Consumer changing perceptions of healthcare

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To support consumers in those changes, the healthcare ecosystem would likely benefit from accelerating the shift toward making care personal and convenient, using omnichannel methods to reach consumers when and how they want, and improving transparency to support decision making. In this article, we explore five actions that healthcare companies can consider to help improve their engagement with consumers:. While established healthcare players are moving to address these challenges, investors are also backing start-ups in search of innovative solutions.

Nina Chiu, Alex Kramer, and Aditya Shah, midyear digital health market update: Unprecedented funding in an unprecedented time , Rock Health, July , rockhealth. Incumbent payers and providers can consider moves to support consumers in their search for high-quality healthcare. In doing so, they can potentially position themselves to reinforce and build their customer bases as the United States emerges from the pandemic.

The pandemic has influenced how consumers view and consume healthcare. We have observed several key changes. In a McKinsey survey, around one in five respondents reported lower physical wellness than before the pandemic, while around one in three reported lower emotional wellness. Among employees who reported a decrease in employment hours since the start of the pandemic, 32 percent indicated that they exercised less and 27 percent indicated that they gained weight.

More than one in three individuals in the group also reported high levels of distress relating to the pandemic, which was nearly eight percentage points higher than the rest of the population. In response to health concerns related to the COVID crisis, more than one in three consumers have demonstrated that they are willing to delay healthcare if they do not feel that physical locations are safe. To allay their concerns, providers and payers can consider ways to provide seamless and integrated physical and virtual care.

The COVID pandemic has shifted attitudes toward telehealthcare across stakeholders, accelerating the trend toward virtual healthcare. In , 3 percent of survey respondents reported having a telemedicine appointment. In February , 24 percent of survey respondents reported that their latest medical appointment was conducted through telephonic or virtual means.

Further, many consumers may prefer virtual healthcare for mental- and behavioral-healthcare appointments, with 47 percent of consumers reporting that they experienced their most recent appointments virtually and 25 percent reporting that they experienced their most recent appointments by phone. That trend is likely reinforced by the shifting attitudes and policies of other healthcare stakeholders, including providers, payers, and regulators. Before the COVID pandemic, only 4 percent of providers reported that they used telemedicine technology for follow-up care—in part because of a lack of parity in reimbursement compared with in-person healthcare.

Providers said in that they are now using telehealthcare methods more and viewing it more favorably. McKinsey Physician Survey, At the same time, healthcare reimbursement is changing to improve its economics and the care covered, both of which are critical to sustained provider use. The COVID crisis has had an impact on how consumers think about the healthcare plans they are using and purchasing, with them reconsidering their options. The economic disruption caused by the crisis has resulted in many consumers losing healthcare-insurance coverage.

Of that group, 39 percent had not yet determined if and how to get coverage. Our research has found that the pandemic is influencing consumer decision making about which healthcare plans to select. While economic uncertainty may likely contribute to consumer demand for more affordable healthcare plans, the health crisis is also creating a need for better coverage and plans that are more responsive to the pandemic. That new demand illustrates how payers can consider improving the personalization of consumer interactions and product recommendations to match divergent consumer needs.

Of the 20 percent of respondents without a primary-care provider PCP , nearly one in three reported an increased interest in obtaining one. Healthcare payers and providers have an opportunity to serve the changing needs of consumers while potentially setting themselves up for growth when the pandemic ends.

They can consider five actions to pursue those opportunities. Healthcare companies should consider the needs of the whole person. Both unmet social needs 14 Respondents who indicated high levels of unmet social needs, stress, and sleep deficiency were 1. Respondents with multiple unmet social needs and self-reported poor mental health were around 2. The relationship between social needs and physical health is important, as more than two in five individuals have at least one unmet social need.

The proportion varies by type of health insurance, with 65 percent of respondents with Medicaid coverage reporting at least one unmet social need, compared with 31 percent of those with Medicare coverage. The COVID pandemic has highlighted the need to focus on whole person health and to address the behavioral, social, and economic vulnerabilities of the healthcare system. Given the disproportionately high impact of unmet social needs on certain races and ethnicities, addressing basic needs will also be a critical step toward health equity.

In the McKinsey Consumer Health Insights Survey, 51 percent and 53 percent of Black and Latino respondents, respectively, reported at least one unmet social need, compared with 39 percent of white respondents. Moreover, 70 percent of Latino and 63 percent of Black respondents said they were satisfied with their healthcare-insurance company, compared with 73 percent of white respondents, while 69 percent of Latino and 76 percent of Black respondents are satisfied with their PCPs, compared with 81 percent of white respondents.

The COVID pandemic has highlighted the need to focus on whole-person health and to address the behavioral, social, and economic vulnerabilities of the healthcare system. For instance, people with behavioral-health conditions make up 25 percent of the general population, but 47 percent of those are at risk for severe COVID In addition, although only 15 percent of people live in areas with significant unmet social needs, 28 percent of COVIDrelated deaths occurred in those areas.

To address those issues, healthcare payers and providers could consider the following initiatives:. Leading healthcare payers, healthcare providers, and employers are investing in start-ups and partnering with innovative vendors to deliver complete healthcare solutions to consumers. Some examples of vendors include Cityblock Health, which offers community-based care for low-income consumers, and Quartet Health, which enables integrated care for patients with chronic medical and behavioral-health conditions.

One in four survey respondents reported that they were frustrated by higher-than-expected healthcare costs, despite many years of efforts toward improvement by healthcare companies.

Higher-than-expected cost of service was the number-one frustration with payers and the number-two frustration with providers. A perceived lack of cost transparency can potentially drive consumer behavior. Members of healthcare payers that are considered the best in class for consumer experience are 58 percent less likely to report postponing care because of a lack of information than are members of less-effective payers.

Debra L. These benefits include more accurate and complete information, as well as better communication and coordination among multiple care providers. Using health IT can improve quality of care for many types of patients, including vulnerable populations, such as the elderly and the chronically ill. HIE across disparate systems allows clinical information to follow patients as they move across different care settings, whether or not each organization shares an affiliation.

HIE is expected to transform the nation's healthcare system through access to patient data from EHRs to support care provision and coordination and improve care quality and population health. Although the utilization of health IT holds great promise, potential threats to wide-scale implementation exists. Consumers have consistently voiced concerns about a lack of trust in health IT systems—including the privacy and security of EHRs and information exchange.

The purpose of this article is to examine consumer perceptions of health IT utilization and benefits through an integrated conceptual framework that considers perceived benefit or value, trust, perceived ease of use, HIE familiarity, Internet usage, and EHR utility.

In the following sections, the conceptual framework and key constructs are outlined. Next, we describe the methods, survey instruments, and the analysis employed for the study. Subsequently, the results, discussion, and implications for practice are presented. This section discusses constructs of interest that emerge from the framework. First, the Theory of Planned Behavior is considered. The first of these considerations is behavioral. Finally, control beliefs ie belief in the existence of factors that can enable or inhibit the performance of the behavior guide behavior.

Taken together, these 3 considerations can have a significant impact on human action or inaction. Next, the technology acceptance model TAM is examined. In turn, attitudes guide the intention to perform the action; intentions subsequently influence behaviors.

TAM is frequently applied to understand how consumers respond to IT. For the purposes of this study, the constructs under consideration that contribute to behavioral intention intention to use technology and, subsequently, actual behavior use of technology are as follows: perceived benefit of change ; compatibility with values, beliefs, past history, and current needs; and perceived ease of use. This construct examines the social aspect of IT adoption.

The extant literature indicates that most end users are not averse to the available technology itself. However, they are unlikely to use systems that prove inadequate or that interfere with their values, aspirations, and roles.

A subcomponent of the compatibility construct is user trust , which is considered a crucial factor in IT research. Many IT users question potential outcomes of technology utilization. In response, vendors should aim to enhance consumer trust in their innovations. These include: easy to use; clear and understandable; easy to become skillful with the system; easy to get the system to perform desired tasks; flexible; requires little mental effort; tasks are easy to remember; does not demand a lot of care and attention; navigable.

Survey development was based on the literature and centered around 3 overarching concepts: perceived benefit or value, trust, and perceived ease of use. The survey for this study was conducted between January and April Respondents consisted of Virginia residents age 18 and over. In order to capture a wide cross-section of Virginia residents, a multi-mode fieldwork approach was used. The approach, outlined below, included Internet, paper, and telephone surveys to ensure that Virginia residents in various locations had an opportunity to participate in this study.

To avoid survey bias, online and telephone surveys rotated questions. Survey incentives were not offered to participants. All participants answered affirmative to the consent prior to participating in the survey. This online fieldwork was performed using Virginia residents in the eRewards panel.

Respondents who were interested in taking the survey were given the paper survey along with a prepaid business reply envelope to mail the completed instrument. A total of surveys, per office, were distributed. This represents a This survey used a random digit dialing telephone sampling approach adhering to the most current industry guidelines and regulations.

The final sample consisted of usable consumer surveys for analysis. Lastly, familiarity with HIE not at all familiar, familiar and survey method online, phone, paper were also included as independent variables in this analysis. Principal factor analysis was used to determine meaningful components.

An eigenvalue of 1 was used as the cut-off point, which resulted in 8 key factors. In addition to the principal factor analysis, the literature provided theoretical insight on constructs and sub-categories to use in the analysis. Table 1 depicts each construct, sub-category, and survey question. Table 1. Mapping of survey questions to theoretically driven constructs and sub-constructs based on principal factor analysis.

Sharing my medical information can save my life in an emergency by providing my doctor with accurate information about the medications I take and the conditions I have. Electronic medical information from all of my doctors would provide a more accurate medical history than I could provide on my own. Improve my overall health through better care coordination between my doctors.

I can restrict the ability of my health insurance company to access my medical information. I worry about security and privacy of my medical information a. Electronic medical records might be too difficult to use a. I should be able to easily add permission for a family member to view my medical information.

I should be able to easily name someone who can make medical decisions for me if I am unable to make medical decisions on my own.

I should be able to easily correct wrong information in my electronic health record. A factor-based scale was developed for each sub-construct by calculating the average score for each sub-construct. Each question was answered by respondents using the Likert scale, where 5 was strongly agree and 1 was strongly disagree. The survey questions for each sub-construct were averaged using only the number of non-missing variables.

This sum was then divided by the number of non-missing variables. The averaged scores allowed us to interpret each sub-construct using the same scale respondents answered in. In other words, each sub-construct was scored from 1 to 5, or strongly disagree to strongly agree. To dichotomize the results, any sub-construct score of 4 or 5 agree or strongly agree was combined into a single category that demonstrated agreement with the sub-construct.

Lack of agreement with the sub-construct was defined as any score below 4. Demographic characteristics of the study population were compared with determine significant differences between respondents whose physicians used EHRs versus physicians who did not use EHRs Table 2.

Multivariable logistic regression that controlled for demographic characteristics of respondents was performed to determine adjusted odds of agreeing with selected opinions of HIE Table 4.

Table 2. The bold face type represent significant values. Reference groups were not checking each category, as multiple categories could have been picked for each question. Table 2 presents demographic information for survey respondents. Overall, a majority of survey respondents were greater than 45 years old The majority of respondents also had private insurance More respondents whose physicians did not use an EHR system were within the 25—44 year age group Results indicate that respondents whose physicians used an EHR system were significantly more likely to agree that were was a perceived benefit with HIE [in emergency care A large majority of respondents After controlling for independent variables on respondent demographics, household demographics, and survey method, respondents with physicians who used an EHR system had greater odds of perceiving the benefit of HIE in emergency care [odds ratio OR 1.

Wen et al 45 also found that respondents aged 65 years and above were more likely to rate HIE as important when compared with other age groups. Those with children in their household reported experiencing less need to control access to their health information than respondents with no children in the household.

Interestingly, those who completed a paper survey were much more likely than online survey respondents to see the benefit of use in emergency care, administrative work, and provision of care. Females were generally more likely than males to see the benefit of EHRs in administrative work and expressed more trust in HIE than males.

This finding contradicts several studies that have reported women are less likely to use and trust health IT. Patel et al 46 also found college education increases potential use and understanding of health IT. While other studies have found that frequent use of the internet leads to greater levels of support and potential use of health IT, 12 , 46 , 47 our study did not find any such differences.

Participants who lacked familiarity with HIE saw less benefit to care provided and were less trusting when compared with those familiar with HIE. However, the paper survey respondents also expressed more need to control their health records and saw a greater need for HIE.

This indicates that while paper survey respondents understand the potential benefit of the HIE, they desire more control and security measures. Steps were taken to mitigate study limitations; however, some remain. Participant sampling was conducted to achieve an amount without regard for age or race. Even though the resulting sample size was large, this study may lack generalizability to other age ranges or other races. Survey questions were based on theoretically driven constructs as mapped in Table 1 ; however, the perception of bias may exist.

Lastly, challenges with studies that try to understand perspective, consumer or otherwise, can offer findings that are not generalizable. This finding resonates with previous research on the topic of provider buy-in to the value of health IT. For instance, Ancker et al 25 found that physicians using EHRs were more likely to believe EHRs could improve the quality of provided care. Providers can increase consumer trust through improved care cost and quality, consumers can increase their knowledge and awareness of, and drive the use of, EHRs and HIE in various care environments, and vendors can use these study findings to create systems that instill consumer trust as well as more user-friendly interfaces that promote consumer and provider collaboration across the care continuum.

Moving forward, the authors of this study join other scholars in recommending that HIE vendors and healthcare providers improve consumer trust 22 and control by educating consumers on the benefits of health IT and by protecting against unauthorized viewing of EHRs. The authors acknowledge the contribution of Randyl Cochran in formatting this manuscript for submission. Additionally, the authors thank the reviewers and editors for their review of this manuscript.

Their suggestions greatly strengthened the paper. This research was from data collected during a project associated with Cooperative Agreement with the Office of the National Coordinator for Health IT. SF conceived of and designed the project and is responsible for data acquisition. GB contributed to the data analysis. SF, GB, and BS all made substantial contributions to the data interpretation and manuscript writing and editing.

All authors SF, GB, and BS give final approval of the version to be published and agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Nerney C. Survey: U. Secondary Survey: U. Accessed April 8, Primer in health information exchange for the emergency physician: benefits and barriers. South Med J ; 6 : — 8. Google Scholar. Health care consumers' preferences around health information exchange.

Ann Fam Med ; 10 5 : — Leventhal R. Accessed April 10, Time for a patient-driven health information economy? Usability testing of a novel system for patient-provider messaging in a health information exchange environment. The association between health information exchange and measures of patient satisfaction. Appl Clin Inform ; 2 4 : — Yaraghi N. An empirical analysis of the financial benefits of health information exchange in emergency departments.

J Am Med Inform Assoc ; 22 6 : — Int J Med Inform ; : 98 — Consumer opinions of health information exchange, e-prescribing, and personal health records. Am Health Inf Manage Assoc ; 12 : 1e.

Esmaeilzadeh P , Sambasivan M. Healthcare consumers' attitudes towards physician and personal use of health information exchange. J Gen Intern Med ; 26 : — The effect of access to electronic health records on throughput efficiency and imaging utilization in the emergency department. Health Serv Res ; 53 2 : — Cipriano PF.

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Our results, therefore, corroborate the broadly held view that consumers have less free time than before, at least in perception.

But here, once again, a deeper cut of the data tells a different story. While it is a fact that the total hours worked in the United States has risen by 43 percent since , the increase has been driven by the growth of the workforce. When we factor in the increased working-age population and labor force participation over the years, the average hours worked per person has fallen by 9 percent since , which means people are spending less time working. According to the Deloitte Consumer Change Study , the time not spent at work is only being partially redirected toward other nondiscretionary activities, such as personal care and household-related events, which rose 13 percent and 8 percent, respectively.

In fact, the amount of time spent on leisure by the average consumer has risen. Available discretionary time is up overall, with time spent on leisure and sports increasing 5 percent between —, or an additional 14 minutes daily, despite what consumers may be feeling. One activity to which consumers have not been devoting as much time as in the past is shopping. According to the US Census Bureau, , the number of minutes spent shopping has fallen by one-fifth over the past 13 years.

The average consumer is spending 20 percent fewer minutes shopping every week. Today, more than ever before, consumers have more efficient ways of shopping, so this decline may not actually reflect a disinterest in shopping itself. This decline in time spent shopping is accompanied by data that shows certain cohorts—such as rural, male, and high-income consumers—are shopping at fewer places as compared to So, a data-backed analysis of how the consumer is spending their time shows that contrary to the popular perception of the stressed and harried consumer, the reality is that people today have more discretionary time than ever before.

What appears to be happening is that the consumer is not able to relax during the increased discretionary time as having to choose between the options competing for that free time is exhausting! April—December Trips to hospitality, travel, and entertainment destinations rose by 8 percent in Trips to convenience, quick service restaurants QSR , and fuel stations jumped 16 percent.

Even brick-and-mortar retail saw a 2 percent increase in traffic. The biggest gains were seen in grocery-related trips, which grew 7. For example, the data reveals that the mix of trips by high-income consumers is skewed 2. More importantly, gains and losses in shopping trips are concentrated among a fraction of the ,plus stores in the United States, with 22 percent of the stores accounting for 90 percent of the gains, and 16 percent stores responsible for 90 percent of the lost trips.

Additionally, the trends related to traffic are not homogeneous by market. The markets hit hardest by declining traffic are also highly consolidated, with the 15 fastest-declining markets largely centering around West Coast urban centers and the 15 fastest-gaining markets centered in the Southeast and Texas figure 8.

Further, and perhaps not surprisingly, e-commerce penetration in those geographies is highly correlated with a decrease in foot traffic. The West Coast Markets had an average e-commerce penetration of 25 percent while the Southeast and Texas where foot traffic growth was strongest had an average e-commerce penetration of 20 percent.

On-mall shopping is on the decline But while conventional wisdom holds that shoppers are shifting their trips away from malls, this is only half the story. What our location data revealed is that this shift away from malls is happening fastest and most dramatically among the older and higher-income cohorts—groups that have traditionally been the core shopper in malls.

According to this narrative, only experiential-oriented retail can get them off their sofas. While there is some truth in the notion that the consumer is going out less, it needs to be viewed through the lens of income.

Changing consumer values have garnered a great deal of attention in recent years. Much has been said and written about how consumers seem increasingly focused on where products are sourced from, child labor in product development, supply chain transparency, sustainability, and other ethical matters. But are these factors determining their decision-making process?

To this end, the survey helped us understand the changing consumer value set. We found that consumers still look to value, product, and convenience as the overwhelmingly important attributes while making decisions figure 9. This finding is in line with the values that have been held by generations of US consumers.

In fact, often-noted attributes of the modern consumer like core values and personalized experiences ranked lowest among their priorities. This preference holds true no matter how we slice the data—along the lines of age or income.

Consumers across the board prioritize price, product, and convenience the most while evaluating purchasing options while alignment with core values and personalization matter the least in their retail experience. Even high-income millennials, who may be the outliers, follow this trend. While what matters to consumers may not have changed significantly, we must remember that the marketplace today is a competitive battlefield.

What is convenient or what offers value is relative, and hence these parameters are likely constantly changing in the mind of the consumer. An analysis of the data and trends across demographics and consumer behavior brings to the surface a nuanced reality: The consumer is changing, but not necessarily in the ways we usually hear or think of.

The consumer is changing because the environment around them is evolving. If retailers and consumer product companies want to cater effectively to changing consumer needs and identify new pockets of opportunity, it is imperative for them to understand the demographic, economic, and competitive milieu that the consumer is reacting to. The consumer is changing because of the economic constraints they are operating under—including the rise in nondiscretionary expenses such as health care and education—and the growing bifurcation between income groups, which are having an impact on spending patterns.

This is especially true of the low-income, middle-income, and millennial categories. However, the wallet share they spend on various categories—food, alcohol, furniture, food away from home, and housing—more or less remains constant. Also, despite the rise in online shopping, consumers are going more places than in the past. The consumer is changing in reaction to the proliferation of competitive options in the market.

This change has been made possible by technology, coupled with reduced barriers to entry, and the emergence of smaller players who are creating niche markets with more targeted offerings. We must not confuse choice with change. In many ways the consumer of today is like the consumer of yesterday, they are a creature of the pressures they are under, coupled with the choices they have available to them.

View in article. Kasey Lobaugh et al. William H. Kim Parker et al. Ann C. Cindy M. Vojtech, Benjamin S. Kay, and John C. Quoctrung Bui and Claire C. Lobaugh, Bieniek, Stephens, and Pincha, The great retail bifurcation.

Deloitte analysis of the Euromonitor Apparel Report. Analysis of Deloitte CCI transaction index. Analysis of Deloitte CCI location index.

Deloitte's Center for Consumer Insight CCI combines customized research with differentiated data sets to develop a deep understanding of consumers through best-in-class analytics.

CCI was built with a belief that true consumer insight must come from a holistic approach that starts with an outside-in view and utilizes a broad mix of data sources, moving beyond a singular reliance on traditional survey research to leverage the wealth of data available today.

Kasey consults with clients to strategize against the changing competitive landscape and the rapidly evolving consumer. He focuses on broad business-based strategy that will enable innovative customer experiences, operational scalability, and provide outsized return-on-investment.

He has nearly 20 years of retail and e-commerce operations, consulting, and start-up experience in the United States and abroad. He focuses on working with clients to drive revenue growth through digital transformation and customer engagement. Prior to joining Deloitte, Stephens co-founded and led Bucketfeet, a VC-backed global omnichannel retail start-up that is still in operation today.

As the consumer insight offering leader with ConvergeCONSUMER, a business focused combining consumer data sets with next-generation technology platforms, applied artificial intelligence and machine learning focused on consumer demand prediction to help consumer businesses understand and optimize decision making, Jeff leads the marketplace strategy for consumer insight solutions.

Jeff leads Deloitte's InSightIQ, which specializes in understanding how consumer behaviors are changing by analyzing hundreds of billions of dollars of consumer spending, location, and primary research data. He specializes in marketing, CRM, and loyalty work, and has designed and launched several large loyalty programs besides serving as the chief marketing officer at a variety of large retailers.

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Welcome back. Still not a member? Join My Deloitte. Article 26 minute read 29 May Kasey Lobaugh United States. Bobby Stephens United States. Jeff Simpson United States. The changing consumer: Deconstructing demographic dynamics Are millennials losing economically? Beyond demographics: A deep dive into consumer behavior Consumers: The more they change, the more they remain the same.

Cover image by: Kevin Weier. View in article Kasey Lobaugh et al. View in article William H. View in article Kim Parker et al. View in article Ann C. View in article Cindy M. View in article Ibid. View in article Quoctrung Bui and Claire C. View in article Deloitte analysis of the Euromonitor Apparel Report. View in article Analysis of Skyhook data. View in article Show more Show less. Learn more Get in touch. Download Subscribe. Related content Interactive 3 days ago.

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Log in with an existing site account:. A fourth stakeholder may include distant agencies e. Future research is needed to ask bold questions and explore complex dimensions involving multiple stakeholders and across multiple drivers.

Health and medical decisions differ widely along various dimensions table 1. Depending on the specific attributes of the focal decision, different decision processes e. While most research focuses on specific decision types, extending the focal decision to other and more complex decision types along one or more dimensions may prove advantageous in illuminating the unique psychology driving these decisions. For example, prior research has shown that high-stake decisions and those that carry a more persistent impact generally entail a more deliberative and analytical decision process than lower-stake and one-time, short-lived decisions.

Would the perceived importance of health as a domain compared to, say, finance attenuate these differences, such that more categories of drivers in the 5S framework are considered by consumers and exert greater impact even for low-stake medical decisions? While persistent vs. Another example is health lifecycle. Would the weight consumers put on these drivers change as decisions advance from one health-lifecycle stage e.

How would consumers perceive such dual-purpose products, and how would these perceptions affect their downstream decisions or behaviors? Furthermore, what if these health and medical decisions were made jointly e. And would this social dynamic depend on the heterogeneity of the decision-making unit Yaniv ?

A thoughtful consideration of these rich decision dimensions will help consumer researchers deepen their inquiries, enhancing the generalizability of their theories and establishing meaningful boundaries for their proposed effects.

Depending on the nature and complexity of the health decision that researchers intend to study, a diverse set of methodologies and participant samples may be necessary to lend greater relevance as well as confidence to the findings.

Accordingly, prior research has employed a variety of methodologies, from lab and field experiments Berger and Rand ; Bolton et al. Besides providing triangulation and ensuring greater robustness in the empirical results, these varied methods may be necessary to inject diverse perspectives that help illuminate the complexity of the decision or issue of interest.

Furthermore, rather than deductive or inductive methods, an abductive approach Janiszewski and van Osselaer can prove beneficial for the discovery of novel theories arising from more complex health and medical decisions. Advanced quantitative techniques such as systems modeling and simulation, and the use of genetic algorithms may also be useful in capturing the complexity and evolving nature of these multi-faceted and multiply determined relationships.

While the two previous research directions relate to deepening our understanding of the core drivers of health and medical decisions, particularly for decisions that possess vastly different attributes along the five dimensions, the next two research directions call for broadening the scope of research on health and medical decisions, and improving understanding of the implications of this expansion.

Although much of the research on consumer health has focused on specific, unilateral consumer decisions and outcomes, some of these decisions and outcomes may have other downstream consequences for consumers, specific communities, or the society at large.

These outcomes can have opposing valence or be even unrelated to health, presenting a tradeoff or double-edged sword that necessitates the consideration of multiple perspectives and diverse criteria in evaluating the overall impact.

For instance, consider the findings of Samper and Schwartz discussed above. While setting a high price for drugs and medicine may discourage consumption through lowering risk perception, this pricing strategy can also help prevent abuse of the drug and over-consumption as in the case of antibiotics, whose liberal use may result in adverse health consequences in the long run by making everyone less resistant to new bacterial variants or superbugs.

To what extent should public health policymakers simply rely on market forces to drive prices down in response to reduced demand? As another example, consider the burgeoning use of AI, synthetic drugs, and other technological innovations that standardize the quality of health care and mass produce these solutions [see Wood and Schulman on the importance of understanding how patients respond to five types of disruptive healthcare innovations].

While such advances may render healthcare services more efficient and potentially more affordable and accessible, might they also generate consumer overconfidence, resulting in a boomerang or risk compensation effect Peltzman , such that consumers perceive a false sense of security and take more risks than otherwise warranted e. From a systemic standpoint, might the increasing use of non-human technology-mediated solutions in health care enhance efficiency and accuracy at the expense of reduced human warmth, empathy, and trust—qualities that may be especially vital for certain medical decisions e.

In approaching this research direction, it will be worthwhile to consider several pertinent questions. Third, extending beyond the domain of health care, which other domains are most intimately linked to health and medical decisions e. We live in a world of limited resources. The limitation lies in human resource, natural resource, software and hardware, money and time.

The limitations in health care are startling. Many people cannot access health care because of its cost and their income, others cannot access health care because of geographical constraints, and yet others cannot access health care because they are uninsured.

In fact, an estimated 9. Equally important, we also need to recruit behavioral science to help overcome erroneous perceptions and beliefs as well as psychological hurdles in implementation. Take medical innovation as an example. One way to scale up human providers is to deploy non-human providers more broadly.

Instead of seeing a physician for every minor health concern, an AI doctor can leverage data to provide quick diagnoses and issue prescriptions at scale. However, prior research has shown that consumers are hesitant to trust non-human service providers Longoni et al. In addition, even doctors prefer to rely on their own intuition rather than computerized models Keeffe et al. What makes matters worse is that doctors who rely on computerized aids may be evaluated as less competent by others Palmeira and Spassova ; Shaffer et al.

To scale up automated service providers, therefore, we not only require better technologies but also a much deeper understanding of human psychologies that are holding us back. One such solution is tested in study 9 in Longoni et al.

We encourage future research to explore more innovative and practical ideas and interventions that can help to scale up healthcare accessibility, leading to broader adoption across different segments of consumers and different domains of service providers, so that more patients can benefit from these medical advancements. Scaling up health care also means bringing better-quality care to more consumers.

In this light, research that helps consumers and service providers re-envision what constitutes better-quality care will go a long way toward solving the demand-versus-supply issue in health care. Similarly, holistic care, by definition, aims to address patients' physical, emotional, social, and spiritual needs, restore their balance, and enable them to deal with their illnesses, consequently improving their quality of life Tjale and Bruce Finally, scaling up health care means broadening the reach of health and medical resources, especially for vulnerable consumer segments and underserved communities.

For instance, Du et al. Research on the health and medical needs of specific ethnic groups is desperately needed to increase adoption and ensure fairness as we scale up healthcare resource.

Another example is the aging consumer. Based on a report by the World Health Organization, by , one in six people in the world will be aged 60 years or over. The aging population introduces a unique challenge to health care, as recent research has shown that objective and subjective age are often orthogonal Amatulli et al. More generally, elderly consumers have different health and medical needs than younger adults; on a morbid yet critical note, healthcare systems may have over-emphasized prolonging lives instead of also helping individuals prepare for their exit Gawande Accordingly, it would be imperative for consumer researchers to employ behavioral science to better understand the needs and wants of elderly consumers and to help them achieve healthier longevity and lead more fulfilling lives.

Just like many behavioral science domains, research on health and medical decision-making has long suffered from the WEIRD phenomenon, in which the majority of social science studies have focused on participants who are Western, educated, and from industrialized, rich, and democratic countries Arnett ; Henrich, Heine, and Norenzayan ; Rad, Martingano, and Ginges To meaningfully broaden the reach of health care, our mission as behavioral scientists is to broaden our research—to identify unique psychological barriers as well as unique opportunities to improve health and medical decisions among the consumer segments that are traditionally less studied.

Failure in understanding these unique psychologies will prevent an effective scale-up of our medical resources; success in capturing these unique psychologies and decision-making processes, on the other hand, will benefit our society as a whole. The challenge is huge, and we believe that consumer researchers play a critical role in leading this change. Szu-chi Huang huangsc stanford. Leonard Lee leonard.

Please address correspondence to Szu-chi Huang. The authors thank Carolyn Lo and Jason Zhou for their research assistance on this work. The authors also thank the editors, especially Stacy Wood, for the invaluable feedback and comments.

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Volume Author notes. Journal Article. Szu-chi Huang , Szu-chi Huang. Email: huangsc stanford. Oxford Academic. Leonard Lee. Corrected and typeset:. Select Format Select format. Permissions Icon Permissions. Open in new tab Download slide. Literature examples. Scope of impact High stake versus low stake mundane Botti et al. Decision target Deciding for oneself versus others Botti et al. Open in new tab. Aubree Shay. Where Is the Evidence?