Software-driven chronic disease management: Algorithm design and implementation in a community-based blood pressure control pilot
Background: Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workf...
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| Veröffentlicht in: | SAGE open medicine Jg. 12; S. 20503121241284025 |
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London, England
SAGE Publications
01.01.2024
Sage Publications Ltd SAGE Publishing |
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| Abstract | Background:
Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach.
Methods:
We describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks.
Results:
A total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130–139 mmHg or DBP 80–89 mmHg), 69% Stage 2 (SBP 140–179 mmHg or DBP 90–119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program).
Conclusion:
Software-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions. |
|---|---|
| AbstractList | Background:
Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach.
Methods:
We describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks.
Results:
A total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130–139 mmHg or DBP 80–89 mmHg), 69% Stage 2 (SBP 140–179 mmHg or DBP 90–119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program).
Conclusion:
Software-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions. Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach.BackgroundOptimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach.We describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks.MethodsWe describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks.A total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130-139 mmHg or DBP 80-89 mmHg), 69% Stage 2 (SBP 140-179 mmHg or DBP 90-119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program).ResultsA total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130-139 mmHg or DBP 80-89 mmHg), 69% Stage 2 (SBP 140-179 mmHg or DBP 90-119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program).Software-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions.ConclusionSoftware-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions. Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach. We describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks. A total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130-139 mmHg or DBP 80-89 mmHg), 69% Stage 2 (SBP 140-179 mmHg or DBP 90-119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program). Software-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions. Background: Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer results in under-resourced communities. Technology, including artificial intelligence-driven decision support and software-driven workflow transformation, can potentially improve disease outcomes at a reduced cost, although it must be integrated with a holistic approach. Methods: We describe the design of a software platform that enables rapid iterative remote management of >20 conditions across cardiac-kidney-metabolic disease. The platform distributes work across a care team of providers and care navigators, automates decision-making, ordering, and documentation, supports rapid incorporation of new evidence, and launches pragmatic trials. We describe software used in a 500-person community-based blood pressure control implemented as a single-arm quality improvement program. The primary endpoint was the proportion of patients meeting the Healthcare Effectiveness Data and Information Set quality measure blood pressure goal (<140/90) at 12 weeks. Results: A total of 1609 patients were screened, 945 (59%) were found to have uncontrolled hypertension, and 512 patients consented to join the program. The average age was 61 ± 11 years; 59% were female, and 99% self-identified as Black. Blood pressure distribution was: 10% Stage 1 (SBP 130–139 mmHg or DBP 80–89 mmHg), 69% Stage 2 (SBP 140–179 mmHg or DBP 90–119 mmHg), and 21% Stage 3 (SBP >180 mmHg or DBP >120 mmHg). Two hundred four patients (39%) proceeded to a provider encounter, and 160 of these (78%) completed the program. The Healthcare Effectiveness Data and Information Set blood pressure goal was achieved in <12 weeks of enrollment for 141 participants (69% of those enrolled, 88% of those who completed the program). Conclusion: Software-driven remote blood pressure is feasible, although strategies to improve patient enrollment will be needed to achieve maximum impact. Future work will be required to compare outcomes to usual care and evaluate concurrent management of multiple cardiac-kidney-metabolic conditions. |
| Author | Sheffield, Horace Deo, Rahul C MacRae, Calum A Price, Esha Patel, Rahul Smith, Rebecca |
| AuthorAffiliation | 3 Detroit Association of Black Organizations, Detroit, MI, USA 1 Atman Health, Needham, MA, USA 2 Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39494161$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1161/CIRCULATIONAHA.123.065469 10.1371/journal.pone.0272883 10.1136/amiajnl-2013-001813 10.1001/jamacardio.2020.0640 10.2147/IJGM.S333501 10.1007/s11606-011-1799-1 10.1161/HYPERTENSIONAHA.120.16418 10.1161/CIRCULATIONAHA.120.051913 10.1001/jama.2024.6609 10.1001/jama.2020.14545 10.1001/jamacardio.2020.3757 10.1161/CIR.0000000000001184 |
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| Keywords | value-based care automation software quality measures Health equity guideline-directed medical therapy hypertension artificial intelligence |
| Language | English |
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| Snippet | Background:
Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with... Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with poorer... Background: Optimal guideline-directed medical therapy is rarely attained in practice, resulting in inadequate control of diseases such as hypertension, with... |
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| StartPage | 20503121241284025 |
| SubjectTerms | Blood pressure Disease Hypertension Metabolism Original Pressure distribution Software |
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| Title | Software-driven chronic disease management: Algorithm design and implementation in a community-based blood pressure control pilot |
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