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Limiting Readmissions through Data and Analytics

By CIOReview | Wednesday, May 3, 2017

Regime change seems to bring no significant changes in the healthcare arena. Healthcare providers strive to deliver best of the healthcare services, but uniqueness of every case put them in the quagmire. Chronic or non-chronic, the history of the patient reads a simpler one, resurfacing of old symptoms necessitate the readmissions. With the same old Medicare Act in force, healthcare organizations should ponder over limiting readmissions that cost them economical pinch in the times of grim financial and market conditions. Though healthcare organizations are large receptors of data, lack of right tools and practices will leave the healthcare providers in the same old catch-22 situation. For healthcare providers, treating patients is the basic tenet whereas they have penalties to pay for quick readmissions.

A glance at Healthcare statistics highlightsing a growing trend while serving a cautionary notice. In recent years , the number of index admissions has drifted south, but the rate of readmission has moved north across the U.S. Rate of readmission is higher for patients with chronic illness, but with data and analytics, healthcare organizations strategize to curtail the rate of readmission and avoid penalties.

Why readmissions cannot be avoided?

Conventionally, the healthcare practice was following a simple principle. Even though patients reported for illness repeatedly, readmission was the simple recourse. To bring the transparency and accountability, and heighten the level of patient satisfaction, Medicare Act came in force with laws that penalize readmissions within 30 days and changed all the paradigms. Implications of Medicare Act were unprecedented as many bylaws are framed with the patient welfare. The situation becomes intricate for large healthcare organizations that operate numerous healthcare facilities in various regions. Monitoring readmissions in their referral centers and community hospitals become herculean task due to inadequate tools and efficient practices. If a patient is discharged by the referral center, but later gets readmitted to regional center for availing extensive gamut of healthcare services, readmission becomes inevitable for the healthcare organization. Subsequently, the large healthcare provider registers sub-par performance in terms of readmissions.

How to reduce the rate of readmission?

IT leadership in the hospitals should strategize to digitalize the essential processes, which majorly contribute toward index admissions and readmissions. In the majority of referral and regional care centers, patient enrollment, check-up, and post-check procedures are performed manually. Though human examination of patients is the integral part of the healthcare practice, telemedicine and cloud reduce the cumbersome processes and give the visibility of healthcare processes in real time to the large healthcare organizations. Telemedicine plays crucial role in expediting the patient examination and critical cases can be reviewed by the specialists in real time. As the interaction between patients and physicians is stored in the cloud native applications or recorded and stored in the cloud, the ease of accessibility of the data, will definitely help to improve patient experience. Incorporation of Electronic Health Records (EHR) can definitely simplify the process of data pooling. Healthcare organizations can partner with the solution providers to discern the genesis of readmissions. Detailed information, which is inclusive of patient history and its measurement against the standard benchmarks in healthcare, might help the healthcare organizations to design algorithm to zero in critical medical cases with high probability of readmissions. A group of stakeholders can conduct the interviews with patients and physicians to gain the first hand information and create a large data sample to enhance the algorithms. Publicly available healthcare data may prove helpful in analyzing causes of readmission, the time window within which readmission took place. The core group should design the process that would contribute toward reducing readmission rates. In recent developments, The University of Tennessee Medical Center has registered remarkable reduction of 70 readmissions per month after the deployment of the analytics and artificial intelligence (AI) based solution. This case might be an eye opener for healthcare organizations.