Randy L. Thomas

Health care is at a crossroads. The cost to provide health care continues to grow with little correlation to improved quality outcomes.

As healthcare costs escalate, access to quality healthcare services - particularly for preventive care-becomes increasingly problematic for a growing portion of the population.

The ability to define, let alone measure, "value" in health care is difficult, if not impossible, in the current environment. These challenges are well recognized by governments, employers, care delivery organizations, consumers, payers, and suppliers. Clearly, changes are needed.

There is tremendous potential in what 21st century health care can offer individuals. The efforts of competent and dedicated healthcare professionals, combined with the promise of genomics, regenerative medicine, and information-based medicine, open many possibilities for the management, if not outright prevention or cure, of many diseases.   

Health care needs to derive value and intelligence from rapidly growing data sources in order to discover new treatments, improve care delivery, and affect health policy. Many experts agree that the application of healthcare IT is a critical part of reengineering and transforming health care for the better (Edington, M., Crossing the Quality Chasm: A New Health System for the 21st Century, Washington, D.C.: Institute of Medicine, 2001). Clinical decision intelligence is a means to drive a more information-based approach to health care. It can be used in the course of care delivery by providers, by patients making decisions about their health care, and by clinical and basic researchers in the pursuit of improved prediction, prevention, diagnosis, and treatments.

CDI is broadly defined as the processes, tool sets (underpinned by scientific, clinical, and operational knowledge and incorporated with new emerging technologies), and advanced analytics that significantly improve individual personal health and wellness, provider clinical decision-making, workflow in healthcare delivery systems, and population health management. CDI is:

  • A mechanism to analyze aggregate data to identify new therapies and approaches to care
  • A tool embedded in electronic health records and other advanced clinical systems that provide alerts, reminders, order sets, documentation templates, and other support vehicles to providers in the course of care delivery (often referred to as "clinical decision support")
  • A means to evaluate the efficacy of adopted approaches to care to ensure the expected outcomes are achieved

CDI has the potential to improve healthcare delivery in three different yet related aspects of the healthcare environment-clinical interaction between the patient and provider, discovery of new and improved approaches to care, and measurement of clinical outcomes.

Clinical Interactions

There are two aspects of clinical interactions that may be supported and improved with clinical decision intelligence. First, there is the "personal health" dimension, where a person is proactively managing his or her health and health care. Second, there is the interaction between the patient and the provider where decisions about care are being made and applied.

CDI can assist individual healthcare consumers with personal health and wellness management, and chronic disease management in collaboration with healthcare providers. The evidence base is less developed in this area, but recent trends would suggest that U.S. citizens go online frequently to search for healthcare information about their own medications and medical problems or those of loved ones. The emergence of personal health records may suggest that healthcare consumers will have an increasingly important role in managing their own healthcare information. In fact, CDI can be imbedded in PHRs to alert consumers and/or their healthcare provider about a potential issue-such as an upward weight trend for a patient with congestive heart failure. Research under way at a number of academic medical centers will evaluate how well shared online health records can impact healthcare services and outcomes.

The most well studied application of clinical decision intelligence in healthcare IT is in the area of clinical decision making. A growing body of evidence suggests that knowledge in clinical decision-support systems can positively impact physician behavior at the point of care. As EHRs become more widely adopted, more clinical decision intelligence will be incorporated in the systems to support a broader array of clinical decisions.

Discovery

The data collected as a result of patient care delivery are a valuable asset in the ongoing efforts to improve the body of knowledge of what does and doesn't work (and why) in preventing and treating disease and trauma. CDI is a vital component in the discovery of new and improved approaches to care delivery. Whether in the basic or clinical research areas, the application of analytic and data mining algorithms to aggregate data collected about patients provides important insights. From the selection of study cohorts to the identification of trial participants to the analysis of all the variables affecting outcomes, the application of clinical decision intelligence assists the discovery process. When a new or changed approach to care is ready for mainstream clinical use, this content can then be expressed in the CDI support element of clinical care delivery to guide providers.

Measurement

Once an approach to care is placed in mainstream clinical use, there is the need to continue to measure and monitor the outcomes of patients treated according to a particular "discovery." CDI efficiently monitors the ongoing clinical care and automatically provides alerts and insights about trends and unexpected occurrences in outcomes. This information can then be efficiently evaluated to help fine-tune the approach to care codified in the clinical decision support of the EHR.

Conclusion

The potential to improve quality of life grows with each new clinical discovery. So does the complexity of diagnostic and therapeutic decision making. At the same time, the cost and effort to both discover new approaches to care and deliver health care is rapidly outstripping our ability to afford them. The promise of CDI is the ability to automate and streamline clinical discovery, to close the gap from discovery to application, and to improve the consistency and appropriateness of care delivery. It is impossible for clinicians to remember all treatment options and their applicability to an individual patient. CDI provides appropriate support to clinical decision making while at the same time personalizing the options to the particular patient.


Randy L. Thomas, FHIMSS, is an associate partner, IBM Healthlink Solutions, part of IBM Global Business Services, Marlton, N.J. (thomasra@us.ibm.com).

Publication Date: Friday, June 01, 2007

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