| Literature DB >> 36005177 |
Marco Cascella1, Sergio Coluccia2, Mariacinzia Grizzuti1, Maria Cristina Romano1, Gennaro Esposito1, Anna Crispo2, Arturo Cuomo1.
Abstract
BACKGROUND: Since cancer pain requires complex modalities of care, the proper strategy for addressing its telemedicine-based management should be better defined. This study aimed to trace a pathway for a progressive implementation of the telemedicine process for the treatment of pain in the setting of cancer patients.Entities:
Keywords: cancer pain; patient satisfaction; protocol; telemedicine; workflow
Mesh:
Year: 2022 PMID: 36005177 PMCID: PMC9406413 DOI: 10.3390/curroncol29080439
Source DB: PubMed Journal: Curr Oncol ISSN: 1198-0052 Impact factor: 3.109
Inclusion criteria for remote pain management.
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Cancer patients aged ≥ 18 years |
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No restriction for cancer disease |
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Availability of the necessary equipment for the video consultation (smartphone or laptop with webcam) |
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Ability to use the platform |
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Availability of a caregiver for patients with poor health status or those unfamiliar with the technology |
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Consent provided |
The adopted 22-item questionnaire.
| 1 | Telehealth improves my access to healthcare services. |
| 2 | Telehealth saves me time traveling to a hospital or specialist clinic. |
| 3 | Telehealth provides for my healthcare need. |
| 4 | It was simple to use this system. |
| 5 | It was easy to learn to use the system. |
| 6 | I believe I could become productive quickly using this system. |
| 7 | The way I interact with this system is pleasant. |
| 8 | I like using the system. |
| 9 | The system is simple and easy to understand. |
| 10 | This system is able to do everything I would want it to be able to do. |
| 11 | I can easily talk to the clinician using the telehealth system. |
| 12 | I can hear the clinician clearly using the telehealth system. |
| 13 | I felt I was able to express myself effectively. |
| 14 | Using the telehealth system, I can see the clinician as well as if we met in person. |
| 15 | I think the visits provided over the telehealth system are the same as in-person visits. |
| 16 | Whenever I made a mistake using the system, I could recover easily and quickly. |
| 17 | The system gave error messages that clearly told me how to fix problems. |
| 18 | I believe that my privacy is protected. |
| 19 | I believe that telemedicine allows for more frequent monitoring of my health conditions. |
| 20 | I feel actively involved in any healthcare decision. |
| 21 | I am satisfied with the doctor–patient communication. |
| 22 | I can easily express the features of my pain through telemedicine. |
Note: The questions were answered using a 7-point Likert scale (i.e., from “strongly disagree” = 1, to “strongly agree” = 7). Questions 1–17 from the Telehealth Usability Questionnaire (TUQ) [9]. The other questions were designed by following the BRUSCO strategy [10].
Figure 1Model of care and the study flowchart. The model of care is designed through the structuring of the platform and the training of the operators. The first visit is carried out in person. It allows for collecting consent, clinical evaluation, and patient training. After the remote visit, follow-ups are scheduled. They can be delivered through telemedicine, but readmission to the clinic is provided. The satisfaction questionnaire is administered via telephone after the first remote visit. The answers and the descriptive analysis serve as feedback to improve the whole process. The collected data on 388 remote visits can be used for clinical investigations and the development of ad hoc predictive models.
Univariate analysis.
| Dropout | ||||
|---|---|---|---|---|
| Variable | Overall, | No, | Yes, | |
|
| 0.2 | |||
| Mean (SD) | 64 (12) | 64 (12) | 57 (16) | |
| Median (IQR) | 66 (55, 73) | 66 (57, 73) | 52 (44, 72) | |
|
| 0.15 | |||
| F | 48 (100%) | 46 (96%) | 2 (4.2%) | |
| M | 44 (100%) | 38 (86%) | 6 (14%) | |
|
| 0.6 | |||
| Other cancers | 40 (100%) | 36 (90%) | 4 (10%) | |
| Colon | 26 (100%) | 23 (88%) | 3 (12%) | |
| Breast | 15 (100%) | 15 (100%) | 0 (0%) | |
| Lung | 11 (100%) | 10 (91%) | 1 (9.1%) | |
|
| 0.15 | |||
| No | 48 (100%) | 46 (96%) | 2 (4.2%) | |
| Yes | 44 (100%) | 38 (86%) | 6 (14%) | |
|
| >0.9 | |||
| ECOG < 3 | 49 (100%) | 45 (92%) | 4 (8.2%) | |
| ECOG = 3 | 43 (100%) | 39 (91%) | 4 (9.3%) | |
| 0.032 | ||||
|
| 92 | 84 | 8 | |
| Mean (SD) | 2.4 (2) | 2.2 (1.9) | 4.1 (2.9) | |
|
| >0.9 | |||
| ≤60 | 40 (100%) | 37 (92%) | 3 (7.5%) | |
| >60 | 52 (100%) | 47 (90%) | 5 (9.6%) | |
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| 0.4 | |||
| No | 87 (100%) | 80 (92%) | 7 (8.0%) | |
| Yes | 5 (100%) | 4 (80%) | 1 (20%) | |
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| 0.074 | |||
| No | 52 (57%) | 50 (60%) | 2 (25%) | |
| Yes | 40 (43%) | 34 (40%) | 6 (75%) | |
† n (%); ‡ Wilcoxon rank-sum test; Fisher’s exact test. Abbreviations: ECOG-PS, Eastern Cooperative Oncology Group Performance Status; MED, morphine equivalent dose; IV-Morphine, intravenous morphine; NP, neuropathic pain.
Multivariate analysis.
| Characteristic | OR | 95% CI | |
|---|---|---|---|
| Age | 0.94 | 0.87, 1.01 | 0.10 |
| Gender | |||
| F | - | - | |
| M | 6.36 | 0.99, 60.9 | 0.068 |
| Metastatic status | |||
| No | - | - | |
| Yes | 4.92 | 0.81, 51.1 | 0.12 |
| NP Drugs | |||
| No | - | - | |
| Yes | 7.68 | 1.25, 75.5 | 0.043 |
| Televisits ( | 1.33 | 0.98, 1.84 | 0.062 |
Multivariate logistic regression: formula: logit (p (Dropout = T|X)) ~ Age + Gender + Metastatic status + NP Drugs + televisits. Abbreviations: OR, odds ratio; CI, confidence interval; NP, neuropathic pain.
Figure 2Probability of in-person visit. The probability of dropout (p) increased as the number of visits increased and especially in male patients who were treated with drugs for neuropathic pain (e.g., anticonvulsants and antidepressants). Abbreviations: NP, neuropathic pain.
Figure 3Patient satisfaction questionnaire (items 1–12). The questions were answered using a 7-point Likert scale (i.e., from “strongly disagree” = 1, to “strongly agree” = 7). The dashed lines indicate the mean values.
Figure 4Patient satisfaction questionnaire (items 13–22). The questions were answered using a 7-point Likert scale (i.e., from “strongly disagree” = 1, to “strongly agree” = 7). The dashed lines indicate the mean values. The figure also reports the number of video consultations for a patient and the mean values for each item.