Abstract
Introduction
While digital health interventions (DHIs) can potentially address the unmet needs for sleep health services, little is known about their implementation in practice. The current study aimed to explore primary care health providers’ attitudes and beliefs towards DHIs for sleep and implementation into practice.
Methods
A cross-sectional online survey was administered to Australian primary care health professionals: general practitioners (GPs), community nurses, and community pharmacists. Semi-structured interviews were conducted within a sub-sample of participants exploring their experiences with DHIs and perceived barriers/facilitators for embedding DHIs into primary care. Semi-structured interviews were thematically analysed using the framework approach to contextualise survey findings.
Results
Ninety-six surveys were returned (GPs = 36, nurses = 30, and pharmacists = 30) and 45 interviews conducted (GPs = 17, nurses = 14, and pharmacists = 14). From the survey, GPs were more likely to endorse familiarity (
Conclusion
Primary care health professionals highlighted the training, care pathway and financial models required to realise the potential for translating findings from efficacy studies for DHIs into primary care to optimise sleep health.
Keywords
Introduction
Sleep disturbances are highly prevalent in primary care but are sub-optimally addressed.1,2 Among factors such as lack of time, workload, and reimbursement, is the shortage of sleep physicians and psychologists to meet the demand for specialist sleep health services.2,3 Given sleep medicine is not a procedure-based speciality, it is amenable to digitalisation. As such, a multitude of digital health interventions (DHIs) have been developed to support core areas of sleep medicine practice over the last decade. Technological advances have further created new platforms for patient care access, ranging from telehealth video-conference calls that replace in-person clinic visits 4 to standalone web-based programs that offer patients on-demand therapeutic interventions. Specifically, sleep-related DHIs have targeted the treatment of sleep disorders such as obstructive sleep apnea using automated feedback mechanisms to improve adherence to continuous positive airway pressure (CPAP) therapy, 5 and delivering cognitive behavioural therapy for insomnia (CBT-I) digitally. 6 The latter has gained significant traction where several landmark studies and systematic reviews have demonstrated the feasibility and efficacy for digitalised CBT-I albeit smaller effect sizes when compared to face-to-face therapy (Cohen’s d = 1.2 vs. Cohen's d = 2.3), 7 while potentially overcoming geographical, 8 resource and scheduling constraints of traditional care models.6,9,10 A recent meta-analysis has further demonstrated comparable effects between face-to-face CBT-I and digital CBT-I involving a virtual or real therapist, 11 highlighting the potential for delivering digitalised CBT-I with guidance from a primary care health professional.6,8–10 More broadly, sleep telehealth services have also been evaluated in a number of settings in the United States, showing great promise for remote care 12 and are increasingly included as part of formalised training. 13
While the empirical evidence is promising, a considerable gap exists in understanding the real-world effectiveness of DHIs for sleep, or how to implement and embed them into routine primary care practice where their scalability is most useful. Effectively implementing sleep DHIs in primary care and the broader community is a timely and pertinent issue for public health policy, given the socio-economic impacts attributable to poor sleep, 14 which are further worsened by the effects of COVID-19 on sleep.15,16 More immediately, primary care providers may have renewed interest in deploying DHIs in their practice as many are likely to be already operating in an increasingly digitalised workspace. 17 Longer term, there is a need to strategically plan and build capacity for the anticipated increase in patient demand for specialist sleep services given the bi-directional relationship between sleep and mental health, 18 that is exacerbated post-pandemic. 19 To date, much of the literature on the implementation of digital health technologies in primary care has focused on the perspective of general practitioners (GPs) despite the diversity of professional stakeholders in primary care including nurses and community pharmacists.20,21 From a translational perspective, this represents a major gap in sleep medicine, considering the range of primary care providers that patients initially seek help from. 22 Further, the digitalisation process in the Australian practice context has largely focused on embedding systems into practice such as My Health Record and electronic prescribing.23,24 In contrast, little is known about the factors/constraints influencing the uptake, scalability, and dissemination of digital therapeutics for managing disease, despite their role in the next key phase for digitalisation in the healthcare landscape.
As such, the present study aims to capture the perspectives of GPs, community nurses, and community pharmacists with respect to their experiences and attitudes towards implementing digital health technologies for improving sleep health. More specifically, this study sought to gain deeper insight into the barriers and enablers of implementation for the respective professional disciplines.
Methods
For the purpose of this study, DHIs were operationalised as ‘the intersection of health care with the internet in which wearable devices, information technology (IT) and electronic communication tools converge to support the practice of medicine’. 25 This definition was also used to guide the framing of our research questions, study design, and analysis.
A mixed methods study was conducted using an online survey instrument and a series of semi-structured interviews conducted with GPs, community nurses, and community pharmacists practising in Australian primary care settings. The research protocol and study materials were approved by the Sydney Local Health District Human Research Ethics Committee (Approval No. 2019/ETH 1330).
Participants and recruitment
To capture the perspectives of key professional stakeholders in primary care, we recruited a convenience sample of individuals who were practising GPs, community nurses, and community pharmacists. Appreciating the heterogeneity of primary care practice, we sought to capture a representative sample of participants across the three professions, with a broad range of practice experience, that is, duration of practice and location of practice (i.e., rural vs. metropolitan).
Participants were recruited between August 2020 and December 2021 through active snowballing, reaching out to Australian public health networks, and drawing on the professional networks of the research team. Social media platforms (i.e., Twitter and Facebook) of the respective professions were also used to reach out to prospective participants. Participants responded to a targeted advertisement flyer on DHIs for sleep which contained an embedded study survey link and a quick response (QR) code. We note that the recruitment period of this study also coincided with the height of the COVID-19 pandemic in Australia. During this period, various public health measures and restrictions took place in local government areas, necessitating rapid digitalisation in healthcare delivery.
Prospective participants who were interested in participating clicked on a link/QR code and were taken to a landing page of the study website which contained a participant information sheet. Consenting participants completed the online survey instrument and on completion were asked about their interest in being interviewed. Those interested were requested to leave their contact details, and an interview on Zoom (audio only) or telephone was organised by a member of the research team. Informed consent was verbally verified prior to commencing the interview. Upon completion of the interview, participants received a $50 gift card as compensation for their time. Those who only completed the survey went in a draw to win one of three $200 gift cards. As this was an exploratory study, with the goal of measuring group differences we adopted a rough estimate of 30 participants per cell corresponding to each of the professions which equates to an approximate total sample size of 90. 26 Recruitment for the qualitative interviews continued until thematic saturation was reached where additional interviews do not yield any new thematic categories. 27 We estimated that approximately 12 participants from each professional group would yield thematic saturation and adopted a stop criterion of two consecutive interviews not yielding new thematic categories.27,28
Research instruments
Online survey
An online survey was developed to capture participant demographics, practice context, and current experience with using DHIs. A 10-item digital health implementation instrument was adapted from the items originally developed by Leigh and Ashall-Payne 29 to capture the importance of core attributes for participants to consider when implementing DHIs in practice (e.g. data security, privacy, and legal compliance). Each item was scored on a 7-point Likert scale (0 = not at all important, 6 = extremely important), but the instrument does not have a cut-off score for participants’ global ratings of the items (Supplemental Appendix A). Based on the modified Monash model, 30 participants’ geographical location of practice was recoded into three categories for ease of interpretation: metropolitan (MM1), regional (MM2), and rural/remote (MM3 to MM7). Participants also indicated their interest to be interviewed.
Semi-structured interviews
The interviews sought to capture participants’ practice environment, experiences with DHIs, and attitudes towards embedding DHIs targeting sleep health at their respective practice. As part of the interview, participants also described the features and functions of what they considered an ideal sleep DHI. Enablers and barriers to DHI implementation were also explored. The interview guide was developed by the first author (pharmacist academic) in collaboration with a nurse academic (CG) and clinical psychologist and DHI expert (MA). The included questions (Supplemental Appendix B) were largely informed by the literature on the management of sleep health 31 and the implementation/uptake of digital health in primary care.32,33 The interview guide was first piloted with a pharmacist, GP, and nurse known to the researchers and feedback was used to further refine the documents, but these interviews were not included in the final analysis. Subsequent interviews were conducted with participants via Zoom or telephone by two researchers: ZMS and JC. All interviews were digitally recorded and transcribed verbatim by an independent transcriber and checked for fidelity with the recorded audio by ZMS. Field notes were taken to facilitate analysis.
Statistical analysis
Descriptive statistics were computed for demographic and practice variables. Mean score ratings of the relative importance for each of the 10 attributes (e.g., financial incentives, data security, and cost to patients) for implementing DHIs were also computed for the total sample and by the health profession. To explore differences between the three professions in implementing DHIs, each was treated as an independent variable. Associations between categorical variables and profession were first explored using the chi-square test (e.g. use of DHIs in current practice; yes/no). The Benjamini–Hochberg procedure was used to adjust
Qualitative data analysis
The framework approach (FA) was adopted to guide the study design and analysis, facilitated by QSR NVivo 12 software. 34 FA evolved out of an applied social policy research tradition with the goal of meeting specific information needs and developing potential actionable outcomes in set timeframes.35,36 Additionally, FA merges inductive and deductive qualitative research traditions, addressing a priori questions set at the beginning of the study while identifying emergent ideas raised by the participants.
FA can be broadly divided into five key steps:
Participant quotes were selected to illustrate the identified themes. To maintain confidentiality, each participant was assigned a code, with the letter P followed by a number to indicate interview order, their professional discipline (i.e. GP, nurse, and pharmacist), gender (M: male; F: female), age, and years of practice.
Results
Participant characteristics
In total, 96 participants completed the survey comprising 36 GPs, 30 nurse practitioners, and 30 pharmacists. The mean age of all participants was 41.91 years (SD = 13.34). Our participant sample comprised approximately 70% female (
Summary of participant characteristics by profession.
Categorization based on the modified Monash model whereby MM1 = metropolitan, MM2 = regional and MM3 to MM7 = rural and remote.
The numerical subscripts denote means for groups in homogenous subsets.
Percentage (%) is expressed as a proportion within each profession; where there is missing data, the denominator from each proportion calculated is also expressed.
The same alphabetical subscript indicates that column proportions do not differ significantly from each other.
Participants who were interviewed (
Comparison of DHI use across healthcare professionals
Table 2 provides a summary of healthcare professionals' (HCPs) current use and attitudes towards DHIs. Of the three professions, GPs were more likely to report engaging with these technologies in general,
Current use and attitudes towards sleep-related digital health by profession.
The numerical subscripts denote means for groups in homogenous subsets.
Percentage (%) is expressed as a proportion within each profession; where there is missing data, the denominator from each proportion calculated is also expressed.
The same alphabetical subscript indicates that column proportions do not differ significantly from each other.
Qualitative thematic synthesis
Analysis of the qualitative data revealed three key emergent themes: Scope for DHIs in current practice, Practice gaps and training needs, and Envisioning a model of care using sleep DHIs. Tables 3 to 5 provide a summary of the thematic synthesis and illustrative quotes for emergent themes.
Theme 1: Scope for digital health interventions (DHIs) in current practice.
Theme 2: Practice Gaps and Training Needs.
Theme 3 envisioning a model of care using sleep digital health interventions (DHIs).
Theme 1: Scope for DHIs in current practice
Knowledge, beliefs, and experiences with DHIs
Among participants, the term DHIs was described as a ‘vague’ umbrella term that involved the use of technology to improve health delivery/patient outcomes. Key products mentioned in the interviews included smart phone applications, health informatics systems (e.g. prescribing systems, dispensing systems, and My Health Records), telehealth consultations, online self-guided programs, websites, as well as tracking devices. Participants’ understanding of DHIs stemmed from their own experiences either through engaging with technology at their workplace or through personal experiences with using tracking devices (e.g. Apple Watch) and smart phone applications. However, participants’ familiarity and implementation of DHIs varied according to their practice specialities. Those working closely in a mental health setting were more likely to integrate relaxation and mindfulness smartphone applications (e.g. Headspace) as part of standard patient care. While 26.8% of the total survey sample endorsed the use of sleep DHIs at their practice, open-text responses and the qualitative data suggest that current sleep DHI use mostly revolves around accessing online sleep health information and providing information printouts for interested patients.
COVID-19: A catalyst for digitalisation in primary care practice
Across the three professions, there was an apparent positive shift in attitudes towards digital health due to the rapid digitalisation of the workplace (i.e. telehealth and e-scripts), upskilling, workflow adjustments and upgraded infrastructure that is ‘already all set up’ (P8_GP: F; age: 66; practice: 30+ years) in response to COVID-19. Contextually, the pandemic has brought about important disruptions to practice, catalysing a shift in attitudes among policy makers such as the introduction of a medicare item for telehealth. In such a practice context, participants uncovered new and unexpected ways to deliver healthcare to patients. Patients were perceived to be more accepting and willing to use digital health technologies such as telehealth consultations and e-scripts. In the case of older patients at the respective practices, many were able to engage with digital health, albeit through the support of family members, to achieve positive outcomes.
Perceived need and place for DHIs
Participants at large spoke about the potential utility of DHIs to improve the efficiency of health services delivery. Specifically, DHIs could potentially overcome staff shortages in aged-care and in rural/remote settings where retaining expertise proved challenging. The utility of DHIs was seen as most applicable in the areas of health tracking (e.g.
Theme 2: Practice gaps and training needs
Knowledge about sleep health: Breadth versus depth
In general, participants described the limited coverage of sleep health as part of their training at university or existing continuing professional development (CPD) activities. Differences in training/knowledge of sleep health and sleep disorders between HCPs were attributed to working in different speciality practice contexts such as a sleep laboratory, pharmacy providing CPAP services, or clinical settings with a mental health focus. Except for three nurses (P23, P24, and P25) who had received formal CBT-I training, sleep hygiene and lifestyle factors were the predominant non-pharmacological treatment options offered to patients across the three professions. Participants described their knowledge of sleep health as ‘knowing a little about everything’ (P03_Pharmacist: F; age: 37; practice: 11–20 years), identifying gaps in their understanding of the underlying pathophysiology of sleep disorders, diagnosis, treatment options, and referral pathways. A subset of participants further highlighted limitations of existing tools for sleep health which provide prompts to assess sleep health but ‘…doesn’t guide you to another source of health’ (P07_Nurse: F; age: 51; practice: 21–30 years) for patients who need further care. Importantly, across the three professions, there was an interest in upskilling therapeutic knowledge in sleep with suggestions for increasing training as part of their CPD (i.e. online modules, webinars, or workshops) or as part of workplace meetings. However, training affordability and competing demands between different therapeutic areas remain important barriers to HCP engagement.
Expectations for a sleep DHI
Descriptions capturing what a sleep DHI would entail were closely related to participants’ current knowledge about sleep health and drew on the platforms and devices they were already familiar with (e.g. Fitbit tracking systems and calm). Key areas of focus for a sleep DHI included sleep tracking (e.g. total sleep hours and sleep stages), education modules and capitalising on the technological capabilities to engage the user and facilitate sleep behaviour changes. Suggestions included the use of algorithms which strategically schedule pop-up alerts based on sleep patterns such as ‘stop screen time now’ (P33_GP: F; age: 36; practice: 6-10 years) or ‘waking up to a favourite song’ (P17_Pharmacist: M; age: 43; practice: 11–20 yrs) as positive behaviour reinforcement for regular sleep–wake schedules. Tailoring the DHI to the individual was highlighted as an important feature in the development of sleep DHIs rather than a ‘one-size-fits-all’ (P16_GP: F; age: 62; practice: 30+ years). A pharmacist drew parallels to the limitations of existing digital health products which are ‘very general and don’t speak to most people in specific…’ (P21_Pharmacist: F; age: 31; practice: 6–10 years). Closely related was the need for an intuitive user-interface, which will facilitate patient onboarding and the clinicians’ ability to access and use data to inform patient care.
Readiness to implement sleep DHIs
With respect to the confidence and feasibility of embedding sleep DHIs into practice, participants described their readiness in terms of two separate domains. From the perspective of technological infrastructure (e.g. computer hardware), participants felt ‘most of the barriers have been overcome’ (P08_GP: F; age: 66, practice: 30+ years), considering the recent upgrades and upskilling at the respective practices in response to COVID-19. As such, implementing new digital health technologies was perceived as an extension of their current practice. In contrast, participants were less confident in their depth of knowledge concerning the physiological mechanisms underlying sleep disorders and their management. Another factor central to the implementation of sleep DHIs was patient uptake. Participants highlighted the importance of test-driving digital health products to gauge usability and identify potential pitfalls to facilitate patient education and counselling. Specifically, having demonstration devices, user guides and patient-centred education materials that are written in a way that ‘consumers will find useful’ (P19_Nurse: M; age: 38; practice: 11–20 years) would enhance the patient onboarding process.
Theme 3: Envisioning a model of care using sleep DHIs
Accessing sleep DHIs in primary care: A vision for future practice
Participants from the respective professional groups articulated different ideas for the pathway to allow patients in the community to access sleep DHIs ranging from ‘anyone should be able to access it’ (P18_GP: F; age: 36; practice: 11–20 years) through to needing a prescription. Despite the range of proposed access options, the involvement and oversight by an HCP were deemed necessary by all three professions. GPs and community nurses generally thought sleep DHIs are best prescribed to patients, drawing parallels to ‘the same way people get prescriptions for knee-strengthening exercises for osteoarthritis’ (P16_GP: F; age: 62; practice: 30+ years). Nurses working in a practice team with other GPs would ‘potentially okay it with the doctor’ (P06_Nurse: F; age: 30; practice: 6–10 years). Both GPs and nurses believed pharmacists would adopt a support role for implementing sleep DHIs, noting that pharmacists’ expertise was largely in medicines. However, all three professions agreed that direct product requests for sleep aids were a unique opportunity for pharmacists to ‘flag patients’ (P31_GP: F; age: 36; practice: 11–20 years) to educate them about sleep DHIs. Extending from this concept, pharmacists further suggested a stepped approach to accessing the sleep DHI, which can operate as a ‘two-tiered sort of program’ (P21_ Pharmacist: F; age: 31; practice: 6–10 years), offering patient access to general education modules while advanced functions/treatment modules would only be unlocked upon consultation with an HCP.
Practice readiness for implementing sleep DHIs: Perceived barriers and enablers
Participants felt ready to implement DHIs in general given the technological infrastructure upgrades and staff upskilling at the respective practices in response to COVID-19. However, limited time and anticipated workload increases were identified as key barriers to implementing DHIs that specifically targeted sleep. There was recognition that investing in more staff would be necessary to build capacity for delivering these services. Willingness to invest in human resources would be contingent on the financial sustainability of the DHIs as ‘it has to run as a profitable practice’ (P23_Nurse: F; age: 59; practice: 30+ years). Unlike technologies that are systemically built for the broader clientele base (e.g. telehealth consultations and e-scripts), participants’ responses implicitly categorised sleep DHIs as a speciality service, which may not have the same level of patient demand. Relatedly, HCP reimbursement was another area of concern. While GPs and nurses commented on the need to identify an appropriate time allocation for DHI implementation, community pharmacists identified a broader range of issues that need to be addressed. Firstly, pharmacists needed more clarity on how DHIs would fit within the Community Pharmacy Agreements (CPAs) 1 as DHIs represent a significant departure from their current provision of medicines.
Government, regulations, and policymaking for DHIs
Currently, participants felt overwhelmed by the sheer number of health apps/devices on the market, which lack information on safety and efficacy, noting that there is ‘so much quackery out there’ (P30_GP: F; age: 58; practice: 30+ years). From a medicolegal perspective, participants highlighted the need for better government involvement in providing therapeutic standards and greater regulatory oversight before digital health products come to market, as per medical devices and medications. Such an approach would enhance the consistency of DHI use while instilling confidence in the general public to use DHIs as part of their care. Importantly, proven clinical efficacy and safety would ‘take away the challenges’ (P23, Nurse: F; age: 59; practice: 30+ years) for clinicians to embed DHIs in their routine practice, allaying concerns around issues of professional liability and compromised public trust in the respective professions. In contrast, participants did not perceive data privacy and security issues as being a huge concern for patients at the respective practice. Many described DHI users as self-selected individuals who ‘worked out they were quite comfortable with their use’ (P16_GP: F; age: 62; practice: 30+ years) of such products. This was largely attributed to the expansive ways in which smartphones and apps are used day to day where there is ‘…no difference…’ (P03_ Pharmacist: F; age: 37; practice: 11–20 years) when it comes to using DHIs. Participants also highlighted patient trust in the HCP as key to allaying patient concerns about the legitimacy of the DHI and data security. As such, transparency about the evidence supporting DHIs, the accreditation process, the types of information collected, and how and where this information is stored would be important to allow HCPs to help patients make informed choices.
Discussion
To our knowledge, this is one of the first studies which has explored and triangulated the perspectives of primary care health professionals on the implementation and usage of sleep DHIs. Three key themes were identified following interviews with GPs, nurses, and community pharmacists: Scope for DHIs in current practice, Practice gaps and training needs
The response to COVID-19 has shifted primary care providers’ perspectives on digital health technologies and perceived an increase in patients’ acceptability and engagement with digital health platforms. However, participant interviews across the three professions confirmed the need for greater clarity for delineating digital health care pathways, patient access points, and integration with existing health informatic systems (e.g. prescribing and dispensing software). The latter is a well-established clinician-level barrier to the uptake of DHIs, 37 which is increasingly important given the proliferation of technology-enabled care across disease states, including sleep health. 38 As such, multi-stakeholder consultation in co-designing the informatic system interface is needed for aligning patient digital health needs with clinician workflow.39,40 One strategy is to capitalise on the existing system structures to lower the threshold of practice uptake. Internationally, DHI developers are increasingly embedding digital therapeutics through a pharmacy pathway, to capitalise on the existing informatics systems that connect patient records with insurers. 41 Another point of integration could be the expansion of the prescriber formulary to include DHIs as demonstrated by Byambasuren et al. 42 There is also scope for expanding the healthcare team to include a digital navigator with expertise in digital health who can facilitate the implementation of new technologies in practice. 43
Differences between the professions were also observed. Survey responses showed that GPs were most familiar with sleep DHIs and were more likely, of the three professions, to use general DHIs and sleep-specific DHIs in their current practice. From Table 1, nurses and pharmacists most frequently reported being employed on a casual status, which may limit opportunities for scaling up DHIs as they are often employed on a needs basis to address staffing shortfalls. Differences in reimbursement needs were also apparent across the three professions. While GPs and nurses sought clarity in terms of how sleep DHIs would fit into the existing consultation structures, pharmacists identified more barriers, endorsing stronger importance of financial incentives (
In implementing sleep DHIs in practice, participants’ main concerns stemmed from the lack of regulation for the safety, quality, and efficacy of existing e-health products. Many commented on feeling overwhelmed by the sheer volume of products, making the selection of DHIs challenging in practice. These sentiments are reflected in participants’ survey responses highlighting the prioritisation of privacy policy, legal compliance, and having a trustworthy repository when considering or implementing DHIs (Table 2).47,48 In fact, clinician uncertainty often prevents the uptake of new interventions in practice changes, 49 which may underpin the challenge of implementing sleep DHIs in primary care. Studies conducted in other therapeutic areas also highlight similar barriers to the uptake of DHIs in cardiovascular 50 and diabetes care.51,52 Strengthening regulatory processes with evidence-based components relating to safety, efficacy, and quality is an important priority for expanding DHIs into routine care including sleep health. A key challenge for regulating the digital health marketplace is its rapid pace and evolution, posing difficulties for regulatory bodies to keep up with the changes/updates. 53 Rodriguez-Villa and Torous 54 proposed a public-interactive approach, which encourages individuals with real-world experiences, to comment on developers’ answers to a set of self-certification check-list questions. Currently, the US Food and Drug Administration (FDA) is piloting the ‘FDA Digital Health Software Pre-certification (Pre-Cert) Program’. 55 While the program aimed to expedite the approval process with companies/enterprises with an existing track-record, it does provide a framework for identifying real-world effectiveness and potentially understanding important variations which arise between research and real-world settings. 56
Strengths and limitations
The strength of the current study stems from the mixed methods study design, corroborating qualitative and quantitative findings. This method increases an understanding of the complexities of implementing DHI, overcoming the methodological limitations of either method alone.
57
Our sample size (
However, there are some limitations to consider. Our participants were a self-selected sample of primary care practitioners who are potentially more interested in digital health technologies compared to the general population. Nonetheless, these participants are more likely to be early adopters of DHI technologies, making their perspectives and experiences highly valuable for informing the early stages of piloting and implementation of DHIs. Another limitation of the current study was hypothetical bias. As participants were not shown an actual sleep DHI that they would implement, participants may overestimate the amount of time/money they would be willing to invest in expanding this area of practice/suitability of the DHI to their current practice may differ. 58 Furthermore, the findings captured only provide a cross-sectional perspective of DHI use and integration at the height of the pandemic and participants’ perspectives may have changed, warranting the need for ongoing research to explore HCP needs and practice trends. Additionally, the instrument for capturing attributes for DHI implementation was not a validated measure. The median scores for the individual item suggest participants endorsed a high level of importance across a range of attributes. However, these findings need to be interpreted with caution as they are based on a single item. Furthermore, it is unclear how different cut-off scores would correlate or predict DHI uptake, emphasising the need for further validation for use in primary care.
Conclusion
Sleep-related DHIs represent a promising avenue for primary care practice to meet patient demands for therapeutic sleep health treatments. While the disruption of COVID-19 provided a unique opportunity (i.e. personnel upskilling and infrastructure upgrades) to embed digital health solutions into routine practice, the interviews highlighted the uncertainties among primary care providers. These uncertainties stem from reimbursement concerns, training, as well as their practice environment. From a disciplinary perspective, there is a need to promote and expand the roles of different HCPs. Developing an operational framework for how DHIs are regulated and fit within current pathways of healthcare in Australia is extremely important. A key agenda in health policy is to allow DHIs to become part of routine care to improve patient outcomes with current finite health resources.
Supplemental Material
sj-docx-1-dhj-10.1177_20552076231180970 - Supplemental material for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists
Supplemental material, sj-docx-1-dhj-10.1177_20552076231180970 for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists by Janet MY Cheung, Zoe Menczel Schrire, Melissa Aji, Matthew Rahimi, Helena Salomon, Iliana Doggett, Nicholas Glozier, Delwyn J. Bartlett, Keith Wong, Ronald R. Grunstein and Christopher J. Gordon in DIGITAL HEALTH
Supplemental Material
sj-docx-2-dhj-10.1177_20552076231180970 - Supplemental material for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists
Supplemental material, sj-docx-2-dhj-10.1177_20552076231180970 for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists by Janet MY Cheung, Zoe Menczel Schrire, Melissa Aji, Matthew Rahimi, Helena Salomon, Iliana Doggett, Nicholas Glozier, Delwyn J. Bartlett, Keith Wong, Ronald R. Grunstein and Christopher J. Gordon in DIGITAL HEALTH
Supplemental Material
sj-docx-3-dhj-10.1177_20552076231180970 - Supplemental material for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists
Supplemental material, sj-docx-3-dhj-10.1177_20552076231180970 for Embedding digital sleep health into primary care practice: A triangulation of perspectives from general practitioners, nurses, and pharmacists by Janet MY Cheung, Zoe Menczel Schrire, Melissa Aji, Matthew Rahimi, Helena Salomon, Iliana Doggett, Nicholas Glozier, Delwyn J. Bartlett, Keith Wong, Ronald R. Grunstein and Christopher J. Gordon in DIGITAL HEALTH
Footnotes
Author's Note
Christopher J. Gordon is also affiliated with Department of Health Sciences, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.
Acknowledgement
We would like to thank all participants for their time and committment to the reseaarch study.
Contributorship
JMYC contributed to the design of the qualitative research instruments and protocols; provided intellectual input to the analysis of qualitative and quantitative data; and wrote the initial draft of the manuscript. ZMS contributed to the coordination of participant interviews, data collection and coding of qualitative data. She has also extensively edited and revised the manuscript. MA contributed to the development and design of the qualitative and quantitative research instruments; facilitated the interpretation of data from analysis; edited and revised the manuscript. MR contributed to the development and design of the qualitative and quantitative research instruments; edited and revised the manuscript. HS contributed to data collection for the quantitative study; edited and revised the manuscript. ID contributed to data collection for the quantitative study; edited and revised the manuscript. NG contributed to the study design, provided intellectual input to the statistical analysis, and extensively revised the manuscript. DJB contributed to the study, provided expert clinical feedback on the research instruments and protocols, and extensively revised the manuscript. KW contributed to the study design and provided expert clinical feedback on the research instruments design and provided feedback and revised the manuscript. RRG contributed to the study design, provided expert clinical feedback on the research instruments and study protocol, and revised the manuscript. CJG is the principal investigator who conceptualised the research project, extensively contributing to the development of research instruments and protocols, managed the analysis strategy for this study and extensively revised the manuscript.
Declaration of conflicting interests
The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: JMYC, ZMS, MA, MR, HS, ID, and KW have no further conflicts to declare. NG serves on the advisory board for and received honoraria from Merck. DJB co-developed SleepFix as part of a funded project from the Cooperative Research Centre for Alertness, Safety, and Productivity; and named two provisional patents for the SleepFix app. RRG was funded by a National Health and Medical Council of Australia Senior Principal Research Fellowship (1106974); co-developed SleepFix as part of a funded project from the Cooperative Research Centre for Alertness, Safety, and Productivity; and named two provisional patents for the SleepFix app. CJG led the development of SleepFix as part of a funded project from the Cooperative Research Centre for Alertness, Safety, and Productivity; and was named two provisional patents for the SleepFix app.
Data availability
The data that support the findings of this study are available on request from the senior author (CJG). The data are not publicly available as it contains information that could compromise the privacy of research participants.
Ethical approval
The research protocol and study materials were approved by the Sydney Local Health District Human Research Ethics Committee (Approval No. 2019/ETH 1330).
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Department of Health (Federal), Sydney Health Partners Medical Research Future Fund 2019 Rapid Applied Research Translation Award Grant.
Guarantor
CJG.
Supplemental material
Supplemental material for this article is available online.
Notes
References
Supplementary Material
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