How an ACO Provides and Arranges for the Best Patient Care Using Clinical and Operational Analytics
“It is not just the delivery of care, but how to arrange for care delivery that we have to consider if we want to succeed as an ACO. We are doing a lot of ‘what if’ analysis now that we could not do before: Which patients go to a certain office? Are they sicker in one area as opposed to another? Answers to these questions help us arrange care to meet our population’s needs. We are becoming a medical logistics organization, and advanced analytics makes it possible.”
– Greg Spencer, MD Chief Medical Information Officer
Healthcare is transitioning from a transaction-based, fee-for-service payment model to a value-based model designed to deliver higher-quality, less wasteful care at the lowest possible cost. This new model emphasizes population health management and requires providers to take on risk and collaborate to an unprecedented extent.
The need for this level of collaboration has led to explosive growth in the number of accountable care organizations (ACOs). In 2013, there were a total of 606 public and private ACOs in the United States1 with 51% led by physicians and another 33% jointly led by physicians and hospitals.2
One pioneering, physician-led ACO is Crystal Run Healthcare in New York. This rapidly growing and forward-thinking organization has received national recognition as one of the first six ACOs to be accredited by the National Committee for Quality Assurance (NCQA), and one of the first 27 ACOs to be selected by CMS to participate in the Medicare Shared Savings Program.
FOCUSING ON GROWTH IN PREPARATION FOR VALUE-BASED CARE AND POPULATION HEALTH MANAGEMENT
Like the majority of ACOs, Crystal Run still receives most of its reimbursement—approximately 80%—under the fee-for-service model, but the organization is beginning to experience the long anticipated shift toward more value-based reimbursement. To ensure financial stability as they assume more risk, the ACO is implementing a strategy focused on rapid growth. Crystal Run already has more than 300 providers in 40 medical specialties with multiple practice locations. The ACO plans to grow to more than 1000 physicians, significantly expanding its geographic reach.
Crystal Run views its enterprise data warehouse (EDW crystal run) and applications as critical to the success of this strategy. This technology foundation enables sophisticated analysis necessary to position Crystal Run for continued success in an increasingly value-based reimbursement environment. In addition to population management, the ACO is leveraging the EDW and analytics to inform critical decisions about clinical excellence, operational optimization and growth targets and to identify new revenue sources such as government grants for treatment of Medicaid patients.
ACO CHALLENGES: MANAGING RISK AND PATIENT POPULATIONS
As Crystal Run leaders searched for technology to support their growth and population health management strategies, they knew they would need an analytics solution that would enable them to continuously improve in the following areas:
- Reducing clinical variation, enhancing operational efficiency and positioning the organization to better manage risk
- Supporting informed decisions by giving clinical and operational decision-makers efficient and effective access to all necessary information
- Using data from a “single source of truth” integrated from multiple disparate source systems (EMR, billing, costing, patient satisfaction and other operational systems) to answer increasingly complex clinical and operational questions
- Avoiding prolonged decision-making processes by making self-service analytics available to decision-makers. In the past, much of the ACO’s analytics required the business intelligence (BI) team to write customized reports. The report turnaround times depended on the complexity of the request and the number of other reports within the BI report queue. Once the clinicians reviewed the report, they often had additional questions, which required another BI request and further delays in receiving the information.
In addition to these general requirements, Crystal Run needed an analytics solution that could help address the day-to-day operational and clinical challenges that ACOs face. These challenges include:
Growth and practice expansion
Crystal Run’s growth has required and will continue to require the construction of new office buildings to support a growing patient base in expanded geographical locations. They were tasked with determining the best locations for these clinics and what provider mix was necessary to best serve patients. To tackle this question, they needed to understand where to locate the new sites and what types of providers they should staff to meet patients’ needs. The cost of large offices is not insignificant—often running into the tens of millions of dollars.
Like many healthcare providers, Crystal Run is anticipating increased participation in risk-based contracts involving bundled payments, shared savings and capitation. They need to understand what it costs to take care of a given patient population. Without this data, Crystal Run has little leverage, which means that payers will dictate the terms based on a risk score that is based on the average for the region. However, not all patient populations align with the regional average—and, in the case of Crystal Run, the bulk of the specialists in the community are in their network. Therefore, by selection bias, their patient populations are often inherently sicker and more complex than the general population. By having the data at the negotiating table, contract terms can be decided.
To ensure accurate reimbursement and assess physician productivity, Crystal Run needed to benchmark physicians’ performance based on their case mix and the risk profile of their patients. The ACO was particularly concerned about accounting for advanced procedures performed by sub-specialists that warrant a higher reimbursement rate.
Population Health Management
As an ACO, Crystal Run’s mission involves improving population health and the patient experience while lowering costs. This requires physician engagement, a concerted focus on evidence-based practices and rigorous budget management.
THE SOLUTION: AN EDW FOR OPERATIONAL ANALYTICS AND CLINICAL DECISION-MAKING
Crystal Run decided that a healthcare-specific EDW was the best solution to help them meet these many challenges. The organization deployed the Late-BindingTM healthcare EDW platform from Health Catalyst, which they were able to get up and running in just 77 days. On top of this platform, they implemented foundational analytics applications to help them address the basic discovery measurements needed to effectively care for patients and manage access to patient care.
Here are some of the ways these foundational applications— including Key Process Analysis, Cohort Builder, Comorbidity Analyzer and Population Explorer—are helping the ACO address operational and clinical challenges:
Data-driven growth and practice expansion
The Population Explorer application (illustrated in Figures 1 and 2) visualizes the number of patients in each zip code area. It enables the ACO to view clinical data by county and by zip codes within each county (a given county can have as many as 100 zip codes). Importantly, the application also displays measurements for that population such as case counts, readmission rates, charges, revenue and length of stay. These metrics can be stratified by demographics and by clinical and financial information.
Using this application, Crystal Run was able to determine how many patients live near the proposed location for their new facility, understand what type of visits those patients were generating and in what specialty, and understand the potential volume of visits based on that information. They also explored risk and demographic information of patients living in the area.
Furthermore, when hiring new physicians, the ACO is now able to evaluate the patient volume for a given specialty in a county or zip code to help determine where the newly-hired specialists should practice or whether they should split their work week at different offices…