Using human factors to achieve patient and family-centered care

Chapter 126

Using human factors to achieve patient and family-centered care Rachel Wynn, Hala Durrah, Deliya B. Wesley MedStar Health Research Institute and MedStar National Center for Human Factors in Healthcare, MedStar Health, Washington, DC, United States

Situation Rapid advances in technology and health information technology (HIT) are changing the reality of the patient experience and pushing the boundaries and expectations for both providers and health systems. The Institute for Healthcare Improvement’s triple aim framework posits that improving the US healthcare system’s performance requires: (1) improving the patient experience, (2) reducing per capita costs of health care, and (3) improving population health (Berwick et al., 2008). These aims can apply to most healthcare systems worldwide that are working toward improving quality, and emphasizing patient experience. Health systems are now focused on and invested in optimizing the safety, quality, outcomes, and efficiency of patient care. This state remains elusive and unattainable without the application of human factors, the science that focuses on understanding how individuals function within their surroundings. While human factors have been increasingly applied to the work that clinicians do, such as examining and improving electronic health records (EHRs) (Middleton et al., 2013), these methods are not as readily applied to the roles patients play in their own care. This is a critical missed opportunity. Human factors methods provide the tools to understand how patients engage with health care and how to optimize this interaction to improve health outcomes. As the US healthcare system shifts increasingly toward a more patient–family-centered model of care, fully engaging and collaborating with the patient, understanding their context and needs, is critical. Patient and family-engaged care (PFEC) is care planned, delivered, managed, and continuously improved in active partnership with patients and their families to ensure integration of their health and healthcare goals, preferences, and values. It includes explicit and partnered determination of goals and care options, and it requires ongoing assessment of the care’s match, with patient goals (Frampton Clinical Engineering Handbook. https://doi.org/10.1016/B978-0-12-813467-2.00127-9 Copyright © 2020 Elsevier Inc. All rights reserved.

et  al., 2017). The National Academy of Medicine (NAM) [formerly the Institute of Medicine (IOM)] defines patientcentered care as care that is respectful of, and responsive to, individual patient preferences, needs and values, and ensuring that patient values guide all decisions (Medicine (IOM), 2011). At the crux of both definitions is a focus on ensuring health systems are designed to achieve the experience most desired by patients, and their families. Along with increasing initiatives to build measures of patient satisfaction and patient experience into performance-based compensation systems, patients themselves are advocating to be more engaged in their care.

Background Patient engagement for patient-centered care One of the key goals of human factors in health care is to promote high quality, safe care for all patients (Saleem et al., 2009; Russ et al., 2013). In 2013, a key NAM report highlighted the importance of engaging patients and their families as active participants in their care in order to improve healthcare safety and quality (Institute of Medicine, 2014). This NAM imperative coincided with the widespread adoption of HIT including EHRs and ­patient-facing HIT such as patient portals. The use and adaptation of such technology is a way to improve the quality of care and improve patient outcomes, but is consistently suboptimal in current forms (Ratwani et al., 2016). Patient portals, as an example, have potential to improve patient experience if codesigned and developed appropriately with the user. These tools potentially serve as a platform for patients to easily access their health information and more easily communicate with their provider. Use of patient portals also affords the opportunity for patients to have their health information preserved overtime (Gephart and Effken, 2013). 881

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Despite these benefits, the majority of the US population does not ever access or engage with patient portals (Goel et al., 2011; Gordon and Hornbrook, 2016). Low rates of patient portal usage are not simply due to patient preferences, or a lack of internet access or ability to use the Internet (Gordon and Hornbrook, 2016). Extensive studies of patient-level barriers point to usability issues and a lack of understanding of the potentially nuanced needs of population subgroups (Gordon and Hornbrook, 2016; Ronda et  al., 2014; Jhamb et  al., 2015; Banda et  al., 2012). As such, low levels of engagement with HIT can be greatly improved by using human factors and a u­ ser-centered design (UCD) approach in developing these patient-facing technologies. A UCD approach to patient-facing HIT development is the key to developing technology that patients are more likely to engage with, and is a human factors directed means to improving patient outcomes. A dearth of evidence demonstrates that having patients as active participants in their own care improves their experience with care and overall health outcomes (Prey et al., 2014; Smith et al., 2016). HIT has been touted as the critical tool for empowering patients and their families to effectively manage healthcare decisions and to educate them about their health (Gephart and Effken, 2013). However, there are critical gaps in our knowledge that prevent us from using HIT to improve patient engagement. The premise and expectation that all patients can be full participants in their care and engage with HIT to improve their outcomes is flawed if design recommendations do not explicitly address the diversity of the population of potential users. For example, patient decision-making support and patient-facing health-related information has not typically been designed or developed with the patient as part of the process, making it unlikely that the diverse needs of patients (e.g., language preference and appropriate literacy levels) are being met. Human factors methods use the process of codevelopment, such as UCD, which involves the intended end user at design stages, iterating on design based on the user’s needs. This technique, if applied to health care, could provide critical information about how diverse patient populations interact with HIT and how the design of HIT can be adjusted to meet these needs. Further, in order for this partnership to be successful, codesign and codevelopment must begin in the early stages of the process and continue throughout development. The rapid proliferation of HIT and increased use of technology by both providers and some patients has promoted an unintended digital divide, as the subset of patients more apt to adopt emergent technology end up more engaged, and with greater access than those who may not adopt the technology for a variety of reasons. This effectively makes care less patient centered for a subset of the population.

Health equity and addressing social determinants of health Human factors methods can be used to successfully identify and address user needs through codesign of new health technologies or redesign of existing HIT. Such methods could be particularly useful in addressing and integrating users’ nonclinical needs to improve their outcomes. Different subgroups of the population have nuanced needs that may relate to factors such as race/ethnicity, age, gender, primary language preference, and literacy level. A failure to understand these differences and to deliberately address them is a primary issue preventing effective patient engagement. The consequences are potentially profound, as these shortcomings in contextual design could also be further driving disparities in health outcomes by systematically excluding the most vulnerable groups of potential users. Employing human factors methods, including a UCD process, are the key to addressing this gap. The Robert Wood Johnson Foundation reports that only 20% of health outcomes can be attributed to clinical care (Berwick et  al., 2008). The remaining 80% is attributable to modifiable factors termed social determinants of health (SDH). Social determinants of health are defined as “the conditions in which people are born, grow, work, live, and age, and the wider set of forces and systems shaping the conditions of daily life.” (Middleton et  al., 2013). These “upstream” factors are so termed because they interact with and directly impact more “downstream” factors such as health outcomes and health behaviors (Frampton et al., 2017; Medicine (IOM), 2011). Despite an extensive and compelling body of literature establishing the dramatic influence of upstream SDH on health outcomes, our traditional approach to patient care still focuses downstream (Saleem et al., 2009; Russ et al., 2013). Social determinants of health data are not routinely collected for the purpose of patient care, nor are they systematically integrated to support clinical decision making (Saleem et al., 2009). The lack of availability of these data further impedes patient/family engagement and shared decision-making. This shortcoming and a lack of systemization may be a significant contributor to the suboptimal outcomes we see in the healthcare system and represent another key patient-centered area where human factors can transform care delivery. Further, because social determinants are factors that can be changed, the failure to collect these data in an accurate and meaningful way is a critical missed opportunity to improve care quality, reduce costs and disparities in care, and significantly improve population health management and patient/family engagement. As an example, the widespread adoption of EHR technology presents an opportunity to optimize the collection of SDH data, integrate this information with the EHR, and support clinical and shared decision-making. To this end,

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the NAM introduced a set of 12 SDH measures, which offer clinicians the opportunity to identify conditions that may modify a patient’s diagnosis and treatment plans (Institute of Medicine, 2014). While these factors have historically been viewed as outside the purview of the medical system, providers are increasingly recognizing that problems such as housing and food insecurity directly impact a patient’s health status, healthcare utilization, and can effectively be addressed in clinical settings (Ratwani et  al., 2016). However, without patient/family engagement, community partnerships and outreach, SDH data cannot be effectively addressed in a clinical setting. In addition, there is still no consensus or standard for collection of these data or for EHR integration. Given the complex process of successfully coordinating clinic workflows and provider teams, patient data from multiple sources require the application of human factors methods as a necessary first step.

Assessment Addressing patient characteristics: comprehension, cognition, and processing Achieving patient-centered care requires we address the larger more systemic factors, such as the SDH, as well as addressing important personal characteristics that may act independently of or in addition to SDH. Patient-centered care requires that a patient is fully engaged, understands their illness and care plan, and that they are able to access the health information they need. To this end, any patientfacing information must be adaptable for patient characteristics including varying levels of health literacy, language proficiency, race and ethnicity, and age. The information should also be based on their personal preferences. We examine a few of these in detail, and present case studies illustrating the successful use of human factors methods to address them.

Health literacy Educational materials When developing materials for patient education, it is critical to consider the health literacy level of the intended user. Health literacy is defined as one’s ability to comprehend and utilize the information regarding health care that is needed to make appropriate decisions. This construct is distinct from general literacy, which is simply reading and writing skills (Nutbeam, 2008). General literacy is only one component of health literacy, which encompasses four domains: cultural and conceptual knowledge, speaking and listening, writing and reading, and numeracy (Institute of Medicine, 2004). These domains interact to determine the health literacy of an individual, which can influence the care a patient

receives at three different points: access to quality health care, interactions with the healthcare provider, and self-care (Nutbeam, 2008). To illustrate how health literacy impacts patient outcomes, consider patients with chronic disease. Successful management of a disease such as hypertension or diabetes requires an understanding of the disease and treatment. The traditional approach is to provide patients with written materials that describe these elements, with the expectation that this will provide the understanding necessary to engage in proper self-care (Williams et al., 1998). This approach relies on the patient having an adequate level of health literacy. A patient’s health literacy influences their understanding of their condition and predicts how well they retain health information such that the lower their health literacy level, the less information they retain. Patients with low health literacy, therefore, require different educational materials than patients with adequate or high health literacy. Current patient education efforts are falling short, leaving patients with low health literacy at a disadvantage and without the information they need to properly manage their disease (Williams et al., 1998). This is notable when considering that 43% of American adults have only basic or below basic reading skills and 36% of American adults have limited health literacy (Erby et al., 2008).

Human factors solutions to differences in health literacy To accommodate the literacy levels of the population, educational resources must be written at appropriate reading levels. One way to accomplish this is to evaluate the proposed text of the resource to assess the reading level required for full comprehension. This assessment can be used to determine how the reading level of the resource compares to the actual reading level of the target population. For example, the average adult in the United States reads at a fifth to sixth grade reading level. The Simple Measure of Gobbledygook (SMOG) Readability Formula is an evaluation tool that can be used to assess texts written in the United States by evaluating text based on the number of words in the sentences and the number of syllables in the words (Mc Laughlin, 1969). The formula returns an estimation of the grade-level reading ability that would be required to understand the text, based on the English language and the US education system. At a minimum, patient-facing educational resources in the United States should be readable at a fifth to sixth grade level, and outside the United States, should be written at the average reading level of those populations. More generally, readability assessments designed for the primary language of the target population should be used to ensure that any patient education material is written at an appropriate level. Accommodation of a spectrum of health literacy levels can also be assessed by first measuring a patient’s health literacy

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level and then observing their interaction with a resource. The Test of Functional Health Literacy in Adults (TOFHLA) assesses health literacy and numeracy, and can be used to understand how levels of health literacy influence interaction with an educational resource (Mc Laughlin, 1969). The SMOG and the TOFHLA are only two examples of tests that could be used to evaluate the readability of patientfacing content and its effectiveness across literacy levels. Other variations of readability, literacy, and numeracy tests exist (Aguirre et al., 2005). An ideal platform could accommodate and adjust for users with a range of literacy levels, providing simplified language to those who need it and allowing for extra detail and complexity for those who may want it. While these strategies to assess reading level would help to ensure that materials were comprehensible, the best solution would be to have patients directly involved in the writing of the materials; codesign with patients would allow the educational materials to be written with a full understanding of the patient perspective.

Considering usability and navigation of patient education materials A well-designed educational resource will ensure that patients can find information relevant to their treatment and will be logically organized, with complex topics building on simpler ones to aid comprehension. For example, when considering genetic testing for cancer treatments, it would not be useful for patients to read about protein expression before reading about genes, as understanding protein expression requires an understanding of genes. To assess these aspects of an educational resource, usability techniques such as a heuristic evaluation can be applied. Heuristic evaluation involves usability experts applying standard usability criteria to a device or platform, assessing whether it violates usability standards (Baker et al., 1999). Experts compile a list of violations and suggestions for improvement that can then be used to improve the device or platform, increasing usability and navigability. In addition to a heuristic analysis, other usability techniques that could be used to assess educational resources include cognitive walk-throughs (Jaspers, 2009), think aloud interviews (Richardson et al., 2017), and iterative design with end-user testing and focus groups (Richardson et al., 2017). Cognitive walk-throughs can reveal discrepancies in the logic of the organization of information; in these analyses usability experts navigate through a platform with a particular goal in mind, identifying issues with usability as they go. Think aloud interviews and iterative design with end-user testing help to ensure that patients are included in the design process by getting their feedback and using it to inform the development of the end product. While not all of these techniques may be necessary for a single educational resource, these techniques can help ensure that the end product is user friendly and meets the patient’s information needs.

Composite effectiveness Considering readability, content, and usability are vital, but it is also important to consider the composite effectiveness of an educational resource. A website may contain readable content that covers all of the important concepts and is laid out in a user-friendly way, but it is essential that the overall effectiveness is also tested. To do this, it would be necessary to test the knowledge of a wide variety of patients before and after interaction. Efforts should be made to ensure that resources address these patient needs across the full spectrum of scores, from low health literacy to high health literacy. Feedback about patients’ satisfaction and likelihood to use resources can also be valuable to assess future use and sustainability. If only patients with high health literacy are satisfied with the resource, then it is not effective for all patients and changes should be made. To illustrate the potential of using reading level assessments and usability techniques, consider a cancer decision support website created by Giuse and colleagues (2016). Three versions of the website were tested, with varying reading levels. The first version was geared toward researchers and clinicians, at a typical reading level of genetic information given to patients. The second version was the original text, but with added hyperlinks to videos that described the more complex terms which was codeveloped with patients. The third version was translated to a sixth grade reading level, while still including necessary videos for complex terms that were unavoidable. This version was also reformatted to make it visually more readable. The authors assessed knowledge scores before and after participants interacted with the decision support aid to assess effectiveness. Participants who received the translated version improved significantly more than the participants receiving the original text; improvement using the original text with the hyperlinked videos was intermediate. This study suggests that translating the material to a sixth grade reading level and including links to videos explaining complex terms provides a robust and scalable way to improve patient understanding of content (Giuse et al., 2016). However, to demonstrate that this approach helps those with low health literacy requires further testing, and there was no assessment of website usability or patient satisfaction. This educational resource is clearly a positive step in the correct direction, but more needs to be done.

Limited English proficiency Another important consideration for patients is their level of English proficiency, or, in non-English speaking countries, their proficiency in the language most commonly used. In the US low-English proficiency (LEP), patients are less likely to receive patient-centered care, with more than half of surveyed providers indicating that they had ­difficulty

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engaging in patient-centered conversations with LEP patients (Karliner et al., 2011). For example, it has been demonstrated that Spanish-speaking Latinas were nearly five times more likely to have an unmet need for discussion regarding genetic testing in breast cancer when compared to white patients (Jagsi et al., 2015). Specifically, Spanishspeaking Latinas were more likely to have a high desire for genetic testing and no discussion with their providers, which the authors suggested was due to the providers determining that there was no risk meriting genetic testing, but not communicating that to the patient (Jagsi et al., 2015). The comparatively high desire for genetic testing among Spanish-speaking Latinas also demonstrates the importance of considering race and ethnicity to enable patient-centered care. This, and other similar examples highlight that different races and ethnicities face different challenges when it comes to receiving patient-centered care (DeCamp et  al., 2015).

Patient-facing technology As technology advances, health care is moving away from traditional care, to a model in which patients are more frequently interacting with the system, via personal health records, patient portables, wearables, and other devices. In addition, the proliferation of telehealth is further changing the way care is delivered directly to patients (Institute of Medicine, 2012). As such, there is opportunity, and imperative to leverage and appropriately design and develop these emerging technologies to improve patient care. To do so, however, it is important to consider many of the aspects already highlighted, especially usability of any technological resource, integrating codesign and codevelopment with patients and families. To illustrate, consider cancer survivorship care coordination. Care for cancer patients is complex, and remains so even after they have completed active treatment. For many, the transition from acute care back into routine care and surveillance can be difficult. There are multiple stakeholders involved in the process, from the oncologists who care for the patient during active treatment to the primary care providers responsible for subsequent surveillance and care. While the patient should be at the center of this process, it can be difficult for survivors for instance to access all of their health records. This limits their ability to fully engage in the coordination of their care and to be empowered in the process. The IOM has suggested that all cancer survivors receive survivorship care plans upon completion of active treatment to help with the transition and to facilitate subsequent care coordination, but the system for administering such a plan has not been effective. Tevaarwerk and colleagues (2014) applied human factors engineering to this problem and examined aspects of the sociotechnical system

that created barriers affecting survivor care coordination. To make survivorship care plans more accessible, these researchers integrated them into the electronic medical record and gave patients access to that system. The survivors who had access to this reported the plans were usable and that they were satisfied. In addition, most of the survivors did access their electronic care plans, which led them to further external resources.

Recommendations The science of human factors can be a key catalyst and driver of change as we move toward making health care more patient centered, and improve outcomes. This hinges on the integration of human factors expertise and methodologies in key ways: 1. Inclusive design of all patient-facing technologies— understanding the needs of all potential groups of user populations and based on an iterative design process, target those groups for testing to incorporate the needs of diverse patient populations into new technologies. 2. Advance existing IT to meet patient needs—focus on expanding HIT applications to reach consumer, patients, and families according to their needs and preferences. Redesigning patient-facing technology to meet user needs by engaging all stakeholders including patients and families, while reimagining provider workflows to integrate these changes. 3. Incorporate the expertise and experience of patients and their families and keep them engaged during all phases of design, contemplation, and decision making.

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