Keywords

1 Introduction

Online consultations between clinician and patient are technically possible and increasingly acceptable in healthcare area. The most recent Health Information National Trends Survey (HINTS) data of US shows that in 2013, 29.6% of U.S. citizens have communicated with doctors or a doctor’s office via the internet (National Cancer Institute, 2014; Jiang and Street 2017). Similar trends have been observed in Europe where the estimated percentage of patients who have approached family doctors or other healthcare providers on the internet is 12.3% in 2007 (Jiang and Street 2017; Kummervold et al. 2008). Online virtual consultation enables patients to access multi-options of doctors anywhere and anytime. However, despite many benefits virtual consultation brings to people especially rural patients, there is a gap between the numbers of patients who are receptive to communicate with doctors via virtual consultation from those who are actually doing so. For many laypersons, all the things that happen ‘inside’ a telemedicine service or online consultation are indistinguishable from magic (Fischer et al. 2014; Van Velsen et al. 2017), which may explain why many people have a trust issue on virtual consultation, especially on diagnosis quality of the consultation. People are uncertain about the quality of online diagnosis, thus they hesitate to use virtual consultation systems in spite of all the theoretical benefits. This paper aims to answer the question of how to reduce people’s uncertainty level on diagnosis quality of virtual consultation.

Virtual consultation refers to a telemedicine service that enable patients to receive treatment in their daily living environment. This paper focuses on the remote video consultation whereby patients remotely select doctors and consult with them via video conferencing, and explores strategies to reduce patients’ uncertainty on virtual online consultation quality based on uncertainty reduction theory. In human communication, uncertainty refers to an interactant’s subjective sense of the number of alternative predictions available when thinking about a partner’s future behavior, for example, or the number of alternative explanations available when thinking about a partner’s past behavior (Bradac 2001). In the context of virtual consultation, we define patients’ uncertainty on consultation quality as people’s feeling unsure on doctors’ past and future consultation behavior.

The uncertainty reduction theory suggests three strategies to reduce uncertainty level: passive, active and interactive. Passive strategies are those in which an informant unobtrusively observe the target person, for instance, by observing videos of the doctor’s previous consultation for patients in virtual consultation. Active strategies pertain to proactive efforts to get to know the target person, without confronting the person, for example, by reading other people’s review about the doctor before virtual consultation, and interactive strategies require a direct interaction between the communication partners, for example, by asking questions or through reciprocal self-disclosure. We propose that patients are more certain about the diagnosis quality if they are provided the demonstration of doctors’ consultation process and other people’s reviews on doctors, according to the three strategies.

To explore strategies to reduce patients’ uncertainty level on diagnosis quality during virtual consultation, we review 12 existing famous virtual consultation systems on how they present doctors’ information, how they demonstrate doctors’ consultation process, and how they enable people to review on doctors. A following content analysis of patients’ reviews on these systems is conducted regarding doctors’ diagnosis quality, and a survey to test our results are conducted. We have the following propositions: (a) Demonstration of doctors’ consultation process can reduce patients’ uncertainty on diagnosis quality. (b) Other people’s reviews especially other doctors’ reviews on doctors can reduce patients’ uncertainty of diagnosis quality. (c) The more natural the consultation is, the less uncertainty people have on diagnosis quality. (d) The number of these strategies is negatively related patients’ uncertainty on diagnosis quality.

This paper focuses solely on conceptual developing process on how to reduce patients’ uncertainty of diagnosis quality on remote video consultation due to time limitation. This paper understands the status of system design to reduce patients’ uncertainty level on diagnosis quality, which can be basis to further research on patients’ physiological and cognitive processes when they visit doctors online, and how these processes are influenced by the revealing of doctors. It explores how to design virtual consultation systems to enhance patients’ trust and certainty on diagnosis quality before actual consultation, which shed a light on future research of online consultation quality. The results can practically facilitate healthcare providers to understand patients’ concerns on diagnosis quality of virtual consultation. They can also guide the design of virtual consultation systems industrially to reduce patients’ uncertainties on online consultation, and consequently to attract more people using these systems. One future direction can be exploring other strategies and design features to reduce patients’ uncertainty not only on diagnosis quality, but also on consultation experiences and so on before actual consultation. The other direction can be investigating how to reduce patients’ uncertainty level in the actual interaction with doctors for better communication, which can promote diagnosis quality as a result. Multi-methodologies can also be applied to test our results.

2 Literature Review

2.1 Virtual Consultation

Technology-supported consultation in healthcare area is viewed by many as at least a partial solution to the complex challenges of delivering healthcare to diverse population especially rural people (Greenhalgh et al. 2016). Telemedicine (or telehealth), as one of these technologies to travel video and audio as a high-definition digital signal from one computer to another for the purpose of direct patient care, can add an additional dimension to patient care by providing a logical extension of existing face-to-face physical doctor-patient consultation (Brooks 2016; Jue et al. 2017; Klaassen et al. 2016; Segato and Masella 2017). Virtual consultation specifically refers to creating a virtual online doctor-patient consultation environment similar as physical consultation with the use of video-conferencing telemedicine technology.

To many, doctor-patient consultation in the context of virtual consultation may be very similar with how they communicate to each other in a physical doctor’s room. Thus, virtual consultation is often overestimated and may be deemed so important that it can very likely replace physical face-to-face consultation at some point in the future. However, the desire to have a face-to-face interaction and not trusting on virtual consultation quality are cited by many patients as reasons not to use virtual consultation services despite the added time and cost to travel to appointments (Gardner et al. 2015; Greenhalgh et al. 2016).

Benefits of Virtual Consultation.

It’s widely accepted that virtual consultation has many benefits delivering healthcare to diverse patients. One of the most well-known and freely available internet video applications to conduct virtual consultation is skype. Previous review of the clinical use of skype provide evidence to support the clinical use of skype (Armfield et al. 2015, Armfield et al. 2012). Armfield et al. (2015) review twenty-seven articles and conclude that skype is reported to be feasible and to have benefits, especially in the management of chronic diseases such as cardiovascular diseases and diabetes. Their results show that skype allows good communication between individuals and health professionals, and is mostly used in developed countries. While not many studies consider the economic effects associated with using skype and similar free or inexpensive tools to do virtual consultation, those that did agree that skype is more economical than face-to-face appointments with savings from avoided travel and waiting (Armfield et al. 2015; Daniel et al. 2012; Travers and Murphy 2014).

The feasibility of clinical use of these tools motives the development of different virtual consultation systems. One famous commercial type is the systems which enable patients to select certified doctors from a sea of options, no matter whether they are familiar with or not, to do virtual consultations online (Greenhalgh et al. 2016; Segura and Bustabad 2016; Zilliacus et al. 2010). With these systems, patients can access professional healthcare anytime and anywhere, without the risk of getting infected by other patients in hospital (Ellenby and Marcin 2015; Greenhalgh et al. 2016; Klaassen et al. 2016).

Besides the benefits above virtual consultation brings to patients, other parties including physicians, nurses, healthcare institutes also receive massive convenience and benefits. Virtual consultation improves the efficiency of physicians, and largely reduces the rate of no-show appointments (Hanna et al. 2012). virtual consultation can complement nursing in cost-effective ways and increase the intimacy between patients and nurses (Reed 2005, Stern 2017). Virtual consultation can also benefit hospitals and other healthcare providers with easier doctor-physicians-specialists-hospitals connection. For example, Patterson and Wootton (2013) carry out a survey by questionnaire of referrers and specialists over a six months period, and find that the patient management and diagnosis efficiency are improved due to the use of telemedicine technology (Patterson and Wootton 2013).

Concerns of Virtual Consultation.

Not all the people use virtual consultation system as they claimed despite all the benefits. One important reason for this probably is the people’s not trusting on the diagnosis quality of virtual consultation as on face-to-face consultation (Gardner et al. 2015; Van Velsen et al. 2017; Wald et al. 2007). Wilson et al. (2006) examine the development of trust in computer-mediated and face-to-face teams by having fifty-two, three-person groups work on a mixed-motive task over a 3-week period using computer-mediated or face-to-face interaction. The results suggest that electronical group doesn’t develop comparable level of trust to face-to-face one (Wilson et al. 2006). In 2015, Gardner et al. conduct a phone survey of a random sample of patients and find that there are significant hurdles to effectively implement telehealth care as part of mainstream practice though many patients are likely to accept telehealth care (Gardner et al. 2015). Besides the trust issue of patients on telemedicine or virtual consultation, many literature also brings the concern of care quality in the remote consultation environments including telephone, email, video, and internet consultation (Daniel et al. 2012; Hewitt et al. 2010; McKinstry et al. 2010; Roter et al. 2008).

2.2 Uncertainty

In the uncertainty reduction theory, uncertainty refers to “an interactant’s subjective sense of the number of alternative predictions available when thinking about a partner’s future behavior, or the number of alternative explanations available when thinking about a partner’s past behavior” (Bradac 2001). There are two types of uncertainty including cognitive uncertainty and behavioral uncertainty (Berger and Bradac 1982). Cognitive uncertainty refers to the level of uncertainty associated with the beliefs and attitudes of each other in the communication, while behavioral uncertainty refers to the extent to which behavior is predictable in a given situation (Berger 1986; Berger and Bradac 1982). In the context of doctor-patient communication in virtual consultation, patients have uncertainties on many things including doctors they selected, the system, the diagnosis, and the uncertainties can exist along with the entire consultation (Andreassen et al. 2006). Nonetheless, very few studies are conducted on increasing people’s willingness to do virtual consultation from an angle of reducing uncertainty (Greenhalgh et al. 2016).

3 Conceptual Development

3.1 Theoretical Foundation

The Uncertainty Reduction Theory

The uncertainty reduction theory (Berger and Calabrese 1975) was first developed to deal with the initial stage of interpersonal interaction. Berger and Calabrese (1975) label three stages of a communication including entry phase, personal phase and exit stage. By assuming the persons involved in the communication transactions are strangers, they define the entry stage as the beginning of communication during which communication content is somewhat structured. That is, the information received and given by the interactants tends to be symmetric (Berger and Calabrese 1975). For example, the message content tends to be demographic information about the interactants. By the end of this phase, the interactants have a fairly confident estimate of whether or not they will develop the relationship to a more intimate level. The personal phase refers to the second stage of the communication transaction which begins when the interactants engage in communication about central attitudinal issues, personal problems, and basic values (Berger and Calabrese 1975). The exit phase is the final stage during which decisions are made concerning the desirability of future interaction.

According to Berger and Calabrese (1975), when strangers meet, their primary concern is one of uncertainty reduction or increasing predictability about the behavior of both themselves of others in the interaction. Uncertainty involves both prediction and explanation components. Prediction components refers to a proactive process of creating predictions. That is, an individual aim to predict how the other interactants will act during the communication. Explanation components refers to the retroactive process of explaining the other’s behavior (Berger and Calabrese 1975). High level of uncertainty in a relationship cause decreases in the intimacy level of communication content. Low levels of uncertainty produce high level of intimacy.

The degree of one’s perceived uncertainty can be lowered by three different uncertainty reduction strategies: (1) passive, (2) active, and (3) interactive (Antheunis et al. 2012; Shin et al. 2017). Passive strategies are those in which an informant unobtrusively observes the target person, for instance, by observing videos of the doctor’s previous consultation for patients in virtual consultation. Active strategies pertain to proactive efforts to get to know the target person, without confronting the person, for example, by reading other people’s review about the doctor before virtual consultation, and interactive strategies require a direct interaction between the communication partners, for example, by asking questions or through reciprocal self-disclosure (Antheunis et al. 2012; Berger and Calabrese 1975), which means actual video consultation with the doctor. Due to the ability of this theory to explain people’s strategies to reduce uncertainties about other parties in a communication, we believe this theory can provide a theoretical perspective on how to better design virtual consultation system to help patients reduce uncertainties during communication with doctor and computer, and consequently improve their satisfaction about the experience.

3.2 Propositions

According to the uncertainty reduction theory, we develop our framework as shown in Fig. 1 and use it as the basis of our propositions.

Fig. 1.
figure 1

Strategies to reduce uncertainty in the context of virtual consultation

Full size image

The strategy reduction theory suggests three strategies to reduce uncertainty during communication. In the context of virtual consultation interaction, the preliminary strategy is passive strategy which enable patients to get an initial sense of the consultation. For patients who are not familiar with the consultation or the consultation system, this step could arise many uncertainties to patients without providing necessary information. People tend to understand the process better by watching vivid video demonstration than solely rigid text description. Therefore, we have the following proposition:

Proposition 1.

Demonstration of doctors’ consultation process can reduce patients’ uncertainty on diagnosis quality.

The second strategy is active strategy which involves patients’ actively collecting information from different sources, important one of which is reviews. People can get better product information before actual purchase by browsing other purchasers’ reviews in electronical commerce (e-commerce) (Shen and Ulmer 2015). And similarly, patients can better understand virtual consultation and consultation system by retrieving information from other patients’ reviews as well. therefore, we have the following propositions:

Proposition 2.

Other people’s reviews especially other doctors’ reviews can reduce people’s uncertainty on diagnosis quality.

The final strategy requires patients interacts with doctors by asking questions and self-disclosure. Patients tend to trust what they are used to. Since people are used to use a natural face-to-face way to do consultation, they would be more acceptable of the virtual consultation which can be so natural that both verbal and non-verbal information are delivered, just as in face-to-face communication. Therefore, we have the following propositions:

Proposition 3.

The more natural the consultation is, the less uncertainty people have on diagnosis quality.

Some patients may make decision on adoption of virtual consultation system relying on one strategy, while careful patients may use different strategies to ensure themselves as possible before actual usage of the system. Therefore, we have the following propositions:

Proposition 4.

The number of these strategies is negatively related patients’ uncertainty on diagnosis quality.

4 Methodology

We plan to conduct a systematic review of 12 famous virtual consultation systems including Teladoc, American Well, Carena, Zipnosis, Ringadoc, PlushCare, MeVisit, Stat Health, MDLive, iSelectMD, Virtuwell, MeMD, and Doctor on Demand, on their demonstration of consultation process, review availability and communication naturalness. All of the 12 systems allow people to self-select doctors and do video-consultation online. This study helps us to understand the status of system design to reduce patients’ uncertainty level on diagnosis quality.

We also plan to analyze people’s attitudes towards and satisfaction on the systems by conducting a survey and content analysis of patients’ reviews. These analyses can help us better understand how the strategies influence patients’ usage of the systems.

5 Conclusion

This paper focuses on a strategy developing process to boost people’s willingness to use virtual consultation systems from an angle of reducing uncertainty on diagnosis quality, based on uncertainty reduction theory. No such study is conducted to our knowledge. We propose that the virtual consultation system should provide patients consultation process demonstration to reduce their uncertainty on the consultation, enable people leave reviews, and make consultation as natural as possible by delivering both verbal and non-verbal information as face-to-face consultation. With strategies combined, the uncertainty of patients can be greatly reduced.

Our method to explore how to increase people’s trust on virtual consultation can broaden the academic body of virtual consultation and doctor-patient relationships. The perspective of reducing patients’ uncertainty shed a light on future research of system adoption, not only in healthcare area. The propositions can practically facilitate healthcare providers to understand patients’ concerns on diagnosis quality of virtual consultation. They can also guide the design of virtual consultation systems industrially to reduce patients’ uncertainties on online consultation, and consequently to attract more people using these systems.

One limitation of this paper is the lack of data support due to the time limitation. We plan to publish the results of our review and content analysis in a near future. We expect our propositions being empirically supported. One future direction can be exploring other strategies and design features to reduce patients’ uncertainty not only on diagnosis quality, but also on consultation experiences and so on before actual consultation. The other direction can be investigating how to reduce patients’ uncertainty level in the actual interaction with doctors for better communication, which can promote diagnosis quality as a result.