Data Management in HealthCare

Data management and Information Technology play a critical role in healthcare transformation under the Health Care Reform. The government is pushing, and banking upon Health Information Technology (HIT) to be the main driver in improving outcomes and reducing health costs. To enable this transformation, the government has created a series of incentives and penalties under the Meaningful Use guidelines.

Meaningful Use has laid the foundation for increasing the role of HIT in healthcare. The three stages of Meaningful Use increase the "usefulness" of electronic health records by:

  1. Promoting “data capture and sharing” (Stage 1)
  2. "Advancing clinical processes" (Stage 2)
  3. Improving outcomes (stage 3)

The goals of Meaningful Use include:

  1. Improving clinical outcomes
  2. Improving population health outcomes
  3. Increasing transparency and efficiency
  4. Empowering individuals
  5. Creating more robust research datasets on the healthcare system

It is clearly evident from these goals that data management is crucial. Without collecting, storing, analyzing data, these goals cannot be achieved.

The usage of electronic health records in the United States has increased dramatically after the implementation of the Affordable Care Act. This increase in the use of EHR's is generating a large amount of both discrete and non-discrete data. To achieve some of the goals of Meaningful Use, this data has to be managed, and converted into information that can be used to improve healthcare outcomes.

Besides Meaningful Use there are a number of other government and nongovernment organizations such as CMS, Joint Commission and Leapfrog group that are collecting data both at the hospital and provider level. Collecting and reporting data for all these agencies is a huge challenge. A number of IT solutions have been developed to address these issues (E.g. Quantros). All these IT solutions use data warehouses or data marts as their backbone.

Hospital Inpatient Care

Due to declining reimbursements in hospital services, many hospitals in the country are operating on razor thin margins. Health IT can help increase efficiency, reduce redundant services and decrease adverse events. Two examples of how data management and health IT can improve hospital inpatient care include, monitoring and preventing "never events," and reducing costs using tools such as "Time Driven Activity-based Costing (TDABC)."

The NQF defines Never Events as “errors in medical care that are of concern to both the public and health care professionals and providers, clearly identifiable and measurable (and thus feasible to include in a reporting system), and of a nature such that the risk of occurrence is significantly influenced by the policies and procedures of the health care organization. ”

Recently CMS announced that they will not be paying for "never events" that happen during a hospital setting. Therefore, many hospitals are using either their EHR's or other specialized tools to monitor and reduce "never events."

Time driven activity-based costing (TDABC) is a new methodology developed by Harvard Business School to measure costs of providing health care. At its most basic level, this methodology estimates the cost and time of each and every resource that is required to provide one unit of care. A unit of care is generally a complete cycle of providing a medical service.

University of Texas M.D. Anderson Cancer Center used TDABC to measure the cost of providing care in their Head and Neck Cancer Department, redesign and implement new processes. This resulted in 16% reduction in process time, a 12% decrease in costs for technical staff, and a 67% reduction in costs for professional staff .

Population Health

Without adequate data it is virtually impossible to implement a population health management program. Population health management, at this stage is centered on two main ideas:

  1. Identifying and closing gaps in care
  2. Implementing patient or disease-based registries to improve outcomes and for research

Many EHR's today have tools to identify gaps in care for patients suffering from chronic diseases. Examples of such gaps in care include monitoring hemoglobin A1C and other complications for diabetics, monitoring blood pressure and lipid profile for patients with cardiovascular disease, and health maintenance visits including cancer screening. In a paper-based environment, providers have to remember when patients are due for their next tests are screening. The data contained in the EHR's can provide alerts to providers that patients have a gap in the care and nudge them to order the tests and thereby close the gap.

Registries are huge databases, which are either disease or patient based. Examples of population-based registries include the Framingham Heart Study, and the Nurses Health Study. Examples of disease-based registries include the American Heart Association's Stroke Registry and Acute Coronary Treatment and Intervention Outcomes Network Registry. Analysis of data from these registries has been instrumental in improving the care of cardiovascular stroke and other diseases.

In summary, health IT and data management plays a critical role by laying down the platform on which providers, hospitals, accountable care organizations can improve health outcomes, increase efficiency and reduce costs at the same time. Without these tools, we will not be able to provide value for the Healthcare Services delivered to our patients.


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  3. John C. Nordt MDMPC, MD; Jamie A. Gregorian, Esq. As Medicare Costs Rise, Reimbursements Drop. 2012
  4. AHRQ. Never Events. 2012
  5. CMS. Center for Medicaid and State Operations: SMDL #08-004[letter]. 2008
  6. Kaplan R, Anderson S. Time-driven activity-based costing. Available at SSRN 485443. 2003
  7. Kaplan RS, Porter ME. How to solve the cost crisis in health care. Harv Bus Rev. 2011;89:46-52.
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  9. AHA. Facts: Clinical Registries.