Establishing Expert, Multi-Disciplinary, Peer-Reviewed Consensus to Lead a Paradigm Shift in Optimal Blood Glucose Management

Establishing Expert, Multi-Disciplinary, Peer-Reviewed Consensus to Lead a Paradigm Shift in... Diabetes Ther (2019) 10:901–916 https://doi.org/10.1007/s13300-019-0598-2 ORIGINAL RESEARCH Establishing Expert, Multi-Disciplinary, Peer- Reviewed Consensus to Lead a Paradigm Shift in Optimal Blood Glucose Management . . . Douglas A. Robertson Richard A. Chudleigh Simon D. Gwynn . . . . Carol Jairam Kaushal Kansagra Naresh Kanumilli Adam Lester-George Charlotte McMurray Timothy C. Warren Received: January 24, 2019 / Published online: March 19, 2019 The Author(s) 2019 commissioners considered BGM in terms of ABSTRACT access, guidance, resources, data integration, patient education, and patient choice. Introduction: The National Health Service Methods: The group generated a series of (NHS) in the UK appears unclear on how blood questions on BGM into a 38-statement ques- glucose monitoring (BGM) should be used to tionnaire using Delphi methodology. This was support diabetes patient care and empower- circulated to clinicians involved in diabetes ment, and local interpretation of NICE guid- management across the UK, receiving 222 ance on the availability of devices varies widely. responses. An expert group of clinicians and Results: From the questionnaire, 35 of the 38 statement responses showed [ 66% consensus, Enhanced Digital Features To view enhanced digital features for this article go to https://doi.org/10.6084/ with 26 of these achieving [ 90% agreement. m9.figshare.7819586. Conclusion: The expert group reviewed the responses and made recommendations based on D. A. Robertson (&) the clear professional consensus demonstrated. Leighton Hospital, Crewe, UK These included the need to use new technology e-mail: doug.robertson@nhs.net and data integration and that wider factors, R. A. Chudleigh including patient choice rather than cost alone, Singleton Hospital, Swansea, UK should inform formulary inclusion of BGM equipment. S. D. Gwynn  T. C. Warren Triducive Ltd., Tunbridge Wells, UK Funding: LifeScan U.K. Ltd. C. Jairam Keywords: BGM; Blood glucose; Glycemic Imperial College, London, UK control; Consensus; Monitoring; Type 1 K. Kansagra diabetes; Type 2 diabetes Shotfield Medical Practice, Wallington, UK N. Kanumilli Northenden Group Practice, Manchester, UK INTRODUCTION A. Lester-George Diabetes is a widely prevalent long-term con- LeLan Ltd, Bristol, UK dition in which raised blood glucose levels over C. McMurray time contribute to complications that are costly Sheffield Clinical Commissioning Group, Sheffield, in terms of healthcare use and impact adversely UK 902 Diabetes Ther (2019) 10:901–916 on quality of life. Blood glucose monitoring METHODS (BGM) has an important part to play in the management of blood glucose in diabetes and This article does not contain any studies with the reduction of risk of serious secondary com- human participants or animals performed by plications [1]. The first BGM meter was intro- any of the authors. duced in 1970 [1], and available technology has The group used the Delphi [6] methodology evolved markedly since then. In today’s tech- to validate the views of a large number of peers nology-rich environment, self-monitoring of regarding BGM in the current UK National blood glucose is an integral part of effective Health Service (NHS) setting, with the goal of diabetes management [2], allowing patients to better understanding their views regarding monitor their glycemic status and adjust their changing demographics and BGM technology. therapy accordingly. The recommendations derived from the Modern healthcare requires that long-term responses seek to support HCPs in assessing new conditions are managed in a shared and col- technologies available to them and provide laborative way between the patient and all decision-support for choice of technology. As stakeholders involved in their care, rather than such, these consensus views and recommenda- solely by the patient or healthcare profession- tions which the group felt were justifiable from als (HCPs). Despite clear demonstrations of the the responses are offered in order to provide a benefits of BGM meters that provide feedback reference point for the use of BGM for both to patients [2], and diabetes being almost uni- commissioners and providers. In addition, the versally managed in the UK by NHS profes- consensus process aimed to identify regional sionals, there is an apparent lack of clarity variation in the responses to statements and is within the NHS regarding emerging BGM intended to inform the paradigm shift required technologies and their potential to positively to adopt new technologies for BGM. impact service delivery and increase resource A group of clinicians and payers involved in efficiency while supporting patient empower- diabetes care met to review the current adop- ment. This was demonstrated in a survey of tion of BGM systems in the UK and determine a over 1000 BGM users carried out by Diabetes framework for consensus. Seven key topics were UK [3], with the responses suggesting that initially identified, and consensus statements NICE (National Institute for Health and Care developed for each (Table 1). These statements Excellence) guidance is not always imple- were collated into a questionnaire, which was mented as recommended for type 1 [4]and circulated widely over a 3-month period to type 2 [5]diabetes. clinicians involved in diabetes management by This consensus steering group (all mem- in-person cascade and by e-mail from group bers are co-authors to this paper) has sought members and with the help of LifeScan, Inc. the real-life perspectives of NHS staff involved (London, UK) representatives. Responses were in diabetes care to gain an understanding of collated and analyzed in confidence by Tridu- their attitudes to BGM technology and its cive Ltd (St Albans, UK). Respondents were value for people with diabetes who require required to use a 4-point Likert scale to rate intensive BG monitoring. This was felt nec- their agreement with each statement. Responses essary because the speed of introduction of were: ‘strongly disagree’; ‘tend to disagree’; technology was perceived to move more ‘tend to agree’; and ‘strongly agree.’ The ques- quickly even than centralized expert guid- tionnaire also asked respondents for their ance. In order to fulfil the requirements for locality, their speciality, and the department in fully collaborative shared care, it is important which they work. While personal details were that optimum technology is utilized and a not used for reporting results, clinical back- ‘big data’ approach is adopted, in order to ground and locality were used to assess poten- increase resource efficiency. tial differences in responses between professions and across the UK. Diabetes Ther (2019) 10:901–916 903 Table 1 Consensus topics and statements Consensus statement Consensus topic Statement number 1 Evidence and outcomes The willingness of the patient to engage with a particular BGM device should be the driving factor in choice 2 Evidence should determine choices relating to BGM 3 There is a lack of evidence that more expensive BGM meters improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more important than evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence alone in choosing an appropriate BGM system in select patient groups 6 Evidence for blood glucose monitoring should include patient reported outcome measures 7 Evidence supporting the real-world usability of a device should be provided by the manufacturers 8 Access to blood glucose Consistency and reproducibility of data is important for decision-support monitoring data 9 BGM data should always support treatment decisions for people with type 1 diabetes or patients using insulin 10 It is important that the user can access real-time reports of their personal BGM data, trends, and patterns 11 Patients should be able to readily share their data with partners and medical professionals in real time 12 Influencing guidance Decision-makers should consider real-world evidence when making recommendations 13 Guidance should include clear, evidence-based decision support that is accessible to all HCPs 14 Guidance should support the value of digital solutions (e.g., real-time data sharing, remote consultations) in formulary selection 15 It is important that patients have access to real-time feedback/reports of their BGM trends and patterns to enable them to act 904 Diabetes Ther (2019) 10:901–916 Table 1 continued Consensus statement Consensus topic Statement number 16 Use of resources BGM manufacturers should provide data to indicate that their products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is misinterpreted and confusing to HCPs in terms of managing patients with type 1 diabetes or patients using insulin 18 Flash glucose monitoring has the potential to improve the use of NHS resources by supporting SMBG 19 Effective BGM (understanding and action) reduces the risks of hypoglycemia and ketoacidosis in patients with type 1 diabetes 20 The NHS should consider innovation in BGM for patients with type 1 diabetes or patients using insulin as an investment, rather than a cost 21 Patient education Decision-making through effective BGM (understanding and action) is a necessary component of patient education 22 HCPs and carers need a common understanding of how to interpret and act upon BGM data, trends and patterns 23 It is important that patients learn how to analyze and act upon trends and patterns in their SMBG/BGM data 24 Access to and action based on BGM data will improve patient motivation to adhere to their optimal SMBG regimen 25 Patient education can be effectively delivered at home through virtual consultations and virtual data sharing using digital applications 26 Decision-making based on frequent and effective SMBG (BGM) is a necessary component of supporting effective patient education 27 Resources could be saved by replacing face-to-face structured education with education delivered virtually using new digital/BGM solutions 28 Effective BGM (with appropriate tools/features) provide a means to offer positive reinforcement to better support patient decisions Diabetes Ther (2019) 10:901–916 905 Table 1 continued Consensus statement Consensus topic Statement number 29 Data integration Patients’ BGM data should be easily accessible by every HCP involved in their care (to whom they have consented to provide access) 30 NHS data systems are not capable of effectively sharing data 31 Data should be accessible and integrated irrespective of the device that the patient uses 32 A standardized approach to cloud-held data and its formatting will improve its accessibility and utility for patients and HCPs 33 Patient choice BGM systems should not present barriers to regular use by patients 34 Formulary availability of BGM systems should not be driven by acquisition cost alone 35 The NHS should allow patient co-payment in order to allow more individualized patient care 36 Choice of BGM system should support the achievement of the patient’s own goals 37 Formulary availability of BGM systems should only be driven by patient choice 38 The willingness of the patient to engage with a particular BGM device should be the driving factor in choice BGM Blood glucose monitoring, HCP healthcare professional, NHS UK National Health Service, NICE National Institute for Health and Care Excellence, QALY quality-adjusted life-year, SMBG self-monitoring of blood glucose 906 Diabetes Ther (2019) 10:901–916 Completed questionnaires were then col- remain unknown and 19 had other roles. lated, and the individual scores for each state- Comparison between the responses of dia- ment analyzed in order to produce a full betologists, DSNs and the group overall is arithmetic agreement score for each statement. shown in Fig. 3. The responses were then sub-grouped by local- With the exception of statements 3, 4, 5, 16, ity and specialty to identify variances in the 17, 27, 30, and 37, the views of DSNs were well respondent’s agreement scores by either geog- aligned with those of the wider group. The raphy or role. variation in agreement scores for these state- The steering group had predefined the ments according to role is shown in Table 7. threshold of agreement for consensus at C 66%. Consensus was defined as ‘high’ at C 66% and DISCUSSION ‘very high’ at C 90%. Due to the high levels of agreement with all In this paper we describe the consensus views of but three of the statements, demonstrating very a large group of clinicians working the UK NHS, strong consensus views, the group elected to a government-funded, cost-limited healthcare avoid a further round of questionnaires to system that is substantially free at the point of generate a larger number of responses, and use. As such, the recommendations and views instead chose to work with the responses to the presented here may not reflect the views of original statements. HCPs in other healthcare systems. For patients with a need to optimize their RESULTS glycemic control, many factors may influence their choice of BGM system. Understanding the Completed questionnaires were returned by 222 value of a system to a patient may be a more respondents. The questionnaires were analyzed important measure than simply looking at the to score the total level of agreement with each acquisition cost of that device. In light of this, of the 38 statements. Of the 38 statements, 35 sharing the acquisition cost with the patient (92%) achieved an agreement score exceeding may be a valid option, as patients have the 66% threshold, and 26 of these (68%) demonstrated that when a device is recognized exceeded 90% agreement (Table 2, Fig. 1). as offering important advantages, they may be Only three of the statements achieved an willing to contribute to the cost [7]. agreement score of \ 66% or [ 33% and thus Effective BGM is recognized by 99.1% of were defined as not achieving consensus respondents as having the potential to reduce (Table 3). hypoglycemia and ketoacidosis in patients with Respondents were analyzed by region. The type 1 diabetes. Effective BGM may be regarded number of respondents from each region is as achieving tight glycemic control (according shown in Table 4. The sample was dominated to the type of diabetes) in line with personalized by respondents from England (n = 136) while goals. only four respondents were from Wales. Eigh- Respondents strongly agree with the asser- teen respondents did not indicate their region. tion that flash glucose monitoring has the While the majority of statements were scored potential to improve the use of NHS resources similarly, irrespective of the respondent’s region (88.9% agreement) and should be considered as (Fig. 2), nine statements showed larger regional an investment rather than a cost (96.3% variation in score (Table 5). agreement). Responses were also analyzed according to the respondent’s role (Table 6). Influencing Guidance While the largest single respondent groups by role were diabetologists and diabetes spe- Unsurprisingly, respondents strongly agree with cialist nurses (DSNs), 39 respondents did not statements 12 and 13 concerning the need for share their role on the questionnaire and thus real-world evidence when making Diabetes Ther (2019) 10:901–916 907 Table 2 Consensus statements and agreement scores Consensus Topic Statement Agreement statement score (%) number 1 Evidence and The willingness of the patient to engage with a particular BGM 93.7 outcomes device should be the driving factor in choice 2 Evidence should determine choices relating to blood glucose 92.7 monitoring 3 There is a lack of evidence that more expensive BGM meters 78.5 improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more important than evidence alone in 71.8 choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence alone in 34.9 choosing an appropriate BGM system in select patient groups 6 Evidence for blood glucose monitoring should include patient 97.2 reported outcome measures 7 Evidence supporting the real-world usability of a device should be 95.0 provided by the manufacturers 8 Access to blood Consistency and reproducibility of data is important for decision 99.1 glucose monitoring support data 9 BGM data should always support treatment decisions for people 98.2 with type 1 diabetes or patients using insulin 10 It is important that the user can access real time reports of their 94.5 personal BGM data, trends and patterns 11 Patients should be able to readily share their data with partners 96.8 and medical professionals in real time 12 Influencing guidance Decision-makers should consider real world evidence when 98.6 making recommendations 13 Guidance should include clear, evidence-based decision support 97.7 that is accessible to all HCPs 14 Guidance should support the value of digital solutions (e.g. real 98.2 time data sharing, remote consultations) in formulary selection 15 It is important that patients have access to real time feedback/ 96.8 reports of their BGM trends and patterns to enable them to take action 908 Diabetes Ther (2019) 10:901–916 Table 2 continued Consensus Topic Statement Agreement statement score (%) number 16 Use of resources BGM manufacturers should provide data to indicate that their 89.9 products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is misinterpreted and confusing to 60.5 HCPS in terms of managing patients with type 1 diabetes or patients using insulin 18 Flash glucose monitoring has the potential to improve the use of 88.9 NHS resources by supporting SMBG 19 Effective BGM (understanding and action) reduces the risks of 99.1 hypoglycemia and ketoacidosis in patients with type 1 diabetes 20 The NHS should consider innovation in BGM for patients with 96.3 type 1 diabetes or patients using insulin as an investment, rather than a cost 21 Patient education Decision making through effective BGM (understanding and 99.5 action) is a necessary component of patient education 22 HCPs and carers need a common understanding of how to 100.0 interpret and act upon BGM data, trends and patterns 23 It is important that patients learn how to analyze and act upon 98.2 trends and patterns in their SMBG/BGM data 24 Access to and action based on BGM data will improve patient 98.1 motivation to adhere to their optimal SMBG regimen 25 Patient education can be effectively delivered at home through 77.5 virtual consultations and virtual data sharing using digital applications 26 Decision making based on frequent and effective SMBG (BGM) 95.9 is a necessary component of supporting effective patient education 27 Resources could be saved by replacing face-to-face structured 66.8 education with education delivered virtually using new digital/ BGM solutions 28 Effective BGMs (with appropriate tools/features) provide a 97.2 means to offer positive reinforcement to better support patient decisions Diabetes Ther (2019) 10:901–916 909 Table 2 continued Consensus Topic Statement Agreement statement score (%) number 29 Data integration Patients’ BGM data should be easily accessible by every HCP 98.6 involved in their care (to whom they have consented to provide access) 30 NHS data systems are not capable of sharing data effectively 81.0 31 Data should be accessible and integrated irrespective of the device 97.2 that the patient uses 32 A standardized approach to cloud-held data and its formatting 98.1 will improve its accessibility and utility for patients and HCPs 33 Patient choice BGM systems should not present barriers to regular use by 100.0 patients 34 Formulary availability of BGM systems should not be driven by 92.2 acquisition cost alone 35 The NHS should allow patient co-payment in order to allow 77.0 more individualised patient care 36 Choice of BGM system should support the achievement of the 98.2 patient’s own goals 37 Formulary availability of BGM systems should only be driven by 44.7 patient choice 38 The willingness of the patient to engage with a particular BGM 84.3 device should be the driving factor in choice Total Consensus Agreement Scores 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 0123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 Fig. 1 Plot of total consensus agreement scores 910 Diabetes Ther (2019) 10:901–916 Table 3 Statements with agreement scores of between 33 and 66% Consensus Topic Statement Agreement statement score (%) number 5 Evidence and HCP preference is more important than evidence alone in choosing an 34.9 outcomes appropriate BGM system in select patient groups 17 Use of Guidance around SMBG is misinterpreted and confusing to HCPS in 60.5 resources terms of managing patients with type 1 diabetes or patients using insulin 37 Patient Formulary availability of BGM systems should only be driven by patient 44.7 choice choice endorsing the need for digital solutions, which Table 4 Respondents by region may support the objective of increasing per- Region Number of respondents sonal management of long-term conditions. In addition, 96.8% of respondents agree that England 136 patients should have access to real-time data Scotland 26 enabling them to act. In total, 98.2% of delegates support the view Wales 4 that guidance should support the value of dig- Northern Ireland 18 ital solutions when it comes to formulary London 13 inclusion. However, BGM formulary decisions are still firmly focused on devices and the Unknown 25 acquisition cost of the device test strips, despite Total 222 the NHS’s intention to move to solutions that are orientated around digital, big data and evi- dence that demonstrates an impact on health recommendations and the need for clarity in outcomes. the evidence base from guidance used in deci- sion-support. There is strong agreement (98.2%) Consensus Agreement Scores by Region 100.0% 90.0% 80.0% All Responses 70.0% England 60.0% Scotland 50.0% 40.0% Wales 30.0% N. Ireland 20.0% London 10.0% 0.0% 0123456789 1011121314151617181920212223242526272829303132333435363738 Fig. 2 Consensus agreement scores by region Diabetes Ther (2019) 10:901–916 911 Table 5 Statements with largest regional variation in agreement scores Consensus Topic Statement Agreement scores (%) statement England Scotland Wales Northern London number (%) (%) (%) Ireland (%) (%) 2 Evidence Evidence should determine choices 94.0 100.0 50.0 94.4 76.9 and relating to BGM outcomes 3 There is a lack of evidence that 76.4 80.8 100.0 94.1 61.5 more expensive BGM meters improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more 78.5 64.0 100.0 50.0 61.5 important than evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important 41.4 23.1 0.0 27.8 38.5 than evidence alone in choosing an appropriate BGM system in select patient groups 16 Use of BGM manufacturers should provide 88.9 92.3 75.0 100.0 84.6 resources data to indicate that their products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is 64.5 61.5 25.0 42.9 46.2 misinterpreted and confusing to HCPS in terms of managing patients with type 1 diabetes or patients using insulin 25 Patient Patient education can be effectively 74.8 73.1 100 76.5 76.9 education delivered at home through virtual consultations and virtual data sharing using digital applications 35 Patient The NHS should allow patient co- 82.0 65.4 50.0 72.2 75.0 choice payment in order to allow more individualised patient care 38 The willingness of the patient to 87.9 84.6 100.0 70.6 38.5 engage with a particular BGM device should be the driving factor in choice 912 Diabetes Ther (2019) 10:901–916 Table 6 Respondents by role it has been reported that 32.3% of measured hypoglycemic episodes are preceded by an Role N observed pattern of low blood glucose [10]. Data Diabetologist 53 should always support treatment decisions for people with type 1 diabetes or patients using Diabetes specialist nurse 45 insulin (96.8%). Pharmacist 22 Data offer patients the insight to manage their blood glucose with confidence. Respon- Nurse 20 dents strongly agree that decisions made by GP 13 patients should always be supported by data (98.2%). Access to data promotes engagement Obstetrics 8 with trends and patterns within the data to Dietician 3 inform the patient in a way that complements the role of the HCP. Other 19 Unknown 39 Patient Education Total 222 There is evidence to show that good BGM results in better outcomes and that people Access to BGM Data should be supported and educated in the interpretation of data to achieve these better All statements relating to BGM data are very outcomes. In our survey 100% of respondents strongly supported by respondents. Having support the importance of a common under- consistency and reproducibility of data is con- standing of how to interpret and act upon BGM sidered to be of paramount importance (99.1%), data, trends, and patterns. Given the nature of and supporting type 1 patient’s treatment diabetes, it is vital that carers are actively decisions in real-time is strongly supported involved with patients, and access to real-time (98.2%). data is an important consideration. Diabetes The need for patients to have real-time impacts the whole household [11]. reports of their personal BGM data is supported Among respondents, 99.5% agree that effec- by 94.5% of respondents. It has been shown tive BGM is a necessary component of patient that automated pattern algorithms can assist in education; in addition, the importance of access the avoidance of hypoglycemic episodes [8, 9]. Total Consensus Agreement Scores by Role 100.0% 90.0% 80.0% 70.0% 60.0% All Responses 50.0% Diabetologists 40.0% DSNs 30.0% 20.0% 10.0% 0.0% 0123456789 1011121314151617181920212223242526272829303132333435363738 Fig. 3 Consensus agreement scores by role. DSN Diabetes specialist nurse Diabetes Ther (2019) 10:901–916 913 Table 7 Statements with largest variation in agreement scores by role Consensus Topic Statement Agreement scores (%) statement Total DSNs Diabetologists number (%) (%) (%) 3 Evidence There is a lack of evidence that more expensive BGM 78.5 71.4 78.0 and meters improve outcomes in type 1 diabetes and outcomes people with diabetes using insulin 4 Patient preference may be more important than 71.8 77.8 60.4 evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence 34.9 17.8 30.8 alone in choosing an appropriate BGM system in select patient groups 17 Use of Guidance around SMBG is misinterpreted and 60.5 57.1 51.0 resources confusing to HCPS in terms of managing patients with type 1 diabetes or patients using insulin 27 Patient Resources could be saved by replacing face-to-face 66.8 62.8 59.6 education structured education with education delivered virtually using new digital/BGM solutions 30 Data NHS data systems are not capable of sharing data 81.0 85.4 81.1 integration effectively 37 Patient Formulary availability of BGM systems should only be 44.7 41.5 49 choice driven by patient choice DSN Diabetes specialist nurse to BGM data and of understanding trends and positive reinforcement in support of patient patterns is strongly supported (statements 23 decisions, reflecting recent published data and 24). Access to feedback on their progress [2, 12]. helps patients to take action to improve their diabetes control or continue with previous Data Integration positive actions [2]. There is strong agreement that virtual data and applications can support Respondents strongly support that the notion education at home. Remote support in the that data systems should be integrated and patient’s home and work environments is inter-operable across the NHS (97.2% agree- important so that patients are not constrained ment). Eventually, integration of data should by the need to attend a clinic. involve a standardized approach in order to Statement 27 achieved consensus (66.8% improve access and utility (statements 31 and agreement) despite the inference that resources 32). Data are of no use unless it can be effec- could be saved by replacing face-to-face educa- tively used and applied. tion. In reality, respondents may better support Members of the consensus group agreed that the assertion that the two should complement high-quality data are essential for constructive one another. This would offer a synergistic consultations; therefore, access to data will benefit. There is 97.2% agreement among improve resource utilization and avoid wasted respondents that BGM offers a means to offer clinic sessions. There was 98.6% agreement 914 Diabetes Ther (2019) 10:901–916 among respondents that patients’ BGM data indicators was associated with improvements in should be accessible by every HCP involved in glycated hemoglobin levels compared to sub- their care. This result is supported in the litera- jects using a wide selection of marketed BGM ture, with published data showing improve- systems without color support [14]. Despite ment in glycemic control by patients using this, respondents support the assertion (78.5%) integrated BGM data [8, 12]. Cloud-held data that there is a lack of evidence that more may lead to better data-utility among patients expensive BGM systems improve outcomes, and HCPs (98.1%) as long as it is easily acces- suggesting that respondents may not be fully sible as per regulatory guidelines. It may also aware of recent innovations and published data. facilitate remote consultations and can alleviate Data are available providing direct comparison the problem of forgotten logbooks or devices in between solutions that help the patient and face-to-face consultations. HCP with insights and interpretation of the Accessible cloud-held data can also be number versus traditional BGM [14]. shared/socialized with caregivers (e.g., elderly While the preference of the HCP is not patients) and loved ones (e.g., parents of chil- regarded by the respondents as being more dren). Studies have demonstrated improve- important than evidence (34.9%), patient pref- ments in outcomes when data is used in this erence is strongly supported (71.8%) as more way [8]. being important than evidence alone in choos- ing the right BGM system for the patient. Respondents strongly agree that evidence Use of Resources should include patient-reported outcome mea- sures (PROMS) (97.2%), such as real-world Respondents strongly agree that manufacturers usability (93.7%). should provide quality-adjusted life-year data to support their products (89.9%). There is a need Patient Choice for clear and consistent guidance regarding BGM, as evidenced by the lack of clarity from respondents regarding statement 17. A majority of respondents concurred that for- Almost all respondents (99.1%) agree that mulary availability should not be driven by a effective BGM will reduce the risks of hypo- single factor alone, with general agreement that glycemia and ketoacidosis in patients with type neither patient choice (55.3%) nor acquisition 1 diabetes. New technology has the potential to cost (92.2%) is sufficient to effectively make improve the use of NHS resources and should be formulary choices. Interestingly, respondents considered as an investment rather than a cost are accepting of patient co-payment (77%) as a (96.3% agreement). New technologies that means of accessing novel technology and sup- facilitate effective glycemic control are strongly porting individualized patient choice. This is a supported by respondents (88.9% agreement to paradigm shift and may reflect changing pro- statement 18, which is specific to flash glucose fessional attitudes. However, many patients monitoring and 96.3% agreement to statement have traditionally self-funded their BGM regi- 20). Solutions with automated pattern algo- men in the past, and the 2017 Diabetes UK rithm integration can improve HCP efficiency Survey recently revealed that BGM is less avail- and accuracy [13]. able than patients’ requirements [3]. There are 98.2% of respondents who agree that the choice of BGM system should support Evidence and Outcomes the achievement of the patients’ own goals and 84.3% who agree that the willingness of the Respondents strongly indicate (92.7%) that patient to engage with a particular BGM device evidence is important in improving patient care should be the driving factor in choice of system. and that it should inform choices relating to Recent data suggest that BGM supported by a BGM. Recent evidence [2] shows that switching web application and OneTouch Verio (OTV; patients to BGM systems featuring color range Diabetes Ther (2019) 10:901–916 915 LifeScan Inc., Milpitas, CA, USA) meter • Real-time BGM data should be made avail- able to patients and provide positive improved blood glucose control [12]. In addi- tion, recent studies indicate that connected reinforcement. • Guidance should be inclusive of evidence, BGM solutions that provide access to cloud- held data allow patients to feel more secure in patient preference, and outcomes data. the knowledge that they can access their dia- • Wider factors, such as patient choice, should betes information at any time [15]. inform guidance rather than cost alone. Overall, the strong support from a large • New technology for BGM should be regarded respondent group underlines the need to ensure as an investment rather than a cost. that patients have access to appropriate BGM • Structured education should be comple- mented by access to real-time feedback data. systems in line with the needs and expectations of their health care professionals. New BGM • The choice of BGM system should support the achievement of the patients’ own goals. technologies should be regarded as an invest- ment rather than a cost, as long-term cost-ef- • Shared ownership of the responsibility for self-care is critical. fectiveness may be achieved due to a reduction in negative outcomes and admissions and in greater patient satisfaction. This opportunity reflects the wider shift towards value-based ACKNOWLEDGEMENTS healthcare in the NHS. Limitations of Study Funding. LifeScan U.K. Ltd provided finan- cial support for the consensus process including article processing charges and steering group The cascade circulation of the questionnaire meetings but had no editorial control over the from the group to their network of colleagues content of the publication or its conclusions. and the willingness of the 222 clinical profes- All authors had full access to all of the data in sionals to respond spontaneously may have this study and take complete responsibility for introduced bias; nevertheless, the statements the integrity of the data and accuracy of the produced a high level of clinical consensus in data analysis. areas of uncertainty around BGM. The profes- sionals who responded covered a wide range of Medical Writing. Medical writing support disciplines and geographical spread within the and project coordination was provided by Tri- UK, but despite this there was a great deal of ducive Ltd., also funded by LifeScan UK Ltd. agreement in their responses. Authorship. All named authors meet the International Committee of Medical Journal CONCLUSIONS Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of The conclusions drawn by the consensus group the work as a whole, and have given their after consideration of the questionnaire approval for this version to be published. responses are as follows: • Informed patient choice should be regarded Disclosures. RichardA. Chudleigh:Received as the prime factor in the effective use of a speaker honorarium from Abbott. Naresh Kanu- BGM system. milli: Received honoraria from Pharmaceutical • Patient co-payment should be supported companies for advisory boards and talks (NN, where appropriate as this will allow more Napp, Takeda, Sanofi, AZ, Abbott, Ascensia). individualized patient care and empower Charlotte McMurray: Received honoraria from self-management. LifeScan. Douglas A. Robertson, Simon D. Gwynn, • Data integration is urgently required for Carol Jairam, Kaushal Kansagra, Adam Lester- BGM system access. 916 Diabetes Ther (2019) 10:901–916 NICE guideline [NG28]. 2005. https://www.nice. George, and Timothy C. Warren have nothing to org.uk/guidance/NG28. Accessed Feb 2019. disclose. 6. Dalkey N, Helmer O. An experimental application Compliance with Ethics Standards. This of the Delphi method to the use of experts. Manag article does not contain any studies with Sci. 1963;9:458–67. human participants or animals performed by 7. Diabetes UK. Diabetes UK consensus guideline for any of the authors. However, we thank the flash glucose monitoring. 2017. https://www. colleagues who responded and gave up their diabetes.org.uk/resources-s3/2017-09/1190_Flash% valuable time to complete and return their 20glucose%20monitoring%20guideline_SB_V9% 5B4%5D.pdf. Accessed Feb 2019. questionnaires. 8. Grady M, Katz LB, Cameron H, Levy BL. Diabetes Data Availability. The datasets analyzed app-related text messages from health care profes- during this study are available from the authors sionals in conjunction with a new wireless glucose on reasonable request. meter with a colour range indicator improves gly- caemic control in patients with type 1 and type 2 diabetes: randomized controlled trial. JMIR Dia- Open Access. This article is distributed betes. 2017;2(2):e19. under the terms of the Creative Commons Attribution-NonCommercial 4.0 International 9. Grady M, Campbell D, MacLeod K, Srinivasan A. Evaluation of a blood glucose monitoring system License (http://creativecommons.org/licenses/ with automatic high- and low-pattern recognition by-nc/4.0/), which permits any noncommer- software in insulin-using patients: pattern detec- cial use, distribution, and reproduction in any tion and patient-reported insights. J Diabetes Sci medium, provided you give appropriate credit Technol. 2013;7(4):970–8. to the original author(s) and the source, provide 10. SB Communications Group. Recognising and a link to the Creative Commons license, and addressing patterns of recurrent ‘‘highs’’ and ‘‘lows’’ indicate if changes were made. in people with insulin-treated diabetes: why is it important and how to go about it? Suppl J Diabetes Nurs. 2013;17:9. 11. Diabetes.co.uk. Emotional impact of diabetes on fam- REFERENCES ily and friends. https://www.diabetes.co.uk/emotio nal-impact-on-families.html. Accessed Jan 2019. 1. Clarke SF, Foster JR. A history of blood glucose 12. Katz LB, Dirani RG, Li G, Randoll RA, Mahoney JJ. meters and their role in self-monitoring of diabetes Automated glycaemic pattern analysis can improve mellitus. Br J Biomed Sci. 2012;69(2):83–93. health care professional efficiency and accuracy. J Diabetes Sci Technol. 2013;7(1):163. 2. Grady M, Katz LB, Cameron H, Levy BL. A compre- hensive evaluation of a novel color range indicator in 13. Katz LB, Stewart LS, Levy BL. Benefits to health care multiple blood glucose meters demonstrates professionals and patients with diabetes of a novel improved glucose range interpretation and aware- blood glucose meter that provides pattern recogni- ness in subjects with type 1 and type 2 diabetes. tion and real-time automatic messaging compared J Diabetes Sci Technol. 2016;10(6):1324–32. to conventional paper logbooks. Int Diabetes Nurs. 2015;12(1):27–33. 3. Testing Times: restrictions accessing test strips and meters for people with diabetes. Diabetes UK 2017. 14. Grady M, Katz LB, Levy BL. Use of blood glucose https://www.diabetes.org.uk/resources-s3/2017-08/ meters featuring color range indicators improves 1092_Testing%20times.pdf. Accessed Feb 2019. glycemic control in patients with diabetes in com- parison to blood glucose meters without color 4. National Institute for Health and Care Excellence (ACCENTS Study). J Diabetes Sci Technol. (NICE). Type 1 diabetes in adults: diagnosis and 2018;12(6):1211–9. management. NICE guideline [NG17]. 2015. https://www.nice.org.uk/guidance/ng17/chapter/1- 15. Grady M, Cameron H, Levy BL, Katz LB. Remote Recommendations#blood-glucose-management-2. health consultations supported by a diabetes man- Accessed Feb 2019. agement web application with a new glucose meter demonstrates improved glycaemic control. J Dia- 5. National Institute for Health and Care Excellence betes Sci Technol. 2016;10(3):737–43. (NICE). Type 2 diabetes in adults: management. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Diabetes Therapy Springer Journals

Establishing Expert, Multi-Disciplinary, Peer-Reviewed Consensus to Lead a Paradigm Shift in Optimal Blood Glucose Management

Loading next page...
 
/lp/springer-journals/establishing-expert-multi-disciplinary-peer-reviewed-consensus-to-lead-Q8ft5ero7g
Publisher
Springer Journals
Copyright
Copyright © 2019 by The Author(s)
Subject
Medicine & Public Health; Internal Medicine; Diabetes; Cardiology; Endocrinology
ISSN
1869-6953
eISSN
1869-6961
DOI
10.1007/s13300-019-0598-2
Publisher site
See Article on Publisher Site

Abstract

Diabetes Ther (2019) 10:901–916 https://doi.org/10.1007/s13300-019-0598-2 ORIGINAL RESEARCH Establishing Expert, Multi-Disciplinary, Peer- Reviewed Consensus to Lead a Paradigm Shift in Optimal Blood Glucose Management . . . Douglas A. Robertson Richard A. Chudleigh Simon D. Gwynn . . . . Carol Jairam Kaushal Kansagra Naresh Kanumilli Adam Lester-George Charlotte McMurray Timothy C. Warren Received: January 24, 2019 / Published online: March 19, 2019 The Author(s) 2019 commissioners considered BGM in terms of ABSTRACT access, guidance, resources, data integration, patient education, and patient choice. Introduction: The National Health Service Methods: The group generated a series of (NHS) in the UK appears unclear on how blood questions on BGM into a 38-statement ques- glucose monitoring (BGM) should be used to tionnaire using Delphi methodology. This was support diabetes patient care and empower- circulated to clinicians involved in diabetes ment, and local interpretation of NICE guid- management across the UK, receiving 222 ance on the availability of devices varies widely. responses. An expert group of clinicians and Results: From the questionnaire, 35 of the 38 statement responses showed [ 66% consensus, Enhanced Digital Features To view enhanced digital features for this article go to https://doi.org/10.6084/ with 26 of these achieving [ 90% agreement. m9.figshare.7819586. Conclusion: The expert group reviewed the responses and made recommendations based on D. A. Robertson (&) the clear professional consensus demonstrated. Leighton Hospital, Crewe, UK These included the need to use new technology e-mail: doug.robertson@nhs.net and data integration and that wider factors, R. A. Chudleigh including patient choice rather than cost alone, Singleton Hospital, Swansea, UK should inform formulary inclusion of BGM equipment. S. D. Gwynn  T. C. Warren Triducive Ltd., Tunbridge Wells, UK Funding: LifeScan U.K. Ltd. C. Jairam Keywords: BGM; Blood glucose; Glycemic Imperial College, London, UK control; Consensus; Monitoring; Type 1 K. Kansagra diabetes; Type 2 diabetes Shotfield Medical Practice, Wallington, UK N. Kanumilli Northenden Group Practice, Manchester, UK INTRODUCTION A. Lester-George Diabetes is a widely prevalent long-term con- LeLan Ltd, Bristol, UK dition in which raised blood glucose levels over C. McMurray time contribute to complications that are costly Sheffield Clinical Commissioning Group, Sheffield, in terms of healthcare use and impact adversely UK 902 Diabetes Ther (2019) 10:901–916 on quality of life. Blood glucose monitoring METHODS (BGM) has an important part to play in the management of blood glucose in diabetes and This article does not contain any studies with the reduction of risk of serious secondary com- human participants or animals performed by plications [1]. The first BGM meter was intro- any of the authors. duced in 1970 [1], and available technology has The group used the Delphi [6] methodology evolved markedly since then. In today’s tech- to validate the views of a large number of peers nology-rich environment, self-monitoring of regarding BGM in the current UK National blood glucose is an integral part of effective Health Service (NHS) setting, with the goal of diabetes management [2], allowing patients to better understanding their views regarding monitor their glycemic status and adjust their changing demographics and BGM technology. therapy accordingly. The recommendations derived from the Modern healthcare requires that long-term responses seek to support HCPs in assessing new conditions are managed in a shared and col- technologies available to them and provide laborative way between the patient and all decision-support for choice of technology. As stakeholders involved in their care, rather than such, these consensus views and recommenda- solely by the patient or healthcare profession- tions which the group felt were justifiable from als (HCPs). Despite clear demonstrations of the the responses are offered in order to provide a benefits of BGM meters that provide feedback reference point for the use of BGM for both to patients [2], and diabetes being almost uni- commissioners and providers. In addition, the versally managed in the UK by NHS profes- consensus process aimed to identify regional sionals, there is an apparent lack of clarity variation in the responses to statements and is within the NHS regarding emerging BGM intended to inform the paradigm shift required technologies and their potential to positively to adopt new technologies for BGM. impact service delivery and increase resource A group of clinicians and payers involved in efficiency while supporting patient empower- diabetes care met to review the current adop- ment. This was demonstrated in a survey of tion of BGM systems in the UK and determine a over 1000 BGM users carried out by Diabetes framework for consensus. Seven key topics were UK [3], with the responses suggesting that initially identified, and consensus statements NICE (National Institute for Health and Care developed for each (Table 1). These statements Excellence) guidance is not always imple- were collated into a questionnaire, which was mented as recommended for type 1 [4]and circulated widely over a 3-month period to type 2 [5]diabetes. clinicians involved in diabetes management by This consensus steering group (all mem- in-person cascade and by e-mail from group bers are co-authors to this paper) has sought members and with the help of LifeScan, Inc. the real-life perspectives of NHS staff involved (London, UK) representatives. Responses were in diabetes care to gain an understanding of collated and analyzed in confidence by Tridu- their attitudes to BGM technology and its cive Ltd (St Albans, UK). Respondents were value for people with diabetes who require required to use a 4-point Likert scale to rate intensive BG monitoring. This was felt nec- their agreement with each statement. Responses essary because the speed of introduction of were: ‘strongly disagree’; ‘tend to disagree’; technology was perceived to move more ‘tend to agree’; and ‘strongly agree.’ The ques- quickly even than centralized expert guid- tionnaire also asked respondents for their ance. In order to fulfil the requirements for locality, their speciality, and the department in fully collaborative shared care, it is important which they work. While personal details were that optimum technology is utilized and a not used for reporting results, clinical back- ‘big data’ approach is adopted, in order to ground and locality were used to assess poten- increase resource efficiency. tial differences in responses between professions and across the UK. Diabetes Ther (2019) 10:901–916 903 Table 1 Consensus topics and statements Consensus statement Consensus topic Statement number 1 Evidence and outcomes The willingness of the patient to engage with a particular BGM device should be the driving factor in choice 2 Evidence should determine choices relating to BGM 3 There is a lack of evidence that more expensive BGM meters improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more important than evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence alone in choosing an appropriate BGM system in select patient groups 6 Evidence for blood glucose monitoring should include patient reported outcome measures 7 Evidence supporting the real-world usability of a device should be provided by the manufacturers 8 Access to blood glucose Consistency and reproducibility of data is important for decision-support monitoring data 9 BGM data should always support treatment decisions for people with type 1 diabetes or patients using insulin 10 It is important that the user can access real-time reports of their personal BGM data, trends, and patterns 11 Patients should be able to readily share their data with partners and medical professionals in real time 12 Influencing guidance Decision-makers should consider real-world evidence when making recommendations 13 Guidance should include clear, evidence-based decision support that is accessible to all HCPs 14 Guidance should support the value of digital solutions (e.g., real-time data sharing, remote consultations) in formulary selection 15 It is important that patients have access to real-time feedback/reports of their BGM trends and patterns to enable them to act 904 Diabetes Ther (2019) 10:901–916 Table 1 continued Consensus statement Consensus topic Statement number 16 Use of resources BGM manufacturers should provide data to indicate that their products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is misinterpreted and confusing to HCPs in terms of managing patients with type 1 diabetes or patients using insulin 18 Flash glucose monitoring has the potential to improve the use of NHS resources by supporting SMBG 19 Effective BGM (understanding and action) reduces the risks of hypoglycemia and ketoacidosis in patients with type 1 diabetes 20 The NHS should consider innovation in BGM for patients with type 1 diabetes or patients using insulin as an investment, rather than a cost 21 Patient education Decision-making through effective BGM (understanding and action) is a necessary component of patient education 22 HCPs and carers need a common understanding of how to interpret and act upon BGM data, trends and patterns 23 It is important that patients learn how to analyze and act upon trends and patterns in their SMBG/BGM data 24 Access to and action based on BGM data will improve patient motivation to adhere to their optimal SMBG regimen 25 Patient education can be effectively delivered at home through virtual consultations and virtual data sharing using digital applications 26 Decision-making based on frequent and effective SMBG (BGM) is a necessary component of supporting effective patient education 27 Resources could be saved by replacing face-to-face structured education with education delivered virtually using new digital/BGM solutions 28 Effective BGM (with appropriate tools/features) provide a means to offer positive reinforcement to better support patient decisions Diabetes Ther (2019) 10:901–916 905 Table 1 continued Consensus statement Consensus topic Statement number 29 Data integration Patients’ BGM data should be easily accessible by every HCP involved in their care (to whom they have consented to provide access) 30 NHS data systems are not capable of effectively sharing data 31 Data should be accessible and integrated irrespective of the device that the patient uses 32 A standardized approach to cloud-held data and its formatting will improve its accessibility and utility for patients and HCPs 33 Patient choice BGM systems should not present barriers to regular use by patients 34 Formulary availability of BGM systems should not be driven by acquisition cost alone 35 The NHS should allow patient co-payment in order to allow more individualized patient care 36 Choice of BGM system should support the achievement of the patient’s own goals 37 Formulary availability of BGM systems should only be driven by patient choice 38 The willingness of the patient to engage with a particular BGM device should be the driving factor in choice BGM Blood glucose monitoring, HCP healthcare professional, NHS UK National Health Service, NICE National Institute for Health and Care Excellence, QALY quality-adjusted life-year, SMBG self-monitoring of blood glucose 906 Diabetes Ther (2019) 10:901–916 Completed questionnaires were then col- remain unknown and 19 had other roles. lated, and the individual scores for each state- Comparison between the responses of dia- ment analyzed in order to produce a full betologists, DSNs and the group overall is arithmetic agreement score for each statement. shown in Fig. 3. The responses were then sub-grouped by local- With the exception of statements 3, 4, 5, 16, ity and specialty to identify variances in the 17, 27, 30, and 37, the views of DSNs were well respondent’s agreement scores by either geog- aligned with those of the wider group. The raphy or role. variation in agreement scores for these state- The steering group had predefined the ments according to role is shown in Table 7. threshold of agreement for consensus at C 66%. Consensus was defined as ‘high’ at C 66% and DISCUSSION ‘very high’ at C 90%. Due to the high levels of agreement with all In this paper we describe the consensus views of but three of the statements, demonstrating very a large group of clinicians working the UK NHS, strong consensus views, the group elected to a government-funded, cost-limited healthcare avoid a further round of questionnaires to system that is substantially free at the point of generate a larger number of responses, and use. As such, the recommendations and views instead chose to work with the responses to the presented here may not reflect the views of original statements. HCPs in other healthcare systems. For patients with a need to optimize their RESULTS glycemic control, many factors may influence their choice of BGM system. Understanding the Completed questionnaires were returned by 222 value of a system to a patient may be a more respondents. The questionnaires were analyzed important measure than simply looking at the to score the total level of agreement with each acquisition cost of that device. In light of this, of the 38 statements. Of the 38 statements, 35 sharing the acquisition cost with the patient (92%) achieved an agreement score exceeding may be a valid option, as patients have the 66% threshold, and 26 of these (68%) demonstrated that when a device is recognized exceeded 90% agreement (Table 2, Fig. 1). as offering important advantages, they may be Only three of the statements achieved an willing to contribute to the cost [7]. agreement score of \ 66% or [ 33% and thus Effective BGM is recognized by 99.1% of were defined as not achieving consensus respondents as having the potential to reduce (Table 3). hypoglycemia and ketoacidosis in patients with Respondents were analyzed by region. The type 1 diabetes. Effective BGM may be regarded number of respondents from each region is as achieving tight glycemic control (according shown in Table 4. The sample was dominated to the type of diabetes) in line with personalized by respondents from England (n = 136) while goals. only four respondents were from Wales. Eigh- Respondents strongly agree with the asser- teen respondents did not indicate their region. tion that flash glucose monitoring has the While the majority of statements were scored potential to improve the use of NHS resources similarly, irrespective of the respondent’s region (88.9% agreement) and should be considered as (Fig. 2), nine statements showed larger regional an investment rather than a cost (96.3% variation in score (Table 5). agreement). Responses were also analyzed according to the respondent’s role (Table 6). Influencing Guidance While the largest single respondent groups by role were diabetologists and diabetes spe- Unsurprisingly, respondents strongly agree with cialist nurses (DSNs), 39 respondents did not statements 12 and 13 concerning the need for share their role on the questionnaire and thus real-world evidence when making Diabetes Ther (2019) 10:901–916 907 Table 2 Consensus statements and agreement scores Consensus Topic Statement Agreement statement score (%) number 1 Evidence and The willingness of the patient to engage with a particular BGM 93.7 outcomes device should be the driving factor in choice 2 Evidence should determine choices relating to blood glucose 92.7 monitoring 3 There is a lack of evidence that more expensive BGM meters 78.5 improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more important than evidence alone in 71.8 choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence alone in 34.9 choosing an appropriate BGM system in select patient groups 6 Evidence for blood glucose monitoring should include patient 97.2 reported outcome measures 7 Evidence supporting the real-world usability of a device should be 95.0 provided by the manufacturers 8 Access to blood Consistency and reproducibility of data is important for decision 99.1 glucose monitoring support data 9 BGM data should always support treatment decisions for people 98.2 with type 1 diabetes or patients using insulin 10 It is important that the user can access real time reports of their 94.5 personal BGM data, trends and patterns 11 Patients should be able to readily share their data with partners 96.8 and medical professionals in real time 12 Influencing guidance Decision-makers should consider real world evidence when 98.6 making recommendations 13 Guidance should include clear, evidence-based decision support 97.7 that is accessible to all HCPs 14 Guidance should support the value of digital solutions (e.g. real 98.2 time data sharing, remote consultations) in formulary selection 15 It is important that patients have access to real time feedback/ 96.8 reports of their BGM trends and patterns to enable them to take action 908 Diabetes Ther (2019) 10:901–916 Table 2 continued Consensus Topic Statement Agreement statement score (%) number 16 Use of resources BGM manufacturers should provide data to indicate that their 89.9 products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is misinterpreted and confusing to 60.5 HCPS in terms of managing patients with type 1 diabetes or patients using insulin 18 Flash glucose monitoring has the potential to improve the use of 88.9 NHS resources by supporting SMBG 19 Effective BGM (understanding and action) reduces the risks of 99.1 hypoglycemia and ketoacidosis in patients with type 1 diabetes 20 The NHS should consider innovation in BGM for patients with 96.3 type 1 diabetes or patients using insulin as an investment, rather than a cost 21 Patient education Decision making through effective BGM (understanding and 99.5 action) is a necessary component of patient education 22 HCPs and carers need a common understanding of how to 100.0 interpret and act upon BGM data, trends and patterns 23 It is important that patients learn how to analyze and act upon 98.2 trends and patterns in their SMBG/BGM data 24 Access to and action based on BGM data will improve patient 98.1 motivation to adhere to their optimal SMBG regimen 25 Patient education can be effectively delivered at home through 77.5 virtual consultations and virtual data sharing using digital applications 26 Decision making based on frequent and effective SMBG (BGM) 95.9 is a necessary component of supporting effective patient education 27 Resources could be saved by replacing face-to-face structured 66.8 education with education delivered virtually using new digital/ BGM solutions 28 Effective BGMs (with appropriate tools/features) provide a 97.2 means to offer positive reinforcement to better support patient decisions Diabetes Ther (2019) 10:901–916 909 Table 2 continued Consensus Topic Statement Agreement statement score (%) number 29 Data integration Patients’ BGM data should be easily accessible by every HCP 98.6 involved in their care (to whom they have consented to provide access) 30 NHS data systems are not capable of sharing data effectively 81.0 31 Data should be accessible and integrated irrespective of the device 97.2 that the patient uses 32 A standardized approach to cloud-held data and its formatting 98.1 will improve its accessibility and utility for patients and HCPs 33 Patient choice BGM systems should not present barriers to regular use by 100.0 patients 34 Formulary availability of BGM systems should not be driven by 92.2 acquisition cost alone 35 The NHS should allow patient co-payment in order to allow 77.0 more individualised patient care 36 Choice of BGM system should support the achievement of the 98.2 patient’s own goals 37 Formulary availability of BGM systems should only be driven by 44.7 patient choice 38 The willingness of the patient to engage with a particular BGM 84.3 device should be the driving factor in choice Total Consensus Agreement Scores 100.0% 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% 0123456789 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 Fig. 1 Plot of total consensus agreement scores 910 Diabetes Ther (2019) 10:901–916 Table 3 Statements with agreement scores of between 33 and 66% Consensus Topic Statement Agreement statement score (%) number 5 Evidence and HCP preference is more important than evidence alone in choosing an 34.9 outcomes appropriate BGM system in select patient groups 17 Use of Guidance around SMBG is misinterpreted and confusing to HCPS in 60.5 resources terms of managing patients with type 1 diabetes or patients using insulin 37 Patient Formulary availability of BGM systems should only be driven by patient 44.7 choice choice endorsing the need for digital solutions, which Table 4 Respondents by region may support the objective of increasing per- Region Number of respondents sonal management of long-term conditions. In addition, 96.8% of respondents agree that England 136 patients should have access to real-time data Scotland 26 enabling them to act. In total, 98.2% of delegates support the view Wales 4 that guidance should support the value of dig- Northern Ireland 18 ital solutions when it comes to formulary London 13 inclusion. However, BGM formulary decisions are still firmly focused on devices and the Unknown 25 acquisition cost of the device test strips, despite Total 222 the NHS’s intention to move to solutions that are orientated around digital, big data and evi- dence that demonstrates an impact on health recommendations and the need for clarity in outcomes. the evidence base from guidance used in deci- sion-support. There is strong agreement (98.2%) Consensus Agreement Scores by Region 100.0% 90.0% 80.0% All Responses 70.0% England 60.0% Scotland 50.0% 40.0% Wales 30.0% N. Ireland 20.0% London 10.0% 0.0% 0123456789 1011121314151617181920212223242526272829303132333435363738 Fig. 2 Consensus agreement scores by region Diabetes Ther (2019) 10:901–916 911 Table 5 Statements with largest regional variation in agreement scores Consensus Topic Statement Agreement scores (%) statement England Scotland Wales Northern London number (%) (%) (%) Ireland (%) (%) 2 Evidence Evidence should determine choices 94.0 100.0 50.0 94.4 76.9 and relating to BGM outcomes 3 There is a lack of evidence that 76.4 80.8 100.0 94.1 61.5 more expensive BGM meters improve outcomes in type 1 diabetes and people with diabetes using insulin 4 Patient preference may be more 78.5 64.0 100.0 50.0 61.5 important than evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important 41.4 23.1 0.0 27.8 38.5 than evidence alone in choosing an appropriate BGM system in select patient groups 16 Use of BGM manufacturers should provide 88.9 92.3 75.0 100.0 84.6 resources data to indicate that their products fall below the NICE £30,000 per QALY threshold 17 Guidance around SMBG is 64.5 61.5 25.0 42.9 46.2 misinterpreted and confusing to HCPS in terms of managing patients with type 1 diabetes or patients using insulin 25 Patient Patient education can be effectively 74.8 73.1 100 76.5 76.9 education delivered at home through virtual consultations and virtual data sharing using digital applications 35 Patient The NHS should allow patient co- 82.0 65.4 50.0 72.2 75.0 choice payment in order to allow more individualised patient care 38 The willingness of the patient to 87.9 84.6 100.0 70.6 38.5 engage with a particular BGM device should be the driving factor in choice 912 Diabetes Ther (2019) 10:901–916 Table 6 Respondents by role it has been reported that 32.3% of measured hypoglycemic episodes are preceded by an Role N observed pattern of low blood glucose [10]. Data Diabetologist 53 should always support treatment decisions for people with type 1 diabetes or patients using Diabetes specialist nurse 45 insulin (96.8%). Pharmacist 22 Data offer patients the insight to manage their blood glucose with confidence. Respon- Nurse 20 dents strongly agree that decisions made by GP 13 patients should always be supported by data (98.2%). Access to data promotes engagement Obstetrics 8 with trends and patterns within the data to Dietician 3 inform the patient in a way that complements the role of the HCP. Other 19 Unknown 39 Patient Education Total 222 There is evidence to show that good BGM results in better outcomes and that people Access to BGM Data should be supported and educated in the interpretation of data to achieve these better All statements relating to BGM data are very outcomes. In our survey 100% of respondents strongly supported by respondents. Having support the importance of a common under- consistency and reproducibility of data is con- standing of how to interpret and act upon BGM sidered to be of paramount importance (99.1%), data, trends, and patterns. Given the nature of and supporting type 1 patient’s treatment diabetes, it is vital that carers are actively decisions in real-time is strongly supported involved with patients, and access to real-time (98.2%). data is an important consideration. Diabetes The need for patients to have real-time impacts the whole household [11]. reports of their personal BGM data is supported Among respondents, 99.5% agree that effec- by 94.5% of respondents. It has been shown tive BGM is a necessary component of patient that automated pattern algorithms can assist in education; in addition, the importance of access the avoidance of hypoglycemic episodes [8, 9]. Total Consensus Agreement Scores by Role 100.0% 90.0% 80.0% 70.0% 60.0% All Responses 50.0% Diabetologists 40.0% DSNs 30.0% 20.0% 10.0% 0.0% 0123456789 1011121314151617181920212223242526272829303132333435363738 Fig. 3 Consensus agreement scores by role. DSN Diabetes specialist nurse Diabetes Ther (2019) 10:901–916 913 Table 7 Statements with largest variation in agreement scores by role Consensus Topic Statement Agreement scores (%) statement Total DSNs Diabetologists number (%) (%) (%) 3 Evidence There is a lack of evidence that more expensive BGM 78.5 71.4 78.0 and meters improve outcomes in type 1 diabetes and outcomes people with diabetes using insulin 4 Patient preference may be more important than 71.8 77.8 60.4 evidence alone in choosing an appropriate BGM system in select patient groups 5 HCP preference is more important than evidence 34.9 17.8 30.8 alone in choosing an appropriate BGM system in select patient groups 17 Use of Guidance around SMBG is misinterpreted and 60.5 57.1 51.0 resources confusing to HCPS in terms of managing patients with type 1 diabetes or patients using insulin 27 Patient Resources could be saved by replacing face-to-face 66.8 62.8 59.6 education structured education with education delivered virtually using new digital/BGM solutions 30 Data NHS data systems are not capable of sharing data 81.0 85.4 81.1 integration effectively 37 Patient Formulary availability of BGM systems should only be 44.7 41.5 49 choice driven by patient choice DSN Diabetes specialist nurse to BGM data and of understanding trends and positive reinforcement in support of patient patterns is strongly supported (statements 23 decisions, reflecting recent published data and 24). Access to feedback on their progress [2, 12]. helps patients to take action to improve their diabetes control or continue with previous Data Integration positive actions [2]. There is strong agreement that virtual data and applications can support Respondents strongly support that the notion education at home. Remote support in the that data systems should be integrated and patient’s home and work environments is inter-operable across the NHS (97.2% agree- important so that patients are not constrained ment). Eventually, integration of data should by the need to attend a clinic. involve a standardized approach in order to Statement 27 achieved consensus (66.8% improve access and utility (statements 31 and agreement) despite the inference that resources 32). Data are of no use unless it can be effec- could be saved by replacing face-to-face educa- tively used and applied. tion. In reality, respondents may better support Members of the consensus group agreed that the assertion that the two should complement high-quality data are essential for constructive one another. This would offer a synergistic consultations; therefore, access to data will benefit. There is 97.2% agreement among improve resource utilization and avoid wasted respondents that BGM offers a means to offer clinic sessions. There was 98.6% agreement 914 Diabetes Ther (2019) 10:901–916 among respondents that patients’ BGM data indicators was associated with improvements in should be accessible by every HCP involved in glycated hemoglobin levels compared to sub- their care. This result is supported in the litera- jects using a wide selection of marketed BGM ture, with published data showing improve- systems without color support [14]. Despite ment in glycemic control by patients using this, respondents support the assertion (78.5%) integrated BGM data [8, 12]. Cloud-held data that there is a lack of evidence that more may lead to better data-utility among patients expensive BGM systems improve outcomes, and HCPs (98.1%) as long as it is easily acces- suggesting that respondents may not be fully sible as per regulatory guidelines. It may also aware of recent innovations and published data. facilitate remote consultations and can alleviate Data are available providing direct comparison the problem of forgotten logbooks or devices in between solutions that help the patient and face-to-face consultations. HCP with insights and interpretation of the Accessible cloud-held data can also be number versus traditional BGM [14]. shared/socialized with caregivers (e.g., elderly While the preference of the HCP is not patients) and loved ones (e.g., parents of chil- regarded by the respondents as being more dren). Studies have demonstrated improve- important than evidence (34.9%), patient pref- ments in outcomes when data is used in this erence is strongly supported (71.8%) as more way [8]. being important than evidence alone in choos- ing the right BGM system for the patient. Respondents strongly agree that evidence Use of Resources should include patient-reported outcome mea- sures (PROMS) (97.2%), such as real-world Respondents strongly agree that manufacturers usability (93.7%). should provide quality-adjusted life-year data to support their products (89.9%). There is a need Patient Choice for clear and consistent guidance regarding BGM, as evidenced by the lack of clarity from respondents regarding statement 17. A majority of respondents concurred that for- Almost all respondents (99.1%) agree that mulary availability should not be driven by a effective BGM will reduce the risks of hypo- single factor alone, with general agreement that glycemia and ketoacidosis in patients with type neither patient choice (55.3%) nor acquisition 1 diabetes. New technology has the potential to cost (92.2%) is sufficient to effectively make improve the use of NHS resources and should be formulary choices. Interestingly, respondents considered as an investment rather than a cost are accepting of patient co-payment (77%) as a (96.3% agreement). New technologies that means of accessing novel technology and sup- facilitate effective glycemic control are strongly porting individualized patient choice. This is a supported by respondents (88.9% agreement to paradigm shift and may reflect changing pro- statement 18, which is specific to flash glucose fessional attitudes. However, many patients monitoring and 96.3% agreement to statement have traditionally self-funded their BGM regi- 20). Solutions with automated pattern algo- men in the past, and the 2017 Diabetes UK rithm integration can improve HCP efficiency Survey recently revealed that BGM is less avail- and accuracy [13]. able than patients’ requirements [3]. There are 98.2% of respondents who agree that the choice of BGM system should support Evidence and Outcomes the achievement of the patients’ own goals and 84.3% who agree that the willingness of the Respondents strongly indicate (92.7%) that patient to engage with a particular BGM device evidence is important in improving patient care should be the driving factor in choice of system. and that it should inform choices relating to Recent data suggest that BGM supported by a BGM. Recent evidence [2] shows that switching web application and OneTouch Verio (OTV; patients to BGM systems featuring color range Diabetes Ther (2019) 10:901–916 915 LifeScan Inc., Milpitas, CA, USA) meter • Real-time BGM data should be made avail- able to patients and provide positive improved blood glucose control [12]. In addi- tion, recent studies indicate that connected reinforcement. • Guidance should be inclusive of evidence, BGM solutions that provide access to cloud- held data allow patients to feel more secure in patient preference, and outcomes data. the knowledge that they can access their dia- • Wider factors, such as patient choice, should betes information at any time [15]. inform guidance rather than cost alone. Overall, the strong support from a large • New technology for BGM should be regarded respondent group underlines the need to ensure as an investment rather than a cost. that patients have access to appropriate BGM • Structured education should be comple- mented by access to real-time feedback data. systems in line with the needs and expectations of their health care professionals. New BGM • The choice of BGM system should support the achievement of the patients’ own goals. technologies should be regarded as an invest- ment rather than a cost, as long-term cost-ef- • Shared ownership of the responsibility for self-care is critical. fectiveness may be achieved due to a reduction in negative outcomes and admissions and in greater patient satisfaction. This opportunity reflects the wider shift towards value-based ACKNOWLEDGEMENTS healthcare in the NHS. Limitations of Study Funding. LifeScan U.K. Ltd provided finan- cial support for the consensus process including article processing charges and steering group The cascade circulation of the questionnaire meetings but had no editorial control over the from the group to their network of colleagues content of the publication or its conclusions. and the willingness of the 222 clinical profes- All authors had full access to all of the data in sionals to respond spontaneously may have this study and take complete responsibility for introduced bias; nevertheless, the statements the integrity of the data and accuracy of the produced a high level of clinical consensus in data analysis. areas of uncertainty around BGM. The profes- sionals who responded covered a wide range of Medical Writing. Medical writing support disciplines and geographical spread within the and project coordination was provided by Tri- UK, but despite this there was a great deal of ducive Ltd., also funded by LifeScan UK Ltd. agreement in their responses. Authorship. All named authors meet the International Committee of Medical Journal CONCLUSIONS Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of The conclusions drawn by the consensus group the work as a whole, and have given their after consideration of the questionnaire approval for this version to be published. responses are as follows: • Informed patient choice should be regarded Disclosures. RichardA. Chudleigh:Received as the prime factor in the effective use of a speaker honorarium from Abbott. Naresh Kanu- BGM system. milli: Received honoraria from Pharmaceutical • Patient co-payment should be supported companies for advisory boards and talks (NN, where appropriate as this will allow more Napp, Takeda, Sanofi, AZ, Abbott, Ascensia). individualized patient care and empower Charlotte McMurray: Received honoraria from self-management. LifeScan. Douglas A. Robertson, Simon D. Gwynn, • Data integration is urgently required for Carol Jairam, Kaushal Kansagra, Adam Lester- BGM system access. 916 Diabetes Ther (2019) 10:901–916 NICE guideline [NG28]. 2005. https://www.nice. George, and Timothy C. Warren have nothing to org.uk/guidance/NG28. Accessed Feb 2019. disclose. 6. Dalkey N, Helmer O. An experimental application Compliance with Ethics Standards. This of the Delphi method to the use of experts. Manag article does not contain any studies with Sci. 1963;9:458–67. human participants or animals performed by 7. Diabetes UK. Diabetes UK consensus guideline for any of the authors. However, we thank the flash glucose monitoring. 2017. https://www. colleagues who responded and gave up their diabetes.org.uk/resources-s3/2017-09/1190_Flash% valuable time to complete and return their 20glucose%20monitoring%20guideline_SB_V9% 5B4%5D.pdf. Accessed Feb 2019. questionnaires. 8. Grady M, Katz LB, Cameron H, Levy BL. Diabetes Data Availability. The datasets analyzed app-related text messages from health care profes- during this study are available from the authors sionals in conjunction with a new wireless glucose on reasonable request. meter with a colour range indicator improves gly- caemic control in patients with type 1 and type 2 diabetes: randomized controlled trial. JMIR Dia- Open Access. This article is distributed betes. 2017;2(2):e19. under the terms of the Creative Commons Attribution-NonCommercial 4.0 International 9. Grady M, Campbell D, MacLeod K, Srinivasan A. Evaluation of a blood glucose monitoring system License (http://creativecommons.org/licenses/ with automatic high- and low-pattern recognition by-nc/4.0/), which permits any noncommer- software in insulin-using patients: pattern detec- cial use, distribution, and reproduction in any tion and patient-reported insights. J Diabetes Sci medium, provided you give appropriate credit Technol. 2013;7(4):970–8. to the original author(s) and the source, provide 10. SB Communications Group. Recognising and a link to the Creative Commons license, and addressing patterns of recurrent ‘‘highs’’ and ‘‘lows’’ indicate if changes were made. in people with insulin-treated diabetes: why is it important and how to go about it? Suppl J Diabetes Nurs. 2013;17:9. 11. Diabetes.co.uk. Emotional impact of diabetes on fam- REFERENCES ily and friends. https://www.diabetes.co.uk/emotio nal-impact-on-families.html. Accessed Jan 2019. 1. Clarke SF, Foster JR. A history of blood glucose 12. Katz LB, Dirani RG, Li G, Randoll RA, Mahoney JJ. meters and their role in self-monitoring of diabetes Automated glycaemic pattern analysis can improve mellitus. Br J Biomed Sci. 2012;69(2):83–93. health care professional efficiency and accuracy. J Diabetes Sci Technol. 2013;7(1):163. 2. Grady M, Katz LB, Cameron H, Levy BL. A compre- hensive evaluation of a novel color range indicator in 13. Katz LB, Stewart LS, Levy BL. Benefits to health care multiple blood glucose meters demonstrates professionals and patients with diabetes of a novel improved glucose range interpretation and aware- blood glucose meter that provides pattern recogni- ness in subjects with type 1 and type 2 diabetes. tion and real-time automatic messaging compared J Diabetes Sci Technol. 2016;10(6):1324–32. to conventional paper logbooks. Int Diabetes Nurs. 2015;12(1):27–33. 3. Testing Times: restrictions accessing test strips and meters for people with diabetes. Diabetes UK 2017. 14. Grady M, Katz LB, Levy BL. Use of blood glucose https://www.diabetes.org.uk/resources-s3/2017-08/ meters featuring color range indicators improves 1092_Testing%20times.pdf. Accessed Feb 2019. glycemic control in patients with diabetes in com- parison to blood glucose meters without color 4. National Institute for Health and Care Excellence (ACCENTS Study). J Diabetes Sci Technol. (NICE). Type 1 diabetes in adults: diagnosis and 2018;12(6):1211–9. management. NICE guideline [NG17]. 2015. https://www.nice.org.uk/guidance/ng17/chapter/1- 15. Grady M, Cameron H, Levy BL, Katz LB. Remote Recommendations#blood-glucose-management-2. health consultations supported by a diabetes man- Accessed Feb 2019. agement web application with a new glucose meter demonstrates improved glycaemic control. J Dia- 5. National Institute for Health and Care Excellence betes Sci Technol. 2016;10(3):737–43. (NICE). Type 2 diabetes in adults: management.

Journal

Diabetes TherapySpringer Journals

Published: Mar 19, 2019

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off