18 Jun Leveraging Data to Improve the Quality of Patient Care
Data is the asset that needs ongoing optimization. Especially so in the healthcare service space. Care delivery organizationsare no longer constrained by a shortage of data for quality patient care. In fact, there is so much data available with healthcare organizations today, that managing and leveraging this data to its full potential has become a challenge.
Natural Language Processing, an element of Artificial Intelligence, is helping care services providers to analyze and use a host of data that lies in repositories. This is information collected from disparate sources such as patient portals, EHRs, EMRs, and so on.
Healthcare analytics, that leverages all this data, promises to reduce the cost of care, improve outcomes, and enhance the patient experience.
These factors come together up to improve the overall quality of patient care- a tremendous opportunity for healthcare organizations to retain patients and gain a competitive edge.
Health Care Services Shift from Volume Care to Value-based Care
For so long, the healthcare service industry has been less than engagedwith its customers- the patients. But times are changing rapidly. Healthcare organizations now realize they have to deliver better outcomes to stay in business.
We are witnessing a dynamic shift from the traditional fee-for-service model to value and outcome-based healthcare delivery.
Value-based healthcare services requires practitioners to implement healthcare analytics at the point of delivery to evaluate the performance and effectiveness of care. With performance assessments and health data related to patient recovery, analytics can be used to provide ongoing feedback to care practitioners.
How Data Propels Quality Patient Care
Here are a few simple and subtle applications of analytics in advancing the quality of care delivery-
- Patient Predictions for Improved Staffing – A Forbes article details how four hospitals are using data from a variety of sources to predict patient influx and then optimize staffing. One of the key datasets these hospitals use is a decade’s data on hospital admissions. Optimum staffing is the backbone of care quality in healthcare organizations. If you put too many workers, you increase unnecessary costs. Too few workers can mean poor service delivery.
- Electronic Health Records – The most popular application of Big Data in healthcare is the use of EHRs. These portals capture patient data in the form of their medical history, demographics, allergies, and so on. EHRs streamline the initial discovery process for healthcare organizations by making all of a patient’s health background available to doctors and specialists at a glance. Subsequently, this data is utilized to predict patient health, plan care delivery, and optimize outcomes.
- Strategic Care Planning – Healthcare data can also allow physicians insights into what motivates patients to complete their treatment. Care managers can analyze people in different demographics and learn what motivates them to stay healthy. By using these motivators for each patient, care practitioners can enhance outcomes and carry out strategic care planning.
- Predictive Analytics in Healthcare – Healthcare business intelligence can allow physicians to use data and analytics to drive intelligent decision-making that delivers better patient care. This is particularly useful in cases of complex medical histories or multiple conditions. New tools would predict if patients are prone to diabetes or heart illnesses and help practitioners weigh those factors into their decisions. This ultimately improves the quality of care delivery ad accelerates outcomes.
- Coordinated Care – Care coordination allows integrated team members to track patient’s significant events, care activities, and appointments. After analyzing patient data, care providers can create a personalized experience for each patient- taking into account their sleep times, diet, activities, and other factors. Patient interactions can be recorded for future use and physicians can create a customized care plan with the patient’s healthcare outcome and goal in mind.
- Reduced Care Costs – Outcome and value-based care incentivize delivering performance in healthcare. Instead of focusing on the reimbursement on a case-by-case basis, overall outcomes determine costs. Interconnected EHRs can provide detailed information to help cut costs by reducing redundant or unnecessary care. By identifying patterns in a population, prescriptive analytics can estimate the cost of care for an individual- allowing organizations to direct care delivery to reduce waste and improve care efficiency.
- Fewer ER Visits and Shorter Length of Stay – One of the chronic issues in healthcare is the crowding of emergency rooms- which often leads to fatal conditions for patients waiting for their turn. With analytics and insights into patient health history, doctors can instantly learn if a patient underwent certain tests recently, what advice they were given the last time, if they already have access to a care manager at another facility, and so on. By optimizing the influx of patients at ERs, the quality of care can drastically improve.
The application of Big Data and Analytics in healthcare could open avenues to dramatically improve the patient experience, the quality of care, and patient satisfaction.
Stay Relevant, Deliver Outcomes
With an aging population, there is an increasing demand for expensive, critical care. But this is also transforming how healthcare companies operate.
Healthcare services is movingtowards an outcome-based model. Organizations are now expected to be transparent and accountable. All of that plays a role in the need for improved efficiency in care delivery. And, data and analytics have an important seat at the table here.
Healthcare service organizations have made tremendous investments in infrastructure. The time now is to cash in and focus on improving care. The key here is to use the assets currently available. One of which is the data available with the industry- thanks to EHRs, integrated care portals, and data captured at the point of delivery.
To do this, providers will have to make excellent operational decisions by leveraging predictive analytics. They will need to deliver prescriptive recommendations throughout the system to clinical and administrative drivers. In this digital age, where customer know exactly what they want and are ready to demandjust that, what other option do healthcare organizations have than to deliver improved care quality?