2016년 원격 의료 산업의 세계적인 동향 및 주요 이슈들을 정리해보았습니다.

1. Director, Digital Healthcare Institute
Managing Partner, Digital Healthcare Partners
Yoon Sup Choi, Ph.D.
원격 의료 산업의 글로벌 동향 및 주요 이슈

2. 2016 복지부/정부 정책 관련

3. 7

4. 8

5. 2016년 4월 18일

6. 2016년 5월 23일

7. 2016년 6월 23일

8. 미국의 원격의료

9. Telemedicine

10. http://www.computerworld.com/article/2490959/healthcare-it-almost-one-in-six-doctor-visits-will-be-virtual-this-year.html

11. http://www.forbes.com/sites/brucejapsen/2015/08/09/as-telehealth-booms-doctor-video-consults-to-double-by-2020/#37fbe7205d66

12. • 2014년 Towers Watson 이 직원이 1,000 명 이상인 미국의 기업들을 대상으로 조사
• 직원들에게 원격 의료 서비스를 제공하려는 기업은 2014년 22% 에서 2015년 37%로 증가할 것으로 예상
• 2017년이 되면 71% 의 기업 고객들이 원격 의료 서비스를 이용할 것으로 예측

13. 미국의 원격 의료
• 본격적으로 활성화되기 시작한 것은 1990년대
• 넓은 영토로 인해 지역별 의료 수준이 상이하며, 의료 접근성 문제가 심각
• 시골과 대도시 병원 간 원격 의료에 대한 필요성 제기
• 1993년 미국원격의료협회(ATA) 설립, 1996년 HIPPA 제정
• 원격 의료가 활성화될 수 밖에 없는 환경적 여건
• 의사의 부족: 의사 1명 당 환자의 수가 평균 370명
• 시골 뿐만 아니라, 대도시의 경우에도 심각: 뉴욕 (1:912명), LA (1:531명)
• 한국: 1:460 (2014년), 서울 (1:315)
• 오바마 케어에 따라 보험 혜택을 받지 못하던 16.4m 명이 새롭게 보험 혜택*
• 2020년까지 90,000명의 의사가 부족할 것으로 예측 (AAMC**)
**https://aspe.hhs.gov/sites/default/files/pdf/139211/ib_uninsured_change.pdf
* The Association of American Medical Colleges
원격 의료 정책 현황 분석 연구, 의료정책연구소, 2015

14. http://money.cnn.com/interactive/economy/average-doctor-wait-times/

15. http://money.cnn.com/interactive/economy/average-doctor-wait-times/

16. 0%
20%
40%
60%
80%
Canada USA UK France Netherlands Germany
76%
63%
57%
52%
48%
41%
0%
10.5%
21%
31.5%
42%
Germany Netherlands UK Switzerland France USA Ca
41%
39%
31%
28%27%
24%
22%
0%
20%
40%
60%
80%
Canada France GermanyNetherlands USA UK Switzerland
80%80%
76%75%
72%
51%
39%
http://economy.money.cnn.com/2013/11/14/america-healthcare/
Able to get same day/next-day appointment?
Used emergency room in past two years
Able to see specialist within four weeks

17. 미국의 원격 의료
• 원격의료에 대한 보험 급여
• 1997년 균형재정법 제정 당시 메디케어(65세 이상 노인대상) 보험 급여 지급 시작
• 1997년 이전에도 12개 주에서 메디케이드(저소득층 대상) 보험 급여 지급
• 2000년대 이후 개인 심리치료, 약물치료, 정신과 진단 등으로 점차 확대
• 현재 원격 의료 보험 인정 현황은 주별로 복잡한 상황
• 적용 범위 / 보상 기준 / 면허 규정 등이 주별로 상이
• Parity Law: 원격 의료에 대면 의료와 동일한 수준의 보험금을 지급하는 법안
• 민간 보험에서 원격의료에 대한 Parity Law 현황 (ATA, 2015)
• 무제한의 Parity Law: 16개 주
• 제한적인 Parity Law (서비스 유형/제공자 유형 등): 2개 주
• 부분적인 Parity Law: 4개 주
원격 의료 정책 현황 분석 연구, 의료정책연구소, 2015

18. 표 5-2 주별 민간 보험에서 원격의료 서비스 보험 급여 관련 parity laws 현황
등급 주 내용
A 16
1996 California
주 전체에 적용
공급자 자격 제한 없음
원격의료 제공 기술 제한 없음
1997 Oklahoma, Texas
1999 Hawaii
2000 Kentucky
2006 Georgia
2009 Maine, New Hampshire
2010 Virginia
2012 Maryland
2013
D. C, Mississippi,
Missouri, Montana,
New Mexico
2014 Tennessee
B 2
1995 Louisiana 2014년에 보험급여 지급 조건 확대
2001 Colorado 농촌지역만 허용
C 4
2009 Oregon 쌍방향 오디오-비디오 형태로 제공되는
원격의료 유형만 허용2012 Michigan, Vermont
2013 Arizona 농촌지역, 7가지 건강서비스만 적용
F 29
Alabama, Delaware, Idaho, Indiana,
Minnesota, Nevada,
North Carolina, North Dakota,
South Dakota, Utah,
Wisconsin, Wyoming
최근 2년 안에 parity 법률 안건 상정 없었음
Arkansas, Kansas
민간 보험 parity laws 적용 거부
최근 2년 안에 parity 법률 안건 상정 없었음
Alaska, Nebraska,
West Virginia
2014년에 민간보험에 parity를 포함하는
원격의료 안건 상정되었으나 통과되지 못함
Connecticut, Florida, Illinois,
Iowa, Massachusetts, New York,
Ohio, Pennsylvania, Rhode Island,
South Carolina, Washington
원격의료에 대한 parity law 도입을 다년간
진행했으나 원격의료 parity law가 없음
New Jersey 원격의료 parity law가 없음
F등급은 원격의료 Parity law가 전혀 없는 주들로 전체 51개 주 중에서 57%인 29개
주가 이 등급을 받았다. Alabama 주를 비롯한 12개 주에서는 최근 2년 안에 parity
미국의 주별 민간보험 parity law 현황
원격 의료 정책 현황 분석 연구, 의료정책연구소, 2015

19. Telehealth Payment Parity Laws Rising Rapidly Across States
• (2016년 2월 기준) 29개 주에서 parity law의 적용을 받음
• 2011년 11개 주에서만 적용
• 48개 주에서는 어떤 형태로든 메디케이드 (저소득층대상)의 적용 받음
• 의회에서는 2016년 메디케어 가입자들에게도 확대 적용하는 것을 계획 중

20. Avalere Health
An Inovalon Company
1350 Connecticut Ave, NW
Washington, DC 20036
P | 202.207.1300
F | 202.467.4455
avalere.com
Medicare would cover RPM for patients with chronic conditions meeting specified criteria for all fee-for-
service (FFS) physicians and practitioners. The coverage will begin six months from the enactment of the
legislation.
Avalere estimates that Policy 1 would increase federal spending by $1.1 billion, Policy 2 would decrease
federal spending by $2.2 billion, and Policy 3 would decrease federal spending by $3.0 billion over the
FY2017 – FY2026 federal budget window. Cumulatively, the three policies would decrease federal
spending by $1.8 billion, given the overlapping nature of the proposals. Our estimates reflect the new cost
to the Medicare program associated with reimbursing for telehealth and RPM services as well as savings
due to the reduced Medicare spending for beneficiaries receiving RPM.
Estimated Change in Federal Spending due to the Three Proposed Telehealth Policies
Outlays, by Fiscal Year, in Billions of Dollars
2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2017-
2021
2017-
2026
Total change in federal spending
Policy 1 0.5 0.5 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 1.1
Policy 2 * * * (0.1) (0.1) (0.2) (0.3) (0.4) (0.5) (0.6) (0.2) (2.2)
Policy 3 * * * (0.1) (0.2) (0.3) (0.4) (0.5) (0.7) (0.8) (0.3) (3.0)
All 3 Policies 0.5 0.5 0.1 (0.1) (0.2) (0.3) (0.4) (0.5) (0.7) (0.8) 0.8 (1.8)
* represents less than $50 million
Note: Numbers may not add due to rounding.
• Estimating the cost or savings to the federal government of three policy changes to
expand Medicare reimbursement of telehealth and remote patient monitoring (RPM)
• Analysis of the provisions regarding the "bridge program," alternative payment models,
and RPM coverage for chronic conditions showed they would produce net savings of
$1.8 billion for Medicare over the course of 10 years
원격의료에 대한 메디케어 혜택의 확대는
향후 10년간 $1.8b 의 비용 절감 효과가 있을 것으로 예상
http://static.politico.com/2d/b5/7715952c4cc7815e7048b91c6c5c/avalere-health-study-of-the-connect-for-health-act.pdf

21. • 원격 진료 (전화/화상 진료)
• 원격 환자 모니터링 (Remote Patients Monitoring, RPM)
• 2차 소견 (2nd opinion)
원격 의료의 주요 유형

22. • 원격 진료 (전화/화상 진료)
• 의사-의사
• 의사-환자: B2B2C / B2C
• 원격 환자 모니터링 (Remote Patients Monitoring, RPM)
• 2차 소견 (2nd opinion)
• 병원 / 기업
• 국내 / 국외
원격 의료의 주요 유형

23. Telemedicine: Teladoc Case

25. How long will you wait to see a doctor?
http://money.cnn.com/interactive/economy/average-doctor-wait-times/

28. Teladoc, Inc
• 최대 / 최초의 원격의료 회사 + 원격의료 최초의 IPO
• 1,100명 이상의 전문의와 의료 전문가들이 소속
• 언제 어디서나 인터넷, 전화, 화상 채팅을 활용해서 진료를 할 수 있게 한다.
• 10분 안에 사람들이 진료를 받을 수 있게 한다.
• B2B2C
• 6,000 개 이상의 기업 고객
• 가입 멤버 수는 총 11.5m 명

30. Growth of Teladoc
Revenue
0
35
70
105
140
2013 2014 2015 2016(E)
Visits
0
250
500
750
1000
2013 2014 2015 2016(E)
Members
0
4.5
9
13.5
18
2013 2014 2015 2016(E)
$44m
$77.4m
$20m
299K
575K
127K
8.1m
11.5m
6.2m
17.5m
930K$128m

31. Teladoc, Inc
• 사업 모델은 B2B2C
• 6,000 개 이상의 기업, 보험사 등을 고객으로 가지고 있음 (상장 당시 4,000개)
• Teladoc 에 접근권한을 구매하여 총 11m 명의 멤버들에게 제공하고 있음
• 기업 고객 (including 200+ Fortune 1000 Clients)
• 보험사:Aetna,Amerigroup, Blue Shield of California, Centene, Highmark
• 기업:Accenture, Bank of America, General Mills, Pepsi, Shell andT-Mobile
• 병원: Health Partners, Henry Ford, Memorial Hermann and Mount Sinai.

32. Teladoc, Inc
• 수익 모델
• 연간 구독료
• 기업 고객에게 가입자 수를 기반으로 단체 구독료를 받는 것
• PMPM (per-Memeber-per-Month): 사용 월수와 멤버수 기반 산정
• 가입자들을 대표해서 기업이 지불
• 개별 진료비
• 실제 진료가 일어날 때 추가의 진료비를 청구
• 기업이 지불하거나 or 멤버 본인이 지불

35. 2016년 6월 30일
• 최근에도 원격진료 회사 HealthiestYou를 $125m 에 인수
• $125m 은 2014-2015년도 매출을 합친 것과 비슷한 규모
• 중소기업 고객 시장에 대한 접근을 강화하기 위한 목적의 인수

37. 240K
+61%
149K

38. 2015
575K
5%
CAGR: ~40%

39. DoctorOnDemand

40. DoctorOnDemand

41. DoctorOnDemand

42. • 미국 46개 주에 서비스 제공, 1,400명의 의사들이 가입
• 진료당 진료비는 $40 (DoD:의사 = $10:$30)
• 별도의 subscription fee 없음
• 간단한 질병만 진료
• 감기, 편도선염, 호흡기 질환, 인플루엔자, 알러지, 운동중 외상, 충혈, 설사,
우울증, 피부 상처, 열병, 방광 감염
• 모바일 처방전까지 제공
• SureScript 전산망 가입 약국 (미국 M/S 96%) 에서 처방 가능
DoctorOnDemand

43. Second Opinion

44. WSJ Aug 24

45. • 진단결과가 명확하지 않거나, 수술이나 치료법 결정시 2차 소견 권고
• 수술 등의 경우 보험사가 2차 소견을 요구
• 미국에서는 온라인으로 2차 소견을 제공하는 서비스의 증가
• 2차 소견을 받음으로써 환자들이 새로운 치료 옵션을 갖게 될 수 있음
• 만약 1, 2차 소견이 다르게 나온다면 추가적인 소견이 필요할 수 있음
• 미국과 달리 국내에는 2차 소견을 받는 문화가 정착되어 있지 않음
• 2가지 모델
• 기존의 병원이 제공: 클리블랜드 클리닉, 메사츄세츠 종합 병원
• 전문의들의 독립된 서비스: Best Doctors, SecondOpinionExpert etc
Second Opinion

48. • 최근 미국에서 2차 소견 수요 증가 추세
• 전체 환자 중 20% 가 2차 소견을 원함
• 암과 같은 전문의 2차 소견이 필요한 경우 50% 이상
• 메사츄세츠 종합병원 (MGH)의 경우
• 8년 전부터 해당 서비스 제공
• 2010년 총 1,000 건 ➞ 2014년 10,000 건
• 서비스 가격: $500-5,000
• 고객: 개인 환자 (해외 환자 포함) / 기업 고객
Second Opinion

49. • 의뢰 중 11%가 1차 소견과 다른 진단
• 치료법에 약간 변화: 24%
• 치료법에 큰 변화: 16%
• 컨설테이션: $565, 병리학과 의사 리뷰 추가: $745

50. Evaluation of Outcomes From a National
Patient-initiated Second-opinion Program
Ashley N.D. Meyer, PhD,a,b
Hardeep Singh, MD, MPH,a,b
Mark L. Graber, MD, FACPc,d
a
Houston Veterans Affairs Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston,
Tex; b
Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, Tex; c
RTI International, Research
Triangle Park, NC; d
SUNY Stony Brook School of Medicine, New York, NY.
ABSTRACT
BACKGROUND: We examined outcomes of patient-initiated second opinions provided by a national
second-opinion program.
METHODS: We independently examined data collected from January 1, 2011 to December 31, 2012 from a
second-opinion program (Best Doctors, Inc.) that allows employee-beneficiaries to request free second
opinions. Clinical intake included ascertaining why patients sought second opinions and acquiring patients’
complete medical records. Trained physicians summarized the cases; identified key, unresolved clinical
questions; and forwarded the cases to expert specialists who provided independent assessments and
recommendations. Second opinions were discussed with and returned to patients for review with their
physicians. Nurses determined whether second opinions confirmed, clarified, or changed initial diagnoses
and treatments, and physicians estimated their clinical impact. Patient satisfaction also was surveyed.
RESULTS: A total of 6791 patient-initiated second opinions were completed across medical specialties.
Patients primarily sought second opinions for help choosing treatment options (41.3%) and for diagnostic
concerns (34.8%). Second opinions often resulted in changes in diagnosis (14.8%), treatment (37.4%), or
changes in both (10.6%). Clinical impact was estimated as moderate/major in 20.9% of cases for diagnosis
and 30.7% of cases for treatment. Changes in diagnoses and/or treatments and clinical impact varied across
medical specialties. In patients surveyed (n ¼ 2683), most (94.7%) were satisfied with the experience, but
fewer (61.2%) planned to follow the recommendations.
CONCLUSIONS: Patient-initiated second opinions led to recommended changes in diagnosis for about 15%
and in treatment for about 37% of participants. Further evaluation is needed to determine whether this
impacts clinical outcomes, such as the reduction of diagnosis and treatment errors.
Published by Elsevier Inc. The American Journal of Medicine (2015) 128, 1138.e25-1138.e33
KEYWORDS: Diagnosis; Diagnostic errors; Patient Safety; Second opinions; Treatment
Patients seek second medical opinions for a variety of rea-
sons.1,2
Some patients seek advice because their symptoms
remain undiagnosed. Others are given diagnoses, but their
symptoms persist, they have doubts about their diagnoses, or
they hope their diagnoses are incorrect, especially when the
diagnoses carry substantial risks of major morbidity or
mortality.3
While seeking second opinions, patients are
looking for more information about their diseases or
Funding: ANDM and HS are supported by the Department of Veterans Authorship: All authors had access to the data and a role in writing the
CLINICAL RESEARCH STUDY
• 2011-2012년 Best Doctors의 patients-initiated second opinion 6791 케이스 분석

51. Evaluation of Outcomes
from a National Patient-Initiated Second-Opinion Program
Am J Med. 2015 Oct;128(10):1138.e25-33.
Reasons Patients Sought Second Opinion
(among 6,791 cases)
M
ANUSCRIPT
TED
ACCEPTED MANUSCRIPT
Figure 2. Reasons Patients Sought Second Opinions
Caption. Reasons that patients sought second opinions were collected during clinical intake
and were mutually exclusive.

52. Evaluation of Outcomes
from a National Patient-Initiated Second-Opinion Program
Am J Med. 2015 Oct;128(10):1138.e25-33.
M
ANUSCRIPT
CCEPTED
ACCEPTED MANUSCRIPT
Figure 3. Changes in Diagnoses and Treatments from Second Opinion in 6,791 Cases
Caption. The percentage of patients whose second opinions led to changes, clarifications, or
confirmations of diagnoses and of treatments, as assessed by program clinical staff.
M
ANUSCRIPT
CCEPTED
ACCEPTED MANUSCRIPT
Figure 4. Estimated Impact of Second Opinions in 6,791 Cases
Caption. The estimated clinical impact of the second opinions, as assessed by program
physicians.Changes in diagnosis/treatment from 2nd opinion
(among 6,791 cases)
Estimated Impact of 2nd opinion
(among 6,791 cases)

53. Specialty Total Cases (n)
Diagnosis Changes (%) Impact of Evaluation on Diagnosis (%)
Changed
Confirmed
or Clarified Pending None Minor Moderate Major Pending
Allergy and Immunology 29 20.7 65.5 13.8 6.9 55.2 20.7 6.9 10.3
Anesthesiology/Pain Medicine 39 35.9 61.5 2.6 38.5 46.2 10.3 5.1 0.0
Cardiovascular Disease 359 9.2 81.1 9.7 24.0 57.4 13.1 1.9 3.6
Colon and Rectal Surgery 24 16.7 70.8 12.5 20.8 62.5 12.5 4.2 0.0
Critical Care Medicine-Pulmonary
Medicine
123 19.5 57.7 22.8 11.4 49.6 32.5 4.1 2.4
Dermatology 100 16.0 70.0 14.0 32.0 37.0 22.0 4.0 5.0
Endocrinology and Metabolism 251 11.6 77.7 10.8 28.7 45.4 18.7 2.0 5.2
Family Medicine 4 25.0 75.0 0.0 25.0 75.0 0.0 0.0 0.0
Gastroenterology 473 23.7 58.8 17.5 18.8 50.3 23.5 3.4 4.0
General Surgery 113 9.7 85.0 5.3 43.4 38.1 8.0 1.8 8.8
Hand Surgery 69 7.2 76.8 15.9 36.2 40.6 13.0 1.4 8.7
Hepatology 57 5.3 84.2 10.5 21.1 49.1 14.0 7.0 8.8
Infectious Disease 59 22.0 61.0 16.9 11.9 47.5 28.8 3.4 8.5
Internal Medicine 87 20.7 54.0 25.3 19.5 44.8 21.8 0.0 13.8
Medical Genetics 20 5.0 80.0 15.0 35.0 40.0 20.0 0.0 5.0
Medical Oncology and Hematology 588 5.1 91.7 3.2 32.5 43.0 18.5 3.2 2.7
Nephrology 54 5.6 83.3 11.1 16.7 50.0 25.9 3.7 3.7
Neurologic Surgery 259 17.8 73.0 9.3 31.3 46.7 14.7 2.7 4.6
Neurology 577 22.5 62.4 15.1 21.5 46.6 23.6 3.6 4.7
Obstetrics and Gynecology 320 14.7 73.1 12.2 23.4 42.5 23.4 4.1 6.6
Ophthalmology 140 12.9 78.6 8.6 35.0 49.3 11.4 0.7 3.6
Orthopedic Surgery 1195 13.8 77.2 9.0 31.7 43.5 16.0 2.5 6.3
Otolaryngology 233 17.2 76.0 6.9 30.5 42.5 18.0 3.4 5.6
Pediatric Specialist 411 14.4 76.4 9.2 21.7 52.6 15.6 3.9 6.3
Physical Medicine and Rehabilitation 458 16.6 61.6 21.8 22.3 55.7 17.5 1.1 3.5
Plastic Surgery 23 8.7 78.3 13.0 34.8 39.1 17.4 0.0 8.7
Radiation Oncology 42 7.1 92.9 0.0 52.4 45.2 2.4 0.0 0.0
Radiology 16 6.3 93.8 0.0 25.0 62.5 6.3 0.0 6.3
Rheumatology 240 26.3 59.2 14.6 27.5 45.0 20.8 2.5 4.2
Sleep Medicine 5 0.0 100.0 0.0 40.0 40.0 20.0 0.0 0.0
Surgical Oncology 58 3.4 93.1 3.4 51.7 32.8 12.1 1.7 1.7
Thoracic Surgery 23 0.0 91.3 8.7 26.1 47.8 17.4 8.7 0.0
Urology 298 7.7 82.6 9.7 45.3 34.9 16.4 0.3 3.0
Vascular Surgery 44 11.4 81.8 6.8 36.4 40.9 18.2 0.0 4.5
All Specialties 6791 14.8 73.8 11.4 27.9 46.3 18.2 2.7 4.9

54. Specialty Total Cases (n)
Treatment Changes (%) Impact of Evaluation on Treatment (%)
Changed
Confirmed
or Clarified Pending None Minor Moderate Major Pending
Allergy and Immunology 29 58.6 27.6 13.8 6.9 44.8 31.0 6.9 10.3
Anesthesiology/Pain Medicine 39 69.2 30.8 0.0 7.7 61.5 28.2 2.6 0.0
Cardiovascular Disease 359 37.3 52.9 9.7 13.4 57.9 20.1 4.5 4.2
Colon and Rectal Surgery 24 41.7 54.2 4.2 0.0 50.0 33.3 16.7 0.0
Critical Care Medicine-Pulmonary
Medicine
123 39.0 39.8 21.1 8.9 52.8 34.1 0.8 3.3
Dermatology 100 38.0 52.0 10.0 9.0 47.0 34.0 5.0 5.0
Endocrinology and Metabolism 251 39.4 51.0 9.6 14.3 48.2 28.7 3.6 5.2
Family Medicine 4 50.0 50.0 0.0 0.0 75.0 25.0 0.0 0.0
Gastroenterology 473 49.3 36.8 14.0 10.4 53.7 29.0 3.2 3.8
General Surgery 113 21.2 75.2 3.5 25.7 46.9 15.9 2.7 8.8
Hand Surgery 69 37.7 55.1 7.2 18.8 43.5 26.1 4.3 7.2
Hepatology 57 24.6 63.2 12.3 15.8 54.4 15.8 5.3 8.8
Infectious Disease 59 45.8 42.4 11.9 22.0 37.3 27.1 5.1 8.5
Internal Medicine 87 41.4 43.7 14.9 16.1 52.9 16.1 0.0 14.9
Medical Genetics 20 15.0 65.0 20.0 30.0 40.0 20.0 0.0 10.0
Medical Oncology and Hematology 588 27.0 68.9 4.1 18.2 41.8 34.2 3.7 2.0
Nephrology 54 31.5 57.4 11.1 7.4 53.7 31.5 5.6 1.9
Neurologic Surgery 259 42.5 50.2 7.3 12.7 49.4 26.6 7.3 3.9
Neurology 577 42.3 43.0 14.7 13.3 57.5 21.7 2.6 4.9
Obstetrics and Gynecology 320 42.5 49.7 7.8 10.6 41.6 32.8 8.1 6.9
Ophthalmology 140 30.0 62.9 7.1 12.9 61.4 20.7 1.4 3.6
Orthopedic Surgery 1195 34.6 57.4 8.0 12.9 48.3 26.4 6.0 6.4
Otolaryngology 233 44.2 51.5 4.3 18.5 48.1 23.6 3.9 6.0
Pediatric Specialist 411 33.8 59.4 6.8 11.4 51.3 24.8 5.4 7.1
Physical Medicine and Rehabilitation 458 41.3 43.9 14.8 14.0 57.2 22.9 2.2 3.7
Plastic Surgery 23 34.8 47.8 17.4 13.0 47.8 21.7 8.7 8.7
Radiation Oncology 42 21.4 78.6 0.0 9.5 54.8 33.3 2.4 0.0
Radiology 16 18.8 81.3 0.0 50.0 31.3 12.5 0.0 6.3
Rheumatology 240 46.7 43.3 10.0 19.2 48.8 24.6 2.9 4.6
Sleep Medicine 5 0.0 100.0 0.0 0.0 60.0 40.0 0.0 0.0
Surgical Oncology 58 19.0 79.3 1.7 25.9 37.9 29.3 5.2 1.7
Thoracic Surgery 23 26.1 65.2 8.7 17.4 30.4 39.1 13.0 0.0
Urology 298 28.5 63.8 7.7 17.8 46.6 30.2 2.3 3.0
Vascular Surgery 44 29.5 63.6 6.8 22.7 45.5 27.3 0.0 4.5
All Specialties 6791 37.4 53.3 9.3 14.2 50.1 26.5 4.2 5.0

55. • 2차소견에 의해서
• 진단의 변화: 15%
• 치료의 변화: 37%
• 진단 치료의 변화: 10%
• 진단과 치료의 변화는 진료 과목마다 차이가 있음
• 모든 진료 과목에서 진단보다 치료 방법의 변화가 더 빈번함
Evaluation of Outcomes
from a National Patient-Initiated Second-Opinion Program

56. Remote Patients Monitoring

57. Epic MyChart App Epic EHR
Dexcom CGM
Patients/User
Devices
EHR Hospital
Whitings
+
Apple Watch
Apps
HealthKit

59. transfer from Share2 to HealthKit as mandated by Dexcom receiver
Food and Drug Administration device classification. Once the glucose
values reach HealthKit, they are passively shared with the Epic
MyChart app (https://www.epic.com/software-phr.php). The MyChart
patient portal is a component of the Epic EHR and uses the same data-
base, and the CGM values populate a standard glucose flowsheet in
the patient’s chart. This connection is initially established when a pro-
vider places an order in a patient’s electronic chart, resulting in a re-
quest to the patient within the MyChart app. Once the patient or
patient proxy (parent) accepts this connection request on the mobile
device, a communication bridge is established between HealthKit and
MyChart enabling population of CGM data as frequently as every 5
minutes. All provider workflow is in the EHR.
Patient enrollment
To assess this communication bridge and optimize analytic tools in
our EHR, we conducted a quality improvement pilot limited to 10 pa-
tients (Table 1) from a single provider (R.B.K.). The lead author se-
lected the first 10 interested patients during standard pediatric
diabetes clinic visits who were already using a Dexcom CGM and used
an iOS device. Those patients whose CGM receivers did not have
Bluetooth-enabled functionality (2 patients) were loaned an equipped
receiver for the duration of the 3-month pilot.
Participation required confirmation of Bluetooth pairing of the CGM re-
ceiver to a mobile device, updating the mobile device with the most recent
version of the operating system, Dexcom Share2 app, Epic MyChart app,
and confirming or establishing a username and password for all accounts,
including a parent’s/adolescent’s Epic MyChart account. Setup time aver-
aged 45–60 minutes in addition to the scheduled clinic visit. During this
time, there was specific verbal and written notification to the patients/par-
ents that the diabetes healthcare team would not be actively monitoring
or have real-time access to CGM data, which was out of scope for this pi-
lot. The patients/parents were advised that they should continue to contact
the diabetes care team by established means for any urgent questions/
concerns. Additionally, patients/parents were advised to maintain updates
for their linked mobile devices, including the latest operating system and
app updates, to maintain communication of CGM data.
EHR visualization and analytics
Given the data volume of up to 288 glucose readings per day, the
standard flowsheet did not support visualizing a patient’s trends over
weeks to months. Therefore, we implemented modal day visualization
with a custom web-service embedded in the EHR (Figure 2). Design of
this clinical decision support tool could be a barrier for other health-
care delivery systems that might want to replicate our workflow. We
therefore have made it publically available at https://gluvue.stanford
Figure 1: Overview of the CGM data communication bridge architecture.
BRIEFCOMMUNICATION
byguestonApril7,2016http://jamia.oxfordjournals.org/Downloadedfrom
• Apple HealthKit, Dexcom CGM기기를 통해 지속적으로 혈당을 모니터링한 데이터를 EHR과 통합
• 당뇨환자의 혈당관리를 향상시켰다는 연구결과
• Stanford Children’s Health와 Stanford 의대에서 10명 type 1 당뇨 소아환자 대상으로 수행 (288 readings /day)
• EHR 기반 데이터분석과 시각화는 데이터 리뷰 및 환자커뮤니케이션을 향상
• 환자가 내원하여 진료하는 기존 방식에 비해 실시간 혈당변화에 환자가 대응
• 논문에 소개된 사례
• 한 유아에게 간헐적인 야간 저혈당증(intermittent nocturnal hypoglycemia) 증상이 발견
• 야간에 부모가 야간 투여 계획(dinnertime dose regimen)에 따라 추가 인슐린을 투여가 원인이라는 것을 발견
• 밤에는 적은 양의 인슈린을 주도록 가이드하고 새로운 인슐린 투여량이 MyChart를 통해 부모에게 전달

60. GluVue
https://gluvue.stanfordchildrens.org/dashboard/?src=DEMO

61. 원격의료, 과연 정확한가?

62. 미국의 원격 진료는 얼마나 정확한가?
Variation in Quality of Urgent Health Care
Provided During Commercial Virtual Visits
Adam J. Schoenfeld, MD; Jason M. Davies, MD, PhD; Ben J. Marafino, BS; Mitzi Dean, MS, MHA;
Colette DeJong, BA; Naomi S. Bardach, MD, MAS; Dhruv S. Kazi, MD, MS; W. John Boscardin, PhD;
Grace A. Lin, MD, MAS; Reena Duseja, MD; Y. John Mei, AB; Ateev Mehrotra, MD, MPH; R. Adams Dudley, MD, MBA
IMPORTANCE Commercial virtual visits are an increasingly popular model of health care for
the management of common acute illnesses. In commercial virtual visits, patients access a
website to be connected synchronously—via videoconference, telephone, or webchat—to a
physician with whom they have no prior relationship. To date, whether the care delivered
through those websites is similar or quality varies among the sites has not been assessed.
OBJECTIVE To assess the variation in the quality of urgent health care among virtual visit
companies.
DESIGN, SETTING, AND PARTICIPANTS This audit study used 67 trained standardized patients
who presented to commercial virtual visit companies with the following 6 common acute
illnesses: ankle pain, streptococcal pharyngitis, viral pharyngitis, acute rhinosinusitis, low
back pain, and recurrent female urinary tract infection. The 8 commercial virtual visit
websites with the highest web traffic were selected for audit, for a total of 599 visits. Data
were collected from May 1, 2013, to July 30, 2014, and analyzed from July 1, 2014, to
September 1, 2015.
MAIN OUTCOMES AND MEASURES Completeness of histories and physical examinations, the
correct diagnosis (vs an incorrect or no diagnosis), and adherence to guidelines of key
management decisions.
RESULTS Sixty-seven standardized patients completed 599 commercial virtual visits during
the study period. Histories and physical examinations were complete in 417 visits (69.6%;
95% CI, 67.7%-71.6%); diagnoses were correctly named in 458 visits (76.5%; 95% CI,
72.9%-79.9%), and key management decisions were adherent to guidelines in 325 visits
(54.3%; 95% CI, 50.2%-58.3%). Rates of guideline-adherent care ranged from 206 visits
(34.4%) to 396 visits (66.1%) across the 8 websites. Variation across websites was
significantly greater for viral pharyngitis and acute rhinosinusitis (adjusted rates, 12.8% to
82.1%) than for streptococcal pharyngitis and low back pain (adjusted rates, 74.6% to 96.5%)
or ankle pain and recurrent urinary tract infection (adjusted rates, 3.4% to 40.4%). No
statistically significant variation in guideline adherence by mode of communication
(videoconference vs telephone vs webchat) was found.
Invited Commentary
page 643
Supplemental content at
jamainternalmedicine.com
Research
Original Investigation

63. Variation in Quality of Urgent Health Care
Provided During Commercial Virtual Visits
• 급성질환에 대한 미국의 원격진료 서비스들의 정확도와 진료의 퀄리티를 비교
• 8개의 선도적인 원격 진료 서비스를 비교
• 67명의 환자 역할을 하는 배우를 통해서 총 599번의 원격 진료를 진행
• 대상 질병
• 발목 통증
• 연쇄상구균 인두염(streptococcal pharyngitis)
• 바이러스성 인두염(viral pharyngitis)
• 급성 부비동염(acute rhinosinusitis)
• 허리 통증(low back pain)
• 재발성 요도 감염(recurrent female urinary tract infection)

64. Figure 2. Rate of Physician Naming the Correct Diagnosis by Condition and by Virtual Visit Company
100
90
80
10
20
30
40
50
60
70
0
RateofNamingCorrectDiagnosis,%
Condition
By conditionA
Ankle
Pain
Streptococcal
Pharyngitis
Viral
Pharyngitis
RhinosinusitisRecurrent
Female UTI
Low
Back Pain
100
90
80
10
20
30
40
50
60
70
0
RateofNamingCorrectDiagnosis,%
Company No.
By companyB
7 8654321
Rates of naming the correct diagnosis for each visit are based on whether the physician stated the correct diagnosis for each encounter. Each data point represents
the adjusted mean rate of naming the correct diagnosis by condition across all virtual visit companies (A) and by virtual visit company across all conditions (B). The
error bars indicate the 95% CIs; dotted line, the aggregate mean across conditions or virtual visit companies. Variations in naming the correct diagnosis by condition
and by virtual visit company were statistically significant (P .001). UTI indicates urinary tract infection.
Figure 3. Adherence to Guidelines for Key Management Decisions by Condition and by Virtual Visit Company
100
90
80
50
60
70
herenceRate
mentDecision,%
By conditionA
100
90
80
50
60
70
herenceRate
mentDecision,%
By companyB
Quality of Urgent Health Care During Commercial Virtual Visits Original Investigation Research
질병별 / 회사별 화상 진료의 정확도
(Rate of Physician Naming the Correct Diagnosis by Condition and byVirtualVisit Company)
• 정확한 진단 (76.5%), 오진 (14.8%), 진단을 내리지 못함 (8.7%)
• 가장 정확하게 진단되는 질병: 요도 감염 (정확도 91%)
• 가장 부정확하게 진단되는 질병: 부비동염 (정확도 71%)
• 가장 정확한 회사의 진료 정확도 (90%)와 부정확한 회사의 정확도 (70%)에 차이 있음

65. physical examinations ranged from 51.7% to 82.4%. The per-
centage of virtual visits with correct diagnoses named ranged
from 65.4% to 93.8%.
Adherence to Guidelines for Management Decisions
Across all conditions at all companies, key management de-
cisions were guideline adherent in 325 visits (54.3%; 95% CI,
50.2%-58.3%). We found substantial variation among condi-
tions and among companies (P .001 and P = .009, respec-
tively; Figure 3). For example, physicians ordered urine cul-
its (adjusted for condition, 15.5%; 95% CI, 7.9%-23.2%),
whereasthey(appropriately)didnotorderaradiographforlow
back pain in 84 of 90 visits (adjusted for condition, 93.1%; 95%
CI, 87.7%-98.5%). Across virtual visit companies, adjusted ad-
herence of key management decisions to guidelines ranged
from 34.4% to 66.1%.
The pattern of variation in virtual visit companies’ perfor-
mance differed by condition (Figure 4). For the 2 conditions
(low back pain and streptococcal pharyngitis) with the high-
est overall adjusted rate of adherence to guidelines (ranging
Condition
Company No.
Rates of naming the correct diagnosis for each visit are based on whether the physician stated the correct diagnosis for each encounter. Each data point represents
the adjusted mean rate of naming the correct diagnosis by condition across all virtual visit companies (A) and by virtual visit company across all conditions (B). The
error bars indicate the 95% CIs; dotted line, the aggregate mean across conditions or virtual visit companies. Variations in naming the correct diagnosis by condition
and by virtual visit company were statistically significant (P .001). UTI indicates urinary tract infection.
Figure 3. Adherence to Guidelines for Key Management Decisions by Condition and by Virtual Visit Company
100
90
80
10
20
30
40
50
60
70
0
GuidelineAdherenceRate
forKeyManagementDecision,%
Condition
By conditionA
Ankle
Pain
Streptococcal
Pharyngitis
Viral
Pharyngitis
RhinosinusitisRecurrent
Female UTI
Low
Back Pain
100
90
80
10
20
30
40
50
60
70
0
GuidelineAdherenceRate
forKeyManagementDecision,%
Company No.
By companyB
7 8654321
Each point represents the adjusted mean rate of adherence by condition across all virtual visit companies (A) and by virtual visit company across all conditions (B).
The error bars indicate 95% CIs; dotted line, the aggregate mean across conditions or virtual visit companies. Variation in guideline adherence was statistically
significant by condition (P .001) and virtual visit company (P = .009). UTI indicates urinary tract infection.
질병별 / 회사별 진료 가이드라인의 준수 비율
(Adherence to Guidelines for Key Management Decisions by Condition and byVirtualVisit Company)
• 질병별 진료 가이드라인의 준수 비중에 큰 차이가 있음
• 허리 통증, 연쇄상구균 인두염 등에 대해서는 가이드라인이 잘 준수됨
• 발목 통증, 요도 감염 등에 대해서는 가이드라인이 잘 준수되지 않음
• 발목 통증 환자에 추가적인 영상 의학데이터를 요구하는 경우는 15.5%에 불과
• 회사별 진료 가이드라인의 준수 비중에 큰 차이가 있음
• 전반적으로 50% 내외에 지나지 않으며,
• 30% 전후에 미치는 회사도 있음

67. 미국의 원격 진료는 얼마나 정확한가?
Choice, Transparency, Coordination, and Quality Among
Direct-to-Consumer Telemedicine Websites
and Apps Treating Skin Disease
Jack S. Resneck Jr, MD; Michael Abrouk; Meredith Steuer, MMS; Andrew Tam; Adam Yen; Ivy Lee, MD;
Carrie L. Kovarik, MD; Karen E. Edison, MD
IMPORTANCE Evidence supports use of teleconsultation for improving patient access to
dermatology. However, little is known about the quality of rapidly expanding
direct-to-consumer (DTC) telemedicine websites and smartphone apps diagnosing and
treating skin disease.
OBJECTIVE To assess the performance of DTC teledermatology services.
DESIGN AND PARTICIPANTS Simulated patients submitted a series of structured dermatologic
cases with photographs, including neoplastic, inflammatory, and infectious conditions, using
regional and national DTC telemedicine websites and smartphone apps offering services to
California residents.
MAIN OUTCOMES AND MEASURES Choice of clinician, transparency of credentials, clinician
location, demographic and medical data requested, diagnoses given, treatments
recommended or prescribed, adverse effects discussed, care coordination.
RESULTS We received responses for 62 clinical encounters from 16 DTC telemedicine
websites from February 4 to March 11, 2016. None asked for identification or raised concerns
about pseudonym use or falsified photographs. During most encounters (42 [68%]), patients
were assigned a clinician without any choice. Only 16 (26%) disclosed information about
clinician licensure, and some used internationally based physicians without California
licenses. Few collected the name of an existing primary care physician (14 [23%]) or offered
to send records (6 [10%]). A diagnosis or likely diagnosis was proffered in 48 encounters
(77%). Prescription medications were ordered in 31 of 48 diagnosed cases (65%), and
relevant adverse effects or pregnancy risks were disclosed in a minority (10 of 31 [32%] and
6 of 14 [43%], respectively). Websites made several correct diagnoses in clinical scenarios
where photographs alone were adequate, but when basic additional history elements (eg,
fever, hypertrichosis, oligomenorrhea) were important, they regularly failed to ask simple
relevant questions and diagnostic performance was poor. Major diagnoses were repeatedly
missed, including secondary syphilis, eczema herpeticum, gram-negative folliculitis, and
polycystic ovarian syndrome. Regardless of the diagnoses given, treatments prescribed were
sometimes at odds with existing guidelines.
CONCLUSIONS AND RELEVANCE Telemedicine has potential to expand access to high-value
health care. Our findings, however, raise concerns about the quality of skin disease diagnosis
Editor's Note
Author Affiliations: Department of
Dermatology, and Philip R. Lee
Institute for Health Policy Studies,
University of California, San Francisco
School of Medicine, San Francisco
(Resneck); University of California,
San Francisco School of Medicine,
Research
Original Investigation

68. Choice,Transparency, Coordination, and Quality Among
Direct-to-Consumer Telemedicine Websites
and Apps Treating Skin Disease
Spruce Modernizing Medicine

69. Choice,Transparency, Coordination, and Quality Among
Direct-to-Consumer Telemedicine Websites
and Apps Treating Skin Disease
• 미국의 16개의 원격 진료 서비스를 대상으로 피부과 검진 테스트
• 6가지 종류의 시뮬레이션 환자 사례 이용: 62번 진료
• 나이, 성별, 직업, 병력 등 상세한 상황을 구비
• 병변에 대한 사진도 3장씩
• 6가지 종류의 시뮬레이션 환자
• 다낭성 난소 증후군 (polycystic ovarian syndrome)
• 매독 (secondary syphilis)
• 그람음성 모낭염 (gram-negative folliculitis)
• 포진상 습진 (eczema herpeticum)
• 흑색종(melanoma)
• 지루성경화증 (seborrheic keratosis)

70. Choice,Transparency, Coordination, and Quality Among
Direct-to-Consumer Telemedicine Websites
and Apps Treating Skin Disease
• 68% 의 경우 환자가 의사에 대한 선택권 없음
• 26% 의 경우에만 의사의 면허 관련 정보가 공개
• 미국에는 환자가 속한 주의 면허를 가진 의사만 진료 가능
• 하지만, 일부 서비스의 경우 인도나 스웨덴 등 외국 의사를 연결
• 77% 의 경우에는 진단을 받음
• 65% 의 경우 처방까지 받음
• 하지만, 약의 부작용이나 임신 관련 위험에 대해 논의한 곳은 일부 (32%, 43%)
• 사진만으로 진단을 내릴 수 있는 질병의 경우 상대적으로 정확
• 추가 병력과 상세 정보가 필요한 경우에도 추가 정보를 요청하지 않는 경우 많음

71. • 염증성 여드름이 있는 여성 다낭성 난소 증후군 환자
• 다모증 (hypertrichosifs)이나 불규칙한 월경 주기 관련 질문을 하지 않은 경우
• 모든 의사들이 여드름은 진단했지만, 다모증 (hirsutism), 남성 호르몬 과잉
(androgen excess), 혹은 다낭성 난소 증후군을 진단해내지는 못함
• 12번의 진료 중에 대면 진료를 권고한 사례는 두 건 밖에 없었음
• 항생제와 레티노이드를 처방해준 곳은 있지만, 호르몬 치료 옵션에 대한 언급은 없음
• 제 2기 매독 (secondary syphilis) 환자
• 최근 열이 난 적이 있는지 질문하지도 않았고, 급성 발진에 대해 의심 하는 의사 없음
• 8명의 의사 중 7명은 건선으로 진단
• 한 명의 의사는 진단을 내리지 못하고 로컬 피부과를 권고
• 국부 스테로이드를 처방 받거나, 보습제를 쓰거나, 미지근한 물로 목욕을 권고

73. Feedback/Questions
• Email: yoonsup.choi@gmail.com
• Blog: http://www.yoonsupchoi.com
• Facebook: 최윤섭 디지털 헬스케어 연구소