Utilizing Big Data To Improve Patient Outcomes In Home Healthcare

By Author: Syntelli Solutions
Total Articles: 29
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Home Healthcare
Home healthcare is characterized by care providers tending to patient health at a home rather than a hospital or skilled nursing facility. The individualized patient care approaches illness or injury in an often less expensive, more comfortable, and longer-term way.

Although home healthcare usually refers to a single patient per location, standardized data collection should still be practiced to make data analysis and the consequent better-informed, value-based care possible.

Big Data in Healthcare
Large data sets can be leveraged with big data analytics to reveal trends, patterns, and correlations.

Big data is broadly used by businesses to target advertising dollars and inform marketing strategies, and medical data is used by many in the healthcare industry to improve health outcomes.

Clinical systems in healthcare are responsible for data management; health data is most often documented in the Electronic Health Record (EHR). When healthcare data is correctly standardized and stored, researchers can come to valuable insights and physicians can inform daily actions. ...
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Using Data to Determine Medical Best Practices
Its current uses among healthcare providers clearly demonstrate how AI transforms healthcare. Patient data can be standardized and aggregate to inform evidence-based treatment plans and preventative care using predictive analytics.

Specifically, clinical data is being collected from inhalers so machine learning can use patient experience to help physicians and patients better track and manage asthma.

Big Data in Home Healthcare
Algorithms can be created to mine clinical notes and patient health information for patterns in symptoms that might predict patient outcomes or developing ailments.

Already, big data helps tackle accidental death related to opioid use, an application especially important for a field that aims to allow more independence in injury and illness treatment.

Nursing analytics can also be used to create a clinical decision support tool for the caregivers of patients turning to home care. Predictive analytics could be used to identify high-risk patients who require immediate care based on clinical notes that home care nurses take.

Finally, machine learning may be able to find cures by leveraging existing data; by regressing patient outcomes with symptoms and treatments, physicians may be able to discover or pinpoint efficacious treatments.

Data Challenges in Healthcare
The healthcare industry has been slow to adapt to changing technology regarding data analytics. This is in part due to the inherent challenges associated with collecting and mining healthcare data.

Even when patient data is digitized, which hasn’t been widespread in hospitals until recently, the lack of standardization makes data mining a difficult process. This also contributes to the difficulty of aggregating data sets, as hospitals often have trouble sharing data sets that aren’t quite compatible.

However, there is reason to be optimistic about the near-future of nursing informatics, as EHR use caught on rapidly in hospitals once the benefits of big data in healthcare were made more readily apparent.

People commonly cite privacy and security concerns when discussing the downfall of big data in healthcare and they are often surprised to learn that big data can play an important role in reducing healthcare fraud and waste. Identifying outliers in the data can catch mistakes and fraud and end up saving insurers and patients money.

Existing and potential regulations surrounding healthcare data are often reason to pause when collecting and aggregating patient information. Syntelli Solutions provides data management support and security to keep your company on top of the regulations.

What Makes Good Data
Not all data can have equally effective applications. Health data is notoriously hard to collect, as many clinical notes rely on unmeasurable observations and hospital-specific scales. Promoting standardization of patient experience documentation, both within facilities and between hospitals, will likely improve the utility of the available data.

Terminology is another aspect of clinical notes that must be standardized to create useful datasets. Going forward, nurses should be taught to document standard terms that fit each observation.

Standardization provides an additional challenge with home healthcare professionals, as these physicians and nurses tend to be relatively independent of the rest of the healthcare industry. However, this is an obstacle that can be surmounted to allow for better leveraging of AI in healthcare.

Keep in mind that data is only as good as the data analytics. Big data can be misleading if improperly interpreted, so it’s important to seek professional help when analyzing your data. Ideally, look for an expert trained in data analytics for the healthcare field; an informatics nurse or data company that works with healthcare data, like Syntelli Solutions, can help you make the most of your data.

About Syntelli Solutions
Syntelli Solutions can help your home healthcare business extract knowledge and insights from data to improve patient outcomes and economize your practice. We employ predictive analytics using machine learning to help clients predict patient behavior and ideal treatments and engagement strategies.

Syntelli Solutions can help you every step of the way; our data engineering services can help you organize and protect your data, and then our reporting and visualization services can help you come to data-driven decisions.

The Takeaway
Big data is not only accessible to big companies. With the support of Syntelli Solutions, you can leverage big data to improve patient outcomes and your bottom line in your home healthcare business.

The healthcare industry has begun to follow the footsteps of the commercial sector, but home healthcare services are largely missing out on the opportunities that data-driven approaches to healthcare can provide.

Take the next step toward bringing your home healthcare practice into the future: contact us to learn more. Ask us how we can help you unlock the value in your data.