Business intelligence (BI)—the process of turning data into actionable information—is a critical capability in the healthcare industry. Business intelligence enables healthcare entities to measure, analyze, and improve across multiple areas of organizational performance.
Most healthcare entities have a business intelligence strategy, but many struggle to get the greatest value from their clinical, operational, and financial data. They may have robust data and the tools for analytic enhancement, but without an interface that facilitates data sharing across departments and job roles and an enterprise-wide commitment to integrating data with business process, they are in effect leaving money on the table. Today’s most competitive healthcare organizations are data-driven.
This paper provides insight into innovative business intelligence in healthcare and steps that an organization can take to get a better return on investment (ROI) from its data.
As reported in Modern Healthcare, the Centers for Medicare and Medicaid Services (CMS) has provided nearly $4.5 billion in electronic health records (EHR) incentive payments. About $2.4 billion of that is under Medicare, which started EHR incentives in May 2011. The rest is under Medicaid, which began EHR incentives in January 2011. Hospitals have received the bulk of the total in both programs, about $3.1 billion. The program has more than 225,000 active accounts. The EHR incentive program is part of the American Recovery and Reinvestment Act of 2009, which authorized $19 billion for the EHR incentive program.
For a couple of Milliman perspectives on the EHR program, check out this paper on state healthcare data exchanges which points out how:
Community-based data pooling initiatives in Minnesota, Massachusetts, Oregon, Washington, and Wisconsin (commonly known as Chartered Value Exchanges or CVEs) have already shown that, at least using administrative data, it is possible to bring stakeholders to the table, get appropriate infrastructure in place, and begin using community health data to improve quality and transparency. These organizations may serve as models or building blocks for more meaningful use of EHR data nationally.
It’s also worth taking a look at this 2009 research report, “The Convergence of Quality and Efficiency and the Role of Information Technology in Healthcare Reform,” which discusses how EHR can move beyond administrative efficiency to become a decision support tool for physicians.
You can download the latest EHR program data from CMS here.
Managed Healthcare Executive looks at the move toward standardized electronic funds transfers. Here is an excerpt:
Savings of $4.5 billion over 10 years is the projection by the federal government relative to a new rule to standardize electronic funds transfers. HIPAA-covered entities have until January 1, 2014, to comply.
Payers will need to develop infrastructure and processes to support electronic remittances, but much of the work to implement this rule will fall on providers, says Andrew L. Naugle, a principal at consulting firm Milliman. The biggest piece of the puzzle is what the provider does with the electronic remittance advice.
“Although most health insurance companies already have the capability to send an electronic remittance advice, the typical healthcare provider is not set up to accept this electronic transaction or automatically post the payment to the corresponding receivable,” says Naugle.
The immediate focus of most HIPAA organizations and their vendors is on the conversion and mitigation of potential risks related to ICD-10 implementation. Many of those risks relate to the data fog that will ensue for at least 18 months following the October 1, 2013, implementation.
Some organizations have thought about what will happen after the data fog clears—the long-term advantages that ICD-10 will likely offer include better identification of fraud or abusive practices, improved ability to manage care and disease processes, and tracking public health and risks.
However, few have thought about the immediate opportunities that ICD-10 offers starting on the first day of implementation. Organizations do not have to wait two or more years for historical ICD-10 data to improve condition management, enhance population management, or engage in outcomes analysis. With a little foresight, organizations may even be able to use ICD-10 to improve coding. Find out more in this new white paper.
An announcement by US Oncology points to a new study that explores a road map toward improved efficiency in cancer care. Healthcare IT News has the story; here’s an excerpt:
The study suggests that leveraging healthcare IT, shared best practices, refined evidence-based medicine guidelines and quality measurements, contribute to the quality, safety and science of cancer care to improve patient outcomes.
Titled “Benchmarks for value in cancer care: an analysis of a large commercial population,” the report found that the key areas driving the spike in costs are chemotherapy, hospital admissions, emergency room visits and aggressive end-of-life care.
Cancer patients in a commercially insured population receiving chemotherapy averaged $111,000 per year in total medical and pharmacy costs – about four times the cost of cancer patients not receiving chemotherapy and nearly 26 times the cost of non-oncology patients. More than half of the cancer patients in the study received chemotherapy within the last 30 days of life.
The study was published in the “State of Oncology” supplement of the peer-reviewed Journal of Oncology Practice…The US Oncology Network partnered with Milliman, Inc. to evaluate the prevalence and costs associated with cancer treatment in a commercially insured population. They used Medstat 2007, a large commercial insurance database that contains private sector health data and claims information for about 14 million insured lives from approximately 100 payers.
Fourteen cancer diagnoses were included and evaluated in ten cancer groups including lung, breast, colon, rectal, pancreatic, ovarian, multiple myeloma, lymphoma, chronic lymphocytic leukemia and prostate. Study endpoints included analyzing the cost of treatment over one year and costs incurred at the end of life.
This news warrants a tombstone here, because this blog began with a focus on electronic health records (EHRs). Goodbye, Google Health. We hardly knew ye.