Question

Discuss the role data analysis plays in financial management of a health care organization.

Answer 1

Managing the finances of any health care business nowadays is like driving a car with foggy windows. The industry has been changing in big ways since long before the Affordable Care Act took effect. Medicare's coding system for billing and the advent of electronic medical records are examples of these changes. Financial management in health care requires exceptional skill.

What Financial Management Means

In any industry, financial management involves handling routine financial operations, such as negotiating contracts, making cash available for expenses such as payroll, and maintaining a cash cushion for unexpected costs. At the company's executive level, financial management means providing the other members of the leadership team with information to make strategic plans to prepare for the future. F

or example, health care providers, such as large physician practices and hospitals, may decide to offer expanded tests or treatments by buying new medical equipment. Helping to make the decision and finding the best way to pay for it are both part of financial management.

Meeting Different Financial Goals

Business strategies and financial management are intertwined. Hospitals have been buying up neighboring physician practices. Doctors who sell their practices become employees of the hospital, and the hospital becomes a regional hospital system. That way, the hospital builds a larger and steadier payment stream: It gets money from the entire spectrum of medical care, from tests to surgery to rehabilitative services.

Acquiring a practice brings in new revenues right away, so the revenue stream helps pay for the purchase, and the regional hospital system, which is much larger than the hospital alone, has more bargaining power with health-insurance companies.

Managing Treatment Costs

To a health insurer, cost-effective medicine is crucial. Insurers create lists of drugs they're willing to pay for and treatment guidelines for their contracting physicians. Insurers then use software to track individual doctors' "utilization" – their choices of tests and treatments – to make sure they follow the guidelines. Cost effectiveness is so important to an insurer's bottom line that developing guidelines rises to the level of financial management. The task requires significant medical know-how.

The insurer wants treatments to work to avoid higher costs down the road. Doctors need to be sure that the treatments are medically sound. Otherwise, they put themselves at risk for malpractice lawsuits.

Preventing Expensive Medical Conditions

A health maintenance organization, which may have the same patients for many years, shares the goals of a public health agency: preventing expensive illnesses by keeping patients healthy. For example, HMOs want to find the best and most cost-effective screening tests for heart disease and cancer. For that, medical research is indispensable.

Indeed, the nation's biggest managed-care organization, Kaiser Permanente, funds some of the nation's most influential medical research. Any health care entity that has an affiliated research group – and many do – adds its funding to the tasks of financial management.

Changes Bring Fresh Challenges

Financial management is an art and a science in any industry, but health care is particularly challenging because the industry changes so fast. With the Affordable Care Act, for instance, insurers have had to recalculate their plans and their premium structures. More changes are inevitable. Providers and insurers will need exceptionally skilled financial management for a good while to come.

HEALTHCARE TRANSFORMATION AND THE IMPORTANCE OF ANALYTICS

The focus on performance improvement in the healthcare industry has grown from a handful of demonstration projects to a nationwide movement. Significant drivers of this trend include:

• Costs. According to the Centers for Medicare and Medicaid Services (CMS), U.S. healthcare costs account for an estimated 17 percent of the gross domestic product (GDP)—and CMS predicts healthcare will increase to 20 percent of the GDP by 2020.
• Quality. Payers are moving from a fee-for-service to a value-based care model.
• The aging population and longevity. An aging population, combined with the prevalence of chronic diseases, contributes to higher healthcare costs.
• Demand for healthcare value and transparency. Consumers will continue to demand higher quality as they pay for a larger portion of their healthcare costs—and as quality, cost and satisfaction metrics become more transparent through digital and social media.
• Population health management. Providers are seeking to proactively manage entire populations of patients rather than simply treating those who present at the hospital or office with symptoms.

Every healthcare organization, without exception, is grappling with the challenges presented by the need to transform healthcare. At the core of healthcare transformation is data-driven quality improvement; therefore, a key tool these organizations are turning to is healthcare analytics. In fact, healthcare analytics is a prerequisite for all major performance improvement initiatives underway to address value-based care in an automated, cost-effective and efficient manner. As a rule, healthcare organizations are aware of the vital importance of healthcare analytics in their efforts to improve performance. Health Catalyst recently surveyed members of the College of Healthcare Information Management Executives (CHIME). Survey respondents—CIOs or other senior IT executives of U.S. healthcare organizations—provided a high-level view of the many competing priorities for IT investment that hospital leaders face in the era of value-based care. Here are some facts the survey revealed: Consumers will continue to demand higher quality as they pay for a larger portion of their healthcare costs—and as quality, cost and satisfaction metrics become more transparent through digital and social media. Healthcare analytics is the highest IT priority of the survey group.

4 Ways Healthcare Data Analysts Can Provide Their Full Value

Every healthcare leader wants to optimize their data analysts’ value and effectiveness. One of the main reasons data analysts aren’t as effective as they could be is not having access to the right tools. As a healthcare data analyst for ten years prior to joining Health Catalyst, I have firsthand experience with this issue. I spent 90 to 95 percent of my time managing data, when I should have been analyzing it.

Managing data was not what I had signed up for. I didn’t want to spend most of my time gathering data, validating data acquisition methods, reformatting, ensuring appropriate data types, trimming, cleaning, scrubbing, and conforming data in preparation for analysis and reporting. I wanted to put my analytical skills to use. I wanted to help these healthcare organizations solve problems and make improvements.

The root of the problem was not having the right tools to analyze data and discover insights that would drive care and process improvement initiatives. I was spending too much time collecting data and not enough time transforming it into meaningful analytics. In this blog, I describe four strategies that will empower your data analysts to transform data into meaningful improvements.