We live in an age where data is used to drive business decisions. Every company has access to massive amounts of data about their customers, but successful businesses are able to turn that data into actionable intelligence to develop better and more optimized business processes. The healthcare industry is no different. In fact, the growth rate of healthcare data is projected to be greater than that of the total global data set. At 153 exabytes back in 2013, the healthcare industry is expected to generate 2,314 exabytes of data by 2020, a 48% annual growth rate.
In addition to the massive volumes of data created by the healthcare system, user-shared data is also on the rise and is expected to make up a quarter of the data used for healthcare by 2020. In addition, socioeconomic data and other information across the public domain can provide valuable insight into trends and patterns associated with patient conditions and treatment. The key, however, is in how healthcare providers use the data to deliver better and more efficient patient care and results.
Consistency of Care
This is perhaps the easiest use of patient information, allowing different doctors, nurses, and other staff to view patient histories to ensure they are delivering consistent care, or are able to modify treatment to generate more positive outcomes if initial treatment plans aren’t having the desired effect. On a broader scale, the aggregation of patient data can help identify best practices for specific conditions, driving standardization of treatment and consistency of care as well as results.
A constant flow of data from sensors monitoring and recording a variety of vital statistics can help providers tailor care based in individual patient needs, circumstances, and results. Connected healthcare devices deliver data that can be used to create more effective treatment plans while recognizing patterns or elevated conditions sooner, allowing faster recognition of changes in condition and adjustment of treatments. Both inpatient and outpatient scenarios benefit from the real-time flow of data that can be set with patient-specific thresholds to alert caregivers of changes, allowing them to attend to more patients while still delivering better and more efficient care for each. From heart rates to pain thresholds, to exercise and eating habits, every piece of data, including social and other non-clinical information can help formulate the most effective personalized treatment plans.
While a large part of data and analytics can directly impact patient care, healthcare systems also have an opportunity to use data to increase their own operational efficiency, which also impacts patients. By understanding how staff and equipment are being used, in conjunction with patient information, systems can identify opportunities for operational improvements, including automation, better use of existing resources, and ways to leverage new capabilities like connected healthcare systems to deliver better outcomes to more patients. This includes automated data collection, rather than manual measurement and recording of information into records. The combination of process efficiency, standardization, and connected healthcare usage opens the door to cost savings as well as the ability to treat more patients – both represent a financial gain for providers and a way to address the current physician shortage.
Simply having data available allows physicians to measure conditions and outcomes on a more regular basis. But, it doesn’t have to place additional burden on doctors. Rather, connected healthcare enables measurement and data collection remotely – whether that’s automated thanks to wearable and connected devices and apps, or through manual entry into patient portals or apps – and the sharing of information between doctors and patients. The byproduct of available data from connected healthcare, combined with an increasing percentage of digital natives in patient populations, is greater engagement and health-consciousness from patients.
Improved Population Health
Aggregate data can help providers identify trends and risk indicators across population groups by analyzing common traits across anonymized data sets. By understanding correlations between holistic patient data and various conditions, physicians can better predict at-risk patients, who can then be treated sooner, even potentially avoiding some conditions altogether. In addition, patient data can create a better understanding of the most effective treatments for different diagnoses based not only on condition, but other patient characteristics that could impact outcomes, allowing healthcare systems to create standards for better care.
Current data models are only scratching the surface of what’s possible with patient data, particularly when combined with other available data sources to create holistic views of patients and population groups. But, coupled with physicians’ knowledge, healthcare and socioeconomic data can identify previously unknown correlations between patient or population characteristics and health conditions, increasing providers’ ability to diagnose and deliver better outcomes.
To find out more about how connected health solutions can help drive data-driven outcomes for your organization, visit here.