Determinants of U.S. Prescription Drug Utilization using County Level Data

Optimization of Medication Use at Accountable Care Organizations

BACKGROUND

Optimized medication use involves the effective use of medications for better outcomes, improved patient experience, and lower costs. Few studies systematically gather data on the actions accountable care organizations (ACOs) have taken to optimize medication use.

OBJECTIVES

To (a) assess how ACOs optimize medication use; (b) establish an association between efforts to optimize medication use and achievement on financial and quality metrics; (c) identify organizational factors that correlate with optimized medication use; and (d) identify barriers to optimized medication use.

METHODS

This cross-sectional study consisted of a survey and interviews that gathered information on the perceptions of ACO leadership. The survey contained a medication practices inventory (MPI) composed of 38 capabilities across 6 functional domains related to optimizing medication use. ACOs completed self-assessments that included rating each component of the MPI on a scale of 1 to 10. Fisher's exact tests, 2-proportions tests, t-tests, and logistic regression were used to test for associations between ACO scores on the MPI and performance on financial and quality metrics, and on ACO descriptive characteristics.

RESULTS

Of the 847 ACOs that were contacted, 49 provided usable survey data. These ACOs rated their own system's ability to manage the quality and costs of optimizing medication use, providing a 64% and 31% affirmative response, respectively. Three ACOs achieved an overall MPI score of 8 or higher, 45 scored between 4 and 7.9, and 1 scored between 0 and 3.9. Using the 3 score groups, the study did not identify a relationship between MPI scores and achievement on financial or quality benchmarks, ACO provider type, member volume, date of ACO creation, or the presence of a pharmacist in a leadership position. Barriers to optimizing medication use relate to reimbursement for pharmacist integration, lack of health information technology interoperability, lack of data, feasibility issues, and physician buy-in.

CONCLUSIONS

Compared with 2012 data, data on ACOs that participated in this study show that they continue to build effective strategies to optimize medication use. These ACOs struggle with both notification related to prescription use and measurement of the influence optimized medication use has on costs and quality outcomes. Compared with the earlier study, these data find that more ACOs are involving pharmacists directly in care, expanding the use of generics, electronically transmitting prescriptions, identifying gaps in care and potential adverse events, and educating patients on therapeutic alternatives. ACO-level policies that facilitate practices to optimize medication use are needed. Integrating pharmacists into care, giving both pharmacists and physicians access to clinical data, obtaining physician buy-in, and measuring the impact of practices to optimize medication use may improve these practices.

DISCLOSURES

This research was sponsored and funded by the National Pharmaceutical Council (NPC), an industry funded health policy research group that is not involved in lobbying or advocacy. Employees of the sponsor contributed to the research questions, determination of the relevance of the research questions, and the research design. Specifically, there was involvement in the survey and interview instruments. They also contributed to some data interpretation and revision of the manuscript. Leavitt Partners was hired by NPC to conduct research for this study and also serves a number of health care clients, including life sciences companies, provider organizations, accountable care organizations, and payers. Westrich and Dubois are employed by the NPC. Wilks, Krisle, Lunner, and Muhlestein are employed by Leavitt Partners and did not receive separate compensation. Study concept and design were contributed by Krisle, Dubois, and Muhlestein, along with Lunner and Westrich. Krisle and Muhlestein collected the data, and data interpretation was performed by Wilks, Krisle, and Muhlestein, along with Dubois and Westrich. The manuscript was written primarily by Wilks, along with Krisle and Muhlestein, and revised by Wilks, Westrich, Lunner, and Krisle. Preliminary versions of this work were presented at the following: National Council for Prescription Drug Programs Educational Summit, November 1, 2016; Academy Health 2016 Annual Research Meeting, June 27, 2016; Accountable Care Learning Collaborative Webinar, June 16, 2016; the 21st Annual PBMI Drug Benefit Conference, February 29, 2016; National Value-Based Payment and Pay for Performance Summit, February 17, 2016; National Accountable Care Congress, November 17, 2015; and American Journal of Managed Care's ACO Emerging Healthcare Delivery Coalition, Fall 2015 Live Meeting, October 15, 2015.

Optimization of Medication Use at Accountable Care Organizations

BACKGROUND

Optimized medication use involves the effective use of medications for better outcomes, improved patient experience, and lower costs. Few studies systematically gather data on the actions accountable care organizations (ACOs) have taken to optimize medication use.

OBJECTIVES

To (a) assess how ACOs optimize medication use; (b) establish an association between efforts to optimize medication use and achievement on financial and quality metrics; (c) identify organizational factors that correlate with optimized medication use; and (d) identify barriers to optimized medication use.

METHODS

This cross-sectional study consisted of a survey and interviews that gathered information on the perceptions of ACO leadership. The survey contained a medication practices inventory (MPI) composed of 38 capabilities across 6 functional domains related to optimizing medication use. ACOs completed self-assessments that included rating each component of the MPI on a scale of 1 to 10. Fisher's exact tests, 2-proportions tests, t-tests, and logistic regression were used to test for associations between ACO scores on the MPI and performance on financial and quality metrics, and on ACO descriptive characteristics.

RESULTS

Of the 847 ACOs that were contacted, 49 provided usable survey data. These ACOs rated their own system's ability to manage the quality and costs of optimizing medication use, providing a 64% and 31% affirmative response, respectively. Three ACOs achieved an overall MPI score of 8 or higher, 45 scored between 4 and 7.9, and 1 scored between 0 and 3.9. Using the 3 score groups, the study did not identify a relationship between MPI scores and achievement on financial or quality benchmarks, ACO provider type, member volume, date of ACO creation, or the presence of a pharmacist in a leadership position. Barriers to optimizing medication use relate to reimbursement for pharmacist integration, lack of health information technology interoperability, lack of data, feasibility issues, and physician buy-in.

CONCLUSIONS

Compared with 2012 data, data on ACOs that participated in this study show that they continue to build effective strategies to optimize medication use. These ACOs struggle with both notification related to prescription use and measurement of the influence optimized medication use has on costs and quality outcomes. Compared with the earlier study, these data find that more ACOs are involving pharmacists directly in care, expanding the use of generics, electronically transmitting prescriptions, identifying gaps in care and potential adverse events, and educating patients on therapeutic alternatives. ACO-level policies that facilitate practices to optimize medication use are needed. Integrating pharmacists into care, giving both pharmacists and physicians access to clinical data, obtaining physician buy-in, and measuring the impact of practices to optimize medication use may improve these practices.

DISCLOSURES

This research was sponsored and funded by the National Pharmaceutical Council (NPC), an industry funded health policy research group that is not involved in lobbying or advocacy. Employees of the sponsor contributed to the research questions, determination of the relevance of the research questions, and the research design. Specifically, there was involvement in the survey and interview instruments. They also contributed to some data interpretation and revision of the manuscript. Leavitt Partners was hired by NPC to conduct research for this study and also serves a number of health care clients, including life sciences companies, provider organizations, accountable care organizations, and payers. Westrich and Dubois are employed by the NPC. Wilks, Krisle, Lunner, and Muhlestein are employed by Leavitt Partners and did not receive separate compensation. Study concept and design were contributed by Krisle, Dubois, and Muhlestein, along with Lunner and Westrich. Krisle and Muhlestein collected the data, and data interpretation was performed by Wilks, Krisle, Muhlestein, along with Dubois and Westrich. The manuscript was written primarily by Wilks, along with Krisle and Muhlestein, and revised by Wilks, Westrich, Lunner, and Krisle. Preliminary versions of this work were presented at the following: National Council for Prescription Drug Programs Educational Summit, November 1, 2016; Academy Health 2016 Annual Research Meeting, June 27, 2016; Accountable Care Learning Collaborative Webinar, June 16, 2016; the 21st Annual PBMI Drug Benefit Conference, February 29, 2016; National Value-Based Payment and Pay for Performance Summit, February 17, 2016; National Accountable Care Congress, November 17, 2015; and American Journal of Managed Care's ACO Emerging Healthcare Delivery Coalition, Fall 2015 Live Meeting, October 15, 2015.