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Analysis of 2016 Connecticut ACO Medicare Shared Savings Program Data to Identify Opportunities for Population Health Pharmacist Services
Kathryn Steckowych, PharmD; Marie Smith, PharmD; and Yan Zhuang, PhD
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Analysis of 2016 Connecticut ACO Medicare Shared Savings Program Data to Identify Opportunities for Population Health Pharmacist Services

Kathryn Steckowych, PharmD; Marie Smith, PharmD; and Yan Zhuang, PhD
Publicly reported Medicare Shared Savings Program accountable care organization (ACO) data can be analyzed to identify cost and medication-related quality performance improvement opportunities to support pharmacist integration into ACO population health services.
ABSTRACT

Objectives: To discuss the use of publicly reported Medicare Shared Savings Program (MSSP) accountable care organization (ACO) data to determine cost and medication-related quality performance improvement opportunities, analyze Connecticut MSSP ACO cost and quality performance data to identify significant findings and directional trends, and demonstrate how clinical pharmacy leaders can use this analytical approach to facilitate conversations with ACO executive leaders for pharmacist service integration. 

Methods: The 2016 MSSP ACO data set was used to analyze cost and medication-related quality performance metrics for 13 Connecticut ACOs. Research questions were formulated to identify significant (1) correlations between 30-day all-cause hospital readmission (HR) or emergency department (ED) utilization rates and ACO cost or medication-related quality metric performance and (2) associations between ACO governance and ACO cost or medication-related quality metric performance. Descriptive trends analyses were performed to explain differences in cost and medication-related quality performance according to ACO governance.

Results: Statistically significant correlations were identified between (1) HR and/or ED utilization rates and several per capita expenditures or medication-related quality performance metrics and (2) ACO governance and per capita total expenditures or per capita skilled nursing facility expenditures. Looking at directional trends, health system–governed ACOs had greater total and per capita expenditures for all cost performance metrics, except per capita physician/supplier expenditures. Physician-governed ACOs performed better on all medication-related quality metrics.

Conclusions: Analysis of publicly reported MSSP ACO data can identify cost and medication-related quality performance improvement opportunities. Pharmacists can use such data for conversations with C-suite executive leaders about integrating population health pharmacist services in ACOs.

The American Journal of Accountable Care. 2018;6(4):e1-e10
In 2008, the Triple Aim was developed to “improve the experience of care, improve the health of populations, and reduce per capita costs of health care.”1 The Triple Aim guided the Center for Medicare and Medicaid Innovation to develop the first accountable care organization (ACO) model in 2012, known as the Pioneer ACO Model.2 This care delivery and healthcare payment transformation initiative allowed high-functioning healthcare organizations to test new payment models based on shared savings and population-based payments.2 As of 2016, more than 400 ACOs in the Medicare Shared Savings Program (MSSP) have been implemented.3

The MSSP is a value-based healthcare payment model that rewards healthcare organizations for delivering high-quality care while reducing total healthcare costs.4 Organizations involved in an MSSP contract must meet quality performance scores for several metrics in order to share in the generated savings with CMS. In the 2016 reporting year, MSSP ACOs were required to report year-end quality performance for 33 metrics spanning a variety of clinical foci, including medication-related process and outcome metrics.5 Many ACOs have not yet integrated pharmacists due to challenges with reimbursement for pharmacist services and identifying high-impact quality improvement opportunities for pharmacists.6

In this paper, we describe the use of publicly available MSSP ACO data in Connecticut to determine opportunities for improvement in cost and medication-related quality performance. Then, we discuss the significant findings and directional trend analyses for ACO cost and medication-related quality performance outcomes. We also describe one approach to identifying the impact of pharmacists on cost and medication-related quality by demonstrating how clinical pharmacist leaders can facilitate conversations with ACO executive leaders to explore pharmacist service integration.

METHODS

Each year, CMS publishes a public compilation of cost and quality performance data for MSSP ACOs across the country.7 Data for the 2016 reporting year5 were analyzed to evaluate cost and medication-related quality performance for 13 Connecticut ACOs. Here, we explain our ACO data analysis approach.

Extraction of Connecticut ACO Data

We extracted the MSSP data5 for ACOs with networks based solely in Connecticut or ACOs with multistate networks that included Connecticut.

Review of MSSP Data Set

To ensure accurate interpretations of the data used in the analyses, we reviewed the definitions of all cost and quality performance metrics reported within the 2016 MSSP ACO data dictionary.8 This tool provides detailed explanations of each cost and quality metric, including the numerators and denominators used to report the data.

Identification of Research Questions

The following research questions guided the MSSP ACO data analyses: (1) What is the correlation between ACO cost performance and 30-day all-cause hospital readmissions (HRs) or emergency department (ED) utilization? (2) What is the correlation between ACO medication-related quality metric performance and HR rates or ED utilization? (3) What is the association between ACO cost performance and ACO governance? and (4) What is the association between ACO medication-related quality metric performance and ACO governance?

Hospital and ED utilization and cost/quality performance. Two of the aforementioned research questions explored correlations between HRs or ED utilization and (1) ACO cost performance or (2) ACO medication-related quality performance. We selected this approach because hospitalizations, including readmissions, and ED visits are large drivers of total healthcare costs.9 Additionally, 38% of the Connecticut ACOs are governed by health systems that are invested in efforts to reduce preventable HRs and unnecessary ED visits. Therefore, the impact of integrated population health pharmacists on reducing medication-related hospital and ED utilization could potentially lead to significant reductions in ACO total healthcare expenditures.

ACO governance and cost/quality performance. The remaining 2 research questions explored associations between ACO governance models and cost or medication-related quality performance metrics. This was done to determine if quality improvement opportunities varied across ACOs with different governance structures. We categorized each Connecticut ACO as either physician-governed (PG) or health system–governed (HSG) based on publicly reported governance information found on each health system’s website. PG ACOs “may include single or multiple owners (ie, physician groups/practices) but are characterized by providing outpatient care directly to their patient population and contracting with other providers to provide hospital or other services.”10 HSG ACOs “may have a single or multiple owners (ie, hospital) with at least one owner providing direct inpatient services. Outpatient services may be provided directly if the owner(s) is an integrated health system or physician-hospital organization.”10

Selection of Cost and Medication-Related Quality Metrics
The definitions of cost and medication-related quality performance metrics were reviewed to select metrics that had strong relevance to medication therapy or the potential for clinical impact by a population health pharmacist. Eight cost performance metrics and 10 medication-related quality performance metrics were used in the statistical analyses.


 
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