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AI Can Crunch Critical Data from Historical Healthcare Records—But Only If They Are Digitized First

It’s no secret that the healthcare industry comes with plenty of paperwork. From insurance claims, reports, and filings to patient profiles and doctor’s notes, these documents are a critical part of this industry’s information infrastructure.

Healthcare providers are sitting on a goldmine of critical information for the industry. Unfortunately, this goldmine is disguised as tons of outdated records—the content of which may seem useless to the individuals in charge of storing them. 

With rapid digitization efforts across various industries in recent years, it is important for hospitals and other medical care facilities to keep pace with upcoming technological changes. Healthcare records from years past allow the healthcare professionals of today to crunch data, develop further insights, better understand the ebbs and flows of public health, and more. This is one of the reasons why this data must be digitized, but perhaps some don’t know where to start. 

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With medical and healthcare paperwork, the sheer amount of information collected can be overwhelming. Even more overwhelming is trying to figure out how to efficiently and accurately capture all of that hand-written information in a digital format. With the healthcare information of millions floating around in paper form, the risk of inaccurate transcription is high, and the fall-out can be dire—leading to insufficient care, incorrect diagnoses, and more. 

Luckily, modern technology offers robust solutions for processing historical information—and it’s time for the healthcare industry to take advantage of it. 

The Importance of Accurate Data Capture in Patient Care, Diagnosis, and Treatment

Data is the backbone of hospital systems, and every day, thousands of data sets are aggregated and passed between doctors, nurses, and other healthcare staff to ensure patients are treated and taken care of. 

Implementing technologies like AI through intelligent document processing (IDP) can help lower the rate of errors through accurate patient record analysis. Human beings are prone to error—especially when dealing with tedious and repetitive tasks. IDP can take on these repetitive tasks like capturing data from documents to a precise level of accuracy, without human weaknesses like fatigue and distraction clouding its accuracy. Then, this data can be put into an Electronic Health Records (EHR) system, where doctors and nurses can access it without needing to flip through the original paper files. 

Gathering data in a precise and automated manner also helps make mistakes and inconsistencies more apparent, so they can be flagged and rectified. In the long run, this leads to better diagnoses, better patient care, more efficient and error-free audits, improved reporting, and more proactive business planning. 

Through predictive analytics, AI can help hospitals and clinics better understand their operational capacity based on historical data. This helps them streamline emergency rooms, staffing, hiring, and more—overall providing a better experience for patients and a better working environment for medical personnel. 

How AI and Machine Learning Can Benefit the Healthcare Industry

AI can help business leaders streamline operations and perform repetitive tasks with ease—but not without accurate data and data governance. In a recent survey, only 7% of healthcare and pharmaceutical companies have embraced digitization. Without digitizing the data and employing a data governance system, the data collects dust.

Despite only a small portion of companies embracing digitization to improve business functions,  annual healthcare spending in the U.S. is the highest its ever been. It’s projected to reach roughly $5.7 trillion in 2026. With the immense amount of resources invested in the industry, the modern healthcare landscape demands better infrastructure and technology. AI, machine learning, and intelligent document processing must be leveraged to help organize systems and create a better environment for patients and practitioners alike. 

Streamline Tasks and Boost Productivity 

Asking patients to fill out duplicative paperwork at each doctor’s visit or hospital stay reduces efficiency and creates another record that needs to be reconciled with previous paperwork—whether digital or analog—bogging down operations and adding to the problem. Plus, it’s a generally negative start to the patient’s experience. (Who likes filling out the same paperwork time and time again?) But when hospitals implement digitization into their patient care systems, the duplicative paperwork goes away. Rather than putting pen to paper, patients can simply verify that their information is correct. This improves the patient experience and frees up the admin and medical staff, allowing them to focus on their core functions. 

Emerging technologies in AI allow medical staff to scan and capture information from even handwritten documents and load them directly into their EHR systems. This means a doctor’s notes from patient records can be scanned and added directly to a patient’s digital file in seconds. Ultimately, this enhances the information available about patients from all types of records. Having this comprehensive collection of data in a digital space enables analytics to make better recommendations for caregivers while also providing better training data to AI models. This leads to more automated processes as well as more insights that can help lower the cost of healthcare and produce better outcomes for patients

Comprehensive technological investment in AI, machine learning, and IDP strategies can only benefit medical systems long-term. Data fuels this industry, and if your patients’ data is just collecting dust in a filing cabinet, it isn’t benefiting you or your patients, or helping advance public health goals. With the modernization of IT systems, there’s no excuse to avoid improvement. Medical offices, hospitals, pharmaceutical companies, and the like can greatly benefit from improving operations, reducing risk, and providing better care with the adoption of these new technologies. 

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