AI Leap Medical

Why Hospital Needs Effective Schedule?

Scheduling has been often described as having both positive and negative effects: It can contribute to a crisis or become a competitive advantage; it can increase revenues or lower team morale. For such a small piece of organization’s administrative responsibilities, it has a huge impact on success. The single largest expense of the organization – payroll – is managed and directly controlled by the schedule. However, the financial impact of the schedule goes deeper than that. It improves productivity, accuracy, and saves funds spent on administering work.
 
For everyone, and especially clinical teams, the work schedule is one of the greatest influencers of personal lives. It is vital to ensure that each team member receives a fair and equitable schedule. If someone is receiving a schedule that the person finds too demanding, or out of line with the rest of the group, morale can take a serious hit. Additionally, in situations where staffing is required 24/7/365, burnout and shift-work disorder are common concerns. Shift-work disorder and excessive fatigue have been linked to increased rates of many illnesses, as well as a decrease in performance, and an increase in the likelihood to make mistakes, which can be dangerous and costly.
 
Based on a number of studies, Americans demand for primary care providers is straining the limited supply. The Association of American Medical Colleges estimates that by 2015 the United States will face a shortage of more than 33,000 primary care practitioners. A physician shortage in the U.S. was expected even before the Affordable Care Act was signed into law in 2010, according to the Association of American Medical Colleges. Now the group estimates that there will be a shortage of 63,000 doctors by 2015 and 130,600 by 2025.
 
The shortage of personnel amplifies the complexity of medical scheduling. The lack of modern technologies exacerbates the issue of the quality of medical schedules, and that is a determining factor in your success in delivering quality care and retaining your best clinicians. Consistently good schedules lead to happier, higher performing providers, and increased revenue generation. Consistently bad schedules can cause internal conflict, decreased quality of care, lower your revenue, and contribute to a personnel turnover.
 

Current Scheduling Practices and Shortcomings

Due to a severe shortage of personnel, high-quality medical scheduling is a challenging task. There are practices where it is done by an administrator manually through a spreadsheet or with an assistance of one of available medical scheduling software applications. However, most of medical scheduling software use last-century technologies: Monte Carlo Simulation, single shift insertion, backtracking, etc. In addition, many existing software packages expect manual entries of numerous requests and assignments, filling out complex forms with rules in a software-friendly format. Often the final phase of the schedule fine-tuning is assigned to a physician who spends up to 20 hours per month doing just that.
 
A broad research has been conducted regarding the success of various scheduling methodologies. It demonstrated that technologies currently used in medical scheduling can succeed only in case of under-loaded resources (physicians, residents, nurses), which is almost never the case. Therefore, all existing applications are doomed to fail even in case of moderate rule complexity. This is exactly what many hospitals see on a daily basis.
 

AI Leap Medical Scheduling Solutions

Many of the mentioned above operations can be replaced by an application with Artificial Intelligence. AI Leap offers a cutting-edge solution that gives an easier and more effective way to construct high quality schedules. It uses two types of data: Master Data of the personnel and their skills and a diverse Rules Data of shift assignment preferences and restrictions.

Master Data is a listing of subjects and objects (personnel, patients, rooms, equipment) available for the next scheduling period, their FTE’s, profiles, attributes, groups, etc. Rules Data describes a variety of rules followed within a scheduling period and from one period to another. Rules can be inherited or adjusted. For example, circadian rules are about assignment sequencing (e.g. no day shift after night or swing shift) and usually remain without changes, vacation requests and CME’s, on the other hand, are expected to vary.
 
Rules also reflect preferences for the number of total, day, night, weekend or other types of work hours, etc. Rules Data could also include more complex blocking structures that specify days off after a sequence of assignments, or complex sequences of shifts, like “2 days off after 5 days on, 4 days off after 6-7 days on”, “start a block with 1-3 triage shifts, then 2-3 Longs, then 2-3 Shorts, then on Call and finish with 1-3 Nights right after Call or one day later”. In the introduction of rules and their specification. AI Leap also uses Artificial Intelligence to understand English descriptions like “every third Friday”, “Monday after a Day off on Saturday”, “from June 27 to July 3”.