Big Data applications have drastically changed the way in which we manage, analyze and improve data in all industries in a very short time. One of the most notable areas where data analysis is generating major changes is medical care .
Indeed, Big Data in health has the potential to reduce the costs of treatments, prevent and prevent outbreaks of epidemics, avoid illnesses and improve the quality of life in general .
This industry is now so booming, that it is predicted that by 2030 it will be a market worth more than US$105 thousand million —which will eventually reach US$33 thousand million in 2021—, which indicates that its annual growth rate is around 14 %.
In this sense, in this post we will explain to you in detail what these Big Data applications are in the healthcare area and how a whole tool can be implemented in your medical care business to optimize and enhance your processes to offer better and better results. precise services to your customers.
Come on!
Benefits of Big Data in health
Big Data applications in healthcare have the potential to improve medical care , managing to optimize multiple processes, from improving patient experience to creating complex machine learning models to diagnose illnesses and medical conditions.
By counting on more data from your customers, you get an invaluable opportunity to better understand your experience and improve the attention you receive.
Furthermore, Big Data offers medical researchers unprecedented access to large volumes of data and information collection methods . This promotes medical advances that can save lives, so that researchers can analyze and use this data to make discoveries and improvements in medical care.
Big Data applications in health
Understanding the importance of analyzing large volumes of data in this industry, let's explore the 5 main uses and applications of custom healthcare software development services such as Big Data from an analytical approach to improve internal processes and patient experience.
Improved clinical research and drug discovery
- obtaining valuable information on the effectiveness of treatments, the progression of illnesses and risk factors.
- allowing you to identify potential therapeutic objectives, predict the effectiveness of medicines and optimize clinical trials.
- Disease surveillance : researchers can detect disease patterns and trends, which facilitates early response and prevention of outbreaks.
- Pharmacovigilance : monitoring safety signals and potential risks associated with specific medicines.
- All these processes facilitate clinical research and drug discovery, accelerating health treatments and saving lives in a timely manner.
Optimization of health resources management
Big Data also plays a crucial role in optimizing health resource management. Here are some specific applications:
- Inventory and supply management : monitoring usage and consumption data, hospitals and medical care centers can optimize your orders and avoid both shortages and excess stocks, especially in countries like Mexico, where medicine supply cuts and Vaccines suffer from multiple problems .
- Personnel programming : identifying personnel needs at different times and locations is possible to ensure an appropriate allocation of human resources, reduce excessive workload and improve operational efficiency.
- Planning of installations and resources : understanding the demand and use of installations, strategic planning can be carried out to guarantee an optimal distribution of resources and avoid infra-utilization or congestion.
- Optimization of routes and logistics : analyzing traffic data, location and waiting times, you can find the most efficient routes and minimize delays.
- Cost and invoicing analysis : evaluating invoicing data, complaints and payments, we can identify areas of improvement, reduce errors and maximize income.
In this way, organizations focused on health care can effectively manage their resources, guaranteeing the responsible and planned use of resources and the provision of inputs to patients.
Improves patient care and user experience
Through custom enterprise software development such as electronic clinical history or EHRs , it is possible to obtain powerful insights thanks to demographic data, medical history, allergies, laboratory results and more, with the end of knowing the bottom of the patient and offering a better service, providing processes as:
- Personalization of medical care : aligning treatments and services according to the individual needs of each patient, improving the accuracy of diagnoses and treatments and providing a more personalized and satisfactory experience for patients.
- Better access to health information : storing and sharing information securely, which allows health professionals to access relevant patient data in real time.
- Remote monitoring and continuous care : this allows continuous monitoring of the patient's health status, where doctors can receive alerts and notifications in real time about changes in vital signs, measurements and other relevant data.
- Feedback and improved quality : helping medical care providers understand better patient needs and expectations, identify areas of improvement and take measures to provide better quality care.
- Prediction and prevention of illnesses : Big Data can identify patterns, trends and risk factors related to illnesses, allowing the prediction and early prevention of illnesses, as well as the implementation of preventive interventions and health promotion programs.Therefore, it is possible to guarantee the correct application of patient care protocols , guaranteeing their health and well-being.
Genomic data analysis
Genomic data analysis is another important area in improving patient care and user experience through the use of Big Data, facilitating processes such as:
- Precision medicine : large-scale genomic data analysis provides valuable information about the genetic characteristics of patients.This allows for precision medicine, where treatments and medications are specifically tailored to each individual’s genetic predisposition.
- Early detection of genetic diseases: Genetic information can provide information about genetic risk for certain inherited diseases. In this way, health care providers can intervene early and develop preventive measures to reduce or completely prevent the effects of the disease
- Better understanding of complex diseases: Massive genomic data analysis is helping researchers better understand the genetic mechanisms involved in these diseases, potentially leading to new, more effective diagnostic and therapeutic approaches
- Research and drug development: By better understanding patients’ genetic profiles and responses to drugs, researchers can identify specific therapeutic approaches and develop effective and personalized drugs.
- Genetic counseling and informed decision making: Patients can receive guidance on the genetic predisposition to certain diseases, enabling them to make informed decisions about their lifestyle, treatment options and preventive measures
All these factors contribute to the construction of the patient's genomic profile, preventing possible illnesses and applying treatments to prevent the appearance of health conditions.
Epidemiological analysis
Another relevant aspect of custom business software development such as Big Data applications in improving patient care and user experience is epidemiological analysis. Next, details on how they relate:
- Disease surveillance and tracking: By collecting and analyzing large amounts of epidemiological data, such as news reports, public health records and survey data, it helps identify surveillance agents and trends in the spread of the disease, which can contribute to the implementation of effective disease prevention and control strategies.
- Identification of risk factors and determinants of health: When studying demographic, socioeconomic, environmental and health factors, relationships and factors can be identified that contribute to understanding the causes and factors contributing to populations some health well understood
- Evaluating health interventions and policies : when processing health data and results of interventions, we can evaluate the impacts of implemented actions and make adjustments based on the results. This, in turn, improves decision-making in public health policy and helps to ensure efficient allocation of resources to achieve positive outcomes in public health
- These enterprise solutions development can prevent outbreaks and reduce the chances of another pandemic or epidemic like the last one that affected global health.
