Benefits of Big Data Analytics in Healthcare

Big data analytics in healthcare is rapidly evolving helping provide insights into very large data sets and improving outcomes while reducing costs. Not only does such analytics help predict diseases, but also improves care provided resulting in reduced suffering and saved lives.

One of the significant applications of big data analytics or predictive analytics is to prevent healthcare fraud, waste and abuse. Such analytics help identify, predict, and minimize fraud by implementing advanced analytic systems for fraud detection.Analyzing large numbers of claim requests rapidly is a crucial step to reduce fraud, waste and abuse.

Another crucial benefit of big data analytics is being able to identify and pin point high-risk patients. This helps ensure that the most effective intervention is applied to the specific patient – and that it’s provided at the appropriate time. Big data analytics also helps analyze disease patterns and record disease outbreaks in the populations. Such data can help deal with large populations where it becomes important to know who can potentially benefit from interventions as a way to improve community health and lower costs while saving lives.

Big Data in Healthcare – Reducing Health Care Costs

Health care providers face many obstacles while analyzing health care data and realizing the costs involved. Securing, sharing, and organizing sensitive data with the help of BI tools and data warehousing is key.

Health care data is diverse, disparate and distributed into hard-to-penetrate silos owned by a multitude of stakeholders. Each stakeholder has different interests and business incentives while still being closely intertwined.

Healthcare analytics connects the technologies to help deliver insights into the complex data and clinical mutuality that drive medical outcomes, costs, and oversight. These follow the disease models, which help the bridge the gap between researchers and clinicians resulting in better outcomes, saved lives and resources.

Fully integrated data is needed to harness ability to identify the area of waste and opportunities of healthcare cost reduction. Healthcare data warehousing is the best method to organize a health system’s financial, clinical, administrative and patient satisfaction information. Once the aggregation of all such data occurs in one place, it helps categorize and identify the sources of waste reducing the involved costs with improved outcomes. 

The Increased Dependence Of Big Data In Hospitals

The hospital big data contains billions of data points collected from different sources within the healthcare facility. These data files are too large, complex to capture, store and manage for any data tool. Big data applications are rapidly transforming the healthcare industry by quickly transforming loads of such disparate and unstructured data into instantly available and highly actionable information.This data improves population health management, care delivery, performance reporting, and resource utilization.

Big data software applications represent the single most effective solution to addressing the multitude of problems faced by healthcare facilities, including the reduction of avoidable hospital readmissions.

A ‘hospital readmission’ is admitting a patient to the hospital within 30 days of discharge from a prior hospitalization. With the help of big data, hospitals can track the patients who are at a high risk of readmissions. There are various reasons of unplanned readmission such as surgical wound infections.

Big data applications aid evidence-based medicine, which involve making use of all clinical data available to improve patient outcomes. This includes improved ability to detect and diagnose diseases in their early stages, before clinical signs are present. This patient level care helps save lives and reduce suffering along with waste of resources.

Healthcare organizations also need to be able to detect fraud based on analysis of irregularities in billing data or patient records. Big data applications can analyze patient records and billing to detect over utilization of resources and services in a hospital.

How Is Big Data Instrumental In Improving Healthcare?

Over the past one-decade or so, hospitals and healthcare centers have witnessed a huge amount of data generation. Big data is the intersection of these changes. In healthcare, it provides profits and reduction on waste overheads. It is benefiting the healthcare industry in multiple ways.

Barriers for using big data

The big data phenomenon has great value and is yet to face several challenges. Specifically, it has two major drawbacks in the healthcare field:

• Requirement of technical expertise
• Lack of robustness

Security of patient data

Security of every patient record or data is primary. Big data is not able to manage an integrated amount of data. For this reason, hospitals require data scientists to take some steps to confirm better security of data. Big data acts on an open source technology with non-compatible security technology. To avoid problems, organizations should select original big data vendors to implement.

Structure of healthcare and predictive analytics

Predictive analytics is one of the most discussed topics in healthcare today.Meaningful analysis of the data in healthcare can improve patient care and chronic disease management based on predictions. However, making predictions would be a waste of time if they do not get transformed into consequential actions.

Enterprise data warehouse is essential for the management of patient records and data. With EDW, systematic integration of data is made easy using the analytics approach.This step helps prioritize resources within the health system focusing on cost reduction and revenue enhancement while improving patient outcomes.

Healthcare Fraud Waste and Abuse- From Detection to Prevention

Big data is helping businesses save costs, gain a competitive advantage or identify new opportunities, and the healthcare industry is no different. Big data technologies help predict illnesses, save lives and improve the overall quality of life.  With modern predictive methodologies in place,chronic diseases and illness can be predicted before the manifestation of symptoms. This helps in early interventions resulting in saved costs, resources and lives.

Provider Fraud Waste and Abuse

Healthcare fraud, waste, and abuse means-

• Fraud- Intentional deception
• Abuse- improper billing
• Waste- carrying out unnecessary treatments

Such practices cause losses in the billions each day for the healthcare industry. Efficient and advanced IT solutions play a crucial role in reducing such waste. 

Risk Stratification Tools – A Helpful Approach To Assess Health Risks

Risk stratification is an estimate of the probability of a person suffering from a particular disease. It analyzes the benefits from a particular treatment a person is taking. The assessment helps providers and doctors analyze their patients and make informed and personalized treatment decisions. Care coordination is a key component of patient-centered medicine.

Risk Stratification Methods

Different methods are available for risk stratification. A Risk Stratified Model of Care includes following methods:

• Hierarchical Condition Categories (HCCs)
• Adjusted Clinical Groups (ACG)
• Elder Risk Assessment (ERA)
• Chronic Comorbidity Count (CCC)
• Minnesota Health Care Home Tiering (MN)
• Charlson Comorbidity Measure

Hospital Acquired Infection Prevention: Better Healthcare Delivery

A hospital acquired infection is an infection that is picked up from a healthcare facility. It can be spread within hospitals and other clinical settings. These infections are caused due to microorganisms, which originate from a hospital environment, staff or other patients. The most common infections are urinary tract, upper-respiratory infections (pneumonia), and surgical wound infections. Infections that become clinically visible after 48 hours of hospitalization are considered hospital-acquired.

Susceptibility to infections in a hospital:

Patientsin the hospital are often at the risk of suffering hospital acquired infections. The populations that are more susceptibleto such infections include:

• Premature babies and sick children
• Elderly and frail
• Patientswith chronic medical conditions (e.g. diabetes)
• Persons having compromised immunity 

Repercussions of hospital acquired infections:

Micro organisms including fungi and bacteria are among the major causes behind infections in a hospital setting that contribute to about 99,000 deaths each year.

Some of the consequences of to such infections include:

• Prolongedsuffering for the patient
• Longer hospital stays
• Longer recovery time
• Mounting costs associated with longer stay in hospital and prolonged recovery time

Causes of health acquired infections:

Infection is spread to the susceptible patient in the clinical setting in various ways such as:

-          Contact with healthcare providers

-          Contaminated equipment

-          Infected air droplets

-          Indwelling catheters

-          Infected food, water or medications

Measures to reduce hospital acquired infections:

The infection can be controlled by following the appropriate protocols as follows:

• Rigorous hospital infection control procedure and policies
• Frequent hand hygiene measure by all the hospital staff and patients
• Cautious use of antibiotic medication
• Use of Personal protective equipment
• Isolation of infectious patients