Operational Intelligence (OI) is a system of real-time data analytics utilized in business operations decision-making. Mathematical algorithms, applying current and historical data, evaluate alternative solutions, calculate the benefits and costs based on set objectives, and provide operational instructions. OI produces real-time information that can be applied immediately, allowing decision-makers to make informed, proactive decisions rather than reacting to issues or situations.
Traditionally used in the military, manufacturing, and general service industries to address the challenge of navigating complex decision making, OI is becoming increasingly important in the healthcare industry to address complexity in clinical operational decision-making.
One specific clinical use case is clinician scheduling – to help balance the critical need for patient care with the available supply of healthcare providers. Especially during the pandemic, it has become crucial to continue to provide appropriate staffing levels to protect patients’ safety and, just as important, alleviate burnout and fatigue in the overburdened nursing staff.
In addition to balancing supply and demand, an optimal schedule must also consider additional objectives, including:
- Maximizing the throughput of the department (the number of patients treated in a time period)
- Minimizing nurse overtime
- Honoring nurse staffing preferences
- Complying with hospital and state rules and regulations
When it comes to scheduling, it is impossible for human efforts to quickly and accurately perform the complex calculations required to solve all these objectives and satisfy the department’s constraints. Therefore it is not surprising that status quo manual scheduling methodology often results in a disregard for individual preferences, dissatisfaction with the process, unnecessary time spent correcting and managing the schedule, patient safety issues, and long patient waits.
By applying scientific solutions with proven results, OI enables Medecipher to design scheduling solutions that incorporate the patient and departmental complexity needed to achieve realistic and feasible solutions for Emergency Departments applications. Medecipher’s solution takes the analysis further by providing real-time decision support to ease the hassle and time involved in scheduling. The optimized schedules predict patient load and flow, prescribe appropriate staffing levels to meet the patient needs and assign staff, and adapt based on the clinical judgment of the Nursing Leadership.
Overall, these optimized schedules help improve the financial performance of a health system (by reducing their reliance on premium pay labor), improve the safety & quality of care for patients (by improving operations), and improve the quality of the work environment for nurses and providers (by justifying a safer staffing position).
