For the majority of ambulatory skin conditions encountered in Primary Care and Dermatology Clinics the impact those conditions have on patients' quality of life is of principal importance. Commonly encountered skin diseases frequently result in discomfort or pain, pruritis, emotional concerns, embarrassment, anxiety, and interfere with activities of daily living, work activities, or interpersonal relations. To date no data exists that compares quality of life outcomes, the fundamental metric to assess in an ambulatory dermatology population, between patients undergoing store and forward teledermatology consultations with patients managed by the conventional consult process. As telemedicine becomes an increasingly common means of delivering health care in the VA, it is important to examine the effect telemedicine has on health care delivery.
The purpose of this study was to compare store and forward teledermatology with a conventional clinic-based dermatology consultation process. Our primary objective was to determine whether the mean change in patient quality of life, as rated by the composite score and subscale scores of a skin-specific quality of life index (Skindex-16), differed between the time of randomization and 9 months for patients evaluated by store and forward teledermatology compared to conventional consult methods. Secondary objectives included (a) assessing quality of life between time of randomization and 3 months, (b) assessing time to initial definitive evaluation for patients using each modality, (c) evaluating clinical course using serial digital imaging, (d) comparing the costs and cost-effectiveness of store and forward teledermatology with conventional consult methods.
The study was a parallel-group, superiority, randomized clinical trial that compared store and forward teledermatology with a conventional clinic-based consult process. Patients were randomized using a simple randomization scheme stratified by site to one of the two consult modalities. Eligible patients included those being referred from the remote sites of primary care to the medical center-based sites of dermatology services. The sample size estimate was based on detecting a mean absolute difference of 10 points in the change score for Skindex-16 between baseline and 9 months. The study was powered at 90% with an alpha of 0.5% (two tailed) which required 190 subjects per enrollment group. Skindex-16 was administered at baseline, 3 months, and 9 months. Time to initial definitive evaluation, calculated based on the need for and timing of a clinic-based visit was measured for both groups. Using digital images, clinical course was assessed on a 5 point scale by an expert panel of three dermatologists. Categories included resolved, improved, unchanged not clinically relevant, unchanged clinically relevant, and worse. Health care utilities were measured using time trade-off data and the Health Utilities Index Mark 2 (HUI2). We compared the costs of teledermatology with conventional consult methods by estimating the average cost per patient over the 9 month study period. Effectiveness was assessed using health care utilities and time to initial definitive evaluation. Costs were estimated from the VA perspective.
One thousand one hundred and sixty-three patients were assessed for eligibility and 771 were excluded, declined participation, or were otherwise not enrolled. One hundred ninety-six patients randomized to each study group. There were no differences in demographics or baseline Skindex-16 scores by randomization group. One hundred sixty-six patients in usual care completed the nine month close-out and 161 did so in teledermatology. For patients in both study groups, mean Skindex-16 scores were lower (improved) across all subscales (symptoms, emotions, functioning) and by composite score between baseline and 9 months. There was no evidence to suggest a difference in Skindex-16 scores between randomization assignments for any subscale or composite score (p = 0.21, 0.71, 0.66, and 0.60, respectively) At nine months clinically significant improvements in quality of life were found for both study groups. Likewise, Skindex-16 scores at three months improved across all subscales and composite score with no evidence to suggest a difference by study assignment (p = 0.83, 0.41, 0.30, 0.45, respectively). Smaller mean change scores were recorded at the 3 month assessment. Time to initial definitive evaluation showed no randomization group differences based on scheduled or actual visit analyses (p = 0.63 and 0.06, respectively), although a trend towards quicker evaluation was noted for teledermatology patients based on actual visit analysis (25.4 days versus 30.8 days). There was no evidence to suggest a difference in clinical course between randomization assignments at either the first clinic visit or at nine months (p = 0.71 and 0.80, respectively). The economic analysis revealed no significant differences in effectiveness measures (time to initial definitive intervention or utilities as measured by the time trade-off and HUI2). With no significant differences in effectiveness, a cost-minimization analysis found that the mean observed cost per patient over the nine month study period was $384 for teledermatology and $704 for conventional care.
The VA continues to increase its adoption of telemedicine as a means of health care delivery and this includes a growing use of teledermatology. Store and forward teledermatology has been shown to be a diagnostically reliable and accurate means of managing dermatologic conditions. What has been less clear is its impact on quality of life, clinical course, and economic outcomes. Our study findings suggest that quality of life outcomes, as measured by the Skindex-16, are not significantly influenced by whether skin conditions are managed by teledermatology or conventional care. Likewise, we found no significant differences in the clinical course experienced by patients undergoing store and forward teledermatology compared to conventional care. The economic analysis yielded no significant randomization group differences in effectiveness. Therefore, the economic analysis becomes an analysis based on cost that revealed an economic advantage to the use of store and forward teledermatology from the VA perspective. These findings may be used to plan and predict outcomes as the VA expands its use of teledermatology health care delivery services.
- Datta SK, Warshaw EM, Edison KE, Kapur K, Thottapurathu L, Moritz TE, Reda DJ, Whited JD. Cost and Utility Analysis of a Store-and-Forward Teledermatology Referral System: A Randomized Clinical Trial. JAMA dermatology (Chicago, Ill.). 2015 Dec 1; 151(12):1323-1329.
- Whited JD. Teledermatology. The Medical Clinics of North America. 2015 Nov 1; 99(6):1365-79, xiv.
- Whited JD. Quality of life: a research gap in teledermatology. International Journal of Dermatology. 2015 Oct 1; 54(10):1124-8.
- Whited JD, Warshaw EM, Kapur K, Edison KE, Thottapurathu L, Raju S, Cook B, Engasser H, Pullen S, Moritz TE, Datta SK, Marty L, Foman NA, Suwattee P, Ward DS, Reda DJ. Clinical course outcomes for store and forward teledermatology versus conventional consultation: a randomized trial. Journal of telemedicine and telecare. 2013 Jun 1; 19(4):197-204.
- Whited JD, Warshaw EM, Edison KE, Kapur K, Thottapurathu L, Raju S, Cook B, Engasser H, Pullen S, Parks P, Sindowski T, Motyka D, Brown R, Moritz TE, Datta SK, Chren MM, Marty L, Reda DJ. Effect of store and forward teledermatology on quality of life: a randomized controlled trial. JAMA dermatology (Chicago, Ill.). 2013 May 1; 149(5):584-91.
Health Systems, Other Conditions
Treatment - Observational, Treatment - Comparative Effectiveness
Cost effectiveness, Quality assessment, Telemedicine