Identification of which glaucoma patients are most appropriate for home monitoring

Carrie Stewart; Hangjian Wu; Uma Alagappan; Augusto Azuara-Blanco; Anthony J King; Andrew J Tatham; Rodolfo Hernández; Bruce Lowe; Darian Shotton; Nana Appiah; Taylor Coffey; Thenmalar Vadiveloo; Graeme MacLennan; Katie Gillies

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Stewart C, Wu H, Alagappan U, et al. Feasibility of in-home monitoring for people with glaucoma: the I-TRAC mixed-methods study. Southampton (UK): National Institute for Health and Care Research; 2024 Aug. (Health Technology Assessment, No. 28.44.)

Feasibility of in-home monitoring for people with glaucoma: the I-TRAC mixed-methods study.

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Chapter 2Identification of which glaucoma patients are most appropriate for home monitoring

There is limited guidance in the literature as to which glaucoma patients would be the ideal candidates for home monitoring using digital technology. Identifying key uncertainties regarding candidate suitability, such as who are the appropriate patients to target for evaluating an intervention, is a critical first step towards evaluating its use. This chapter reports the findings from an online survey with expert glaucoma clinicians to determine which glaucoma patients are most appropriate for home monitoring and to investigate clinical decision-making in relation to patient suitability.

Methods

Study design

Online survey involving expert glaucoma clinicians, who have not been involved in the glaucoma home monitoring intervention component of the study.

Sampling and recruitment

The target population were expert glaucoma clinicians (i.e. ophthalmologists and optometrists). To take part in our study, participants needed to work within the UK NHS, presently deliver care to persons with glaucoma, and agree to take part in the study. Based upon the estimated number of glaucoma clinicians registered with the UK and Eire Glaucoma Society (UKEGS), a non-profit professional society for clinicians with a specialist interest in glaucoma (range n = 69–72⁴⁰^,⁴¹) we are accepting our denominator for calculating response rate as n = 72. UKEGS does not currently record the designation of its members, so the exact number of glaucoma consultants surveyed is unknown.

In order to target clinicians with directly relevant experience, the survey was disseminated via UKEGS. A link to the questionnaire with an invitation to participate was e-mailed to members of UKEGS by the UKEGS Communications Manager. In addition to the invitation e-mail, the clinical co-investigators raised awareness of the questionnaire among existing clinical networks. The survey was active from 14 May to 30 October 2021.

Data collection

An online survey including both closed and open-ended questions, informed by the literature and expert opinion within the research [including three clinical Principal Investigators (PIs): AAB, AK and AT], was created through SurveyMonkey^® (Palo Alto, CA, USA).⁴² A participant information leaflet (containing general information about the I-TRAC study and the home monitoring devices) was included at the start of the survey to support informed consent but also to ensure participants were given contextual insights to promote informed responses. For example, a summary of the NICE guidelines for ocular hypertension (OHT) and primary open-angle glaucoma (POAG) was included alongside an introduction to the technologies being discussed (iCare HOME tonometer and tablet-based apps for measuring visual function).

Participants were asked to decide if they would use the iCare HOME tonometer and/or an app for visual function, for four clinical scenarios. The patient scenarios were developed to reflect fictional patients (but based on real examples) and included hypothetical details on glaucoma severity (mild, moderate, severe), current treatment, risk of visual loss, disease control (apparently well controlled, uncertain, poorly controlled), and management options, as well as demographic details (Table 1). These cases were designed to reflect the NICE guidelines for OHT and POAG. When a clinician did not recommend a patient’s suitability for home monitoring, they were asked to justify this decision. Scenario 5 described a clinical model of care in which a doctor integrates the home monitoring devices within their routine glaucoma care due to reduced clinic capacity. Clinicians were asked to determine whether this model of care was acceptable to them, why it was/was not acceptable, and to tell us about perceived advantages and disadvantages to this model of care.

TABLE 1

Summary description of clinical scenarios presented

Survey participants were asked to provide demographic data including age, gender, ethnicity, profession, the number of years’ experience in treating glaucoma, and current or past use of technologies for measuring IOP and/or visual function in patients at home.

The data collected through SurveyMonkey were downloaded and stored in an Excel^® worksheet [Microsoft^® Excel for Microsoft 365 MSO (Version 2205 Build 16.0.15225.20394); Microsoft Corporation, Redmond, WA, USA]. Participant responses were anonymous and assigned a unique identifier number.

Data analysis

Quantitative data from closed-ended questions were analysed using descriptive statistics (e.g. frequencies, percentages). Agreement with clinical scenarios was defined by the study team as being ≥ 60% in either supporting or not supporting the hypothetical patient to be home monitored using the digital technology. Agreement across clinical scenarios was also investigated in a post hoc analysis and reported using frequencies. Free-text responses, such as those asking for clinical reasoning for the monitoring decision, and the frequency and duration of monitoring, were analysed using directed content analysis.⁴³ Within this, a hybrid approach, combining both inductive (data-driven) and deductive (based on preconceived ideas) methods was followed. Frequency and duration responses were free text and were reviewed across all clinical scenarios (scenarios 1–4) to create categories that could be applied across scenarios for ease of comparison. Reasons behind the perceived unsuitability of each clinical scenario for home monitoring were analysed and reported within each scenario. Similarly, explorations of the acceptability of this model of care were analysed within scenario 5 where several questions regarding perceived barriers and facilitators were presented. Within this project, a barrier was defined as ‘a circumstance or obstacle that keeps people or things apart or prevents communication or progress’.⁴⁴ A facilitator was defined as ‘the factors that enable the implementation of evidence-based interventions’.⁴⁵

The Microsoft Excel spreadsheet was transferred to NVivo software (version 12 qualitative analysis programme; QSR International, Warrington, UK).⁴⁶ Data were reviewed and emerging themes noted. Following several reviews of the data by two reviewers (UA and CS), a coding dictionary describing the themes and categories found within participant responses was developed. Within NVivo, a tree chart was constructed to explore the weighting of each of the themes, subthemes and codes created from the survey responses. This allowed identification of the major themes based on the volume of responses addressing this topic, number of participant comments and relevance as deemed by the researcher.

Results

Sample demographics

A total of 64 clinicians accessed the survey, a response rate of 89% (n = 64/72, 72 being the upper limit in the range of eligible clinicians registered with UKEGS who had a special interest in glaucoma). Four participants were excluded based on lack of experience treating glaucoma (n = 3), as per the exclusion criteria, and one participant did not respond to any of the questions. A further 11 were excluded from the final analysis as they did not respond to the clinical scenario questions and only provided demographic data. Therefore, 49 clinicians who replied to at least one of the questions in relation to the clinical scenarios were included in the final analysis (77%, n = 49/64). Table 2 shows the characteristics of the respondents. The majority of participants were white (59%, n = 29), male (69%, n = 34), consultants (92%, n = 45), aged between 50 and 59 years (45%, n = 22), who have treated glaucoma patients for > 10 years (71%, n = 35). The demographics of those removed from final analysis (n = 11, not presented) showed a similar pattern in that they were mostly of white ethnicity (82%, n = 9), consultants (82%, n = 9) with extensive experience (64%, n = 7, over 10 years’ experience). However, they were younger (64%, n = 7, < 50 years of age) and the gender split was more equal between male and female (male, 36%, n = 4; female, 36%, n = 4, with 3 preferring not to report their gender).

TABLE 2

Expert glaucoma clinicians demographics (n = 49)

Clinician decisions regarding patient suitability for glaucoma home monitoring

Across the scenarios, there were varying rates of agreement regarding the suitability of each patient scenario for home monitoring (Figure 1 and Table 3). Based on the levels of agreement defined (i.e. > 60% reporting a patient as suitable), only one patient, scenario 4, was deemed suitable for home monitoring. In the scenario, 61% (n = 30) of clinicians would refer the patient to use the iCare tonometer and 65% (n = 32) the home visual function app assessment. Scenario 4 reported Ms McEwen, a low-risk patient with normal tension glaucoma (NTG) and mild disease who had not progressed in 5 years.

FIGURE 1

Clinician agreement on home monitoring using digital technology within patient scenarios.

TABLE 3

Expert glaucoma clinician agreement on patient suitability for glaucoma home monitoring (N = 49)

Clinicians were asked to suggest optimal time frames for the frequency and duration of home monitoring (of both IOP and visual function) through open-ended questions in each scenario. Similar to the variation in responses to clinical scenarios, a wide spectrum of monitoring frequencies and durations for each scenario were suggested (Table 3). Despite this, greatest consensus appeared within low-risk scenarios (2 and 4) where for both IOP and visual function monitoring, participants reported opting for reduced frequency of monitoring (every 2–6 months) but over an increased duration (7–24 months). For high-risk scenarios (1 and 3), frequency and duration for visual function monitoring were consistent and similar to low-risk scenarios (2 and 4). However, in relation to IOP monitoring, participants reported increased frequency (every 1–7 days) but for a lower duration (1–6 months).

Explaining clinician glaucoma home monitoring decision-making

The justifications provided by the clinicians when reporting that Ms McEwen, scenario 4, would be suitable for home monitoring stated this was due to the nature of her stable disease and her low risk of progression. They felt that she could be safely monitored at home without high risk of missed progression, which could allow increased clinic capacity for individuals with advanced disease, ‘[f]reeing up capacity in the hospital eye service, allowing better use of resources and enabling better care of high-risk patients. Low-risk patients may prefer not having to come in the hospital’ (Consultant, 5–10 years of experience).

Among the participants who predicted that this patient would be unsuitable for home monitoring, the justification was that it may be a waste of resources due to the stable nature of her current condition. This was a contradiction with other participants who deemed her suitable due to the exact same reasoning, ‘stable for 5 years, waste of effort’ (Consultant, over 10 years of experience).

Table 4 summarises the justifications given by clinicians when deciding a patient described in the clinical scenarios would be unsuitable for home monitoring. When evaluating the rationale behind clinicians deeming the other scenarios unsuitable, the main concerns contradicted each other. However, many clinicians (n = 32) highlighted that they may be more hesitant to recommend home monitoring to high-risk individuals. They predicted that they would rather assess these patients in clinic to confidently determine their IOP and visual function. This was expressed to be important as it would avoid any discrepancies or impaired clinical judgement due to potentially ‘unreliable’ readings. They also felt that these advanced cases may require additional resources such as imaging, ‘[h]igh risk of further vision loss within lifetime – young, advanced VF defects bilaterally. Would prefer to see in clinic and discuss surgery at each visit’ [regarding scenario 1] (Optometrist, > 10 years of experience).

TABLE 4

Reasons for patients being deemed ‘unsuitable’ for glaucoma home monitoring

In addition to measuring clinical agreement within each clinical scenario regarding home monitoring of glaucoma patients, we also investigated agreement across scenarios to determine whether the disagreement in scenarios is related to the digital technology or to which patients should be monitored. There was a lack of consensus relating to which patients should be monitored using the tonometer, with 23 clinicians (47%) reporting that home monitoring of patients would be useful in at least three of the four clinical scenarios. This was also true for visual function, with 22 clinicians (45%) believing it to be useful for three out of the four scenarios.

Clinicians’ acceptability of home monitoring of glaucoma within NHS Care pathways

The fifth clinical scenario in the questionnaire described a clinical care model that combined home monitoring into the current hospital-based system. Regarding acceptability, no agreement was reached on this scenario, with just over half of clinicians (52%, n = 26) reporting that this model was acceptable and around one-third (37%, n = 18) reporting that it was unsuitable; 10% (n = 5) did not respond. Thematic content analysis of free-text responses in relation to this scenario resulted in the following seven themes: Resources, Patient Characteristics, Clinician Confidence in Home Monitoring, Perception of Risk, Wider Benefits, Accessibility, and Disease Suitability of Patient. Within each theme, anticipated advantages and disadvantages in relation to glaucoma home monitoring were identified, as shown in Table 5.

TABLE 5

Anticipated advantages and disadvantages of glaucoma home monitoring

Resources

From a resource perspective, many clinicians believe that implementing home monitoring could increase clinic capacity for review of high-risk patients and believe that this model could be better than the current alternative of no or limited monitoring. There was also a belief that access to timely care via home monitoring could prevent irreversible severe visual loss, promoting patient health and well-being. However, many doubted the cost-effectiveness of glaucoma home monitoring. Some felt that this model could reduce clinic capacity for patients by the time this service was staffed in relation to the human resource needed to train patients and review the data collected.

Patient characteristics

Clinicians had concerns about patients’ cognitive, physical and mental capacity for home monitoring. While concerns were broadly shared about physical and cognitive capacity, opinions were divided in relation to patient anxiety; while some felt home monitoring could alleviate anxiety in relation to glaucoma progression, some felt it had potential to increase this. The majority reported concerns that home monitoring could lead to reduced patient compliance with regular testing and concerns about how this would be monitored. For the few, compliance could increase as regular feedback on disease status was anticipated to be motivational for patients.

Clinician confidence in home monitoring

We found that while there was some optimism about more frequent monitoring, home monitoring was largely anticipated to cause a decrease in clinician confidence in the quality of care delivered to patients. This was related to concerns about the reliability, standardisation, and compatibility of the devices, with and against hospital equipment, and concerns about relying on a narrower range of measures, as opposed to additional measures obtained in clinic (e.g. optical coherence tomography). There was some optimism, however, that more frequent monitoring of IOP and visual function, as would be possible with home monitoring, could detect progression sooner.

Perception of risk

While several clinicians reported more timely monitoring being a positive, there was a strong concern about the risks posed by the home monitoring of glaucoma. Risks raised reflected patient harms (e.g. missing glaucoma progression, resulting in loss of vision) and data and technology risks resulting from events such as failing equipment.

Wider benefits

A couple of wider benefits to home monitoring were raised. For example, the reduced travel arising from monitoring at home offers an environmental advantage. For some, home monitoring was expected to be more convenient for patients. Some also raised the advantage of being able to monitor patients who currently are not able to be monitored in clinic, such as those who are bedbound and/or residing in care homes.

Accessibility

Several disadvantages which could be potential barriers to accessing home monitoring were reported, namely language barriers and technology/internet access. These were expected to result in low uptake of home monitoring among some population groups.

Disease suitability of patient

Similar to the variation in responses to the clinical scenarios (1–4) there was little consensus in responses made in relation to a patient’s medical suitability for home monitoring. Most agreed that those at high risk of progression were unsuitable for home monitoring. Certain disease classifications (OHT and NTG) were frequently considered good candidates. The use of these technologies for glaucoma screening and phasing purposes was often frequently suggested as having potential in addition to or instead of regular monitoring.

Chapter summary

This chapter has demonstrated that there is agreement among the expert glaucoma clinicians surveyed that there is a place for home monitoring of glaucoma patients using digital technology. However, based on the scenarios used in this study, there is limited agreement among clinicians about which glaucoma patients are most suitable for home monitoring using digital technologies to measure IOP and visual function. Agreement (> 60%) was achieved for scenario 4 (a stable, low-risk patient), with clinicians supporting monitoring of IOP and visual function at home. Clinicians reported that they were generally not supportive of the home monitoring of high-risk patients, due to the fear of missing disease progression or unreliable readings. However, they were generally supportive of home monitoring having a role within low-risk scenarios, such as NTG monitoring and 24-hour phasing. Clinicians anticipated that the integration of home monitoring into the current healthcare system could act as an adjunct to increase hospital capacity for glaucoma patients who require face-to-face assessment.

This survey has highlighted a range of issues and challenges related to the home monitoring of glaucoma patients using digital technologies. A central theme is clinicians’ lack of trust in home monitoring technologies, related to concerns about the reliability, accuracy and usefulness of these technologies. Clinicians expressed concerns about patient safety, decreased rather than increased glaucoma progression detection and concerns about how resource efficient (time and financial) this approach could be in comparison to current provision. These areas are explored in more detail in Chapter 3.

This work was produced by Stewart et al. under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This is an Open Access publication distributed under the terms of the Creative Commons Attribution CC BY 4.0 licence, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. See: https://creativecommons.org/licenses/by/4.0/. For attribution the title, original author(s), the publication source – NIHR Journals Library, and the DOI of the publication must be cited.

Bookshelf ID: NBK606834

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