1 / 96

Biomedical Informatics Year in Review

Biomedical Informatics Year in Review. Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine Vanderbilt University School of Medicine.

elita
Télécharger la présentation

Biomedical Informatics Year in Review

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Biomedical Informatics Year in Review Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine Vanderbilt University School of Medicine

  2. 2007 Year in ReviewContent for this session is at:http://dbmichair.mc.vanderbilt.edu/amia2007/including citation lists and linksand this PowerPoint

  3. Design for this Session • Modeled on American College of Physician “Update” sessions • Emphasis on ‘what it is’ and ‘why it is important’ • 1-2 examples of each in detail and others in synopsis • Audience interaction for each category of item discussed

  4. Source of Content for Session • Literature review of RCTs indexed by MeSH term “Medical Informatics”, “Telemedicine” & descendents or main MeSH term “Bioinformatics”, and publication date between November 2006 and October 2007 (n=42), further qualified by involvement of >100 providers or patients • Poll of American College of Medical Informatics fellows list

  5. Rebecca Jerome Andrew Balas Marion Ball Dominic Covvey Robert Dolin Sherrilynne Fuller Terri Hannan Brian Haynes Bill Hersh Betsy Humphreys George Hripcsak Bonnie Kaplan Denis Protti Don Simborg David States Paul Tang Mark Tuttle William Yasnoff It takes a village… Thanks to

  6. Topics • Representative New Literature • Notable Events – the ‘Top Ten’ list

  7. New Literature Highlights: Clinical Informatics • Unintended consequences of clinical information technology • Clinical Decision Support • Telemedicine • The practice of informatics

  8. New Literature Highlights: Bioinformatics and Computational Biology • Human Health and Disease • The practice of bioinformatics

  9. Unintended consequences of clinical information technology

  10. Unintended Consequences of Information Technologies • Reference • Linder et al., Arch Intern Med. 2007 Jul 9;167(13):1400-5. [Brigham & Women’s Hospital] • Title • Electronic health record use and the quality of ambulatory care in the United States. • Aim • Assess effects of Electronic Health Records on quality of care delivered in ambulatory settings • Methods • Retrospective, cross-sectional analysis of 17 quality measures from 2003-2004 National Ambulatory Medical Care Survey, correlated with use of EHRs.

  11. Unintended Consequences of Information Technologies • Reference • Linder et al., Arch Intern Med. 2007 Jul 9;167(13):1400-5. • Results • EHRs used in 18% of 1.8 billion visits • For 14 of 17 quality measures, fraction of visits where recommended best practice occurred was no different in EHR settings than manual records settings. • 2 better with EHR: avoiding benzodiazepines in depression, avoiding routine urinalysis • 1 worse with EHR: prescribing statins for hypercholesteremia (33% vs. 47%, p=0.01) • Conclusion • As implemented, EHRs not associated with better quality ambulatory care

  12. Unintended Consequences of Information Technologies • Reference • Linder et al., Arch Intern Med. 2007 Jul 9;167(13):1400-5. • Importance • Received disproportionate media attention due to reactionary message • Lost in the media hype: Less than 40% of EHR implementations have all elements important for effects on quality (e-prescribing, test ordering, results, clinical notes, decision support). • Best performance regardless of infrastructure was suboptimal (< 50% adherence to best practice).

  13. Clinical Decision Support for Providers • Reference • Raebel MA et al. J Am Geriatr Soc. 2007 Jul;55(7):977-85. [Kaiser Permanente, Denver, Colorado] • Title • Randomized trial to improve prescribing safety in ambulatory elderly patients. • Aim • To determine whether a computerized tool that alerted pharmacists when patients aged 65 and older were newly prescribed potentially inappropriate medications was effective in decreasing the proportion of patients dispensed these medications. • Methods • 60,000 pts randomized evenly; in intervention group pharmacists got e-alerts for 11 types of medication

  14. Clinical Decision Support for Providers • Reference • Raebel MA et al J Am Geriatr Soc. 2007 Jul;55(7):977-85. • Results • Over 1 year, 543 (1.8%) of intervention groups over age 65 were prescribed targeted meds, vs. 644 (2.2%) of usual care group (P= 0.002) • Statistically significant drop in use of amitryptiline and diazepam. • Importance • Adds to extensive literature on reducing Adverse Drug Effects via alerts and reminders • Targeting healthcare team members who can modify physician orders has beneficial effect • Note: Similar design study of meds during pregnancy reported in JAMIA July-Aug 2007

  15. Clinical Decision Support for Providers • Reference • Bailey T et al. Arch Intern Med. 2007 Mar 26;167(6):586-90. [Wash U., St. Louis] • Title • An intervention to improve secondary prevention of coronary heart disease. • Aim • Determine whether alerts sent to pharmacists, combined with ‘academic detailing’ by pharamacists, change physician prescribing behavior. • Methods • RCT randomizing patients with acute MI in hospital setting to alerts sent to pharmacist based on elevated troponin I levels. Pharmacists receiving alerts reviewed inpt meds list and communicated with care providers.

  16. Clinical Decision Support for Providers • Reference • Bailey T et al. Arch Intern Med. 2007 Mar 26;167(6):586-90. • Methods, cont’d • Outcome measures: proportion of Pts discharged on ASA, beta-blockers, ACE inhibitors, and statins. • Results • Improved compliance with ACE and statin guidelines, no impact on beta blockers or ASA. • When all 4 classes of drugs considered together, 84% (305 of 365 eligible) intervention vs. 70% (343 of 488) in control received recommended therapy (P<0.001) • Importance • Routing messages to pharmacists, combined with academic detailing, provides useful model for systematic improvements in care

  17. Clinical Decision Support • Reference • Chaudhry R et al. Arch Intern Med. 2007 Mar 26;167(6):606-11. [Mayo Clinic] • Title • Web-based proactive system to improve breast cancer screening: a randomized controlled trial. • Aim • Improve mammography screening rates using alerts and reminders directed at appointment secretaries. • Methods • Web-based preventive care reminder system created to alert staff making appointments about screening mammography. • 6600 patients signed up for study, randomized to usual care or use of system that sent a letter or e-mail message in advance of screening data, and provided response status to appt. secretary.

  18. Clinical Decision Support • Reference • Chaudhry R et al. Arch Intern Med. 2007 Mar 26;167(6):606-11. • Results • Screening rate for annual mammography was 64% in intervention group vs. 55% in control group (P<.001) • No difference in intervention vs. control on any other preventive service. • Conclusion • Practice re-design to send reminder messages to appointment secretary rather than to physician provider improved compliance with preventive care services guidelines. • Importance • More evidence that care team members other than physicians are better targets for information interventions designed to increase consistency of care.

  19. Clinical Decision Support for Providers • 3 RCTs on Tobacco Cessation • Unrod et al. Randomized controlled trial of a computer-based, tailored intervention to increase smoking cessation counseling by primary care physicians. J Gen Intern Med. 2007 Apr;22(4):478-84. [Mt. Sinai, NYC] • Wadland WC et al Practice-based referrals to a tobacco cessation quit line: assessing the impact of comparative feedback vs general reminders. Ann Fam Med. 2007 Mar-Apr;5(2):135-42. [Michigan State] • Bentz CJ et al. Provider feedback to improve 5A's tobacco cessation in primary care: a cluster randomized clinical trial. Nicotine Tob Res. 2007 Mar;9(3):341-9. [Providence/St. Vincent, Portland, OR]

  20. Clinical Decision Support for Providers • Methods • Mt. Sinai study: Computer tailored one page summary to physician and patient re: Smoking Cessation Guidelines (5A’s: Assess, Advise, Assist-written, Assist-referral, Arrange). Measured adherence to 5A’s guidelines, and smoking cessation success at 6 months • MSU study: Provider specific feedback on smoking cessation referrals vs. general reminders. Measured referral numbers and quit rate at 18 months. • Providence Portland study: Provider specific monthly feedback reports vs. no feedback from state tobacco quitline.

  21. Clinical Decision Support for Providers • Results • All three studies showed statistically improved compliance with 5A’s guidelines by providers and increased in referrals for cessation help (Odds ratios 2.7 – 5) • All showed increased numbers of patients quitting smoking at borderline statistical significance levels vs. control groups • Conclusion • Modest positive impacts of proactive (tailored information sheet) and retrospective (regular feedback reports on numbers of referrals) smoking cessation interventions • Interventions judged to be cost effective and are continuing • Importance • Approximately the same results in a CDSS area (smoking cessation) from three different sites with similar intervention and process/outcomes measures • Information intervention necessary but not sufficient to achieve optimal outcomes

  22. Clinical Decision Support for Providers • Reference • Rothschild JM, et. al. Transfusion. 2007 Feb;47(2):228-39. [Brigham and Women’s, Boston] • Title • Assessment of education and computerized decision support interventions for improving transfusion practice. • Aim • Reduce overuse of blood products via a CDSS intervention. • Methods • Random assignment of junior house officers to receiving education and CPOE-based decision support at time of ordering blood products. • Orders classified as DS-agree or DS-disagree • DS-disagree charts reviewed for appropriateness

  23. Clinical Decision Support for Providers • Reference • Rothschild JM, et. al. Transfusion. 2007 Feb;47(2):228-39. • Results • Inappropriate non-emergent transfusion at baseline was 72% in both interventional and control groups. • Improved to 63% with conventional education. • DS intervention group continued to improve to 59%. • Physicians accepted 14% of DS-recommended orders, especially recommendations to increase dose (73%). • Conclusion • Education and CDSS had statistically significant reduction of inappropriate transfusion orders, though residual amount remained high. • Impact • Don’t be sanguine about expecting CDSS to change prescribing

  24. Clinical Decision Support for Providers • Reference • Kheterpal et al. Anesth Analg. 2007 Mar;104(3):592-7. [Univ. Michigan] • Title • Electronic reminders improve procedure documentation compliance and professional fee reimbursement. • Aim • To evaluate alert system to improve documentation of care for increased reimbursement. • Methods • Automated system scanned EMR for surgical procedures using arterial catheters, sent e-mail and/or pager reminder to provider if no procedure note about catheter placement. • Residents and CRN anesthetists randomized to msg or no msg

  25. Clinical Decision Support for Providers • Reference • Kheterpal et al. Anesth Analg. 2007 Mar;104(3):592-7. • Results • Baseline compliance rate 80% • During 2 month study, 88% of intervention group completed documentation requirements vs. 75% of control. • After RCT ended, all staff got reminder and compliance rose to 98% • Professional fee reimbursement projected to increase $40,500 over 12 months. • Conclusion • Documentation deficiencies amenable to alerts/reminders • Impact • ADSS works in a fashion similar to CDSS, perhaps better

  26. Clinical Decision Support for Patients • Reference • Thompson RG et al. Qual Saf Health Care. 2007 Jun;16(3):216-23. [Univ Newcastle, UK] • Title • A patient decision aid to support shared decision-making on anti-thrombotic treatment of patients with atrial fibrillation: randomised controlled trial. • Aim • To determine the efficacy of a computerised decision aid in patients with atrial fibrillation making decisions on whether to take warfarin or aspirin therapy. • Methods • 109 Pts with a. fib randomized to computerized DSS vs. pamphlet on ASA vs. warfarin • Outcomes: decision conflict scale, and therapy choice

  27. Clinical Decision Support for Patients • Reference • Thompson RG et al. Qual Saf Health Care. 2007 Jun;16(3):216-23. • Results • Decision conflict lower in CDSS group (ie., happier with decision made) • CDSS Pts agreed to start coumadin only 25% of time when recommended by physician, vs. 94% of printed guidelines group • Conclusion • CDSS for patients can empower them to feel comfortable about decisions that are medically suboptimal • Impact • Increased understanding mediated by CDSS systems is a double edged sword

  28. Clinical Decision Support for Patients • Reference • Saitz R et al. Alcohol Alcohol. 2007 Jan-Feb;42(1):28-36. [Boston Univ.] • Title • Screening and brief intervention online for college students: the ihealth study. • Aim • To test the feasibility of online alcohol screening and brief intervention (BI) by comparing (i) two approaches to inviting all students to be screened, and (ii) a minimal versus a more extensive BI. • Methods • All freshman students(4008) sent one of two e-mail invitations to participate in alcohol counseling online application: either invitation for general health assessment, or invitation for alcohol assessment

  29. Clinical Decision Support for Patients • Reference • Saitz R et al. Alcohol Alcohol. 2007 Jan-Feb;42(1):28-36 • Methods, cont’d • Participants with unhealthy alcohol use randomly assigned to minimal or more extensive information intervention • Follow-up after one month for those receiving interventions • Results • 55% of students completed online screening, no difference if invitation specifically mentioned alcohol vs. general health. • 37% of male students and 26% of female students had unhealthy alcohol use. • More extensive intervention caused more students to expression interest in changing behavior • 75% of intervention completed second assessment, and of these unhealthy behaviors reduced by 33% in women and 15% in men.

  30. Clinical Decision Support for Patients • Reference • Saitz R et al. Alcohol Alcohol. 2007 Jan-Feb;42(1):28-36 • Conclusion • Over half of freshman class reached by e-mail and completed health risk assessment • Mention of alcohol not a deterrent to participation • Brief online intervention appeared to have favorable short term impact. • Impact • Contibutes to literature on self-reporting of health conditions traditionally considered ‘stigmatizing’

  31. Clinical Decision Support for Patients • 2 RCTs on Smoking Cessation • Strecher VJ et al. Moderators and mediators of a web-based computer-tailored smoking cessation program among nicotine patch users. Nicotine Tob Res. 2006 Dec;8 Suppl 1:S95-101. [Univ. Michigan] • Japuntich et al. Smoking cessation via the internet: a randomized clinical trial of an internet intervention as adjuvant treatment in a smoking cessation intervention. Nicotine Tob Res. 2006 Dec;8 Suppl 1:S59-67. [Univ Wisconsin Madison]

  32. Clinical Decision Support for Patients • Methods • Michigan study: 3971 smokers who purchased nicotine patches randomized to standard web-based materials vs. tailored web intervention.Measured abstinence at 12 weeks. • Wisconsin study: 284 smokers randomized to bupropion + counseling +/- access to an online support group and information site. Measured abstinence at 12 weeks and 24 weeks.

  33. Clinical Decision Support for Patients • Results • Michigan study found tailored program more effective by number abstinent in certain subgroups (children at home, frequent alcohol use, tobacco-related illness present) but not significant for groups as whole • Wisconsin study found use of online resources correlated with smoking abstinence, but no overall difference in abstinence between groups. • Conclusion • Targeted information interventions help a subset of smokers to quit who would not otherwise • Importance • Addiction interventions are a difficult area of therapeutics, for which informatics has a modest role to play

  34. New CDSS RCTs showing no difference for intervention vs. control • Curtis et al. Challenges in improving the quality of osteoporosis care for long-term glucocorticoid users: a prospective randomized trial. Arch Intern Med. 2007 Mar 26;167(6):591-6. • Glassman et al. The utility of adding retrospective medication profiling to computerized provider order entry in an ambulatory care population. J Am Med Inform Assoc. 2007 Jul-Aug;14(4):424-31. • Schapira et al. Decision-making at menopause: a randomized controlled trial of a computer-based hormone therapy decision-aid. Patient Educ Couns. 2007 Jul;67(1-2):100-7. • Tuil et al. Empowering patients undergoing in vitro fertilization by providing Internet access to medical data. Fertil Steril. 2007 Aug;88(2):361-8.

  35. Clinical Decision Support Questions and Comments

  36. Telemedicine 12 new RCTs published November 2006 – October 2007 • 3 chronic airways disease • 2 psychiatric care • 2 diabetes care • 2 imaging: dermatology and ophthalmology • 1 each prostate cancer, cardiac rehab, hypertension

  37. Telemedicine • 3 RCTs on airways disease • Chan DS et al. Internet-based home monitoring and education of children with asthma is comparable to ideal office-based care: results of a 1-year asthma in-home monitoring trial. Pediatrics. 2007 Mar;119(3):569-78. [Tripler Army Medical Center, Honolulu] • Jan RL et al. An internet-based interactive telemonitoring system for improving childhood asthma outcomes in Taiwan. Telemed J E Health. 2007 Jun;13(3):257-68. [National Cheng Kung University, Taiwan] • Whitten P, Mickus M. Home telecare for COPD/CHF patients: outcomes and perceptions. J Telemed Telecare. 2007; 13(2):69-73. [Michigan State University]

  38. Telemedicine • Methods • Tripler study: 120 asthma pts age 6-17 randomized to same clinical pathway with follow-up either via office visit or website interaction. Measured medication adherence, PFTs • Taiwan study: 88 asthma pts randomized to either Internet care guidance and spirometry reporting, or printed materials and spirometry diary. Measured self-reported symptoms, spirometry results, quality of life, knowledge of disease • Michigan State study: 161 pts with COPD/CHF randomized to home care visits in person or via telemedicine unit. Measured SF-36, patient perceptions, physiologic status at beginning and end of study.

  39. Telemedicine • Results • Taiwanese study found telemedicine group had better adherence to meds, better PFTs. • Other two studies found clinical equivalence of telemedicine and face-to-face visits at home or office • Impact • Adds to substantial literature showing therapeutic equivalency of telemedicine vs. in person monitoring of chronic airways disease.

  40. Telepsychiatry • 2 RCTs • Fortney JC et al. A randomized trial of telemedicine-based collaborative care for depression. J Gen Intern Med. 2007 Aug;22(8):1086-93. Epub 2007 May 10. [VA Health Svcs Research, Little Rock AR] • O'Reilly R. Is telepsychiatry equivalent to face-to-face psychiatry? Results from a randomized controlled equivalence trial. Psychiatr Serv. 2007 Jun;58(6):836-43. [Regional Mental Healthcare, London, Ontario, Canada]

  41. Telepsychiatry • Methods • VA study: 395 pts with moderately severe depression followed at small VA community clinics without psychiatrists. Measured med adherence, treatment response, quality of life, pt satisfaction with treatment. • Canadian study: 495 pts referred for initial psych consultation randomized to telepsych interview or face-to-face consult. Measured health status, patient satisfaction, costs

  42. Telepsychiatry • Results • VA study: supplementing usual care with telemedicine psych consultation improved medication adherence and therapeutic response. Also found higher patient satisfaction, and better quality of life measures in intervention group. • Canadian study found equivalence for telepsychiatry outcomes and face to face outcomes, with 10% decrease in overall costs for telemedicine based care. • Impact • Telemedicine technologies can extend subspecialty support to primary care settings • Telepsychiatry equivalent to F2F as perceived by Pts

  43. Tele-imaging • 2 RCTs • Conlin PR et al. Nonmydriatic teleretinal imaging improves adherence to annual eye examinations in patients with diabetes. J Rehabil Res Dev. 2006 Sep-Oct;43(6):733-40. [Boston VA] • Pak H, et al. Store-and-forward teledermatology results in similar clinical outcomes to conventional clinic-based care. J Telemed Telecare. 2007;13(1):26-30. [Army TATRC, Fort Dietrick MD]

  44. Tele-imaging • Methods • VA study: 448 pts randomized to annual dilated eye exam vs. non-dilated screening image with remote interpretation, followed by in person consult if indicated. Measured correspondence of remote and in person findings, and adherence to annual exam schedule • Army study: 776 pts randomized to face-to-face dermatology consult vs. telemedicine via store and forward imaging + text description

  45. Tele-imaging • Results • VA study: Strong but not perfect correlation of tele-imaging with dilated in person exam. Improvement in compliance with annual screening. Patient acceptance high. • Army study found equivalence of diagnosis and ongoing monitoring of response to therapy for teledermatology and in person care. • Impact • Store and forward telemedicine lends itself well to specialties where static images are keys to diagnosis and follow-up

  46. 2006-7 Telemedicine RCTs • Continue 30+ year history of showing equivalence of telemedicine for selected types of home monitoring, chronic disease follow-up, and visual diagnosis • Only 1 of 12 addressed cost vs. benefit • Leave unaddressed principal historical impediments to telemedicine acceptance: reimbursement, licensure, liability

  47. Telemedicine Questions and Comments

  48. Practice of Informatics • Reference • Beebe TJ et al. Health Serv Res. 2007 Jun;42(3 Pt 1):1219-34. [Mayo Clinic] • Title • Mixing web and mail methods in a survey of physicians. • Aim • To assess the effects of two different mixed-mode (mail and web survey) combinations on response rates, response times, and nonresponse bias in a sample of primary care and specialty internal medicine physicians. • Methods • Randomized 500 physicians at Mayo clinic to receiving either a mailed paper survey on EMR, or web link for online survey, with cross over.

  49. Practice of Informatics • Reference • Beebe TJ et al. Health Serv Res. 2007 Jun;42(3 Pt 1):1219-34. • Results • Overall response rate higher with mailed survey sent first than web link sent first (70% vs. 63%). • Results obtained 2 days faster with web survey • Key outcome variables no different in paper vs. web survey methods • Impact • Some insight on approaches to surveying physicians in large institutional setting

More Related