
From the Editorial Board: Michael E. Chernew, PhD
Michael E. Chernew, PhD
Optimizing Number and Timing of Appointment Reminders: A Randomized Trial
John F. Steiner, MD, MPH; Michael R. Shainline, MS, MBA; Jennifer Z. Dahlgren, MS; Alan Kroll, MSPT, MBA; and Stan Xu, PhD
Impact of After-Hours Telemedicine on Hospitalizations in a Skilled Nursing Facility
David Chess, MD; John J. Whitman, MBA; Diane Croll, DNP; and Richard Stefanacci, DO
Baseline and Postfusion Opioid Burden for Patients With Low Back Pain
Kevin L. Ong, PhD; Kirsten E. Stoner, PhD; B. Min Yun, PhD; Edmund Lau, MS; and Avram A. Edidin, PhD
Patient and Physician Predictors of Hyperlipidemia Screening and Statin Prescription
Sneha Kannan, MD; David A. Asch, MD, MBA; Gregory W. Kurtzman, BA; Steve Honeywell Jr, BS; Susan C. Day, MD, MPH; and Mitesh S. Patel, MD, MBA, MS
Currently Reading
Evaluating HCV Screening, Linkage to Care, and Treatment Across Insurers
Karen Mulligan, PhD; Jeffrey Sullivan, MS; Lara Yoon, MPH; Jacki Chou, MPP, MPL; and Karen Van Nuys, PhD
Medicare Advantage Enrollees’ Use of Nursing Homes: Trends and Nursing Home Characteristics
Hye-Young Jung, PhD; Qijuan Li, PhD; Momotazur Rahman, PhD; and Vincent Mor, PhD

Evaluating HCV Screening, Linkage to Care, and Treatment Across Insurers

Karen Mulligan, PhD; Jeffrey Sullivan, MS; Lara Yoon, MPH; Jacki Chou, MPP, MPL; and Karen Van Nuys, PhD
An optimized hepatitis C virus screening and linkage-to-care process reduces the number of patients lost to follow-up and improves linkage to care for Medicare, Medicaid, and commercially insured patients.
DISCUSSION

Comparing baseline, reflex, and consolidated results shows the value of streamlining the SLTC process. Collapsing baseline to reflex reduces the number of patients lost prior to receiving a treatment recommendation by 62% to 66%. Further streamlining to consolidated reduces the number lost by 92% to 95%. Because the Medicaid population has the most inefficient SLTC process to begin with, it experiences the largest improvements from streamlining the process.

Although our analysis focuses on the number of visits as a measure of SLTC process efficiency, the underlying prevalence in a given population also plays an important role in the process. For example, although the Medicaid subpopulation loses the most patients, it also has the highest Ab+ prevalence (16%), resulting in higher yield versus the commercial population. Moreover, in consolidated, only 20 additional Medicaid patients need to be screened on average to get 1 additional chronically infected patient into treatment compared with 100 additional patients screened to achieve the same result in the commercial population.

Our findings are consistent with those of a recently published study of the care continuum for patients with HCV diagnosed in 2 urban emergency departments.21 In the study, the Medicaid process was less efficient, with only 8.5% of RNA-positive patients initiating treatment compared with 12% of Medicare patients. Additionally, 82% of Ab+ patients completed viral load testing, similar to our finding of approximately 80% of patients progressing to RNA testing. Generally, the literature presents conditional yield rather than yield; conditional yield estimates range from 3.9% to 24%.11,14,22-24 Our baseline conditional yields (3.7%-9.5%) are on the lower end compared with recent studies. Our baseline Ab+ conditional yields (eAppendix) range from 2.7% to 7.5%, which is consistent with findings from 2 recent studies (3.3% and 4.0%).25,26

Not surprisingly, total costs increase dramatically from baseline to reflex and consolidated, because more patients receive treatment. This paper is not intended as a cost-benefit exercise, nor do we model other medical expenditures for patients with HCV. However, the increased treatment costs are arguably of high value because identifying and treating more patients will provide benefits associated with reduced transmission rates, long-term cost savings on medical expenditures related to untreated HCV, and a reduction in liver transplants.27-29

Reducing the number of patients lost decreases screening costs per person treated because the total system costs are spread among more patients. This aligns with prior literature showing that expanded HCV screening provides the most value when coupled with expanded treatment.30 Additionally, there are costs associated with the SLTC process that are difficult to measure (eg, patient navigation, social work) and are not included in our analysis. It is likely that Medicaid patients would benefit most from these services and incur additional costs, but this population also experiences the greatest gains from reflex and consolidated.

For all insurance types, a majority of patients are lost prior to visiting a specialist, which suggests that having insurance does not eliminate inefficiencies associated with multiple visits required in the SLTC process. Although our 3 scenarios focus on streamlining the SLTC process prior to treatment recommendation, barriers to treatment exist in later stages of the process. Specifically, PA poses a significant barrier for patients who are prescribed treatment, particularly in the Medicaid and commercial populations. Of patients who seek PA, 46% and 55% of Medicaid and commercial patients, respectively, are denied, whereas only 13% of Medicare patients are denied.

A patient who is denied PA is comparable with one who is lost, and for patients who are eventually denied, streamlining the process simply delays the point at which they are lost. This delay increases overall costs from screening and time spent in the process but does not change the disease outcome because treatment is not received. Consequently, to maximize the number of patients treated, barriers to treatment must be reduced.


 
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