| Literature DB >> 31615433 |
Ni Wang1, Hui Zhang1, Yang Zhou2, Hui Jiang3, Bing Dai3, Miaomiao Sun4, Ying Li1, Amelia Kinter5, Fei Huang6.
Abstract
BACKGROUND: In settings such as China, where universal implementation of directly observed therapy (DOT) is not feasible, innovative approaches are needed to support patient adherence to TB treatment. The electronic medication monitor (EMM) is one of the digital technologies recommended by the World Health Organization (WHO), but evidence from implementation studies remains sparse. In this study, we evaluated acceptance of the EMM among health care workers and patients while implementing the device for differential TB patient management at the community level.Entities:
Keywords: China; Electronic medication monitor; Patient management; Tuberculosis
Year: 2019 PMID: 31615433 PMCID: PMC6794727 DOI: 10.1186/s12879-019-4521-2
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Flow chart depicting study enrollment and the outcome of using the EMM in the study city
Factors associated with refusing to use the EMM among eligible TB patients in the study city (n = 231)
| Factors | Total | Refused to use EMM | OR | (95% CI) | aORf | (95% CI) | ||
|---|---|---|---|---|---|---|---|---|
| n | (%)a | n | (%)b | |||||
| Sex | ||||||||
| Male | 164 | 71.0 | 18 | 11.0 | ref | ref | ||
| Female | 67 | 29.0 | 8 | 11.9 | 1.1 | 0.5–2.7 | 1.3 | 0.5–3.3 |
| Agec | ||||||||
| < 44 | 54 | 23.4 | 4 | 7.4 | ref | ref | ||
| 45–64 | 82 | 35.5 | 8 | 9.8 | 1.6 | 0.6–4.0 | 1.5 | 0.6–3.9 |
| > =65 | 95 | 41.1 | 14 | 14.7 | 2.2 | 0.7–6.9 | 1.7 | 0.5–6.1 |
| Occupation | ||||||||
| Farmer/migrant worker | 142 | 61.5 | 17 | 12.0 | 1.2 | 0.5–2.8 | 1.2 | 0.5–3.0 |
| Other | 89 | 38.5 | 9 | 10.1 | ref | ref | ||
| Migrantd | ||||||||
| No | 160 | 69.3 | 18 | 11.3 | ref | ref | ||
| Yes | 71 | 30.7 | 8 | 11.3 | 1.0 | 0.4–2.4 | 1.6 | 0.5–2.9 |
| Category | ||||||||
| New | 206 | 89.2 | 22 | 10.7 | ref | ref | ||
| Retreated | 25 | 10.8 | 4 | 16.0 | 1.6 | 0.5–5.1 | 1.0 | 0.3–3.5 |
| Classification | ||||||||
| Bacteriologically confirmed | 115 | 49.8 | 20 | 17.4 | 3.9e | 1.5–10.0 | 3.7e | 1.4–9.8 |
| Clinically diagnosed | 116 | 50.2 | 6 | 5.2 | ref | ref | ||
TB Tuberculosis, EMM Electronic medication monitor, OR Odds ratio, aOR Adjusted odds ratio, CI Confidence interval
aColumn percentages
bRow percentages
cOnly one patient was under 15 years old, so < 15 group was merged into < 44 group
dMigrant defined as patient coming from another county
eStatistically significant
fEven though some variables didn’t show statistical significance in univariate analysis, considering the important influence of patient’s background and diagnosis in the treatment management, we included all the variables in the multivariable analysis
Factors associated with TB patients who were switched to DOT due to non-adherence in the study city (n = 169)
| Factors | Total | Switched to DOT | OR | (95% CI) | aORf | (95% CI) | ||
|---|---|---|---|---|---|---|---|---|
| n | (%)a | n | (%)b | |||||
| Sex | ||||||||
| Male | 123 | 72.8 | 9 | 7.3 | ref | ref | ||
| Female | 46 | 27.2 | 6 | 13.0 | 1.9 | 0.6–5.7 | 1.9 | 0.5–7.0 |
| Agec | ||||||||
| < 44 | 44 | 26.0 | 7 | 15.9 | 2.6 | 0.7–9.5 | 1.9 | 0.4–9.7 |
| 45–64 | 66 | 39.1 | 4 | 6.1 | 0.9 | 0.2–3.7 | 0.9 | 0.2–4.3 |
| > =65 | 59 | 34.9 | 4 | 6.8 | ref | ref | ||
| Occupation | ||||||||
| Farmer/Migrant worker | 100 | 59.2 | 4 | 4.0 | ref | ref | ||
| Other | 69 | 40.8 | 11 | 15.9 | 4.6e | 1.4–15.0 | 4.2e | 1.1–15.4 |
| Migrantd | ||||||||
| No | 119 | 70.4 | 4 | 3.4 | ref | ref | ||
| Yes | 50 | 29.6 | 11 | 22.0 | 8.1e | 2.4–26.9 | 8.4e | 2.3–30.6 |
| Category | ||||||||
| New | 151 | 89.3 | 12 | 7.9 | ref | ref | ||
| Retreated | 18 | 10.7 | 3 | 16.7 | 2.3 | 0.6–9.1 | 7.6e | 1.1–51.0 |
| Classification | ||||||||
| Bacteriologically confirmed | 75 | 55.6 | 6 | 8.0 | ref | ref | ||
| Clinically diagnosed | 94 | 44.4 | 9 | 9.6 | 1.2 | 0.4–3.6 | 1.4 | 0.4–5.3 |
TB Tuberculosis, DOT Directly observed therapy, OR Odds ratio, aOR Adjusted odds ratio, CI Confidence interval
aColumn percentages
bRow percentages
cOnly one patient was under 15 years old, so < 15 group was merged into < 44 group
dMigrant defined as patient coming from another county
eStatistically significant
fEven though some variables didn’t show statistical significance in univariate analysis, considering the important influence of patient’s background and diagnosis in the treatment management, we included all the variables in the multivariable analysis
Results from the structured questionnaire survey with participating physicians and nurses in the study city
| Question | Number of nurses who agreed ( | Number of physicians who agreed ( | Total |
|---|---|---|---|
| EMM was useful to patients | 5 | 4 | 9 |
| EMM was useful to physicians | 5 | 4 | 9 |
| Operation was acceptable | 5 | N/A | 5 |
| Workload increased while using the EMM | 4 | 4 | 8 |
| Increased workload was moderate | 3 | 4 | 7 |
EMM Electronic medication monitor, N/A Not applicable
Differences in the workload of community physicians when using DOT management or EMM management in the study city (n = 205)
| Category | DOT management | EMM management | Reduction (%)a | |||||
|---|---|---|---|---|---|---|---|---|
| n | Visits | EMM use only | Switched to DOT midway | Total visits | ||||
| n | Visits | n | Visits | |||||
| New | 184 | 33,120 | 155 | 1550 | 29 | 2205 | 3755 | 88.7 |
| Retreated | 21 | 5040 | 16 | 192 | 5 | 657 | 849 | 83.2 |
| Total | 205 | 38,160 | 171 | 1742 | 34 | 2862 | 4604 | 87.9 |
DOT Directly observed therapy, EMM Electronic medication monitor
aReduction between DOT management visits and EMM management total visits