In just over a half-century since the initiation of telemedicine, technological developments have created multiple options to shape how patients can access healthcare and interact with healthcare providers to better prevent and manage hypertension. In several high-income countries, patients are connecting to their healthcare providers online to book appointments, request prescriptions, see test results and engage in pro-active health management. Mounting evidence suggests that telemedicine and mobile health (mHealth) services can yield greater reductions in blood pressure when compared with usual care while also offering greater reach, efficiency, and potential cost-saving. A deeper examination of implementing such systems at scale in high-income countries shows varying approaches and levels of success. While research investigating the benefits of technology for blood pressure control in low- and middle-income countries is growing, in regions such as sub-Saharan Africa, economic and digital divides present major challenges to scaling such technology. Substantial national investments in infrastructure and skills development are needed alongside consultation with multiple stakeholders to ensure that technological advancements do not further drive health disparities in the region.
{"title":"Telemedicine for blood pressure control in low- and middle-income countries: the journey ahead","authors":"L. Ware","doi":"10.20517/ch.2022.16","DOIUrl":"https://doi.org/10.20517/ch.2022.16","url":null,"abstract":"In just over a half-century since the initiation of telemedicine, technological developments have created multiple options to shape how patients can access healthcare and interact with healthcare providers to better prevent and manage hypertension. In several high-income countries, patients are connecting to their healthcare providers online to book appointments, request prescriptions, see test results and engage in pro-active health management. Mounting evidence suggests that telemedicine and mobile health (mHealth) services can yield greater reductions in blood pressure when compared with usual care while also offering greater reach, efficiency, and potential cost-saving. A deeper examination of implementing such systems at scale in high-income countries shows varying approaches and levels of success. While research investigating the benefits of technology for blood pressure control in low- and middle-income countries is growing, in regions such as sub-Saharan Africa, economic and digital divides present major challenges to scaling such technology. Substantial national investments in infrastructure and skills development are needed alongside consultation with multiple stakeholders to ensure that technological advancements do not further drive health disparities in the region.","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83865159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Ionov, E. Usova, Michil P. Egorov, N. Zvartau, A. Konradi
Aim: Guidelines recommend treating hypertension (HTN) by keeping office blood pressure (BP) within the therapeutic range (TR). However, little is known about the TR of home BP. Therefore, we aimed to find a reliable proportion of home systolic (S) BP in TR (sBPiTR) using a telehealth platform, which facilitates the access to reliable and structured home BP data. Methods: We used the data of HTN patients who participated in BP telemonitoring and counseling for 3 months. Patients had to manually enter their home BP in electronic diaries. Home SBP readings were averaged by the system itself except the very first or every first day of BP monitoring. We divided sBPiTR (110-130 mmHg) by quartiles. A weighted Cohen’s kappa coefficient was used as an estimate of inter-rater reliability between sBPiTR and office/home SBP in TR. We used a binomial logistic regression to test the predictive value of sBPiTR on target office/home SBP achievement. Results: In total, 123 patients were included (median age 54 years; 102 males) with a median office SBP of 140 mmHg. By 3 months, it decreased to 130 mmHg (P < 0.001), with 60% of patients with target office BP and 70% in the upper sBPiTR quartiles. There was a slight agreement between office SBP in TR and sBPiTR of ≥ 50% (k = 0.19, P < 0.035) and fair agreement when countered against home SBP in TR (k = 0.32-0.65, P < 0.0001). Patients with sBPiTR of ≥ 50% were more likely to fall within the office and home SBP TR after adjustment for baseline covariates. Conclusion: The threshold of 50% of home SBP measurements within 110-130 mmHg has a slight agreement with office BP control and a fair agreement with home BP control. This variable may serve as a predictor for the achievement of target SBP both in and out of office. Larger studies are needed to confirm these preliminary results.
{"title":"Home blood pressure in target range as an additional therapeutic goal in hypertensive patients: a telemonitoring-based analysis","authors":"M. Ionov, E. Usova, Michil P. Egorov, N. Zvartau, A. Konradi","doi":"10.20517/ch.2022.12","DOIUrl":"https://doi.org/10.20517/ch.2022.12","url":null,"abstract":"Aim: Guidelines recommend treating hypertension (HTN) by keeping office blood pressure (BP) within the therapeutic range (TR). However, little is known about the TR of home BP. Therefore, we aimed to find a reliable proportion of home systolic (S) BP in TR (sBPiTR) using a telehealth platform, which facilitates the access to reliable and structured home BP data. Methods: We used the data of HTN patients who participated in BP telemonitoring and counseling for 3 months. Patients had to manually enter their home BP in electronic diaries. Home SBP readings were averaged by the system itself except the very first or every first day of BP monitoring. We divided sBPiTR (110-130 mmHg) by quartiles. A weighted Cohen’s kappa coefficient was used as an estimate of inter-rater reliability between sBPiTR and office/home SBP in TR. We used a binomial logistic regression to test the predictive value of sBPiTR on target office/home SBP achievement. Results: In total, 123 patients were included (median age 54 years; 102 males) with a median office SBP of 140 mmHg. By 3 months, it decreased to 130 mmHg (P < 0.001), with 60% of patients with target office BP and 70% in the upper sBPiTR quartiles. There was a slight agreement between office SBP in TR and sBPiTR of ≥ 50% (k = 0.19, P < 0.035) and fair agreement when countered against home SBP in TR (k = 0.32-0.65, P < 0.0001). Patients with sBPiTR of ≥ 50% were more likely to fall within the office and home SBP TR after adjustment for baseline covariates. Conclusion: The threshold of 50% of home SBP measurements within 110-130 mmHg has a slight agreement with office BP control and a fair agreement with home BP control. This variable may serve as a predictor for the achievement of target SBP both in and out of office. Larger studies are needed to confirm these preliminary results.","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"323 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80299296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
“Digital hypertension” is a new information and communication technology (ICT)-based research field of digital healthcare that adds significant value to the management of hypertension by integrating multidimensional and time-series data. It includes the study of pathogenesis and predictive, individualized, and preemptive treatments, and its clinical outcomes can be introduced in telemedicine. The ICT in digital hypertension includes the research and development of blood pressure (BP) monitoring, e.g., wearable, cuff-less BP monitoring, a platform for digital transformation and transmission systems, and artificial intelligence. A recent clinical trial demonstrated the significant BP-lowering effect of digital therapeutics that facilitate lifestyle modification at the individual level via the patient’s smartphone. One of the goals of digital hypertension is personalized anticipation medicine that identifies the timing, place, and behavior that may trigger the onset of a cardiovascular event. This narrative review aims to address and discuss the cutting-edge information on the technology and concept of “digital hypertension”.
{"title":"State-of-the-art rapid review of the current landscape of digital hypertension","authors":"K. Kario, N. Harada, Ayako Okura","doi":"10.20517/ch.2022.02","DOIUrl":"https://doi.org/10.20517/ch.2022.02","url":null,"abstract":"“Digital hypertension” is a new information and communication technology (ICT)-based research field of digital healthcare that adds significant value to the management of hypertension by integrating multidimensional and time-series data. It includes the study of pathogenesis and predictive, individualized, and preemptive treatments, and its clinical outcomes can be introduced in telemedicine. The ICT in digital hypertension includes the research and development of blood pressure (BP) monitoring, e.g., wearable, cuff-less BP monitoring, a platform for digital transformation and transmission systems, and artificial intelligence. A recent clinical trial demonstrated the significant BP-lowering effect of digital therapeutics that facilitate lifestyle modification at the individual level via the patient’s smartphone. One of the goals of digital hypertension is personalized anticipation medicine that identifies the timing, place, and behavior that may trigger the onset of a cardiovascular event. This narrative review aims to address and discuss the cutting-edge information on the technology and concept of “digital hypertension”.","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"222 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73996586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9780804788410-010
Steven Cassedy
{"title":"7 The Globalized Consumer Network: From Pineapples to Turkey Red Cigarettes to the Bunny Hug","authors":"Steven Cassedy","doi":"10.1515/9780804788410-010","DOIUrl":"https://doi.org/10.1515/9780804788410-010","url":null,"abstract":"","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"104 9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86537360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9780804788410-014
{"title":"Conclusion: Who You Are","authors":"","doi":"10.1515/9780804788410-014","DOIUrl":"https://doi.org/10.1515/9780804788410-014","url":null,"abstract":"","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90255045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9780804788410-009
{"title":"6 The Networked House and Home","authors":"","doi":"10.1515/9780804788410-009","DOIUrl":"https://doi.org/10.1515/9780804788410-009","url":null,"abstract":"","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82565280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-12-31DOI: 10.1515/9780804788410-008
{"title":"5 The Network of Spatialized Time","authors":"","doi":"10.1515/9780804788410-008","DOIUrl":"https://doi.org/10.1515/9780804788410-008","url":null,"abstract":"","PeriodicalId":93536,"journal":{"name":"Connected health","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86985896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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