The advent of cloud-based technologies and data analytics has transfigured the way healthcare was functioned back then. It has repositioned healthcare to a more feasible and efficient state for everyone.
Analytics followed by cloud-based technologies joined their hands with the modern data-centric solutions to tweak healthcare more result-oriented.
The big-fat cloud infrastructure facilitators such as IBM and Google Cloud are helping to tweak healthcare practices promisingly. By providing resilient technology infrastructure, these cloud environments are acting as the growth machines for healthcare practices progressively.
A survey held by IBM figured out that over 70% of the organization, including healthcare institutions, are finding that advanced IT infrastructures are helping them to gain strategical and operational efficiency.
These tech-platforms help to gather all sorts of healthcare data, including patient and hospital, and make way for innovative healthcare solutions. Plus, it enabled to formulate innovative value-based-payment systems and deliver hospital services to the patient locations via patient collaboration solutions (PCS). For example, patient treatment and follow up visits could be made ease with these systems.
Leveraging the healthcare information exchange technology, analytics has enabled healthcare systems to measure the quality of treatment, reduce the cost of healthcare, and fuel up the speed of diagnosis.
However, with the emergence of new advancements in information sharing technology analytics can pour out more over healthcare practice.
Let us check how healthcare analytics can improve the healthcare system:
Performance of medical practice:
Data-driven medical practice is leaping its prominence across the globe. The detailed and refined medical data sheds useful insights for enhanced diagnosis and treatment. Integrating the health data, demographic data, and medical reports of patients, data analytics is helping to filter the useful and redundant data in medical practice.
To illustrate, Practice Fusion (a healthcare software company) offers patient medical record management and appointment scheduling. This San Francisco based company is an obvious example to explain how cloud and analytics tweak the healthcare system.
The errors occurring during manual data processing in medical practice were cured with the intervention of the real-time data analytics process. Further, by moving healthcare practice into an incorporated data channel assures an error-free healthcare environment.
Moreover, health data analytics enable hospitals to evaluate the quality of healthcare practice delivery. Thereby the patient's experience and value of treatment can be improved drastically. Subsequently, with the gathered medical data, medical practitioners can analyze similar cases to predict the future health status of the disease, and they can act early to prevent epidemics and their impact in the future.
Healthcare Data security:
Patient health data seems to be the most sensitive and confidential. Any compromise on patient data results in colossal liability to the hospitals. The regulatory boards such as HIPPA put forward and consistently assessing the security of patient data through all mediums.
However, cloud solutions have made such a drastic change across the management of healthcare data.
"Cloud-based solutions have matured to a point where they are more secure than local server solutions alone," said Hector Rodriguez, Microsoft's Worldwide Health chief information security officer.
Today, cloud storage solutions are more secure and feasible than on-premise servers. Because the cloud environment provides more security and accessibility to data than the other solutions. Even if you have an in-house IT service team or you hire a managed IT service provider, to fence your data server infrastructure, data can’t be more secure than in a cloud space.
Marty Puranik (Atlantic.Net founder and CEO) says cloud solutions seem to be more secure than the on-premise /closet-IT solutions. In fact, larger cloud environments get more attention and updated with the latest patches and security measures.
Reduce treatment expense:
The immediate reason for the hefty treatment expenses is- the complex procedures to diagnose the patient to determine the disease. The prolonged treatment period and hospitalization also become a determinant in deciding the expenditure involved in treatment. Sadly, many of the times, this long-duration devour the health of patients worse as well.
Data analytics and cloud systems mitigate all these challenges by delivering an accurate account of relevant data of patients. This made the pace of diagnosis and treatment faster to save both the life and money of the people.
Physicians could gather the history of patient health and diagnose the disease at its early stage to start the treatments. Further, big data help to peer through similar patient cases to arrive at a precise decision.
Hence, as the time to diagnosis and treatment grow shorter, the expense involved in diagnosis and treatment get reduced immensely.
Further, the provision of preventive care and telemedicine helps a huge number of patients to reduce frequent hospital visits and hospitalization.
Empowering population health:
Population health refers to the management of health practice over a large mass of people in a specific social, economic, or geographical zone.
Amassing the health informatics of a population is no less than a hectic task. The necessarily disparate health data of a mass of people in a social or geographical context has been streamlined by data analytics. Hence it enables us to format the data into useful insights for formulating a collective health informatics archive. This collective health data can be used to evaluate the health status of a population and the trends of health conditions across geography.
Data analytics have helped healthcare sector to gain:
- Direct insights into the clinical matrix of a group of people.
- Outsight of global health impact by climate change.
- Detailed health history of patients from diverse geographies.
- Socioeconomic data of patients for better health management programs.
- In-depth health informatics data collection model for enhanced medication practice.
- Collective data resource for policymakers and healthcare professionals.
As prevention is always better than cure, healthcare data analytics have a profound role in preventing diseases from growing up and spreading out. The provision of predictive analysis is a promising tool to figure out diseases in its early stages.
Investigating the likelihood of current health condition in the future is what predictive analytics in health care. Analyzing the health history of patients with the archived data of the same and different conditions, this mode of analytics helps to predict the possibilities of the future of any health condition quicker.
Rather than putting efforts alone to resolve the existing conditions, predictive analytics helps to care for possible future events. Thus, this mode of analytics helps medical practitioners, analysts, and administrative persons to make informed choices for effective decisions. Thereby, according to the expected risk factor that a patient may confront in future appropriate treatments can be decided.
- Deliver prospective insight for further treatments.
- Due decision in accordance with the risk factor of disease.
- Unplanned hospitalization has reduced drastically.
- Need-based value medical treatment practice.
- Prevent unwise decisions of patients by proper medication.
The ultimate prospects of cloud computing and data analytics in healthcare are not limited to these features. As the technology is leaping to new heights, the utilization of data and its scopes are growing higher. In the movement to improve healthcare for everyone, data analytics, and cloud solutions are serving as a valued partner to healthcare technology.#News-BA#News-BA-home#pa-home#PlanningAnalyticswithWatson#PlanningAnalyticsWorkspace