Canadian University Dubai, United Arab Emirates
* Corresponding author
University of Alicante, Spain
University of Alicante, Spain

Article Main Content

Smart technologies such as artificial intelligence and big data have transformed hospitals from a medical, management and communication perspective. This paper aims to analyze how the best hospitals in the United Kingdom manage these technologies to build a reputed brand. To do that, we conducted a literature review about smart technologies and online branding processes in hospitals. Then, we defined 34 indicators to evaluate how the 140 best hospitals in the United Kingdom managed smart technologies for branding purposes. Our results proved that most of them focused their branding efforts on patients (4.98 criteria out of 11 applicable), rather than journalists (3.01/11) or public authorities (2.16/6). We concluded that hospitals should implement an integrated marketing communication approach, use smart technologies to establish new organizational processes with stakeholders, and develop digital transformation plans to efficiently manage this process.

Introduction

Artificial intelligence, big data, telemedicine, and mobile applications have radically transformed hospital’s organizational processes, as well as health professionals’ mentalities and practices. In this new technological framework, hospitals integrate mobile applications into medical protocols, doctors use artificial intelligence-based tools to diagnose patients, and nurses resort to big data to monitor patients’ medical outcomes. Thanks to smart technology, hospitals are becoming digital organizations, which also impacts their corporate communication strategies. Indeed, most hospitals resort now to websites, mobile applications, and social media platforms to reinforce their relationships with stakeholders, such as patients, employees, and media companies. However, using smart technologies for corporate communication purposes constitutes a challenge for these organizations: limited economic resources, lack of experts in this area, strict legal frameworks, and so on.

This paper aims to analyze how the best hospitals in the United Kingdom manage smart technologies to reinforce their relationships with stakeholders and build a reputed brand. To do that, we conducted a literature review about smart technologies in hospitals (artificial intelligence, big data, telemedicine), patients’ privacy, hospitals’ branding initiatives on social media, and the role of doctors and nurses in hospitals’ online branding processes. Then, we defined 34 indicators to quantitatively evaluate how the 140 best hospitals in the United Kingdom managed websites, mobile apps, social media, and other smart platforms to implement branding initiatives addressed to their stakeholders: patients, media companies, shareholders, suppliers, public authorities, and employees. Finally, we presented our results as well as three main conclusions that could help hospitals all over the world to improve their online smart branding initiatives in the next years.

Smart Branding in Hospitals

Smart Hospitals

Hospitals resort to different technologies to improve their patients’ medical outcomes: artificial intelligence, big data, telemedicine, health wearables (Howe & Elenberg, 2020). Artificial intelligence refers to the ability of computers or computer-controlled robots to perform tasks usually associated with doctors and nurses (Zegerset al., 2021). This technology determines the relationships between hospitals and patients from a medical, social, and legal perspective (Ramon Fernández, 2021). In fact, thanks to artificial intelligence, hospitals enhance medical imaging techniques (Kaissiset al., 2020), as well as diagnosis, treatments, and prognosis (Manrique de Lara & Peláez-Ballestas, 2020). Moreover, this technology contributes to optimize hospitals’ internal processes: online appointments, data recording, etc. (Dhagarraet al., 2020). However, using artificial intelligence represents some challenges for these organizations: limited dataset availability for algorithms training and validation due to the absence of standardized electronic medical records (Lin & Hou, 2020), legal and ethical requirements (Shiet al., 2020), and security risks concerning patients’ personal data (Kaissiset al., 2020). For this reason, before implementing any artificial intelligence-based tool, hospitals need to professionalize their internal processes and protect their patients’ and doctors’ rights (Tomet al., 2020).

Along with artificial intelligence, hospitals resort to big data to improve their patients’ medical outcomes (Dhagarraet al., 2020). Thanks to big data, hospitals acquire large amounts of data from multiple sources and then they combine this data by using analytics tools (Ferrettiet al., 2020). Thanks to results obtained, hospitals improve their internal processes and medical protocols (Shiet al., 2020), which positively influences on patients’ medical outcomes (Howe & Elenberg, 2020). Using big data is especially useful to treat patients suffering from three diseases. First, infectious diseases. Hospitals resort to big data to collect, clean and integrate data from different sources, and this way better understand infectious diseases: trends, treatments, and risks (Wuet al., 2020). Second, obesity. Big data allows hospitals to monitor and analyze people’s behaviours, which is useful for preventing obesity in some populations, such as children (Shahidet al., 2021). And third, rare diseases. Hospitals use big data to share information about rare diseases, understand health trends, and analyze patients’ needs (Courbieret al., 2019).

Artificial intelligence, big data, telemedicine, and health wearables have transformed hospitals. However, these organizations must always consider the impact of this technology on their patients’ privacy (Zhanget al., 2021). Protecting patients’ right to privacy has become a medical and legal responsibility that hospitals must assume to be perceived as professional organizations (Fazalet al., 2022). To efficiently protect patients’ privacy, hospitals implement several initiatives: communicating data protection efforts to patients, being proactive when hospitals face a privacy breach, and explaining the measures adopted to avoid these crises in the future (Trinidadet al., 2020). Besides, hospitals implement codes of conduct to help their employees use these technological tools professionally (Molnár-Gábor & Korbel, 2020). Finally, some hospitals implement different initiatives addressed to patients: explain to patients the importance of legal consent (Murdoch, 2021), educate patients on the impact of big data and artificial intelligence on medical treatments (Hulsen, 2020), and encourage patients to assume their individual responsibilities and ask questions to healthcare professionals (Belaniet al., 2021).

Branding Smart Hospitals

Smart technology allows hospitals to improve their medical protocols; however, it also positively affects their branding processes (Lithopouloset al., 2021). These processes refer to communication initiatives implemented by hospitals to influence their stakeholders’ perceptions of the organization’s brand (Odoomet al., 2019). Nevertheless, before implementing these processes, hospitals must define their brand architecture: identity, values, mission, vision, and culture (Medina Aguerrebereet al., 2020). According to Singla and Sharma (2021), identity refers to the main reasons why an organization is unique in society. To efficiently promote identity, hospitals define corporate values that guide the organization’s internal and external processes (Sanderet al., 2021). When companies respect their identity and values, they can achieve their mission and vision, which refer to the company’s objectives in the mid-term and the long-term, respectively (Hart & Phau, 2022). Finally, the culture can be defined as the unique way in which employees behave to help the organization became a unique brand (Li & Zhao, 2021). Once hospitals have defined their brand architecture, they implement branding processes that must be consistent with the organization’ roots (Rindell & Santos, 2021), its ethical principles, and the main legal framework (Sanderet al., 2021).

When hospitals promote their brand, they focus on content useful for stakeholders from a medical, social, and emotional perspective (Lithopouloset al., 2021). This meaningful content is essential to reinforce the hospital’s brand credibility (Reitsamer & Brunner-Sperdin, 2021). On the other hand, this content must also consider two main elements: culture and emotions. Cultural elements contribute to making hospitals’ brands more dynamic (Tanet al., 2020), which positively influences doctor-patient relationships (Zhao, 2021). Concerning emotions, hospitals analyse their stakeholders’ feelings to understand their needs better. This way, they build a more relevant brand (Rahmanet al., 2021; Razmus, 2021). Integrating emotions and cultural elements into the hospital’s branding allows these organizations to build a more dynamic brand (Hart & Phau, 2022; Tsaiet al., 2021).

Hospitals use different platforms to implement their branding initiatives: social media, mobile apps, and so on (Medina Aguerrebereet al., 2020). These organizations use social media platforms to revamp their relationships with stakeholders and build a more reputed brand (Chou, 2021). To do that, hospitals need to be creative and train their employees to use these platforms professionally (Shiehet al., 2020). Once hospitals have trained their employees in this area, they can launch corporate communication initiatives to build their brand in a collective way along with their stakeholders (Kordzadeh & Young, 2018; Yantianet al., 2022). On the other hand, these organizations also manage mobile applications for branding purposes (Hart & Phau, 2022). Most of them train their doctors and nurses on how to use these applications to interact with patients (Chamberlainet al., 2021): promoting healthy habits, monitoring patients, reinforcing patients’ skills in health literacy (Crossleyet al., 2020). Thanks to mobile apps, hospitals improve their patients’ medical outcomes and reinforce the organization’s brand reputation (Mackertet al., 2020).

Smart Branding and Healthcare Professionals

Hospitals promote multidisciplinarity and integration to reinforce their branding processes; in that sense, they train their doctors to communicate efficiently with patients (Li & Xu, 2020). Doctors’ skills in communication determine patients’ perceptions of the hospital, its services, and its brand (Butow & Hoque, 2020). Patients view doctors as a human brand with a unique brand personality; that is why doctors should reinforce their skills in interpersonal and online communication to efficiently interact with patients (Rezaet al., 2022). In other words, doctors need to reinforce their skills in telemedicine (Bassan, 2020) and artificial intelligence. This way, they can establish more dynamic relationships with their patients (Butow & Hoque, 2020). On the other hand, doctors should be trained to use corporate communication platforms for branding purposes, especially mobile apps, social media, and online communities (Medina Aguerrebereet al., 2020). Doctors can use mobile apps to promote health education initiatives addressed to patients (Mackertet al., 2020); they can manage social media platforms to support patients from an emotional perspective (Etheredge & Fabian, 2022); and they can participate in online communities to reinforce the hospital’s scientific credibility (Wuet al., 2019).

Besides doctors, nurses also play a key role in hospitals’ branding processes (Rezaet al., 2022). Thanks to their skills in communication, nurses improve the hospital’s internal processes (Rodrigueset al., 2020) and establish better relationships with patients (Nicholset al., 2021). These skills in communication help nurses reinforce their personal brand; however, they also need to reinforce their expertise in using smart technology to interact with patients (Godseyet al., 2020). Nurses need to be trained to use telemedicine and artificial intelligence in medical settings (Lv & Qiao, 2020; Nittariet al., 2020). Moreover, they must reinforce their skills in online corporate communication: mobile apps, social media, and online communities (Wuet al., 2019). These professionals can use mobile apps to educate patients on healthy habits (Piculellet al., 2021), they can manage social media to monitor patients (Farsi, 2021), and they can participate in online communities to share medical information about prevention and health education (Chen & Wang, 2021).

Methodology

Artificial intelligence, big data, telemedicine, social media, and mobile applications have transformed hospitals’ corporate communication strategies. Hospitals manage these tools to make their brands more dynamic. To better understand how hospitals manage this process, we resorted to the World’s Best Hospitals 2023, an international ranking published annually by Newsweek and Statista. Both organizations analyzed 2,300 hospitals from 28 countries. They considered four indicators: (a) 80,000 online surveys to doctors from 28 countries, (b) patients’ opinions about hospitals, (c) hospitals’ quality indicators, and (d) PROM questionnaires about patients’ quality of life. Based on these results, they calculated each hospital’s score and position in the ranking. To do that, they respected the following weights: online surveys to medical experts (54%), patients’ opinions (14,5%), hospitals’ quality indicators (29%), and PROM questionnaires (2,5%). Once they defined rankings, they confirmed these results with a Global Board of Medical Experts, including doctors from Israel, the United States, Germany, Switzerland, and France (Newsweek, 2023).

Thanks to this ranking, we identified the 140 best hospitals in the United Kingdom (see Appendix). To analyze how these hospitals managed different technological tools to implement branding initiatives, we considered several targets that we grouped into four main categories: (a) patients and society; (b) media companies; (c) public authorities, suppliers, and shareholders; and (d) employees. We focused on patients since they play a key role in every hospital’s corporate communication strategies and because they influence other stakeholders’ perceptions of the organization’s brand (Chou, 2021). We included media companies in our analysis because these organizations contribute to reinforcing hospitals’ scientific credibility as well as doctors’ and nurses’ reputations (Etheredge & Fabian, 2022). Concerning public authorities, these institutions influence hospitals’ brands because they collaborate with hospitals for several projects, such as health education initiatives or public health campaigns (Odoomet al., 2019). Finally, we considered employees since they represent the hospital’s brand and because they play a key role when hospitals build the brand in a collective way (Medina Aguerrebereet al., 2020).

From 17th August to 10th September 2023, we conducted a quantitative analysis of how the 140 best hospitals in the United Kingdom managed smart technologies to reinforce their brands. To do that, we defined 34 brand indicators that we grouped into four main categories according to stakeholders and platforms: (a) homepage (patients, society); (b) online newsroom (media companies); (c) about us (public authorities, suppliers, shareholders); and (d) artificial intelligence department (employees)—see Table I. We only considered hospitals’ official websites. Finally, we resorted to the binary system to analyze each indicator.

Homepage (Patients and society) Online newsroom (Media companies) About us (Public authorities, suppliers, and shareholders) Artificial intelligence department (Employees)
1. Hospital homepage2. Patient portal3. Mobile apps4. Symptom checker5. Video consultations with doctors6. Chatbot7. Interactive maps8. Virtual tours9. Interactive health library10. Podcasts11. Social media platforms 1. Newsroom2. Digital press archives3. Interactive infographics4. B-roll videos5. Podcasts6. Interactive corporate reports7. Online translation services8. Online interviews with doctors9. Online press conferences10. News alerts11. Mobile apps or platforms for journalists 1. About us section2. Videos3. Interactive infographics4. Interactive corporate documents5. Suppliers platform6. Shareholders platform 1. Artificial intelligence department2. Integrating AI into medical protocols3. Training employees4. Research projects5. Collaborations with universities or research centers6. Collaborations with external technological companies
Table I. Brand Indicators

Results

Most hospitals in the United Kingdom resorted to smart technologies to establish meaningful relationships with their stakeholders and build a more reputed brand. Indeed, 97,14% of hospitals had a corporate website. However, many hospitals can improve in different areas: online newsrooms, about us sections, etc. We present our results grouped into five main categories: (a) homepage, (b) online newsroom, (c) about us section, (d) artificial intelligence department, and (e) global performance.

Homepage

Our results demonstrated that all hospitals had a homepage, and most of them also proposed social media platforms (89.71%), interactive health libraries (61.03%), video consultations with doctors (60.29%), and virtual tours for patients (59.56%). However, few hospitals resorted to other tools, such as interactive maps (43.38%), mobile apps (41.91%), patient portals (30.88%), podcasts (8.82%), chatbots (1.47%) or symptom checkers (1.47%). On average, hospitals respected 4.98 criteria out of 11 applicable, and only six hospitals achieved 9 criteria: Addenbrooke’s, Warwick Hospital, Darent Valley Hospital, The Princess Margaret Hospital, Royal Stoke University Hospital, and KIMS Hospital.

Newsroom

According to our results, 96.32% of hospitals managed an online newsroom where they mainly shared digital press archives (98.47%). However, most hospitals did not fulfill other criteria: B-roll videos (41.98%), interactive corporate reports (37.40%), interactive infographics (7.63%), news alerts (7.63%), podcasts (6.11%), online translation services (0.76%), online interviews with doctors (0,76%), online press conferences (0%), and mobile apps for journalists (0%). On the other hand, 67.94% of hospitals respected between 2 and 3 criteria, and the only one achieving 6 indicators was KIMS Hospital.

About Us Section

Even if 98.53% of hospitals had an about us section, most of them did not comply with the indicators considered: interactive corporate documents (72.93%), videos (34.33%), interactive infographics (9.7%), suppliers’ platform (0%), and shareholders platform (0%). On average, hospitals respected 2.16 criteria, and only 11 hospitals achieved 4 indicators: East Surrey Hospital, Frimley Park Hospital, and Royal Derby Hospital, among others.

Artificial Intelligence Department

Our results proved that only 6 hospitals had implemented an in-house department specializing in artificial intelligence. These six departments integrated artificial intelligence into the hospital’s medical protocols, organized sessions to train their employees in this area, and conducted research projects in collaboration with external partners (see Table II). On the other hand, 40 hospitals had not implemented an artificial intelligence department, but they developed research projects about this area in collaboration with different external organizations (see Table III). Finally, 59 hospitals did not have an artificial intelligence department, but they had implemented research projects in this area that they managed without collaborating with any external company. Concerning the 35 hospitals remaining, they did not mention anything about artificial intelligence on their corporate websites.

Hospital Artificial intelligence department Universities, Research centers Technological companies
1 St Thomas’ Hospital Centre for innovation, Transformation and improvement KHP Ventures, KiTEC, AI Centre, Clinical Scientific Computing, Clinical Engineering, KHP Biobank.
2 Guy’s Hospital Centre for innovation, Transformation and improvement KHP Ventures, KiTEC, AI Centre, Clinical scientificComputing, Clinical Engineering, KHP Biobank.
3 King’s College Hospital London medical imaging and AI centre for value based healthcare Imperial college London, QueenMary University of London. Wellcome EPSRC centre medical Engineering,Health innovation network, Siemens, IBM, Nvida, Ixico, Biotronics 3D, Mirada, Cedar Medical, Innersight, Brainminer, Ai Nostics, Kheiron. Perspectum Diagnostics.
4 Alder Hey Children’s Hospital-Pediatrics Alder Hey innovation centre Hartree Centre, IBM, Microsoft.
5 Great Ormond Street Hospital for Children-Pediatrics Digital research, Innovation and virtual environments KPMG Sensyne Health, Roche.
6 National Hospital For Neurology and Neurosurgery-Neurology Brain Surgery with Robotics, Artificial Intelligence and Neuronavigation Imperial College London, King’sCollege London, University of Calgary,University of Edinburgh. Medtronic, Artificial Bits, Olympus, VineHealth, Storz, Bbraun, Lightpoint Medical.
Table II. Hospitals’ Artificial Intelligence Departments
Hospital Universities and Research centers Technological companies
1 University College Hospital Cambridge University Microsoft
2 Addenbrooke’s Cambridge University Microsoft
3 Queen Elizabeth Hospital Birmingham University of Birmingham, Massachusetts Institute of Technology. Roche, Health Data Research UK.
4 Leeds General Infirmary West Yorkshire and Harrogate CancerAlliance, Densitas.
5 Frimley Park Hospital Qure.ai, Canon Medical Systems.
6 Manchester Royal Infirmary Rinicare, Medtronic.
7 Royal Free Hospital University College London, QueenMary University of London, NationalInstitute of Health. Abbott Cardiovascular
8 Glasgow Royal Infirmary Scotland’s Industrial Centre for Artificial IntelligenceResearch in Digital Diagnostics, Paige, Dynamic Scot.
9 Royal Berkshire Hospital Brainomix, NCIMI.
10 Southampton General Hospital Southampton Biomedical Research Centre Engineering and Physical Sciences Research Council
11 Homerton University Hospital Nuance
12 Queen Elizabeth University Hospital University of Glasgow Icaird, Canon Medical Research Europe, Philips.
13 Kingston Hospital Siemens Healthineers
14 Southmead Hospital University of the West of England Bristol Robotics Laboratory
15 Musgrove Park Hospital Sensyne Health, Google.
16 The London Clinic Medtronic, Hyland Healthcare.
17 Chapel Allerton Hospital University of Leeds SerenusAI
18 Glenfield Hospital University of Leicester Medtronic, UK Space Agency.
19 Royal Bolton Hospital Qure.ai, Allscripts, Vectra.
20 Bupa Cromwell Hospital Visionable, Dell, Streets Heaver, Philips.
21 Basingstoke and North Hampshire Hospital Accelerate Diagnostics
22 Poole Hospital University of Kent Philips, System C & Graphnet Care Alliance.
23 Northumbria Specialist Emergency Care Hospital Microsoft, Wheelshare, Tyco Security Products, FloKi Health.
24 Heatherwood Hospital Kier
25 Trafford General Hospital Siemenes
26 North Tyneside General Hospital Newcastle University, University of Warwick, Coventry University. Medtronic, Crescendo.
27 University Hospital-Coventry University of Barcelona, University of Warwick Corporate Health International.
28 Golden Jubilee National Hospital University of Glasgow Canon, Stryker MedEd.
29 The James Cook University Hospital National Institute for Health and Care Research Olympus America, Alcidion, Ingenica Solutions, Canon Medical System.
30 Darlington Memorial Hospital Philips, Intuitive Surgical.
31 Bradford Royal Infirmary University of Bradford GE Healthcare
32 Royal Hampshire County Hospital GE Healthcare
33 University Hospital of North Durham Philips
34 Sunderland Royal Hospital National Institute for Health and Care Excellence Medtronic, HIMSS Analytics Solutions.
35 Derriford Hospital University of Plymouth Brainomix, Nuance.
36 Torbay Hospital Microsoft
37 Yeovil District Hospital Intersystems, Deepmind, Google, Veracode.
38 Queen Alexandra Hospital SWASH Heartflow
39 Liverpool Heart and Chest Hospital-Cardiology Aidence, iRhythm Technologies.
40 Royal Papworth Hospital-Cardiology & Pulmonology University of Cambridge
Table III. Artificial Intelligence: External Companies

Global Performance

After analyzing how the 140 best hospitals in the United Kingdom managed smart platforms to promote their brands, we can state that, on average, these organizations respected 10.68 criteria out of 34 applicable. Finally, the best hospital was Alder Hey Children’s Hospital–Pediatrics (see Table IV).

Hospital Number of criteria (out of 34)
Alder Hey Children’s Hospital-Pediatrics 21
KIMS Hospital 19
Warwick Hospital 18
Royal Stoke University Hospital 17
Darent Valley Hospital 17
North Tyneside General Hospital 17
Table IV. Best Hospitals in the United Kingdom

Discussion

Most British hospitals resorted to smart communication platforms to interact with their stakeholders and build their brand collectively. They interacted with different stakeholders such as employees, public authorities, and media companies; however, most of them focused their efforts on patients. According to Oxmanet al. (2022), patients are opinion leaders influencing other stakeholders’ perceptions about different topics, such as hospitals’ services or doctors’ behaviours. When hospitals interact with patients, they implement communication initiatives based on meaningful values such as knowledge, education, emotions, and social support (Wang & Wu, 2020). This way, hospitals help their doctors and nurses improve their relations with patients (Li & Xu, 2020). However, our results proved that the best hospitals in the United Kingdom can still improve. On their homepage, only a few hospitals proposed education tools such as patient portals (30.88%), podcasts about health promotion (8.82%), or symptom checkers (1.47%).

Hospitals collaborate with media companies to implement public health campaigns and reinforce citizens’ skills in health literacy (Mheidly & Fares, 2020). Journalists have become social educators who contribute to building a healthier society (Kreps, 2020). That is why hospitals’ doctors and nurses actively collaborate with them (Rezaet al., 2022). Despite these facts, our results demonstrated that most British hospitals did not prioritize media companies as a main target. That is why, on their online newsroom, only a few hospitals provided media companies with different tools, such as b-roll videos (41.98%), interactive corporate reports (37.30%), or interactive infographics (7.63%). Besides, no hospital proposed an option to organize online press conferences to facilitate journalists’ tasks.

Hospitals implement branding processes to build the brand in a collective way along with their stakeholders (Medina Aguerrebereet al., 2020). These organizations mainly interact with patients and employees, but they should also collaborate with public health authorities to implement health education campaigns (Castiglia & Dettori, 2022). When hospitals include all stakeholders in their branding processes, they can build a reputed brand (Adebesin & Mwalugha, 2020). Nevertheless, our quantitative analysis proved that most British hospitals can still improve in this area. Indeed, on their about us sections, no hospital proposed a platform for suppliers or shareholders. Besides, most hospitals were very conservative concerning the content shared with these targets: they mainly focused on the hospital’s history and annual reports. These organizations should provide shareholders, suppliers, and public authorities with different contents, such as the hospital’s social projects or digital strategies for the next years.

Artificial intelligence, big data, and telemedicine have radically transformed hospitals, as well as doctors’ and nurses’ professional practices (Burret al., 2020). Thanks to smart technology, these professionals develop new skills and improve their patients’ medical outcomes (Rickert, 2020), which positively affects their personal brand reputation (Zhanget al., 2021). However, our results demonstrated that only 6 hospitals out of 140 had implemented an artificial intelligence department where employees were trained in this area. On the other hand, only 46 hospitals collaborated with external organizations to implement artificial intelligence projects. British hospitals could reinforce these collaborations to accelerate their digital transformation, help employees understand how to use this technology, improve patients’ medical outcomes, and reinforce the organization’s reputation.

This paper aimed to analyze how the best hospitals in the United Kingdom managed smart platforms to reinforce their brand. Even if we prove some important facts that will help hospitals hone their online branding strategies in the next years, we must highlight three main limitations. First, we did not analyze each hospital’s corporate communication plan, which prevented us from understanding the role of smart platforms in their branding processes. Second, we could not find any paper evaluating stakeholders’ perceptions of hospitals’ online branding initiatives, which made it difficult for us to evaluate the true impact of these platforms. And third, we did not find any article that analysed similar topics, which is why we could not compare our results with other countries or organizations. We recommend that researchers interested in this area should focus their efforts in the next years on the following topics: how to integrate smart technologies into the hospital’s medical protocols, how to train doctors and nurses on the professional management of smart platforms for branding purposes, and how to quantify the impact of online branding initiatives on the hospital’s scientific credibility.

Conclusion

Artificial intelligence, big data, telemedicine, mobile applications, and social media platforms have led hospitals to redefine their internal and external processes, as well as their corporate communication strategies. Integrating technology, medical protocols, and corporate communication constitutes a priority for hospitals interested in building a reputed brand. To efficiently do that, they need to redefine their relations with stakeholders. This paper aimed to analyse how the best hospitals in the United Kingdom managed smart technologies (websites, online newsroom, about us section, artificial intelligence department website) to interact with different stakeholders (patients, media companies, suppliers, shareholders, public authorities, and employees) and collectively build the organization’s brand. After analysing this area from a qualitative and quantitative perspective, we propose three last ideas.

First, most hospitals in the United Kingdom mainly focused on patients (4.98 criteria out of 11 applicable) and not on other targets such as journalists (3.01/11) or public authorities (2.16/6). This decision can seriously damage these organizations’ efforts to build a reputed brand since interacting with all stakeholders is essential to build a reputed brand. British hospitals should implement an integrated marketing communication approach considering several targets, platforms, and contents. Second, British hospitals should use smart platforms to implement new organizational processes with different targets and not only to disseminate corporate content. In other words, hospitals should establish processes that allow stakeholders to interact with hospitals in a different way: online press conferences (journalists), symptom checkers (patients), and smart platforms (suppliers, shareholders). Third, hospitals must develop digital transformation plans that establish how these organizations will use artificial intelligence to improve medical protocols, organizational processes, and branding initiatives. To do that, the first step consists of implementing an artificial intelligence department that leads this organizational change in a coordinated way.

References

  1. Adebesin, F., & Mwalugha, R. (2020). The Mediating role of organizational reputation and trust in the intention to use wearable health devices: Cross-country study. JMIR Mhealth and Uhealth, 8(6), e16721. 10.2196/16721.
     Google Scholar
  2. Bassan, S. (2020). Data privacy considerations for telehealth consumers amid COVID-19. Journal of Law and the Biosciences, 7(1), 1–12. 10.1093/jlb/lsaa075.
     Google Scholar
  3. Belani, S., Tiarks, G., Mookerjee, N., & Rajput, V. (2021). “I Agree to Disagree”: Comparative ethical and legal analysis of big data and genomics for privacy, consent, and ownership. Cureus, 13(10), e18736. 10.7759/cureus.18736.
     Google Scholar
  4. Burr, C., Taddeo, M., & Floridi, L. (2020). The ethics of digital well-being: A thematic review. Science and Engineering Ethics, 26, 2313–2343. 10.1007/s11948-020-00175-8.
     Google Scholar
  5. Butow, P., & Hoque, E. (2020). Using artificial intelligence to analyze and teach communication in healthcare. Breast, 50, 49–55. 10.1016/j.breast.2020.01.008.
     Google Scholar
  6. Castiglia, P., & Dettori, M. (2022). Second edition of special issue “Strategies and evidence in health communication: Evidence and perspectives”. International Journal of Environmental Research and Public Health, 19(3), 1460. 10.3390/ijerph19031460.
     Google Scholar
  7. Chamberlain, S., Dutt, P., Godfrey, A., Mitra, R., Lefevre, A., Scott, K. (2021). Ten lessons learnt: Scaling and transitioning one of the largest mobile health communication programmes in the world to a national government. BMJ Global Health, 6, e005341. 10.1136/bmjgh-2021-005341.
     Google Scholar
  8. Chen, J., & Wang, Y. (2021). Social media use for health purposes: Systematic review. Journal of Medical Internet Research, 23(5), e17917. 10.2196/17917.
     Google Scholar
  9. Chou, W. (2021). Using content analysis to inform health communication efforts on social media: Is popularity the goal? Mhealth, 7, 40. 10.21037/mhealth-2020-1.
     Google Scholar
  10. Courbier, S., Dimond, R., & Bros-Facer, V. (2019). Share and protect our health data: An evidence-based approach to rare disease patients’ perspectives on data sharing and data protection-quantitative survey and recommendations. Orphanet Journal of Rare Diseases, 14(1), 175. 10.1186/s13023-019-1123-4.
     Google Scholar
  11. Crossley, S., Balyan, R., Liu, J., Karter, A., McNamara, D., & Schillinger, D. (2020). Predicting the readability of physicians’ secure messages to improve health communication using novel linguistic features: Findings from the ECLIPPSE study. Journal of Community Health, 13(4), 1–13. 10.1080/17538068.2020.1822726.
     Google Scholar
  12. Dhagarra, D., Goswami, M., & Kumar, G. (2020). Impact of trust and privacy concerns on technology acceptance in healthcare: An Indian perspective. International Journal of Medical Informatics, 11(141), 104164. 10.1016/j.ijmedinf.2020.104164.
     Google Scholar
  13. Etheredge, H., & Fabian, J. (2022). Communication in healthcare: Global challenges in the 21st Century. Hamostaseologie, 42(1), 29–35. 10.1055/a-1685-7096.
     Google Scholar
  14. Farsi, D. (2021). Social media and health care, Part I: Literature review of social media use by health care providers. Journal of Medical Internet Research, 23(4), e23205. 10.2196/23205.
     Google Scholar
  15. Fazal, R., Shah, M., Khattak, H., Rauf, H., & Al-Turjman, F. (2022). Achieving data privacy for decision support systems in times of massive data sharing. Cluster Computing, 25(18), 1–13. 10.1007/s10586-021-03514-x.
     Google Scholar
  16. Ferretti, A., Ienca, M., Hurst, S., & Vayena, E. (2020). Big data, biomedical research, and ethics review: New challenges for IRBs. Ethics & Human Research, 42(5), 17–28. 10.1002/eahr.500065.
     Google Scholar
  17. Godsey, J., Houghton, D., & Hayes, T. (2020). Registered nurse perceptions of factors contributing to the inconsistent brand image of the nursing profession. Nursing Outlook, 68(6), 808–821. 10.1016/j.outlook.2020.06.005.
     Google Scholar
  18. Hart, B., & Phau, I. (2022). Conceptualising attitudes towards brand genuinuity: Scale development and validation. Journal of Brand Management, 29, 327–340. 10.1057/s41262-022-00272-y.
     Google Scholar
  19. Howe, E., & Elenberg, F. (2020). Ethical challenges posed by big data. Innovations in Clinical Neuroscience, 17(10–12), 24–30. 10.1007/s10067-020-04969-w.
     Google Scholar
  20. Hulsen, T. (2020). Sharing is caring-data sharing initiatives in healthcare. International Journal of Environmental Research and Public Health, 17(9), 3046. 10.3390/ijerph17093046.
     Google Scholar
  21. Kaissis, G., Makowski, M., Rückert, D., & Braren, R. (2020). Secure, privacy-preserving and federated machine learning in medical imaging. Nature Machine Intelligence, 2, 305–311. 10.1038/s42256-020-0186-1.
     Google Scholar
  22. Kordzadeh, N., & Young, D. (2018). Exploring hospitals’ use of Facebook: Thematic analysis. Journal of Medical Internet Research, 20(5), e190. 10.2196/jmir.9549.
     Google Scholar
  23. Kreps, G. (2020). The value of health communication scholarship: New directions for health communication inquiry. International Journal of Nursing Sciences, 10(7), 4–7. 10.1016/j.ijnss.2020.04.007.
     Google Scholar
  24. Li, Z., & Xu, J. (2020). Medicine together with humanities and media: An MHM model to move forward for health communication studies. International Journal of Nursing Sciences, 7(1), S1–S3. 10.1016/j.ijnss.2020.07.011.
     Google Scholar
  25. Li, Y., & Zhao, M. (2021). Underdog or top dog brand story? The role of self-construal and need of uniqueness. Frontiers in Psychology, 12, 765802. 10.3389/fpsyg.2021.765802.
     Google Scholar
  26. Lin, L., & Hou, Z. (2020). Combat COVID-19 with artificial intelligence and big data. Journal of Travel Medicine, 27(5), 80. 10.1093/jtm/taaa080.
     Google Scholar
  27. Lithopoulos, A., Evans, D., Faulkner, G., & Rhodes, R. (2021). Marketing physical activity? Exploring the role of brand resonance in health promotion. Journal of Health Communication, 26(10), 675–683. 10.1080/10810730.2021.1989524.
     Google Scholar
  28. Lv, Z., & Qiao, L. (2020). Analysis of healthcare big data. Future Generation Computer Systems, 109(1), 103–110. 10.1016/j.future.2020.03.039.
     Google Scholar
  29. Mackert, M., Mandell, D., Donovan, E., Walker, L., Garcia, M., & Bouchacourt, L. (2020). Mobile apps as audience-centered health communication platforms. JMIR mHealth and uHealth, 9(8), e25425. 10.2196/preprints.25425.
     Google Scholar
  30. Manrique de Lara, A., & Peláez-Ballestas, I. (2020). Big data and data processing in rheumatology: Bioethical perspectives. Clinical Rheumatology, 39(4), 1007–1014. 10.1007/s10067-020-04969-w.
     Google Scholar
  31. Medina Aguerrebere, P., Pacanowski, T., & Medina, E. (2020). Stakeholders’ participation in hospitals’ branding initiatives on social media: A proposal model for building collective brands. Revista Española de Comunicación en Salud, 11(1), 129–138. 10.20318/recs.2020.5097.
     Google Scholar
  32. Mheidly, N., & Fares, J. (2020). Leveraging media and health communication strategies to overcome the COVID-19 infodemic. Journal of Public Health Policy, 41(4), 410–420. 10.1057/s41271-020-00247-w.
     Google Scholar
  33. Molnár-Gábor, F., & Korbel, J. (2020). Genomic data sharing in Europe is stumbling-Could a code of conduct prevent its fall? EMBO Molecular Medicine, 12(3), e11421. 10.15252/emmm.201911421.
     Google Scholar
  34. Murdoch, B. (2021). Privacy and artificial intelligence: Challenges for protecting health information in a new era. BMC Medical Ethics, 22, 122. 10.1186/s12910-021-00687-3. Newsweek (2023)Newsweek (2023, June 10). World’s best hospitals 2023. https://www.newsweek.com/rankings/worlds-best-hospitals-2023/united-kingdom.
     Google Scholar
  35. Nichols, H., Dababnah, S., Berger, Z., Long, C., & Sacco, P. (2021). Can you hear me now? Effects of patient-centered communication with young adults aged 26 to 39. Journal of Patient Experience, 8, 23743735211033116. 10.1177/23743735211033116.
     Google Scholar
  36. Nittari, G., Khuman, R., Baldoni, S., Pallotta, G., Battineni, G., Sirignano, A. (2020). Telemedicine practice: Review of the current ethical and legal challenges. Telemedicine and EHealth, 26(12), 1427–1437. 10.1089/tmj.2019.0158.
     Google Scholar
  37. Odoom, P., Narteh, B., & Odoom, R. (2019). Healthcare branding: Insights from Africa into health service customers’ repeat patronage intentions. International Journal of Healthcare Management, 14(1), 1–13. 10.1080/20479700.2019.1688503.
     Google Scholar
  38. Oxman, A., Fretheim, A., Lewin, S., Flottorp, S., Glenton, C., Helleve, A. (2022). Health communication in and out of public health emergencies: To persuade or to inform? Health Research Policy and Systems, 20, 28. 10.1186/s12961-022-00828-z.
     Google Scholar
  39. Piculell, E., Skär, L., Sanmartin, J., Anderberg, P., & Bohman, D. (2021). Using a mobile application for health communication to facilitate a sense of coherence: Experiences of older persons with cognitive impairment. International Journal of Environmental Research and Public Health, 18(21), 11332. 10.3390/ijerph182111332.
     Google Scholar
  40. Rahman, R., Langner, T., & Temme, D. (2021). Brand love: Conceptual and empirical investigation of a holistic causal model. Journal of Brand Management, 28(1), 609–642. 10.1057/s41262-021-00237-7.
     Google Scholar
  41. Ramon Fernández, F. (2021). Inteligencia artificial en la relación médico-paciente: Algunas cuestiones y propuestas de mejora. Revista Chilena de Derecho y Tecnología, 10(1), 329–351. 10.5354/0719-2584.2021.60931.
     Google Scholar
  42. Razmus, W. (2021). Consumer brand engagement beyond the “Likes”. Frontiers in Psychology, 12, 692000. 10.3389/fpsyg.2021.692000.
     Google Scholar
  43. Reitsamer, B., & Brunner-Sperdin, A. (2021). It’s all about the brand: Place brand credibility, place attachment, and consumer loyalty. Journal of Brand Management, 28, 291–301. 10.1057/s41262-020-00229-z.
     Google Scholar
  44. Reza, S., Ansari, F., & Mahjob, H. (2022). Physicians’ brand personality: Building brand personality scale. Services Marketing Quarterly, 43(1), 48–66. 10.1080/15332969.2021.1989890.
     Google Scholar
  45. Rickert, J. (2020). On patient safety: The Lure of artificial intelligence-are we jeopardizing our patients’ privacy? Clinical Orthopedics and Related Research, 478(4), 712–714. 10.1097/CORR.0000000000001189.
     Google Scholar
  46. Rindell, A., & Santos, F. (2021). What makes a corporate heritage brand authentic for consumers? A semiotic approach. Journal of Brand Management, 28, 545–558. 10.1057/s41262-021-00243-9.
     Google Scholar
  47. Rodrigues, M., Belarmino, A., Custódio, L., Gomes, I., & Ferreira, A. (2020). Communication in health work during the COVID-19 pandemic. Investigación y Educación en Enfermería, 38(3), e09. 10.17533/udea.iee.v38n3e09.
     Google Scholar
  48. Sander, F., Föhl, U., Walter, N., & Demmer, V. (2021). Green or social? An analysis of environmental and social sustainability advertising and its impact on brand personality, credibility and attitude. Journal of Brand Management, 28, 429–445. 10.1057/s41262-021-00236-8.
     Google Scholar
  49. Shahid, A., Nguyen, T., & Kechadi, T. (2021). Big data warehouse for healthcare-sensitive data applications. Sensors, 21(7), 2353. 10.3390/s21072353.
     Google Scholar
  50. Shi, M., Jiang, R., Hu, X., & Shang, J. (2020). A privacy protection method for health care big data management based on risk access control. Health Care Management Science, 23(3), 427–442. 10.1007/s10729-019-09490-4.
     Google Scholar
  51. Shieh, G., Wu, S., Tsai, C., Chang, C., Chang, T., Lui, P. (2020). A strategic imperative for promoting hospital branding: Analysis of outcome indicators. Interactive Journal of Medical Research, 9(1), e14546. 10.2196/14546.
     Google Scholar
  52. Singla, V., & Sharma, N. (2021). Understanding ole of fonts in linking brand identity to brand perception. Corporate Reputation Review, 25, 272–286. 10.1057/s41299-021-00127-3.
     Google Scholar
  53. Tan, A., Soneji, S., Choi, K., & Moran, M. (2020). Prevalence of using pod-based vaping devices by brand among youth and young adults. Tobacco Control, 29(4), 461–463. 10.1136/tobaccocontrol-2019-055064.
     Google Scholar
  54. Tom, E., Keane, P., Blazes, M., Pasquale, L., Chiang, M., Lee, A. (2020). Protecting data privacy in the age of AI-enabled ophthalmology. Translational Vision Science and Technology, 9(2), 36. 10.1167/tvst.9.2.36.
     Google Scholar
  55. Trinidad, G., Platt, J., & Kardia, S. (2020). The public’s comfort with sharing health data with third-party commercial companies. Humanities and Social Sciences Communications, 7, 149. 10.1057/s41599-020-00641-5.
     Google Scholar
  56. Tsai, W., Lun, D., Carcioppolo, N., & Chuan, C. (2021). Human versus chatbot: Understanding the role of emotion in health marketing communication for vaccines. Psychology and Marketing, 38(12), 2377–2392. 10.1001/10.1002/mar.21556.
     Google Scholar
  57. Wang, J., & Wu, L. (2020). A comparison of health communication effectiveness and the improvement of management strategies: Taking two Chinese traditional medicine hospitals’ WeChat public accounts as examples. BMC Health Services Research, 20, 1055. 10.1186/s12913-020-05901-3.
     Google Scholar
  58. Wu, T., Deng, Z., Chen, Z., Zhang, D., Wu, X., & Wang, R. (2019). Predictors of patients’ loyalty toward doctors on web-based health communities: Cross-sectional study. Journal of Medical Internet Research, 21(9), e14484. 10.2196/14484.
     Google Scholar
  59. Wu, J., Wang, J., Nicholas, S., Maitland, E., & Fan, Q. (2020). Application of big data technology for COVID-19 prevention and control in China: Lessons and recommendations. Journal of Medical Internet Research, 22(10), e21980. 10.2196/2198.
     Google Scholar
  60. Yantian, M., Ahmad, Z., Alkhairy, I., Alsuhabi, H., Alizadeh, M., & Mouhamed, M. R. (2022). Brand awareness via online media: An evidence using instagram medium with statistical analysis. Computational Intelligence and Neuroscience, 2022, 1–13. 10.1155/2022/2739685.
     Google Scholar
  61. Zegers, C., Witteveen, A., Schulte, M., Henrich, J., Vermeij, A., & Klever, B. (2021). Mind your data: Privacy and legal matters in eHealth. JMIR Formative Research, 5(3), e17456. 10.2196/17456.
     Google Scholar
  62. Zhang, T., Yan, X., Wang, W., & Chen, Q. (2021). Unveiling physicians’ personal branding strategies in online healthcare service platforms. Technological Forecasting and Social Change, 171(3), 120964. 10.1016/j.techfore.2021.120964.
     Google Scholar
  63. Zhao, X. (2021). Challenges and barriers in intercultural communication between patients with immigration backgrounds and health professionals: A systematic literature review. Health Communication, 38(4), 824–833. 10.1080/10410236.2021.1980188.
     Google Scholar


Most read articles by the same author(s)