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      Development and Evaluation of a Mobile Decision Support System for Hypertension Management in the Primary Care Setting in Brazil: Mixed-Methods Field Study on Usability, Feasibility, and Utility

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          Abstract

          Background

          Despite being an important cardiovascular risk factor, hypertension has low control levels worldwide. Computerized clinical decision support systems (CDSSs) might be effective in reducing blood pressure with a potential impact in reducing cardiovascular risk.

          Objective

          The goal of the research was to evaluate the feasibility, usability, and utility of a CDSS, TeleHAS (tele– hipertensão arterial sistêmica, or arterial hypertension system), in the care of patients with hypertension in the context of a primary care setting in a middle-income country.

          Methods

          The TeleHAS app consists of a platform integrating clinical and laboratory data on a particular patient, from which it performs cardiovascular risk calculation and provides evidence-based recommendations derived from Brazilian and international guidelines for the management of hypertension and cardiovascular risk. Ten family physicians from different primary care units in the city of Montes Claros, Brazil, were randomly selected to use the CDSS for the care of hypertensive patients for 6 months. After 3 and 6 months, the feasibility, usability, and utility of the CDSS in the routine care of the health team was evaluated through a standardized questionnaire and semistructured interviews.

          Results

          Throughout the study, clinicians registered 535 patients with hypertension, at an average of 1.24 consultations per patient. Women accounted for 80% (8/10) of participant doctors, median age was 31.5 years (interquartile range 27 to 59 years). As for feasibility, 100% of medical users claimed it was possible to use the app in the primary care setting, and for 80% (8/10) of them it was easy to incorporate its use into the daily routine and home visits. Nevertheless, 70% (7/10) of physicians claimed that the time taken to fill out the CDSS causes significant delays in service. Clinicians evaluated TeleHAS as good (8/10, 80% of users), with easy completion and friendly interface (10/10, 100%) and the potential to improve patients’ treatment (10/10, 100%). A total of 90% (9/10) of physicians had access to new knowledge about cardiovascular risk and hypertension through the app recommendations and found it useful to promote prevention and optimize treatment.

          Conclusions

          In this study, a CDSS developed to assist the management of patients with hypertension was feasible in the context of a primary health care setting in a middle-income country, with good user satisfaction and the potential to improve adherence to evidence-based practices.

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          Most cited references27

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          A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010

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            Separate multivariable risk algorithms are commonly used to assess risk of specific atherosclerotic cardiovascular disease (CVD) events, ie, coronary heart disease, cerebrovascular disease, peripheral vascular disease, and heart failure. The present report presents a single multivariable risk function that predicts risk of developing all CVD and of its constituents. We used Cox proportional-hazards regression to evaluate the risk of developing a first CVD event in 8491 Framingham study participants (mean age, 49 years; 4522 women) who attended a routine examination between 30 and 74 years of age and were free of CVD. Sex-specific multivariable risk functions ("general CVD" algorithms) were derived that incorporated age, total and high-density lipoprotein cholesterol, systolic blood pressure, treatment for hypertension, smoking, and diabetes status. We assessed the performance of the general CVD algorithms for predicting individual CVD events (coronary heart disease, stroke, peripheral artery disease, or heart failure). Over 12 years of follow-up, 1174 participants (456 women) developed a first CVD event. All traditional risk factors evaluated predicted CVD risk (multivariable-adjusted P<0.0001). The general CVD algorithm demonstrated good discrimination (C statistic, 0.763 [men] and 0.793 [women]) and calibration. Simple adjustments to the general CVD risk algorithms allowed estimation of the risks of each CVD component. Two simple risk scores are presented, 1 based on all traditional risk factors and the other based on non-laboratory-based predictors. A sex-specific multivariable risk factor algorithm can be conveniently used to assess general CVD risk and risk of individual CVD events (coronary, cerebrovascular, and peripheral arterial disease and heart failure). The estimated absolute CVD event rates can be used to quantify risk and to guide preventive care.
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              Prediction of creatinine clearance from serum creatinine.

              A formula has been developed to predict creatinine clearance (Ccr) from serum creatinine (Scr) in adult males: (see article)(15% less in females). Derivation included the relationship found between age and 24-hour creatinine excretion/kg in 249 patients aged 18-92. Values for Ccr were predicted by this formula and four other methods and the results compared with the means of two 24-hour Ccr's measured in 236 patients. The above formula gave a correlation coefficient between predicted and mean measured Ccr's of 0.83; on average, the difference predicted and mean measured values was no greater than that between paired clearances. Factors for age and body weight must be included for reasonable prediction.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                March 2019
                25 March 2019
                : 7
                : 3
                : e9869
                Affiliations
                [1 ] Telehealth Center Hospital das Clínicas Universidade Federal de Minas Gerais Belo Horizonte Brazil
                [2 ] Post-Graduate Program in Infectious Diseases and Tropical Medicine Faculdade de Medicina Universidade Federal de Minas Gerais Belo Horizonte Brazil
                [3 ] Telehealth Network of Minas Gerais Belo Horizonte Brazil
                [4 ] Medical School Universidade Federal de Uberlândia Uberlândia Brazil
                [5 ] Medical School Universidade Estadual de Montes Claros Montes Claros Brazil
                Author notes
                Corresponding Author: Antonio Luiz Pinho Ribeiro tom@ 123456hc.ufmg.br
                Author information
                http://orcid.org/0000-0002-7381-1651
                http://orcid.org/0000-0003-4278-3771
                http://orcid.org/0000-0002-3226-3476
                http://orcid.org/0000-0002-5371-1901
                http://orcid.org/0000-0002-4241-1866
                http://orcid.org/0000-0002-6704-4505
                http://orcid.org/0000-0002-1544-5454
                http://orcid.org/0000-0001-9421-9828
                http://orcid.org/0000-0002-0364-3584
                Article
                v7i3e9869
                10.2196/mhealth.9869
                6452279
                30907740
                ab07f380-237a-424a-a42f-147fe743ff6f
                ©Daniel Vitório Silveira, Milena Soriano Marcolino, Elaine Leandro Machado, Camila Gonçalves Ferreira, Maria Beatriz Moreira Alkmim, Elmiro Santos Resende, Bárbara Couto Carvalho, André Pires Antunes, Antonio Luiz Pinho Ribeiro. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 25.03.2019.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/.as well as this copyright and license information must be included.

                History
                : 18 January 2018
                : 11 July 2018
                : 5 November 2018
                : 10 December 2018
                Categories
                Original Paper
                Original Paper

                telemedicine,clinical decision support system,cardiovascular disease,hypertension

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