This article details best practices to help healthcare organizations to understand consumers across the spectrum of care and to engage with patients and equip them with accurate, accessible pricing information.
In response to 2 articles recently published in The American Journal of Managed Care, “Characterizing Health Plan Price Estimator Tools: Findings from a National Survey” (February 2016), and “National Estimates of Price Variation by Site of Care” (March 2016), by Higgins et al, this editorial details best practices that healthcare organizations should employ in an effort to improve pricing transparency, enhancing patient engagement, and ultimately change patient behaviors to improve patient outcomes. Specifically, this article details a fourfold framework to help healthcare organizations, including both payers and providers, to understand consumers across the spectrum of care. As a part of this, key ways of leveraging technology to observe, segment, and communicate with patients to elicit positive behavioral change and improved outcomes, are discussed.
Am J Manag Care. 2016;22(4):e122-e124
Two articles recently published in The American Journal of Managed Care, “Characterizing Health Plan Price Estimator Tools: Findings from a National Survey” and “National Estimates of Price Variation by Site of Care,” by Higgins et al, highlighted a growing need for price estimator tools and showcased the reality that there is a price differential for individuals across sites of care for the same healthcare service.1,2 Keith Roberts, Vice President of Engagement at Change Healthcare Engagement Solutions, responds to these articles by delving further into the real best practices and key steps for engaging with patients and equipping them with pricing information that is accurate and accessible.
Healthcare shopping and plan selection are topics the average person does not necessarily want to think about—in fact, they may hope they will never have to use their health insurance. Nevertheless, although it sounds antithetical and naïve to those of us in healthcare, this is a common mindset we have observed while gaining understanding of consumer behavior.
The average consumer enrolls in a plan without reading the fine print and they also may choose providers without any consideration for price. Further, they stay with the default plan option or continue to go to a provider out of habit, not necessarily because it is the best option for them. As a result of ignoring the details, confusion can ensue once they enter the continuum of care: they might not know what is covered or not covered, for example. Once caught in this web, the consumer may become frustrated, discouraged, and possibly bitter; they may even forgo the care that they actually need due to decreased trust in the healthcare system.
With this in mind, Change Healthcare Engagement Solutions employs a fourfold framework to help healthcare organizations, including both payers and providers, understand consumers across the spectrum of care.
Solving all problematic aspects of the healthcare industry is impossible, but empathetic observation of individuals’ interactions with the system can reveal meaningful opportunities for reform and advancement. Those opportunities exist even before an episode of care, such as during plan selection, and proactively engaging for ongoing care, such as reminders for medication adherence. This type of understanding is the first step to enabling smarter healthcare.
Additionally, although it is easy to rely on the latest and greatest technology (and we do use it!), nothing replicates real in-person conversations. Once Change Healthcare Engagement Solutions discussed patient journeys from open enrollment to a medical event and through billing reconciliation, 3 things became abundantly clear: 1) people generally don’t know where to go for answers; 2) the more they learn, the more confused they may become, such as understanding why an in-network doctor would make a referral to an out-of-network specialist; and 3) their personal needs are disconnected from the standard processes in place. After observing a myriad of consumer behaviors with commissioned research from a third-party agency, we also discovered 2 key traits that influence the design of effective decision-support methods: trust and knowledge.
How do trust and knowledge impact health shopping moving forward? We realized that individuals fall into different behaviors and attitudes based on their level of trust in the healthcare system and their providers, as well as their knowledge of healthcare in general. Specifically, as we segmented cost, quality, convenience, and consumer experience outcomes on the parameters of trust and knowledge, a highly predictive framework of consumer behavior emerged, as shown in the Figure.
Once they are placed into these segments, each group responds consistently through an episode of care. This could include questioning everything in the process for every bill or treatment (low trust/high knowledge) or not checking or reviewing anything (high trust/low knowledge). Further, individuals in these segments performed consistently even across traditional demographic and diagnostic segmentation. Overlaying consumer behavior insights helps us further predict how people will react and the effort they put forth for seeking care, paying their bills, or reconciling discrepancies.
Understand and Respond
After observing individuals across the consumer journey of shopping, receiving, and then paying for their care, the next step is to respond with ways to actually improve the health shopping experience. Providing individually relevant decision support at different points in the continuum of care will reduce effort for the patient, facilitate conversations with payers and providers, and improve outcomes. To that end, effective healthcare engagement needs to improve 5 key demands:
Relevant experiences that account for these 5 elements will prove to consumers that a health plan or provider is there to help, not frustrate.
Achieve Improved Outcomes
After observing and monitoring the consumer journey to see what can be realistically achieved and improved, mix those 5 elements with relevant tactical strategies for better outcomes. The tactics should be robust and comprehensive.
To improve healthcare shopping, people have to be at the heart of any solution. In this regard, we can borrow a page from the leading retailers and segment users based on demographic and behavioral data. Consumer-centered empathy can be achieved even through technology and human-centered design. Communication campaigns must be optimized based on the consumer’s preferences, and that, in turn, will make it easier to understand and shape the way these individuals respond to information. Simple, timely and individually relevant communications should fit the user’s personality type, as one size doesn’t fit all: although text messages may be effective for some, they may not be for others, and some may prefer a phone call over e-mail.
Behavioral economics is another tactic that can profoundly influence communications and design. Studies show that humans make decisions with emotional biases, rooted in psychology and in their past experiences.3-5 Creating positive interactions with health plans and providers will lead to better health shopping habits in the future. Behavioral economics accomplishes that.
Within a culture of trust and helpfulness, the aforementioned tactics will help consumers become more comfortable and informed, and subsequently, make better decisions—such as with plan selection and locating high-quality, best-value providers—earlier in the process. It is important to also remember that healthcare shopping is more just than about price; it is also about creating better consumers and reinforcing their “shopportunities” along a continuum of care. Effective engagement helps consumers mind the gaps and educates them on potential pitfalls along the way. With faithful monitoring and observation, it is possible to understand the stumbling blocks for consumers in a certain episode of care. If health plans or provider systems can recognize these on the front end, we can help consumers to prepare and navigate around these issues before they get hit with unexpected healthcare costs, and we can decrease the potential for frustration before it begins.
Achieving this goal requires a lot of time and investment, both from the consumer and from health plans. However, behavioral change, on both the part of the provider and the consumer, can lead to real results, and begins with simple, smart health shopping that spans the full continuum of care.
Author Affiliation: Change Healthcare, Nashville, TN.
Source of Funding: None.
Author Disclosures: The author reports no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design; acquisition of data; analysis and interpretation of data; drafting of the manuscript; critical revision of the manuscript for important intellectual content.
Address correspondence to: Keith Roberts, MBA, Vice President of Engagement, Change Healthcare Engagement Solutions, 216 Centerview Dr, Ste 300, Brentwood, TN 37027. E-mail: email@example.com.
1. Higgins A, Brainard N, Veselovskiy G. Characterizing health plan price estimator tools: findings from a national survey. Am J Manag Care. 2016;22(2):126-131.
2. Higgins A, Veselovskiy G, Schinkel J. National estimates of price variation by site of care. Am J Manag Care. 2016;22(3):e116-e121.
3. Lempert, KM, Phelps EA. Neuroeconomics of emotion and decision making. In: Glimcher PW, Fehr E (eds). Neuroeconomics: Decision Making and the Brain (2nd ed). Waltham, MA: Elsevier; 2014: 219-236.
4. Santos LR, Rosati AG. The evolutionary roots of human decision making. Annu Rev Psychol. 2015:66:321-347. doi: 10.1146/annurev-psych-010814-015310.
5. Zeelenberg M, van Dijk WW, van der Pligt J, Manstead ASR, van Empelen P, Reinderman D. Emotional reactions to the outcomes of decisions: the role of counterfactual thought in the experience of regret and disappointment. Organ Behav Hum Decis Process. 1998;75(2):117-141