Data Analytics and Its Advantages for Addressing the Complexity of Healthcare: A Simulated Zika Case Study Example

Abstract

The need to control rising costs in healthcare has led to an increase in the use of data analytics to develop more efficient healthcare business models. This article discusses a simulation that uses data analytics to minimize the number of physicians and nurses needed in healthcare facilities during a crisis situation. Using a hypothetical emergency scenario, the hospital uses a healthcare analytical system to predict the necessary resources to govern the situation. Based on historical data regarding the flow of patients through the facility, a discrete-event simulation estimates resource scheduling and the resulting impact on both wait times and personnel demand. Furthermore, the value of multiple replications for discrete-event simulation models is discussed and defined, along with factors that enable greater control of multiple design points with this simulated experiment. The results of this study demonstrate the value of simulation modeling in effective resource planning. The addition of only a single doctor significantly reduced predicted wait times for patients during the crisis. Further, the findings support the use of data analytics and predictive modeling to mitigate rising healthcare costs in the United States through efficient planning and resource allocation.

Discrete-Event Simulation Modeling in Healthcare: A Comprehensive Review

“…First, there is the cultural side, as healthcare professionals (e.g., doctors and nurses) respond to pressure and system modifications by changing their performance and behavior [9]. In conjunction with changes, diversity across entities causes a lack of acceptance and fear regarding information and confidentiality [229]. Second, infrastructure plays a critical role.…”

“…Second, infrastructure plays a critical role. Difficulty in accessing enough quality data, system failures, and changes in work processes, security, and privacy, all are critical barriers to implementing models [229]. In addition, other financial constraints could undermine research.…”

Multimethodology for diagnosis and intervention in a prosthetics and orthotics factory in Brazil

“…It is also important to conceive different hypotheses, consolidated in scenarios, for planning interventions and addressing demand estimates (Kopach‐Konrad et al., 2007; Popova Zhuhadar and Thrasher, 2019). DES requires reliable representative data for the construction of models (Vanbrabant et al., 2019).…”

Data Analytics in Smart Healthcare: The Recent Developments and Beyond

“…Application Methodology [7] Prediction of inpatient violence incidents [18] Minimizing the number of physicians and nurses Discrete event simulations [19] Classification of organ inflammation Genetic algorithm; support vector machine…”

“…L. Popova Zhuhadar, and E. Thrasher simulated a crisis scenario in "Data analytics and its advantages for addressing the complexity of healthcare: A simulated Zika case study example" [18] in which the number of physicians and nurses was minimized using data analytics techniques. The simulation analyzed various cases based on the number of outpatients arriving the clinic and the waiting time to consult a medical doctor or pre-examination by a nurse.…”