Could speech analytics help overcome care obstacles?
Imagine the following scenario: a hospital system is reviewing its latest patient feedback survey results. Their customer experience ratings are below average, and they need to know why. They start combing through comments from the 100 survey responses to gain understanding.
Keep in mind, this hospital system served one million patients last year and they're relying on feedback from 100 to understand the experience of their entire patient population.
The reality is, you can't diagnose a systemic problem with a 0.01% response rate. When healthcare leaders rely on incomplete data, they only see part of the story.
Enter the pivot to — and wider adoption of — digital transformation within the healthcare industry, as over 90% of health system technology leaders believe this solution is the key to providing better patient care.
Within digital transformation lives one particular tool: speech analytics. A number of healthcare organisations are turning to speech analytics for actionable insights to improve patient care, experiences and outcomes. These tools offer organisations a more scalable strategy for listening to patients, accessing critical datasets and telling the whole story.
Unstructured data: an undervalued resource
Healthcare organisations face a daily deluge of customer feedback data sent and received across different platforms, tools, channels, technologies and online portals. Yet much of this collected data is unstructured. In fact, unstructured data comprises over 80% of enterprise data used by many industries — including healthcare.
Several factors contribute to the challenge of organising and accessing unstructured data:
- High volume: Too much stored data exists, and it's costly to process and organise.
- Varied file formats: Data originates from multiple sources and formats, making it hard to structure routinely.
- Velocity of incoming data: Organisations generate more data than they can effectively and efficiently process.
Because of the obstacles it presents, fewer than 20% of organisations take advantage of unstructured data. The majority of information collected sits in the dark, unused. But organisations that leverage speech analytics software to aggregate and activate this 'dark data' have a competitive advantage. Why? Because executives relying on unstructured data for insight are 24% more likely to exceed their business goals.
Fundamentals of speech analytics
Because they collect a significant amount of unstructured, undefined data, healthcare organisations rely on speech analytics tools to provide context and analyse recorded conversations. Decision-makers can aggregate this conversational data to identify common customer pain points by flagging keywords and phrases.
Typical speech analytics software includes: transcription, which provides deeper insight into conversations by transcribing voice calls verbatim into more easily accessible text; sentiment analysis, which analyses call data, customer support text chats and email exchanges to evaluate the overall sentiment of a customer or brand; word clouds, which summarise calls and identify topical-based words to offer a high-level overview of the words customers use most frequently; association analysis, which uses multiple algorithms to relate topics and emotions to one another. For example, "negative sentiment" is often associated with "the bill paying process".
Speech analytics can mine dark data to pinpoint recurring themes more accurately and quickly decrease organisations' reliance on surveys or conclusions formed by assumptions. Honing in on customer voices creates meaningful change that identifies disruptions, develops more explicit context and provides actionable insights on the next steps.
Most organisations use various approaches to collect customer data. However, standalone data cannot create a patient-centred, goal-oriented approach because it lacks actionable context. Robust speech analytics software solutions amplify customer voices and enable healthcare organisations to interact with and learn from these stories.
Identifying barriers to care
Speech analytics can identify barriers to patient care, including:
- Patient confusion about status updates, prescriptions or treatments.
- Insufficient patient understanding of insurance and medical terms.
- Indications of customer turnover.
- Unresolved gaps in patient care.
- Low customer satisfaction.
Analytics could help organisations uncover macro trends that warrant deeper analysis. It can highlight customer concerns and focuses, like digital accessibility, billing and benefits but lacks the 'why' behind the words and phrases currently at top of mind for customers. For example, a word cloud may identify a customer's frustration but not the specifics of that frustration.
Instead, healthcare leaders should use analytics to strategically focus human listening for deeper understanding. This type of listening at scale is crucial to gain context around the data and better understand patient needs.
Speech analytics paired with human listening empowers organisations to more effectively predict customer behaviour, anticipate potential pain points along the customer journey and improve the patient experience. By embracing the digital transformation speech analytics offers, organisations equip themselves to define recurring trends, recognise key behaviours and interpret patient perspectives more accurately.
To drive change and create invaluable impact, organisations should:
- Refocus on customer interactions within the whole customer experience pipeline.
- Recognise opportunities to make improvements.
- Identify opportunities for speech analytics tools to provide insight.
- Leverage human listening and qualitative analytics by using customer voices to inform strategy development.
Too many patients experience frustration while navigating the business of health care. Speech analytics tools could help empower the industry to identify common pain points and confusion within the customer journey, and also magnify patient voices to create actionable change.
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