As we get further away from the Covid-19 pandemic of 2020, we are still feeling the repercussions four years later. As one of the hardest-hit sectors, it’s no surprise that one of the industries that is still struggling from that period of uncertainty is healthcare, with data from Gallup revealing that 52% of Americans find healthcare quality in the US “subpar”.
Through data collected by customer feedback terminals positioned in healthcare buildings around the U.S., we see patient feedback which shows that ‘wait time’ was the most common area of complaint in 2023. Other commonly complained about areas of the patient experience included:
staff professionalism
quality of care
food quality.
However, it is not enough to acknowledge that there is a problem with patient satisfaction levels in healthcare. Instead, providers need to incorporate methods of locating problems, and then solving them, in order to improve the patient experience. The question remains, how?
For healthcare service providers, thinking from the perspective of the organization and staff efficiency is a major priority. Therefore, implementing real-time feedback systems can provide the impetus for healthcare providers to get out of this rut of poor patient experience. They can be an invaluable tool for hospital providers to grasp the complex dynamics of patient experiences. By actively and consistently collecting feedback, hospitals can gain rapid insights into critical areas, allowing them to track and measure patient satisfaction levels, and crucially to react to any dips in standards of care.
Hospitals can also use these insights to better understand why their staff might not have been aware that certain areas of care were lacking from the patient’s perspective, which can oftentimes be very different compared to a nurse or doctor’s point of view. When problems do arise, having real-time feedback means that management is able to give staff valuable information and then guide staff to solve any issues effectively and prevent them from becoming a source of patient and employee unhappiness.
For example, the fact that ‘wait time’ is such a common complaint across the industry indicates that more effort is needed to remedy this problem. When changes are implemented, real time patient feedback allows management to see which solutions ease the issue or if further adjustments are necessary. If it’s evident that wait times are making patients unhappy, one possible response is that staff can be offered training in how to communicate effectively and sympathetically to help patients understand why they might be experiencing longer waits than they expected. Another example is that, if the waiting room is uncomfortable, it can be reasonably assumed that patients are more likely to complain about waiting times. This is just one simple example of how having the data regarding what is making patients unhappy can signpost the way to a solution, such as improving the environment of the waiting room. With every small change implemented, or potential problem averted, the overall impact on the patients’ circumstances will be one of positive change.
Dave Brailsford (one of the most successful cycling coaches in history) has a theory he calls “the aggregation of marginal gains” which works by saying that if you improve lots of different areas by 1%, then all the little improvements you make will add up to a significant amount in total. This theory rings true with patient experience; if you are getting real-time data on where you can improve, you can start to address the problems and make the changes needed to forge stronger connections to your patients.
Quality of care should be every hospital’s main goal, so giving patients the necessary means to flag an area of their experience that was lacking and show that their feedback is being heard and vital. Lots of patients that are suffering from long term illnesses, who either have long stays or regular appointments, will be glad to notice the positive changes that are made as a result of identifying the problem.
With the global AI in patient engagement market size estimated at $6.08 billion in 2023, and set for growth rate of more than 20% between 2024 and 2030, AI will become an increasingly useful tool in the field of patient experience. Not only are there increasingly sophisticated feedback terminals which are able to anonymously identify demographic details about those giving feedback using AI, but AI can be employed as a tool within data analytics. Using AI to analyze and recognize patterns in feedback given can aid decision-makers in identifying and then implementing the required and relevant changes.
AI can help in automating and streamlining the analysis of customer feedback. By using AI and machine learning, which can rapidly analyze vast amounts of data, hospitals can uncover;
trends
sentiment patterns
decode demographics (age/gender)
spikes in feedback that could point to a specific problem patients are facing.
The most important takeaway is that the patient feedback data which hospitals and clinics collect must be reviewed, whether manually or using the tools made available by increasing technological advances. It is only through looking for the patterns that the feedback data reveals that providers will be able to deliver more personalized care, by tailoring the patient’s journey from the moment they enter the facility until they leave based on what their demographic most commonly wants and needs.
Feedback analysis allows hospitals to run at maximum efficiency, since uncovering trends quickly means you can preempt what problems may arise in certain situations. Whether that’s adjusting staff rotas so more staff are working during certain hours, days, even holidays where more patients are likely to arrive or perhaps increasing cleaning of certain areas with which patients are dissatisfied. The key is using insights to reduce strain on staff, and forge trust and loyalty with patients.
The important role of data analytics in improving patient experience in the healthcare industry cannot be understated. As the healthcare industry is still climbing back to its feet following on from years of stress and strain since 2020, innovation is necessary to improve the standard of care given to patients. Knowing exactly what is causing unhappiness in patients is crucial, and using modern technology such as AI or machine learning can be a silver bullet for healthcare providers moving forward.
Photo: imtmphoto, Getty Images
Miika Mäkitalo is CEO of HappyOrNot, the company which created the globally recognised four Smileys, and which serves 4,000 brands across 135 countries, like Elkjøp, Levi’s Stadium, Autogrill, and London Heathrow Airport. HappyOrNot has collected and reported on over 1.5 billion feedback responses. Over the last 15 years Miika has held several upper management roles and holds a PhD in Industrial Engineering & Management.
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