mindtalks artificial intelligence: How AI and Predictive Analytics Are Enabling the Digital Transformation of Hospital Operations – HealthLeaders Media – picked by mindtalks

Each day, hospitals face stiff challenges in trying to ensure high quality patient care while balancing the constraints across the organization.

“It requires a holistic view to do it well, but the reality is hospital leaders still rely on a disjointed process of spreadsheets, phone calls, texts, and even faxes to make critical operating decisions,” says Jason Harber, executive vice president of operations at Hospital IQ. He says that digital transformation allows organizations to increase their situational awareness, automate business practices, and embed AI to improve decision making. Harber discusses how digital transformation platforms are helping healthcare organizations improve key areas that have suffered more financial pressure than ever before due to COVID-19 and other industry disruptors.

Q: What are some of the common operational challenges hospitals are facing daily?

A: Hospital leaders are balancing numerous challenges related to the management and coordination of their operations. Two great examples are coordinating patient discharges and nurse staffing due to the last-minute dynamics they face in a constantly shifting environment. The tools they use to ensure patients are seen at the right time and place by the right provider are very fragmented, and communication between leaders, staff, and teams are often siloed. COVID-19 brought these challenges to the forefront when hospitals were stretched to capacity in many regions of the country, which ultimately impacted the patients, as many communities struggled to gain access to care.

Unfortunately, front-line teams often don’t have the right information about current and upcoming capacity needs to align on the priorities across their various patient units (critical care, med/surg, behavioral, etc.) to effectively coordinate timely patient movements and relieve the organization of their capacity constraints. Additionally, nursing shortages—made worse during the pandemic—put even more stress on an already fragile system. Very few organizations have the tools in place to enable frontline staff to manage these dynamic situations appropriately.

Q: You mentioned that with the dynamic day-to-day operating environment, hospital leaders lack time and insight to make more efficient and effective decisions. What are these leaders doing to overcome the overall challenges?

A: As staffing and patient volumes, along with barriers to discharge, constantly change, leaders rely on phone calls, rounding, text messages, and even faxes to understand the constraints and make decisions. However, many are starting to realize this highly manual process is no longer sustainable. They are looking to create “systemness,” the coordination of multiple operating units that, when working together, create a network of activity that is more impactful than any action of individual units themselves.  Unfortunately, they simply don’t have the technology to drive the level of efficiency that is needed to operate in today’s complex healthcare environment. Organizations often try to rely on their EHR and existing IT systems, business intelligence tools, performance improvement teams, and consultants to support systemness, but ultimately they are finding it is not enough, and they are looking for more advanced technology to overcome these challenges

Q: Explain how AI-enabled machine learning and predictive analytics play a role in streamlining operational efficiency?

A: AI and predictive analytics work inside of daily operational processes to provide targeted information to decision makers in areas such as patient throughput and staffing. This combination of capabilities, known as intelligent automation, gets the right information, with the right action, to the right person hours, days, and weeks in advance, ensuring alignment of actions and priorities across the enterprise. The result is a new level of peak operational performance that will not degrade over time. So, we are implementing standardized processes and replacing manual and ad-hoc communications with AI-driven insights that can show everything from today’s discharge priorities and associated staffing needs to potential organizational bottlenecks up to seven days in advance.

Q: What are some of the outcomes you’ve seen with hospitals that are today using intelligent automation?

A: Our clients are seeing amazing results in how they manage patient discharge and staffing practices. For example, our discharge management customers commonly shave ½ day off their length of stay, discharging patients earlier than ever before, which not only reduces the cost of that patient visit, but also opens up a bed for the next patient. Clients focused on improving their staffing practices have seen impressive results as well. When healthcare organizations begin balancing staff more proactively, they can free up hundreds of hours of time across their nursing leaders each week, reduce premium pay, and increase staff satisfaction. These improvements not only have a positive impact on strategic KPIs and the bottom line for the hospital, but they also improve the quality of care provided to the patients.


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