A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work?
ABSTRACT Background It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others. Objective We conducted a mediation analysis to determine wh...
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creator | Margolis, Karen L. Asche, Stephen E. Bergdall, Anna R. Dehmer, Steven P. Maciosek, Michael V. Nyboer, Rachel A. O’Connor, Patrick J. Pawloski, Pamala A. Sperl-Hillen, JoAnn M. Trower, Nicole K. Tucker, Ann D. Green, Beverly B. |
description | ABSTRACT
Background
It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others.
Objective
We conducted a mediation analysis to determine which of seven factors had the greatest effect on change in systolic blood pressure (BP) after 6 months in a trial to improve hypertension control.
Design
The study was a preplanned secondary analysis of a cluster-randomized clinical trial. Eight clinics in an integrated health system were randomized to provide usual care to their patients (
n
= 222), and eight were randomized to provide a telemonitoring intervention (
n
= 228).
Participants
Four hundred three of 450 trial participants completing the 6-month follow-up visit were included.
Interventions
Intervention group participants received home BP telemonitors and transmitted measurements to pharmacists, who adjusted medications and provided advice to improve adherence to medications and lifestyle modification via telephone visits.
Main measures
Path analytic models estimated indirect effects of the seven potential mediators of intervention effect (defined as the difference between the intervention and usual care groups in change in systolic BP from baseline to 6 months). The potential mediators were change in home BP monitor use, number of BP medication classes, adherence to BP medications, physical activity, salt intake, alcohol use, and weight.
Key Results
The difference in change in systolic BP was 11.3 mmHg. The multivariable mediation model explained 47 % (5.3 mmHg) of the intervention effect. Nearly all of this was mediated by two factors: an increase in medication treatment intensity (24 %) and increased home BP monitor use (19 %). The other five factors were not significant mediators, although medication adherence and salt intake improved more in the intervention group than in the usual care group.
Conclusions
Most of the explained intervention effect was attributable to the combination of self-monitoring and medication intensification. High adherence at baseline and the relatively low intensity of resources directed toward lifestyle change may explain why these factors did not contribute to the improvement in BP. |
doi_str_mv | 10.1007/s11606-015-3355-x |
format | Article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4617923</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1727988001</sourcerecordid><originalsourceid>FETCH-LOGICAL-c540t-a2b9d1aa1f1211187641e0aa6bfbe81c7de80832f5a08e41db606b0c9111aa453</originalsourceid><addsrcrecordid>eNp1UU1v1TAQtBCIvj74AVyQJS5cAl4nThwOoOpRaKUikCjq0do4m9YlL37YSdX373GUUj4kTnuY2dmZHcaegXgFQlSvI0ApykyAyvJcqez2AVuBkiqDoq4espXQush0lRcH7DDGayEgl1I_ZgdS1UqWKl8xPOJfJ2spxm7q-aepH12HlkZq-Xlw2PPR89PtLvgb4if7HYWRhuj8wDd-GIPvuRv4l-C2GPZ8g4He8IurPX_vWu5GfuHD93dP2KMO-0hP7-aafftwfL45yc4-fzzdHJ1lVhVizFA2dQuI0IEEAF2VBZBALJuuIQ22akkLnctOodBUQNuk6I2wdSIjFipfs7eL7m5qttRaSv6wN7vFnPHozN_I4K7Mpb8xRQlVLfMk8PJOIPgfE8XRbF201Pc4kJ-igUpWtdbzF9fsxT_Uaz-FIcUzcsa1ljA7goVlg48xUHdvBoSZCzRLgSYVaOYCzW3aef5nivuNX40lglwIMUHDJYXfp_-v-hNET6bX</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2001388215</pqid></control><display><type>article</type><title>A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work?</title><source>MEDLINE</source><source>EZB-FREE-00999 freely available EZB journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><source>SpringerLink Journals - AutoHoldings</source><creator>Margolis, Karen L. ; Asche, Stephen E. ; Bergdall, Anna R. ; Dehmer, Steven P. ; Maciosek, Michael V. ; Nyboer, Rachel A. ; O’Connor, Patrick J. ; Pawloski, Pamala A. ; Sperl-Hillen, JoAnn M. ; Trower, Nicole K. ; Tucker, Ann D. ; Green, Beverly B.</creator><creatorcontrib>Margolis, Karen L. ; Asche, Stephen E. ; Bergdall, Anna R. ; Dehmer, Steven P. ; Maciosek, Michael V. ; Nyboer, Rachel A. ; O’Connor, Patrick J. ; Pawloski, Pamala A. ; Sperl-Hillen, JoAnn M. ; Trower, Nicole K. ; Tucker, Ann D. ; Green, Beverly B.</creatorcontrib><description>ABSTRACT
Background
It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others.
Objective
We conducted a mediation analysis to determine which of seven factors had the greatest effect on change in systolic blood pressure (BP) after 6 months in a trial to improve hypertension control.
Design
The study was a preplanned secondary analysis of a cluster-randomized clinical trial. Eight clinics in an integrated health system were randomized to provide usual care to their patients (
n
= 222), and eight were randomized to provide a telemonitoring intervention (
n
= 228).
Participants
Four hundred three of 450 trial participants completing the 6-month follow-up visit were included.
Interventions
Intervention group participants received home BP telemonitors and transmitted measurements to pharmacists, who adjusted medications and provided advice to improve adherence to medications and lifestyle modification via telephone visits.
Main measures
Path analytic models estimated indirect effects of the seven potential mediators of intervention effect (defined as the difference between the intervention and usual care groups in change in systolic BP from baseline to 6 months). The potential mediators were change in home BP monitor use, number of BP medication classes, adherence to BP medications, physical activity, salt intake, alcohol use, and weight.
Key Results
The difference in change in systolic BP was 11.3 mmHg. The multivariable mediation model explained 47 % (5.3 mmHg) of the intervention effect. Nearly all of this was mediated by two factors: an increase in medication treatment intensity (24 %) and increased home BP monitor use (19 %). The other five factors were not significant mediators, although medication adherence and salt intake improved more in the intervention group than in the usual care group.
Conclusions
Most of the explained intervention effect was attributable to the combination of self-monitoring and medication intensification. High adherence at baseline and the relatively low intensity of resources directed toward lifestyle change may explain why these factors did not contribute to the improvement in BP.</description><identifier>ISSN: 0884-8734</identifier><identifier>EISSN: 1525-1497</identifier><identifier>DOI: 10.1007/s11606-015-3355-x</identifier><identifier>PMID: 25952653</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adhesion ; Aged ; Alcohol Drinking ; Alcoholic beverages ; Antihypertensive Agents - therapeutic use ; Blood pressure ; Blood Pressure - drug effects ; Blood Pressure Monitoring, Ambulatory - methods ; Case Management ; Combined Modality Therapy ; Drugs ; Female ; Health care ; Humans ; Hypertension ; Hypertension - diagnosis ; Hypertension - physiopathology ; Hypertension - therapy ; Internal Medicine ; Intervention ; Life Style ; Male ; Mathematical models ; Mediation ; Medication Adherence - statistics & numerical data ; Medicine ; Medicine & Public Health ; Middle Aged ; Motor Activity ; Occupational health ; Original Research ; Physical activity ; Primary Health Care - methods ; Salts ; Secondary analysis ; Sodium Chloride, Dietary - administration & dosage ; Telemedicine ; Telemedicine - methods ; Treatment Outcome</subject><ispartof>Journal of general internal medicine : JGIM, 2015-11, Vol.30 (11), p.1665-1672</ispartof><rights>Society of General Internal Medicine 2015</rights><rights>Journal of General Internal Medicine is a copyright of Springer, (2015). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c540t-a2b9d1aa1f1211187641e0aa6bfbe81c7de80832f5a08e41db606b0c9111aa453</citedby><cites>FETCH-LOGICAL-c540t-a2b9d1aa1f1211187641e0aa6bfbe81c7de80832f5a08e41db606b0c9111aa453</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4617923/pdf/$$EPDF$$P50$$Gpubmedcentral$$H</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4617923/$$EHTML$$P50$$Gpubmedcentral$$H</linktohtml><link.rule.ids>230,314,727,780,784,885,27924,27925,41488,42557,51319,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25952653$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Margolis, Karen L.</creatorcontrib><creatorcontrib>Asche, Stephen E.</creatorcontrib><creatorcontrib>Bergdall, Anna R.</creatorcontrib><creatorcontrib>Dehmer, Steven P.</creatorcontrib><creatorcontrib>Maciosek, Michael V.</creatorcontrib><creatorcontrib>Nyboer, Rachel A.</creatorcontrib><creatorcontrib>O’Connor, Patrick J.</creatorcontrib><creatorcontrib>Pawloski, Pamala A.</creatorcontrib><creatorcontrib>Sperl-Hillen, JoAnn M.</creatorcontrib><creatorcontrib>Trower, Nicole K.</creatorcontrib><creatorcontrib>Tucker, Ann D.</creatorcontrib><creatorcontrib>Green, Beverly B.</creatorcontrib><title>A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work?</title><title>Journal of general internal medicine : JGIM</title><addtitle>J GEN INTERN MED</addtitle><addtitle>J Gen Intern Med</addtitle><description>ABSTRACT
Background
It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others.
Objective
We conducted a mediation analysis to determine which of seven factors had the greatest effect on change in systolic blood pressure (BP) after 6 months in a trial to improve hypertension control.
Design
The study was a preplanned secondary analysis of a cluster-randomized clinical trial. Eight clinics in an integrated health system were randomized to provide usual care to their patients (
n
= 222), and eight were randomized to provide a telemonitoring intervention (
n
= 228).
Participants
Four hundred three of 450 trial participants completing the 6-month follow-up visit were included.
Interventions
Intervention group participants received home BP telemonitors and transmitted measurements to pharmacists, who adjusted medications and provided advice to improve adherence to medications and lifestyle modification via telephone visits.
Main measures
Path analytic models estimated indirect effects of the seven potential mediators of intervention effect (defined as the difference between the intervention and usual care groups in change in systolic BP from baseline to 6 months). The potential mediators were change in home BP monitor use, number of BP medication classes, adherence to BP medications, physical activity, salt intake, alcohol use, and weight.
Key Results
The difference in change in systolic BP was 11.3 mmHg. The multivariable mediation model explained 47 % (5.3 mmHg) of the intervention effect. Nearly all of this was mediated by two factors: an increase in medication treatment intensity (24 %) and increased home BP monitor use (19 %). The other five factors were not significant mediators, although medication adherence and salt intake improved more in the intervention group than in the usual care group.
Conclusions
Most of the explained intervention effect was attributable to the combination of self-monitoring and medication intensification. High adherence at baseline and the relatively low intensity of resources directed toward lifestyle change may explain why these factors did not contribute to the improvement in BP.</description><subject>Adhesion</subject><subject>Aged</subject><subject>Alcohol Drinking</subject><subject>Alcoholic beverages</subject><subject>Antihypertensive Agents - therapeutic use</subject><subject>Blood pressure</subject><subject>Blood Pressure - drug effects</subject><subject>Blood Pressure Monitoring, Ambulatory - methods</subject><subject>Case Management</subject><subject>Combined Modality Therapy</subject><subject>Drugs</subject><subject>Female</subject><subject>Health care</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hypertension - diagnosis</subject><subject>Hypertension - physiopathology</subject><subject>Hypertension - therapy</subject><subject>Internal Medicine</subject><subject>Intervention</subject><subject>Life Style</subject><subject>Male</subject><subject>Mathematical models</subject><subject>Mediation</subject><subject>Medication Adherence - statistics & numerical data</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Motor Activity</subject><subject>Occupational health</subject><subject>Original Research</subject><subject>Physical activity</subject><subject>Primary Health Care - methods</subject><subject>Salts</subject><subject>Secondary analysis</subject><subject>Sodium Chloride, Dietary - administration & dosage</subject><subject>Telemedicine</subject><subject>Telemedicine - methods</subject><subject>Treatment Outcome</subject><issn>0884-8734</issn><issn>1525-1497</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1UU1v1TAQtBCIvj74AVyQJS5cAl4nThwOoOpRaKUikCjq0do4m9YlL37YSdX373GUUj4kTnuY2dmZHcaegXgFQlSvI0ApykyAyvJcqez2AVuBkiqDoq4espXQush0lRcH7DDGayEgl1I_ZgdS1UqWKl8xPOJfJ2spxm7q-aepH12HlkZq-Xlw2PPR89PtLvgb4if7HYWRhuj8wDd-GIPvuRv4l-C2GPZ8g4He8IurPX_vWu5GfuHD93dP2KMO-0hP7-aafftwfL45yc4-fzzdHJ1lVhVizFA2dQuI0IEEAF2VBZBALJuuIQ22akkLnctOodBUQNuk6I2wdSIjFipfs7eL7m5qttRaSv6wN7vFnPHozN_I4K7Mpb8xRQlVLfMk8PJOIPgfE8XRbF201Pc4kJ-igUpWtdbzF9fsxT_Uaz-FIcUzcsa1ljA7goVlg48xUHdvBoSZCzRLgSYVaOYCzW3aef5nivuNX40lglwIMUHDJYXfp_-v-hNET6bX</recordid><startdate>20151101</startdate><enddate>20151101</enddate><creator>Margolis, Karen L.</creator><creator>Asche, Stephen E.</creator><creator>Bergdall, Anna R.</creator><creator>Dehmer, Steven P.</creator><creator>Maciosek, Michael V.</creator><creator>Nyboer, Rachel A.</creator><creator>O’Connor, Patrick J.</creator><creator>Pawloski, Pamala A.</creator><creator>Sperl-Hillen, JoAnn M.</creator><creator>Trower, Nicole K.</creator><creator>Tucker, Ann D.</creator><creator>Green, Beverly B.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7RV</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>8AO</scope><scope>8FD</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M0T</scope><scope>M1P</scope><scope>M2O</scope><scope>M7N</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20151101</creationdate><title>A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work?</title><author>Margolis, Karen L. ; Asche, Stephen E. ; Bergdall, Anna R. ; Dehmer, Steven P. ; Maciosek, Michael V. ; Nyboer, Rachel A. ; O’Connor, Patrick J. ; Pawloski, Pamala A. ; Sperl-Hillen, JoAnn M. ; Trower, Nicole K. ; Tucker, Ann D. ; Green, Beverly B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c540t-a2b9d1aa1f1211187641e0aa6bfbe81c7de80832f5a08e41db606b0c9111aa453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Adhesion</topic><topic>Aged</topic><topic>Alcohol Drinking</topic><topic>Alcoholic beverages</topic><topic>Antihypertensive Agents - therapeutic use</topic><topic>Blood pressure</topic><topic>Blood Pressure - drug effects</topic><topic>Blood Pressure Monitoring, Ambulatory - methods</topic><topic>Case Management</topic><topic>Combined Modality Therapy</topic><topic>Drugs</topic><topic>Female</topic><topic>Health care</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Hypertension - diagnosis</topic><topic>Hypertension - physiopathology</topic><topic>Hypertension - therapy</topic><topic>Internal Medicine</topic><topic>Intervention</topic><topic>Life Style</topic><topic>Male</topic><topic>Mathematical models</topic><topic>Mediation</topic><topic>Medication Adherence - statistics & numerical data</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Motor Activity</topic><topic>Occupational health</topic><topic>Original Research</topic><topic>Physical activity</topic><topic>Primary Health Care - methods</topic><topic>Salts</topic><topic>Secondary analysis</topic><topic>Sodium Chloride, Dietary - administration & dosage</topic><topic>Telemedicine</topic><topic>Telemedicine - methods</topic><topic>Treatment Outcome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Margolis, Karen L.</creatorcontrib><creatorcontrib>Asche, Stephen E.</creatorcontrib><creatorcontrib>Bergdall, Anna R.</creatorcontrib><creatorcontrib>Dehmer, Steven P.</creatorcontrib><creatorcontrib>Maciosek, Michael V.</creatorcontrib><creatorcontrib>Nyboer, Rachel A.</creatorcontrib><creatorcontrib>O’Connor, Patrick J.</creatorcontrib><creatorcontrib>Pawloski, Pamala A.</creatorcontrib><creatorcontrib>Sperl-Hillen, JoAnn M.</creatorcontrib><creatorcontrib>Trower, Nicole K.</creatorcontrib><creatorcontrib>Tucker, Ann D.</creatorcontrib><creatorcontrib>Green, Beverly B.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Nursing & Allied Health Database</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of general internal medicine : JGIM</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Margolis, Karen L.</au><au>Asche, Stephen E.</au><au>Bergdall, Anna R.</au><au>Dehmer, Steven P.</au><au>Maciosek, Michael V.</au><au>Nyboer, Rachel A.</au><au>O’Connor, Patrick J.</au><au>Pawloski, Pamala A.</au><au>Sperl-Hillen, JoAnn M.</au><au>Trower, Nicole K.</au><au>Tucker, Ann D.</au><au>Green, Beverly B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work?</atitle><jtitle>Journal of general internal medicine : JGIM</jtitle><stitle>J GEN INTERN MED</stitle><addtitle>J Gen Intern Med</addtitle><date>2015-11-01</date><risdate>2015</risdate><volume>30</volume><issue>11</issue><spage>1665</spage><epage>1672</epage><pages>1665-1672</pages><issn>0884-8734</issn><eissn>1525-1497</eissn><abstract>ABSTRACT
Background
It is important to understand which components of successful multifaceted interventions are responsible for study outcomes, since some components may be more important contributors to the intervention effect than others.
Objective
We conducted a mediation analysis to determine which of seven factors had the greatest effect on change in systolic blood pressure (BP) after 6 months in a trial to improve hypertension control.
Design
The study was a preplanned secondary analysis of a cluster-randomized clinical trial. Eight clinics in an integrated health system were randomized to provide usual care to their patients (
n
= 222), and eight were randomized to provide a telemonitoring intervention (
n
= 228).
Participants
Four hundred three of 450 trial participants completing the 6-month follow-up visit were included.
Interventions
Intervention group participants received home BP telemonitors and transmitted measurements to pharmacists, who adjusted medications and provided advice to improve adherence to medications and lifestyle modification via telephone visits.
Main measures
Path analytic models estimated indirect effects of the seven potential mediators of intervention effect (defined as the difference between the intervention and usual care groups in change in systolic BP from baseline to 6 months). The potential mediators were change in home BP monitor use, number of BP medication classes, adherence to BP medications, physical activity, salt intake, alcohol use, and weight.
Key Results
The difference in change in systolic BP was 11.3 mmHg. The multivariable mediation model explained 47 % (5.3 mmHg) of the intervention effect. Nearly all of this was mediated by two factors: an increase in medication treatment intensity (24 %) and increased home BP monitor use (19 %). The other five factors were not significant mediators, although medication adherence and salt intake improved more in the intervention group than in the usual care group.
Conclusions
Most of the explained intervention effect was attributable to the combination of self-monitoring and medication intensification. High adherence at baseline and the relatively low intensity of resources directed toward lifestyle change may explain why these factors did not contribute to the improvement in BP.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>25952653</pmid><doi>10.1007/s11606-015-3355-x</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Adhesion Aged Alcohol Drinking Alcoholic beverages Antihypertensive Agents - therapeutic use Blood pressure Blood Pressure - drug effects Blood Pressure Monitoring, Ambulatory - methods Case Management Combined Modality Therapy Drugs Female Health care Humans Hypertension Hypertension - diagnosis Hypertension - physiopathology Hypertension - therapy Internal Medicine Intervention Life Style Male Mathematical models Mediation Medication Adherence - statistics & numerical data Medicine Medicine & Public Health Middle Aged Motor Activity Occupational health Original Research Physical activity Primary Health Care - methods Salts Secondary analysis Sodium Chloride, Dietary - administration & dosage Telemedicine Telemedicine - methods Treatment Outcome |
title | A Successful Multifaceted Trial to Improve Hypertension Control in Primary Care: Why Did it Work? |
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