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How Digital Tools in Healthcare Help Provide Superior Patient Care

Paper-based data can be digitized with data conversion services. AI can be used to derive valuable insights vital for accurate diagnosis and superior care.

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How Digital Tools in Healthcare Help Provide Superior Patient Care

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  1. How Digital Tools in Healthcare Help Provide Superior Patient Care? Paper-based data can be digitized with data conversion services. AI can be used to derive valuable insights vital for accurate diagnosis and superior care. Managed Outsource Solutions 8596 E. 101st Street, Suite H Tulsa, OK 74133

  2. Over the last decade the healthcare industry witnessed huge growth and the demand for health informatics workers. This encouraged the use of electronic health records, and the demand of data conversion services to convert any paper-based data into digital format. Healthcare technology gives care providers the ability to streamline processes and offer personalized care with more efficiency. The digital world has taken the healthcare industry to a new level. Technology has reshaped how patients and physicians communicate. With the help of constant information sharing, physicians can identify the disease, provide medication and design medication schedules accordingly. Similarly, medical record keeping has also become more efficient with digital patient data. Proper standards and regulation around the Electronic Healthcare Record are vital to capture reliable healthcare data for valuable insights. With the right digital tools, healthcare units can implement and integrate technology into healthcare to improve efficiency and operations. Digital transformation is a new way of providing quality service to patients and it requires all aspects such as people, processes and technology to align together to get optimum results. It also helps to identify the business drivers, ensure ease of use adoption and actively communicate benefits associated with digitization initiatives to ensure complete business ownership and adoption on the same. To make digitization more effective, IT leaders should understand the difficulties of clinicians and patients and find ways to strengthen patient safety, experience and cost-efficiency. Digital Tools: Artificial Intelligence and Big Data The healthcare industry generates a huge amount of data, both physical and digital. Big Data is harnessed, and artificial intelligence is now used in the healthcare industry to gather new insights and provide better patient care. Compared to other industries, the healthcare sector has been slow in adopting digitization but now it is rapidly picking up. Today, healthcare uses computational power to analyze huge datasets, identify patterns and gather useful insights from the existing patient data to make accurate diagnoses and provide better patient care. Use of Artificial Intelligence in Medicine Traditional drug discovery requires 12 to 15 years of trial and research to know whether it’s effective or not and this causes delay in the delivery of the drug. AI can boost pharmaceutical research. www.managedoutsource.com (800) 670 2809

  3. With clinical data and molecular research, predictive modeling can help in understanding potential-candidate molecules that have a high probability of being successfully developed into drugs. • Monitoring live data from patients and feeding it directly into the system helps the model to adapt to the changing medical history. • The predictive mode helps to eliminate the overall cost and time needed for trial and monitor processes usually seen in drug discovery Better Diagnostics AI is used to detect skin cancer. Scientists from Stanford University have created algorithms that can visually diagnose a potential cancer cell using a database of around 130,000 skin disease images. Following are some the major players in disease diagnostics: • Google’s DeepMind health is developing a technology to address macular degeneration in aging eyes. • IBM Watson Genomics is making strides in precision medicine by integrating cognitive computing and genomic tumor sequencing. • Boston-based biopharma company Berg is using AI in healthcare to research and develop diagnostics and therapeutic treatments in various areas, including oncology. • For depression, Oxford’s P1vital® Predicting Response to Depression Treatment (PReDicT) project is using predictive analytics to diagnose and provide treatment, with the goal of producing a commercially-available emotional test battery for use in clinical settings. Better Treatment for Patients Telemedicine has been in the healthcare industry for over 40 years. With advanced technology like online conferences, wireless devices, wearable devices, smartphones etc, it has been transformed into a reliable service for remotely treating patients. AI and Telemedicine are match-made in heaven because they both aim at cutting costs and also provide better diagnosis and faster recovery. • Physicians can diagnose, monitor, and treat conditions like diabetes through telemedicine. The Los Angeles County Department of Health Services recently reduced visits to specialty care professionals by more than 14,000 with the help of telemedicine screenings for diabetic retinopathy at its safety net clinics. www.managedoutsource.com (800) 670 2809

  4. Integrating telemedicine with AI like IBM Watson helps in better diagnosis with less human effort. For instance, an algorithm could monitor every treatment for a particular illness and then ask patients how long it took them to get better on average. The platform could then adapt and suggest treatments based on past success rates. • AI can minimize long hospital waits times and other administrative headaches. It can route questions to the doctor with the best outcomes for a patient’s symptoms instead of just sending them to the first doctor available. Optimizing Duty Allocation Staffing is a major issue in healthcare. Too many staff can lead to increased costs whereas poor staffing can compromise patient care. Big data analytics in healthcare is helping to solve this problem in a few hospitals in Paris. 4 hospitals used data from internal and external sources to develop a prediction model. The data collected included a 10 years’ history of hospital admission records. The model could predict the approximate number of patients you could expect at each hospital at a given time with an accuracy of 80 – 90% on a day-to-day basis. With the advent of AI, healthcare businesses are realizing that they can now process and make use of all the data they have accumulated all these years. Paper-based data can be converted into digital format with the help of data conversion company. All relevant data can be integrated with AI to make valuable insights to provide accurate diagnosis and superior treatment. www.managedoutsource.com (800) 670 2809

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