How Predictive Analytics May Impact the Health Care System
Accurate predictions are only useful to the health care industry if specific knowledge can be translated into action. Health care organizations that harness the power of historical and real-time data must strive to predict trends and change behaviors. This means that both the prediction and the intervention must be applied to the original system and workflow that produced the data.
Enhanced Decision-making
Clinical indecision often leads to over treatment and under treatment, which are both wasteful and potentially harmful. Predictive analytics allows clinicians to reserve complex and cost interventions to high-risk patients who genuinely need them. For example, first-time parents and …show more content…
It is being used to systematically compare severe medical events, predict individual outcomes associated with specific conditions and study the relationships between mortality and readmission rates. Health care systems are motivated to use predictive analytics because it improves patient care while avoiding financial, compliance and reimbursement problems. The success of any predictive analytics project depends on live hospital IT environments and vendors that teach their clients how to control costs and streamline operations.
The Secrets of Success
The Harvard Business Review (HBR) offers advice on how to make predictive analytics a regular part of patient care. The HBR states that electronic health records (EHRs) offer limitless amounts of insightful information that just need Big Data techniques to predict individual health outcomes. Clinical decisions produce potential clinical outcomes that should help create and refine predictive algorithms. For example, the algorithms that predict a patient’s risk of hospital readmission do not answer the questions of whether or not patients should be discharged and assigned to a readmission prevention program.
Accurate predictions are only useful to the health care industry if specific knowledge can be translated into action. Health care organizations that harness the power of historical and real-time data must strive to predict trends and change behaviors. This means that both the prediction and the intervention must be applied to the original system and workflow that produced the data.
Enhanced Decision-making
Clinical indecision often leads to over treatment and under treatment, which are both wasteful and potentially harmful. Predictive analytics allows clinicians to reserve complex and cost interventions to high-risk patients who genuinely need them. For example, first-time parents and …show more content…
It is being used to systematically compare severe medical events, predict individual outcomes associated with specific conditions and study the relationships between mortality and readmission rates. Health care systems are motivated to use predictive analytics because it improves patient care while avoiding financial, compliance and reimbursement problems. The success of any predictive analytics project depends on live hospital IT environments and vendors that teach their clients how to control costs and streamline operations.
The Secrets of Success
The Harvard Business Review (HBR) offers advice on how to make predictive analytics a regular part of patient care. The HBR states that electronic health records (EHRs) offer limitless amounts of insightful information that just need Big Data techniques to predict individual health outcomes. Clinical decisions produce potential clinical outcomes that should help create and refine predictive algorithms. For example, the algorithms that predict a patient’s risk of hospital readmission do not answer the questions of whether or not patients should be discharged and assigned to a readmission prevention program.