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Transformational Self-Reported Data Collection with Digital Empathy™

By November 10, 2021May 16th, 2024No Comments

Globally, healthcare organizations are transforming their care delivery models to more personalized, preventative, and integrated care. This aligns with the shift to value-based care which encourages patients to be active participants in their care journey. This includes many types of self-reported data tools. PROMs (Patient Reported Outcomes Measures), PREMs (Patient Reported Experience Measures) PRMs (Patient Reported Measures), assessments, scales and surveys. To measure and evaluate value-based care, healthcare organizations need tools that more effectively capture data for enhanced individual and population health. However, health inequities in historically underserved, diverse populations remain a challenge for the Canadian Health care system when it comes to the capturing quality self-reported data.

Challenges in capturing quality self-reported data

One-size doesn’t fit all

Organizations are discovering that a one-size fits-all approach to communicating with each unique individual who makes up a population often results in low uptake and poor-quality data. This poses even more of a challenge when the information requested covers sensitive or stigmatizing topics. These challenges are compounded when considering varying levels of literacy, cultural differences, and socio-economic disparities – all of which can impact a person’s ability to trust the data collection process, and effectively communicate their personal information and needs. While asking questions is a good first step to collect person-reported data, the utility of this data cannot be fully achieved if respondents struggle with using tools that are not “tuned” to the individual’s identity, culture, literacy, or state of mind. Data is only as powerful as its accuracy and when poor quality data is collected (garbage in), the results will be compromised (garbage out). Other factors also impact data quality including:

Response bias due to cultural differences

Research has shown that different groups of people respond to the same questions differently due to factors like gender, race, culture, lived experiences, and beliefs. These factors can cause some people to impact the data integrity for example while responding to a question on mental wellbeing.

Fear of judgement and concerns for information privacy

Many health screening tools ask sensitive personal health information like family issues and sexual activity. Youth and adults avoid discussing culturally sensitive issues and may be reluctant to report this data because they are worried about consequences or interventions from care providers, especially for alcohol or illegal drug use.[1] If participants do not trust researchers or the goal behind the screening is not clear, they may not provide proper or honest answers, impacting the fidelity of the data.

Reduced accessibility due to communication barriers

While Canadians have higher levels of health literacy than Americans, some surveys contain medical jargon or unclear terms which may confuse people when answering a survey, resulting in inaccurate data. Additionally, surveys only offered in English can limit data quality as many people might not understand the questions properly.

Low engagement with poor survey designs

The transformation from paper to digital forms, without considerations of the medium, or design have resulted in poorly designed self-reported data tools. Survey fatigue is a common problem in the collection of data. Factors that are known to influence respondent fatigue include survey length, survey topic, question complexity, and open-ended question type.[2] With the recent explosion of mobile smartphone technology, many paper based surveys are directly being transcribed to electronic surveys with almost no experimentation with question wording, graphic format or survey content, primarily due to limitations posed by survey instrument validation.[3] Lack of graphics, long worded questions and poor user experience discourages both meaningful engagement and quality data collected.

A fresh, new approach to collecting sensitive and stigmatizing data

New concepts, such as bringing empathy into the technology used for self-reported data collection processes, provide a fresh and innovative approach in addressing these issues, and the term, Digital Empathy has been coined to describe this approach. Digital Empathy uses the core principles of empathy – compassion, cognition, and emotion – in designing technology to enhance a person’s experience.

The foundational element of a digital empathic approach helps build trust, engagement, and empowerment into self-reported tools to tackle the issues of inequity, stigma, and accuracy and level the playing field.

It has also been found to bring additional opportunities, transforming transactional relationships between healthcare organizations, providers, and patients into deeper, ongoing, trusting ones, supporting patients as partners in care.

Tickit’s Digital Empathy Design Framework introduces empathy into the digital world through a design language that touches each point of the journey to capture person-reported data.

Drawing from different design processes, the framework acts as a guide for each element user experience design, ensuring a safe and comfortable space for people to access, interact and share information, resulting in higher-fidelity data collection at lower costs for organizations. By addressing communication barriers for different audiences of focus, digitally empathetic tools capture highly accurate, sensitive, and specific actionable person-reported data. Research has shown that a comfortable, empowered and engaged persons will provide more accurate and usable data.

Embracing an inclusive hierarchy of design, the framework introduces design elements that move from universal humanistic attributes to recognizing the specific qualities of an individual that make them unique including age, race, gender, and literacy levels. Surveys built on this framework personalize the user experience based on their individual attributes, thereby building trust and invoking willingness to share their unique voice.

Inside the framework, the tools themselves can be configured to include design details like colour palettes, images, illustrations, icons, and the overall structure of the survey tool. This flexibility in design enables digitally empathetic tools to be made appropriate for different use cases (surveys, assessments, education, interactive workshops) and different populations while maintaining a single data set for organizations. Four principles enable surveys to collect meaningful data by:

  • Being responsive and reactive to keep a person’s attention, activism, and motivation
  • Contextualizing and personalizing the experience
  • Establishing a comfortable cognitive load that considers low literacy, disabilities, cultural and language differences, differing ages, and varied comfort levels with technology
  • Empowering people by explaining the tool and ensuring they understand its value

From the beginning, users are given information about who has access to the data and the option to consent or decline. Tools can be configured to offer people the option to receive tips, feedback, links to resources, and give them the chance to talk to a support person. Every design detail, and the tone and type of language used allows each person to feel heard, and to gain something from the process of sharing their personal information. By empowering each person, these tools also empower organizations to engage and support the populations they serve.

 

Some success stories on the benefits of Digital Empathy

Where conventional surveying methods lack personalization as they focus solely on the needs of data collectors, Digital Empathy transforms the data collection process by prioritizing the needs of its respondents as well as collectors. The approach recognizes that different people have different needs and views these as a design opportunity for building surveys that engage users. Organizations that harness the power of Digital Empathy in conducting surveys, assessments, and educational tools have reported improved data quality, response completion rates, efficiency, and satisfaction while decreasing risks of missing information.

Increased response rate and workflow efficiency

Cleveland Clinic Canada, a global nonprofit medical centre is guided by its “Patients First” ethos to provide outstanding service to clients. As part of putting patients first, Cleveland Clinic runs the Executive Health program, tailored to the individual to reduce health risk factors, and detect and treat diseases in their earliest stages. Coordinating care as well as tracking and measuring the patient experience was of utmost importance to program success.

To measure patient experience, Cleveland Clinic used a generic digital survey tool to capture information directly from patients but weren’t receiving consistent and quality data to accurately measure program success largely due to patients skipping questions, not completing the survey and rarely giving additional comments regarding their experience. Without honest and unbiased feedback directly from patients, the program executives felt uninformed when making important program decisions.

Using digital surveying solutions based on the principles of Digital Empathy, Cleveland Clinic saw a 42% increase in patient usage as well as greater engagement. Previously patients would only answer ranked questions (i.e. “on a scale of 1-5…”), but when using the new tool, they provided more granular and personalized responses, choosing to answer free-response questions at length. Using Digital Empathy revealed an entirely new understanding of patient needs and levels of satisfaction with the clinic’s services, further supporting the ‘Patients First’ initiative. Richer data, automated reporting, and analytics in real-time drastically improved workflow efficiencies in reporting and acting upon patient feedback.

Improved organizational efficiency

Bayshore HealthCare, one of Canada’s largest national providers of community healthcare services runs Bayshore Specialty Rx which offers state-of-the-art pharmacies and a high level of expertise in the preparation, storage and delivery of intravenous and injectable drugs and equipment, coupled with case management and health coaching by clinical nurses.

A core element of ensuring the success of Bayshore’s drug delivery program is collecting information from patients with a baseline health assessment questionnaire to determine the “before” and “after” change in a patient’s health score and satisfaction. Bayshore nursing staff conducted the Baseline Health Assessment surveys over the phone which resulted in both time taken away from higher-value health coaching activities and reduced ability to proactively identify health and wellness issues of concern to patients ahead of the coaching call. Post-coaching surveys were inconsistently completed by patients, making it difficult to know if the Nurse Case Management Service improved health outcomes. This incomplete data set and ineffective manner of collecting information via phone surveys that were manually collated and analyzed in Excel to identify trends, added further challenges and workflow delays.

Applying the principles of Digital Empathy to the assessments’ designs, Bayshore Specialty Rx saw an improvement in the efficiency of collecting information from patients as well as in the quality of the data with a 300% increase in assessment completion rates compared to the previous digital survey tool. Empathetic question phrasing, intuitive survey formatting, and dynamic responses to cultural nuances in real-time decreased barriers to honest communication, making patients feel more comfortable sharing both personal health information and feedback on their experience with Bayshore’s services.

Higher sensitivity and specificity in identifying at-risk youth

Schools in King County, like schools across the US, carry much of the burden of poor youth mental health. A The 2018 Healthy Youth Survey found 16% of 8th and 12th graders in King County had made a suicide plan in the last year, and 8-9% of all students had attempted suicide. Students contemplating suicide are suffering, often silently, and many slip through cracks in the support available in schools and elsewhere. In addition to the potential tragedy of losing a life, students who are suffering impact community wellbeing and often lower their school performance, attendance rates, and graduation rates–all of which can negatively affect school funding. Lack of school funding further impedes the ability to provide services and sets in motion a negative spiral for the entire community and wellbeing of the student body.

In an attempt to improve youth health, King County’s Department of Community and Human Services implemented a school-based Screening, Brief Intervention and Referral to Treatment (SBIRT) program in 42 middle and high schools to identify and treat students suffering from mental health issues and potential misuse of substances. A common challenge in typical screening tools is limited accuracy, measured in terms of sensitivity and specificity rates. Youth in particular – afraid of stigma, judgement, and lack of trust – oftentimes do not openly and honestly provide detailed information regarding their lives and challenges and fears they face.

Employing the principles of Digital Empathy, King County used the Tickit Health screening tool Check Yourself to better identify students in need, efficiently implementing SBIRT across a large population of students. The approach helped students become more forthcoming with information, enabling counselors to witness a 77% improvement in detection of risk factors not previously known and connecting 37% of students who were screened to brief interventions while referring 15% of screened students to community services. The enabling technology improved the identification and treatment of mental health challenges among the King County student population, particularly among previously hard to reach students.

A greater view to population health

At the population level, robust data can drive decision making to improve care, safety and services. For example, Black Creek Community Health serves a diverse, historically underserved population in Toronto. Using Tickit to collect PREMs (Patient Reported Experience Measures) caused a 400% increase in uptake, and higher completion rates than their previous system. The Tickit data resulted in the management team changing scheduling practices throughout the organization.

Data-driven decision making

Healthier populations, lower care costs, more visibility into performance, and higher staff and consumer satisfaction rates are among the many benefits of data-driven decision making in the healthcare realm.[4] Increasingly, organizations are investing resources to capture data that is clean, diverse, complete, accurate, and formatted correctly for use in multiple systems. When organizations need an understanding of diverse, underserved populations to drive organizational efficiency, they are turning to more inclusive and accessible surveys built on the principles of the Digital Empathy.

The way questions are asked must cater to the diversity of patient populations with respect to language, culture, literacy, and education.[5] It’s also important that minority groups feel comfortable to openly share their health and lifestyle information. This trust hinges on inclusivity, culture appropriateness, and respectful language. Only once we understand and implement this, can we design truly engaging questionnaires that collect useful data for better population health outcomes.

We know “one size fits all” healthcare ultimately does not work, since it neglects the unique needs of populations, an approach that in the long run is neither effective nor cost-efficient. That’s why diverse data isn’t just a moral imperative that can better health disparities – it is also a financial strategy that will help reduce costs while keeping people healthier, happier and out of hospitals longer.

In an era where technology promises to revolutionize population health, keeping healthcare human with Digital Empathy is more important than ever.

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[1] Zanis, D.A., A.T. Mc Lellan, and M. Randall, Can you trust patient self-reports of drug use during treatment? Drug and Alcohol Dependence, 1994. 35 (2): p. 127- 132.

[2] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5600176/

[3] https://www.google.com/url?q=https://www.researchprotocols.org/2013/2/e42/&sa=D&source=docs& ust=1635491284381000&usg=AOvVaw1ONxiuIMVAPcPXpePnzHBC

[4] https://healthitanalytics.com/news/top-10-challenges-of-big-data-analytics-in-healthcare

[5] https://pubmed.ncbi.nlm.nih.gov/9250628/