While remaining data-driven, health-centric, and complying with regulations, how do you store patient data and use this data? Digital transformation in healthcare organizations recognizes the importance of patient-generated data and the opportunities to store patient data.
It contributes to discovering new information on the causes of disease and illness. In addition, researchers have more chances thanks to advances in information technology and the adoption of electronic medical records.
What is patient data?
Patient data refers to medical information regarding a specific patient. For example, information about a patient’s past and current health or sickness, treatment history, lifestyle choices, and genetic data are all examples of patient data.
Biometric data, any measurable physical trait that a machine or computer can check, may also be included.
Individual medical records contain patient data, which may be accessed by health care professionals in a variety of locations. It also included a patient’s surgery and their local hospital.
The data is utilized to help make decisions about that person’s care and treatment. This type of patient data is also used in research to identify effective treatments and monitor drug safety.
Why is patient data collection important in healthcare?
Like that of any other industry, customers’ data provides insights into how to make better business decisions. As a result, patient-generated health data collection and analysis are important in healthcare and medical services.
It enables clinicians to remain on top of a patient’s health changes and recommend treatment options to improve the patient’s outcome.
It also allows for optimizing in-hospital business procedures, lowering operational expenses, and enhancing medical staff efficiency. intelyConnect is a healthcare integration tool that brings all the essential data in one place.
How to store patient data?
There are two ways to store patient data.
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On-premise:
The most obvious method is to store data on your premises. It provides complete data access, storage, and security control.
However, unlike the second alternative, storing health data in the cloud, on-premise storage has higher operational expenses and fewer scaling choices.
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Cloud storage:
It’s a more advanced, adaptable, and cost-effective way to keep track of medical information. In addition, a business can pick from a variety of cloud settings, including private and hybrid cloud environments.
Healthcare organizations serious about digital transformation usually opt for a multi-cloud strategy. Because of the physical proximity of a data center, it is a distributed cloud system that allows for faster data transport.
The most innovative patient data storage option is a multi-cloud. It enables instant data transfer, better bandwidth, and instant decision making when used with edge computing, which is critical in remote surgery.
Challenges of patient data storage:
Patient data management can be difficult regardless of your healthcare facility’s storage solution. The biggest hazards to avoid are listed below.
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Unclassified information:
Patient data is generated by various technologies, including MRI scanners and smartwatches. This generation necessitates the organization and classification of data in a patient data vault to provide a complete picture of a patient’s health.
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Data integration from different sources:
Healthcare data collecting necessitates the collection of data from a variety of sources. For example, medical institutions, wearable devices, third-party laboratories, and other entities frequently generate health data arrays.
There is a need for smooth and secure interfaces between the patient database and the data source to get a complete picture of a patient’s health. intely provides workflow automation for healthcare interoperability.
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Updates to the data:
Patient data should be updated as fast as feasible, in addition to seamless integrations, because it can influence medical decisions.
How to use patient data?
The most successful strategies to use patient-level data are listed below. Each healthcare institution should select the use case to benefit both the business and the greatest patient experience.
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Medical research:
One of the best use cases for medical science and pharmacology is the collection of patient data for anonymous and ethical medical research. It enables scientists and practitioners to put their theories to the test and back them up with patient-generated data.
It helps to reveal trends, prove their recommendations, and provide better solutions for health improvement, support, and illness prevention.
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Internal business process optimization:
By analyzing patient data, healthcare organizations can improve their day-to-day operations and keep track of vacant beds at a hospital.
For example, it might assist doctors in prioritizing patients and making the best judgments possible in emergencies.
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Remote patient monitoring:
Smart medical gadgets are utilized for various purposes, including post-surgical recovery, blood pressure, glucose monitoring, mental health changes, etc.
Doctors can use the data arrays generated for greater control and faster response while remotely providing advanced and data-driven medical treatment.
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Predictive and automated scheduling:
This patient data use case streamlines the process of arranging doctor visits, saving time and money.
For example, a system powered by artificial intelligence (AI) may suggest a timeframe for the next appointment after evaluating patient data and sending a notification to a patient’s mobile app, keeping the user interested.
It can use patient feedback and survey data to improve the clinic’s customer service to balance healthcare quality, safety, and consumer experience.
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Risk forecasting:
When intelligent data analysis technologies augment health data storage, medical practitioners can better predict clinical outcomes and patient-specific hazards. Artificial intelligence systems,
For example, doctors can estimate the likelihood of age-related illness development based on a patient’s medical data to build preventative healthcare plans.
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Data-driven treatment strategies:
Doctors can get a complete picture of a patient’s health by analyzing data from different sources. Then, they can build and advise patient-specific treatment programs using artificial intelligence while also comprehending risks and potential problems.
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Best practices for storing and using patient data include:
Legal and ethical standards govern the gathering and use of patient data. The best methods for ensuring compliance, successfully using patient data, and protecting it from unauthorized use are outlined below.
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Maintain HIPAA compliance:
The health insurance portability and accountability act (HIPAA) is a set of guidelines for collecting, managing, storing, protecting, and using healthcare data.
It is the most important legal problem since it outlines both the technological standards for handling patient data and best practices for doctors and other staff who have access to it.
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Limit patient data access:
One of the HIPAA security rule’s recommendations is that patient data access be restricted based on the user category accessing it. In addition, the data itself should be encrypted, and workers should access it via unique identities.
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Regulate medical professionals’ use of personal mobile devices:
While many medical professionals utilize personal mobile devices for work, there is a need for clear privacy and security regulation on how they can do so.
Educating doctors on patient data security recommendations, securing their devices with strong passwords, and forbidding the use of public networks to access medical data.
It provides a list of apps they can install on their work smartphones are some of the most basic procedures.
Conclusion:
Using patient data in healthcare can improve the quality of medical services provided while streamlining commercial procedures inside a medical facility.
intelyConnect has extensive experience developing tech solutions for patient data collecting, management, and analysis and connecting them with current software.
It also assists healthcare organizations in making the transition to digital transformation.
