Appointment management in the outpatient setting is important for health care organizations, as waits and delays lead to poor outcomes. The Institute of Medicine has 6 aims for health care organizations to improve quality [1]. Despite the goal of timely access to care, the topic of visit timeliness is one of the least evaluated and understood aspects of care delivery, and there is little assessment of what drives care timeliness and the potential approaches for improving this dimension of care [2]. Appointment wait times and scheduling difficulties can negatively affect patient satisfaction [3-5], access to care [6], patient safety [7], and health care use and organizational reputation [2]. Timely access has a broader impact on the delivery of cost-effective health care [8] and individuals’ well-being [9]. The association between patient experience and the perception of quality of care has been demonstrated by Schneider et al [10]. Reasonable wait times are expected by patients [11,12].

Outside of health care, other industries with limited resources have addressed timeliness to service by engaging customers through self-service. For example, the transportation and hospitality industries have experienced improvements in operations [13,14], profitability [15], customer loyalty [16], and customer wait times [17] via the execution of consumer-based reservation systems. At present, consumers make reservations for services from a multitude of non–health care businesses. However, the adoption of management technologies, such as the self-scheduling of appointments in health care, has trailed other industries.

There is evidence that automated self-scheduling provides value and that health care organizations can benefit from it. Researchers have identified the advantages of automated patient self-scheduling for health care organizations in the form of labor savings [18-22], information transparency [23,24], cost reduction [25], cycle time [26], patient satisfaction [27,28], patient accountability [29], patient information [30], patient time savings [31], physician punctuality [32], patient loyalty [23], and patient attendance [33-37]. Reducing missed appointments increases a health care organization’s efficiency and the effective allocation of resources [38]. Automated self-scheduling eliminates the barriers inherent in the fixed capacity of phone lines and scheduling staff [39].

Health care organizations are faced with the need to increase access to accommodate patients’ changing expectations [40,41]. Self-scheduling may offer the convenience that patients seek [42,43]. Countries in Europe [44], England [19,34], Canada [36], Australia [45], and the United States [23], have established health technology initiatives at the national level. Nigeria [20], India [30], Taiwan [22], the Philippines [26], and Iraq and the Kurdistan region [46] have determined that self-scheduling may serve as a better alternative to obtaining an appointment as opposed to the traditional process of accessing outpatient care by physically standing in line. In Iran [47] and China [24,48,49], hospitals are mandated to provide the capability, in part, to address the problems associated with in-person queues for appointments. In Estonia, this functionality is built into the national system [50]. The benefits of self-scheduling may not be realized by persons in low- and middle-income countries, where many patients report negative experiences related to poor communication, short visits, or lengthy waits [51]. Self-scheduling may be perceived as elusive or ineffective, with patients preferring to physically wait in line to combat inefficiencies. This may not be a malfunction of the technological solution but rather a result of low- and middle-income countries’ failure to address socioeconomic disparities that have eroded patients’ confidence in the health care system [52].

Despite evidence of the potential benefits of self-scheduling, the organizational uptake of self-scheduling in health care has been limited. The lack of adoption may be a result of several factors examined in other studies of technology adoption, including the absence of financial incentives for the organization [53], cost [54], leadership [55], and policy and regulations [56]. Health care providers have expressed reluctance about self-scheduling based on cost, flexibility, safety, and integrity; patients cited concerns based on their prior experience with computers and the internet, as well as communication preferences [21]. Organizations may be reacting to patient hesitancy. Despite the infusion of technology in daily living, patients exhibit reluctance to automation in health care, citing concerns about accuracy, security, and the lack of empathy compared with human interactions [57].

There is a small body of literature regarding organizational barriers to the adoption of automated self-scheduling in popular literature. A practicing physician, informaticist, and the founder of a software company that offered self-scheduling products, Dr Jonathan Teich, revealed the following to the American Medical News in 2004 [58]:

Research has demonstrated that physicians’ concerns about addressing scheduling complexity [58] and preferences [59] are key factors in scheduling, with physicians expressing a fear of losing control of their schedules [60-62].

A previous review in this field provided evidence of facilitators of (no-shows, labor, waiting time, and patient satisfaction) and barriers to (cost, flexibility, safety, and integrity) automated self-scheduling [21]. Patients’ expectations regarding their health care experience, as well as the application, adoption, and use of health care technology have evolved significantly since the publication of the systematic review in 2017, thereby compelling a new review to be performed.

Against this background, this scoping review seeks to identify the barriers to and facilitators of self-scheduling for health care organizations. The scoping review technique was selected based on a broad research question, the pursuit of identifying content without judging the quality of the material, and the intention to perform a qualitative synthesis [63].

The following research questions guided the review: What are the barriers to and facilitators of health care organizations’ uptake of automated patient self-scheduling? What are the gaps in the literature regarding barriers and facilitators?

This scoping review was performed by searching electronic databases according to the PRISMA-S (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Search) guidelines [65]. The databases used were PubMed, CINAHL, Business Source Ultimate, and Scopus. The search strategy was developed with the assistance of an informaticist specializing in reviews. The search terms for self-scheduling were developed by researching titles, keywords, and commonly used phrases in the relevant literature. The search strategy was initiated on PubMed using combinations and word variations of key terms for the scoping review: “self-scheduling,” “automated scheduling,” “Web-based scheduling,” “e-appointments,” “online scheduling,” “Internet scheduling,” and “self-serve scheduling.” Additional terms were integrated using keywords from articles of interest that were retrieved from a preliminary search on PubMed. The implementation-related search string was adapted from a study of barriers and facilitators [66]. The initial search strategy was referenced against the published systematic review by Zhao et al [21] to identify supplementary terms. The search strategies used in the databases are reported in Multimedia Appendix 1. Articles were identified, screened, and selected for further review in two stages by the author: titles and abstracts, followed by the full text.

Records were selected if they involved automated patient self-scheduling. Articles were determined eligible for inclusion if they discussed the use of self-scheduling by health care organizations. Peer-reviewed articles, primary research, reviews, and original studies described in editorials in peer-reviewed journals that focused on patient self-scheduling were included. Only articles published in English were included during study selection.

For the review, the definition of self-scheduling involves real time, synchronous booking, and automated fulfillment of appointments by patients on the web or via a smartphone app for themselves. Self-scheduling does not include an appointment by a physician on behalf of a patient, as in the case of a primary care physician scheduling an appointment with a specialist for the patient. Furthermore, the definition excludes asynchronous scheduling transactions that feature the patient initiating a request for an appointment but not booking it automatically, or the slot being appointed automatically through a waitlist feature [67] or a reschedule option [68]. Patients scheduled as research participants were excluded. The definition excludes self-scheduling of providers and staff.

A data extraction Microsoft Excel spreadsheet was developed to systematically record the details of the articles. Charted data (Multimedia Appendix 2 [5, 18, 19, 21-24, 26, 28, 29, 31-37, 42-45, 47, 48, 69-75]) included article characteristics (author, year, and country), intervention characteristics (stand-alone or component, source, introduction, description of design, and identified need), research design, setting, intervention measures assessing the impact of self-scheduling, and main results. Relevant results were extracted from the results section of each article.

The scoping review was organized and presented in alignment with the Consolidated Framework for Implementation Research (CFIR). The conceptual framework provides guidance for the research by constructing a standard, evidence-based path for identifying, organizing, and communicating the dimensions of barriers and facilitators across organizations to advance the opportunity for adoption of the study’s findings. The framework is comprehensive, synthesizing essential constructs from 29 organizational and implementation science theories. Standard terminology promotes generalizability across disciplines (Textbox 1) [76].

Thematic analysis was performed to convey the main findings of the material.

Titles and abstracts were reviewed for 1726 records, with 1604 (92.93%) records being excluded. The full texts of 7.06% (122/1726) of articles were retrieved and reviewed. In total, 5.33% (92/1726) of studies were excluded because they failed to meet the inclusion criteria. A total of 1.73% (30/1726) of studies were included in this scoping review. Figure 1 outlines the selection methodology using a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) diagram.

The countries covered in the review include the United States [18,28,29,31,33,35,37,43,73,74], Taiwan [22,23,42], England [19,34,69,72], China [24,48,75], Australia [45,70,71], Canada [36], Iran [5,32,47], and the Philippines [26]. Another article included 7 countries in Europe [44]. Table 1 presents the countries and the number of articles from each. The first article retrieved for the scoping study was published in 2004 [18], with ≤3 articles each year up to and including 2019. In 2020, 8 articles [22,26,28,29,31,37,72,73] featuring barriers to and facilitators of automated self-scheduling were published. Table 2 displays the number of articles published by year of publication.

The key elements of the structural characteristics of the research settings are included in Multimedia Appendix 2. Of the 28 studies that defined the research setting, 14 (50%) were based in outpatient practices [5,18,19,32,34-37,43,45,70-72,74], 10 (36%) were based in medical centers [22, 24, 26, 28, 31, 42, 47, 48, 73, 75], and 4 (14%) surveyed community members [23,29,44,69]. Among the outpatient practice studies, 13% (4/30) featured settings of single specialties: 7% (2/30) dermatology [35,37], 3% (1/30) audiology [34], and 3% (1/30) genitourinary [19].

Data were not included in the studies for networks and communication or culture. Limited information was provided about the implementation climate. Friedman [18] conveyed that his physician colleagues “turned white as ghosts” at the suggestion of implementing self-scheduling, citing concerns about transparency; however, most adopted the platform. Acknowledging reluctance, Craig [33] advised, “like anything new, [self-scheduling] will take some getting used to.”

Habibi et al [5] determined the importance of rendering favorable services owing to increased competition. This study was joined by 9 others that expressed the priority for change [18,22,24,26,28,31,42,45,47]. The sense of urgency increased over time. Zhang et al [24] reported lines forming late at night and “incidents of knife attacks at hospitals” resulting from patients’ frustrations.

The importance of problem solving in the outpatient environment, which is the face of the hospital, was emphasized [26]. Lee et al [22] concluded that the impression of service quality put forth by the self-scheduling technology was a key success factor for a hospital to “gain an...advantage...in an increasingly competitive healthcare market.” Volk et al [28] described the current environment that led to the introduction of the intervention as “threatening the organization's reputation and financial well-being.”

Readiness for implementation was not addressed in detail: 3% (1/30) of studies [32] mentioned about providing the secretaries with a tablet and training; however, no other study described the engagement of leadership, available resources, or access to knowledge and information.

This scoping review located 30 published articles that described synchronous, automated self-scheduling tools for patient appointments. The number of studies related to self-scheduling increased over time. The growing volume of research reflects the popularity of the technology, signaling its broadening appeal. Research performed in the same community-based clinic setting concluded a low intention to use [45,70,71]. However, low intention to use was not demonstrated in a study since 2015, perhaps reflecting the now pervasive use of computers. Patients’ trust in the intervention has been studied as a possible barrier to the intervention [29]. Studies have continued to identify gaps between the interest and awareness of the technology and its use [29,75]. Researchers have concluded that concerns about access to the internet persist [26]. The introduction of self-scheduling in the context of a hospital as a business entity with financial interests commenced in 2020, perhaps reflecting the opportunity that a self-scheduling offering is no longer considered an initiative to appeal to innovators but rather a necessity of service delivery. Lee et al [22] determined that ease of use was no longer a factor of patients’ continuous use, concluding that the system is now “stable, reliable, and well designed.” This study reflected patients’ increasing comfort with technology, which is supported by the literature about other consumer-oriented offerings such as telemedicine [78,79]. Articles aimed at optimization methods for scheduling, such as recommendations for demand matching [80], were formulated on a platform of automated scheduling, a reflection that the literature has evolved from the foundational elements of implementation to a more sophisticated approach.

Efforts to determine the effect of self-scheduling may be hindered by the incorporation of the intervention as an element in a suite of technologies. Of the 30 studies, 11 (37%) studies in this scoping review [19,22,28,29,31,42,44,69,72,74,75] included self-scheduling as a component of a larger technology initiative, which may indicate that another intervention that was aligned with self-scheduling was the source of the organizational benefit.

The scoping study incorporated a systematic review that was conducted in 2017. The systematic review [21] reported the advantages of self-scheduling for organizations. In the literature before the systematic review, most gains were reported to have the potential to benefit the organization. Beginning in 2017, the advantages of self-scheduling have increasingly focused on the outer setting. Organizations react to consumers’ access to technology and their competitive environment. Furthermore, the benefits of self-scheduling from the patients’ perspective—satisfaction, time, convenience, and engagement—were increasingly referred to as potential rewards. Table 3 highlights the changes in the focus of the literature related to the identified need for the intervention. This may reflect an alteration in the determinants of adoption.

In a systematic review, Zhao et al [21] concluded that cost, flexibility, safety, and integrity were the barriers to adoption. Except for safety, these organizational barriers have not been replicated in the literature since 2017 [26,73]. However, the research upon which these conclusions were based drew upon the popular literature except for a 2004 case study [18] and a 2007 commentary [33], both of which noted providers’ hesitancy. The lack of evidence-based organizational barriers over time may mean that the obstacles have historically been organizations’ perceptions of patient behavior. The reluctance of patients to adopt based on their experience with computers reported in the systematic review [21] was not reproduced other than the potential impact of broadband speed noted in a focus group [26]. Despite the lack of evidence-based barriers, use of self-scheduling has continued to be reported at low rates during the period of 2017-2020 [47,72,75].

Self-scheduling may offer value to health care organizations. Additional research regarding the barriers to and facilitators of implementation is warranted.

The author (EW) conducted the screening process, which may have introduced selection bias. The lack of a standard naming convention may have resulted in missing relevant articles for the scoping review. Given the large number of findings from countries with a primary language other than English, the inclusion of English-only articles may have missed publications that were not accessible from the databases deployed in the search strategy.

In contrast to systemic reviews, scoping studies, by definition, do not incorporate a quality assessment of individual studies; therefore, it is challenging to assess whether studies produce robust findings [64]. As such, data synthesis and interpretation are limited [63].

An agreement on common measures to identify and monitor the impact of self-scheduling is required. Research that tracked the most cited advantage of reducing the no-show rate failed to accompany the discourse with a definition of said rate.

This scoping review cataloged existing knowledge and identified gaps in knowledge regarding the uptake of automated self-scheduling by health care organizations. The intervention was defined. There was evidence of the broadening appeal and demonstrable benefits of automated self-scheduling; however, the uptake remained low.

Prior research examined implementation effectiveness; this review focused on barriers to and facilitators of self-scheduling by health care organizations. Outer setting determinants to include national policy, competition, the response to patients’ needs, and technology access played an increasing role in influencing implementation over time. Automated self-scheduling may offer a solution to health care organizations striving to positively affect access.