Since the COVID-19 pandemic, telemedicine has moved to center stage. Telemedicine is the use of electronic information and communications technologies to provide and support health care providers when distance limits the access of patients to medical encounters. Telemedicine helps break barriers for access to medical care providing improved speed and accuracy for healthcare services in areas that are more difficult to access. It also allows experts and specialists to be available for patients in remote and non-remote areas, making it an effective alternative to in-person care, potentially reducing inequity, and responding to a global challenge across health systems.
Therefore, immense investments have been made across countries to develop information technology infrastructures for healthcare, expanding telemedicine options, and changing the traditional dynamics between doctors and patients. Investments also made interfaces intuitive and easy to use for patients, reducing frustration, errors, and enhancing the sense of safety, essential for the patient well-being and for trust between patients and healthcare providers. The telemedicine market was valued at $98.8 billion in 2023, projected to grow from $110.9 billion in 2024 to $222.70 billion by 2032 (https://www.marketresearchfuture.com/reports/telemedicine-market-216?utm_term=&utm_campaign=&utm_source=adwords&utm_medium=ppc&hsa_acc=2893753364&hsa_cam=20266715755&hsa_grp=151736942524&hsa_ad=661538375401&hsa_src=g&hsa_tgt=dsa-2313722142214&hsa_kw=&hsa_mt=&hsa_net=adwords&hsa_ver=3&gad_source=1)This growth is attributed to increasing demands for efficient health care services, the rising of chronic illnesses, and the growing adoption the digital transformation in health.
In digital encounters the delivery of medical treatment is over the internet, commonly using video chat technology in closed systems for protecting private data. Thus, technology moderates the provider-patient communication. Doctors are concerned due to the lack of social cues in body language of patients that they easily detect in physical encounters. Patients are less responsive and digital encounters become impersonal. Patients need to feel that their health provider “sees them” as individuals and are concerned about losing interpersonal contact. Patients expect a patient-provider relationship and health providers to meet their expectations. When providers don't meet their patient expectations, barriers to using telemedicine are evident, countering the immense investments that were made for telemedicine.
How may digital encounters meet patient needs and expectations, enhance the active engagement of patients, which is essential for self-management of illness and improved health outcomes? How may providers respond optimally to patient needs in digital encounters?
To date, research on telemedicine focused mainly on differences in the length of provider-patient communication, on contents, on quality of care, access, consent, and privacy. A more effective utilization of telemedicine, however, entails meeting patient expectations of communication with providers, to enhance patient involvement, self-management, and medication-adherence, resulting in stronger provider-patient alliances. Such alliances will reduce future healthcare costs and will utilize the infrastructures of telemedicine to resolve issues of health inaccessibility and inequity.
As telemedicine is becoming ubiquitous in healthcare, it is important to overcome barriers to providing personalized care via telemedicine. To overcome existing barriers of telemedicine, it is essential to understand patient expectations of communication with providers in telemedicine. We bridged the gap in the state-of-the-art by testing expectations of patients from their health providers in telemedicine.
To test patient expectations and simulate our complex reality, where many stimuli may interact with one another, in our research we used a conjoint-based experimental design to test numerous communication messages using an innovative methodological design. Patients who participated as respondents began our studies with an orientation page, signed an informed consent, completed three demographic questions for classification, and then rated the messages. The dependent variable was ‘patient expectations of communication with healthcare providers in telemedicine.’ Patients were asked “How important are these expectations in communication in telemedicine”, they rated 4320 messages on a 1 (not important to me at all) to 9 (very important to me) anchored scale.
The independent variables were acknowledged categories of patient expectations from provider-patient communication: Locus of control; Education and health literacy; Attentive listening; and Body language. Respondents were instructed to rate each vignette of messages as a unity. The test stimuli of vignettes of messages were dictated by a well-crafted mathematical method which structured the 24 vignettes, to ensure statistical independence of the communication categories for subsequent regression at the individual level and the group level. The vignettes generated a compound message, pulling in different directions, forcing the respondents to evaluate the vignette quickly, thus reducing biases of social desirability typical in surveys.
Findings regarding the total panel suggested no significant differences among patients regarding their expectations. They all expected the same. When we applied mathematical clustering, three segments emerged with indices indicating that differences among segments are significant. Members of each segment have different expectations of communication with their health providers. Expectations of patients belonging to one segment were irrelevant to patients in other segments. What were these expectations?
Patients of segment 1 (34% of the sample) were focused on communication in a process of change and expected the provider to walk them through the change process. Patients of segment 2 (36% of the sample) were focused on communication of internal locus of control expecting the health provider to enhance their health literacy, referring them to a reliable source of information to learn more about their condition. Communication to enhance internal locus of control of patients was found to encourage self-management of illness among young chronic patients and reduce re-admissions to the hospital. Patients of segment 3 (30% of the sample), focused on non-verbal communication, were seeking respect in conduct and for their time. Figure 1 presents the patient segmentation.
Thus, patients differ in their expectations from health providers by the way they think. Providers may use algorithms to detect the belonging of each patient to a sample-segment and meet patient expectations when delivering care via telemedicine. Understanding the communication expectations of patients in each segment, can assist providers to structure the digital encounter with greater specificity, enhance quality of care, and overcome existing barriers to telemedicine. Providers are called upon to meet the expectations of patients according to patient segment-belonging by considering the proclivities and sensitivities of patients of each segment.
Additional Readings
Gabay G, Ornoy H, Gere A, Moskowitz H. Personalizing Communication of Clinicians with Chronically Ill Elders in Digital Encounters—A Patient-Centered View. InHealthcare 2024 Feb 8 (Vol. 12, No. 4, p. 434). MDPI.
Gabay G, Ornoy H, Moskowitz H. Patient-centered care in telemedicine–An experimental-design study. International Journal of Medical Informatics. 2022 Mar 1;159:104672.