[정보] 성공하는 디지털 헬스케어 스타트업을 위한 8가지 조언

성공하는 디지털 헬스케어 스타트업을 위한 8가지 조언 내용 입니다.

많은 참고 하시기 바랍니다.

 

 

성공하는 디지털 헬스케어 스타트업을 위한 8가지 조언 from Yoon Sup Choi

 

1.  1. Professor, SAHIST, Sungkyunkwan University Managing Partner, Digital Healthcare Parnters Yoon Sup Choi, Ph.D. 성공하는 디지털 헬스케어 스타트업을 위한 8가지 조언
2. 2. “It's in Apple's DNA that technology alone is not enough. 
 It's technology married with liberal arts.”
3. 3. The Convergence of IT, BT and Medicine
4. 4. Inevitable Tsunami of Change
5. 5. http://rockhealth.com/2015/01/digital-health-funding-tops-4-1b-2014-year-review/
6. 6. https://rockhealth.com/reports/digital-health-funding-2015-year-in-review/
7. 7. Digital Healthcare Industry Landscape Data Measurement Data Integration Data Interpretation Treatment Smartphone Gaget/Apps DNA Artificial Intelligence Telemedicine 2nd Opinion Device On Demand (O2O) Wearables / IoT 3D Printer Counseling (ver. 2) Digital Healthcare Institute Diretor, Yoon Sup Choi, Ph.D. yoonsup.choi@gmail.com EMR/EHR Data Platform Accelerator/early-VC
8. 8. Digital Healthcare Industry Landscape Data Measurement Data Integration Data Interpretation Treatment Smartphone Gaget/Apps DNA Artificial Intelligence Telemedicine Device On Demand (O2O) Wearables / IoT 3D Printer Counseling (ver. 2) Digital Healthcare Institute Diretor, Yoon Sup Choi, Ph.D. yoonsup.choi@gmail.com EMR/EHR Data Platform Accelerator/early-VC
9. 9. 디지털 헬스케어 (예비) 스타트업을 위한 여덟 가지 잔소리
10. 10. 아무도 원하지 않는 제품을 만들고 있는 것은 아닌가? 예쁜 쓰레기를 만들지 마라
11. 11. 아무도 원하지 않는 제품을 만들고 있는 것은 아닌가? • 진짜 니즈가 무엇인지 파악하라 • 고객들이 원한다고 말하는 것 (X) • 고객들이 원한다고 당신이 생각하는 것 (X) • 실제로 진짜 고객들이 원하는 것 (O) • 무엇이 가능한지 모르기 때문에, 고객은 스스로 무엇을 원하는지 모를 것이다.
12. 12. 고객이 누구인가? 그 고객 중 누구를 고를 것인가
13. 13. 고객이 누구인가? • 헬스케어 시장의 니즈는 고객마다 매우 세분화되어 있다. • 건강인 / 환자 • 20대 / 30대 / 40대 / 50대 / 60대 / 70대 / 80대 • 남성 / 여성 • 저체중 / 정상/ 과체중 • 가족력
 • B2C / B2B
14. 14. 고객이 누구인가? • 모든 고객의 니즈를 모두 충족시키는 것은 불가능하다. • 그렇다면 어떤 고객을 골라야하나? • 가장 절박한 니즈를 가진 고객 세그먼트는? • 우리가 실제로 해결책을 제시할 수 있는 고객은? • 돈을 낼 수 있는 고객은?
15. 15. Fitbit
16. 16. https://www.empatica.com/science
17. 17. 3.6 percent Proportion of U.S. couples that use its tests before trying to conceive
18. 18. 의료적 관점에서도 동의할 수 있는 해결책인가 의료 전문가의 도움이 필요하다
19. 19. 의료적 관점에서도 동의할 수 있는 해결책인가 • 의료 전문가 (의사)의 조언이 필요하다. • 과학적/의학적 설득력이 없는 (a.k.a. 사이비) 서비스/제품은 곤란하다. • 의료 현실에 맞지 않는 서비스는 외면 당하거나, 극심한 반대에 부딪힌다.
 
 • 초기 팀원 중에 의사가 꼭 있을 필요는 없지만, 조언을 얻을 수 있는 분은 필요하다. • 의사들 사이에서도 성향 차이 / 의견 차이가 존재한다.
20. 20. 중개자적 리더가 필요하다 서로 말이 통해야 한다
21. 21. Digital Technology Biotechnology Medicine Digital Healthcare
22. 22. 수퍼맨
23. 23. 개발자 사업개발 의사 마케터 과학자 디자이너
24. 24. 개발자 사업개발 의사 마케터 과학자 디자이너 중개자적 리더
25. 25. 한국 의료 시스템의 특수성을 이해하라 실리콘밸리 따라했다가 망하는 수가 있다
26. 26. 한국 의료 시스템의 특수성을 이해하라 • 한국 의료 체계는 미국과는 크게 다르다. • 국내 의료 시스템의 특성을 명확히 파악할 필요가 있다. • 의료 접근성, 의료 보험 체계, 의료 수가 등등 • 미국에서 통했던 것이, 한국에서는 통하지 않거나 / 아예 불법일 수 있다. • 그렇다고 꼭 국내 시장에 국한될 필요는 없다.
27. 27. CellScope’s iPhone-enabled otoscope
28. 28. • NewYork • First-time home visit $50; regular visits $200; physical $100
29. 29. 헬스케어는 규제 산업이다 … 우린 아마 안 될꺼야?
30. 30. 의료 vs. 비의료 일단 이 두 가지를 구분해야 한다
31. 31. 헬스케어넓은 의미의 건강 관리에는 해당되지만, 디지털 기술이 적용되지 않고, 전문 의료 영역도 아닌 것 예) 운동, 영양, 수면 디지털 헬스케어 건강 관리 중에 디지털 기술이 사용되는 것 예) 사물인터넷, 인공지능, 3D 프린터 모바일 헬스케어 디지털 헬스케어 중 모바일 기술이 사용되는 것 예) 스마트폰, 사물인터넷, SNS 개인 유전정보분석 예) 암유전체, 질병위험도, 보인자, 약물 민감도 예) 웰니스, 조상 분석 헬스케어 관련 분야 구성도(ver 0.3) 의료 질병 예방, 치료, 처방, 관리 등 전문 의료 영역 원격의료 원격진료
32. 32. 헬스케어는 규제 산업이다 • 규제는 본질적으로 기술의 발전을 뒤따를 수 밖에 없다. • 국내 규제 상황은 별로 좋지 않다. • 합리성, 일관성, 불확실성 • 싫든 좋든, 규제를 개척하는 것도 역할의 하나이다. • 하지만 식약처도 열심히 일하고 있다. • 초기에 식약처 등 관련 기관을 컨택하는 것도 필요하다.
33. 33. 근거를 만들어야 한다. 데이터, 데이터, 데이터!
34. 34. • 헬스케어/의료 서비스는 근거가 필수적이다. • 하지만 그렇지 못한 것이 현실 applications, from photometric diagnostics to medical-grade imaging (16).Taking advantage of these properties, newly developed devices permit the automated determination of refractive error merely by having an individual look through a lens attached to a smartphone (17). Another transportable imaging capability involves the enabling of remote diagnosis through the use of a smartphone case with an attached otoscope (for detecting an ear infection) (18), multimodal colposcope for cervical cancer identification (19), or optical screening tool for potentially cancerous oral lesions (20). Dermatologic diagnostics may be especially well suited for exploiting the myriad smartphone capabilities for teledermatology (21). The technologies highlighted above can improve care simply through their ability to markedly in- crease the accessibility and convenience of care by bringing clinic- and hospital-quality moni- toring and diagnostics to the point of need. How- ever, their greatest potential might be in allowing for the complete redefining of “normal” physio- logical responses and in enhancing our under- standing of the natural histories of poorly defined chronic conditions. Continuous beat-to-beat moni- toring of blood pressure throughout daily activities will help to refine the catchall diagnosis of “essential hypertension” as multiple distinct phenotypes. Similarly, understanding individual varia- views conclude that high-quality evidence is lacking for the use of mHealth to effect behavioral changes or to manage chronic diseases, 1000 Funding ($) in millions Publications Funding($inmillions) 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 800 600 400 200 0 10,000 8000 6000 4000 2000 0 WoSpublications(number) Fig. 2. mHealth taking center stage. Measures are funding and number of related publications. Shown are the annual total funding for patient-facing mHealth companies and the annual num- ber of related publications [identified with Web of Science (WoS) using search terms “telemedi- cine” and “mhealth*” and “digital health” and “digital medicine”]. Funding data provided by B. Dolan and A. Pai of MobiHealthNews. R E V I E W onApril27,2015emag.org 근거를 만들어야 한다.
35. 35. 근거를 만들어야 한다. • 의료 기관과의 협업이 필요할 가능성이 높다. • 하지만 의료 기관과 일하기 쉽지 않다. • Right person, Right hospital, Right department, Right time… • 의사의 관심과 스타트업의 관심사가 다르다. • 의사와 스타트업의 공통점: 리소스가 턱없이 부족하다. • 가장 좋은 근거는 역시 임상 연구 결과 • 연구 조건은 case by case. • Randomised, Double-blinded, controlled trial. • 충분한 N 수, 충분한 기간
36. 36. https://www.theranos.com/content/images/news/we-publish-prices.jpg 240 lab tests, less than $15 each
37. 37. http://graphics.wsj.com/billion-dollar-club/ •기업 가치 $9b (June 2014) •총 투자유치 규모: $400m •엘리자베스 홈즈 본인이 과반 이상 지분 보 유
38. 38. The Journal of Clinical Investigation C L I N I C A L M E D I C I N E Introduction Clinical laboratory testing plays a critical role in health care and evidence-based medicine (1). Lab tests provide essential data that support clinical decisions to screen, diagnose, and treat health conditions (2). Most individuals encounter clinical testing through their health care provider during a routine health assess- ment or as a patient in a health care facility. However, individu- als are increasingly playing more active roles in managing their health, and some now seek direct access to laboratory testing for self-guided assessment or monitoring (3–5). IntheUSA,allclinicallaboratorytestingconductedonhumans is regulated by Centers for Medicare & Medicaid Services (CMS) based on guidelines outlined in Clinical Laboratory Improvement Amendments (CLIA) (6). To ensure analytical quality of labora- tory methods, certified laboratories are required to participate in periodic proficiency testing using a homogeneous batch of sam- ples that are distributed to each laboratory from a CMS-approved proficiency testing program. These programs assess the total allowable error (TEa) that combines method bias and total impre- cision for each analyte. Acceptability criteria are determined by CLIA and/or the appropriate accrediting agency (7). Direct-to-consumer service models now provide means for individuals to obtain laboratory testing outside traditional health care settings (4, 5). One company implementing this new model is Theranos, which offers a blood testing service that uses capillary tube collection and promises several advantages over traditional venipuncture: lower collection volumes (typically ≤150 μl versus ≥1.5 ml), convenience, and reduced cost — on average about 5-fold less than the 2 largest testing laboratories in the USA (Quest and LabCorp) (8). However, availability of these services varies by state, where access to offerings may be more or less restrictive BACKGROUND. Clinical laboratory tests are now being prescribed and made directly available to consumers through retail outlets in the USA. Concerns with these test have been raised regarding the uncertainty of testing methods used in these venues and a lack of open, scientific validation of the technical accuracy and clinical equivalency of results obtained through these services. METHODS. We conducted a cohort study of 60 healthy adults to compare the uncertainty and accuracy in 22 common clinical lab tests between one company offering blood tests obtained from finger prick (Theranos) and 2 major clinical testing services that require standard venipuncture draws (Quest and LabCorp). Samples were collected in Phoenix, Arizona, at an ambulatory clinic and at retail outlets with point-of-care services. RESULTS. Theranos flagged tests outside their normal range 1.6× more often than other testing services (P < 0.0001). Of the 22 lab measurements evaluated, 15 (68%) showed significant interservice variability (P < 0.002). We found nonequivalent lipid panel test results between Theranos and other clinical services. Variability in testing services, sample collection times, and subjects markedly influenced lab results. CONCLUSION. While laboratory practice standards exist to control this variability, the disparities between testing services we observed could potentially alter clinical interpretation and health care utilization. Greater transparency and evaluation of testing technologies would increase their utility in personalized health management. FUNDING. This work was supported by the Icahn Institute for Genomics and Multiscale Biology, a gift from the Harris Family Charitable Foundation (to J.T. Dudley), and grants from the NIH (R01 DK098242 and U54 CA189201, to J.T. Dudley, and R01 AG046170 and U01 AI111598, to E.E. Schadt). Evaluation of direct-to-consumer low-volume lab tests in healthy adults Brian A. Kidd,1,2,3 Gabriel Hoffman,1,2 Noah Zimmerman,3 Li Li,1,2,3 Joseph W. Morgan,3 Patricia K. Glowe,1,2,3 Gregory J. Botwin,3 Samir Parekh,4 Nikolina Babic,5 Matthew W. Doust,6 Gregory B. Stock,1,2,3 Eric E. Schadt,1,2 and Joel T. Dudley1,2,3 1 Department of Genetics and Genomic Sciences, 2 Icahn Institute for Genomics and Multiscale Biology, 3 Harris Center for Precision Wellness, 4 Department of Hematology and Medical Oncology, and 5 Department of Pathology, Icahn School of Medicine at Mount Sinai, NewYork, NewYork, USA. 6 Hope Research Institute (HRI), Phoenix, Arizona, USA. Conflict of interest: J.T. Dudley owns equity in NuMedii Inc. and has received consulting fees or honoraria from Janssen Pharmaceuticals, GlaxoSmithKline, AstraZeneca, and LAM Therapeutics. Role of funding source: Study funding provided by the Icahn Institute for Genomics and Multiscale Biology and the Harris Center for Precision Wellness at the Icahn School of Medicine at Mount Sinai. Salaries of B.A. Kidd, J.T. Dudley, and E.E. Schadt Downloaded from http://www.jci.org on March 28, 2016. http://dx.doi.org/10.1172/JCI86318 •Mt Sinai 에서 내어놓은 Theranos 의 정확도에 대한 논문 •2015년 7월 경에 60명의 건강한 환자들을 대상으로 5일 간에 걸쳐서 •22가지의 검사 항목을 테라노스와 또 다른 두 군데의 검사 기관에 맡겨서 결과를 비교 •결론적으로 Theranos의 결과가 많이 부정확 •콜레스테롤 등의 경우는 의사의 진단이 바뀔 정도로 크게 부정확 •전반적인 테스트들 결과 정상 범위가 아니라고 판단하는 경우가 테라노스가 1.6배 많음 •22개의 검사 항목 중에서 15개에서 유의미하게 결과의 차이가 있었습니다. •논문에서는 알 수 없는 또 다른 문제 •Theranos가 자체적으로 개발했다고 '주장' 했던 에디슨 기기를 정말로 썼느냐...하는 것 •WSJ 에 나온 과거 직원의 증언에 따르면, 이미 2015년 7월경이라면, •에디슨 기기를 쓰지 않고 지멘스 등 기존 다른 기기에 혈액을 희석해서 쓰고 있을 때 •역시나(?) 이번에도 테라노스는 conflict-of-interest 가 있는 잘못된 논문이라는 반응
39. 39. Neofect
40. 40. Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial ments at T2 and 23 completed the follow-up assessments at T3. During the study, 5 and 8 participants from the SG and CON groups, respectively, did not complete the inter- vention programs. The sample sizes at the assessment time points are presented in Fig. 2. There were no serious ad- verse events, and only 1 participant from the CON group dropped out owing to dizziness, which was unrelated to the intervention. Thus, most of the study withdrawals were related to uncooperativeness, and the number was higher than that hypothesized in the study design. At baseline, dist: F = 4.64, df = 1.38, P = 0.024). Secondary outcomes Jebsen–Taylor hand function test The JTT scores of the SG and CON groups are presented in Table 2. There were no significant differences in the JTT-total, JTT-gross, and JTT-fine scores between the 2 groups at T0. The post-hoc test found that there were sig- nificant improvements in the JTT-total, JTT-gross, and JTT-fine scores in the SG group during the intervention Fig. 2 Flowchart of the participants through the study. Abbreviations: SG, Smart Glove; CON, conventional intervention Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17
41. 41. Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial composite SIS score (F = 5.76, df = 1.0, P = 0.021) and the overall SIS score (F = 6.408, df = 1.0, P = 0.015). Moreover, among individual domain scores, the Time × standard OT than using amount-matched conventional re- habilitation, without any adverse events, in stroke survivors. Additionally, this study noted improvements in the SIS- Fig. 3 Mean and standard errors for the FM scores in the SG and CON groups. Abbreviations: FM, Fugl–Meyer assessment, SG, Smart Glove; CON, conventional intervention Fig. 4 Mean and standard errors for the JTT scores in the SG and CON groups. Abbreviations: JTT, Jebsen–Taylor hand function test; SG, Smart Glove; CON, conventional intervention Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 7 of 10 composite SIS score (F = 5.76, df = 1.0, P = 0.021) and the overall SIS score (F = 6.408, df = 1.0, P = 0.015). standard OT than using amount-matched conventional re- habilitation, without any adverse events, in stroke survivors. Fig. 3 Mean and standard errors for the FM scores in the SG and CON groups. Abbreviations: FM, Fugl–Meyer assessment, SG, Smart Glove; CON, conventional intervention Fig. 4 Mean and standard errors for the JTT scores in the SG and CON groups. Abbreviations: JTT, Jebsen–Taylor hand function test; SG, Smart Glove; CON, conventional intervention Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17 Page 7 of 10 Shin et al. Journal of NeuroEngineering and Rehabilitation (2016) 13:17
42. 42. Noom
43. 43. Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching Andreas Michaelides, Christine Raby, Meghan Wood, Kit Farr, Tatiana Toro-Ramos To cite: Michaelides A, Raby C, Wood M, et al. Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching. BMJ Open Diabetes Research and Care 2016;4:e000264. doi:10.1136/bmjdrc-2016- 000264 Received 4 May 2016 Revised 19 July 2016 Accepted 11 August 2016 ABSTRACT Objective: To evaluate the weight loss efficacy of a novel mobile platform delivering the Diabetes Prevention Program. Research Design and Methods: 43 overweight or obese adult participants with a diagnosis of prediabetes signed-up to receive a 24-week virtual Diabetes Prevention Program with human coaching, through a mobile platform. Weight loss and engagement were the main outcomes, evaluated by repeated measures analysis of variance, backward regression, and mediation regression. Results: Weight loss at 16 and 24 weeks was significant, with 56% of starters and 64% of completers losing over 5% body weight. Mean weight loss at 24 weeks was 6.58% in starters and 7.5% in completers. Participants were highly engaged, with 84% of the sample completing 9 lessons or more. In-app actions related to self-monitoring significantly predicted weight loss. Conclusions: Our findings support the effectiveness of a uniquely mobile prediabetes intervention, producing weight loss comparable to studies with high engagement, with potential for scalable population health management. INTRODUCTION Lifestyle interventions,1 including the National Diabetes Prevention Program (NDPP) have proven effective in preventing type 2 diabetes.2 3 Online delivery of an adapted NDPP has resulted in high levels of engagement, weight loss, and improvements in glycated hemoglobin (HbA1c).4 5 Prechronic and chronic care efforts delivered 6 convenient, and accessible method to deliver the NDPP. The weight loss efficacy of a completely mobile delivery of a structured NDPP has not been tested. The main aim of this pilot study was to evaluate the weight loss efficacy of Noom’s smartphone-based NDPP-based cur- ricula with human coaching in a group of overweight and obese hyperglycemic adults receiving 16 weeks of core, plus postcore cur- riculum. In this study, it was hypothesized that the mobile DPP could produce trans- formative weight loss over time. RESEARCH DESIGN AND METHODS A large Northeast-based insurance company offered its employees free access to Noom Key messages ▪ To the best of our knowledge, this study is the first fully mobile translation of the Diabetes Prevention Program. ▪ A National Diabetes Prevention Program (NDPP) intervention delivered entirely through a smart- phone platform showed high engagement and 6-month transformative weight loss, comparable to the original NDPP and comparable to trad- itional in-person programmes. ▪ This pilot shows that a novel mobile NDPP inter- vention has the potential for scalability, and can address the major barriers facing the widespread translation of the NDPP into the community setting, such as a high fixed overhead, fixed locations, and lower levels of engagement and weight loss. Open Access Research group.bmj.comon September 23, 2016 - Published byhttp://drc.bmj.com/Downloaded from
44. 44. 디지털 헬스케어를 이해하는 VC는 거의 없을 것이다. 재무적 투자 이상은 기대하기 어렵다
45. 45. 디지털 헬스케어를 이해하는 VC는 거의 없을 것이다. • IT를 이해하는 VC 는 많다. • 바이오를 이해하는 VC 도 적지 않다.
 • … 하지만 둘 다 이해하고 • 네트워크와 통찰력을 가진 VC는 거의 없다.
46. 46. PRESENTATION © 2015 ROCK HEALTH Digital health continues to receive funding from a wide range of funds with a noticeable growth in the number of active corporate investors. 13 2 2 5 4 5 3 2 10 4 5 7 8 8 MOST ACTIVE FUNDS Deals in 2015 & cumulative deals 2011-2015 8 Source: Rock Health Funding Database Note: Only includes U.S. deals >$2M; data through December 8, 2015 10 1 3 3 4 3 3 24 2 3 4 10 10 13 4 4 2 4 6 7 2 3 11 2 3 1 2 2 3 4 2 8 20 6 9 5 20 5 12 11 5 5 4 4 4 6 12 4 4 # of deals LEGEND 2015 Seed / A by venture funds 2015 Total by venture funds 2015 Seed / A by corporate funds 2015 Total by corporate funds 2011-2015 Cumulative seed / A 2011-2015 Cumulative total 4 4 8 6 6 5 4 4 18 17 14 7 17 23 15 14 18 20 4 5 4 5 4 5 14 27 4 4 https://rockhealth.com/reports/digital-health-funding-2015-year-in-review/
47. 47. 의료를 이해하는 엑셀러레이터도 별로 없을 것이다. 마찬가지다.
48. 48. 의료/헬스케어 전문가 의료기관과의 협력 Exit 경험이 있는 기업가 자금 조달 전문가 제조 기술 전문가 해외 시장 진출 지원 0 10 20 30 40 헬스케어 스타트업이 엑셀러레이터로부터 가장 지원받기를 원하는 요소는? (2016.3 자체 조사)
49. 49. DHP는 최고의 의료 전문가들이 초기 헬스케어 스타트업에 의학 자문, 의료 기관 연계, 임상 검증, 투자 유치 등을 지원합니다. 최윤섭 대표파트너 정지훈 파트너 김치원 파트너 • 성균관대학교 디지털헬스학과 교수 • 최윤섭 디지털 헬스케어 연구소 소장 • VUNO, Zikto, 녹십자홀딩스 등 자문 • 저서: ‘헬스케어 이노베이션’ • 전) 서울대학교 의과대학 암연구소 교수 • 전) 서울대학교병원 의생명연구원 교수 • 포항공대 전산생물학 이학박사 • 포항공대 컴퓨터공학/생명과학 학사 • 경희사이버대학 미디어모바일 전공 교수 • 빅뱅엔젤스 파트너 • Lunit, 매직에코, 휴레이포지티브 등 자문 • 저서: ‘제 4의 불', ‘거의 모든 IT의 역사’ 등 • 전) 명지병원 IT융합연구소장 • 한양대학교 의과대학 졸업 • 서울대학교 보건정책관리학 석사 • USC 의공학박사 • 내과전문의, 서울와이즈요양병원 원장 • 성균관대학교 디지털 헬스학과 교수 • Noom, Zikto, Future Play 등 자문 • 저서: ‘의료, 미래를 만나다’ • 전) 맥킨지 서울사무소 경영컨설턴트 • 전) 삼성서울병원 의료관리학과 교수 • 서울대학교 의과대학 졸업 • 연세대학교 보건대학원 석사
50. 50. Feedback/Questions • Email: yoonsup.choi@gmail.com • Blog: http://www.yoonsupchoi.com • Facebook: 최윤섭 디지털 헬스케어 연구소 / 디지털 헬스케어 파트너스