Big Data

How does Big Data affect healthcare?

how does big data affect healthcare

How does Big Data affect healthcare?

From planning strategically to relying on predictive analytics, here are 15 answers to the question, “What are some important ways Big Data affects healthcare?”

  • Informing Strategic Planning
  • Improving Access to Accurate Patient Info
  • Reducing Socioeconomic Health Barriers
  • Giving Doctors More Info Through ADSS
  • Decreasing Prescription Errors
  • Cutting Operating Expenses
  • Allowing for a Holistic Healthcare Staffing View
  • Predicting Opioid Misuse
  • Helping Find the Root Cause of Diseases
  • Enhancing Readiness to Handle Public Health Risks
  • Accelerating Clinical Trials
  • Delivering Personalized Medical Treatment
  • Preventing Suicide and Self-harm
  • Growing Fertility Success Rates
  • Offering Helpful Predictive Analytics

Informing Strategic Planning

Big Data is a powerful tool for healthcare organizations. By collecting and analyzing enormous volumes of data from health systems, medical records, insurance claims, and government sources, Big Data analytics can help identify patterns that can inform strategic planning.

For example, it can help providers understand how patient preferences influence the utilization of services, where resources should be allocated, and what services should optimize outcomes.

Big Data can also help identify cost-saving opportunities, detect fraud, analyze provider performance, and make personalized treatments more accessible. In short, Big Data has the potential to revolutionize healthcare by giving providers the information they need to make informed decisions that improve patient care.

Michael Fischer, Founder, Elite HRT

Improving Access to Accurate Patient Info

One of the key ways in which Big Data affects healthcare is by providing healthcare providers with more comprehensive and accurate patient information. With the increasing amount of patient data generated every day, from electronic health records to wearable devices, healthcare providers now have access to vast amounts of data that can be analyzed and used to gain insights into patient health and disease.

This‌ allows healthcare providers to make more informed and accurate diagnoses, develop more effective treatment plans, and ultimately improve patient outcomes. By utilizing Big Data, healthcare providers can take a more data-driven approach to patient care, ensuring that each patient receives the best possible treatment based on their needs and medical history.

In conclusion, using Big Data in healthcare transforms how medical professionals diagnose and treat patients, improves patient outcomes, and revolutionizes the healthcare industry.

Zach Goldstein, CEO and Founder, Public Rec

Reducing Socioeconomic Health Barriers

Big Data allows upper-level health executives to source information about various patient demographics and their behavior toward their healthcare. Technology can capture details like income levels, residential areas, job descriptions, and diagnosed conditions which we can use to deduce the factors that influence health disparities across regions.

These insights have been invaluable in identifying the socioeconomic challenges impeding patients’ access to optimum healthcare. Humanitarian and health organizations are actively applying these figures to community programs and other large-scale plans designed to boost health conditions among struggling populations.

Stephan Baldwin, Founder, Assisted Living Center

Giving Doctors More Info Through ADSS

One major area where Big Data is impacting healthcare is through automated decision support systems (ADSS).

ADSS assists physicians in making clinical decisions based on real-time analysis of medical records generated during patient visits and high volumes of information regarding their health history, lab test results, etc. This reduces potential errors caused by misdiagnoses or prescribing incorrect medication dosages over time because of a lack of updated information/data points across diverse sources/devices (like EHRs).

When linked into an intelligent system like an electronic health record (EHR), treatment plans update automatically when new data comes in, giving doctors more up-to-date information about their patients’ condition than ever before, enabling them to provide better outcomes for their patients faster than was previously possible—this transformation saves both money and lives!

Travis Lindemoen, Managing Director, nexus IT group

Decreasing Prescription Errors

Prescription errors harm at least 1.5 million consumers annually, and big data is poised to help reduce and prevent them.

Some healthcare organizations are already adopting a decision support tool that won’t simply flag prescription errors, but use AI algorithms to predict when they are more likely to happen. With 24/7 functionality, the system continually checks at all points of medication access and delivery and effectively reduces the risk of human error during the process.

Jack Underwood, CEO and Co-Founder, Circuit

Cutting Operating Expenses

A comparable necessity to switch to a new model is required in the current healthcare environment in order to reduce total operating expenses. It will be possible to establish stronger links between consumer and patient needs for healthcare by utilizing rich data sources in a shared environment.

For instance, by using historical data, hospitals can estimate the number of flu vaccines they should purchase based on past usage, or healthcare professionals can help patients more rapidly if they have access to their complete medical histories.

Through the use of healthcare applications, consumers or patients can contribute significantly to the process by providing accurate, reliable health and wellness monitoring. Businesses have used Big Data in other industries to drastically cut operating costs through better forecasting, which is connected to operating problems in the healthcare sector.

Brian Clark, Founder, United Medical Education

Allowing for a Holistic Healthcare Staffing View

One aspect that’s sometimes overlooked is the interplay of worker satisfaction and patient outcomes. A happy employee is more dedicated to the task at hand, but this sort of predictive analysis can be overwhelming without the help of software programs that merge sometimes contradictory information, like emotional intelligence, scheduling preferences, experience, and skill sets for each candidate.

Big data allows me to look at everything at once: a holistic approach that ensures the perfect person for each role. Appropriate placements result in a more engaged workforce, and that leads to better care and fewer mistakes overall.

Debbie Winkelbauer, CEO, Surf Search

Predicting Opioid Misuse

Opioid misuse is being combated head-on by big data. Big Data allows machine learning and analytics to pinpoint patients who are most likely to misuse opioids or die from opioid-related causes.

By identifying pharmaceutical errors and adverse reactions, big data enables the reversal of drug-related occurrences. Data scientists can now pinpoint risk indicators that foretell opioid misuse inclinations using petabytes of pharma and insurance data.

Leonidas Sfyris, CTO, NEEDaFIXER

Helping Find the Root Cause of Diseases

By leveraging massive amounts of data, medical professionals can unlock valuable insights into patient care. For example, Big Data can help clinicians better understand the root causes of diseases and discover potential treatments more quickly.

The analysis of large-scale clinical trials can aid in understanding the safety and efficacy of a drug or medical device much more rapidly than ever before. In conclusion, Big Data gives physicians access to meaningful insights that are revolutionizing patient care.

Benjamin Okyere, Data Engineer, Stress Reliever

Enhancing Readiness to Handle Public Health Risks

One thing we learned from the tragic COVID-19 pandemic is that the world is not nearly as prepared and ready to deal with a major public health crisis. Although we got by, there were so many gaps, especially in anticipating and addressing COVID risks before the outbreak.

However, I firmly believe that we are going to see increased use of big data and advanced analytics to enhance our ability and preparedness to deal with substantial public health emergencies.

We are likely to see advanced use of artificial intelligence in tracking public health patterns in efforts to predict or preempt the next pandemic. Even if we cannot predict precisely when the next public health crisis will arise, Big Data will still play a key role in developing response strategies by analyzing previous pandemics and their patterns‌.

Logan Nguyen, Co-Founder, MIDSS

Accelerating Clinical Trials

Clinical trials are crucial to medical research, but they often come with high financial costs. By leveraging big data, healthcare providers can speed up the clinical trial process by quickly identifying potential candidates for trials and then tracking their progress throughout the entire procedure.

This allows researchers to save time, money, and resources by reducing the number of people needed in a trial or by reallocating resources where they are needed most. Big data analytics can also identify trends in outcomes across different treatment options, which can help guide decisions about which treatments should be tested in future clinical trials.

Karl Robinson, CEO, Logicata

Delivering Personalized Medical Treatment

One way that Big Data affects healthcare is by enabling more personalized and precise medical treatment. By collecting and analyzing large amounts of patient data, healthcare providers can gain a more comprehensive understanding of individual patients and their specific health needs.

This information can develop tailored treatment plans, predict potential health issues, and improve overall patient outcomes. For example, Big Data can analyze amounts of electronic health records (EHRs) to identify patterns and trends in patient populations. This information can then be used to develop predictive models that help healthcare providers identify patients who are at risk for specific conditions, such as heart disease or diabetes.

Damjan Tanaskovic, CMO, Localizely

Preventing Suicide and Self-harm

Through a combination of digital surveillance technologies, predictive analytics, and machine learning algorithms, we can analyze data to identify patterns and provide healthcare professionals with useful insights into those at risk of suicide or self-harm.

The data gathered helps to create targeted preventative interventions, which can effectively reduce the rate of suicide attempts. An added benefit is that healthcare practitioners often have more time to devote to other services, as they no longer have to completely rely on manual screenings. Big Data can be a powerful asset for suicide prevention as part of our overall healthcare system.

Nadzeya Sankovich, Regional Manager, Health Reporter

Growing Fertility Success Rates

In recent years, fertility clinics have been using advances in data science to increase fertility success rates. By using sophisticated algorithms and data analytics, fertility clinics have been able to better predict fertility success rates, identify fertility problems earlier on, and determine which fertility treatments are most likely to be successful.

Gabriel Bogner, Co-Founder, Mate Fertility

Offering Helpful Predictive Analytics

Big Data has revolutionized the healthcare industry by providing a wealth of data that can predict certain trends or outcomes. Predictive analytics use historical and real-time information to anticipate future events, allowing healthcare organizations to make more informed decisions that might improve patient care, reduce costs, and lower risks.

Examples include predicting the likelihood of readmissions, understanding which treatments are most successful for particular conditions, and predicting which patients are at risk for certain diseases or health complications. Big Data also helps healthcare organizations identify areas where they may need to make changes or improvements in order to improve outcomes.

Michael Dadashi, CEO, Infinite Recovery

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