Assisted living caregiver
In multicultural cities around the world, the requirement for an army of care workers to look after the needs of seniors and those living with long-term health conditions grows year on year.
According to the most recent data, 16% of the U.S. population is over 65, while the figure is closer to 20% in the United Kingdom.
Whilst Covid-19 exposed the inherent frailties at the heart of the social care system and the long-term isolation faced by many it serves – conversations around reform of the care sector too often simply focus on having sufficient boots on the ground, rather than the nature and quality of the care itself.
A vital part of this is ensuring that carers have a solid grasp of the cultural background of the individuals in their charge and how this might impact aspects like language, diet, personal grooming and social attitudes.
Though there is a growing recognition of the benefits to patient outcomes of domiciliary staff and health workers possessing “cultural competence” – there has, to date, existed far less certainty about how to embed it.
The perfect match
There may still be a long road ahead but all this may be about to change with the entry into the market earlier this year of Care Algo (formerly known as Care Matched) – a technology PAS (Platform as a Service) that seeks to assist care agencies and councils match care workers and recipients based on cultural competence amongst other metrics.
Predominantly serving the BAME community in London since its launch in January – Care Algo is the brainchild of young social entrepreneur and founder Maaha Suleiman.
From a Somali background with a bachelor’s in Global Health and Social Medicine from Kings College London and growing up as a tech-focused millennial in Tower Hamlets – one of the most deprived and ethnically diverse boroughs in the capital – Suleiman already possessed a solid overview of the care sector.
However, the real clincher that helped point her in the direction of what was missing in mainstream care services was her mother’s experiences working in the borough as a domiciliary care worker.
“When my mum got home from work, she'd always receive calls from the agency asking her if she spoke this language or that language and that got me intrigued because I figured there must be an easier, more efficient way of matching people,” says Suleiman.
“The next thing I did was to call 35 care agencies in Towe Hamlets and ask them if they ever received requests for culturally appropriate care and the feedback I got was that it happens all the time.”
Given her mother’s experiences, she was hardly surprised by this admission but the real shock came when she asked the agencies about how they delivered on this requirement.
“If they had a request for a care worker that speaks Tamil and could cook vegetarian Indian food, they would just take a look at their spreadsheet with the names of their care workers and call up whoever had an Indian-sounding name. This is problematic, to say the least, let alone inefficient and racist,” she adds.
Buoyed by encouragement from industry leaders that the sector was indeed crying out for a technological solution that could suitably match and allocate culturally appropriate care, Suleiman saw her idea take a runner-up place at the prestigious 2019 Care Innovation Challenge with the finals held in the offices at the Department of Health and Social Care.
During the long hard months of uncertainty that characterized the early days of the Covid-19 pandemic, when the care sector found itself firmly in the media glare, she set about making her idea a reality.
Care Algo received a cash injection from PPI Tech Investments to build the technology stack, while Suleiman ensured she regularly consulted with leading industry stakeholders including the Care Quality Commission (CQC), Skills for Care and Care Innovation Hub.
Skilling up
The web portal and app launched in January 2022 and works like any traditional matchmaking tool – with both care receivers and givers filling out their requirements and qualifications respectively and the matching algorithm performing its magic in the background.
Care Algo doesn’t just focus on language and culture and matches on other core competencies including medical experience like being a dementia specialist nurse.
As far as the cultural components are concerned, the carer profiles go well beyond language to encompass more culturally subtle but equally important elements like religious understanding, food preparation, hair and grooming and appreciation of special holidays like Eid, Diwali, Christmas and Hanukkah.
Crucially, the platform is nothing like as simplistic or trivial as matching individuals based purely on language and ethnicity.
For a start, carers have to complete a cultural questionnaire and undertake training within the platform - requiring a high test score to attain full accreditation in being culturally competent to care for a certain group.
The beauty is, of course, that any carer from any background can take these tests and get accredited as the ultimate aim is, as Suleiman explains, not to match on ethnicity but purely on knowledge and competence.
“We get a lot of questions about whether we match people based on race but, for us, it’s just about inclusivity and the caregiver having a better understanding of an individual’s religion while also improving their career opportunities,” says Suleiman.
She explains that there are huge practical upsides for the sector too:
“It helps the care agencies because they always have way more demand for care than they do care workers. So, if they had 10 Muslim care receivers but only three Muslim caregivers to care for them, then they'd ideally want access to more staff that are willing to learn about that culture.”
Ultimately, the human relationships blending care and cultural understanding are amongst the most complex out there but the beauty of this technology that can enable its practical application lies in its simplicity.
This should help ensure its future scalability and scope to go beyond just religion and culture and potentially assist other diversity segments in attaining the personalized compassionate care every human being deserves.
