Sociodemographic and clinical correlates of key outcomes from a Mobile Insulin Titration Intervention (MITI) for medically underserved patients
Copyright © 2018 Elsevier B.V. All rights reserved..
BACKGROUND: Insulin titration is typically done face-to-face with a clinician; however, this can be a burden for patients due to logistical issues associated with in-person clinical care. The Mobile Insulin Titration Intervention (MITI) used basic cell phone technology including text messages and phone calls to help patients with diabetes find their optimal basal insulin dose (OID).
OBJECTIVE: To evaluate sociodemographic and clinical correlates of reaching OID, text message response rate, and days needed to reach OID.
METHODS: Primary care providers referred patients to MITI and nurses delivered the program. Three multivariable regression models quantified relationships between various correlates and primary outcomes.
RESULTS: The sample included 113 patients from 2 ambulatory clinics, with a mean age of 50 years (SD = 10), 45% female, 79% Hispanic, 43% unemployed, and 46% uninsured. In regression models, baseline fasting blood glucose (FBG) was negatively associated with odds of reaching OID and 100% text responses, and positively associated with days to reach OID, p < .05).
CONCLUSIONS: Patients with higher baseline FBG levels were less successful across outcomes and may need additional supports in future mHealth diabetes programs.
PRACTICAL IMPLICATIONS: Basic cell phone technology can be used to adjust patients' insulin remotely, thereby reducing logistical barriers to care.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2019 |
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| Erschienen: |
2019 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:102 |
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| Enthalten in: |
Patient education and counseling - 102(2019), 3 vom: 30. März, Seite 520-527 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Langford, Aisha T [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 05.09.2019 Date Revised 06.09.2019 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.pec.2018.09.016 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM289292670 |
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| 100 | 1 | |a Langford, Aisha T |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Sociodemographic and clinical correlates of key outcomes from a Mobile Insulin Titration Intervention (MITI) for medically underserved patients |
| 264 | 1 | |c 2019 | |
| 336 | |a Text |b txt |2 rdacontent | ||
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| 500 | |a Date Completed 05.09.2019 | ||
| 500 | |a Date Revised 06.09.2019 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2018 Elsevier B.V. All rights reserved. | ||
| 520 | |a BACKGROUND: Insulin titration is typically done face-to-face with a clinician; however, this can be a burden for patients due to logistical issues associated with in-person clinical care. The Mobile Insulin Titration Intervention (MITI) used basic cell phone technology including text messages and phone calls to help patients with diabetes find their optimal basal insulin dose (OID) | ||
| 520 | |a OBJECTIVE: To evaluate sociodemographic and clinical correlates of reaching OID, text message response rate, and days needed to reach OID | ||
| 520 | |a METHODS: Primary care providers referred patients to MITI and nurses delivered the program. Three multivariable regression models quantified relationships between various correlates and primary outcomes | ||
| 520 | |a RESULTS: The sample included 113 patients from 2 ambulatory clinics, with a mean age of 50 years (SD = 10), 45% female, 79% Hispanic, 43% unemployed, and 46% uninsured. In regression models, baseline fasting blood glucose (FBG) was negatively associated with odds of reaching OID and 100% text responses, and positively associated with days to reach OID, p < .05) | ||
| 520 | |a CONCLUSIONS: Patients with higher baseline FBG levels were less successful across outcomes and may need additional supports in future mHealth diabetes programs | ||
| 520 | |a PRACTICAL IMPLICATIONS: Basic cell phone technology can be used to adjust patients' insulin remotely, thereby reducing logistical barriers to care | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, Non-U.S. Gov't | |
| 650 | 4 | |a Blood glucose | |
| 650 | 4 | |a Cell phone | |
| 650 | 4 | |a Diabetes mellitus | |
| 650 | 4 | |a Humans | |
| 650 | 4 | |a Insulin | |
| 650 | 4 | |a Medically uninsured | |
| 650 | 4 | |a Primary health care | |
| 650 | 4 | |a Telemedicine | |
| 650 | 4 | |a Text messaging | |
| 650 | 4 | |a Vulnerable populations | |
| 650 | 4 | |a mHealth | |
| 650 | 7 | |a Blood Glucose |2 NLM | |
| 650 | 7 | |a Hypoglycemic Agents |2 NLM | |
| 650 | 7 | |a Insulin |2 NLM | |
| 700 | 1 | |a Wang, Binhuan |e verfasserin |4 aut | |
| 700 | 1 | |a Orzeck-Byrnes, Natasha A |e verfasserin |4 aut | |
| 700 | 1 | |a Aidasani, Sneha R |e verfasserin |4 aut | |
| 700 | 1 | |a Hu, Lu |e verfasserin |4 aut | |
| 700 | 1 | |a Applegate, Melanie |e verfasserin |4 aut | |
| 700 | 1 | |a Moloney, Dana N |e verfasserin |4 aut | |
| 700 | 1 | |a Sevick, Mary Ann |e verfasserin |4 aut | |
| 700 | 1 | |a Rogers, Erin S |e verfasserin |4 aut | |
| 700 | 1 | |a Levy, Natalie K |e verfasserin |4 aut | |
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