Post-acute care settings offer unique challenges for care providers. They must monitor and support patient recovery, with the goal of preventing hospital readmissions.
Predictive analytics in healthcare is a new solution made to help providers improve post-acute care. This advanced use of data allows care providers to anticipate their patients' future needs, so they can better plan care and monitoring.
Predictive analytics is the use of pooled data to anticipate trends and events. In healthcare, predictive analytics draws upon health data not only from the individual patient but also from patient populations as a whole.
Analyzing patient care trends can help post-acute care providers determine appropriate care levels for each patient and provide the support and monitoring necessary to minimize risks and enhance recovery outcomes.
There are numerous unknowns in patient care, but predictive analytics can help reduce providers' uncertainty when it comes to their patients' care plans. In a post-acute care setting, data can represent which patients might be more likely to have complications like falls or post-surgical infections. Understanding which health events a patient may experience enables providers to more effectively monitor their patients and form personalized therapy plans, ultimately improving care processes.
In post-acute care settings, patient readmissions to the hospital are common. While there are many reasons for readmission, among them are a decline in a patient's functional status and the need for intravenous medications. Health care providers are often able to reduce readmission rates by supporting patient recovery.
Predictive analytics can help providers identify which patients might need more support, and develop customized therapy plans to prevent health events before they occur. For example, if a provider is informed via predictive analytics that their patient is at an increased risk of falls, the provider can intervene with an occupational therapy regimen meant to improve movement and stability. Putting a proactive care plan in place based on predictive data can help improve post-acute care outcomes and reduce hospital readmission rates.
Data can also be an important tool to flag potential warning signs of an impending serious medical event. Care providers can use electronic documents to log eating and activity to note when a patient isn't meeting recovery goals. Early knowledge can lead to early intervention, thus giving the patient the opportunity to return to better health.
Care providers and administrators can use predictive analytics to improve care throughout the facility. By identifying individual patient needs, they can better allocate staff and equipment resources so that patients with higher needs can receive the greater attention they require.
Monitoring is also made simpler when data automatically highlights patients who need immediate action. Team members at all levels, from administrators to direct patient care providers, are better able to complete daily operational planning based on anticipated care demands.
Predictive data is a benefit for providers and organizations alike, but you need the right tools to gather and use that data. The best predictive tools ensure the accuracy of data input in order to maintain reliable predictions, reduce the risk of human error, and simplify healthcare process documentation. Solutions should also have a support network that helps organizations to train their care teams on predictive alerts and how to interpret them. In addition, these technology tools require robust security protocols with built in safeguards to protect patient information and comply with privacy regulations.
WorldView Healthcare Solutions has a suite of tools that incorporate data analysis to improve patient care and operational workflows and streamline healthcare document management. Referral AI is a healthcare AI tool that streamlines patient intake and referral, simplifying the upload of new patient information by eliminating the need for manual entry. The predictive insights on WorldView's tools allow providers to act quickly and efficiently based on the unique needs of each individual patient.
As significant as the current state of predictive tools in healthcare is, there are even more promising technologies on the horizon. Care providers should anticipate innovations that will expand the use of predictive tools, incorporating more real-time data and a broader range of health indicators. This can improve care coordination, as a patient's immediate needs will be more quickly understood and disseminated across a team network. As patient care improves, so does the ability to improve administrative care planning, which leads to more effective cost management within post-acute care organizations.
Predictive analytics is a valuable tool in the post-acute care environment. It can be incorporated into patient care settings to help providers make better care decisions, ultimately reducing the prevalence of complications, improving patient care and recovery, and making daily operations more manageable.
Learn how WorldView can help your team use predictive analytics to support patient recovery and reduce complications. Schedule a demo today to see it in action!