Systematic Approach in Digital Health Transformation in Healthcare: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
Mark Brommeyer
,
Zhanming Liang

The COVID-19 pandemic has sped up digital health transformation across the health sectors to enable innovative health service delivery. Such transformation relies on competent managers with the capacity to lead and manage. Sustainable, quality, and safe healthcare services require a management workforce equipped with contemporary leadership and management capabilities. With the ever-changing landscape of digital health, health service managers are required to lead and manage in times of system transformation. Digital competencies are required for the health service management (HSM) profession as well as the general healthcare workforce, which needs collaborative efforts across healthcare organizations, government, educational, and professional institutions. Management workforce capacity-building needs to adopt a holistic approach to developing the requisite HSM capabilities and system-wide capacity, which may include appropriate policy, supportive organizational systems and structure, and aligned education and training offerings. HSM workforce development is not a one-off effort. It requires system-level investment, support, and recognition, and collective efforts in removing the barriers and hurdles to the ongoing development of required digital health competencies and capabilities.

  • health service managers
  • digital health
  • health informatics
  • health workforce
  • health management

1. Introduction

In the rapidly changing, digitally-connected healthcare environment, health service managers need capabilities and relevant competencies to enable data-driven, strategic and operational decision-making [1][2][3], and the capacity to lead and manage digital health transformation. Health service managers must tackle the challenges of unprecedented growth in digital health literacy within this period of systemic transformation, and be proficient in planning and managing the digital tools and technologies across this shifting landscape [4][5].

1.1. COVID-19 and Digital Health Transformation in Healthcare

The COVID-19 pandemic has pressured the adoption of innovation in service delivery within healthcare systems and organizations globally, including the rapid adoption of digital health technologies, as healthcare practitioners and systems needed to adapt to new ways of working, with omnipresent social distancing and travel restriction requirements the norm. As witnessed in Europe and the United Kingdom, “many countries have adopted digital-first strategies, remote monitoring and telehealth platforms to enable healthcare provision without physical interactions” [6] (p. 1). In addition, digital health systems have also played a critical role in support of public health policies [7][8] and improving communication and information in healthcare; COVID monitoring and surveillance; health services provision, and vaccination bookings, recording, and monitoring [9]. In the United States of America, elements that supported the rapid adoption of digital health solutions and innovation during the pandemic included “technology innovations and policy prescriptions” (p. 9), including “right-sizing of regulation” (p. 8), for example, recalibrating virtual medical visit requirements under the Health Insurance Portability and Accountability Act [10]. In Australia, the Federal government’s pandemic response included implementing the required policy and funding arrangements for digital health innovation to be used across the country [11].
Globally, in August 2020, the G20 Riyadh Declaration on Digital Health was formulated, which presented nine recommendations on digital health to address the challenges of the COVID-19 and future pandemics. This included a “consensus on high-priority issues identified within 5 themes: team, transparency and trust, technology, techquity (the strategic development and deployment of technology in health care and health to achieve health equity), and transformation” [12] (p. 1). The fast growing cross-sector, digital health transformations highlight the pressing need to develop a workforce equipped with the knowledge, skills, and capabilities in deploying and managing digital technologies vital to meet the current and future public health challenges, in a timely and systematic manner [12].

1.2. Evidence on Workforce Development Needs

Success in healthcare innovation and transformation necessitates a health workforce with the required understanding and new skill sets, which does not happen overnight and is a continuous improvement process. Using the introduction of electronic health records (EHR) as an example, after being broadly implemented in the healthcare system, in particular the hospital sector for more than a decade, mounting evidence indicates that EHRs have not been adequately utilized by clinicians to guide clinical decision-making [13]. Clinicians’ lack of understanding of the benefits of EHRs, their frequent encounter with difficulties in access, and the perceived lack of effectiveness and efficiency of EHR usage, were the three major reasons for the lack of EHR take-up [14][15].
Empirical evidence further identified that leaders’ lack of awareness of their role in mobilizing and supporting staff and collaborating between key stakeholders in implementation, and inadequate understanding of the benefits of EHR, were two of the barriers to EHR success [1][16][17]. Not having the understanding of how EHRs can benefit and guide practices, and not having the technical skills required to work in the EHR context and utilize the digital data to guide decision-making, were the two key areas requiring targeted training and development prior to and during the introduction and implementation process [13].

1.3. Policy Guiding Digital Health Workforce Development

Overall health workforce development should be fundamentally driven and supported by workforce policy with allocated funding and resources [18], and concomitant efforts at system, institution, organization, and individual levels. In Australia, the Australian Digital Health Agency (ADHA) provides national policy direction and targeted funding for digital health, including the development of the National digital health workforce and education roadmap [19]. The roadmap clearly specifies the need to acquire a variety of digital literacy and baseline capabilities across the healthcare workforce, and suggests that the digital knowledge and skills required, will differ based on the diverse digital health roles and service delivery requirements throughout the healthcare system. They have also identified eight digital profiles, recognizing some consistency of digital capabilities required across health workforce roles, contexts or environments.
Two of the profiles: ‘leadership and executive profile’, and ‘the business, administration, and clinical support digital profile’, are both of particular importance as capable leaders and managers of a digitally-enabled workforce are key factors in successfully adopting and managing digital health transformation.
Unlike other health professions, health service management is not regulated, resulting in no specific requirements for management qualifications. Management competency improvements are often not embedded in regular management performance appraisals. This results in inadequate incentives for continuous, informal management training and development, which are both costly and time-consuming. Hence, in order to develop overall management workforce competence, political will and policy direction are required. International studies [20][21][22][23][24][25] have also highlighted that policy and system-level factors are crucial for healthcare management workforce development, in ensuring digital health adoption success. These factors include ensuring that a comprehensive digital health policy clearly aligns with the organization’s strategic goals, that support and investment in socio-economic and regulatory impact assessments of digital technologies are provided, and the privacy and integrity of digital data are assured. Clear governance rules and regulations regarding the use of digital technologies, supported by contextually applied technology implementation and outcome measurement training, are also critical.

1.4. The Role of Universities, Professional Institutions, and Organizations in Workforce Development

In addition to policy direction and incentives, the provision of skill development for the health workforce relies on the combined efforts between university programs, professional institutions, and individual healthcare organizations. Using the health service management (HSM) workforce in Australia as an example, at the institutional level, its development relies on 21 university programs such as the Master of Health Administration (MHA) and Master of Health Service Management (MHSM) awards, and professional institutions: the Australasian College of Health Service Management (https://www.achsm.org.au: accessed on 1 September 2022) and Royal Australasian College of Medical Administrators (https://racma.edu.au: accessed on 1 September 2022). Other member-based professional institutions, such as the Australian College of Nursing (https://www.acn.edu.au: accessed on 1 September 2022), Australian College of Rural and Remote Medicine (https://www.acrrm.org.au: accessed on 1 September 2022), and Australasian Institute of Digital Health (https://digitalhealth.org.au: accessed on 1 September 2022), also provide management development opportunities to specific professions.

Systematic Approach in Digital Health Transformation in Healthcare

2.1. Efforts in Developing a Digitized HSM Workforce

Efforts in developing a digitized HSM workforce are evident at multiple levels. Digital health and workforce policies have been developed [18]; professional institutions have been fast to recognize the additional skill development requirements by adding new competencies into the existing training frameworks. New postgraduate degrees focused on the systematic development of digital health professionals have also been developed and offered by a small number of Australian universities. However, whether the policies and revised frameworks have been translated into guiding the development of the HSM workforce that is digital health ready, remains unclear [26].
Although formal education is important in its ability to systematically develop one’s overall professional competence, the immediate upskilling of the HSM workforce relies on short-term professional development programs that allow immediate translation into practice [27][28][29][30][31][32]. This is particularly true when evidence indicates that specific competencies relevant to leading and managing digital health transformation are required to be developed among health service managers [33]. Short-term training targeting identified gaps in competencies is more appealing and relevant to health service managers for several reasons: workload, time availability, and level of required commitment.
Literature has confirmed that management and management competency is context- sensitive and influenced by the different nature of management positions and management levels [34][35]. A number of papers discussing the evaluation results of training programs reinforced the importance of taking organizational culture into consideration when designing training programs [36][37], hence, a work-based and action-learning approach was suggested [29][32]. This is certainly much easier to be adopted through short-term training programs rather than formal education, which was subject to strict university rules and regulations.
The higher the management levels, the higher the proportion of managers who would have acquired postgraduate qualifications [34][35], hence, short-term programs, without fulfilling other degree requirements, may be more attractive to senior management levels. On the other hand, entry- and middle-level managers may take on postgraduate study to increase competitiveness in advancing their management careers, hence, ensuring that the existing postgraduate curriculum addressing the competency development needs of their targeted student cohorts, must become one of the annual quality assurance processes for all postgraduate programs. In the case of digital health readiness, incorporating competencies that are necessary for managers to lead and manage in the digital health era, within the existing educational framework, is a very important step to take [38]. Professional institutions, such as ACHSM in Australia, have the responsibility to support and ensure the accredited formal education programs for health service managers, and are responsive to the development needs of the changing workforce [39].

2.2. The Importance of Strategic Planning, Support, and Removing Obstacles

It is important to develop health service managers’ digital health competencies, but this is only part of the answer to developing a workforce capable of leading and managing digital health transformation. Leading and managing digital health transformation is an emerging and essential requirement for health service managers, in addition to their existing core responsibilities. No training can immediately fully develop their competencies in strategically utilizing the ever-changing digital health tools and technologies, applying data governance [40], developing the right systems for data management [41], and having an organization-wide awareness of required digital tools and technologies [42]. Furthermore, a sound understanding of how digital health systems promote quality care [43], as well as personal health information privacy and security principles, are key attributes required of successful health service managers [5][41]. Technical expertise and organizational support are also necessary.
It is equally important to develop the health workforce’s overall understanding of digital health and how it can be used in context. This can be achieved through integrating digital health capabilities in all workforce activities, including systematic planning and embedding of professional development needs in long-term individual and organizational digital health goals [44]. The focus on developing foundational levels of digital literacy across the health workforce, and the depth of the requisite knowledge, needs to be based on the different digital health roles and people within the system [19].

2.3. A Holistic Approach toward HSM Workforce Development to Enable Digital Health Transformation

As discussed above, short-term training targeting the improvement of specific competencies, is one key strategy for the development of a competent and capable health management workforce. However, current training for managers is mostly designed and offered on an ad hoc basis and is based on a ‘what I believe is important’ mentality, by those who offer the training. A systematic approach to integrating the specific competencies required for leading and managing the workforce through digital transformation needs to be included in formal education, continuing professional development, and professional association recognition and certifications. This should include developing the system, organizational, and team management skills, as well as aligning the digital tools and technologies to support the necessary business and clinical, evidence-informed decision-making [45].
Competency assessment can identify an individual’s competency gaps and training needs via various processes such as self-assessment and 360-degree assessment [35][46]. Empirical evidence has also suggested that self-assessment is a very beneficial self-educational process leading to actual knowledge and skills improvement, and also an important motivating factor for self-learning [47][48]. Considering all key strategies and factors as discussed above, a framework to guide overall health management workforce development in the digital health era was proposed.
The framework suggests a national collaboration to articulate a more coordinated, consistent, and coherent set of policy guidelines that foster digital health and workforce development. Any national, digital health policy guidance and directions should be underpinned by relevant and contextualized global policies, for example, the World Health Organization guideline on digital interventions for health system strengthening [49].
Ongoing and collective efforts are required in developing a national, core set of digital health competencies for the healthcare management workforce that guide a more consistent curriculum and set of course offerings, which could then be accredited via a nationally endorsed, digital health capability framework, to better guide postgraduate workforce development and relevant professional development offerings. Recognizing that in Australia, as in many countries around the world, significant work has been undertaken, and is ongoing, to produce and ratify national digital health capability frameworks. These could also include reference to relevant and contextualized global frameworks, for example, the World Health Organization’s guidance on digital education for building health workforce capacity [50].

This entry is adapted from the peer-reviewed paper 10.3390/ijerph192113843

References

  1. Ingebrigtsen, T.; Georgiou, A.; Clay-Williams, R.; Magrabi, F.; Hordern, A.; Prgomet, M.; Li, J.; Westbrook, J.; Braithwaite, J. The impact of clinical leadership on health information technology adoption: Systematic review. Int. J. Med. Inform. 2014, 83, 393–405.
  2. Strudwick, G.; Nagle, L.M.; Morgan, A.; Kennedy, M.A.; Currie, L.M.; Lo, B.; White, P. Adapting and validating informatics competencies for senior nurse leaders in the Canadian context: Results of a Delphi study. Int. J. Med. Inform. 2019, 129, 211–218.
  3. Grain, H.; Hovenga, E. Health informatics competencies—Underpinning e-health. In Health Informatics: The Transformative Power of Innovation; IOS Press: Amsterdam, The Netherlands, 2011; pp. 73–81.
  4. Strudwick, G.; Nagle, L.; Kassam, I.; Pahwa, M.; Sequeira, L. Informatics competencies for nurse leaders: A scoping review. J. Nurs. Adm. 2019, 49, 323–330.
  5. Sheridan, P.T.; Watzlaf, V.; Fox, L.A. Health information management leaders and the practice of leadership through the lens of Bowen theory. Perspect. Health Inf. Manag. 2016, 13, 1–36.
  6. Peek, N.; Sujan, M.; Scott, P. Digital health and care in pandemic times: Impact of COVID-19. BMJ Health Care Inform. 2020, 27, e100166.
  7. Sust, P.P.; Solans, O.; Fajardo, J.C.; Peralta, M.M.; Rodenas, P.; Gabaldà, J.; Eroles, L.G.; Comella, A.; Muñoz, C.V.; Ribes, J.S.; et al. Turning the Crisis into an Opportunity: Digital Health Strategies Deployed during the COVID-19 Outbreak. JMIR Public Health Surveill. 2020, 6, e19106.
  8. Wong, B.L.H.; Maaß, L.; Vodden, A.; van Kessel, R.; Sorbello, S.; Buttigieg, S.; Odone, A.; Section, D.H.; European Public Health Association. The dawn of digital public health in Europe: Implications for public health policy and practice. Lancet Reg. Health-Eur. 2022, 14, 100316.
  9. Williams, G.A.; Fahy, N.; Aissat, D.; Lenormand, M.C.; Stüwe, L.; Zablit-Schmidt, I.; Delafuys, S.; Le Douarin, Y.M.; Muscat, N.A. COVID-19 and the use of digital health tools: Opportunity amid crisis that could transform health care delivery. Eurohealth 2022, 28, 29–34.
  10. Lee, P.; Abernethy, A.; Shaywitz, D.; Gundlapalli, A.V.; Weinstein, J.; Doraiswamy, P.M.; Schulman, K.; Madhavan, S. Digital Health COVID-19 Impact Assessment: Lessons Learned and Compelling Needs. In NAM Perspectives; National Academy of Medicine: Washington, DC, USA, 2022.
  11. Sturgiss, E.; Desborough, J.; Dykgraaf, S.H.; Matenge, S.; Dut, G.; Davis, S.; de Toca, L.; Kelly, P.; Kidd, M. Digital health to support primary care provision during a global pandemic. Aust. Health Rev. 2022, 46, 269–272.
  12. Al Knawy, B.; McKillop, M.M.; Abduljawad, J.; Tarkoma, S.; Adil, M.; Schaper, L.; Chee, A.; Bates, D.W.; Klag, M.; Lee, U.; et al. Successfully implementing digital health to ensure future global health security during pandemics: A consensus statement. JAMA Netw. Open 2022, 5, e220214.
  13. Laukka, E.; Huhtakangas, M.; Heponiemi, T.; Kanste, O. Identifying the Roles of Healthcare Leaders in HIT Implementation: A Scoping Review of the Quantitative and Qualitative Evidence. Int. J. Environ. Res. Public Health 2020, 17, 2865.
  14. Jones, E.B. Factors Associated with Electronic Health Record Use Among Nurse Practitioners in the United States. J. Ambul. Care Manag. 2017, 40, 48–58.
  15. Sockolow, P.S.; Bowles, K.H.; Adelsberger, M.C.; Chittams, J.L.; Liao, C. Challenges and Facilitators to Adoption of a Point-of-Care Electronic Health Record in Home Care. Home Health Care Serv. Q. 2014, 33, 14–35.
  16. Aarons, G.A.; Ehrhart, M.G.; Farahnak, L.R.; Sklar, M. Aligning Leadership Across Systems and Organizations to Develop a Strategic Climate for Evidence-Based Practice Implementation. Annu. Rev. Public Health 2014, 35, 255–274.
  17. Murphy, J. Leading from the future: Leadership makes a difference during electronic health record implementation. Front. Health Serv. Manag. 2011, 28, 25–30.
  18. Socha Dietrich, K. Empowering the Health Workforce—Strategies to Make the Most of the Digital Revolution. OECD Directorate of Employment. 2020. Available online: https://www.oecd.org/health/health-systems/Empowering-Health-Workforce-Digital-Revolution.pdf (accessed on 11 September 2022).
  19. Australian Digital Health Agency. National Digital Health Workforce and Education Roadmap; Australian Government: Sydney, Australia, 2020.
  20. Castillo, V.H.; Martínez-García, A.I.; Pulido, J.R.G. A knowledge-based taxonomy of critical factors for adopting electronic health record systems by physicians: A systematic literature review. BMC Med. Inform. Decis. Mak. 2010, 10, 60.
  21. Beane, A.; De Silva, A.P.; Athapattu, P.L.; Jayasinghe, S.; Abayadeera, A.U.; Wijerathne, M.; Udayanga, I.; Rathnayake, S.; Dondorp, A.M.; Haniffa, R. Addressing the information deficit in global health: Lessons from a digital acute care platform in Sri Lanka. BMJ Glob. Health 2019, 4, e001134.
  22. Scott, P.J.; Dunscombe, R.; Evans, D.; Mukherjee, M.; Wyatt, J.C. Learning health systems need to bridge the ‘two cultures’ of clinical informatics and data science. J. Innov. Health Inform. 2018, 25, 126–131.
  23. Craig, S.; Kodate, N. Understanding the state of health information in Ireland: A qualitative study using a socio-technical approach. Int. J. Med. Inform. 2018, 114, 1–5.
  24. Afnan, A.; Chandrasekaran, R. Factors Associated with EHR User Satisfaction in Small Clinic Settings. In Proceedings of the Thirty Sixth International Conference on Information Systems, Fort Worth, TX, USA, 13–16 December 2015; pp. 1–10.
  25. Stroetmann, K.A.; Artmann, J.; Stroetmann, V. Developing national eHealth infrastructures–results and lessons from Europe. In Proceedings of the AMIA Annual Symposium, American Medical Informatics Association, Washington, DC, USA, 22–26 October 2011; pp. 1347–1354.
  26. Ritchie, A.; Siemensma, G.; Fenton, S.H.; Butler-Henderson, K. Competencies, Education, and Accreditation of the Health Information Workforce. In Health Informatics; Springer: Cham, Switzerland, 2021; pp. 79–95.
  27. Agarwal, R.; Green, R.; Agarwal, N.; Randhawa, K. Management practices in Australian healthcare: Can NSW public hospitals do better? J. Health Organ. Manag. 2016, 30, 331–353.
  28. Chapman, T.W.; Confessorre, S. The dominant influence of social context on CEO learning in health care: A challenge to traditional management continuing education and development. J. Health Adm. Educ. 2002, 20, 123–134.
  29. Clarke, E.; Diers, D.; Kunisch, J.; Duffield, C.; Thoms, D.; Hawes, S.U.E.; Stasa, H.; Fry, M. Strengthening the nursing and midwifery unit manager role: An interim programme evaluation. J. Nurs. Manag. 2012, 20, 120–129.
  30. Gumus, G.; Borkowski, N.; Deckard, G.J.; Martel, K.J. Healthcare Managers’ perceptions of Professional Development and Organizational Support. J. Health Hum. Serv. Adm. 2011, 34, 42–63.
  31. Mutale, W.; Vardoy-Mutale, A.T.; Kachemba, A.; Mukendi, R.; Clarke, K.; Mulenga, D. Leadership and management training as a catalyst to health system strengthening in low-income settings: Evidence from implementation of the Zambia Management and Leadership course for district health managers in Zambia. PLoS ONE 2017, 12, e0174536.
  32. Edmonstone, J. Leadership development in health care in low and middle-income countries: Is there another way? Int. J. Health Plan. Manag. 2018, 33, e1193–e1199.
  33. Leung, T.I.; Wang, K.H.; McCall, T.; Merode, F.V. Leadership Roles in the Specialist Digital Health Workforce. In The Health Information Workforce; Springer: Cham, Switzerland, 2021; pp. 171–184.
  34. Liang, Z.; Howard, P.; Wang, J.; Xu, M.; Zhao, M. Developing senior hospital managers: Does ‘one size fit all’? Evidence from the evolving Chinese health system. BMC Health Serv. Res. 2020, 20, 281.
  35. Liang, Z.; Howard, P.F.; Leggat, S.; Bartram, T. Development and validation of health service management competencies. J. Health Organ. Manag. 2018, 32, 157–175.
  36. Weatherford, B.; Bower, K.A.; Vitello-Cicciu, J. The CNO and leading innovation: Competencies for the future. Nurs. Adm. Q. 2018, 42, 76–82.
  37. Cathcart, E.B.; Greenspan, M.; Quin, M. The making of a nurse manager: The role of experiential learning in leadership development. J. Nurs. Manag. 2010, 18, 440–447.
  38. Ackerly, D.C.; Sangvai, D.G.; Udayakumar, K.; Shah, B.R.; Kalman, N.S.; Cho, A.H.; Schulman, K.A.; Fulkerson, W.J., Jr.; Dzau, V.J. Training the next generation of physician–executives: An innovative residency pathway in management and leadership. Acad. Med. 2011, 86, 575–579.
  39. Australasian College of Health Service Management. Master Health Service Management Competency Framework; ACHSM: Sydney, Australia, 2016.
  40. Butler-Henderson, K.; Dalton, L.; Probst, Y.; Maunder, K.; Merolli, M. A meta-synthesis of competency standards suggest allied health are not preparing for a digital health future. Int. J. Med. Inform. 2020, 144, e104296.
  41. Valenta, A.L.; Meagher, E.A.; Tachinardi, U.; Starren, J. Core informatics competencies for clinical and translational scientists: What do our customers and collaborators need to know? J. Am. Med. Inform. Assoc. 2016, 23, 835–839.
  42. Westra, B.L.; Delaney, C.W. Informatics competencies for nursing and healthcare leaders. In Proceedings of the AMIA Annual Symposium, American Medical Informatics Association, Washington, DC, USA, 8–12 November 2008; pp. 804–808.
  43. Kennedy, M.A.; Moen, A. Nurse leadership and informatics competencies: Shaping transformation of professional practice. Stud. Health Technol. Inform. 2017, 232, 197–206.
  44. Gray, K.; Dattakumar, A.; Maeder, A.; Butler-Henderson, K.; Chenery, H. Advancing Ehealth Education for the Clinical Health Professions; Final Report; Australian Government Department of Education Office for Learning and Teaching: Sydney, Australia, 2018.
  45. Butler-Henderson, K.; Gray, K.; Pearce, C.; Ritchie, A.; Brophy, J.; Schaper, L.K.; Bennett, V.; Ryan, A. Exploring the health informatics occupational group in the 2018 Australian health information workforce census. Stud. Health Technol. Inform. 2019, 266, 44–50.
  46. Tetui, M.; Coe, A.B.; Hurtig, A.K.; Bennett, S.; Kiwanuka, S.N.; George, A.; Kiracho, E.E. A participatory action research approach to strengthening health managers’ capacity at district level in Eastern Uganda. Health Res. Policy Syst. 2017, 15, 39–53.
  47. Latham, G.; Almost, J.; Mann, S.; Moore, C. New developments in performance management. Organ. Dyn. 2005, 34, 77–87.
  48. Maurer, J.; Kimberly, A.; Haefner, J.; Stuart, A.; William, C. Beliefs about ‘improvability’ of career-relevant skills: Relevance to job/task analysis, competency modelling, and learning orientation. J. Organ. Behav. 2003, 24, 107–131.
  49. World Health Organization. WHO Guideline: Recommendations on Digital Interventions for Health System Strengthening; World Health Organization: Geneva, Switzerland, 2019.
  50. World Health Organization. Digital Education for Building Health Workforce Capacity; World Health Organization: Geneva, Switzerland, 2020.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
ScholarVision Creations
Feedback