The pandemic is not just hurting people, it’s hurting the entire healthcare industry. The Covid-19 outbreak has severely impacted the system, exposing several vulnerabilities that need urgent patching.according to State of the U.S. Health System Reporthealth care disparities related to specific population groups, lack of key data on social determinants, delayed care and other issues have become more vivid recently.
So how do we solve this situation? Effectively addressing these challenges requires an integrated approach that requires specific efforts by policymakers, industry experts, and healthcare providers.
Suppliers’ commitment to addressing the global crisis
On the supplier side, there is a lot of targeted effort for differentiation. This is where health data analytics can come into play, helping and simplifying the collection of massive amounts of social determinants of health (SDOH) and other data, properly processing it, and visualizing the results.
To assess the status of vulnerable patient populations in their clinics, providers need to collect data on SDOH and its impact on different high-risk population groups. To understand why care is delayed in their organization, providers can use data analytics tools to measure the effectiveness of established workflows, personnel, and medical and educational activities running in the area. By examining the resulting insights, analysts can propose ways to reform existing processes and draft new targeted outreach programs to meet patient needs and improve health outcomes.
Let’s take a closer look at how health data analytics can help address all three major causes of health care disparities: lack or inappropriate use of SDOH, imbalances in services based on demographics, and delays in care.
Extract data from unstructured information
Manually extracting and organizing all patient health data from multiple sources is nearly impossible. Some parts are missing, duplicated, misplaced, or incorrectly placed. If we are talking about thousands of patients, the burden of this manual labor is onerous for medical staff. As a result, healthcare organizations’ systems lack vital information about patients’ health and living conditions.
Through machine learning (ML) algorithms, data extraction, and artificial intelligence (AI) training, analytics solutions can handle vast amounts of unstructured information: documents in different formats, even handwriting, medical images, conversation transcripts, and more. In this way, healthcare organizations will have access to accurate information that is already organized about their patients and will be able to use this information for their benefit.
Improve population health and prevent inequalities
After extracting data from different sources, including research databases and demographic sources, healthcare analytics software helps detect and report cohort patterns to assess the overall health of specific groups of patients who may live in specific regions and belong to vulnerable groups ethnicity, exercising a particular lifestyle, etc. Using predictive analytics, it is possible to predict the impact of lifestyle or living conditions on population health, set epidemiological alerts, improve educational campaigns, and take other actions to promote population health.
In addition to this, a whole set of challenges associated with vulnerable patient populations can be addressed. These challenges include insufficient transportation, necessities and income. Designing outreach technologies that address these challenges could have implications for any healthcare provider. For example, by applying data analytics to a patient’s SDOH, providers can find low-income patients and suggest where they can buy generic alternatives to expensive drugs.
Monitor organizational performance and enhance care
Medical analytics software made by Сustom allows real-time monitoring of operations, employee efficiency, facility performance, and more. It also helps find correlations between established workflows and patient health outcomes. As a result, organizations can redesign some processes, reallocate finance, resources, and personnel to more efficient locations, and upgrade medical services to meet current needs in specific areas. These actions can help overcome delays in care:
- make up for staff shortages By pointing out routines that can be automated, tasks that can be performed in a more efficient manner, and ways to reallocate workforces across an organization.
- Reduce stress for emergency room and hospital staff Prevent serious deterioration that requires an emergency room visit with early diagnosis and alerts of possible complications. The same is true of hospitalizations in general – with better preventive care, the number of hospitalized patients can be significantly reduced, which reduces wait times for those who require hospitalization and improves hospitalization.
- Get more financing By making operations more transparent and results more measurable. Investors are more willing to put their money toward clear goals, where people can understand why they succeed or fail. Analytics can visualize a healthcare organization’s financial and operational processes, making them easier to understand.
Real-world case: Reducing hospital stays with intelligent analytics
Amid the pandemic, a hospital in Pueblo, Colorado, had to partner with another local nursing facility. However, when the partners closed many of their units, the hospital had to take in large numbers of patients. However, most hospitalized patients were hospitalized for too long, which hindered hospitalization of new patients.
To address this challenge, hospitals are leveraging a new AI-driven tool that looks at unstructured data and identifies factors preventing patients from being discharged. The system then creates a discharge checklist for physicians that includes each patient’s barriers and helps clinicians address them.
The new tool has reduced hospital stays by 88 percent. At the same time, it has also helped them achieve some positive changes: hospitalized patients’ concerns began to be addressed more quickly, patient satisfaction and loyalty increased as they received more personalized pre-discharge care, hospitalizations occurred The faster the rate, the more patients can be admitted to the hospital.
add up
While the pandemic has not subsided, there are steps that can be taken to address critical system vulnerabilities and their adverse effects. In this context, “disaster recovery” needs to include an integrated approach, which means taking effective measures at the government and local levels.
The latter depends in particular on the provider and whether they take action to address the health disparities faced by patients. Collecting SDOH, adding this data to patient files, enabling health data analytics, and taking data-based actions has proven very helpful. Working together, government organizations, healthcare professionals and data analytics solution providers can help improve patient outcomes and population health locally and nationally.
Photo: goir, Getty Images
