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Tables
Responses, n Mean+standard error Standard deviation Range (min–max) Age 147 46.03+1.145 13.883 57 (26–83) Sex 146 65.4% female 1 (1–2) City size 146 4.11+.133 1.611 5 (1–6) 0-999 inhabitants 2.7% 1000-4999 inhabitants 17.60% 5000-19999 inhabitants 21.60% 20 000-99 999 inhabitants 15.50% 100 000-299 999 inhabitants 10.10% ≥300 000 inhabitants 32.40% Years of practice 152 15.839+1.08 13.352 57.5 (0.5–58) Own practice 99 64.70% 1 (1–2) Years of own practice 99 15.116+1.013 10.075 39 (1–40) Number of patients in own practice 99 1901.4+61.419 608.017 3910(990–4900) ICT use in general practice (aggregated) 153 2.98+0.152 1.879 6 (0–6) Number of ICT devices owned by GP 147 3.30+0087 1.05 4 (2–6) Self-reported ICT skill 147 3.69+0.076 0.926 4 (1–5) Professional burnout syndrome 147 16.02+0.257 3.117 20 (5–25) eHealth readiness 142 26.05+0.623 7.42 32 (10–42) - Table 2. Descriptive characteristics of eHealth usage by responding Czech GPs (n = 153; 2017–2018)
ICT used Frequency, % Owned technology TV 23.5 Wi-Fi 24.2 Camera/e-evidence of patients 5.9 Tablet 1.3 Communication with patients Telephone 98.7 SMS 41.8 Email 73.2 Sharing results of laboratory assessments Patient calls the practice 96.1 The practice calls the patient 73.2 Results sent via SMS 18.3 Results sent via email 48.4 Results sent via web-portal 3.3 Results sent via post-office (hard copies) 11.8 Using mobile technologies in general practice ‘It seems useful…’ 62.1 for making appointments 76.5 for sending results of assessments 65.4 for monitoring patients’ health outcomes 30.7 for answering patients’ questions 48.4 for monitoring of medication 35.3 for motivating patients towards a more healthy lifestyle 29.4 for showing care and interest in patients’ health problems 28.8 for monitoring and feedback about health status (e.g. blood pressure) 41.8 GPs´ with their own practice (n = 99) public internet profile Own website 53.5 Planning to have website 9.1 Social media 14.1 Planning to have social media 3.0 Setting up appointments Personal communication 76.8 Telephone 87.9 Email 51.5 SMS 17.2 Web-portal 13.1 No ICT: served on first-come-first-served basis 51.5 - Table 3. Results of bivariate correlation coefficients among responding Czech GPs (n = 153; 2017–2018)
1 2 3 4 5 6 7 8 9 10 1. Age – -0.023 0.924a 0.053 0.003 -0.306a -0.310 0.036 -0.229a 0.052 2. City size 0.220b – -0.045 -0.131 0.010 -0.095 -0.061 -0.033 0.029 0.154 3. Years of practice 0.905a -0.045 – 0.069 -0.008 -0.320a -0.291a 0.122 -0.206b 0.019 4. Practice size 0.053 -0.131 0.069 – NA NA NA NA NA NA 5. Burnout 0.122 -0.023 0.097 -0.023 – 0.051 0.042 -0.006 0.005 -0.071 6. eHealth readiness -0.256b -0.198 -0.300a 0.342a 0.079 – 0.428a 0.263a 0.406a -0.176b 7. ICT skill -0.278a -0.129 -0.260a 0.225 -0.076 0.418a – 0.373b 0.155 -0.092 8. Number of owned ICT devices -0.030 0.010 -0.049 0.343a 0.038 0.326a 0.360a – 0.189b 0.017 9. ICT usage in general practice -0.370a -0.105 -0.358a 0.342a -0.028 0.522a 0.257b 0.290a – -0.048 10. Interest in mHealth usage -0.036 0.191 -0.005 -0.208b -0.184 -0.165 -0.064 -0.031 -0.092 – a P<0.01. b P<0.05. Correlations above the diagonal refer to associations in the entire sample. Correlations below the diagonal refer to associations observed in GPs who own their practice.
- Table 4. Results of hierarchical multilinear regression estimating the association between ICT usage in general practice and its predictors among responding GPs (n = 153; 2017–2018)
Model R2 change β Standard error Critical value Significance 1 Age 0.050 -0.224 0.011 -2.662 0.009 Sex 0.021 -0.144 0.340 -1.654 0.100 City size 0.004 0.061 0.098 0.712 0.478 Burnout 0.004 0.061 0.051 0.730 0.467 0.066 F (4,135) 2.397 0.053 2 Age 0.020 -0.143 0.012 -1.651 0.101 Sex 0.009 -0.097 0.324 -1.166 0.246 City size 0.007 0.085 0.092 1.052 0.295 Burnout 0.002 0.047 0.048 0.602 0.548 Digital skills 0.014 -0.118 0.185 -1.259 0.210 Digital devices 0.011 0.105 0.151 1.209 0.229 eHealth readiness 0.145 0.381 0.022 4.268 0.000 0.134 F (3,132) 7.400 0.000 - Table 5. Results of hierarchical multilinear regression estimating the association between ICT usage in general practice and its predictors among responding GPs with their own practice (n = 99; 2017–2018)
Model R2 change β Standard error Critical value Significance 1 Age 0.172 -0.415 0.013 -4.455 0.000 Sex 0.026 -0.161 0.336 -1.685 0.096 City size 0.006 0.080 0.105 0.812 0.419 Practice size 0.138 0.372 0.000 4.064 0.000 Burnout 0.003 0.055 0.050 0.603 0.548 0.305 F (5,86) 7.556 0.000 2 Age 0.107 -0.328 0.013 -3.473 0.001 Sex 0.008 -0.090 0.328 -0.970 0.335 City size 0.006 0.079 0.100 0.841 0.403 Practice size 0.052 0.227 0.000 2.357 0.021 Burnout 0.000 0.021 0.047 0.243 0.809 Digital skills 0.003 -0.058 0.185 -0.582 0.562 Digital devices 0.010 0.099 0.158 1.014 0.314 eHealth readiness 0.118 0.343 0.023 3.310 0.001 0.098 F (3,83) 4.568 0.005
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GPs’ perspectives on eHealth use in the Czech Republic: a cross-sectional mixed-design survey study
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