There is power in knowledge and knowledge in data. This makes data powerful.. Insights affect the quality, safety, and efficiency of care delivery. Improved data processes in care enhance insights. These insights directly measure how impactful care is delivered. Data and care are interconnected, from diagnosis and data-driven decision-making at the point of care to giving clinicians a more comprehensive view of patient health.
Enriched data for hospital systems also play a role in hospital efficiencies. Data strengthens metrics used to measure operational efficiency and highlight areas for improvement. Aside from showcasing operational metrics, it can also help accurately forecast resource needs. These needs reflect the best care for the patients coming in and the communities it serves. Speaking of community, the infrastructure for collecting and analyzing social needs data is crucial in population health to segment a patient's health-related needs. As a result, the more efficient hospital system operations are, the more cost-efficient they will be.Â
With the current state of healthcare, there are a few bottlenecks in data processes. One of these is how data is stored. Data is originated and stored in numerous locations across numerous care facilities. This disbursement is met with the complexity of non-standardized, complex healthcare system workflows that can delay transfer of data. Data being recorded manually may result in inaccurate data due to rushed note taking or being misplaced. There’s also the current staffing shortage, where healthcare workers are already spread thin and supplemented with transient workers.Â
From input to transfer and aggregation to contextualization, data processing is met with many challenges and bottlenecks affecting its quality and efficiency, ultimately impacting the quality and safety of care delivery. Many of these challenges can be solved through tech enablement in data processes to streamline and standardize workflows.
Maximizing nurses and clinicians time caring for patients is an integral focus of digital innovations in care. Improving data captured across the system of care improves accuracy. Improved access to data enhances timeliness of collection and transfer. These improvements impact care delivery and diagnosis. Predictive analytics utilizing new data technologies like AI and ML, help sift through large amounts of data to catch diagnosis sooner and provide more accurate diagnosis and treatment options. Previously AI has been used to help patients who were slim on options. Last September, a child was diagnosed with the help of ChatGPT,this shows the potential AI has in saving lives when integrating with healthcare data.
When data recording is more efficient, health care providers are able to use the time spent with patients more effectively; by spending time talking to the patient rather than typing on a computer. One potential of utilizing emerging technologies, like generative AI, in data processes, is to surface alarming trends in a patient’s health data that would typically have gone unnoticed or taken longer for a care provider to notice on their own. These technologies can then assist in diagnosis and treatment by autonomously comparing patient data to potential causes and remedies.Â
In addition to patient insights at the point of care, enhanced data supports other areas of hospital systems. The more accurately data is collected, the more accurate decision making will be. Operationally, data can highlight areas for improvement through precise growth, quality, and cost metrics.
One of which is scheduling. Inefficient scheduling tools mixed with a workforce shortage are a recipe for bottlenecks. Improved scheduling data can help forecast potential demand to prevent waiting rooms from filling up due to insufficient nursing staff or overwhelmed and burnt out nurses due to being overbooked.
Another area of data that makes a considerable impact is population health. A key reason for population health data is to understand how to deploy resources most effectively based on the health needs of the community served. To understand a population, it’s essential to comprehend geographically where health-related needs exist, what those health-related needs are, and what’s hindering those needs from being met. Population health data is typically gathered from numerous input sources, creating variance that impacts care.Â
Through enhancing current digital tools and products, hospital systems can improve data activities in related workflows. This is done by minimizing the number of touchpoints and applications used across the care continuum. Custom solutions provide the ability to simplify and standardize healthcare system workflows to their specific hospital processes. Automation and AI are emerging to be pivotal players in this process.
The true advantages of enhanced data lie in improved data-driven decision making. Timeliness and accuracy is key in capturing health data to efficiently and effectively diagnose and treat patients. There’s also operational advantages to having efficient data processes ensuring more efficient care. Exploring custom solutions that leverage new technologies improves the data that directs how hospital systems run and ultimately how care is delivered.
