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The American Journal of Managed Care September 2016
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Measuring the Cost Implications of the Collaborative Accountable Care Initiative in Texas
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Measuring the Cost Implications of the Collaborative Accountable Care Initiative in Texas

Vivian Ho, PhD; Timothy K. Allen, PhD; Urie Kim, BBA; William P. Keenan, BA; Meei-Hsiang Ku-Goto, MA; and Mark Sanderson, PhD
A private accountable care organization model with an embedded care coordinator and a list of recommended providers yields cost savings similar to initiatives with risk-based contracts.
ABSTRACT

Objectives:
We analyzed changes in healthcare spending associated with the implementation of Cigna’s Collaborative Accountable Care (CAC) initiative in a large multi-clinic physician practice.

Study Design: We compared claims from 2009, prior to the CAC initiative, against claims for 2010 to 2011, contrasting the patients covered by Cigna’s CAC initiative with patients in other practices in the same geographic area covered by Cigna’s medical plan.

Methods: We used a propensity weighted difference-in-differences approach, adjusting for age, sex, health status, and secular trends to isolate the treatment effect of the CAC.

Results: The CAC initiative resulted in a 5.7% reduction in net spending per patient for 2010 to 2011, relative to what spending would have been without the initiative. This reduced spending was evident in multiple service categories: evaluation and management, procedures, imaging, tests, and durable medical equipment. Professional payments, inpatient facility, and outpatient facility payments for Medical Clinic of North Texas enrollees all experienced significant cost savings relative to the control group. About half of the savings resulted from using lower-priced sources.

Conclusions: The CAC initiative, which includes an embedded care coordinator and a list of recommended providers, was associated with cost savings similar to those reported by other initiatives, such as global budgets and risk-based contracts.

Am J Manag Care. 2016;22(9):e304-e310
Despite the proliferation of private accountable care organizations, few studies have examined whether they yield potential cost savings relative to fee-for-service medicine. We tested whether a shared savings contract between a large insurer and a multi-clinic physician practice saved money over a 2-year period. 
  • Cigna’s Collaborative Accountable Care initiative achieved a 5.7% reduction in net spending per patient for 2010 to 2011, relative to what spending would have been without the initiative. 
  • Significant cost savings, relative to the control group, were achieved with inpatient facility, outpatient facility, and other medical service payments.
  • About half of the savings resulted from using lower-priced sources of care.
Accountable care organizations (ACOs) are provider-led organizations with a strong base of primary care providers who are collectively accountable for the quality and per-capita costs across the full continuum of healthcare for a population of patients.1-4 As part of the Affordable Care Act, many provider organizations have formed ACOs that are reimbursed for the care provided to Medicare patients. Under Medicare’s program, ACOs share in any savings and, in some cases, excesses, in the cost of care provided, relative to historic benchmarks.5

A recent report estimates that there are 782 ACOs across the country, with 54% operated by private payers.6 Private ACOs differ greatly in form and size. They can be led by a hospital or hospital system, or include physician practices only.7 Provider reimbursement could take the form of shared savings in a fee-for-service (FFS) environment or as limited or substantial capitation arrangements. Private insurers also differ in the performance measures used to track quality.1 The criteria used for provider selection also differ across insurers, as does the level of technical assistance provided to participating providers (eg, disease management or health information exchange support).8

Several policy experts and clinicians have written about the potential advantages of ACOs for improving the quality of healthcare and controlling healthcare cost growth,3,7,9,10 and many other papers have focused on advice for structuring or regulating ACOs.1,11-14 There has been extensive literature—we are unable to fully acknowledge it here—examining the cost and/or quality implications of integrated care, which is one important feature of ACOs.15-25 Meanwhile, there are fewer studies documenting the actual performance of ACOs, which include incentive payments for providers on cost or quality metrics.26-36

A 2012 publication reported the early results on patient costs and outcomes for Cigna’s Collaborative Accountable Care (CAC) initiative for physician practices in 3 parts of the country: Arizona, New Hampshire, and Texas.28 This initiative is a shared savings program that offers practices, in their first year of participation, an upfront care coordination fee to pay for investments in infrastructure that furthers progress toward quality and cost targets. Cigna provided substantial support in informatics, care coordination, and consultation to aid participating practices. After the first year of intervention, Cigna analyzed medical claims and found no significant decrease in medical costs compared with expected costs for 2010. Other than this paper, we are aware of only 5 other studies of the cost effects of private ACO programs that have included a control group in their performance assessment.26,27,34-36 All of these studies examined the cost and/or quality impact of the Blue Cross Blue Shield (BCBS) Alternative Quality Contract in Massachusetts; the combined results suggest that the program lowered spending and improved quality overall, although effects differed for specific patient populations and conditions.

In this study, we report more detailed results after 2 years of CAC implementation for the physician practice in Texas (Medical Clinic of North Texas, P.A.). Using longer-term data, we compare the cost trends for physicians participating in Cigna’s initiative, relative to physicians in the surrounding market. We also compare the trends in costs by type of service and site of care in order to assess whether these trend differences were consistent with the financial incentives introduced by Cigna. It is beyond the scope of this current analysis to examine changes in the quality of care after CAC implementation; however, the physician practice received a payout from the initiative, implying that the quality criteria in the contract were met and quality did not deteriorate as a result of the initiative.

Program Features

The CAC arrangement with the Medical Clinic of North Texas, P.A. (MCNT), was similar to the CAC initiatives that were described in a previous study.28 To summarize, Cigna paid MCNT a care coordination fee in addition to standard FFS payments. In the first year of implementation, the amount of the fee was based on an estimate of the projected benefits to Cigna’s patients, and in subsequent years, the payments were supplemented based on a formula that employed cost and quality measurements from the prior year. Cigna also supplied MCNT with reports on their patients to monitor progress and to identify those most likely to benefit from special assistance.

In return, MCNT took steps to provide Cigna patients with a level of care consistent with a patient-centered medical home. MCNT hired a nurse who served as an embedded care coordinator for Cigna patients, with primary activities that included the following: hospital discharge coordination for patients at increased risk of readmission, outreach to patients identified through Cigna’s predictive modeling programs as likely to incur high medical costs, and patient education and coaching regarding gaps in care, such as lack of preventive care or medication adherence. The arrangement also included active use of Cigna’s preferred provider list for referrals. A referral template in MCNT’s electronic health record (EHR) identified preferred specialists based on their in-network and value-based designations. MCNT providers and staff were also educated on the importance of in-network usage and how to use the template in the EHR.

METHODS

Study Population


MCNT had 141 primary care physicians (PCPs) in 42 practices, treating 7109 patients covered by Cigna in the Dallas–Fort Worth area in 2010. We compared the expenditures for these patients to Cigna patients who were aligned with other PCPs in the same geographic region between 2009 and 2011. This control group contained 192,655 patients in 2010. Study and control group patients were included only if they were aligned to PCPs and had 12 months of eligibility in any of the 3 years; there were no age restrictions. The methodology for aligning customers to PCPs has been described in a previous study.28 All payments to both groups were FFS. The data sources were the Cigna claim line and enrollment databases, contracts between Cigna and MCNT, and Cigna fee-payment reports.

Study Design

The study design closely follows that used by previous researchers to analyze the effects of the Massachusetts BCBS Alternative Quality Contract.26,27 We compared changes in total spending pre-intervention versus post intervention for the CAC intervention patients versus the control group of patients in other Texas clinics. In this difference-in-differences analysis, the pre-intervention period is 2009 and the postintervention period is 2010 to 2011.

We decomposed the overall 2-year effect on spending into year 1 and year 2 effects. We also decomposed the spending effect by clinical category, as defined by the Berenson-Eggers Type of Service (BETOS) classification system,37 and by site and type of care. We describe our methodology for assigning claims to BETOS categories in eAppendix 1 [eAppendices available at www.ajmc.com]. We then decomposed the spending effect result into a price effect and a utilization effect by repricing claims for each service to their median prices across all providers in 2011. Spending results generated using standardized claims reflect only differences in utilization.

Variables

The dependent variable was aggregate medical spending per enrollee (in 2011 dollars) per 6-month period. Total medical costs included allowable charges typically covered under medical plan benefits (eg, inpatient facility, outpatient facility, professional, ancillary expenses); pharmacy expenses were not included. The care coordination fees that were in the claims were included in the charges for professional services. Medical spending included enrollees’ cost sharing. Aggregate medical spending was truncated at $100,000 for each patient in a given time period.

We controlled for age categories, interactions between age and sex, the patient’s retrospective risk score, and secular trends. We also categorized patients based on the cost-sharing characteristics of their insurance plan benefits. The cost-sharing category of each plan was based on the mean percent paid out of pocket for all individuals in the sample covered by the same set of benefits. Sets of benefits with fewer than 100 customers were assigned to the “undefined” category due to insufficient sample size.

Retrospective risk scores were calculated from the medical claims using commercially available software (Symmetry Episode Risk Groups, release 7.5 [Optum, Eden Prairie, Minnesota]). Claims for the current year were aggregated for each individual, creating a yes/no decision on 167 medical condition categories (eg, acute bronchitis, malignant neoplasm of the breast), called Episode Risk Groups (ERGs). Each ERG has a relative risk value, and the sum of these values is the risk score. The relative risks were derived from claims costs and utilization in a managed care population with more than 8 million members.

Statistical Analysis

We analyzed spending (in 2011 dollars) at the semi-annual–enrollee level using a multivariate linear model with propensity weights calculated using age, sex, risk, and cost sharing (eAppendix 2). Additional independent variables included indicators for intervention status (MCNT vs non-MCNT), 6-month period, the postintervention period, and the interaction between the postintervention period and the intervention. This final indicator produced our initial estimate of the policy effect.

However, not all of the care coordination fees were embedded in the claims. Cigna was in the early stages of developing the CAC program, which led to delays in some payments. Therefore, we adjusted the regression estimate of the overall 2-year effect of the program for the additional care coordination fees that Cigna paid to MCNT that were not part of the claims data. We lacked sufficient information to conduct a similar adjustment of the regression estimates of the program effects by BETOS categories or site and type of care.

Standard errors were robust, based on clustering at the practice level.38,39 We tested the sensitivity of our results to restricting the analysis to patients who were continuously covered by Cigna for all 3 years of the study. We also tested omitting the adjustment for cost sharing and omitting the propensity weights.

RESULTS

 
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