Business intelligence (BI) refers to the technology associated with the integration and analysis of collected information. In a health care system or hospital setting, having access to large amounts of information -- whether clinical or financial -- can lead to better evidence-based decision making.
Traditionally, information in health systems has been compiled in static, text-based memoranda. BI helps shape that information into visual data that provides a basis for evidence-based decision making in many different departments.
In recent years, health care's adoption of BI systems is on the rise. This is due to continued implementation of electronic health record (EHR) systems, the storing of clinical data in more discrete formats and a variety of federal mandates. The U.S. Department of Health & Human Services requires organizations to submit specific clinical quality reports as part of the meaningful use incentives program, as well as additional quality measures through the Physician Quality Reporting System (PQRS) and The Joint Commission.
The motivation for data mining and analysis does not stop there, though. As health care shifts toward the accountable care organization (ACO) model and other pay-for-performance initiatives, many organizations will be required to provide proof of improved patient outcomes. This would be directly tied to their reimbursements.
In a typical hospital, there are several areas where BI tools can be used to drive evidence-based decision making. Productivity, efficiency, financial performance and customer service are covered below. The use of business intelligence for clinical analysis is covered in a separate tip, as is an examination of common health care data analysis methods.
Performance analysis is related to the review of effectiveness and productivity of staff in the hospital. This can measure how specific departments perform while drilling down to the actual employee level for further productivity analysis.
In this type of review, for example, performance can be based on how well a lab performs compared to other labs in the same health system. Another example would be reviewing the revenue and reimbursement generated per physician.
In a typical hospital, there are several areas where BI tools can be used to drive evidence-based decision making.
Financial performance analysis is, of course, commonly used in many markets besides health care. Hospitals would typically use BI tools to review trends and receive a snapshot of financial performance in terms of profits, reimbursements, write-offs, AR by aging days, collections, margins, and revenues. Patient length of stay and payer reimbursements may be analyzed as part of financial performance as well. On many occasions, hospitals use the results of this financial analysis to renegotiate the contracts of payers.
The key to success for many organizations is their ability to constantly assess themselves and their ability to improve different aspects of their business. A hospital can benefit from process efficiency measurements of internal processes and workflows. This can have a big impact on patient care and satisfaction. In some cases, for example, simply measuring and improving patient wait times can help identify the different delays in the workflows, and vice versa.
Hospitals are also businesses. This means they compete for patients. For many organizations, measuring patient satisfaction is important. BI tools can help identify customer service measures such as a patient's average hold time on the phone and hospital satisfaction ratings per department, subspecialty and even individual hospital ward. While there are several other standardized methods being used in the market, such as the Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys that hospitals use to gather patient input, a hospital can still perform self-assessments to identify areas for improvement.
Reda Chouffani is the co-founder and vice president of development at Biz Technology Solutions Inc. Let us know what you think about the story; email firstname.lastname@example.org.
This was first published in October 2011