Digital Age Transformation in Patient-Physician Communication: 25-Year Narrative Review (1999-2023)

Abstract

Background: The evolution of patient-physician communication has changed since the emergence of the World Wide Web. Health information technology (health IT) has become an influential tool, providing patients with access to a breadth of health information electronically. While such information has greatly facilitated communication between patients and physicians, it has also led to information overload and the potential for spreading misinformation. This could potentially result in suboptimal health care outcomes for patients. In the digital age, effectively integrating health IT with patient empowerment, strong patient-physician relationships, and shared decision-making could be increasingly important for health communication and reduce these risks.

Objective: This review aims to identify key factors in health communication and demonstrate how essential elements in the communication model, such as health IT, patient empowerment, and shared decision-making, can be utilized to optimize patient-physician communication and, ultimately, improve patient outcomes in the digital age.

Methods: Databases including PubMed, Web of Science, Scopus, PsycINFO, and IEEE Xplore were searched using keywords related to patient empowerment, health IT, shared decision-making, patient-physician relationship, and health communication for studies published between 1999 and 2023. The data were constrained by a modified query using a multidatabase search strategy. The screening process was supported by the web-based software tool Rayyan. The review methodology involved carefully designed steps to provide a comprehensive summary of existing research. Topic modeling, trend analysis, and synthesis were applied to analyze and evaluate topics, trends, and gaps in health communication.

Results: From a total of 389 selected studies, topic modeling analysis identified 3 primary topics: (1) Patient-Physician Relationship and Shared Decision-Making, (2) Patient Empowerment and Education Strategies, and (3) Health Care Systems and Health IT Implementations. Trend analysis further indicated their frequency and prominence in health communication from 1999 to 2023. Detailed examinations were conducted using secondary terms, including trust, health IT, patient-physician relationship, and patient empowerment, derived from the main topics. These terms clarified the collective impact on improving health communication dynamics. The synthesis of the role of health IT in health communication models underscores its critical role in shaping patient-centered health care frameworks.

Conclusions: This review highlights the significant contributions of key topics that should be thoroughly investigated and integrated into health communication models in the digital age. While health IT plays an essential role in promoting shared decision-making and patient empowerment, challenges such as usability, privacy concerns, and digital literacy remain significant barriers. Future research should prioritize evaluating these key themes and addressing the challenges associated with health IT in health communication models. Additionally, exploring how emerging technologies, such as artificial intelligence, can support these goals may provide valuable insights for enhancing health communication.

Keywords: health IT; health communication; patient empowerment; patient-physician relationship; shared decision-making; trust.

Figure 1

The diagram illustrates the selection process (identification, screening, eligibility assessment and inclusion) of this review study.

Figure 2

A 2D scatterplot and a bar plot illustrating the distribution and relevance of topics identified from the topics modeling analysis using LDAvis. Each circle in the scatterplot represents a topic, while the bar plot displays the most relevant terms for topic 1 as an example here.

Figure 3

Bar plot illustrating the annual distribution of papers categorized by their relevance to 3 identified topics from topic modeling with different colors. The bar plot provides a visualization of how the distribution and frequency of each topic within health communication have evolved from 1999 to 2023.

Figure 4

UpSet figure showing the key factors of health communication, including patient empowerment, patient-physician relationship, health IT, and trust, which are represented in 4 different sets individually. The bar chart on the left shows the size of each set, which corresponds to the number of articles that contains any factors among our key factors. The main bar chart on the top represents the size of intersections between different sets within health communication. Each bar's height indicates how many elements are common to the individual sets connected below by dots and lines in the matrix. The matrix of intersections at the bottom has rows labeled with the names of the 5 sets and columns represented by dots under each set name. A filled dot indicates that the set involves the intersection corresponding to that column.