For healthcare providers, having a diverse workforce is paramount to quality of care. The communities they serve contain patients from a wide array of backgrounds, races, and socioeconomic classes. Without shared similarities and cultural values among them, it’s difficult for medical professionals to establish the strong patient relationships that are needed for effective care.
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From building trust and enhancing communication to reducing health disparities and driving collaborative innovation, the benefits of inclusivity and equal representation in healthcare extend far and wide. However, large diversity gaps still exist today within the U.S. healthcare sector. Approximately 64% of physicians are white, while those who identify as Hispanic and African American only represent a combined 11% of physicians despite accounting for 33% of American citizens. And while a majority of nurse practitioners, physical therapists, and occupational therapists are women, only 25% of them identify as non-white.
With the diversity of the U.S. population steadily increasing by the year, there’s never been a greater need for healthcare recruiters to enhance their ability to search for and hire candidates from underrepresented groups.
Fostering Diversity Through Data Intelligence
Our current evolving era of digital transformation represents a clear opportunity for healthcare providers to part ways with traditional recruiting models that hinder equal representation in their workforce. By automating multichannel sourcing, recruiters can improve the efficiency of their DE&I screening capabilities with broadened search access to qualified minority candidates and a better understanding of the nuances associated with the talent they are looking for.
Through machine learning, AI solutions also generate actionable data insights that flag DE&I anomalies in their recruiting processes, such as the rates of candidate engagement by gender and ethnicity. After discovering any candidate search, engagement, or hiring anomalies associated with underrepresented groups, healthcare organizations can then take corrective action to develop better practices that promote a more level playing field.
Expanding Minority Candidate Reach
An AI talent sourcing engine enables healthcare recruiters to cast a wider net for discovering and engaging with candidates from underrepresented groups in real time to further diversify their recruiting funnels. It automates data aggregation from open web platforms and analyzes the data sets for keywords, schools, or professional organizations on candidate profiles so recruiters can implement searches tailored to underrepresented groups. A recent study by Hiretual found that 60% of talent acquisition professionals struggled to find enough underrepresented talent while 46% said the process of searching for those profiles was too time-consuming. Automated targeted searching streamlines the entire process so recruiters can reduce hours spent sourcing while eliminating generic searches that lack the flexibility to uncover these profiles.
Each individual organization has its own workplace equity gaps to fill. For example, one healthcare provider may have a diverse workforce but lack gender inclusivity, while another provider has a pressing demand for more bilingual caregivers. These AI filters can be tailored to their specific needs to identify the right DE&I candidates at the right times even when talent pools are limited. This technology does not aim to replace human judgment but instead takes on the role of processing and analyzing larger subsets of data that a team of recruiters would not have the time or bandwidth to search through. The results of these searches are then delivered to hiring teams for them to make the final call of moving forward with a profile that best matches what their organization is looking for.
Eliminating Unconscious Bias from Searching
Avoiding unconscious bias in recruiting has been an ongoing problem in the healthcare sector, where hiring managers are pressured to find top talent as quickly as possible within a limited pool to choose from.
It’s nearly impossible to eliminate all unconscious bias when you’re posting a job application and sifting through applications and résumés. However, if technology is approached with caution, hiring teams can make the most of features built to support visibility of underrepresented groups while mitigating tendencies to make decisions based on attributes such as names or physical appearance. Healthcare organizations with the goal of reducing biased screening decisions among their hiring team can opt for AI-powered recruitment technology that anonymizes and excludes candidate information historically vulnerable to bias. A recruiting approach built on more data-driven decision-making can help healthcare organizations minimize bias and, in turn, maximize their outreach to minority candidates.
Leveraging AI-powered sourcing can empower healthcare organizations to increase the rate of underrepresented groups in their workforce. Now is the time for traditional, human-created talent pools that put minorities, females, and veterans at a disadvantage to be left in the past in favor of data intelligence solutions that foster diversity.
Steven Jiang is CEO and co-founder of Hiretual.