Why Adding External Data to Your EDW Is Critical to Driving Outcomes Improvement
Across the healthcare industry, organizations are seeking ways to improve the quality and lower the cost of care. To assist in this endeavor, many of these organizations are using myriad of data and analytics and investing in enterprise data warehouses (EDWs). Aggregating internal data into the EDW from disparate clinical, administrative, and financial systems is the first critical step to identifying quality improvement and cost savings opportunities.
Internal data alone is not sufficient, however. Identifying and addressing a savings or care improvement opportunity requires senior leaders have access to data from external sources as well. Identifying and addressing a savings or care improvement will increasingly require senior healthcare leaders to turn to important sources of external data to achieve significant savings or identify care improvement opportunities. A few examples of the types of external data sources that will be needed for population health and accountable care level opportunities:
At-Risk Contract Performance Required CMS and Claims Data
Many healthcare organizations are entering, or are planning to enter, into some type of at-risk contract such as—a bundled payment program, a Medicare Advantage plan, or an ACO. Successfully integrating external and internal claims data enables leaders to oversee these contracts more effectively. Data from CMS and commercial payers represent the most common kind of external data currently incorporated by health systems into their EDW.
- CMS provides a robust and comprehensive data set for a range of claims types. Integrating this data into the EDW gives leaders a comprehensive view of the organization. Comparative Medicare claims and organizational performance analysis for the organization’s patients versus those patients under the care of another healthcare system are crucial. The information allows decision makers to enter into future at-risk contracts with a clear understanding of the improvements required to achieve success.
- Incorporating claims data from commercial payers for specific populations covered by at-risk contracts can answer some important questions.
- Is the organization paying for services provided out of network?
- What other choices does the patient have when seeking treatment?
- Is there a significant difference in spend for in-network and out-of-network care?
- How can the organization minimize leakage in order to achieve cost savings?
Integrating claims data is not without its challenges. Claim data sets typically lag the delivery of care by at least 60 days. Some claim data sets are de-identified, limiting the insights gleaned from them.
Maximizing the usefulness of claims data often requires matching the patient on each claim with a patient in the EHR using a master patient index. In some cases, there may not be a suitable matching technology already deployed. The incremental investment required to integrate claims data into the EDW is necessary, even vital, to attain success in risk-based contracts.
Performance Benchmarking Versus Other Health Systems
Healthcare organizations are very keen on benchmarking. The majority of hospitals and health systems subscribe to some type of benchmarking service. These services deliver fixed sets of reports to subscribers which, when incorporated in the EDW, can allow organizations to conduct their own performance benchmarking.
The main challenges with loading benchmarking data are anonymization and the aggregate nature of benchmarking data. Anonymization means benchmarking services often do not send data for a particular, named hospital. The data provided is for “a community hospital with between 200-300 beds.”
Benchmarking data is usually not as fine-tuned as clinical or claims data. As opposed to receiving information containing the individual pneumonia readmissions rates for 17 specific hospitals, the reports provide the average pneumonia readmissions rate for a group of 17 anonymous hospitals.
Given these challenges, along with its limited utility, integrating benchmarking data should be a lower priority for most organizations.
Demographic Data Addresses the Impact of Changing Patient Populations
Analyzing demographic data has always been a part of healthcare as hospitals strive to meet the needs of patients in the communities they serve. The emergence of shared accountability agreements established financial incentives for institutions to deliver high-quality, patient-centered care at lower costs.
EDW and analytics technologies allow healthcare organizations to request more-specific data sets, creating the opportunity for a more thorough analysis of their local patient population. Applying the strategies of Population Health Management, institutions can proactively identify and assist high-risk patients; improving the health of not only these particular patients, but of the patient population as a whole. Hospitals and healthcare systems are beginning to incorporate consumer and household data in to their analysis.
The U.S. Census is an excellent, and freely available, source for this type of information. It is essentially accurate, updated frequently, and the data correlates well with health information.
Companies like Experian and TransUnion offer a much richer—and much more expensive—data set. Leaders should keep in mind, however, that the value of this type of data may not be as high as the cost to acquire and analyze it.
Another valuable, and inexpensive, alternative is Area Health Resource Files published by CMS. This collated data set brings together a wide range of health-related information by county.
An organization needs a high level of analytical expertise in consumer and household data to understand, communicate, and take action on the information provided by these data sources. To solve specific problems, many organizations employ consultants to assist them in this process. A select few, large institutions, with significant analytics capabilities and dedicated strategic planning resources, will find it worthwhile to do take this type of analysis on themselves.
For example, an academic medical system might use the Area Health Resource files to assess the skill set of the current healthcare workforce and forecast projected population growth, when considering the expansion of educational programs or capital investments.
The EDW: As-Is Versus What-If
New models of care delivery are driving hospitals and medical practices to build EDW solutions to answer complex, mission-critical questions. Armed with data from a trusted, single source of truth, leaders, physicians, nurses, and frontline employees are empowered. Together, they can critically evaluate and aggressively pursue the best opportunities for improving outcomes. Harnessing the power from aggregating internal and external data enables the entire organization to create a culture of continuous improvement.
A Big Future for External Data
Healthcare systems continue to develop competencies for capturing, disseminating, and taking action on data from external sources. The process to determine how to make such data meaningful is in its infancy, but its potential to tangibly improve the quality of care, increase patient satisfaction, while lowering costs is great.
Aggregating data in to an EDW from internal, disparate, clinical, administrative, and financial systems is the first critical step to identify opportunities for quality improvement and cost savings. As the transition to value-based care continues to gain momentum, success will be determined by how effectively external data is integrated in to the EDW. Aggregating external and internal data enables leaders to successfully oversee and manage current contracts. It empowers the entire team to confidentially plan to deliver value-based care in the future.
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