From the health histories of patients to the effectiveness of different healthcare services, hospitals are sitting on a treasure trove of historical data. Unfortunately, most of these data go unused, often because they are so difficult to store or format for actionable use.

Due to inconsistencies in numerous areas, such as documentation, structure, formatting, and aggregation methods, hospital data are widely viewed as a burden rather than an advantage. Most hospitals also simply lack the manpower to organize and manage this overwhelming volume of information.

As a result, hospitals miss out on many opportunities to drive improvements in health outcomes and operational efficiency. And when efficiency suffers, staff members become overworked and burn out, which has since prompted many healthcare workers to leave their professions.

Fortunately, recent advancements in artificial intelligence can help hospitals finally leverage large and complex data sets. With myriad valuable trends and insights at their disposal, hospitals can deliver better patient care, identify operational hazards, and optimize operations to manage their workloads without compromising the mental health of staff members.

What’s stopping hospitals from using historical data?

Hospital data are particularly difficult to organize because they come from a variety of sources. Patient data, for example, can be obtained through electronic health records (EHR), administrative systems, insurance providers, patient-submitted forms, local HR systems, hospital medical devices, and remote monitoring services. Moreover, different sources display their data in different formats, such as physical documents, photographs, charts, and digitally structured data.

The problem is that certain formats can’t be entered into one conventional database and instantly converted into another, easily comprehensible format. Conventional databases also lack the capacities to store such huge volumes of data, let alone organize it for seamless use.

Where to start

The first step toward improving a hospital’s data-collection capabilities is to stop using paper documentation. In addition to decreasing the risk of human error, collecting data through digital means prevents small but significant pieces of information from inadvertently getting lost in the chaos of manual processes. Digital tools such as EHRs and electronic devices are evolving every day to produce increasingly accurate and consistent data.

Next, the data must be organized in a manner that makes them easy for clinicians to manage and integrate into patient care. As it stands today, healthcare workers are so overloaded with information that they can’t begin to even think about incorporating it into their day-to-day routines.

This is why much of the latest AI-driven tools for healthcare were designed with users in mind. By putting critical statistics and insights front and center, these tools allow hospital administrators to consistently monitor the operational efficiency of the entire hospital as well as specific departments or even clinicians.

How can historical data help hospitals deliver better treatment?

AI’s initial appeal for healthcare can be attributed to its ability to ingest large quantities of data from a multitude of sources. This can give providers a detailed and holistic view of a patient’s health history as well as the current state of the patient’s health. When physicians can understand the health of their patients to this degree, they can create increasingly personalized treatment plans, identify early warning signs of serious conditions, and apply preventive measures before it’s too late.

Furthermore, AI can review historical data from many patients of similar health to determine an individual’s risk of contracting certain diseases or suffering a health emergency. These predictive models can even be programmed to alert physicians when a patient’s risk for a disease or health emergency has reached a certain threshold. Physicians are only human and, without the type of insight that AI brings, they may struggle to excavate critical trends and patterns from large datasets.

Improving efficiency and working conditions

Hospitals can improve patient care even further by using AI to collect additional data in relation to patient admissions, patient traffic, and the number of critically ill patients requiring life-saving care during different intervals of time. This helps hospitals determine the exact points where operations and individual workflows become congested or disrupted. For instance, operational data could reveal the specific events that trigger a domino effect in which multiple workflows become disrupted, one after the other. Rather than being caught off-guard over and over again, supervisors can prepare strategies for preventing these busy periods from inhibiting the hospital’s efficiency.

With this in mind, hospitals can also review the aforementioned metrics to identify the most overworked staff members before they become burned out, which is particularly hazardous in the healthcare industry. Supervisors can then consult these findings when creating shifts for staff members, as opposed to blindly allowing certain staff members to take on significantly more stress than their colleagues.

Staff members can deliver more effective care when they’re less stressed and more respected by their workplace. Along with physical exhaustion, excessive stress can cause healthcare workers to lose motivation and develop a sense of apathy about their field. That’s why hospitals need to make sure that no staff member is treated unfairly by gathering the data to assign increasingly sensible and equalized shifts. After all, most negative hospital experiences can likely be attributed to overworked staff members.

High volumes of data are already flowing throughout the health care system. Until hospitals invest in the necessary staff and resources to use this information to their advantage, historical data will remain the most underutilized asset in the entire industry.

These are big changes, considering that technology has not traditionally played a substantial role in guiding patient care or employee management. But most hospital staff members would certainly welcome a major cultural shift that gives them more resources to care for their patients. Newly empowered by AI’s insights and optimizations, healthcare workers can save more lives without making their own lives unnecessarily harder.