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Enregistrement W4401518766 · doi:10.1093/ajh/hpae107

Towards Optimal Use of Home BP Monitoring Technology: Incorporating Patient Perspectives

2024· letter· en· W4401518766 sur OpenAlexaffabout
Raj Padwal, Jennifer Cluett

Notice bibliographique

RevueAmerican Journal of Hypertension · 2024
Typeletter
Langueen
DomaineMedicine
ThématiqueBlood Pressure and Hypertension Studies
Établissements canadiensCanadian VIGOUR CentreUniversity of Alberta
Organismes subventionnairesnon disponible
Mots-clésMedicineLibrary sciencePhoneClinical epidemiologyNew englandFamily medicineGerontologyEpidemiologyInternal medicineLaw

Résumé

récupéré en direct d'OpenAlex

The highly variable nature of blood pressure (BP), which is constantly fluctuating in response to many endogenous and exogenous stimuli, creates challenges when trying to determine if a given patient has hypertension. Important factors, ubiquitous in everyday life, that can influence BP in a clinically meaningful way include ambient noise and temperature, body position, physical activity, arm location in relation to the heart, post-prandial state, and emotional status.1 It is therefore useful to perform BP measurements using standardized technique, as hastily taken readings in busy clinical settings will most often result in higher BP readings.2,3 The act of measurement in the clinical setting itself can be an additional source of variability by raising BP in some patients—this is referred to as “white coat hypertension” if a patient is untreated and “white coat effect” if a patient is on antihypertensive therapy.3,4 Notably, when patients with an initially elevated clinic reading are simply observed rather than treated with antihypertensive medications, mean BP continues to drop over time and did not reach a nadir until the fifth or sixth visit in one study.5 This variable nature of BP leads to a conundrum that is more often present when diagnosing and treating hypertension compared to other cardiovascular risk factors like diabetes or dyslipidemia. For the latter, A1c and plasma lipid measurements, although somewhat variable, generally enable decisive action to be taken once known without the need for verifying through repeat measurement. Dealing with hypertension often requires more patience, as it is typically desirable to avoid using elevated measurement(s) from a single clinic visit to “diagnose” hypertension and initiate pharmacotherapy.3 Such practice should be resisted, as it can lead to mislabeling patients as having hypertension, potentially leading to unnecessary pharmacotherapy. The solution to the conundrum of accurately determining an individual’s usual BP given its constantly changing nature, is to perform repeated, standardized measurements over time and use the mean BP for clinical decision making.3,6 Indeed, this was the method used in many landmark clinical trials of antihypertensive agents, in which the mean of multiple measurements performed by trained research personnel (“research quality measurements”), were used to determine initial eligibility (often over multiple visits) and for drug dose titration.7 Emulating this approach in contemporary clinical practice would be ideal but is inherently challenging given time and resource constraints. Use of automated devices that calculate the mean of 3–5 measurements performed in short sequence (i.e., automated office BP or automated office blood pressure) helps and, if performed unattended while the patient rests quietly in the exam room, enables health care personnel to perform other tasks in parallel.8 Automated office blood pressure has been used in several landmark clinical trials, including the Systolic Blood Pressure Intervention Trial (SPRINT), and is a reasonable approach.8,9 Even so, it still only reflects a snapshot assessment of BP at a single clinical visit. An alternative approach to obtaining multiple BP readings separated in space and time, and one that is endorsed by contemporary clinical practice guidelines in the United States and globally, is to perform out-of-office BP monitoring.6,10 Options include home (or self) BP monitoring and 24-hour ambulatory BP monitoring, with the former being more feasible given widespread use of home BP devices among patients. A common objection to the use of home BP is that it does not replicate the research quality measurement procedures used in landmark clinical trials and observational studies—however, it is worth noting that neither does the BP measurement performed routinely in a typical clinical practice because standardized technique is rarely used.3 Notably, home BP monitoring, has additional advantages compared to other modalities: It increases patient engagement and self-monitoring of BP11; Its prognostic value is similar to ambulatory BP monitoring12; Particularly when combined with telemonitoring (the electronic transmission of readings), it enables remote data collection for virtual care13; When coupled with care management (usually provided by a nurse, pharmacist, or community worker), clinically important reductions in BP have been demonstrated in randomized trials14; At least in the United States, use is supported by reimbursement through remote patient monitoring (RPM) and dedicated hypertension-focused self-measured BP (SMBP) Current Procedural Terminology codes. While seemingly similar, there are notable differences between these two different types of billing codes. RPM codes can apply to any chronic disease, not just hypertension, and specify the need for direct data transmission of a minimum of 16 days of biometric readings/month (BP is just one of several allowable data elements). In addition, care plan communication must be interactive and synchronous and can be billed incrementally based on time (with 20 minutes per month as the minimum). SMBP codes, on the other hand, are specific for BP and have much lower technology requirements; there is no requirement for direct data transmission into an electronic health record. A minimum of 12 BP readings over the course of the month is sufficient and can be condensed into fewer days of measurement. Care plan communication can be asynchronous and performed via secure portal messaging. For both RPM and SMBP codes, patients may be responsible for portional copays or deductibles. Though insurance coverage is variable depending on the region, payer and specific combinations of codes submitted, generally speaking the cost—and subsequent reimbursement—is substantially higher for RPM than for SMBP. If home BP monitoring is to be used, a structured approach is useful. Important steps that should increase the likelihood that home BP data are valid and, therefore, actionable include: Recommended home BP measurement technique should be reviewed with the patient on the initial visit and through periodic reinforcement; Clinicians should guide patients to use a clinically validated device (e.g., www.validatebp.org and/or www.stridebp.org) and a properly fitted upper arm cuff; Use of the mean of multiple readings for clinical decision making is recommended. To minimize occurrence of selective reporting of readings, electronic transmission of relevant BP measurements over a defined period can be performed, with mean BP autocalculated. In addition, direct integration into the electronic medical/health record of, at minimum, the mean home BP value is helpful, although often not practically feasible. Relative to other modalities, patients are asked, by definition, to take a more active role when home BP monitoring technology is used to generate the data underpinning clinical management decisions. Understanding patient’s views on the use of such technologies could, therefore, help ensure a more patient-centric deployment. Two recently published qualitative studies in the American Journal of Hypertension provide useful data in this regard. In the first, semi-structured interviews were performed in 35 participants with hypertension as part of a sub-study embedded within a randomized controlled trial comparing the accuracy and acceptability of different BP measurement modalities (home, in-clinic, in-pharmacy kiosks) to 24-hour ambulatory BP monitoring.15 Participants viewed home BP monitoring as convenient, comfortable, accurate, and useful for assessing BP over time. Concerns included ensuring proper technique and the cost of devices. In a related publication from this trial, home BP monitoring was the highest rated of the 4 modalities in terms of acceptability and adherence to monitoring.16 In the second qualitative study, published in this issue of the Journal, Chu et al.17 conducted semi-structured interviews in 14 patients with uncontrolled hypertension receiving a guideline-concordant RPM and team-based care intervention to improve BP control. This was performed in academic primary care, with participants recruited from racially diverse, low-income setting. The analysis was stratified by patient engagement level, with high engagement defined as greater than 16 readings transmitted per month for the first 3 months. In general, patients found the intervention to be acceptable, appropriate, and feasible and the technology or remote nature of the care paradigm were not felt to be limitations. Use of cellular rather than Bluetooth-enabled BP devices to electronically transmit data likely helped ensure a smoother experience, although we note that, on a relative basis, there are currently many more validated Bluetooth-enabled devices than cellular devices available on the market and cellular devices also are sold at a higher price point and can incur additional monthly expenses. Not surprisingly, the burden of obtaining BP measurements twice daily was identified as a challenge, particularly in the low engagement subgroup. This important finding underscores the need to ensure that the requirements for data collection achieve accuracy goals without being unnecessarily burdensome. According to contemporary and evidence-based US guidelines, two home BP readings in the morning and two in the evening are recommended and should ideally be obtained beginning 2 weeks after a change in the treatment regimen and/or the week before a clinic visit.6 We believe aligning requirements for reimbursement for remote hypertension care with contemporary clinical practice guidelines should be a priority because it would help finance incentives align with these evidence-based recommendations. Since one of the earliest descriptions of its use in 1974, use of home BP monitoring, and associated technologies continues to be refined.18 It has developed into a useful tool and it is hoped that further enhancement, including by incorporating patient perspectives, can further optimize its use to improve outcomes in hypertensive patients. Financial conflicts of interest and disclosures: RP is CEO of mm Hg, provider of digital health solutions including home blood pressure telemonitoring software. JC: none.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,050
score de la tête « metaresearch » (Gemma)0,171
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,050
Score d'incertitude au seuil0,263

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0500,171
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0020,001
Bibliométrie0,0030,001
Études des sciences et des technologies0,0030,002
Communication savante0,0140,009
Science ouverte0,0020,009
Intégrité de la recherche0,0040,008
Charge utile insuffisante (le modèle a refusé de juger)0,0050,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,043
Tête enseignante GPT0,267
Écart entre enseignants0,225 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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