Addressing the multi-source, multi-attribute information acquired across the continuum of care is integral for healthcare providers and their patients.
James G. Spahn,
M.D., FACS
The vast amount of data collected throughout the healthcare system could undoubtedly provide facilities with the knowledge and opportunity to target a potential health problem in its early stages with accurate risk assessments and preventive care. Unfortunately, the means by which this data is currently compiled and utilized is falling short in application. If clinicians do not possess thorough assessment tools, they cannot accurately assess a patient's care and/or treatment needs in a timely manner, resulting in a failure to match patient acuity levels with effective care and accurate reimbursement.
In practice, judgment exercised by a clinician in the choice of prevention and/or treatment plans for an individual patient is based, to an extent, on theoretical considerations derived from an understanding of the nature of the illness. But, it is based also on an appreciation of statistical information about diagnosis, treatment and prognosis acquired either through personal experience or through medical education. The important argument is whether such information should be stored in a rather informal way in the clinician's mind, or if it should be collected and reported in a systemic way.
No clinician — no matter how thorough and intelligent he or she may be — has the ability to personally acquire enough factual information when compared to that which can be obtained from technology and statistical models. It is partly by the collection, analysis and reporting of statistical information that a common body of knowledge is built and solidified. The truth is that the amount of on-hand knowledge needed to deliver appropriate preventive and/or treatment care has become so vast that even highly specialized clinicians have trouble keeping current with new information relevant to their professional area of focus.
Addressing the multi-source, multi-attribute information acquired across the continuum of care is integral for healthcare providers and their patients. As they adopt new methods, providers must help integrate and analyze data based on each patient and his or her given situation. Upon analysis, effective care plans that address all the potential risk factors for each patient can then be extrapolated to ensure proper prevention and/or treatment and desired results. Additionally, it is important for caregivers to have access to patient data at the point of care. When face to face with a patient, a clinician must be able to obtain and utilize all available medical information to make critical determinations regarding the direction of patient care.
The organization and trending of data is a relatively new area of activity when it comes to patient analysis, management and overall treatment. During this process, a software solution is generated to assist the caregiver in designing an acceptable outcome for the patient. Ideally, these refined data processes can be implemented into a system that gives healthcare providers the freedom and confidence to authorize treatment for their individual patient needs under the art of medicine. The solution might lie in enhanced risk tools in the form of a data system that allows clinicians the freedom to apply their considerable skills in combination with the power of accurate and current patient data.
These software solutions serve as an enhancement to current technologies, protocols and processes that caregivers are following today. However, effective real-time analysis of data helps produce knowledge bedside, a unique value that trumps existing technologies. Upon the review of properly organized and trended data, caregivers can understand the patient's health in a holistic manner; a capability that is extremely unique, as current techniques merely gather data without offering any knowledge to the provider based on that data.
Though many risk-assessment tools are currently in place, they tend to be inadequate due to the fact that they take a limited number of patient variables into account, rather than focus on the interaction of all of the variables and how they factor in to the outcome of the patient. Also, because they were developed years ago, they do not utilize the most up-to-date technology. These tools have many limitations, including the following:
• Weighing each risk factor equally, when in fact, certain responses are far more predictive of risk;
• Not capturing resident history. For example, the cumulative effects of chronic conditions and diagnoses that contribute to risk; and
• Failure to weigh interactions of smaller risk factors that in turn add up to high risk.
Quick and accurate clinical application of data is a powerful tool and can provide a measurable improvement in the quality of life, the length of life and lower mortality rates. As for the individual patient, organized and trended data can be implemented in a clinical setting for improved patient selection based on a patient's individual medical profile and specifically tailored to the level and breadth of their clinical acuity. Ultimately, this leads to higher-quality care for patients and optimization of resource allocation for healthcare facilities. As healthcare dollars diminish, precise tuning of clinical information systems designed to help manage risk assessment has never been more important. When implemented properly, these solutions provide an instant, highly specific and sensitive risk assessment at the
point of care.
James G. Spahn, M.D., FACS, is the founder of WoundVision, a pioneer in advanced wound-detection technology.
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