Improve Customer Experience In Healthcare With Decision Trees

Whether you are an app-based healthcare provider or run a practice, your patients need to be able to come to you for health-related queries. In the era of Google search domination, it is not an easy task to make customers come to your customer service teams first.

Still, it is a possible reality with practical decision-making resources that can help in enhancing the customer experience in healthcare sector. 

Common challenges faced in healthcare customer service 

To give adequate healthcare CX, support, and answers to the customer or patient queries, it is essential to understand where you might be lacking. Following are a few industry common challenges that restrict your patients’ communication with your healthcare customer services. 

1. Lack of guide resources

• Guides or resources that help customers with problems like does my insurance cover so and so procedures, post-op healing guides, and clinical practice guidelines need to be available on-hand to healthcare assistants
• Lack of any significant source of information would result in poor customer service and might even lead to the customer feeling dissatisfied for not finding out the crucial information they needed
• This results in losing credibility in healthcare service and would not invite the patient or customer to build trust

2. Data confidentiality

• The leak in any data or personal information in the healthcare industry is treacherous. In healthcare, one of the utmost responsibilities is to maintain the confidentiality of the patient.
• A breach in data confidentiality could happen if poor or no proper knowledge management is in place
• The challenge with patient data confidentiality holds a thin line because each and every detail about a patient helps to come to the best solution

3. No-automated service 

• Automation in healthcare is a huge challenge. This is because every patient is unique. Experiences often can’t be clubbed as patient history holds unique patterns similar to the threads of their DNA.
• Automation of services might lead to misinformation or misdiagnosis of the patient
• Automation, even if present, should be limited to processes like bill payment and where efficiency can be lifted instead of making processes complicated

4. Maintaining service quality 

• Healthcare is a sector where all hands on deck are always needed. So with many incoming calls and healthcare executives overworked, it is hard to maintain service quality.
• One way to overcome this challenge is to have call flow scripts with SOP adherence guidelines so that healthcare support teams do not skip any crucial steps in collecting information
• Customer experience in healthcare can be elevated significantly with proper documentation using knowledge management tools

5 Ways How Decision Trees Improve Healthcare Customer Experience

Decision-making is a revolutionary knowledge management tool to provide an exemplary customer experience in the healthcare industry. Especially in times of emergency, to provide the best objective solution.

Decision trees are step-by-step solutions that help customer care professionals make the best decision possible for the next best action, further enhancing customer experience in hospitals. Following are how decision trees in healthcare are a game-changer. 

1. Accurate diagnosis

•  Accurate diagnosis is the first step to treatment in healthcare. With the help of machine learning, it becomes easy for decision tree makers to understand the pattern.
• After understanding the pattern, the permutations and combinations must be carefully examined. These points can be jotted down in the decision tree to arrive at the correct conclusion.
• Taking appropriate steps, like correctly noting down a patient’s history and symptoms, is one of the most critical steps

2. Emergency assistance

• Quick decision-making is a need for any emergency healthcare service. Even experts need time to diagnose exactly what a problem is. In healthcare, it is equally important to maintain accuracy with speed.
• Decision trees in healthcare are quick with assistance, even in emergencies. With correct analysis through decision trees, the right decision can be taken by patients
• With CRM integration-supported decision trees like Knowmax has, one can eliminate time wasted in collecting patient information without much trouble by accessing the CRM. This ensures best practices even if the patient is in a state of panic.

3. Automated support

• Decision trees in healthcare can serve the purpose of order tracking or simple billing-related queries through an automated process
• Automated support can be extended to healthcare customer experience through in-app or other chatbots, where decision trees can be deployed at the customer-facing front
• Automated support helps healthcare support teams handle more important calls and extend automated support to those who are not in immediate need

4. Visual at-home assistance

• Visually explaining situations to patients helps a lot in medical care, especially where first aid is the need of the hour
• For those who might not be medical professionals, visual assistance can be inserted within a decision tree to explain specific procedures from any place of their convenience 
• Visual assistance can be done for both medical aid or other navigating queries or also ways to use a particular gadget or machine 

5. Essential data capturing 

• Data capturing is an integral part of a patient’s journey to collect the history of the patient
• Patient histories are very crucial as they help take the next step forward, especially in case of emergencies where allergic reactions and medications are taken essential to note for the treatment
• Through data collection with consent, deducing patients’ history to take the next best action becomes a breeze 

Conclusion 

Decision trees in healthcare are path givers to hassle-free healthcare queries. They can be used in any department for healthcare support, from emergency wards to customer support and post-op assistance.

Decision trees in healthcare supported by machine learning through the right knowledge management partner change the quality of support people receive.