Promote ACO Success Under Value-Based Payment with These 5 Data Sources

ACOs have used “old school” data sources for many years to focus coordination of care activities. Perhaps your ACO has done the same, using reports such as admissions and ER discharges, post-acute admissions, visit history and missing labs to target patients for outreach. Similarly, your ACO might use HCCs to identify patients with higher risk factors for population health.

Basic, easily found data like these sources provided a means for ACOs to launch valuable efforts in population health, when comprehensive claims and EHR data were not easily available. But as the pendulum swings toward financial Risk, your ACO needs to shift from Fee-for-Service to value-based payment models, upping the ante on data to protect your bottom line.

Three Ways that Better Data Opens ACO Opportunities to Thrive Under Risk

Your ACO will need deeper analytics and data-driven interventions to ensure financial sustainability and growth. You can’t intelligently manage Risk without being able to predict and control total patient care costs. Collecting data from easy sources like admissions, ER, and HCCs is certainly not enough and is not predictive of future costs. More importantly, this piecemeal approach does not provide the detail you need to address costs or outcomes. Retrospective data has only partial clinical relevance to the status of those patients in the future.

For your ACO to operate with confidence under value-based payment models, think about how you can use data to achieve these three objectives that heavily impact your aggregate patient care costs:

• Systematically identify patients with chronic conditions who are in decline or not improving. These are the patients who will impact your future bottom line as their health further erodes. Better data creates the opportunity for you to target clinical and social services interventions based on key indicators, and potentially improve the course of their lives and cost trajectory.
• Identify cost drivers in specialty care, with data packaged in procedural or condition-based patient episodes of care. By examining each patient within the group against others, linked with specialty providers, you will identify variations as well as notable observations and outcomes. Share these results with specialty providers to evaluate and improve, engaging them in your ACO goals.
• Provide meaningful and relevant cost data to your clinicians to involve them in improvements. These should include more than general analytics and encompass the provision of point-of-care tools for questioning and considering specific interventions for patients at the time of the visit.

Five Data Sources and Their Value for Value-Based Payment Models

Now let’s examine the sources of data that you should be tapping. First, understand that if you are to achieve any of the goals listed above, you will need to integrate the data from these sources into a patient-centric database. Why? Because at the heart of each goal is a set of actions to examine or act upon for each patient. Whether population health, clinical change in treatment, or examination of variations in care for patients with the same condition—each intervention or improvement is based on findings from patient-level data. Therefore, you must layer the data from each of the five sources into patient histories, outcomes, and costs.

1. EHR Data

Your ACO has probably considered Claims data from CMS as the nucleus of your ACO data empire. Nope. While Claims data is valuable for revealing most patient care costs and utilization, you need EHR data to provide the foundation of clinical information necessary for analyzing costs and outcomes, and certainly for targeting interventions.

Unless you are a single group ACO supported by a common EHR, the concept of aggregating data from multiple EHRs may be new. With APP reporting on the horizon in 2025, many groups are just starting to understand the dimensions of EHR data-driven opportunities.

These are just a few of the essential data types that the EHR offers for meeting the three ways to thrive under Risk, none of which are available through Claims alone:

• Lab and other test values for conditions, enabling you to stage patient risks;
• Prescribed drugs and history of prescriptions;
• All diagnoses, not just those billed during the year;
• Trend of critical lab values such as A1C, blood pressure;
• Other patient history that can explain poor outcomes or events.

2. Claims Data

Claims data contributes to your patient information in three important ways. First, it adds data about your patients, including conditions or procedures and some clinical status indicators of which you may have been unaware. This information should be blended into your patient’s data history.

Second, it provides information on other providers giving services to your patients. Knowing providers outside your network should enable you to better evaluate your referral sources and help cultivate your specialty referral strategy. Your specialty relationships could include data sharing or involvement of the specialty group in your ACO initiatives.

Finally, it reveals essential cost of care and utilization information that can be analyzed by patient episodes to identify variations and cost drivers.

3. Patient-reported Outcomes and Devices

Many patients are now collecting information through wearable devices, and this data is rarely flowing into EHRs. Whether captured through portals or devices, patient-origin data both supports the patient’s efforts to document and improve their health status and also incorporates vital feedback into the clinical data. Why depend on survey data or limit your patient contributions to feedback on services, when you could benefit from rich lifestyle data or incorporate clinical values into your repository? Patient-reported data can also provide valuable information on the patient’s level of engagement in treatment, or how effective the treatment is.

Despite the value, however, there’s a hitch. Clinicians and organizations are often opposed to such data being directly ingested by the EHR. If that is the case, ACOs should consider instead how to incorporate this data into the ACO patient-centric repository.

4. Social Determinants of Health (SDOH)

Many ACOs are enthusiastic about improving health equity yet distressed about the staffing and process required to collect SDOH data, and still struggling as a result. In the long term, the use of standardized tools and Z codes may improve the incorporation of SDOH data in EHRs, but input from provider offices will be required for the ACO to reap the rewards of good SDOH data. The ACO has a legitimate leadership role in this area because the value-based agreements negotiated by the ACO incorporate health equity requirements. As such, the ACO may consider working with community organizations or creating better strategies for collection of SDOH data going forward.

In the meantime, ACOs can use the other sources of data they are aggregating to target patients for examination of SDOH issues. For example, condition episodes such as diabetes should identify patients with stagnant, poor outcomes and no change in medication. This and other indicators signify that investigation is necessary to determine affordability or other issues contributing to the patient’s situation. Targeting patients for identifying SDOH issues will lessen the burden of collecting data on everyone, while providing a path forward for the ACO to address the most critical and obvious cases.

5. Specialty Provider Data

As discussed previously, significant sources of specialty care make an important contribution to ACO patients, and all efforts to formalize the relationship between the specialty providers and the ACO mission is key. One aspect of this relationship must center on data sharing.

There are several options for this if the specialty practice is not ACO-participating, all of which require good faith negotiations for the benefit of each party. First, the specialty practice can provide EHR data to the ACO, which can be ACO-limited (only with technical capability). Second, the ACO could also arrange for its data vendor to aggregate and separately categorize ACO patients and provide analytics to the ACO and practice alike. This would provide the full benefit of episode-based cost analysis to the specialty practice while also providing detail on ACO patients to the ACO. Finally, the specialty practice could independently aggregate and furnish the data to the ACO.

Building ACO data prowess will take some time, and funding but will be required to sustain the revenues of the ACO as Risk proceeds. The cost of aggregation is lowest and the data value highest using a holistic data gathering approach, rather than measure-specific or single purpose. With Claims for Medicare patients already available, additional data sources can be added and enhanced over time.

ACO reluctance to adopt data aggregation has occurred for various reasons—cost, history, lack of value in data, provider pushback. Now is the time to get smart about data. Equity-backed providers have already invested in the technology needed to really address costs. To manage Risk and compete for providers and patients, ACOs emerging from legacy provider groups must do the same.

This article originally appeared on the Roji Health Intelligence blog, 3-30-23.