Economic modeling to evaluate the impact of chronic myeloid leukemia therapy management on the oncology care model in the US.

Objective: To develop an economic model to evaluate changes in healthcare costs driven by restricting usage of branded tyrosine kinase inhibitors (TKIs) through substitution with generic imatinib among chronic myeloid leukemia (CML) patients in a typical Oncology Care Model (OCM) practice, and examine the impact on Performance-Based Payment (PBP) eligibility. Methods: An Excel-based economic model of an OCM practice with 1,000 cancer patients during a 6-month episode of care was developed. Cancer types and proportions of patients treated in the practice were estimated from an OCM report. All-cause healthcare costs were obtained from published literature. It was assumed that if a practice restricts usage of branded TKIs for newly-diagnosed CML patients, 80% of the market share of branded imatinib and 50% of the market shares of 2nd-gen TKIs would shift to generic imatinib. Among established TKI-treated patients, it was assumed that 80% of the market share of branded imatinib and no patients treated with 2nd-gen TKIs would shift to the generic. Results: Four CML patients were estimated for a 1,000-cancer patient OCM practice with a total baseline healthcare cost of $51,345,812 during a 6-month episode. If the practice restricts usage of branded TKIs, the shift from 2nd-gen TKIs to generic imatinib would reduce costs by $12,970, while shifting from branded to generic imatinib lowers costs by $25,250 during a 6-month episode. Minimum reductions of $3,013,832 in a one-sided risk model and $2,372,010 in a two-sided risk model are required for PBP eligibility; the shift from 2nd-gen TKIs to generic imatinib would account for 0.4% and 0.5% of the savings required for a PBP, respectively. Conclusions: This analysis indicates that the potential cost reduction associated with restricting branded TKI usage among CML patients in an OCM setting will represent only a small proportion of the cost reduction needed for PBP eligibility.

Valuable features in mobile health apps for patients and consumers: content analysis of apps and user ratings.

BACKGROUND: The explosion of mobile phones with app capabilities coupled with increased expectations of the patient-consumers' role in managing their care presents a unique opportunity to use mobile health (mHealth) apps. OBJECTIVES: The aim of this paper is to identify the features and characteristics most-valued by patient-consumers ("users") that contribute positively to the rating of an app. METHODS: A collection of 234 apps associated with reputable health organizations found in the medical, health, and fitness categories of the Apple iTunes store and Google Play marketplace was assessed manually for the presence of 12 app features and characteristics. Regression analysis was used to determine which, if any, contributed positively to a user's rating of the app. RESULTS: Analysis of these 12 features explained 9.3% (R(2)=.093 n=234, P<.001) of the variation in an app's rating, with only 5 reaching statistical significance. Of the 5 reaching statistical significance, plan or orders, export of data, usability, and cost contributed positively to a user's rating, while the tracker feature detracted from it. CONCLUSIONS: These findings suggest that users appreciate features that save time over current methods and identify an app as valuable when it is simple and intuitive to use, provides specific instructions to better manage a condition, and shares data with designated individuals. Although tracking is a core function of most health apps, this feature may detract from a user's experience when not executed properly. Further investigation into mHealth app features is worthwhile given the inability of the most common features to explain a large portion of an app's rating. In the future, studies should focus on one category in the app store, specific diseases, or desired behavior change, and methods should include measuring the quality of each feature, both through manual assessment and evaluation of user reviews. Additional investigations into understanding the impact of synergistic features, incentives, social media, and gamification are also warranted to identify possible future trends.