Quantifying the Value of Reduced Health Disparities: Low-Dose Computed Tomography Lung Cancer Screening of High-Risk Individuals Within the United States

OBJECTIVE

This study aimed to measure the value of increasing lung cancer screening rates for high-risk individuals and its impact on health disparities.

METHODS

The model estimated changes in health economic outcomes if low-dose computed tomography screening increased from current to 100% compliance, following clinical guidelines. Current low-dose computed tomography screening rates were estimated by income, education, and race, using 2017-2019 Behavioral Risk Factor Surveillance System data. The model contained a decision tree module to segment the population by screening outcomes and a Markov chain module to estimate cancer progression over time. Model parameters included information on survival, quality of life, and costs related to cancer diagnosis, treatment, and adverse events. Distributional cost-effectiveness analysis estimated the net monetary value from reduced health disparities-measured using quality-adjusted life expectancy-across income, education, and race groups. Outcomes were assessed over 30 years.

RESULTS

Lung cancer screening eligibility using US Preventive Services Task Force guidelines was higher for individuals with income <$15 000 (47.2%) and without a high-school education (46.1%) than individuals with income >$50 000 (16.6%) and with a college degree (13.5%), respectively. Increasing lung cancer screening to 100% compliance was cost-effective ($64 654 per quality-adjusted life-year) and produced economic value by up to $560 per person ($182.1 billion for United States overall). Up to 32.2% of the value was due to reductions in health disparities.

CONCLUSIONS

Significant value in increasing lung cancer screening rates derived from reducing health disparities. Policy makers and clinicians may not be appropriately prioritizing cancer screening if value from reducing health disparities is unconsidered.

Treatment Patterns and Healthcare Resource Utilization of Patients With Paroxysmal Nocturnal Hemoglobinuria: A Retrospective Claims Data Analysis

Paroxysmal nocturnal hemoglobinuria (PNH) is a rare, acquired hematologic disorder commonly treated with complement inhibitors such as eculizumab, ravulizumab, and pegcetacoplan. This study aims to describe treatment patterns, healthcare resource utilization, and cost for newly diagnosed PNH patients in 2 large, health insurance claims databases: MarketScan and Optum. Among the 271 patients meeting the inclusion criteria in MarketScan, 57.9% were female, and the average age was 46.6 years. Among these newly diagnosed patients, 25.1% (n = 68) of patients received a PNH-specific pharmacologic treatment, and the average time from diagnosis to treatment was 4.7 months. The medication possession ratio was 97.0%, but discontinuation was common (58.8%). The average per-patient-per-month costs were $18,978, driven by pharmacy and infusion ($11,182), outpatient ($4086), and inpatient ($3318) costs. Despite the availability of multiple treatments, 39.9% of patients had an inpatient stay, and 50.9% had an emergency department visit. Better care management and the introduction of new treatment options are needed to address delays between diagnosis and treatment, and high rates of hospitalization and emergency department use among patients with PNH.

Use of Conditionally Essential Amino Acids and the Economic Burden of Postoperative Complications After Fracture Fixation: Results from a Cost Utility Analysis

Objective

To measure the economic impact of conditionally essential amino acids (CEAA) among patients with operative treatment for fractures.

Methods

A decision tree model was created to estimate changes in annual health care costs and quality of life impact due to complications after patients underwent operative treatment to address a traumatic fracture. The intervention of interest was the use of CEAA alongside standard of care as compared to standard of care alone. Patients were required to be aged ≥18 and receive the surgery in a US Level 1 trauma center. The primary outcomes were rates of post-surgical complications, changes in patient quality adjusted life years (QALYs), and changes in cost. Cost savings were modeled as the incremental costs (in 2022 USD) of treating complications due to changes in complication rates.

Results

The per-patient cost of complications under CEAA use was $12,215 compared to $17,118 under standard of care without CEAA. The net incremental cost savings per patient with CEAA use was $4902, accounting for a two-week supply cost of CEAA. The differences in quality-adjusted life years (QALYs) under CEAA use and no CEAA use was 0.013 per person (0.739 vs 0.726). Modeled to the US population of patients requiring fracture fixations in trauma centers, the total value of CEAA use compared to no CEAA use was $316 million with an increase of 813 QALYs per year. With a gain of 0.013 QALYs per person, valued at $150,000, and the incremental cost savings of $4902 resulted in net monetary benefit of $6852 per patient. The incremental cost-effectiveness ratio showed that the use of CEAA dominated standard of care.

Conclusion

CEAA use after fracture fixation surgery is cost saving. Level of Evidence: Level 1 Economic Study.

A Decade of Health Innovation: The Impact of New Medicines on Patient Health and the Implications for NICE's Size of Benefit Multiplier

OBJECTIVES

This study aimed to estimate the incremental health benefits of pharmaceutical innovations approved between 2011 and 2021 and the share that would surpass the National Institute for Health and Care Excellence (NICE) "size of benefit" decision weight thresholds.

METHODS

We identified all US-approved drugs between 2011 and 2021. Health benefits, in terms of quality-adjusted life-years (QALYs) for each treatment, were extracted from published cost-effectiveness analyses. Summary statistics by therapeutic area and cell/gene therapy status identified the treatments with the largest QALY gains.

RESULTS

The Food and Drug Administration approved 483 new therapies between 2011 and 2021 and of these 252 had a published cost-effectiveness analysis meeting our inclusion criteria. The average incremental health benefits produced by these treatments were 1.04 QALYs (SD = 2.00) relative to standard of care, with wide variation by therapeutic area. Pulmonary and ophthalmologic therapies produced the highest health benefits with 1.47 (SD = 2.17, n = 13) and 1.41 QALYs gained (SD = 3.53, n = 7), respectively; anesthesiology and urology had the lowest gains (< 0.1 QALYs). Cell and gene therapies produced an average health benefit that was 4 times greater than noncell and gene therapies (4.13 vs 0.96). Among the top treatments in terms of incremental QALYs gained, half (10 of 20) were oncology therapies. Three of 252 treatments (1.2%) met NICE's threshold for a "size of benefit" multiplier.

CONCLUSIONS

Treatments for rare disease, oncology, and cell and gene therapies produced some of the highest level of health innovation relative to previous standard of care, but few therapies would have qualified for NICE's "size of benefit" multiplier as currently constructed.

Economic burden of antibiotic-not-susceptible isolates in uncomplicated urinary tract infection: Analysis of a US integrated delivery network database

Background

Uncomplicated urinary tract infections (uUTIs) are one of the most common bacterial infections in the United States (US). Contemporary data are important for understanding the health economic impact of antimicrobial-resistant uUTIs. We compared the economic burden among patients with uUTI isolates susceptible or not-susceptible to the initial antibiotic prescription.

Methods

This retrospective cohort study utilized electronic health record data (1 July 2016–31 March 2020) from a large Mid-Atlantic US integrated delivery network database. Patients were females aged ≥ 12 years with a uUTI, who received oral antibiotic treatment and had ≥ 1 urine culture within ± 5 days of diagnosis. The primary outcome was the difference in healthcare resource use and costs (all-cause, urinary tract infection [UTI]-related) among patients with susceptible versus not-susceptible isolates during the 6 months after the index uUTI diagnosis. Secondary outcomes included: pharmacy costs, hospital admissions and emergency department visits, as well as the probability of uUTI progressing to complicated UTI (cUTI) between patients with susceptible and not-susceptible isolates. Patient outcomes were compared using 1:1 propensity score matching. Winsorized costs were adjusted to 2020 quarter 1 US dollars ($).

Results

A total of 2565 patients were eligible for analysis. The propensity score-matched sample comprised 2018 patients, with an average age of 44.0 and 41.0 years for the susceptible and not-susceptible populations, respectively. In the 6 months post-index uUTI event, patients with not-susceptible isolates had significantly more all-cause prescriptions orders (+ 1.41 [P = 0.001]), UTI-related prescriptions orders (+ 0.26 [P < 0.001]) and a higher probability of all-cause inpatient (+ 1.4% [P = 0.009]), outpatient (+ 6.1% [P = 0.006]), or UTI-related outpatient (+ 3.7% [P = 0.039]) encounters. Patients with a uUTI and an antibiotic-not-susceptible isolate were significantly more likely to progress to cUTI than those with susceptible isolates (odds ratio: 2.35 [confidence interval: 1.66–3.33; P < 0.001]). Over 6 months, patients with not-susceptible versus susceptible isolates had significantly higher all-cause costs (+ $426 [P = 0.031]) and UTI-related costs (+ $157 [P = 0.034]).

Conclusions

Patients with a uUTI caused by antibiotic-not-susceptible isolates had higher healthcare resource usage, costs, and increased likelihood of progressing to cUTI than those with antibiotic-susceptible isolates.

Impact of suboptimal or inappropriate treatment on healthcare resource use and cost among patients with uncomplicated urinary tract infection: an analysis of integrated delivery network electronic health records

Background

Although uncomplicated urinary tract infections (uUTIs; occurring in female patients without urological abnormalities or history of urological procedures or complicating comorbidities) are one of the most common community infections in the United States (US), limited data are available concerning associations between antibiotic resistance, suboptimal prescribing, and the economic burden of uUTI. We examined the prevalence of suboptimal antibiotic prescribing and antibiotic resistance and its effects on healthcare resource use and costs.

Methods

This retrospective cohort study utilized electronic health record data from a large Mid-Atlantic US integrated delivery network database, collected July 2016–March 2020. Female patients aged ≥ 12 years with a uUTI, who received ≥ 1 oral antibiotic treatment within ± 5 days of index uUTI diagnosis, and had ≥ 1 urine culture with antimicrobial susceptibility test, were eligible for inclusion in the study. The study examined the proportion of antibiotics that were inappropriately or suboptimally prescribed among patients with confirmed uUTI, and total healthcare costs (all-cause and UTI-related) within 6 months after a uUTI, stratified by antibiotic susceptibility and/or inappropriate or suboptimal treatment. Patient outcomes were assessed after 1:1 propensity score matching of patients with antibiotic-susceptible versus not-susceptible isolates and then by other covariates (e.g., demographics and recent healthcare use). A similar propensity score calculation was used to analyze the effect of inappropriate/suboptimal treatment on health outcomes. Costs were adjusted to 2020 US dollars ($).

Results

Among 2565 patients with a uUTI included in the analysis, the most commonly prescribed antibiotics were nitrofurantoin (61%), trimethoprim-sulfamethoxazole (19%), and ciprofloxacin (15%). More than one-third of the sample (40.2%) had isolates that were not-susceptible to ≥ 1 antibiotic indicated for treating patients with uUTI. Two-thirds (66.6%) of study-eligible patients were prescribed appropriate treatment; 29.9% and 11.9% were prescribed suboptimal and/or inappropriate treatment, respectively. Inappropriate or suboptimally prescribed patients had greater all-cause and UTI-related costs compared with appropriately prescribed patients. Differences were most striking among patients with antibiotic not-susceptible isolates.

Conclusions

These findings highlight how the increasing prevalence of antibiotic resistance combined with suboptimal treatment of patients with uUTI increases the burden on healthcare systems. The finding underlines the need for improved prescribing accuracy by better understanding regional resistance rates and developing improved diagnostic tests.

Association of health care utilization and costs with patient-reported outcomes in patients with ankylosing spondylitis

BACKGROUND: Interventions for ankylosing spondylitis (AS) have improved patient-reported outcomes (PROs) in clinical studies. However, limited data exist associating these improvements with health care resource utilization (HCRU) or cost savings. Few studies have evaluated the economic impact of patient-reported physical status and related disease burden in patients with AS in the United States. OBJECTIVE: To assess the association of PRO measures with HCRU and health care costs in patients with AS from a national US registry. METHODS: This cohort study included adults with a diagnosis of AS enrolled in the FORWARD registry from July 2009 to June 2019 who completed at least 1 questionnaire from January 2010 to December 2019 and completed the Health Assessment Questionnaire Disability Index (HAQ-DI) (0-3) and/or Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) (0-10). Patient-reported data for demographics, clinical characteristics, and PROs were collected through questionnaires administered biannually and reported from the most recent questionnaire. Patient-reported HCRU and total health care costs (2019 US dollars) for hospitalizations, emergency department (ED) visits, outpatient visits, diagnostic tests, and procedures were captured during the 6 months prior to the most recent survey completion. The relationship between HAQ-DI or BASDAI and HCRU outcomes was assessed using negative binomial regression models, and the relationship between HAQ-DI or BASDAI and the cost outcomes was evaluated using generalized linear models with γ distribution and log-link function. RESULTS: Overall, 334 patients with AS who completed the HAQ-DI (n = 253) or BASDAI (n = 81) were included. The mean (SD) HAQ-DI and BASDAI scores at the time of patients' most recent surveys were 0.9 (0.7) and 3.7 (2.3), respectively. HAQ-DI score was positively associated with number of hospitalizations, ED visits, outpatient visits, and diagnostic tests, whereas BASDAI was not associated with HCRU outcomes. Overall annualized mean (SD) total health care, medical, and pharmacy costs for patients with AS were $44,783 ($40,595); $6,521 ($12,733); and $38,263 ($40,595), respectively. Annualized total health care, medical, and pharmacy costs adjusted for confounders increased by 35%, 76%, and 26%, respectively, for each 1.0-unit increase in HAQ-DI score (coefficient [95% CI]: 1.35 [1.15-1.58], 1.76 [1.22-2.55]; both P < 0.01 and 1.26 [1.04-1.52]; P < 0.05, respectively); BASDAI score was not significantly associated with cost outcomes. CONCLUSIONS: Higher HAQ-DI scores were associated with higher HCRU and total health care costs among patients with AS in FORWARD, but BASDAI scores were not. These findings indicate that greater functional impairment may impose an increased economic burden compared with other patient-reported measures of AS. DISCLOSURES: A. Ogdie has received consulting fees from Amgen, AbbVie, Bristol Myers Squibb, Celgene, CorEvitas (formerly Corrona), Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB and has received grant support from the National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases, Rheumatology Research Foundation, National Psoriasis Foundation, Pfizer (University of Pennsylvania), Amgen (FORWARD), and Novartis (FORWARD). M. Hwang has received consulting fees from Novartis and UCB and has received grant support (5KL2TR003168-03) from the University of Texas Health Science Center at Houston Center of Clinical and Translational Sciences KL2 program. P. Veeranki and J. Shafrin were employees of PRECISION-heor at the time of this analysis. A. Portelli and S. Sison are employees of PRECISION-heor. S. Pedro does not have anything to disclose. N. Kim was a postdoctoral fellow at the University of Texas at Austin and Baylor Scott and White Health, providing services to Novartis at the time of this study. E. Yi is an employee of Novartis. K. Michaud received grant funding from the Rheumatology Research Foundation at the time of this analysis. This study was funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ.

Health care utilization and costs associated with functional status in patients with psoriatic arthritis

BACKGROUND: The Health Assessment Questionnaire Disability Index (HAQ-DI) has been validated and widely used in psoriatic arthritis (PsA) clinical trials for the assessment of patient functional status. Significant improvements in the HAQ-DI have been reported in response to therapeutic interventions; however, few US studies have evaluated the economic impact of functional disability in patients with PsA. OBJECTIVE: To evaluate the association of functional status with health care resource utilization (HCRU) and total health care costs in US patients diagnosed with PsA. METHODS: This retrospective study included adult patients with PsA enrolled in FORWARD between July 2009 and June 2019 who completed 1 or more HAQ-DI questionnaires between January 2010 and December 2019. Patient demographics, clinical characteristics, and patient-reported outcomes were collected from the most recent questionnaire. HCRU and total health care costs (2019 US dollars) for all hospitalizations, emergency department (ED) visits, outpatient visits, diagnostic tests, and procedures were assessed for the 6 months prior to survey completion. Negative binomial regression models (HCRU outcomes) and generalized linear models with γ distribution and log-link function (cost outcomes) were used to assess the relationship between HAQ-DI and HCRU and cost outcomes, respectively. RESULTS: A total of 828 patients with PsA who completed HAQ-DI questionnaires were included. The mean (SD) age was 58.5 (13.5) years, 72.3% were female, and 92.3% were White. The mean (SD) disease duration was 17.5 (12.4) years, and the mean (SD) HAQ-DI score at the time of the patients' most recent questionnaire was 0.9 (0.7). More severe functional disability, measured by higher HAQ-DI score, was significantly associated with increased risk (incident rate ratio [95% CI]) of hospitalizations (1.68 [1.11-2.55]), ED visits (2.09 [1.47-2.96]), outpatient visits (1.14 [1.05-1.24]), and diagnostic tests (1.42 [1.16-1.74]). There was also a significant positive association between greater HAQ-DI score and increased total annualized health care costs (incremental amount [95% CI], 1.13 [1.03-1.23]) and medical costs (1.38 [1.13-1.69]), but there was no significant association found with pharmacy costs. Total adjusted average patient medical costs increased with increasing HAQ-DI score. CONCLUSIONS: Among patients with PsA enrolled in FORWARD, more functional disability-as measured by higher HAQ-DI scores-was associated with greater HCRU and increased total health care costs. These results suggest that improving functional status in patients with PsA may reduce economic burden for health care payers and systems. DISCLOSURES: Dr Ogdie has received consulting fees from Amgen, AbbVie, Bristol Myers Squibb, Celgene, CorEvitas (formerly Corrona), Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB and has received grant support from the National Institutes of Health/National Institute of Arthritis and Musculoskeletal and Skin Diseases, Rheumatology Research Foundation, National Psoriasis Foundation, Pfizer (University of Pennsylvania), Amgen (FORWARD), and Novartis (FORWARD). Dr Hwang has received consulting fees from Novartis and UCB and has received grant support (5KL2TR003168-03) from the University of Texas Health Science Center at Houston Center of Clinical and Translational Sciences KL2 program. Drs Veeranki and Shafrin were employees of PRECISIONheor at the time of this analysis. Ms Portelli and Mr Sison are employees of PRECISIONheor. Ms Pedro has nothing to disclose. Dr Hass is an employee of H. E. Outcomes, providing consulting services to Novartis. Dr Hur was an employee of Novartis at the time of this analysis. Dr Kim was a postdoctoral fellow at the University of Texas at Austin and Baylor Scott and White Health, providing services to Novartis at the time of this analysis. Dr Yi is an employee of Novartis. Dr Michaud received grant funding from the Rheumatology Research Foundation at the time of this analysis. This study was funded by Novartis Pharmaceuticals Corporation, East Hanover, NJ.

White Paper on the Value of Time Savings for Patients and Healthcare Providers of Breast Cancer Therapy: The Fixed-Dose Combination of Pertuzumab and Trastuzumab for Subcutaneous Injection as an Example

Health technology assessments and value frameworks are becoming increasingly important for clinical decision-making. Most of these frameworks, however, focus on value to payers rather than patients and healthcare providers and may ignore other sources of economic value such as patient and physician time cost, impact on productivity, and direct health system costs. This article focusses on fixed-dose combination of pertuzumab and trastuzumab for subcutaneous injection (PH FDC SC) in the treatment of HER2-positive breast cancer. We review relevant clinical evidence, examine data on time and resource use of the subcutaneous administration of trastuzumab compared with intravenous treatment and how it can be extrapolated to PH FDC SC, and discuss the value PH FDC SC can bring to patients and healthcare providers. We will also provide our own experiences of PH FDC SC from the healthcare (oncologist, healthcare economist, pharmacist) and patient point of view. The data, combined with our personal experiences, suggest that switching from intravenous pertuzumab and trastuzumab to PH FDC SC could reduce non-drug costs for healthcare providers treating patients with HER2-positive breast cancer through time savings and other economic benefits. Furthermore, PH FDC SC could also save patient time given its shorter administration and post-injection observation time versus intravenous infusions, potentially resulting in reduced productivity loss. These benefits could be applied to other subcutaneous formulations, either currently available or in development.

New therapies are increasingly assessed by looking at their value to those who pay for them rather than their value to patients and healthcare providers. Value assessments conducted from the payers’ perspective often ignore such things as patient and healthcare system time and costs. The fixed-dose combination of pertuzumab and trastuzumab for subcutaneous injection (also known as pertuzumab, trastuzumab, and hyaluronidase-zzxf, abbreviated to PH FDC SC), is injected under the skin to treat a subtype of breast cancer called HER2-positive breast cancer. PH FDC SC is as effective as pertuzumab and trastuzumab, which are infused separately into a vein, but takes a lot less time to administer to patients. This transition is similar to what was seen when a subcutaneous version of trastuzumab was developed and compared to the intravenous original. Also, subcutaneous trastuzumab reduced costs associated with treating patients compared with intravenous infusions. The same benefits of PH FDC SC to patients and healthcare providers can be expected, and our personal experiences as an oncologist, healthcare economist, patient, and pharmacist agree. PH FDC SC could save patient and healthcare provider time given its shorter injection and observation times versus intravenous infusions, potentially resulting in better productivity for these people and a smaller cost to healthcare providers. These benefits could be applied to other subcutaneous formulations, either currently available or in development.

Estimating the impact of biosimilar entry on prices and expenditures in rheumatoid arthritis: a case study of targeted immune modulators

OBJECTIVE

To model changes in prices, utilization, and expenditures of targeted immune modulators (TIMs) for rheumatoid arthritis, accounting for biosimilar entry.

METHODS

Using IQVIA National Sales Perspective data between 2013 and 2019, we examined sales and expenditures of biologics and non-biological complex molecules, 20 quarters before and after patent exclusivity milestones. We estimated the impact of a molecule's exclusivity milestones and biosimilar entry on prices, using a regression discontinuity design (RDD). We then combined the RDD estimate with historical trends to assess the impact of adalimumab's exclusivity milestones on future TIM expenditures.

RESULTS

Changes in average molecule prices were associated largely with biosimilar uptake. For molecules with relatively high biosimilar uptake (>60%), prices fell considerably (-21.2% to -59.3%) one year after exclusivity milestones, whereas molecules with lower biosimilar uptake (<10%) experienced smaller price decreases (-2.4% to -8.4%). Average price reduction at the molecule level after biosimilar entry was not significant (-18.6%; p = .657). When applying the RDD results after adalimumab's exclusivity milestones, its projected share of total TIM market expenditures decreased from 48.0% in 2019 to 26.0% in 2025, whereas expenditures on Janus kinase inhibitors increased from 4.0% to 34.0%.

CONCLUSIONS

Biologics facing biosimilar competition may experience price decreases, potentially offering substantial savings to payers, patients, and society, although the magnitude of these estimates depends on biosimilar uptake. Formulary placement, along with manufacturer-payer dynamics, may also play a role in determining the impact on price and market uptake of biosimilars.

Are caregivers ready for digital? Caregiver preferences for health technology tools to monitor medication adherence among patients with serious mental illness

Background

Adherence to antipsychotic medication is critical for bipolar disorder (BPD), major depression (MDD) and schizophrenia (SCZ) patients. Digital tools have emerged to monitor medication adherence along with tracking general health. Evidence on physician or patient preferences for such tools exists but is limited among caregivers. The study objective was to assess preferences and willingness-to-pay (WTP) for medication adherence monitoring tools among caregivers of SMI patients.

Methods

A web-based survey was administered to caregivers of adult SMI patients. Twelve discrete choice questions comparing adherence monitoring tools that varied across two attribute bundles: (1) tool attributes including source of medication adherence information, frequency of information updates, access to adherence information, and physical activity, mood, and rest tracking, and (2) caregiver monthly out-of-pocket cost attribute were administered to caregiver respondents. Attributes were parameterized for both digital and non-digital tools. Random utility models were used to estimate caregivers’ preferences and WTP.

Results

Among 184 study-eligible caregivers, 57, 61 and 66 participants cared for BPD, MDD, and SCZ patients, respectively. Caregivers highly preferred (odds ratio (OR): 7.34, 95% confidence interval (CI): 5.00–10.79) a tool that tracked medication ingestion using a pill embedded with an ingestible event market (IEM) sensor and tracked patients’ physical activity, mood, and rest than a non-digital pill organizer. Additionally, caregivers were willing to pay $255 per month (95% CI: $123–$387) more for this tool compared to a pill organizer.

Conclusion

Caregivers of SMI patients highly preferred and were willing to pay more for digital tools that not only measures medication ingestion but also tracks general health.

194. Progression of an Uncomplicated Urinary Tract Infection Among Female Patients with Susceptible and Non-Susceptible Urine Isolates: Findings from an Integrated Delivery Network

Background

Uncomplicated urinary tract infection (uUTI) is often treated empirically without antibiotic (AB) susceptibility testing; however, antimicrobial-resistant bacteria could lead to suboptimal treatment and progression to complicated UTI (cUTI). We examined the likelihood of uUTI progression to cUTI in patients with susceptible and non-susceptible uropathogens.

Methods

We performed a retrospective cohort study using data from a large Mid-Atlantic US integrated delivery network’s electronic health records from July 1, 2016 to March 31, 2020. Patients included were female, aged ≥ 12 years with incident uUTI (diagnosis code or urine culture), and given an oral AB ± 5 days of diagnosis and ≥ 1 antibiotic susceptibility test. The primary outcome was progression to cUTI, defined as: new fever, nausea, or vomiting, in addition to uUTI symptoms; or receipt of intravenous antibiotic 3–28 days after index uUTI. Probability of progression to cUTI was assessed comparing patients with non-susceptible and susceptible isolates, with 1:1 propensity score matching. Patients retained for analysis had a nonzero predicted probability of being in the case and control group and were retained for analysis only if there were patients in the mirror group with similar propensity scores. Data were analyzed with logistic regression. Sensitivity analyses were performed to test the robustness of the primary analysis (Table).

Results

A total of 2565 patients were included: 1030 (40.2%) had non-susceptible isolates and 1535 (59.8%) had susceptible isolates. Mean age was 43.5 years and 59.5% of the cohort was White. After propensity score matching, patients with non-susceptible isolates were more than twice as likely to progress to cUTI versus patients with sensitive isolates (10.7% versus 4.9%; odds ratio, 2.35; p < 0.001; Figure). In sensitivity analyses, patients with non-susceptible isolates remained significantly more likely to progress to cUTI (p ≤ 0.009), excluding those receiving fluoroquinolones only (Table).

Figure. Probability of progression to cUTI

Table. Sensitivity analyses of the probability of uUTI progressing to cUTI in patients with non-susceptible versus susceptible isolates (matched population)

Conclusion

Patients with uUTI and AB-resistant isolates were significantly more likely to progress to cUTI than those with susceptible isolates. This finding highlights the need for greater understanding of antimicrobial resistance and has implications for the clinical management of uUTI.

Disclosures

Jason Shafrin, PhD, Precision Medicine Group (Employee, Former employee of Precision Medicine Group, which received funding from GlaxoSmithKline plc. to conduct this study) Alen Marijam, MSc, GlaxoSmithKline plc. (Employee, Shareholder) Ashish V. Joshi, PhD, GlaxoSmithKline plc. (Employee, Shareholder) Fanny S. Mitrani-Gold, MPH, GlaxoSmithKline plc. (Employee, Shareholder) Katie Everson, MSc, Precision Medicine Group (Employee, Employee of Precision Medicine Group, which received funding from GlaxoSmithKline plc. to conduct this study) Rifat Tuly, MPH, Precision Medicine Group (Employee, Employee of Precision Medicine Group, which received funding from GlaxoSmithKline plc. to conduct this study) Peter Rosenquist, MSc, Precision Medicine Group (Employee, Employee of Precision Medicine Group, which received funding from GlaxoSmithKline plc. to conduct this study) Michael Gillam, MD, MedStar Health (Employee, Employee of MedStar Health and received funding from GlaxoSmithKline plc. through Precision Medicine Group to conduct this study) Maria Elena Ruiz, MD, Nothing to disclose

Measuring the Value Healthy Individuals Place on Generous Insurance Coverage of Severe Diseases: A Stated Preference Survey of Adults Diagnosed With and Without Lung Cancer

OBJECTIVES

To compare the ex ante willingness to pay (WTP) of healthy individuals for generous insurance coverage of novel lung cancer treatments to the WTP for coverage of such treatment among individuals with lung cancer.

METHODS

A survey was administered to 2 cohorts of US adults: (1) healthy individuals without cancer and (2) individuals diagnosed with lung cancer. A multiple random staircase survey design was used to elicit respondent WTP for coverage of novel lung cancer therapy associated with survival gains.

RESULTS

Of the 84 937 healthy individuals invited, 300 completed the survey. Of the 36 249 in the lung cancer cohort invited, 250 completed the survey. Mean age by cohort was 50.0 (SD 14.6) and 48.4 (SD 16.8) years, and 55.2% and 47.2% were female, respectively. Respondents in the healthy and lung cancer cohorts were willing to pay $97.52 (95% confidence interval (CI) $89.89-$105.15) and $22 304 (95% CI $20 194-$24 414) per month, respectively, for coverage of a novel therapy providing 5-year survival of 15% versus standard-of-care therapy with a 5-year survival of 4%. After accounting for the likelihood that healthy individuals are diagnosed with lung cancer in the future, we estimated that 89.8% of the total value of new lung cancer treatments comes from the WTP healthy individuals place on generous insurance coverage.

CONCLUSIONS

Total societal willingness to pay for lung cancer is much higher than conventionally thought, as most healthy individuals are risk-averse and highly value having lung cancer treatments available to them in the future.

When Should You Trust Your Doctor? Establishing a Theoretical Model to Evaluate the Value of Second Opinion Visits

In order to produce a mathematical model for better understanding of the benefits and utilization of second opinions and to understand the contradiction between the value of second opinions and their perceived underuse, we developed an expected utility theory model to quantify their value. We use a case-based example to find types of biases that could affect second opinions. Although the baseline expected utility theory model presented assumes providers are rational, we relax this and discuss the implications for how these alternative specifications alter predicted use. We found that second opinions are valuable when diagnostic accuracy is variable across physicians or access to high-quality care is restricted. In a stylized simulation example in which about half (50.1%) of diagnoses were incorrect, receipt of 1 second opinion reduced the error rate to 25.8% and receipt of 2 second opinions reduced the error rate to 16.0%. After incorporating potential biases into the model, the value of second opinions increases only when aversion to changing the initial diagnosis is greater than aversion to correcting a mistake. Additionally, this model reveals that second opinions have value even when diagnostic accuracy is perfect. Further, when financial incentives differ from the incentives of the initial consult, a second opinion offers patients a reasonable bound of their treatment options. To conclude, we identify numerous reasons for underuse of second opinions. Specifically, value depends on the degree of diagnostic uncertainty, presence of behavioral biases, and variation in local compensation regimes. Despite their value, recent trends could actually decrease the value of second opinions.

The impact of vaso-occlusive crises and disease severity on quality of life and productivity among patients with sickle cell disease in the US

AIM

Sickle cell disease (SCD) is a lifelong blood disorder affecting approximately 100,000 individuals in the United States (US). A number of new treatments have recently become available to improve SCD clinical outcomes, but it is unclear how treatment innovations that reduce disease severity could affect patients' humanistic and economic outcomes.

METHODS AND MATERIALS

To answer this question, an online survey of US adult residents with a self-reported SCD diagnosis was conducted. Humanistic outcomes based on health-related quality of life (HRQoL)) were assessed during and outside of vaso-occlusive crises (VOCs). Economic outcomes were measured by annual household income and whether the respondent received disability insurance.

RESULTS

Among the 301 respondents completing the survey, average age was 34.4 years and 73.4% were female. Average HRQoL, measured using health utilities, were 0.311 (95% CI: 0.286, 0.337) during a VOC and 0.738 (0.720, 0.756) not during a VOC. The likelihood of claiming disability insurance was correlated with more frequent VOCs (0 VOCs: 12% vs. ≥4 VOCs: 47%, p = .002) and disease severity (Severity Class II: 16% vs. Severity Class III: 39%, p = .03). There was a weak relationship between VOC frequency and household income (0 VOCs: $47,488 vs. ≥4 VOCs: $34,569, p = .06) and no evidence of a relationship between disease severity class and income (Severity Class II: $42,443 vs. Severity Class III: $36,842, p = .29).

CONCLUSION

In conclusion, disease severity, strongly predicted worse self-reported HRQoL, moderately predicted increased likelihood of collecting disability insurance, and weakly predicted lower household income levels.

For which diseases do broader value elements matter most? An evaluation across 20 ICER evidence reports

BACKGROUND: U.S. value framework developers such as the Institute for Clinical and Economic Review (ICER) use cost-effectiveness analysis to value new health care technologies. Often, these value assessment frameworks use a health system perspective without fully accounting for societal and broader benefits and costs of an intervention. Although there is ongoing debate about the most appropriate methods for including broader value elements in value assessment, it remains unclear whether the inclusion of these value elements is likely to affect the quantitative estimates of treatment value. OBJECTIVE: To assess variations in the relevance of broader value elements to cost-effectiveness analysis across diseases. METHODS: Thirty-two broader value elements (e.g., caregiver burden, health equity, real option value, productivity) not traditionally included in health technology assessments were identified through a targeted literature review. Evidence reports published by ICER between July 2017 and January 2020 were evaluated to identify which broader value elements were discussed as relevant to each disease in the report text. The study examined whether there were associations among ICER's discussion of broader value elements, rare disease status, treatment cost, estimated treatment cost-effectiveness, and ICER committee voting results for contextual considerations and additional benefits/disadvantages. RESULTS: The most commonly cited broader value element category in the ICER evidence reports was household and leisure (e.g., absenteeism from normal activities and caregiver burden). More value elements were cited for inherited retinal disease (19 elements) and sickle cell disease (18 elements) than for other diseases. Cardiovascular disease and diabetes had the fewest number of value elements cited (7 elements). Rare diseases were more likely to have broader value elements cited compared with nonrare diseases (15.9 vs. 11.5, P < 0.001). Treatments with higher (i.e., less favorable) incremental cost-effectiveness ratios were more likely to have a greater number of broader value elements cited (ρ = 0.625, P < 0.001). CONCLUSIONS: The presence of broader value elements varied across diseases, with less cost-effective treatments more likely to have a higher number of relevant broader value elements. Inclusion of all relevant value elements in value assessments will more appropriately incentivize innovation and improve allocation of research funding. DISCLOSURES: This study was sponsored by Novartis Pharmaceutical Corporation. At the time of this study, Shafrin was employed by PRECISIONheor, a consultancy to the life sciences industry that received financial support from Novartis to conduct this study. Dennen, Pednekar, and Birch are employed by PRECISIONheor. Bhor was an employee of Novartis Pharmaceutical Corporation at the time this research was conducted and manuscript was developed and reports grants from Novartis, unrelated to this work. Kanter has served on scientific advisory boards and steering committees for and reports receiving consulting fees from Novartis Pharmaceutical Corporation and is a site principal investigator on studies funded by Novartis Pharmaceutical Corporation. Kantar also reports support from Sickle Cell Disease Association of America Inc. and National Heart, Lung, and Blood Institute, unrelated to this work. Neumann reports advisory boards or consulting fees from Novartis Pharmaceutical Corporation and PRECISIONheor, as well as advisory boards or consulting fees unrelated to this study from AbbVie, Amgen, Avexis, Bayer, Congressional Budget Office, Janssen, Merck, Novartis, Novo Nordisk, Precision Health Economics, Veritech, Vertex; funding from The CEA Registry Sponsors by various pharmaceutical and medical device companies; and grants from Amgen, Lundbeck, Bill and Melinda Gates Foundation, National Pharmaceutical Council, Alzheimer's Association, and the National Institutes for Health.

Adoption of Digital Health Technologies in the Practice of Behavioral Health: Qualitative Case Study of Glucose Monitoring Technology

Background

Evaluation of patients with serious mental illness (SMI) relies largely on patient or caregiver self-reported symptoms. New digital technologies are being developed to better quantify the longitudinal symptomology of patients with SMI and facilitate disease management. However, as these new technologies become more widely available, psychiatrists may be uncertain about how to integrate them into daily practice. To better understand how digital tools might be integrated into the treatment of patients with SMI, this study examines a case study of a successful technology adoption by physicians: endocrinologists’ adoption of digital glucometers.

Objective

This study aims to understand the key facilitators of and barriers to clinician and patient adoption of digital glucose monitoring technologies to identify lessons that may be applicable across other chronic diseases, including SMIs.

Methods

We conducted focus groups with practicing endocrinologists from 2 large metropolitan areas using a semistructured discussion guide designed to elicit perspectives of and experiences with technology adoption. The thematic analysis identified barriers to and facilitators of integrating digital glucometers into clinical practice. Participants also provided recommendations for integrating digital health technologies into clinical practice more broadly.

Results

A total of 10 endocrinologists were enrolled: 60% (6/10) male; a mean of 18.4 years in practice (SD 5.6); and 80% (8/10) working in a group practice setting. Participants stated that digital glucometers represented a significant change in the treatment paradigm for diabetes care and facilitated more effective care delivery and patient engagement. Barriers to the adoption of digital glucometers included lack of coverage, provider reimbursement, and data management support, as well as patient heterogeneity. Participant recommendations to increase the use of digital health technologies included expanding reimbursement for clinician time, streamlining data management processes, and customizing the technologies to patient needs.

Conclusions

Digital glucose monitoring technologies have facilitated more effective, individualized care delivery and have improved patient engagement and health outcomes. However, key challenges faced by the endocrinologists included lack of reimbursement for clinician time and nonstandardized data management across devices. Key recommendations that may be relevant for other diseases include improved data analytics to quickly and accurately synthesize data for patient care management, streamlined software, and standardized metrics.

Quantifying spillover benefits in value assessment: a case study of increased graft survival on the US kidney transplant waitlist

AIM

To quantify the wider impacts of increased graft survival on the size of the kidney transplant waitlist and health and economic outcomes.

MATERIALS AND METHODS

The analysis employed known steady-state solutions to a double-queueing system as well as simulations of this system. Baseline input parameters were sourced from the Organ Procurement and Transplant Network and the United States Renal Data System. Three increased graft survival scenarios were modeled: decreases in repeat transplant candidates joining the waitlist of 25%, 50%, and 100%.

RESULTS

Under the three scenarios, we estimated that the US waitlist size would decrease from 91,822 to 85,461 (6.9% decrease), 80,073 (12.8% decrease), and 69,340 (24.4% decrease), respectively. Patient outcomes improved, with lifetime quality-adjusted life years (QALYs) for a 1-year cohort of transplant recipients increasing by 10,010, 16,888, and 43,345 over the three scenarios. Discounted lifetime costs for the cohort in the new steady state were lower by $1.6 billion, $2.3 billion, and $9.0 billion for each scenario, respectively. Spillover impacts (i.e. benefits that accrued beyond the patients who directly experienced increased graft survival) accounted for 41-48% of the QALY gains and ranged from cost increases of 3.3% to decreases of 5.5%.

LIMITATIONS

The model is a simplification of reality and does not account for the full degree of patient heterogeneity occurring in the real world. Health economic outcomes are extrapolated based on the assumption that the median patient is representative of the overall population.

CONCLUSIONS

Increasing graft survival reduces demand from repeat transplants candidates, allowing additional candidates to receive transplants. These spillover impacts decrease waitlist size and shorten wait times, leading to improvements in graft and patient survival as well as quality-of-life. Cost-effectiveness analyses of treatments that increase kidney graft survival should incorporate spillover benefits that accrue beyond the direct recipient of an intervention.

Alternative payment models and innovation: a case study of US health system adoption of a sacubitril/valsartan to treat acute decompensated heart failure

AIM

To understand the financial impact of health system adoption of novel heart failure medications under US alternative payment models (APMs).

MATERIALS AND METHODS

This study used a decision tree model to assess the financial impact of health system adoption of sacubitril/valsartan to treat acute decompensated heart failure (ADHF). A comparator scenario modeled current health care utilization and cost for treating hospitalized ADHF patients with angiotensin-converting-enzyme inhibitors (ACEi) or angiotensin-receptor blockers (ARB). The study then measured the impact of adopting sacubitril/valsartan to treat ADHF on health system economic outcomes. Differences in treatment efficacy were based on the PIONEER-HF clinical trial. The financial impact of changes in patient outcomes under the sacubitril/valsartan and ACEi/ARB arms was assessed across three APMs: the Medicare Shared Savings Program, Bundled Payments for Care Improvement, and fee-for-service payments adjusted according to the Hospital Readmission Reduction Program.

RESULTS

Sacubitril/valsartan reduced re-hospitalizations after an initial ADHF admission by 46.3% for individuals aged 18-64 years and 23.4% for individuals aged ≥65 years. Health systems' financial benefit of adopting sacubitril/valsartan was $740 per ADHF case per year (PCPY). Savings were larger for patients aged ≥65 years ($803 PCPY) compared to those <65 years ($653 PCPY). The majority of the health system financial benefit came from changes in APM bonus and penalty reimbursements. Value-based payments from the Hospital Readmission Reduction Program ($1,190 financial gain PCPY) and the Bundled Care Payment Improvement Initiative ($645 financial gain PCPY) produced larger financial benefits than participation in the Medicare Shared Savings Program ($253 financial gain PCPY).

LIMITATIONS

The model uses clinical trial data, which may not reflect real-world outcomes. Further, the financial implications were modeled based only on three widely used APMs.

CONCLUSION

Sacubitril/valsartan adoption decreased hospitalizations and led to a positive net financial impact on health systems after accounting for APM bonus payments.

Changes in mortality associated with cancer drug approvals in the United States from 2000 to 2016

AIMS

To estimate the extent to which the approvals of new pharmacological therapies were associated with cancer mortality in the USA between 2000 and 2016.

MATERIALS AND METHODS

The analysis quantified cancer drug approvals across the 15 tumor types with the highest incidence. Number of approvals in a given time period for each tumor was translated into a treatment stock measure, defined as a weighted sum of new indication approvals since 1976. The primary outcome was the annual tumor-specific cancer mortality, defined as the number of deaths per 100,000 U.S. population. The analysis used a multivariable ordinary least squares and a fixed effects model, controlling for incidence (new cases per 100,000 U.S. population) and the primary exposure, the treatment stock measure by year.

RESULTS

Between 2000 and 2016, deaths per 100,000 population across the 15 most common tumor types declined by 24%. Additionally, 10.2 new indications were approved per year across the 15 most common tumor types. Cancer drug approvals were associated with statistically significant deaths averted in 2016 for colorectal cancer (4,991, p = 0.004), lung cancer (33,825, p < 0.001), breast cancer (11,502, p < 0.001), non-Hodgkin's lymphoma (6,636, p < 0.001), leukemia (4,011, p < 0.001), melanoma (1,714, p < 0.001), gastric cancer (758, p = 0.019), and renal cancer (739, p < 0.001). Between 2000 and 2016, new cancer treatments were correlated with 1,291,769 (p < 0.001) total deaths prevented across the 15 most common tumor types.

LIMITATIONS AND CONCLUSIONS

Cancer drug approvals between 2000 and 2016 were associated with significant reduction in deaths from the most common cancers in the USA. Mortality changes were largest in prevalent tumor types with relatively more approvals, i.e. lung cancer, breast cancer, melanoma, lymphoma and leukemia. Future research evaluating the relationship between drug approvals and cancer mortality post 2016 is needed.

Crizanlizumab and comparators for adults with sickle cell disease: a systematic review and network meta-analysis

OBJECTIVES

Treatment options for preventing vaso-occlusive crises (VOC) among patients with sickle cell disease (SCD) are limited, especially if hydroxyurea treatment has failed or is contraindicated. A systematic literature review (SLR) and network meta-analysis (NMA) were conducted to evaluate the efficacy and safety of crizanlizumab for older adolescent and adult (≥16 years old) SCD patients.

METHODS

The SLR included randomised controlled trials (RCTs) and uncontrolled studies. Bayesian NMA of VOC, all-cause hospitalisation days and adverse events were conducted.

RESULTS

The SLR identified 51 studies and 9 RCTs on 14 treatments that met the NMA inclusion criteria. The NMA found that crizanlizumab 5.0 mg/kg was associated with a reduction in VOC (HR 0.55, 95% credible interval (0.43, 0.69); Bayesian probability of superiority >0.99), all-cause hospitalisation days (0.58 (0.50, 0.68); >0.99) and no evidence of difference on adverse events (0.91 (0.59, 1.43) 0.66) or serious adverse events (0.93 (0.47, 1.87); 0.59) compared with placebo. The HR for reduction in VOC for crizanlizumab relative to L-glutamine was (0.67 (0.50, 0.88); >0.99). These results were sensitive to assumptions regarding whether patient age is an effect modifier.

CONCLUSIONS

This NMA provides preliminary evidence comparing the efficacy of crizanlizumab with other treatments for VOC prevention.

Modeling the impact of patient treatment preference on health outcomes in relapsing-remitting multiple sclerosis

Aims: Model how moving from current disease-modifying drug (DMD) prescribing patterns for relapsing-remitting multiple sclerosis (RRMS) observed in the United Kingdom (UK) to prescribing patterns based on patient preferences would impact health outcomes over time.Materials and methods: A cohort-based Markov model was used to measure the effect of DMDs on long-term health outcomes for individuals with RRMS. Data from a discrete choice experiment were used to estimate the market shares of DMDs based on patient preferences (i.e. preference shares). These preference shares and real-world UK market shares were used to calculate the effect of prescribing behavior on relapses, disability progression, and quality-adjusted life-years (QALYs). The incremental benefit of patient-centered prescribing over current practices for the UK RRMS population was then estimated; scenario and sensitivity analyses were also conducted.Results: Compared to current prescribing practices, when UK patients with RRMS were treated following patient preferences, health outcomes were improved. This population was expected to experience 501,690 relapses and gain 1,003,263 discounted QALYs over 50 years under patient-centered prescribing practices compared to 538,417 relapses and 958,792 discounted QALYs under current practices (-6.8% and +4.6%, respectively). Additionally, less disability progression was observed when prescribed treatment was based on patient preferences. In a scenario analysis where only oral treatments were considered, the results were similar, although the magnitude of benefit was smaller. Number of relapses was most sensitive to how the annualized relapse rate was modeled; disability progression was most sensitive to mortality rate assumptions.Limitations: Treatment efficacy estimates applied to various models in this study were based on data derived from clinical trials, rather than real-world data; the impact of patient-centered prescribing on treatment adherence and/or switching was not modeled.Conclusions: The population of UK RRMS patients may experience overall health gains if patient preferences are better incorporated into prescribing practices.

A Flexible Open-Source Decision Model for Value Assessment of Biologic Treatment for Rheumatoid Arthritis

OBJECTIVE

The nature of model-based cost-effectiveness analysis can lead to disputes in the scientific community. We propose an iterative and collaborative approach to model development by presenting a flexible open-source simulation model for rheumatoid arthritis (RA), accessible to both technical and non-technical end-users.

METHODS

The RA model is a discrete-time individual patient simulation with 6-month cycles. Model input parameters were estimated based on currently available evidence and treatment effects were obtained with Bayesian network meta-analysis techniques. The model contains 384 possible model structures informed by previously published models. The model consists of the following components: (i) modifiable R and C++ source code available in a GitHub repository; (ii) an R package to run the model for custom analyses; (iii) detailed model documentation; (iv) a web-based user interface for full control over the model without the need to be well-versed in the programming languages; and (v) a general audience web-application allowing those who are not experts in modeling or health economics to interact with the model and contribute to value assessment discussions.

RESULTS

A primary function of the initial version of RA model is to help understand and quantify the impact of parameter uncertainty (with probabilistic sensitivity analysis), structural uncertainty (with multiple competing model structures), the decision framework (cost-effectiveness analysis or multi-criteria decision analysis), and perspective (healthcare or limited societal) on estimates of value.

CONCLUSION

In order for a decision model to remain relevant over time it needs to evolve along with its supporting body of clinical evidence and scientific insight. Multiple clinical and methodological experts can modify or contribute to the RA model at any time due to its open-source nature.

Using Information on Patient Adherence to Antipsychotic Medication to Understand Their Adherence to Other Medications

PURPOSE

To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension.

METHODS

Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001).

CONCLUSION

Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications.

The economic burden of switching targeted disease-modifying anti-rheumatic drugs among rheumatoid arthritis patients

AIMS

To estimate real world healthcare costs and resource utilization of rheumatoid arthritis (RA) patients associated with targeted disease modifying anti-rheumatic drugs (tDMARD) switching in general and switching to abatacept specifically.

MATERIALS AND METHODS

RA patients initiating a tDMARD were identified in IMS PharMetrics Plus health insurance claims data (2010-2016), and outcomes measured included monthly healthcare costs per patient (all-cause, RA-related) and resource utilization (inpatient stays, outpatient visits, emergency department [ED] visits). Generalized linear models were used to assess (i) average monthly costs per patient associated with tDMARD switching, and (ii) among switchers only, costs of switching to abatacept vs tumor necrosis factor inhibitors (TNFi) or other non-TNFi. Negative binomial regressions were used to determine incident rate ratios of resource utilization associated with switching to abatacept.

RESULTS

Among 11,856 RA patients who initiated a tDMARD, 2,708 switched tDMARDs once and 814 switched twice (to a third tDMARD). Adjusted average monthly costs were higher among patients who switched to a second tDMARD vs non-switchers (all-cause: $4,785 vs $3,491, p < .001; RA-related: $3,364 vs $2,297, p < .001). Monthly RA-related costs were higher for patients switching to a third tDMARD compared to non-switchers remaining on their second tDMARD ($3,835 vs $3,383, p < .001). Switchers to abatacept had significantly lower RA-related monthly costs vs switchers to TNFi ($3,129 vs $3,436, p = .021), and numerically lower all-cause costs ($4,444 vs $4,741, p = 0.188). Switchers to TNFi relative to abatacept had more frequent inpatient stays after switch (incidence rate ratio (IRR) = 1.85, p = .031), and numerically higher ED visits (IRR = 1.32, p = .093). Outpatient visits were less frequent for TNFi switchers (IRR = 0.83, p < .001) compared to switchers to abatacept.

LIMITATIONS AND CONCLUSIONS

Switching to another tDMARD was associated with higher healthcare costs. Switching to abatacept, however, was associated with lower RA-related costs, fewer inpatient stays, but more frequent outpatient visits compared to switching to a TNFi.

HSR19-099: Harnessing the Voice of Patients With Genetic Mutations in NSCLC Treatment

Background: Targeted therapies for non-small lung cancer (NSCLC) have vastly improved survival and other outcomes for patients whose tumors have genetic mutations such as ALK, BRAF, EGFR, and ROS1. Identification of genetic mutations often indicates a mutation-specific course of therapy; however, the relationship between genetic mutation status, patient treatment preferences, and other determinants of patient value in NSCLC cancer care is not well understood. Methods: Qualitative study utilizing focus groups and in-depth interviews were conducted with metastatic NSCLC patients who had received systemic therapy. Interviews explored how patients valued and prioritized factors and attributes associated with NSCLC therapy. Interviews were audio-recorded, transcribed, and coded for key themes using MAXQDA qualitative data analysis software (VERBI, GmbH). Thematic analysis identified determinants of value that patients with genetic mutations considered most important in decision-making. Results: Of 19 total participants with metastatic NSCLC (mean [SD] age, 55.8 [12.6] years; 79% female), 15 (79%) reported a known genetic mutation. Most participants valued oncogene testing and indicated that they had developed a distinct identity based on their specific mutation. Further, participants in our study with identified mutations reported facing distinctly different decisions than those without known mutations. Participants also highlighted unmet needs for diagnosis, treatment, and support tailored to their patient subgroup, including a critical need for better provider training and awareness of genetic testing and mutation-specific treatment options. Across patient subgroups, mutation-specific social media and support networks were highly valued for the care and treatment information they provide, especially among those with rare mutations, limited treatment options, or less-experienced providers. Conclusions: Our study suggests important differences among NSCLC patients based on identified genetic mutations. As treatment for NSCLC evolves, so do the needs and preferences of patients, especially those with driver mutations. Our findings highlight the need for a better understanding of how mutation status may impact patient goals and preferences in order to provide the highest value care to each patient.

The potential value of rapid, cloud-enabled onsite testing for the diagnosis of rheumatoid arthritis in the United States

AIMS

Improvements in information technology have granted the recent development of rapid, cloud-enabled, onsite laboratory testing for rheumatoid arthritis (RA). This study aims to quantify the value to payers of such technologies.

MATERIALS AND METHODS

To calculate the value of rapid, cloud-enabled, onsite laboratory testing to diagnose RA relative to traditional, centralized laboratory testing, an Excel-based decision tree model was created that simulated potential cost-savings to payers who cover routine evaluations of RA patients in the US. First, a conceptual framework was created to identify the value components of rapid, cloud-enabled onsite testing. Second, value associated with patient time savings, savings on visit fees, change in treatment costs, and QALY improvements was measured, leveraging existing literature and information from an observational study. Lastly, these value components were combined to estimate the total incremental value accruing to payers per patient-year relative to centralized laboratory testing.

RESULTS

Rapid, cloud-enabled, onsite testing is estimated to save one office and 1.81 laboratory visits during the evaluation period for the average patient. Results from an observational study found that rapid, cloud-enabled testing increased the likelihood of completing diagnostic orders from 84.5% to 97%, resulting in an increased probability of early treatment (3.5 percentage points) with disease-modifying anti-rheumatic drugs among patients eligible for treatment. The combined total value was $5,648 per evaluated patient-year. This value is primarily attributed to health benefits of early treatment ($5,048), fewer visit payments ($459), and patient time savings due to fewer office ($216) and laboratory visits ($255).

LIMITATIONS AND CONCLUSIONS

Data on the impact of rapid, cloud-enabled, onsite testing on patient health, care delivery, and clinical decision-making is scarce. More robust real-world data would confirm the validity of our model. Rapid, cloud-enabled, onsite testing has the potential to generate significant value to payers.

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Background

New digital technologies offer providers the promise of more accurately tracking patients’ medication adherence. It is unclear, however, whether access to such information will affect provider treatment decisions in the real world.

Methods

Using prescriber-reported information on patient non-compliance from health insurance claims data between 2008 and 2014, we examined whether prescribers’ knowledge of non-compliance was associated with different prescribing patterns for patients with serious mental illness (SMI). We examined patients who initiated an oral atypical antipsychotic, but were later objectively non-adherent to this treatment, defined as proportion of days covered (PDC) <0.8. We examined how a physician’s awareness of patient non-compliance (ICD-9 diagnosis code: V15.81) was correlated with the physician’s real-world treatment decisions for that patient. Treatment decisions studied included the share of patients who increased antipsychotic dose, augmented treatment, switched their antipsychotic, or used a long-acting injectable (LAI).

Results

Among the 286,249 patients with SMI who initiated an antipsychotic and had PDC <0.8, 4,033 (1.4%) had documented non-compliance. When prescribers documented non-compliance, patients were more likely to be switched to another antipsychotic (32.8% vs 24.7%, P<0.001), have their dose increased (24.4% vs 22.1%, P=0.004), or receive an LAI (0.09% vs 0.04%, P=0.008), but were less likely to have augmented therapy with another antipsychotic (1.1% vs 1.3%, P=0.035) than patients without documented non-compliance.

Conclusion

Among SMI patients with documented non-compliance, the frequency of dose, medication switches, and LAI use were higher and augmentation was lower compared to patients without documented non-compliance. Access to adherence information may help prescribers more rapidly switch ineffective medications as well as avoid unnecessary medication augmentation.

Long-Term Health and Economic Value of Improved Mobility among Older Adults in the United States

BACKGROUND

Mobility impairments have substantial physical and mental health consequences, resulting in diminished quality of life. Most studies on the health economic consequences of mobility limitations focus on short-term implications.

OBJECTIVES

To examine the long-term value of improving mobility in older adults.

METHODS

Our six-step approach used clinical trial data to calibrate mobility improvements and estimate health economic outcomes using a microsimulation model. First, we measured improvement in steps per day calibrated with clinical trial data examining hylan G-F 20 viscosupplementation treatment. Second, we created a cohort of patients 51 years and older with osteoarthritis. In the third step, we estimated their baseline quality of life. Fourth, we translated steps-per-day improvements to changes in quality of life using estimates from the literature. Fifth, we calibrated quality of life in this cohort to match those in the trial. Last, we incorporated these data and parameters into The Health Economic Medical Innovation Simulation model to estimate how mobility improvements affect functional status limitations, medical expenditures, nursing home utilization, employment, and earnings between 2012 and 2030.

RESULTS

In our sample of 12.6 million patients, 66.7% were female and 70% had a body mass index of more than 25 kg/m2. Our model predicted that a 554-step-per-day increase in mobility would reduce functional status limitations by 5.9%, total medical expenditures by 0.9%, and nursing home utilization by 2.8%, and increase employment by 2.9%, earnings by 10.3%, and monetized quality of life by 3.2% over this 18-year period.

CONCLUSIONS

Interventions that improve mobility are likely to reduce long-run medical expenditures and nursing home utilization and increase employment.

Medication Adherence Patterns Among Patients with Multiple Serious Mental and Physical Illnesses

INTRODUCTION

Patients with mental and physical health conditions are complex to treat and often use multiple medications. It is unclear how adherence to one medication predicts adherence to others. A predictive relationship could permit less expensive adherence monitoring if overall adherence could be predicted through tracking a single medication.

METHODS

To test this hypothesis, we examined whether patients with multiple mental and physical illnesses have similar adherence trajectories across medications. Specifically, we conducted a retrospective cohort analysis using health insurance claims data for enrollees who were diagnosed with a serious mental illness, initiated an atypical antipsychotic, as well as an SSRI (to treat serious mental illness), biguanides (to treat type 2 diabetes), or an ACE inhibitor (to treat hypertension). Using group-based trajectory modeling, we estimated adherence patterns based on monthly estimates of the proportion of days covered with each medication. We measured the predictive value of the atypical antipsychotic trajectories to adherence predictions based on patient characteristics and assessed their relative strength with the R-squared goodness of fit metric.

RESULTS

Within our sample of 431,591 patients, four trajectory groups were observed: non-adherent, gradual discontinuation, stop-start, and adherent. The accuracy of atypical antipsychotic adherence for predicting adherence to ACE inhibitors, biguanides, and SSRIs was 44.5, 44.5, and 49.6%, respectively (all p < 0.001 vs. random). We also found that information on patient adherence patterns to atypical antipsychotics was a better predictor of patient adherence to these three medications than would be the case using patient demographic and clinical characteristics alone.

CONCLUSION

Among patients with multiple chronic mental and physical illnesses, patterns of atypical antipsychotic adherence were useful predictors of adherence patterns to a patient's adherence to ACE inhibitors, biguanides, and SSRIs.

FUNDING

Otsuka Pharmaceutical Development & Commercialization, Inc.

Estimated prevalence of undiagnosed atrial fibrillation in the United States

Introduction

As atrial fibrillation (AF) is often asymptomatic, it may remain undiagnosed until or even after development of complications, such as stroke. Consequently the observed prevalence of AF may underestimate total disease burden.

Methods

To estimate the prevalence of undiagnosed AF in the United States, we performed a retrospective cohort modeling study in working age (18–64) and elderly (≥65) people using commercial and Medicare administrative claims databases. We identified patients in years 2004–2010 with incident AF following an ischemic stroke. Using a back-calculation methodology, we estimated the prevalence of undiagnosed AF as the ratio of the number of post-stroke AF patients and the CHADS₂-specific stroke probability for each patient, adjusting for age and gender composition based on United States census data.

Results

The estimated prevalence of AF (diagnosed and undiagnosed) was 3,873,900 (95%CI: 3,675,200–4,702,600) elderly and 1,457,100 (95%CI: 1,218,500–1,695,800) working age adults, representing 10.0% and 0.92% of the respective populations. Of these, 698,900 were undiagnosed: 535,400 (95%CI: 331,900–804,400) elderly and 163,500 (95%CI: 17,700–400,000) working age adults, representing 1.3% and 0.09% of the respective populations. Among all undiagnosed cases, 77% had a CHADS₂ score ≥1, and 56% had CHADS₂ score ≥2.

Conclusions

Using a back-calculation approach, we estimate that the total AF prevalence in 2009 was 5.3 million of which 0.7 million (13.1% of AF cases) were undiagnosed. Over half of the modeled population with undiagnosed AF was at moderate to high risk of stroke.

The effect of medication nonadherence on progression-free survival among patients with renal cell carcinoma

Objective

To examine how observed medication nonadherence to 2 second-line, oral anticancer medications (axitinib and everolimus) affects progression-free survival (PFS) among patients with renal cell carcinoma.

Methods

We used an adherence–exposure–outcome model to simulate the impact of adherence on PFS. Using a pharmacokinetic/pharmacodynamic (PK/PD) population model, we simulated drug exposure measured by area under the plasma concentration–time curve (AUC) and minimum blood or trough concentration (C_min) under 2 scenarios: 1) optimal adherence and 2) real-world adherence. Real-world adherence was measured using the medication possession ratios as calculated from health insurance claims data. A population PK/PD model was simulated on individuals drawn from the Medical Expenditure Panel Survey (MEPS), a large survey broadly representative of the US population. Finally, we used previously published PK/PD models to estimate the effect of drug exposure (i.e., C_min and AUC) on PFS outcomes under optimal and real-world adherence scenarios.

Results

Average adherence measured using medication possession ratios was 76%. After applying our simulation model to 2164 individuals in MEPS, drug exposure was significantly higher among adherent patients compared with nonadherent patients for axitinib (AUC: 249.5 vs. 159.8 ng×h/mL, P<0.001) and everolimus (AUC: 185.4 vs. 118.0 µg×h/L, P<0.001). Patient nonadherence in the real world decreased the expected PFS from an optimally adherent population by 29% for axitinib (8.4 months with optimal adherence vs. 6.0 months using real-world adherence, P<0.001) and by 5% (5.5 vs. 5.2 months, P<0.001) for everolimus.

Conclusion

Nonadherence by renal cell carcinoma patients to second-line oral therapies significantly decreased the expected PFS.

Evaluating Matching-Adjusted Indirect Comparisons in Practice: A Case Study of Patients with Attention-Deficit/Hyperactivity Disorder

Differences in patient characteristics across trials may bias efficacy estimates from indirect treatment comparisons. To address this issue, matching-adjusted indirect comparison (MAIC) measures treatment efficacy after weighting individual patient data to match patient characteristics across trials. To date, however, there is no consensus on how best to implement MAIC. To address this issue, we applied MAIC to measure how two attention-deficit/hyperactivity disorder (ADHD) treatments (guanfacine extended release and atomoxetine hydrochloride) affect patients' ADHD symptoms, as measured by the ADHD Rating Scale IV score. We tested MAIC sensitivity to: matched patient characteristics, matched statistical moments, weighting matrix, and placebo-arm matching (i.e., matching on outcomes in the placebo arm). After applying MAIC, guanfacine and atomoxetine had similar reductions in ADHD symptoms (Δ: 0.4, p < 0.737). The results were similar for three of four sensitivity analyses. When we applied MAIC with placebo-arm matching, however, guanfacine reduced symptoms more than atomoxetine (Δ: -3.9, p < 0.004). We discuss the implication of this finding and advise MAIC practitioners to carefully consider the use of placebo-arm matching, depending on the presence of residual confounding across trials. Copyright © 2016 John Wiley & Sons, Ltd.

Value-Based Payments and Incentives to Improve Care: A Case Study of Patients with Type 2 Diabetes in Medicare Advantage

OBJECTIVES

To estimate the impact of increased glycated hemoglobin (A1C) monitoring and treatment intensification for patients with type 2 diabetes (T2D) on quality measures and reimbursement within the Medicare Advantage Star (MA Star) program.

METHODS

The primary endpoint was the share of patients with T2D with adequate A1C control (A1C ≤ 9%). We conducted a simulation of how increased A1C monitoring and treatment intensification affected this end point using data from the National Health and Nutrition Examination Survey and clinical trials. Using the estimated changes in measured A_1C levels, we calculated corresponding changes in the plan-level A_1C quality measure, overall star rating, and reimbursement.

RESULTS

At baseline, 24.4% of patients with T2D in the average plan had poor A1C control. The share of plans receiving the highest A1C rating increased from 27% at baseline to 49.5% (increased monitoring), 36.2% (intensification), and 57.1% (joint implementation of both interventions). However, overall star ratings increased for only 3.6%, 1.3%, and 4.8% of plans, respectively, by intervention. Projected per-member per-year rebate increases under the MA Star program were $7.71 (monitoring), $2.66 (intensification), and $10.55 (joint implementation).

CONCLUSIONS

The simulation showed that increased monitoring and treatment intensification would improve A1C levels; however, the resulting average increases in reimbursement would be small.

The association between observed mobility and quality of life in the near elderly

INTRODUCTION

Chronic diseases associated with aging, such as arthritis, frequently cause reduced mobility, pain and diminished quality of life. To date, research on the association between mobility and quality of life has primarily focused in the elderly; hence, much less is known about this association in the near elderly. This cross-sectional study aimed to assess the association between mobility and quality of life measures in the near elderly.

METHODS

A prospective observational study of persons aged 50-69 years was conducted. The primary endpoint was quality of life measured by EQ-5D-5L, and the primary explanatory variable was observed mobility assessed using the 6-minute walk distance (6MWD). We applied regression models controlling for demographic, health status and other factors to evaluate the association between 6MWD and EQ-5D-5L.

RESULTS

Of the 183 participants analyzed in the study, 37% were male and the average age was 59.8 years. After adjusting for differences in demographic characteristics and health status, EQ-5D-5L-based utility values were 0.046 points (p<0.001), or 5.2% (95% CI: 2.7% to 7.8%), higher on average for individuals with 100 meters longer 6MWD. Holding constant the mobility-specific component of EQ-5D-5L, we still found that walking an additional 100 meters was associated with an EQ-5D-5L utility value that was 0.029 points (p<0.001), or 3.5% (95% CI: 1.7% to 5.5%), higher than the average participant. Among persons with arthritis, the association between 6MWD and EQ-5D-5L was slightly stronger.

CONCLUSIONS

Near elderly persons with better mobility had higher quality of life. Diseases that decrease mobility, such as arthritis, are likely to have a significant impact on quality of life.

The Economic Burden of ACPA-Positive Status Among Patients with Rheumatoid Arthritis

BACKGROUND

Anticitrullinated protein antibodies (ACPAs) are serological biomarkers associated with early, rapidly progressing rheumatoid arthritis (RA), including more severe disease and joint damage. ACPA testing has become a routine tool for RA diagnosis and prognosis. Furthermore, treatment efficacy has been shown to vary by ACPA-positive status. However, it is not clear if the economic burden of patients with RA varies by ACPA status.

OBJECTIVE

To determine if the economic burden of RA varies by patient ACPA status.

METHODS

IMS PharMetrics Plus health insurance claims and electronic medical record (EMR) data from 2010-2015 were used to identify patients with incident RA. Patients were aged ≥ 18 years, had ≥ 1 inpatient or ≥ 2 outpatient claims reporting an RA diagnosis code (ICD-9-CM code 714.0), and had an anticyclic citrullinated peptide (anti-CCP; a surrogate of ACPA) antibody test within 6 months of diagnosis. Incident patients were defined as those who had no claims with an RA diagnosis code in the 6 months before the first observed RA diagnosis. The primary outcome of interest was RA-related medical expenditures, defined as the sum of payer- and patient-paid amounts for all claims with an RA diagnosis code. Secondary outcomes included health care utilization metrics such as treatment with a disease-modifying antirheumatic drug (DMARD) and physician visits. Generalized linear regression models were used for each outcome, controlling for ACPA-positive status (defined as anti-CCP ≥ 20 AU/mL), age, sex, and Charlson Comorbidity Index score as explanatory variables.

RESULTS

Of 647,171 patients diagnosed with RA, 89,296 were incident cases, and 47% (n = 42,285) had an anti-CCP test. After restricting this sample to patients with a linked EMR and reported anti-CCP test result, 859 remained, with 24.7% (n = 212) being ACPA-positive. Compared with ACPA-negative patients, adjusted results showed that ACPA-positive patients were more likely to use either conventional (71.2% vs. 49.6%; P < 0.001) or biologic (20.3% vs. 11.8%; P < 0.001) DMARDs during the first year after diagnosis and had more physician visits (5.58 vs. 3.91 times per year; P < 0.001). Annual RA-associated total expenditures were $7,941 for ACPA-positive and $5,243 for ACPA-negative patients (Δ = $2,698; P = 0.002). RA-associated medical expenditures were $4,380 for ACPA-positive and $3,427 for ACPA-negative patients (Δ = $954; P = 0.168), whereas DMARD expenditures were $3,560 and $1,817, respectively (Δ = $1,743; P = 0.001).

CONCLUSIONS

RA-related economic burden is higher for patients who are ACPA-positive compared with those who are ACPA-negative. Providers may wish to inform patients diagnosed with ACPA-positive RA about the likely future disease and economic burden in hopes that both stakeholders can be more proactive in addressing them.

DISCLOSURES

Funding for this research was contributed by Bristol-Myers Squibb. Patel and Price are employees and stockholders of Bristol-Myers Squibb. Shafrin and Tebeka are employees of Precision Health Economics, a health care consulting firm that received funding from Bristol-Myers Squibb to conduct this study. Michaud has received a grant from Pfizer and is employed by the National Data Bank for Rheumatic Diseases, which has received funds from Amgen, Bristol-Myers Squibb, Eli Lilly, Janssen, Pfizer, and Regeneron. Study concept and design were contributed by Shafrin, Price, Patel, and Michaud. Shafrin, Price, and Patel collected the data, and all authors contributed equally to data analysis. The manuscript was written by Shafrin and Tebeka and revised by Shafrin, Price, Patel, and Michaud.

Predicting Real-World Effectiveness of Cancer Therapies Using Overall Survival and Progression-Free Survival from Clinical Trials: Empirical Evidence for the ASCO Value Framework

OBJECTIVES

To measure the relationship between randomized controlled trial (RCT) efficacy and real-world effectiveness for oncology treatments as well as how this relationship varies depending on an RCT's use of surrogate versus overall survival (OS) endpoints.

METHODS

We abstracted treatment efficacy measures from 21 phase III RCTs reporting OS and either progression-free survival or time to progression endpoints in breast, colorectal, lung, ovarian, and pancreatic cancers. For these treatments, we estimated real-world OS as the mortality hazard ratio (RW MHR) among patients meeting RCT inclusion criteria in Surveillance and Epidemiology End Results-Medicare data. The primary outcome variable was real-world OS observed in the Surveillance and Epidemiology End Results-Medicare data. We used a Cox proportional hazard regression model to calibrate the differences between RW MHR and the hazard ratios on the basis of RCTs using either OS (RCT MHR) or progression-free survival/time to progression surrogate (RCT surrogate hazard ratio [SHR]) endpoints.

RESULTS

Treatment arm therapies reduced mortality in RCTs relative to controls (average RCT MHR = 0.85; range 0.56-1.10) and lowered progression (average RCT SHR = 0.73; range 0.43-1.03). Among real-world patients who used either the treatment or the control arm regimens evaluated in the relevant RCT, RW MHRs were 0.6% (95% confidence interval -3.5% to 4.8%) higher than RCT MHRs, and RW MHRs were 15.7% (95% confidence interval 11.0% to 20.5%) higher than RCT SHRs.

CONCLUSIONS

Real-world OS treatment benefits were similar to those observed in RCTs based on OS endpoints, but were 16% less than RCT efficacy estimates based on surrogate endpoints. These results, however, varied by tumor and line of therapy.

Value Tools in Managed Care Decision Making: Current Hurdles and Future Opportunities

BACKGROUND

Organizations such as the National Comprehensive Cancer Network, American Society of Clinical Oncology, Institute for Clinical and Economic Review, and Memorial Sloan Kettering have created distinct tools to help different stakeholders assess the value of oncology treatments. However, the oncology value tools were not necessarily created for payers, and it is unclear whether payers are using these tools as part of their drug management process.

OBJECTIVE

To understand what value tools payers are using in oncology management and what benefits and shortcomings the tools may have from the payer perspective.

METHODS

A survey targeting drug coverage decision makers at health plans was conducted in August 2016. Respondents attesting to using 2 or more value tools in drug management were eligible for an additional in-depth interview to understand the respondents' perceived benefits and shortcomings of current value tools. Respondents also were asked to describe desired attributes of a hypothetical payer-centric value tool.

RESULTS

A total of 28 respondents representing approximately 160 million commercially insured medical lives completed the survey. Twenty respondents (71%) reported using at least 1 value tool in their drug management process. Twelve respondents (43%) used at least 2 tools, and 4 respondents (14%) used at least 3 tools. A total of 6 respondents were selected for in-depth interviews. Interviewees praised value tools for advancing the discussion on drug value and incorporating clinical evidence. However, interviewees felt available value tools varied on providing firm recommendations and relevant price benchmarks. Respondents most commonly recommended the following attributes of a proposed payer-centric value framework: taking a firm position on product value; product comparisons in lieu of comparative clinical trials; web-based tool access; and tool updates at least quarterly. Interview respondents also expressed some support for allowing manipulation of inputs and inclusion of quality-of-life and patient-reported outcome data.

CONCLUSIONS

Although nearly half of payers surveyed use 2 or more value tools in the drug management process, payers identified a number of areas where the tools could be revised to increase their utility to payers.

DISCLOSURES

No outside funding or assistance of any kind was used for this research or in manuscript preparation. Schafer and Galante are employed by Precision for Value, a payer ad marketing agency that works exclusively with life science companies. Shafrin is employed by Precision Health Economics, a consulting company to insurance and life science industries. Shafer, along with Galante and Shafrin, contributed to study design, data collection, and manuscript preparation. The authors contributed equally to data analysis and interpretation and manuscript revision.

The cost of adherence mismeasurement in serious mental illness: a claims-based analysis

OBJECTIVES

To quantify how adherence mismeasurement affects the estimated impact of adherence on inpatient costs among patients with serious mental illness (SMI).

STUDY DESIGN

Proportion of days covered (PDC) is a common claims-based measure of medication adherence. Because PDC does not measure medication ingestion, however, it may inaccurately measure adherence. We derived a formula to correct the bias that occurs in adherence-utilization studies resulting from errors in claims-based measures of adherence.

METHODS

We conducted a literature review to identify the correlation between gold-standard and claims-based adherence measures. We derived a bias-correction methodology to address claims-based medication adherence measurement error. We then applied this methodology to a case study of patients with SMI who initiated atypical antipsychotics in 2 large claims databases.

RESULTS

Our literature review identified 6 studies of interest. The 4 most relevant ones measured correlations between 0.38 and 0.91. Our preferred estimate implies that the effect of adherence on inpatient spending estimated from claims data would understate the true effect by a factor of 5.3, if there were no other sources of bias. Although our procedure corrects for measurement error, such error also may amplify or mitigate other potential biases. For instance, if adherent patients are healthier than nonadherent ones, measurement error makes the resulting bias worse. On the other hand, if adherent patients are sicker, measurement error mitigates the other bias.

CONCLUSIONS

Measurement error due to claims-based adherence measures is worth addressing, alongside other more widely emphasized sources of bias in inference.

Estimating the Value of New Technologies That Provide More Accurate Drug Adherence Information to Providers for Their Patients with Schizophrenia

BACKGROUND

Nonadherence to antipsychotic medication among patients with schizophrenia results in poor symptom management and increased health care and other costs. Despite its health impact, medication adherence remains difficult to accurately assess. New technologies offer the possibility of real-time patient monitoring data on adherence, which may in turn improve clinical decision making. However, the economic benefit of accurate patient drug adherence information (PDAI) has yet to be evaluated.

OBJECTIVE

To quantify how more accurate PDAI can generate value to payers by improving health care provider decision making in the treatment of patients with schizophrenia.

METHODS

A 3-step decision tree modeling framework was used to measure the effect of PDAI on annual costs (2016 U.S. dollars) for patients with schizophrenia who initiated therapy with an atypical antipsychotic. The first step classified patients using 3 attributes: adherence to antipsychotic medication, medication tolerance, and response to therapy conditional on medication adherence. The prevalence of each characteristic was determined from claims database analysis and literature reviews. The second step modeled the effect of PDAI on provider treatment decisions based on health care providers' survey responses to schizophrenia case vignettes. In the survey, providers were randomized to vignettes with access to PDAI and with no access. In the third step, the economic implications of alternative provider decisions were identified from published peer-reviewed studies. The simulation model calculated the total economic value of PDAI as the difference between expected annual patient total cost corresponding to provider decisions made with or without PDAI.

RESULTS

In claims data, 75.3% of patients with schizophrenia were found to be nonadherent to their antipsychotic medications. Review of the literature revealed that 7% of patients cannot tolerate medication, and 72.9% would respond to antipsychotic medication if adherent. Survey responses by providers (n = 219) showed that access to PDAI would significantly alter treatment decisions for nonadherent or adherent/poorly controlled patients (P < 0.001). Payers can expect to save $3,560 annually per nonadherent patient who would respond to therapy if adherent. Savings increased to $9,107 per nonadherent patient when PDAI was given to providers who frequently augmented therapy for these patients. Among all poorly controlled patients (i.e., the nonadherent or those who were adherent but unresponsive to therapy), access to PDAI decreased annual patient cost by $2,232. Savings for this group increased to $7,124 per patient when PDAI was given to providers who frequently augmented therapy.

CONCLUSIONS

Access to PDAI significantly improved provider decision making, leading to lower annual health care costs for patients who were nonadherent or adherent but poorly controlled. Additional research is warranted to evaluate how new technologies that accurately monitor adherence would affect health and economic outcomes among patients with serious mental illness.

DISCLOSURES

This study and medical writing assistance was funded by Otsuka Pharmaceutical Development & Commercialization. Shafrin and Schwartz are employees of Precision Health Economics, which received funding from Otsuka Pharmaceutical Development & Commercialization in support of this study. Lakdawalla is Chief Scientific Officer and a founding partner of Precision Health Economics. Schwartz is a consultant for Otsuka Pharmaceutical Development & Commercialization, and Forma is an employee of Otsuka Pharmaceutical Development & Commercialization. The authors presented the abstract for this study as a poster presentation at the AMCP Managed Care & Specialty Pharmacy Annual Meeting, April 19-22, 2016, San Francisco, California. All authors contributed equally to the study design, data collection and analysis, and the writing and revision of the manuscript.

Effects of delays in the adoption of cancer innovation: Case studies of six landmark medications

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Background: Although new oncology treatments have the potential to improve patient health, these innovations take time to reach to real-world patients. In this study, we estimated how delays in the uptake of novel oncology treatments affect real-world patient survival. Methods: This retrospective cohort study used 1991-2013 data from a cancer-registry linked to health care claims (SEER-Medicare). Our endpoint of interest was patient overall survival. We used variability in the adoption of new cancer treatments across aggregated Metropolitan Statistical Areas (MSAs) (n = 50) as a “natural experiment” that assigned treatments randomly across patients, depending entirely on where they live. This approach recovers the effect of the new treatment on the overall survival of the “marginal patient,” who received treatment solely because she resides in an area with faster uptake. This framework was applied to six case studies: trastuzumab (breast), bevacizumab (colorectal), bevacizumab (lung), erlotinib (lung), bortezomib (myeloma) and lenalidomide (myeloma). Results: Among the 92,496 patients in the study, the difference between adoption rates among eligible patients for MSAs at the 90th percentile and those at the 10th percentile was 20.1 percentage points, with the largest differences being for bevacizumab (colorectal) (51.2% at the 90th percentile MSA vs. 20.9% at the 10th percentile), and smallest for erlotinib (10.3% vs. 2.8%). Median OS among eligible patients gaining access to these landmark therapies increased by 9.6 months. Survival improvements were largest for the lenalidomide case study (33.4 months OS improvement, p < 0.005) followed by erlotinib (21.2 mo., p < 0.001), trastuzumab (19.2 mo., p = 0.016), bevacizumab for lung (7.4 mo., p = 0.002), bevacizumab for colorectal cancer (4.0 mo., p = 0.062), and bortezomib (2.9 mo., p = 0.630). Conclusions: Improving the speed at which landmark treatments are adopted in practice—through physician education and outreach or more generous health insurance access policies—has the potential to improve real-world survival for cancer patients.

Patient Versus Physician Valuation of Durable Survival Gains: Implications for Value Framework Assessments

BACKGROUND

Previous research indicates that patients value therapies that provide durable or tail-of-the-curve survival gains, but it is unclear whether physicians share these preferences.

OBJECTIVE

To compare patient and physician preferences for treatments with a positive probability of durable survival gains relative to those with fixed survival gains.

METHODS

Patients with advanced stage melanoma or lung cancer and the oncologists who treated these patients were surveyed. The primary end point was the share of respondents who selected a therapy with a variable survival profile, with some patients experiencing long-term durable survival and others experiencing much shorter survival, compared to a therapy with a fixed survival duration. Parameter estimation by sequential testing was applied to calculate the length of nonvarying survival that would make respondents indifferent between that survival and therapy with durable survival.

RESULTS

The sample comprised 165 patients (lung = 84, melanoma = 81) and 98 physicians. For lung cancer, 65.5% of patients preferred the therapy with a variable survival profile, compared with 40.8% of physicians (Δ = 24.7%; P < 0.001). For melanoma, these figures were 63.0% for patients and 29.7% for physicians (Δ = 33.3%; P < 0.001). Patients' indifference point implied that therapies with a variable survival profile are preferred unless the treatment with fixed survival had 13.6 months (melanoma) or 11.6 months (lung) longer mean survival; physicians would prescribe treatments with a fixed survival if the treatment had 7.5 months (melanoma) or 1.0 month (lung) shorter survival than the variable survival profile.

CONCLUSIONS

Patients place a high value on therapies that provide a chance of durable or "tail-of-the-curve" survival, whereas physicians do not. Value frameworks should incorporate measures of tail-of-the-curve survival gains into their methodologies.

Access to credible information on schizophrenia patients' medication adherence by prescribers can change their treatment strategies: evidence from an online survey of providers

OBJECTIVE

Overestimating patients' medication adherence diminishes the ability of psychiatric care providers to prescribe the most effective treatment and to identify the root causes of treatment resistance in schizophrenia. This study was conducted to determine how credible patient drug adherence information (PDAI) might change prescribers' treatment decisions.

METHODS

In an online survey containing 8 clinical case vignettes describing patients with schizophrenia, health care practitioners who prescribe antipsychotics to patients with schizophrenia were instructed to choose a preferred treatment recommendation from a set of predefined pharmacologic and non-pharmacologic options. The prescribers were randomly assigned to an experimental or a control group, with only the experimental group receiving PDAI. The primary outcome was the prescribers' treatment choice for each case. Between-group differences were analyzed using multinomial logistic regression.

RESULTS

A convenience sample (n=219) of prescribers completed the survey. For 3 nonadherent patient vignettes, respondents in the experimental group were more likely to choose a long-acting injectable antipsychotic compared with those in the control group (77.7% experimental vs 25.8% control; P<0.001). For 2 adherent but poorly controlled patient vignettes, prescribers who received PDAI were more likely to increase the antipsychotic dose compared with the control group (49.1% vs 39.1%; P<0.001). For the adherent and well-controlled patient vignette, respondents in both groups made similar treatment recommendations across all choices (P=0.099), but respondents in the experimental arm were more likely to recommend monitoring clinical stability (87.2% experimental vs 75.5% control, reference group).

CONCLUSION

The results illustrate how credible PDAI can facilitate more appropriate clinical decisions for patients with schizophrenia.

Geographic Variation in Diagnostic Ability and Quality of Care Metrics: A Case Study of Ankylosing Spondylitis and Low Back Pain

Studies examining geographic variation in care for low back pain often focus on process and outcome measures conditional on patient diagnosis but generally do not take into account a physician's ability to diagnose the root cause of low back pain. In our case study, we used increased detection of ankylosing spondylitis-a relatively rare inflammatory back disease-as a proxy for diagnostic ability and measured the relationship between ankylosing spondylitis detection, potentially inappropriate low back pain care, and cost. Using 5 years of health insurance claims data, we found significant variation in ankylosing spondylitis detection across metropolitan statistical areas (MSAs), with 8.1% of the variation in detection explained by a region's racial composition. Furthermore, low back pain patients in MSAs with higher ankylosing spondylitis detection had 7.9% lower use of corticosteroids, 9.0% lower use of opioids, and 8.2% lower pharmacy cost, compared with patients living in low-detection MSAs.

Quality-adjusted cost of care: a meaningful way to measure growth in innovation cost versus the value of health gains

Technology drives both health care spending and health improvement. Yet policy makers rarely see measures of cost growth that account for both effects. To fill this gap, we present the quality-adjusted cost of care, which illustrates cost growth net of growth in the value of health improvements, measured as survival gains multiplied by the value of survival. We applied the quality-adjusted cost of care to two cases. For colorectal cancer, drug cost per patient increased by $34,493 between 1998 and 2005 as a result of new drug launches, but value from offsetting health improvements netted a modest $1,377 increase in quality-adjusted cost of care. For multiple myeloma, new therapies increased treatment cost by $72,937 between 2004 and 2009, but offsetting health benefits lowered overall quality-adjusted cost of care by $67,863. However, patients with multiple myeloma on established first-line therapies saw costs rise without corresponding benefits. All three examples document rapid cost growth, but they provide starkly different answers to the question of whether society got what it paid for.

Geographic Variation in the Quality and Cost of Care for Patients with Rheumatoid Arthritis

BACKGROUND

There is considerable push to improve value in health care by simultaneously increasing quality while lowering or containing costs. However, for diseases that are best treated with comparatively expensive treatments, such as rheumatoid arthritis (RA), there could be tension between these aims. In this study, we measured geographic variation in quality, access, and cost for patients with RA, a disease with effective but costly specialty treatments.

OBJECTIVE

To assess the geographic differences in the quality, access, and cost of care for patients with RA.

METHODS

Using large claims databases covering the period between 2008 and 2014, we measured quality of care metrics by metropolitan statistical areas (MSAs) for patients with RA. Quality measures included use of disease-modifying antirheumatic drugs (DMARDs) and tuberculosis (TB) screening before initiating biologic DMARD therapy. Access to care measures included measured detection and the share of patients with RA who visited a rheumatologist. Regression models were used to control for differences in patient demographics and health status across MSAs.

RESULTS

For the 501,376 patients diagnosed with RA, in the average MSA 64.1% of RA patients received a DMARD, and 29.6% of RA patients initiating a biologic DMARD appropriately received a TB screening. Only 17% (73/430) of MSAs comprised the top 2 Medicare Advantage star ratings for DMARD use. Measured detection was 0.59% (IQR = 0.47%-0.71%; CV = 0.355) on average, and 57.6% (IQR = 48%-69%; CV = 0.341) of RA patients visited a rheumatologist. MSAs with the highest DMARD use spent $26,724 (in 2015 U.S. dollars) annually treating patients with RA, $5,428 more (P < 0.001) than low DMARD-use MSAs, largely because of higher pharmacy cost ($5,090 vs. $7,610, P < 0.001). However, MSAs with higher DMARD use had lower RA-related inpatient cost ($1,890 vs. $2,342, P = 0.024).

CONCLUSIONS

There were significant geographic variations in the quality of care received by patients with RA, although quality was poor in most areas. Fewer than 1 in 5 MSAs could be considered high quality based on patient DMARD use. Access to specialist care may be an issue, since just over half of patients with RA visited a rheumatologist annually. Efforts to incentivize better quality of care holds promise in terms of unlocking value for patients, but for some diseases, this approach may result in higher costs.

DISCLOSURES

The research reported in this manuscript was supported by AbbVie through consulting fees paid to Precision Health Economics (PHE). AbbVie and PHE collaborated to develop the study design and protocol. AbbVie and PHE participated in the interpretation of data, review, and approval of the manuscript. Shafrin and Shim are employed by PHE. Ganguli and Sanchez Gonzalez are employed by AbbVie. Seabury reports consulting fees from PHE. The results from this study were presented in poster form at the Academy of Managed Care Pharmacy's 2015 Annual Meeting and Expo; April 7-10, 2015; San Diego, California, and at the Academy of Managed Care Pharmacy's 2016 Annual Meeting and Expo; April 19-22, 2016; San Francisco, California. Study concept and design were contributed primarily by Shafrin, along with Ganguli and Seabury. Shafrin and Shim took the lead in data collection, and data interpretation was performed by Ganguli, Sanchez Gonzalez, Seabury, and Shafrin. The manuscript was written primarily by Shafrin, along with Shim and Seabury, and revised primarily by Ganguli, along with Sanchez Gonzalez and Seabury.

Patterns of Adherence to Oral Atypical Antipsychotics Among Patients Diagnosed with Schizophrenia

BACKGROUND

Poor medication adherence contributes to negative treatment response, symptom relapse, and hospitalizations in schizophrenia. Many health plans use claims-based measures like medication possession ratios or proportion of days covered (PDC) to measure patient adherence to antipsychotics. Classifying patients solely on the basis of a single average PDC measure, however, may mask clinically meaningful variations over time in how patients arrive at an average PDC level.

OBJECTIVE

To model patterns of medication adherence evolving over time for patients with schizophrenia who initiated treatment with an oral atypical antipsychotic and, based on these patterns, to identify groups of patients with different adherence behaviors.

METHODS

We analyzed health insurance claims for patients aged ≥ 18 years with schizophrenia and newly prescribed oral atypical antipsychotics in 2007-2013 from 3 U.S. insurance claims databases: Truven MarketScan (Medicaid and commercial) and Humana (Medicare). Group-based trajectory modeling (GBTM) was used to stratify patients into groups with distinct trends in adherence and to estimate trends for each group. The response variable was the probability of adherence (defined as PDC ≥ 80%) in each 30-day period after the patient initiated antipsychotic therapy. GBTM proceeds from the premise that there are multiple distinct adherence groups. Patient demographics, health status characteristics, and health care resource use metrics were used to identify differences in patient populations across adherence trajectory groups.

RESULTS

Among the 29,607 patients who met the inclusion criteria, 6 distinct adherence trajectory groups emerged from the data: adherent (33%); gradual discontinuation after 3 months (15%), 6 months (7%), and 9 months (5%); stop-start after 6 months (15%); and immediate discontinuation (25%). Compared to patients 18-24 years of age in the adherent group, patients displaying a stop-start pattern after 6 months had greater odds of having a history of drug abuse (OR = 1.46; 95% CI = 1.26-1.66; P < 0.001), alcohol abuse (OR = 1.34; 95% CI = 1.14-1.53; P< 0.001), and a codiagnosis of major depressive disorder (OR = 1.24; 95% CI = 1.05-1.44; P < 0.001) and were less likely to be aged 35-54 years (OR = 0.66; 95% CI = 0.46-0.85; P < 0.001).

CONCLUSIONS

Longitudinal medication adherence patterns can be expressed as distinct trajectories associated with specific patient characteristics and health care utilization patterns. We found 6 distinct patterns of adherence to antipsychotics over 12 months. Patients in different groups may warrant different types of clinical interventions to prevent hospitalizations, longer hospital stays, and increased clinical complexity. For example, clinicians may consider regular home visits, assertive community treatment, and other related interventions for patients at high risk of immediate discontinuation. Health plans should consider supplementing claims-based adherence measures with new technologies that are able to track patient adherence patterns over time.

DISCLOSURES

Otsuka Pharmaceutical Development & Commercialization provided support for this research. MacEwan and Shafrin are employees of Precision Health Economics, which was contracted by Otsuka Pharmaceutical Development & Commercialization to conduct this study. Lakdawalla is the Chief Scientific Officer and a founding partner of Precision Health Economics. Forma is an employee of Otsuka Pharmaceutical Development & Commercialization. Hatch is a former employee of Otsuka Pharmaceutical Development & Commercialization and is a current employee of ODH, Inc. Lindenmayer has received grant/research support from Janssen, Lilly, AstraZeneca, Johnson & Johnson, Pfizer, BMS, Otsuka, Dainippon, and Roche and is a consultant for Janssen, Lilly, Merck, Shire, and Lundbeck. Portions of this study were presented as a poster at the American Society of Clinical Psychopharmacology Annual Meeting in Miami Beach, Florida; June 23, 2015; and at the 28th Annual U.S. Psychiatric and Mental Health Congress; San Diego, California; September 12, 2015. Study concept and design were contributed by Forma, Ladkawalla, MacEwan, and Shafrin, along with Hatch and Lindenmayer. MacEwan, Shafrin, Forma, and Lakdawalla collected the data, along with Hatch and Lindenmayer. Data interpretation was performed by Hatch, Lindenmayer, MacEwan, and Shafrin, assisted by Forma and Lakdawalla. The manuscript was written and revised by MacEwan, Forma, and Shafrin, along with Hatch Lakdawalla, and Lindenmayer.

Physician and Patient Preferences for Nonvalvular Atrial Fibrillation Therapies

OBJECTIVES

The objective of this study was to compare patient and physician preferences for different antithrombotic therapies used to treat nonvalvular atrial fibrillation (NVAF).

METHODS

Patients diagnosed with NVAF and physicians treating such patients completed 12 discrete choice questions comparing NVAF therapies that varied across five attributes: stroke risk, major bleeding risk, convenience (no regular blood testing/dietary restrictions), dosing frequency, and patients' out-of-pocket cost. We used a logistic regression to estimate the willingness-to-pay (WTP) value for each attribute.

RESULTS

The 200 physicians surveyed were willing to trade off $38 (95% confidence interval [CI] $22 to $54] in monthly out-of-pocket cost for a 1% (absolute) decrease in stroke risk, $14 (95% CI $8 to $21) for a 1% decrease in major bleeding risk, and $34 (95% CI $9 to $60) for more convenience. The WTP value among 201 patients surveyed was $30 (95% CI $18 to $42) for reduced stroke risk, $16 (95% CI $9 to $24) for reduced bleeding risk, and -$52 (95% CI -$96 to -6) for convenience. The WTP value for convenience among patients using warfarin was $9 (95% CI $1 to $18) for more convenience, whereas patients not currently on warfarin had a WTP value of -$90 (95% CI -$290 to -$79). Both physicians' and patients' WTP value for once-daily dosing was not significantly different from zero. On the basis of survey results, 85.0% of the physicians preferred novel oral anticoagulants (NOACs) to warfarin. NOACs (73.0%) were preferred among patients using warfarin, but warfarin (78.2%) was preferred among patients not currently using warfarin. Among NOACs, both patients and physicians preferred apixaban.

CONCLUSIONS

Both physicians and patients currently using warfarin preferred NOACs to warfarin. Patients not currently using warfarin preferred warfarin over NOACs because of an apparent preference for regular blood testing/dietary restrictions.