Contributions to the literature
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This mixed-methods study explored the implementation process for practitioners using a digital intervention shown to be effective for lowering blood pressure.
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Practitioners showed moderate adherence to escalating medication based on home readings.
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Diverse perceptions of implementing medication escalations when prompted were revealed, with some practitioners perceiving that the intervention facilitated appropriate medication escalation whilst a few described low perceived necessity and/or concerns about patient risk.
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Adherence to remotely notifying patients of medication escalation was low.
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Definitions of appropriate inaction could facilitate future implementation of interventions addressing clinical inertia.
Background
Methods
Design
Intervention and proposed mechanisms of action
Practitioner | Target behaviour | Description |
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Prescriber | Planning medication escalations | At a baseline consultation, prescribers planned three potential consecutive medication escalations which they would initiate if the patient’s average blood pressure was raised for two consecutive months during the trial. |
Changing medication in response to recommendations | When patients’ average blood pressure readings were above-target for two consecutive months, prescribers received an automated email recommending they make the next planned medication escalation (Additional file 2). When patients had a one-off very high or very low reading, the automated email recommended a clinical review. The patient could email their prescriber via the intervention in the case of raised blood pressure readings or after a recent medication escalation. Prescribers could reply to patients via email using the HOME BP programme. | |
Notifying patient of medication escalation via remote communication | A template letter was provided for practitioners to send patients, asking them to pick up the prescription. | |
Supporter | Providing remote support | Supporters were prompted by automated email to send monthly support emails to patients using pre-written templates (Additional file 3). These templates were designed to keep patients motivated to continue self-monitoring their blood pressure and engaging in any healthy lifestyle changes (an optional add-on). Supporters could also send ad hoc emails to patients. These could be supporter-initiated (e.g. congratulating them on well-controlled readings or asking about a new medication) or patient-initiated (e.g. to respond to emails sent from patients via HOME BP using the ‘Ask the Nurse’ function). |
Providing in-person support using the CARE approach | In-person support was designed to be minimal, but patients were offered optional appointments to help learn how to use the blood pressure monitor, and to support them in choosing a healthy lifestyle change. |
Data collection and measures
Quantitative
Process evaluation theme | Variable | Data source | Timepoint |
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Implementation | Planned medication escalations | Patient medical notes | Post 12-month follow-up |
N of medication escalation recommendations per prescriber | Objective data automatically recorded by intervention software | Throughout study | |
N and dates of medication escalations initiated | Patient medical notes | Post 12-month follow-up | |
Method for contacting patients re medication escalation | Patient medical notes | Post 12-month follow-up | |
N of support emails sent to patients via HOME BP | Objective data automatically recorded by intervention software | Post 12-month follow-up | |
Mechanisms | Self-efficacy to implement the intervention procedures | 3-item self-report questionnaire (Additional file 4) | Pre and post training module at baseline |
Outcome expectancies about the intervention | 6-item self-report questionnaire (Additional file 4) | Pre and post training module at baseline | |
Perceived acceptability of the intervention for patients | 3-item self-report questionnaire (Additional file 4) | Pre and post training module at baseline | |
Contextual factors | Systolic and diastolic blood pressure readings entered by patient | Objective data automatically recorded by intervention software | Throughout study |
N of blood pressure entries and n of medication escalation recommendations per patient | Objective data automatically recorded by intervention software | Throughout study | |
Patient age | Objective data automatically recorded by intervention software | Baseline | |
Patient blood pressure targets: a) Standard (135/85 mmHg) b) Adjusted due to diabetes (135/75 mmHg) c) Adjusted due to age (145/85 mmHg if aged over 80 years) | Objective data automatically recorded by intervention software | Baseline |
Qualitative
Participants
Quantitative
Qualitative
Analysis
Quantitative
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Mean adherence to planning medication escalations (100% adherence would be three planned escalations per patient).
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Mean adherence to initiating recommended medication escalations (n of recommended medication escalations initiated within 28 days/total medication escalations recommended by the intervention). Twenty-eight days was the threshold agreed by two clinicians, which ensured the escalation was made before the next set of blood pressure readings was submitted by the patient.
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Proportion of medication escalations made remotely (email or letter).
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Mean adherence to sending monthly support emails to patients.
Qualitative
Integration
Results
Participants providing qualitative data (n = 27) | Participants providing quantitative data (n = 125) | |||||
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Prescribers | Supporters | Prescriber-supporters | Prescribers | Supporters | Prescriber-supporters | |
n | 13 | 11 | 3 | 62 | 58 | 5 |
Gender | 5 female (38%) | 10 female (91%) | 3 female (100%) | 22 female (35%) | 55 female (95%) | 3 female (60%) |
Mean n of patients in intervention group at each Practice (range) | 5 (2–10) | 5 (2–8) | 7 (2–10) | 4.3 (− 1–12) | 4.4 (1–12) | 6.2 (2–10) |
Mean n of weeks from randomisation of first participant to time of interview (range) | 29 weeks (17–54) | 27 weeks (20–43) | 20 weeks (16–24) | N/A | ||
Mean duration of interview (range) | 26:14 (14–37 min) | 29:02 (11–62 min) | 43:19 (37–53 min) | N/A | ||
Mean n of recommendations for medication escalation received by prescriber at point of interview (range) | 3 (0–7) | N/A | 3 (1–4) | N/A |
Implementation
Theme | Sub-theme | Definitions | NPT construct |
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Ease or burden of implementing HOME BP | Perceptions about how well the digital intervention fits with current roles | Coherence (Individual Specification) | |
How tasks were implemented with colleagues | Collective action (Interactional Workability) | ||
Belief in the concept of HOME BP | Perceptions about how the digital intervention fitted with organisational goals or patient outcomes | Coherence (Internalisation) | |
Supporting patients to manage their own blood pressure | Planning medication escalations | How prescribers adapted the medication planning to facilitate implementation | Collective Action (Contextual Integration) |
Perceptions of the benefits and issues with using this approach to blood pressure management | Reflexive Monitoring (Individual appraisal) | ||
Using remote communication to manage blood pressure | Prescribers’ perceptions of implementing medication escalation remotely | Collective Action (Relational Integration, Interactional Workability) | |
Supporters’ experiences of supporting patients via email | Collective Action (Relational Integration) | ||
Prescribers’ and supporters’ experiences of receiving emails from patients | Collective Action (Interactional workability) | ||
Delivering additional support to patients at the Practice | Perceptions about using the CARE approach to support patients | Coherence (Individual Specification) Collective Action (Skillset Workability) | |
Reluctance to escalate medication | Barriers to adhering to recommended medication escalations | Collective Action (Relational Integration) |
Target behaviour | N incidents of adherence | Total possible incidents of adherence (n) | % adherence |
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Prescriber adherence to planning three medication escalations | 231 | 283 | 81.63 |
Prescriber adherence to initiating recommended medication escalations within 28 days | 215 | 405 | 53.09 |
Prescriber adherence to contacting patient remotely about a medication escalation | 74 | 196 | 37.76 |
Supporter adherence to sending monthly support emails to patients | 1611 | 2865 | 56.23 |
Mechanisms of change
Scale | Individual items where not treated as a scale | Response options | Before training median (range) | After training median (range) | Wilcoxon z score | 95% CI for mean difference scores |
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Prescriber self-efficacy (n = 67) | a. Create individualised patient medication plans | 1–10 | 9 (1–10) | 10 (1–10) | − 5.20 | 0.59 to 1.30 |
b. Increase patient medication when blood pressure remains too high | 9 (1–10) | 10 (1–10) | − 3.06 | 0.13 to 0.68 | ||
c. Integrate the HOME BP programme in to regular care | 7 (1–10) | 9 (2–10) | − 5.95 | 1.41 to 2.38 | ||
Prescriber outcome expectancies mean score (n = 67) | 1–5 | 4.00 (3–5) | 4.17 (3.33–5.00) | − 5.09 | 0.19 to 0.36 | |
Prescriber perceived acceptability of the intervention for patients (n = 67) | a. Self-monitor their blood pressure at home | 1–10 | 7 (5–10) | 8 (5–10) | − 4.96 | 0.62 to 1.30 |
b. Enter their blood pressure readings in to HOME BP | 7 (1–10) | 8 (5–10) | − 4.72 | 0.80 to 1.65 | ||
c. Make medication changes to control their blood pressure | 6 (1–10) | 8 (5–10) | − 5.57 | 1.23 to 2.28 | ||
Supporter self-efficacy mean score (n = 57) | 1–10 | 7.67 (2.33–10) | 9.33 (6.67–10) | − 5.55 | 1.32 to 2.33 | |
Supporter outcome expectancies mean score (n = 57) | 1–5 | 4.17 (3–5) | 4.5 (3–5) | − 4.34 | 0.16 to 0.38 | |
Supporter perceived acceptability of the intervention for patients mean score (n = 57) | 1–10 | 6.67 (1–10) | 8.33 (3.67–10) | − 4.82 | 0.88 to 2.00 |
Context
Quantitative data finding | Qualitative data finding | Triangulation outcome |
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Prescribers’ and supporters’ post-training questionnaires showed positive outcome expectancies and high confidence in intervention acceptability. | Practitioners perceived the digital intervention as a more accurate way of managing blood pressure and as being in line with the direction of Primary Care. | Partial agreement (complementary findings) |
No quantitative data were collected on setting up and integrating the digital intervention in normal practice. | Most practitioners considered that the programme was easy to integrate and described flexible approaches to organising the work. | Silence |
Adherence to planning three medication escalations was high (82%). Social cognitive beliefs and perceived acceptability of the intervention were not associated with adherence to planning medication escalations. | Whilst some prescribers perceived planning medication facilitated more comprehensive care, others described issues with planning in advance, including patient anxiety and additional effort when the plan needed revising. | Dissonance |
Adherence to initiating medication escalations was moderate (53%). Pre-planning medication escalations, self-efficacy beliefs and contextual patient factors such as average blood pressure reading and n of previous recommendations were related to adherence to initiating medication escalation. | Some prescribers believed that changing medication in response to recommendations was straightforward, but some reasons were discussed for not changing medication, including readings being close to the threshold, concerns about hypotension, and preferring to wait for more evidence. | Agreement |
Adherence to remotely changing medication was fairly low (38%). | Prescribers described preferring real-time contact at the time of a medication escalation in order to ensure patients have understood, and to avoid the hassle of sending a letter. | Agreement |
Adherence to sending patient support emails was moderate (56%). Social cognitive beliefs and perceived acceptability of the intervention were not associated with adherence to sending patient support emails. | Perceptions about supporting patients by email were mixed. Positive feedback from patients about the emails seemed to promote the perceived value of email support for supporters. | Agreement |
No quantitative adherence data were collected on using the CARE approach. | Supporters described a very low uptake to appointments by patients, so many had no experience of using CARE in practice. Hypothetical concerns included how to congratulate when patients’ progress was limited, and how to avoid giving advice when the patient expected it. | Silence |
Discussion
Distinguishing non-adherence from appropriate adaptation
Implications for future research
Barrier to implementation | NPT mechanism | Possible solution | Expert Recommendations for Implementing Change (ERIC) taxonomy |
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Doubts about the thresholds used to escalate medication | Low coherence | Adjusting the mismatch between the legislative targets of 150/90 mmHg (NHS England 2018) and the evidence-based targets of 135/85mmHg. | Involve executive boards |
For some practitioners, applying an algorithm to promote clinical decisions creates perceived conflict with delivering patient-centred care and shared-decision making | Low cognitive participation | Using an approved checklist [37] to inform criteria for distinguishing appropriate inaction from clinical inertia, to allow clinicians more flexibility in decision-making, whilst still encouraging medication escalation in cases where clinical inertia can occur. Where a practitioner decides not to escalate medication, the checklist could prompt them to plan when they will review their decision and any interim actions agreed with the patient, such as lifestyle change. | Promote adaptability |
Patients’ blood pressure readings are close to the target | Low coherence | Tailored email prompts with evidence for the benefits and safety of lowering blood pressure below the target. | Tailor strategies |
Wanting to wait for more evidence from further home blood pressure readings before making a medication change | Low interactional workability | Improved tracking capacity to allow practitioners to view patients’ readings over time and see cumulative evidence for medication escalation. Clinical Performance Feedback Intervention Theory describes several mechanisms for optimising the effectiveness of audit and feedback systems, including trends to show patient’s performance over time, and benchmarking to allow comparison with other practitioners [42]. | Audit and provide feedback |
Concerns about risk of hypotension following a medication change | Low reflexive monitoring | Tracking could reduce perceived risk of escalating medication by enabling practitioners to check patients’ clinical status after an escalation. | Audit and provide feedback |
GPs’ concerns about one-way notifications for patients not being received | Low cognitive participation | Some SMS systems already used in Primary Care allow patients to rapidly acknowledge receipt, which could increase feasibility of patient notifications for GPs. | Obtain and use feedback from patients/consumers and family |
Some nurses had concerns that one-way notifications conflict with their role of providing tailored patient support | Low coherence | Provide facility to allow nurses to enable two-way communication with patients if they wish to. | Involve patients/consumers and family members |