Clinicians’ Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Design and Participants
2.2. Study Questionnaire
2.3. Data Collection and Analyses
3. Results
3.1. Participant Characteristics and Exposure to Genetics and Cardiovascular Disease Screening
3.2. Genetics and Precision Medicine Knowledge
3.3. Perceptions toward Precision Medicine-Based CVD Risk Stratification
3.4. Confidence in Applying a Precision Medicine-Based CVD Risk Stratification Tool in Their Practice Settings
3.5. Factors Influencing Knowledge, Perceptions, and Confidence
3.6. Multivariable Analysis of the Factors Affecting Knowledge, Perceptions, and Confidence
3.7. Benefits and Concerns of a PM-Based CVD Risk Stratification
3.8. Clinician’s Expectations: Time Horizon, Funding, and Expected Role
3.9. Perceived Barriers to the Implementation of PM-Based CVD Risk Stratification
4. Discussion
4.1. Positive Perceptions of PM-Based Tools despite Knowledge Gaps and Resource Constraints
4.2. Addressing the Genetics Education Gap Is Paramount to Successful Adoption
4.3. Integrated Models Compatible with Current Clinical Practices Are Needed
4.4. Funding Shortfalls and Skills Shortages Hinder PM Adoption in Resource-Scarce Settings
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Section | Theme | No. of Items | Scale |
---|---|---|---|
1 | Demographic and professional | 10 | Not applicable |
information | |||
2 | Exposure: CVD risk stratification, and | 21 | Not applicable |
genetics training and testing | |||
3 | Knowledge: Genetics and PM, and | 15 | Understanding: None, Little, Some, Moderate, Expert |
educational video | Agreement: True, False, I do not know | ||
4 | Perception toward PM-based CVD risk stratification | 5 | Agreement: Strongly disagree, Disagree, Neutral, Agree, Strongly agree |
5 | Benefits and concerns of PM-based CVD risk stratification | 19 | Benefit/concern: Not, A little, Somewhat, Moderately, Very |
6 | Confidence in applying PM-based CVD risk stratification | 8 | Confidence: None, A little, Somewhat, Moderately, Very |
7 | Expectations in applying PM-based CVD risk stratification | 9 | Role: None, Supporting, Primary, Not sure |
Adoption likelihood: Very unlikely, Unlikely, No difference, Likely, Very likely | |||
8 | Barriers to implementing PM-based CVD risk stratification | 15 | Impact: None, Little, Some, Moderate, Strong |
Variable | Description | Type (Range) | Categories | |
---|---|---|---|---|
Outcome variables | ||||
Mean knowledge score (MKS) | Average self-reported knowledge relating to genetics and PM | Continuous (0–4) | Not applicable | |
Mean perception score (MPS) | Average self-reported perception relating to value of PM-based CVD risk stratification tool | Continuous (0–4) | Not applicable | |
Mean confidence score (MCS) | Average self-reported confidence relating to implementation of PM-based CVD risk stratification tool | Continuous (0–4) | Not applicable | |
Predictor variable | ||||
Sex | Reported sex | Categorical | Female | |
Male | ||||
Medical group | Practitioner type based on self-reported practice level and years of experience | Categorical | Consultant | |
Trainee | ||||
Clinical experience | Number of years conducting clinical duties | Categorical | <8 years | |
≥8 years | ||||
Postgraduate qualifications | Have a postgraduate qualification in addition to a medical degree | Categorical | Yes | |
No | ||||
Involvement in research | Are involved in medical research activities | Categorical | Yes | |
No | ||||
Genetics or PM training | Have training specifically relating to genetics and/or PM | Categorical | Yes | |
No | ||||
CVD stratification in clinical practice | Conducts CVD screening in their clinical practice | Categorical | Yes | |
Sometimes | ||||
No |
Variable | Detail | N (%) |
---|---|---|
Hospital affiliation | Chris Hani Baragwanath Academic Hospital | 23 (21.1) |
Charlotte Maxeke Johannesburg Academic Hospital | 36 (33.0) | |
Helen Joseph Hospital | 13 (11.9) | |
Rahima Moosa Mother and Child Hospital | 32 (29.4) | |
I prefer not to answer | 5 (4.6) | |
Medical specialty | Internal medicine | 21 (19.3) |
Non-internal medicine | 57 (52.3) | |
Not yet specialized (trainee) | 27 (24.8) | |
I prefer not to answer | 4 (3.7) | |
Sex | Female | 67 (61.5) |
Male | 42 (38.5) | |
Age | <33 years | 57 (51.4) |
≥33 years | 51 (46.8) | |
I prefer not to answer | 1 (0.9) | |
Medical group | Consultant | 82 (75.2) |
Trainee | 27 (24.8) | |
Clinical experience | <8 years | 55 (50.5) |
≥8 years | 50 (45.9) | |
Postgraduate qualifications | Yes | 66 (60.6) |
No | 41 (37.6) | |
I prefer not to answer | 2 (1.8) | |
Involvement in medical research | Yes | 59 (54.1) |
No | 50 (45.9) | |
CVD stratification in clinical practice | Yes | 41 (37.6) |
Sometimes | 31 (28.4) | |
No | 36 (33.0) | |
I prefer not to answer | 1 (0.9) | |
CVD stratification using a risk score | Yes | 25 (34.7) |
(n = 72) | Sometimes | 19 (26.4) |
No | 28 (38.9) | |
Genetics training | Yes | 17 (15.6) |
No | 91 (83.5) | |
I prefer not to answer | 1 (0.9) | |
Genetics testing in clinical practice | Yes | 31 (28.4) |
No | 78 (71.6) | |
Conditions genetics testing discussed * (n = 31) | Monogenic disorders | 30 (96.8) |
Cancers | 16 (51.6) | |
CVD | 6 (19.4) | |
Nutrigenomics | 1 (3.2) | |
Pharmacogenomics | 2 (6.5) | |
Genetic testing frequency (n = 31) | 1 patient every 2 to 3 months | 13 (41.9) |
1 patient per month | 2 (6.5) | |
2 to 5 patients per month | 6 (19.4) | |
6 to 10 patients per month | 2 (6.5) | |
11 to 20 patients per month | 3 (9.7) | |
20+ patients per month | 3 (9.7) | |
I prefer not to answer | 2 (6.5) |
Variable | Mean (SD) Knowledge Score (n = 107) | p Value | Mean (SD) Confidence Score (n = 104) | p Value | Mean (SD) Perception Score (n = 106) | p Value |
---|---|---|---|---|---|---|
Medical specialty | ||||||
Internal medicine | 1.67 (0.67) | 2.70 (0.94) | 2.95 (0.64) | 0.052 | ||
Non-internal medicine | 1.47 (0.62) | 0.310 | 2.12 (1.09) | 0.098 | 2.40 (0.98) | |
Not yet specialized | 1.66 (0.62) | 2.30 (0.92) | 2.58 (0.85) | |||
Sex | ||||||
Female | 1.59 (0.67) | 0.682 | 2.41 (0.98) | 0.404 | 2.45 (1.11) | 0.632 |
Male | 1.54 (0.61) | 2.26 (1.08) | 2.64 (0.74) | |||
Medical group | ||||||
Clinician | 1.52 (0.64) | 0.318 | 2.26 (1.08) | 0.933 | 2.54 (0.93) | 0.969 |
Trainee | 1.66 (0.62) | 2.30 (0.92) | 2.58 (0.85) | |||
Practice level | ||||||
Specialist | 1.61 (0.66) | 0.470 | 2.25 (1.27) | 0.897 | 2.48 (0.90) | 0.526 |
Registrar | 1.41 (0.65) | 2.32 (0.81) | 2.71 (1.05) | |||
Medical officer | 1.48 (0.53) | 2.56 (0.86) | 2.60 (0.82) | |||
Intern | 1.66 (0.62) | 2.30 (0.92) | 2.58 (0.85) | |||
Clinical experience | ||||||
<8 years | 1.59 (0.60) | 0.580 | 2.32 (0.84) | 0.651 | 2.59 (0.86) | 0.945 |
≥8 years | 1.53 (0.67) | 2.31 (1.23) | 2.55 (0.95) | |||
Postgrad. qualifications | ||||||
Yes | 1.62 (0.68) | 0.195 | 2.32 (1.17) | 0.490 | 2.62 (0.890) | 0.317 |
No | 1.45 (0.53) | 2.27 (0.78) | 2.48 (0.93) | |||
Medical research involvement | ||||||
Yes | 1.71 (0.61) | 0.007 ** | 2.57 (0.96) | 0.007 ** | 2.69 (0.87) | 0.249 |
No | 1.38 (0.61) | 2.01 (1.06) | 2.43 (0.92) | |||
Genetics training | ||||||
Yes | 2.26 (0.62) | 3.518 × 10−5 *** | 2.46 (0.86) | 0.720 | 2.96 (0.61) | 0.146 |
No | 1.42 (0.54) | 2.29 (1.17) | 2.50 (0.93) | |||
CVD screening | ||||||
Yes | 1.75 (0.59) | 0.074 | 2.65 (1.10) | 0.010 * | 2.89 (0.63) | 4.162 × 10−4 *** |
No | 1.46 (0.63) | 1.93 (0.96) | 2.11 (1.03) | |||
Sometimes | 1.45 (0.65) | 2.33 (0.94) | 2.65 (0.88) |
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Kamp, M.; Pain, O.; May, A.; Lewis, C.M.; Ramsay, M. Clinicians’ Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa. J. Pers. Med. 2022, 12, 1360. https://doi.org/10.3390/jpm12091360
Kamp M, Pain O, May A, Lewis CM, Ramsay M. Clinicians’ Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa. Journal of Personalized Medicine. 2022; 12(9):1360. https://doi.org/10.3390/jpm12091360
Chicago/Turabian StyleKamp, Michelle, Oliver Pain, Andrew May, Cathryn M. Lewis, and Michèle Ramsay. 2022. "Clinicians’ Perceptions towards Precision Medicine Tools for Cardiovascular Disease Risk Stratification in South Africa" Journal of Personalized Medicine 12, no. 9: 1360. https://doi.org/10.3390/jpm12091360