Measuring patient experience: Evaluating healthcare quality with modern tech | Inga Shugalo

“If you can’t measure it, you can’t improve it.”

Simple as it may sound, this phrase is the key to efficacy in any business, and healthcare is no different. The continued effort to advance quality and address patient-specific needs stands at the heart of value-based medical services.

Still, achieving the highest standards requires knowledge. While doctors are experts in treatment, it is patients who know best what service they expect from a practice or hospital. And they’re very keen to share their experiences.

Positive word-of-mouth is one of the primary factors influencing patients’ decision about the choice of a physician. Sometimes it appeals to the patient community stronger than previous success in treatment or timely return of lab results. It means that in order to thrive, healthcare providers need to pay attention to patient experience and satisfaction. But how to measure them?

Learning about patient experience

Traditionally, healthcare businesses have measured patient satisfaction using printed surveys and phone interviews. Easy to implement, affordable, and accessible, these methods played an important role in gathering patient feedback. However, the shift towards value-based medicine has exposed their shortcomings.

• They requiremanual data entry. Manually typing in the findings of patient calls and surveys adds to the heavy workload of healthcare workers in the already busy medical care setting. Besides, human data entry is extremely error-prone.
• They are limited in volume. There’s only a limited number of calls and surveys healthcare employees can take to gather feedback. In addition, many patients may find these methods of gauging their experience too personal or intimidating, resulting in their refusal to participate.
• They are reactive by nature. Traditional methods of measuring patient experience may work fine for collecting data for smaller medical facilities that don’t have a large patient base. But interpreting that data is a whole different story. Manual data analysis is an extremely time-consuming task that often requires an expert approach. And without it, the entire process of requesting patient feedback is worthless.

The answer to these limitations lies in technology. Modern automated solutions help measure the patient experience efficiently, gain essential insight into what patients think, and allow providers to act on it, regardless of the volume of patient data collected.

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CRM software for healthcare

CRM (Customer Relationship Management) systems are used in virtually any modern industry that involves interactions between a business and customers. They rely on data from disparate sources and communication channels to provide detailed information about the client base. By integrating and structuring data, CRM solutions allow businesses to learn more about their customers without added effort.

Medical businesses make use of vast amounts of data spread between various management tools. For them, healthcare CRM allows fully leveraging the wealth of patient records from patient portals, hospital information systems, EHRs, scheduling tools, and many other sources. The information is merged in one place, facilitating data access and sharing, all in compliance with HIPAA regulations.

Once CRM has gathered all the records, it creates a unique profile for each patient. The profile stores various parameters, such as patient activity, past and future appointments, demographics, and medical history.

Based on that information, a provider can easily group and categorize patients and adjust their services accordingly. For example, different communication channels can be used for different patient segments — seniors may prefer calls, while the younger client base would rather opt for app notifications.

• Related story: Healthcare companies do more electronically, but there's room to improve

AI-powered solutions

Data collection is essential for any modern healthcare provider that wants to enhance services based on patients’ input. But data overload often becomes too much to handle for many hospital managers. When there’s too much information to process, valuable input from patients may easily go unnoticed. It’s particularly problematic when patients’ complaints slip through the cracks due to excessive data volumes.

AI and machine learning help providers efficiently deal with large-scale data collection. These technologies provide assistance when medical staff can’t process all the feedback the practice is receiving. They not only deal well with large volumes of data — they thrive on it, getting more knowledgeable and relevant with each byte.

The learning capabilities of AI allow it to act preemptively rather than reactively. For instance, AI software can learn to predict which patients are at an increased risk of developing a chronic disease. The model considers not only the medical records but also the unique socioeconomic background of each patient.

Such an approach is key in fighting illnesses like diabetes or cancer. Allowing patients and providers to act early translates into time and money savings — and patient delight.

AI finds another use in physician assessment. By factoring in patient outcomes, complaints, and praises, data analytics give hospital managers a clear overview of each professional’s performance. This is done in real-time, enabling day-to-day evaluation and prompt reaction.

Smart chatbots

A personal connection between patients and providers is undeniably important, and at the same time hard to establish — particularly in times of social distancing and a growing demand for a personalized experience. Even though chatbots still cannot replace human agents, they are getting increasingly better at mimicking human conversations and interactions in some contexts, such as providing quick feedback to patients.

A well-programmed chatbot can contribute to measuring patient experience in different ways. Diagnostic chatbots are tasked with identifying possible illnesses on the go by asking the patient about their symptoms. At the same time, they can upload this information to the patient’s profile to enhance analytics and streamline future processes, such as admission.

Additionally, a chatbot can ask the patient to rate or comment on the service quality in the facility. This feedback is easy to store since it’s digital and automatically saved after the session. Even better, it takes only a couple of seconds to collect, so that clinicians can get more input and, effectively, a more complete image of patient sentiment.

Bottom line

As quality and excellence are becoming the main focus of today’s medicine, providers must know their patients’ worries and expectations in order to succeed. In the future, keeping up with the needs of the modern patient will be possible only with modern technologies.

Inga Shugalo is a healthcare industry analyst at Itransition, a custom software development company headquartered in Denver, Colorado. She focuses on healthcare IT, highlighting the industry challenges and technology solutions that tackle them.