육성, 연결하고 투자합니다. 발굴 • 세상을 바꿀 수 있는 혁신적인 헬스케어 스타트업 및 예비 창업팀을 발굴합니다. • 발굴을 위해 DHP Office Hour, 해커톤, 자체 행사 개최 등의 다방면의 채널을 활용합니다. 육성 • 의료/헬스케어 전문가들로 이루어진 파트너 및 자문가들이 초기 스타트업을 멘토링합니다. • 사업 개발, 아이템 검증, 임상 연구, 인허가 관련 자문 등 전방위적으로 지원합니다. 투자 • 초기 스타트업 및 예비 창업팀에게 정해진 원칙에 따라 지분 투자를 집행합니다. • 스타트업을 성장시켜 지분 가치의 상승에 따라서 재무적 수익을 추구합니다. 연결 • 초기 스타트업을 병원, 규제기관, 보험사, VC, 대학 등 다양한 이해관계자들과 연결합니다. • 파트너와 자문가들의 네트워크를 적극 활용하여 스타트업을 의료계 이너서클로 끌어들입니다.
전문 의료 영역도 아닌 것 예) 운동, 영양, 수면 디지털 헬스케어 건강 관리 중에 디지털 기술이 사용되는 것 예) 사물인터넷, 인공지능, 3D 프린터, VR/AR 모바일 헬스케어 디지털 헬스케어 중 모바일 기술이 사용되는 것 예) 스마트폰, 사물인터넷, SNS 개인 유전정보분석 암유전체, 질병위험도, 보인자, 약물 민감도 예) 웰니스, 조상 분석 헬스케어 관련 분야 구성도(ver 0.6) 의료 질병 예방, 치료, 처방, 관리 등 전문 의료 영역 원격의료 원격 환자 모니터링 원격진료 전화, 화상, 판독 디지털 치료제 당뇨 예방 앱 중독 치료 앱 ADHD 치료게임
분야 투자 급증 •2015-2016년 총 22건의 deal (=2010-2014년의 5년간 투자 건수와 동일) •Merck 가 가장 활발: 2009년부터 Global Health Innovation Fund 를 통해 24건 투자 ($5-7M) •GSK 의 경우 2014년부터 6건 (via VC arm, SR One): including Propeller Health
Valuation $1.8B $3.1B $3.2B $1B $1B 38 healthcare unicorns valued at $90.7B Global VC-backed digital health companies with a private market valuation of $1B+ (7/26/19) UNITED KINGDOM $1.5B MIDDLE EAST $1B Valuation ISRAEL $7B $1B $1.2B $1B $1.65B $1.8B $1.25B $2.8B $1B $1B $2B Valuation $1.5B UNITED STATES GERMANY $1.7B $2.5B CHINA ASIA $3B $5.5B Valuation $5B $2.4B $2.4B France $1.1B $3.5B $1.6B $1B $1B $1B $1B CB Insights, Global Healthcare Reports 2019 2Q
breast cancer with malignant pleural effusions and empyema. The patient timeline at the top of the ﬁgure contains circles for every time-step for which at least a single token exists for the patient, and the horizontal lines show the data type. There is a close-up view of the most recent data points immediately preceding a prediction made 24 h after admission. We trained models for each data type and highlighted in red the tokens which the models attended to—the non-highlighted text was not attended to but is shown for context. The models pick up features in the medications, nursing ﬂowsheets, and clinical notes relevant to the prediction Scalable and accurate deep learning with electronic health A Rajkomar et al. 6 미국 병원, “환자의 재입원율을 예측해서 패널티를 줄이고 싶다”
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 Noom, Inc., New York, New York, USA Correspondence to Dr Andreas Michaelides; email@example.com 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 by other means (text and emails,6 nurse support,7 DVDs,8 community care9) have also been successful in promoting behavior change, weight loss, and glycemic control. One study10 adapted the NDPP to deliver the ﬁrst part of the curriculum in-person and the remaining sessions through a mobile app, and found 6.8% weight loss at 5 months. Mobile health poses a promising means of delivering prechronic and chronic care,11 12 and provides a scalable, 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 Health, a mobile-based application that deli- vers structured curricula with human coaches. An email or regular mail invitation with information describing the study was sent to potential participants based on an elevated HbA1c status found in their medical records, reﬂecting a diagnosis of prediabetes. Interested participants were assigned to a virtual Centers for Disease Control and Prevention (CDC)-recognized NDPP master’s level coach. 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. BMJ Open Diabetes Research and Care 2016;4:e000264. doi:10.1136/bmjdrc-2016-000264 1 Open Access Research group.bmj.com on April 27, 2017 - Published by http://drc.bmj.com/ Downloaded from •Noom Coach 앱이 체중 감량을 위해서 효과적임을 증명 •완전히 모바일로 이뤄진 최초의 당뇨병 예방 연구 •43명의 전당뇨단계에 있는 과체중이나 비만 환자를 대상 •24주간 Noom Coach의 앱과 모바일 코칭을 제공 •그 결과 64% 의 참가자들이 5-7% 의 체중 감량 효과 •84%에 달하는 사람들이 마지막까지 이 6개월 간의 프로그램에 참여
application in those with overweight and obesity Sang Ouk Chin1,*, Changwon Keum2,*, Junghoon Woo3, Jehwan Park2, Hyung Jin Choi4, Jeong-taek Woo5 & Sang Youl Rhee5 A discrepancy exists with regard to the effect of smartphone applications (apps) on weight reduction due to the several limitations of previous studies. This is a retrospective cohort study, aimed to investigate the effectiveness of a smartphone app on weight reduction in obese or overweight individuals, based on the complete enumeration study that utilized the clinical and logging data entered by Noom Coach app users between October 2012 and April 2014. A total of 35,921 participants were included in the analysis, of whom 77.9% reported a decrease in body weight while they were using the app (median 267 days; interquartile range = 182). Dinner input frequency was the most important factor for successful weight loss (OR = 10.69; 95% CI = 6.20–19.53; p < 0.001), and more frequent input of weight significantly decreased the possibility of experiencing the yo-yo effect (OR = 0.59, 95% CI = 0.39–0.89; p < 0.001). This study demonstrated the clinical utility of an app for successful weight reduction in the majority of the app users; the effects were more significant for individuals who monitored their weight and diet more frequently. Obesity is a global epidemic with a rapidly increasing prevalence worldwide1,2. As obese individuals experience significantly higher mortality when compared with the non-obese population3,4, this phenomenon poses a sig- nificant socioeconomic burden, necessitating strategies to manage overweight and prevent obesity5. Although numerous interventions such as life style modification including exercise6–10, and pharmacotherapy11–13 have been shown effective for both the prevention and treatment of obesity, some of these methods were found to have a limitation which required substantial financial inputs and repeated time-consuming processes14,15. Recently, as the number of smartphone users is increasing dramatically, many investigators have attempted to implement smartphone applications (app) for health promotion16–19. Consequently, many smartphone apps have demonstrated at least partial efficacy in promoting successful weight reduction according to the number of previous studies20–24. However, due to the limitations associated with study design such as small-scale studies and short investigation periods, a discrepancy exists with regard to the effect of apps on weight reduction20,21,23. Even systemic reviews which investigated the efficacy of mobile apps for weight reduction reported more or less inconsistent results; Flores Mateo et al. reported a significant weight loss by mobile phone app intervention when compared with control groups25 whereas Semper et al. reported that four of the six studies included in the analysis showed no significant difference of weight reduction between comparison groups26. Thus, the aim of this study was to investigate the effectiveness of a smartphone app on weight reduction in obese or overweight individuals Recei e : 0 pri 016 Accepte : 15 eptem er 016 Pu is e : 0 o em er 016 OPEN •스마트폰 앱이 체중 감량에 도움을 줄 수 있는가? •2012년부터 2014년 까지 최소 6개월 이상 애플리케이션을 사용 •80여 국가(미국, 독일, 한국, 영국, 일본 등)에서 모집된 35,921명의 데이터 •애플리케이션 평균 사용기간은 267일 Chin et al. Sci Rep 2016
Percentages (and 95% CIs) of participants achieving < 5%, 5–10%, 10–15%, 15–20% and > 20% weight loss relative to baseline at the end of the 6-month trial period. Data are reported as the mean ± SD. Univariate Linear Regression p-value Multivariate Linear Regression p-value β (95% CI) β (95% CI) Gender (male) 0.60 (0.54, 0.66) < 0.001 0.71 (0.65, 0.77) < 0.001 Age 0.01 (0.008, 0.013) < 0.001 − 0.026 (− 0.03, − 0.02) < 0.001 Follow-up Days − 0.001 (− 0.001, − 0.001) < 0.001 0.00 (0.00, 0.00) 0.886 Baseline BMI 0.146 (0.143, 0.150) < 0.001 0.165 (0.161, 0.168) < 0.001 Successful weight reduction and maintenance by using a smartphone application in those with overweight and obesity Chin et al. Sci Rep 2016 •대상자의 약 77.9%에서 성공적인 체중감량 효과를 확인 •이 중 23%는 본인 체중의 10% 이상 감량에 성공 •앱의 사용이 약물 치료 등 다른 비만 관리 기법에 비해 체중 감량 효과가 뒤쳐지지 않음
effectiveness, reproducibility, and durability of tailored mobile coaching on diabetes management in policyholders: A randomized, controlled, open-label study Da Young Lee1,2, Jeongwoon Park3, Dooah Choi3, Hong-Yup Ahn4, Sung-Woo Park1 & Cheol-Young Park 1 This randomized, controlled, open-label study conducted in Kangbuk Samsung Hospital evaluated the effectiveness, reproducibility, and durability of tailored mobile coaching (TMC) on diabetes management. The participants included 148 Korean adult policyholders with type 2 diabetes divided into the Intervention-Maintenance (I-M) group (n = 74) and Control-Intervention (C-I) group (n = 74). Intervention was the addition of TMC to typical diabetes care. In the 6-month phase 1, the I-M group received TMC, and the C-I group received their usual diabetes care. During the second 6-month phase 2, the C-I group received TMC, and the I-M group received only regular information messages. After the 6-month phase 1, a significant decrease (0.6%) in HbA1c levels compared with baseline values was observed in only the I-M group (from 8.1 ± 1.4% to 7.5 ± 1.1%, P < 0.001 based on a paired t-test). At the end of phase 2, HbA1c levels in the C-I group decreased by 0.6% compared with the value at 6 months (from 7.9 ± 1.5 to 7.3 ± 1.0, P < 0.001 based on a paired t-test). In the I-M group, no changes were observed. Both groups showed significant improvements in frequency of blood-glucose testing and exercise. In conclusion, addition of TMC to conventional treatment for diabetes improved glycemic control, and this effect was maintained without individualized message feedback. The incidence and prevalence of type 2 diabetes are increasing rapidly worldwide, and the disease is expected to affect 439 million adults by 20301. Previous large clinical trials indicated that adequate glycemic control con- tributed to a reduction in both microvascular and macrovascular complications as well as mortality rates due to diabetes2,3. Complications from diabetes result in greater expenditure and reduced productivity. Therefore, it is a socioeconomic concern4,5. Adequate glycemic control is important not only as an individual health problem, but also as a challenge to healthcare systems worldwide. However, approximately 40% of subjects with diabetes in the United States do not meet the recommended target for glycemic control, low-density lipoprotein cholesterol (LDL-C) level, or blood pressure (BP)6. In Korea, glycated hemoglobin (HbA1c) levels for nearly half of diabetic patients were above 7.0%7. Although successful diabetes care requires therapeutic lifestyle modification in addition to proper medica- tion8–10, only 55% of individuals with type 2 diabetes receive diabetes education from healthcare professionals11, and 16% report adhering to recommended self-management activities9. Multifaceted professional inter- ventions are needed to support patient efforts for behavior change including healthy lifestyle choices, disease self-management, and prevention of diabetes complications10. 1Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea. 2Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University College of Medicine, Seoul, Republic of Korea. 3Huraypositive Inc. Sinsa-dong, Gangnam-gu, Seoul, Republic of Korea. 4Department of Statistics, Dongguk University-Seoul, Seoul, Republic of Korea. Correspondence and requests for materials should be addressed to C.-Y.P. (email: cydoctor@ chol.com) Received: 29 November 2017 Accepted: 15 February 2018 Published: xx xx xxxx OPEN e.com/scientificreports/ Figure 3. Changes in means and standard errors of glycated hemoglobin (H study period. HbA1c levels of the C-I group who received TMC during phase 2 of the study decreased by 0.6% compared to phase 1 levels. In the I-M group, initial improvement in HbA1c levels at 3 months continued until 12 months. Consequently, HbA1c levels in both the C-I and I-M groups decreased signiﬁcantly compared to baseline values over the 12-month study period.
16p11.2 deletion using adaptive ‘video game’ technology: a pilot study JA Anguera1,2, AN Brandes-Aitken1, CE Rolle1, SN Skinner1, SS Desai1, JD Bower3, WE Martucci3, WK Chung4, EH Sherr1,5 and EJ Marco1,2,5 Assessing cognitive abilities in children is challenging for two primary reasons: lack of testing engagement can lead to low testing sensitivity and inherent performance variability. Here we sought to explore whether an engaging, adaptive digital cognitive platform built to look and feel like a video game would reliably measure attention-based abilities in children with and without neurodevelopmental disabilities related to a known genetic condition, 16p11.2 deletion. We assessed 20 children with 16p11.2 deletion, a genetic variation implicated in attention deﬁcit/hyperactivity disorder and autism, as well as 16 siblings without the deletion and 75 neurotypical age-matched children. Deletion carriers showed signiﬁcantly slower response times and greater response variability when compared with all non-carriers; by comparison, traditional non-adaptive selective attention assessments were unable to discriminate group differences. This phenotypic characterization highlights the potential power of administering tools that integrate adaptive psychophysical mechanics into video-game-style mechanics to achieve robust, reliable measurements. Translational Psychiatry (2016) 6, e893; doi:10.1038/tp.2016.178; published online 20 September 2016 INTRODUCTION Cognition is typically associated with measures of intelligence (for example, intellectual quotient (IQ)1), and is a reﬂection of one’s ability to perform higher-level processes by engaging speciﬁc mechanisms associated with learning, memory and reasoning. Such acts require the engagement of a speciﬁc subset of cognitive resources called cognitive control abilities,2–5 which engage the underlying neural mechanisms associated with atten- tion, working memory and goal-management faculties.6 These abilities are often assessed with validated pencil-and-paper approaches or, now more commonly with these same paradigms deployed on either desktop or laptop computers. These approaches are often less than ideal when assessing pediatric populations, as children have highly varied degree of testing engagement, leading to low test sensitivity.7–9 This is especially concerning when characterizing clinical populations, as increased performance variability in these groups often exceeds the range of testing sensitivity,7–9 limiting the ability to characterize cognitive deﬁcits in certain populations. A proper assessment of cognitive control abilities in children is especially important, as these abilities allow children to interact with their complex environment in a goal-directed manner,10 are predictive of academic performance11 and are correlated with overall quality of life.12 For pediatric clinical populations, this characterization is especially critical as they are often assessed in an indirect fashion through intelligence quotients, parent report questionnaires13 and/or behavioral challenges,14 each of which fail to properly characterize these abilities in a direct manner. One approach to make testing more robust and user-friendly is to present material in an optimally engaging manner, a strategy particularly beneﬁcial when assessing children. The rise of digital health technologies facilitates the ability to administer these types of tests on tablet-based technologies (that is, iPad) in a game-like manner.15 For instance, Dundar and Akcayir16 assessed tablet- based reading compared with book reading in school-aged children, and discovered that students preferred tablet-based reading, reporting it to be more enjoyable. Another approach used to optimize the testing experience involves the integration of adaptive staircase algorithms, as the incorporation of such appro- aches lead to more reliable assessments that can be completed in a timely manner. This approach, rooted in psychophysical research,17 has been a powerful way to ensure that individuals perform at their ability level on a given task, mitigating the possi- bility of ﬂoor/ceiling effects. With respect to assessing individual abilities, the incorporation of adaptive mechanics acts as a normalizing agent for each individual in accordance with their underlying cognitive abilities,18 facilitating fair comparisons between groups (for example, neurotypical and study populations). Adaptive mechanics in a consumer-style video game experi- ence could potentially assist in the challenge of interrogating cognitive abilities in a pediatric patient population. This synergistic approach would seemingly raise one’s level of engagement by making the testing experience more enjoyable and with greater sensitivity to individual differences, a key aspect typically missing in both clinical and research settings when testing these populations. Video game approaches have previously been utilized in clinical adult populations (for example, stroke,19,20 1Department of Neurology, University of California, San Francisco, San Francisco, CA, USA; 2Department of Psychiatry, University of California, San Francisco, San Francisco, CA, USA; 3Akili Interactive Labs, Boston, MA, USA; 4Department of Pediatrics, Columbia University Medical Center, New York, NY, USA and 5Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA. Correspondence: JA Anguera or EJ Marco, University of California, San Francisco, Mission Bay – Sandler Neurosciences Center, UCSF MC 0444, 675 Nelson Rising Lane, Room 502, San Francisco, CA 94158, USA. E-mail: firstname.lastname@example.org or email@example.com Received 6 March 2016; revised 13 July 2016; accepted 18 July 2016 Citation: Transl Psychiatry (2016) 6, e893; doi:10.1038/tp.2016.178 www.nature.com/tp Figure 2. Project: EVO selective attention performance. (a) EVO single- and multi-tasking response time performance f non-affected siblings and non-affected control groups). (b) EVO multi-tasking RT. (c) Visual search task performance Characterizing cognitive control abilities in child JA Anguera et al •Project EVO (게임)을 통해서, •아동 집중력 장애(attention disorder) 관련 특정 유전형 carrier 를 골라낼 수 있음 •게임에서의 Response Time을 기준으로 carrier vs. non-carrier 간 유의미한 차이
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). In the USA, all clinical laboratory testing conducted on humans 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 1Department of Genetics and Genomic Sciences, 2Icahn Institute for Genomics and Multiscale Biology, 3Harris Center for Precision Wellness, 4Department of Hematology and Medical Oncology, and 5Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, New York, USA. 6Hope 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
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 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 Figure 1: Overview of the CGM data communication bridge architecture. BRIEF COMMUNICATION Kumar R B, et al. J Am Med Inform Assoc 2016;0:1–6. doi:10.1093/jamia/ocv206, Brief Communication by guest on April 7, 2016 http://jamia.oxfordjournals.org/ Downloaded from JAMIA 2016 Remote Patients Monitoring via Dexcom-HealthKit-Epic-Stanford 제1형 당뇨환자의 혈당을 연속혈당계로 측정하여, 아이폰, EMR을 거쳐 스탠퍼드 대학병원의 의료진이 모니터링한다.
new-age payer’ or ‘a new-age PBM(Pharmacy Benefit Management)’ •기존의 헬스케어 산업의 범주를 뭉개버리는 스타트업 •Oscar는 기존의 payer 역할에서 provider 까지 진출하고 있음 •23andMe 는 유전정보 분석회사에서 제약회사도 되고 있음 •Ginger.io 는 B2B 헬스케어 스타트업에서 provider도 되었음 어떠한 스타트업을 찾고 있는가? Health 2.0 2017 Annual Conference VC’s Talk New Trends in Investing