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Biomedical Informatics Year in Review Notable publications and events in Informatics since the 2008 AMIA Symposium Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine Vanderbilt University School of

Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

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Biomedical Informatics Year in Review Notable publications and events in Informatics since the 2008 AMIA Symposium. Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine Vanderbilt University School of Medicine. - PowerPoint PPT Presentation

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Page 1: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Biomedical Informatics Year in Review

Notable publications and events in Informatics since the 2008 AMIA Symposium

Daniel R. Masys, MD

Professor and Chair

Department of Biomedical Informatics

Professor of Medicine

Vanderbilt University School of Medicine

Page 2: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Content for this session is at:

http://dbmichair.mc.vanderbilt.edu/amia2009/

including citation lists and linksand this PowerPoint

Page 3: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

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

Page 4: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Source of Content for Session

Literature review of RCTs indexed by MeSH term “Medical Informatics”, “Telemedicine” & descendents or main MeSH term “Bioinformatics”, and Entrez date between November 2008 and October 2009 further qualified by involvement of >100 providers or patients

Poll of American College of Medical Informatics fellows list

Page 5: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Thanks to: Rebecca Jerome David Bates Don Detmer Ken Goodman Bill Hersh George Hripcsak Betsy Humphreys

It takes a (global) village…

Kevin Johnson Bonnie Kaplan Nancy Lorenzi Dean Sittig Bill Stead Jan Talmon

Page 6: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Session components

Representative New Literature Notable Events – the ‘Top Ten’ list

Page 7: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

New Literature Highlights: Clinical Informatics

Clinical Decision SupportTelemedicineThe practice of informatics

Page 8: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

New Literature Highlights: Bioinformatics and Computational Biology

Human Health and DiseaseThe practice of bioinformatics

Page 9: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support

25 new RCTs published meeting search criteria

November 2008 – October 2009

Page 10: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Med. 2009 Apr 27;169(8):771-80.[Brigham & Women’s, Boston MA]

Schnipper JL et. al.. Arch Intern Title

Effect of an electronic medication reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial.

Aim To measure the impact of an information technology-based

medication reconciliation intervention on medication discrepancies with potential for harm (potential adverse drug events [PADEs])

Methods Controlled trial, randomized by medical team, on general medical

inpatient units at 2 academic hospitals from May to June 2006. 322 patients admitted to 14 medical teams, for whom a medication

history could be obtained before discharge. Intervention was a computerized medication reconciliation tool and

process redesign involving physicians, nurses, and pharmacists.

Page 11: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Schnipper JL et. al.. Arch Intern Med. 2009 Apr 27;169(8):771-80.

Methods, cont’d The main outcome was unintentional discrepancies between

preadmission medications and admission or discharge medications that had potential for harm (PADEs).

Results Among 160 control patients, there were 230 PADEs (1.44 per patient),

while among 162 intervention patients there were 170 PADEs (1.05 per patient) (adjusted relative risk [ARR], 0.72; 95% confidence interval [CI], 0.52-0.99).

A significant benefit was found at hospital 1 (ARR, 0.60; 95% CI, 0.38-0.97) but not at hospital 2 (ARR, 0.87; 95% CI, 0.57-1.32) (P = .32 for test of effect modification).

Hospitals differed in the extent of integration of the medication reconciliation tool into computerized provider order entry applications at discharge.

Page 12: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Schnipper JL et. al.. Arch Intern Med. 2009 Apr 27;169(8):771-80.

Conclusions A computerized medication reconciliation tool and process redesign

were associated with a decrease in unintentional medication discrepancies with potential for patient harm.

Software integration issues are important for successful implementation of computerized medication reconciliation tools.

Importance Contributes to literature on ‘people, process and technology’ that

confirms Reed Gardner’s classic observation that technology is only (10-15-20) percent of success, the rest is sociology.

Page 13: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Terrell KM, et al. J Am Geriatr Soc. 2009 Aug;57(8):1388-94. Epub

2009 Jun 22. [Indiana University, Indianapolis, Indiana] Title

Computerized decision support to reduce potentially inappropriate prescribing to older emergency department patients: a randomized, controlled trial.

Aim To evaluate the effectiveness of computer-assisted decision

support in reducing potentially inappropriate prescribing to older adults.

Setting: Academic emergency department where computerized physician

order entry was used to write all medication prescriptions

Page 14: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Terrell KM, et al. J Am Geriatr Soc. 2009 Aug;57(8):1388-94. Epub

2009 Jun 22. Methods

63 emergency physicians randomized to the intervention (32 physicians) or control (31 physicians) group.

Decision support advised against use of nine potentially inappropriate medications and recommended safer substitute therapies.

Primary outcome was the proportion of ED visits by seniors that resulted in one or more prescriptions for an inappropriate medication.

Secondary outcomes were the proportions of medications prescribed that were inappropriate and intervention physicians' reasons for rejecting the decision support.

Page 15: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Terrell KM, et al. J Am Geriatr Soc. 2009 Aug;57(8):1388-94. Epub

2009 Jun 22. Results

Average age of the patients = 74, two-thirds were female, and just over half were African American.

Decision support was provided 114 times to intervention physicians, who accepted 49 (43%) of the recommendations.

Intervention physicians prescribed one or more inappropriate medications during 2.6% of ED visits by seniors, compared with 3.9% of visits managed by control physicians (P=.02).

The proportion of all prescribed medications that were inappropriate significantly decreased from 5.4% to 3.4%.

The most common reason for rejecting decision support was that the patient had no prior problems with the medication.

Page 16: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Terrell KM, et al. J Am Geriatr Soc. 2009 Aug;57(8):1388-94.

Epub 2009 Jun 22. Conclusions

Computerized physician order entry with decision support significantly reduced prescribing of potentially inappropriate medications for seniors.

Approach might be used in other efforts to improve ED care. Importance

Overrides of clinical decision support guidance occur because of data not captured in the EMR but elicited by providers

An installed CPOE system with CDSS is an essential infrastructure for such interventions

Page 17: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Smith DH et al. Am J Manag Care. 2009 May;15(5):281-9. [Kaiser

Permanente, Portland, OR] Title

Improving laboratory monitoring of medications: an economic analysis alongside a clinical trial.

Aim To test the efficiency and cost-effectiveness of interventions

aimed at enhancing laboratory monitoring of medication. Methods:

A cost-effectiveness analysis. Patients of a not-for-profit, group-model HMO were randomized to

1 of 4 interventions: an electronic medical record reminder to the clinician, an automated voice message to patients, pharmacy-led outreach, or usual care.

Page 18: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Smith DH et al. Am J Manag Care. 2009 May;15(5):281-9

Methods, cont’d: Patients followed for 25 days to determine completion of all

recommended baseline laboratory monitoring tests. Measured the rate of laboratory test completion and the cost-

effectiveness of each intervention. Direct medical care costs to the HMO (repeated testing, extra

visits, and intervention costs) were determined using trial data and a mix of other data sources.

Results Average cost of patient contact was $5.45 in the pharmacy-led

intervention, $7.00 in the electronic reminder intervention, and $4.64 in the automated voice message reminder intervention.

Page 19: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Smith DH et al. Am J Manag Care. 2009 May;15(5):281-9

Results, cont’d The electronic medical record intervention was more costly

and less effective than other methods. The automated voice message intervention had an

incremental cost-effectiveness ratio (ICER) of $47 per additional completed case, and the pharmacy intervention had an ICER of $64 per additional completed case.

Conclusions: Using the data available to compare strategies to enhance

baseline monitoring, direct clinician messaging was not an efficient use of resources.

Page 20: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers Reference

Smith DH et al. Am J Manag Care. 2009 May;15(5):281-9

Conclusions, cont’d: Depending on a decision maker's willingness to pay,

automated voice messaging and pharmacy-led efforts can be efficient choices to prompt therapeutic baseline monitoring.

Direct clinician messaging is a less efficient use of resources.

Importance Adds to a growing literature that when implementing clinical

decision support, members of the care team other than physicians appear to be better targets for automated alerts and reminders

Page 21: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Linder JA et. al. Arch Intern Med. 2009 Apr 27;169(8):781-7 [Brigham & Womens,

Boston MA].

Title An electronic health record-based intervention to improve tobacco treatment in

primary care: a cluster-randomized controlled trial.

Aim To assess impact of intervention design to improve the documentation and

treatment of tobacco use in primary care

Methods Developed and implemented a 3-part electronic health record enhancement:

(1)smoking status icons, (2) tobacco treatment reminders, and (3) a Tobacco Smart Form that facilitated the ordering of medication and fax and e-mail counseling referrals.

Page 22: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 23: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Linder JA et. al. Arch Intern Med. 2009 Apr 27;169(8):781-7 [Brigham &

Womens, Boston MA].

Methods, cont’d A cluster-randomized controlled trial of the enhancement in 26 primary

care practices between December 19, 2006, and September 30, 2007. Primary outcome was the proportion of documented smokers who made

contact with a smoking cessation counselor. Secondary outcomes included coded smoking status documentation and

medication prescribing.

Results During the 9-month study period, 132,630 patients made 315,962 visits to

study practices.

Page 24: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Linder JA et. al. Arch Intern Med. 2009 Apr 27;169(8):781-7

Results, cont’d Coded documentation of smoking status increased from 37% of

patients to 54% (+17%) in intervention practices and from 35% of patients to 46% (+11%) in control practices (P < .001 for the difference in differences).

Among the 9589 patients who were documented smokers at the start of the study, more patients in the intervention practices were recorded as nonsmokers by the end of the study (5.3% vs 1.9% in control practices; P < .001).

Among 12,207 documented smokers, more patients in the intervention practices made contact with a cessation counselor (3.9% vs 0.3% in control practices; P < .001).

Page 25: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Linder JA et. al. Arch Intern Med. 2009 Apr 27;169(8):781-7

Results, cont’d Smokers in the intervention practices were no more likely to be

prescribed smoking cessation medication (2% vs 2% in control practices; P = .40).

Conclusions The EHR-based intervention improved smoking status documentation

and increased counseling assistance to smokers but not the prescription of cessation medication.

Importance CDSS literature on smoking has shown it to be a remarkably difficult

condition to modify through interventions. Gratifying positive results.

Page 26: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers Reference

Schriefer SP et al. Fam Med. 2009 Jul-Aug;41(7):502-7. [MAHEC Family Health Center, Asheville, NC]

Title Effect of a computerized body mass index prompt on diagnosis and

treatment of adult obesity. Aim

To determine whether a computerized body mass index (BMI) chart prompt would increase the likelihood that patients of family physicians would be diagnosed with obesity and referred for obesity treatment.

Methods A total of 846 obese patients of 37 family physicians were randomly

assigned to either have a patient's BMI chart prompt placed in their electronic medical record (intervention group) or not have a BMI prompt (comparison group) placed in the record.

Page 27: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Schriefer SP et al. Fam Med. 2009 Jul-Aug;41(7):502-7.

Methods, cont’d Patient medical records examined for evidence of an obesity

diagnosis and referral for specific obesity treatments. Also measured whether the presence of comorbidities in

obese patients influenced the likelihood of diagnoses and treatments by the physicians.

Results Obese patients of physicians who had a BMI chart prompt in

their medical records were significantly more likely than obese patients of physicians who did not receive a BMI chart prompt to receive a diagnosis of obesity (16.6% versus 10.7%; P=.016).

Clinical Decision Support for Providers

Page 28: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Schriefer SP et al. Fam Med. 2009 Jul-Aug;41(7):502-7.

Results Patients of physicians who were provided with a BMI chart

prompt were also more likely than patients of physicians who did not get a chart prompt to receive a referral for diet treatment (14.0% versus 7.3%, P=.002) and exercise (12.1% versus 7.1%, P=.016).

Of the obesity comorbidities, only obstructive sleep apnea (OSA) was a predictor of a patient being diagnosed with obesity (P=.014).

Conclusion: Inclusion of a computerized BMI chart prompt increased the

likelihood that physicians would diagnose obesity in obese patients and refer them for treatment.

Clinical Decision Support for Providers

Page 29: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Schriefer SP et al. Fam Med. 2009 Jul-Aug;41(7):502-7.

Importance Consistent with well established literature on physician alerts

and prompts that shows both a modest increase in compliance with best practices and disappointing overall effect on care processes.

Clinical Decision Support for Providers

Page 30: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Ahmad F et al. Ann Intern Med. 2009 Jul 21;151(2):93-102. Epub

2009 Jun 1. [University of Toronto, Ontario, Canada] Title

Computer-assisted screening for intimate partner violence and control: a randomized trial.

Aim To assess whether computer-assisted screening can

improve detection of women at risk for intimate partner violence and control (IPVC) in a family practice setting.

Setting: An urban, academic, hospital-affiliated family practice clinic

in Toronto.

Page 31: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Ahmad F et al. Ann Intern Med. 2009 Jul 21;151(2):93-102. Epub

2009 Jun 1. Methods

293 adult women in a current or recent relationship randomized to computer-based multi-risk assessment report attached to the medical chart.

The report was generated from information provided by participants before the physician visit (n = 144).

Control participants received standard medical care (n = 149). Measured frequency of initiation of discussion about risk for IPVC

(discussion opportunity) and detection of women at risk based on review of audiotaped medical visits.

Page 32: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Ahmad F et al. Ann Intern Med. 2009 Jul 21;151(2):93-102. Epub 2009

Jun 1. Results

The overall prevalence of any type of violence or control was 22% (95% CI, 17% to 27%).

In adjusted analyses based on complete cases (n = 282), the intervention increased opportunities to discuss IPVC (adjusted relative risk, 1.4 [CI, 1.1 to 1.9]) and increased detection of IPVC (adjusted relative risk, 2.0 [CI, 0.9 to 4.1]).

Participants recognized the benefits of computer screening but had some concerns about privacy and interference with physician interactions.

Conclusion Computer screening effectively detected IPVC in a busy family

medicine practice, and it was acceptable to patients.

Page 33: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers

Reference Ahmad F et al. Ann Intern Med. 2009 Jul 21;151(2):93-

102. Epub 2009 Jun 1. Importance

Extends literature on patients’ willingness to use computerized interviewing methods to report sensitive and potentially stigmatizing conditions.

Additional evidence that tailored reports inserted into outpatient setting can reduce barriers to initiation of difficult conversations between providers and patients

Page 34: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers and Patients

Reference Holbrook A. et al. CMAJ. 2009 Jul 7;181(1-2):37-44. [McMaster

University, Hamilton ON] Title

Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial.

Aim To determine whether electronic decision support, providing

information that is shared by both patient and physician, encourages timely interventions and improves the management of this chronic disease.

Methods Randomly assigned adult primary care patients with type 2 diabetes

to receive the intervention or usual care.

Page 35: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Holbrook A. et al. CMAJ. 2009 Jul 7;181(1-2):37-44. [McMaster

University, Hamilton ON] Methods

Intervention involved shared access by the primary care provider and the patient to a Web-based, color-coded diabetes tracker.

Intervention provided sequential monitoring values for 13 diabetes risk factors, their respective targets, and brief, prioritized messages of advice.

Primary outcome measure was a process composite score. Secondary outcomes included clinical composite scores, quality of

life, continuity of care and usability. Outcome assessors were blinded to each patient's intervention

status.

Clinical Decision Support for Providers and Patients

Page 36: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Diabetes tracker: Physician view

Page 37: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Diabetes tracker: Patient view

Page 38: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Holbrook A. et al. CMAJ. 2009 Jul 7;181(1-2):37-44. [McMaster

University, Hamilton ON] Results, cont’d

Recruited 46 primary care providers and 511 of their patients, mean age 60.7.

Mean follow-up was 5.9 months. Process composite score was significantly better for patients in the

intervention group than for control patients (difference 1.27, p < 0.001);

61.7% (156/253) of patients in the intervention group, compared with 42.6% (110/258) of control patients, showed improvement (difference 19.1%, p < 0.001).

Clinical Decision Support for Providers and Patients

Page 39: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Holbrook A. et al. CMAJ. 2009 Jul 7;181(1-2):37-44. [McMaster University,

Hamilton ON] Results, cont’d

The clinical composite score also had significantly more variables with improvement for the intervention group (0.59, 95% CI 0.09-1.10, p = 0.02), including significantly greater declines in blood pressure (-3.95 mm Hg systolic and -2.38 mm Hg diastolic) and glycated hemoglobin (-0.2%).

Patients in the intervention group reported greater satisfaction with their diabetes care.

Conclusions A shared electronic decision-support system improved the process of care

and some clinical markers of the quality of diabetes care. Importance

New models of shared decision support are succeeding

Clinical Decision Support for Providers and Patients

Page 40: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers and Patients

Reference Sequist TD. Arch Intern Med. 2009 Feb 23;169(4):364-71[Dept Health

Care Policy, Harvard, Boston MA] Title

Patient and physician reminders to promote colorectal cancer screening: a randomized controlled trial.

Aim To determine whether systematic reminders to patients and physicians

could increase cancer screening rates . Methods

A randomized controlled trial in 11 ambulatory health care centers. Participants included 21 860 patients aged 50 to 80 years who were

overdue for colorectal cancer screening and 110 primary care physicians.

Patients were randomly assigned to receive mailings containing an educational pamphlet, fecal occult blood test kit, and instructions for direct scheduling of flexible sigmoidoscopy or colonoscopy.

Physicians were randomly assigned to receive electronic reminders during office visits with patients overdue for screening.

Page 41: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Providers and Patients

Reference Sequist TD. Arch Intern Med. 2009 Feb 23;169(4):364-71[Dept Health

Care Policy, Harvard, Boston MA] Methods, cont’d

Primary outcome was receipt of fecal occult blood testing, flexible sigmoidoscopy, or colonoscopy over 15 months

Secondary outcome was detection of colorectal adenomas. Results

Screening rates were higher for patients who received mailings compared with those who did not (44.0% vs 38.1%; P < .001).

Effect increased with age: +3.7% for ages 50 to 59 years; +7.3% for ages 60 to 69 years; and +10.1% for ages 70 to 80 years (P = .01 for trend).

Screening rates were similar among patients of physicians receiving electronic reminders and the control group (41.9% vs 40.2%; P = .47).

However, electronic reminders tended to increase screening rates among patients with 3 or more primary care visits (59.5% vs 52.7%; P = .07).

Detection of adenomas tended to increase with patient mailings (5.7% vs 5.2%; P = .10) and physician reminders (6.0% vs 4.9%; P = .09).

Page 42: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Sequist TD. Arch Intern Med. 2009 Feb 23;169(4):364-71[Dept Health

Care Policy, Harvard, Boston MA] Conclusions

Mailed reminders to patients are an effective tool to promote colorectal cancer screening

Electronic reminders to physicians may increase screening among adults who have more frequent primary care visits.

Importance Adds to CDSS literature that shows larger effect size when best

practice guidance sent to patients compared to same message sent to physicians

Clinical Decision Support for Providers and Patients

Page 43: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Patients

Reference Volandes AE et al. BMJ. 2009 May 28;338:b2159. doi:

10.1136/bmj.b2159. [Massachusetts General Hospital, Boston, MA] Title

Video decision support tool for advance care planning in dementia: randomised controlled trial.

Aim To evaluate the effect of a video decision support tool on the preferences

for future medical care in older people if they develop advanced dementia, and the stability of those preferences after six weeks.

Setting Four primary care clinics (two geriatric and two adult medicine) affiliated

with three academic medical centers in Boston.

Page 44: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Patients

Reference Volandes AE et al. BMJ. 2009 May 28;338:b2159. doi: 10.1136/bmj.b2159. [Massachusetts

General Hospital, Boston, MA] Methods.

Convenience sample of 200 older people (>or=65 years) living in the community with previously scheduled appointments at one of the clinics. Mean age was 75 and 58% were women.

Intervention was verbal narrative alone (n=106) or with a video decision support tool (n=94).

Main outcome measure was preferred goal of care: life prolonging care (cardiopulmonary resuscitation, mechanical ventilation), limited care (admission to hospital, antibiotics, but not cardiopulmonary resuscitation), or comfort care (treatment only to relieve symptoms). Checked again six weeks later.

Analyzed difference in proportions of participants in each group who preferred comfort care.

Page 45: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Patients

Reference Volandes AE et al. BMJ. 2009 May 28;338:b2159. doi: 10.1136/bmj.b2159.

[Massachusetts General Hospital, Boston, MA] Results.

Among participants receiving the verbal narrative alone, 68 (64%) chose comfort care, 20 (19%) chose limited care, 15 (14%) chose life prolonging care, and three (3%) were uncertain.

In the video group, 81 (86%) chose comfort care, eight (9%) chose limited care, four (4%) chose life prolonging care, and one (1%) was uncertain (P=0.003).

Among all participants the factors associated with a greater likelihood of opting for comfort care were being a college graduate or higher, good or better health status, greater health literacy, white race, and randomization to the video arm.

Page 46: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Patients

Reference Volandes AE et al. BMJ. 2009 May 28;338:b2159. doi: 10.1136/bmj.b2159.

[Massachusetts General Hospital, Boston, MA] Results

Participants were re-interviewed after six weeks. Among the 94/106 (89%) participants re-interviewed in the verbal group, 27 (29%) changed their preferences (kappa=0.35).

Among the 84/94 (89%) participants re-interviewed in the video group, five (6%) changed their preferences (kappa=0.79) (P<0.001 for difference).

Conclusions Older people who view a video depiction of a patient with advanced dementia after

hearing a verbal description of the condition are more likely to opt for comfort as their goal of care compared with those who solely listen to a verbal description.

They also have more stable preferences over time.

Page 47: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support for Patients

Reference Volandes AE et al. BMJ. 2009 May 28;338:b2159. doi:

10.1136/bmj.b2159. [Massachusetts General Hospital, Boston, MA]

Importance Multimedia technologies can assist patients in understanding

future health states. To understand dementia, a movie is worth a thousand words…

Page 48: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

10 New CDSS RCTs showing no difference for intervention vs. control

1. Piazza G. Physician alerts to prevent symptomatic venous thromboembolism in hospitalized patients. Circulation. 2009 Apr 28;119(16):2196-201. Epub 2009 Apr 13. [Brigham & Woman’s Hospital, Boston MA]

2. Bosworth HB et al.  Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J. 2009 Mar;157(3):450-6. Epub 2009 Jan 10. [Center for Health Svcs Research, Durham NC]

3. Kline JA et al. Randomized trial of computerized quantitative pretest probability in low-risk chest pain patients: effect on safety and resource use. Ann Emerg Med. 2009 Jun;53(6):727-35.e1. Epub 2009 Jan 9. [Carolinas Medical Ctr, Charlotte NC]

4. Leveille SG et al. Health coaching via an internet portal for primary care patients with chronic conditions: a randomized controlled trial. Med Care. 2009 Jan;47(1):41-7. [Beth Israel Deaconnes Med Ctr, Boston MA]

Page 49: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

10 New CDSS RCTs showing no difference for intervention vs. control, cont’d

5. Stoddard JL et al. Effect of adding a virtual community (bulletin board) to smokefree.gov: randomized controlled trial. J Med Internet Res. 2008 Dec 19;10(5):e53. [SAIC -NCI Frederick, MD]

6. Gurwitz JH et al. Effect of computerized provider order entry with clinical decision support on adverse drug events in the long-term care setting. J Am Geriatr Soc. 2008 Dec;56(12):2225-33. [U. Mass, Worcester, MA]

7. Askins MA et al. Report from a multi-institutional randomized clinical trial examining computer-assisted problem-solving skills training for English- and Spanish-speaking mothers of children with newly diagnosed cancer. J Pediatr Psychol. 2009 Jun;34(5):551-63. Epub 2008 Dec 17. [MD Anderson, Houston, TX]

8. Kasper J et al.  Informed shared decision making about immunotherapy for patients with multiple sclerosis (ISDIMS): a randomized controlled trial. Eur J Neurol. 2008 Dec;15(12):1345-52. [Univ. Hamburg, Germany]

Page 50: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

10 New CDSS RCTs showing no difference for intervention vs. control, cont’d

9. Hung CS et al. Using paper chart based clinical reminders to improve guideline adherence to lipid management.  J Eval Clin Pract. 2008 Oct;14(5):861-6. [National Taiwan University Hospital, Taiwan]

10. Lo HG et al. Impact of non-interruptive medication laboratory monitoring alerts in ambulatory care. J Am Med Inform Assoc. 2009 Jan-Feb;16(1):66-71. Epub 2008 Oct 24. [Univ. Penn., Philadelphia, PA]

Page 51: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Clinical Decision Support

Questions and Comments

Page 52: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine

12 new RCTs published

November 2008 – October 2009•4 diabetes

•2 each psychiatric care, hypertension and smoking cessation

•1 chronic conditions coaching

•1 insomnia

Page 53: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - diabetes Reference

Shea S et. al. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):446-56. Epub 2009 Apr 23. [Columbia Univ., New York NY]

Title A randomized trial comparing telemedicine case management with usual

care in older, ethnically diverse, medically underserved patients with diabetes mellitus: 5 year results of the IDEATel study.

Aim To examine the effectiveness of a telemedicine intervention to achieve

clinical management goals in older, ethnically diverse, medically underserved patients with diabetes.

Methods A randomized controlled trial was conducted, comparing telemedicine case

management to usual care, with blinded outcome evaluation, in 1,665 Medicare recipients with diabetes, aged >/= 55 years, residing in federally designated medically underserved areas of New York State.

Page 54: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - diabetes

Reference Shea S et. al. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):446-56. Epub 2009

Apr 23. [Columbia Univ., New York NY] Methods, cont’d

Intervention was home telemedicine unit with nurse case management versus usual care.

Main outcome measures were hemoglobin A1c (HgbA1c), low density lipoprotein (LDL) cholesterol, and blood pressure levels.

Results Intention-to-treat mixed models showed that telemedicine achieved net overall

reductions over five years of follow-up in the primary endpoints (HgbA1c, p = 0.001; LDL, p < 0.001; systolic and diastolic blood pressure, p = 0.024; p < 0.001).

Estimated differences (95% CI) in year 5 were 0.29 (0.12, 0.46)% for HgbA1c, 3.84 (-0.08, 7.77) mg/dL for LDL cholesterol, and 4.32 (1.93, 6.72) mm Hg for systolic and 2.64 (1.53, 3.74) mm Hg for diastolic blood pressure.

Page 55: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - diabetes

Reference Shea S et. al. J Am Med Inform Assoc. 2009 Jul-

Aug;16(4):446-56. Epub 2009 Apr 23. [Columbia Univ., New York NY]

Conclusions Telemedicine case management resulted in net

improvements in HgbA1c, LDL-cholesterol and blood pressure levels over 5 years in medically underserved Medicare beneficiaries.

Importance Effectiveness of telemedicine technologies is not

restricted to well educated and affluent individuals

Page 56: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine – smoking cessation Reference

Rabius V et al. J Med Internet Res. 2008 Nov 21;10(5):e45. [National Cancer Information Center, American Cancer Society, Austin, Texas]

Title Comparing internet assistance for smoking cessation: 13-month

follow-up of a six-arm randomized controlled trial. Aims

To describe long-term smoking cessation rates associated with 6 different Internet-based cessation services and the variation among them,

To test the hypothesis that interactive and tailored Internet services yield higher long-term quit rates than more static Web-posted assistance

To explore the possible effects of level of site utilization and a self-reported indicator of depression on long-term cessation rates.

Page 57: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine – smoking cessation Reference

Rabius V et al. J Med Internet Res. 2008 Nov 21;10(5):e45. [National Cancer Information Center, American Cancer Society, Austin, Texas]

Methods In 2004-05, a link was placed on the American Cancer Society (ACS)

website for smokers who wanted help in quitting via the Internet. The link led smokers to the QuitLink study website, where they could answer eligibility questions, provide informed consent, and complete the baseline survey.

Enrolled participants were randomly assigned to receive emailed access to one of five tailored interactive sites provided by cooperating research partners or to a targeted, minimally interactive ACS site with text, photographs, and graphics providing stage-based quitting advice and peer modeling.

Results 6451 of the visitors met eligibility requirements and completed

consent procedures and the baseline survey. All of these smokers were randomly assigned to one of the six experimental groups.

Page 58: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine – smoking cessation Reference

Rabius V et al. J Med Internet Res. 2008 Nov 21;10(5):e45. [National Cancer Information Center, American Cancer Society, Austin, Texas]

Results, cont’d Follow-up surveys done online and via telephone interviews at

approximately 13 months after randomization yielded 2468 respondents (38%) and found no significant overall quit rate differences among those assigned to the different websites (P = .15).

At baseline, 1961 participants (30%) reported an indicator of depression. Post hoc analyses found that this group had significantly lower 13-month quit rates than those who did not report the indicator (all enrolled, 8% vs 12%, P < .001; followed only, 25% vs 31%, P = .003).

When the 4490 participants (70%) who did not report an indicator of depression at baseline were separated for analysis, the more interactive, tailored sites, as a whole, were associated with higher quitting rates than the less interactive ACS site: 13% vs 10% (P = .04) among 4490 enrolled and 32% vs 26% (P = .06) among 1798 followed.

Page 59: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine – smoking cessation

Reference Rabius V et al. J Med Internet Res. 2008 Nov 21;10(5):e45. [National

Cancer Information Center, American Cancer Society, Austin, Texas] Conclusions

Internet assistance is attractive and potentially cost-effective and suggest that tailored, interactive websites may help cigarette smokers who do not report an indicator of depression at baseline to quit and maintain cessation.

Importance Specific features of telemedicine technology (eg., website content

and functionality) may be less important that patient characteristics when measuring health outcomes.

Page 60: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - depression

Reference Kessler D, et al. Lancet. 2009 Aug 22;374(9690):628-34. [University of Bristol,

Bristol, UK] Title

Therapist-delivered Internet psychotherapy for depression in primary care: a randomised controlled trial.

Aim To investigate the effectiveness of CBT delivered online in real time by a

therapist for patients with depression in primary care. Methods

297 individuals with a score of 14 or more on the Beck depression inventory (BDI) and a confirmed diagnosis of depression recruited from 55 general practices in Bristol, London, and Warwickshire, UK.

Participants were randomly assigned, by a computer-generated code, to online CBT in addition to usual care (intervention; n=149) or to usual care from their general practitioner while on an 8-month waiting list for online CBT (control; n=148).

Page 61: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - depression

Reference Kessler D, et al. Lancet. 2009 Aug 22;374(9690):628-34.

Methods The primary outcome was recovery from depression (BDI score <10) at

4 months. Analysis by intention to treat. Results

113 participants in the intervention group and 97 in the control group completed 4-month follow-up.

43 (38%) patients recovered from depression (BDI score <10) in the intervention group versus 23 (24%) in the control group at 4 months (p=0.011), and 46 (42%) versus 26 (26%) at 8 months (2.07, 1.11-3.87; p=0.023).

Conclusion CBT effective when delivered online in real time by a therapist, with

benefits maintained over 8 months.

Page 62: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - depression

Reference Kessler D, et al. Lancet. 2009 Aug 22;374(9690):628-34.

Importance Extends 35+ year literature showing effectiveness of telemedicine-

mediated psychiatry services. Observed effects also consistent with more therapy better than less

therapy.

Page 63: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - insomnia

Reference Vincent N, Lewycky S., Sleep. 2009 Jun 1;32(6):807-15. [University of

Manitoba, Canada] Title

Logging on for better sleep: RCT of the effectiveness of online treatment for insomnia.

Aim To evaluate the impact of a 5-week, online treatment for insomnia.

Methods Randomization of 118 adults with chronic insomnia to either online

treatment or waiting list control. Participants received online treatment in their homes. Online treatment consisted of psychoeducation, sleep hygiene, and

stimulus control instruction, sleep restriction treatment, relaxation training, cognitive therapy, and help with medication tapering.

Page 64: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - insomnia Reference

Vincent N, Lewycky S., Sleep. 2009 Jun 1;32(6):807-15. Results

From pre- to post-treatment, there was a 33% attrition rate, and attrition was related to referral status (i.e., dropouts were more likely to have been referred for treatment rather than recruited from the community).

Using a mixed model analysis of variance procedure (ANOVA), results showed that online treatment produced statistically significant improvements in the primary end points of sleep quality, insomnia severity, and daytime fatigue.

Online treatment also produced significant changes in process variables of pre-sleep cognitive arousal and dysfunctional beliefs about sleep.

Conclusion “Implications of these findings are that identification of who most benefits

from online treatment is a worthy area of future study.”

Page 65: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine - insomnia Reference

Vincent N, Lewycky S., Sleep. 2009 Jun 1;32(6):807-15. Importance

An appealing Telemedicine application (“As long as I’m up, I might as well…”)

Beware cohort effects in technology evaluation studies

Page 66: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Telemedicine

Questions and Comments

Page 67: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Practice of Informatics

Page 68: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Practice of Informatics

Reference Simon SR et al. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):465-70.

Epub 2009 Apr 23.[HMS and Harvard Pilgrim Healthcare, Boston, MA]

Title Physicians' use of key functions in electronic health records from

2005 to 2007: a statewide survey. Aim

To determine physicians’ lack of use of EHR functionality is decreasing over time.

Methods Follow-up mail survey of 1,144 physicians in Massachusetts who

completed a 2005 survey.

Page 69: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Simon SR et al. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):465-

70. Epub 2009 Apr 23.[HMS and Harvard Pilgrim Healthcare, Boston, MA]

Results Response rate was 79.4%. In 2007, 35% of practices had EHRs, up from 23% in 2005. Among practices with EHRs, there was little change between 2005

and 2007 in the availability of nine of ten EHR features; the notable exception was electronic prescribing, reported as available in 44.7% of practices with EHRs in 2005 and 70.8% in 2007.

Use of EHR functions changed inconsequentially, with more than one out of five physicians not using each available function regularly in both 2005 and 2007.

Only electronic prescribing increased substantially: in 2005, 19.9% of physicians with this function available used it most or all the time, compared with 42.6% in 2007 (p < 0.001)..

Practice of Informatics

Page 70: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Simon SR et al. J Am Med Inform Assoc. 2009 Jul-Aug;16(4):465-70.

Epub 2009 Apr 23.[HMS and Harvard Pilgrim Healthcare, Boston, MA] Conclusions

By 2007, more than one third of practices in Massachusetts reported having EHRs

The availability and use of electronic prescribing within these systems increased vs. 2005.

In contrast, physicians reported little change in the availability and use of other EHR functions.

System refinements, certification efforts, and health policies, including standards development, should address the gaps in both EHR adoption and the use of key functions.

Importance Even the best applications won’t show outcomes differences if not used Data for the national debate on ‘meaningful use’ of EHRs

Practice of Informatics

Page 71: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Jha AK et al (Sr. author Blumenthal, D). N Engl J Med. 2009 Apr

16;360(16):1628-38. Epub 2009 Mar 25. [Dept of Health Policy & Management, Harvard, Boston, MA]

Title Use of electronic health records in U.S. hospitals.

Aim To determine the presence of specific electronic-record

functionalities. To examine the relationship of adoption of electronic health records

to specific hospital characteristics and factors that were reported to be barriers to or facilitators of adoption.

Practice of Informatics

Page 72: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Jha AK et al (Sr. author Blumenthal, D). N Engl J Med. 2009 Apr

16;360(16):1628-38. Epub 2009 Mar 25. [Dept of Health Policy & Management, Harvard, Boston, MA]

Methods Survey of all AHA member hospitals

Results 63% response rate Of hospitals surveyed, only 1.5% have a comprehensive electronic-

records system (i.e., present in all clinical units), and an additional 7.6% have a basic system (i.e., present in at least one clinical unit).

Computerized provider-order entry for medications has been implemented in only 17% of hospitals.

Larger hospitals, those located in urban areas, and teaching hospitals were more likely to have electronic-records systems.

Respondents cited capital requirements and high maintenance costs as the primary barriers to implementation, although hospitals with electronic-records systems were less likely to cite these barriers than hospitals without such systems.

Practice of Informatics

Page 73: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Jha AK et al (Sr. author Blumenthal, D). N Engl J Med. 2009 Apr

16;360(16):1628-38. Epub 2009 Mar 25. [Dept of Health Policy & Management, Harvard, Boston, MA]

Conclusions The very low levels of adoption of electronic health records in U.S.

hospitals suggest that policymakers face substantial obstacles to the achievement of health care performance goals that depend on health information technology.

A policy strategy focused on financial support, interoperability, and training of technical support staff may be necessary to spur adoption of electronic-records systems in U.S. hospitals.

Practice of Informatics

Page 74: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Practice of Informatics

Reference Stead, W.W. & Lin, H.S. (Eds.). (2009) Computer Science

and Telecommunications Board, National Research Council. Washington, D.C.: National Academies Press.

Title Computational technology for effective health care:

immediate steps and strategic directions. Committee on Engaging the Computer Science Research Community in Health Care Informatics.

Aim National Academies report on ways to make progress in

EHR technologies and their broad scale implementation.

Page 75: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 76: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Practice of Informatics

Questions and Comments

Page 77: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

New Literature Highlights: Bioinformatics and Computational Biology

Human Health and DiseaseThe practice of bioinformatics

Page 78: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Bioinformatics: Human Health & Disease

Reference Treutlein J et al. Arch Gen Psychiatry. 2009 Jul;66(7):773-84

[Central Institute of Mental Health, Mannheim, Germany] Title

Genome-wide association study of alcohol dependence. Aim

To identify susceptibility genes for alcohol dependence through a genome-wide association study (GWAS) and a follow-up study in a population of German male inpatients with an early age at onset.

Methods Five university hospitals in southern and central Germany. GWAS included 487 male inpatients with alcohol dependence as

defined by the DSM-IV and an age at onset younger than 28 years and 1358 population-based control individuals.

Follow-up study included 1024 male inpatients and 996 age-matched male controls.

Outcome measures: significant association findings in the GWAS and follow-up study with the same alleles.

Page 79: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Bioinformatics: Human Health & Disease

Reference Treutlein J et al. Arch Gen Psychiatry. 2009 Jul;66(7):773-84

[Central Institute of Mental Health, Mannheim, Germany] Results

In the combined analysis, 2 closely linked intergenic SNPs met genome-wide significance (rs7590720, P = 9.72 x 10(-9); rs1344694, P = 1.69 x 10(-8)). They are located on chromosome region 2q35, which has been implicated in linkage studies for alcohol phenotypes.

Nine SNPs were located in genes, including the CDH13 and ADH1C genes, that have been reported to be associated with alcohol dependence.

Conclusion The first GWAS and follow-up study to identify a genome-wide

significant association in alcohol dependence. Significance

GWAS studies now venturing into behavioral disorders that may be considered stigmatizing

Page 80: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Published Genome-Wide Associations through 6/2009, 439 published GWA at p < 5 x 10-8

NHGRI GWA Catalogwww.genome.gov/GWAStudies

Page 81: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Mardis ER et al. N Engl J Med. 2009 Sep 10;361(11):1058-66. Epub 2009

Aug 5. [Dept. Genetics, Washington Univ, St. Louis, MO] Title

Recurring mutations found by sequencing an acute myeloid leukemia genome.

Methods Massively parallel DNA sequencing use to obtain a very high level of

coverage (approximately 98%) of a primary, cytogenetically normal, de novo genome for AML with minimal maturation (AML-M1) and a matched normal skin genome.

Results 12 acquired (somatic) mutations identified within the coding sequences of

genes 52 somatic point mutations in conserved or regulatory portions of the

genome. All mutations appeared to be heterozygous and present in nearly all cells in

the tumor sample. The AML genome contained approximately 750 point mutations, of which

only a small fraction are likely to be relevant to pathogenesis.

Bioinformatics: Human Health & Disease

Page 82: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Mardis ER et al. N Engl J Med. 2009 Sep 10;361(11):1058-66.

Epub 2009 Aug 5. [Dept. Genetics, Washington Univ, St. Louis, MO]

Conclusion By comparing the sequences of tumor and skin genomes of a

patient with AML-M1, it is possible to identify recurring mutations that may be relevant for pathogenesis.

Importance Current GWAS studies involving SNPs still provide only a ‘picket

fence’ view of the genome for studies of disease mechanism. Full genome sequencing will be the preferred technology for

many diseases when it becomes cost-effective.

Bioinformatics: Human Health & Disease

Page 83: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Turer AT et al. Circulation. 2009 Apr 7;119(13):1736-46. Epub 2009

Mar 23. [Duke Univ. Med Ctr., Durham, NC] Title

Metabolomic profiling reveals distinct patterns of myocardial substrate use in humans with coronary artery disease or left ventricular dysfunction during surgical ischemia/reperfusion.

Aim To characterize human myocardial metabolism in the setting of

surgical cardioplegic arrest and ischemia/reperfusion. Methods

Mass spectrometry-based platform used to profile 63 intermediary metabolites in serial paired peripheral arterial and coronary sinus blood effluents obtained from 37 patients undergoing cardiac surgery, stratified by presence of coronary artery disease and left ventricular dysfunction.

Bioinformatics: Human Health & Disease

Page 84: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Turer AT et al. Circulation. 2009 Apr 7;119(13):1736-46. Epub 2009

Mar 23. [Duke Univ. Med Ctr., Durham, NC] Title

Metabolomic profiling reveals distinct patterns of myocardial substrate use in humans with coronary artery disease or left ventricular dysfunction during surgical ischemia/reperfusion.

Results The myocardium was a net user of a number of fuel substrates

before ischemia, with significant differences between patients with and without coronary artery disease.

After reperfusion, significantly lower extraction ratios of most substrates were found, as well as significant release of 2 specific acylcarnitine species. These changes were especially evident in patients with impaired ventricular function, who exhibited profound limitations in extraction of all forms of metabolic fuels.

Principal component analysis highlighted several metabolic groupings as potentially important in the postoperative clinical course.

Bioinformatics: Human Health & Disease

Page 85: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Turer AT et al. Circulation. 2009 Apr 7;119(13):1736-46. Epub 2009

Mar 23. [Duke Univ. Med Ctr., Durham, NC] Conclusions

The preexisting ventricular state is associated with significant differences in myocardial fuel uptake at baseline and after ischemia/reperfusion.

The dysfunctional ventricle is characterized by global suppression of metabolic fuel uptake and limited myocardial metabolic reserve and flexibility after global ischemia/reperfusion stress in the setting of cardiac surgery.

Altered metabolic profiles after ischemia/reperfusion are associated with postoperative hemodynamic course and suggest a role for perioperative metabolic monitoring and targeted optimization in cardiac surgical patients.

Importance Metabolomics is another “high dimensionality” class of data that will

eventually influence clinical decision support.

Bioinformatics: Human Health & Disease

Page 86: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Rello J et al. Chest. 2009 Sep;136(3):832-40. Epub 2009 May

11. [Hospital Universitari, Tarragona, Spain] Title

Severity of pneumococcal pneumonia associated with genomic bacterial load.

Aim To develop objective methods of identifying patients at risk for

septic shock and poorer outcomes among those with community-acquired pneumonia (CAP).

Methods Quantification of Streptococcus pneumoniae DNA level by real-

time polymerase chain reaction (rt-PCR) was prospectively conducted on whole-blood samples from a cohort of 353 patients who were displaying CAP symptoms upon their admission to the ED.

Bioinformatics: Human Health & Disease

Page 87: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Rello J et al. Chest. 2009 Sep;136(3):832-40. Epub 2009 May

11. [Hospital Universitari, Tarragona, Spain] Results

CAP caused by S pneumoniae was documented in 93 patients (36.5% with positive blood culture findings). A positive S pneumoniae rt-PCR assay finding was associated with a statistically significant higher mortality (odds ratio [OR], 7.08), risk for shock (OR, 6.29), and the need for mechanical ventilation (MV) [OR, 7.96].

Logistic regression, adjusted for age, sex, comorbidities, and pneumonia severity index class, revealed bacterial load as independently associated with septic shock (adjusted odds ratio [aOR], 2.42; 95% CI, 1.10 to 5.80) and the need for MV (aOR, 2.71; 95% CI, 1.17 to 6.27).

An S pneumoniae bacterial load of >or= 10(3) copies per milliliter occurred in 29.0% of patients (27 of 93 patients; 95% CI, 20.8 to 38.9%) being associated with a statistically significant higher risk for septic shock (OR, 8.00), the need for MV (OR, 10.50), and hospital mortality (OR, 5.43). .

Bioinformatics: Human Health & Disease

Page 88: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Reference Rello J et al. Chest. 2009 Sep;136(3):832-40. Epub 2009

May 11. [Hospital Universitari, Tarragona, Spain] Conclusions

In patients with pneumococcal pneumonia, bacterial load is associated with the likelihood of death, the risk of septic shock, and the need for MV.

High genomic bacterial load for S pneumoniae may be a useful tool for severity assessment.

Importance Disease diagnosis and prognosis based on pathogen DNA

type and load is an emerging area of clinical bioinformatics

Bioinformatics: Human Health & Disease

Page 89: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Computational Biology and Bioinformatics

Questions and Comments

Page 90: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Top Ten List of Notable Events

in the Past 12 months

Page 91: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

Page 92: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in hyper-exponential increases in the genomic data analyzed, stored and distributed.

“Over the past year, 10 trillion base pairs of high-throughput sequence data were submitted to NCBI and placed in a new database (Sequence Read Archive) designed specifically for these types of data. To put that number in perspective, these data are already 40 times greater than the 250 billion base pairs that were deposited over the last 20 years in NCBI's GenBank DNA sequence database. “

Betsy Humphreys

Page 93: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

Page 94: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

Page 95: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 96: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results (July 6, 2009)

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

Page 97: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 98: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget

Page 99: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 100: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget

4. Passage of ARRA brings new breach notification and expansion of HIPAA privacy/security requirements

Page 101: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 102: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget

4. Passage of ARRA brings new breach notification and expansion of HIPAA privacy/security requirements

3. Passage of ARRA provides extra $10 billion for NIH ($83 million to NLM)

Page 103: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 104: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget

4. Passage of ARRA brings new breach notification and expansion of HIPAA privacy/security requirements

3. Passage of ARRA provides extra $10 billion for NIH ($83 million to NLM)

2. Passage of ARRA requires establishment of first set of "meaningful use" criteria for EHRs

Page 105: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 106: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

And the #1 top event of 2009 is…

Page 107: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director 9. High throughput sequencing technologies result in exponential increases in the

genomic data analyzed, stored and distributed. 8. AMIA Clinical Informatics sub-certificate being sponsored by American Board

of Preventive Medicine to the American Board of Medical Specialties. 7. Launch of PMC Canada: the trend toward broader access to research results 6. Senate Finance Committee alleges serious computer flaws from doctors,

patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget (March 2009)

4. Passage of ARRA brings new breach notification and expansion of HIPAA privacy/security requirements

3. Passage of ARRA provides extra $10 billion for NIH ($83 million to NLM) 2. Passage of ARRA requires establishment of first set of "meaningful use"

criteria for EHRs 1. Passage of ARRA provides billions for EHR adoption

Page 108: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine
Page 109: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

“Top Ten” Events

10. Appointment of Francis Collins as NIH Director

9. High throughput sequencing technologies result in exponential increases in the genomic data analyzed, stored and distributed.

8. AMIA Clinical Informatics sub-certificate being sponsored by American Board of Preventive Medicine to the American Board of Medical Specialties.

7. Launch of PMC Canada: the trend toward broader access to research results

6. Senate Finance Committee alleges serious computer flaws from doctors, patients and engineers unhappy with current systems, demanding to know what steps vendors have taken to safeguard patients. (October 16)

5. Passage of ARRA established ONC in law and expands its responsibilities and budget

4. Passage of ARRA brings new breach notification and expansion of HIPAA privacy/security requirements

3. Passage of ARRA provides extra $10 billion for NIH ($83 million to NLM)

2. Passage of ARRA requires establishment of first set of "meaningful use" criteria for EHRs

1. Passage of ARRA provides billions for EHR adoption

Page 110: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

2009: Informatics’ Big Chance Begins

Page 111: Daniel R. Masys, MD Professor and Chair Department of Biomedical Informatics Professor of Medicine

Content for this session is at:

http://dbmichair.mc.vanderbilt.edu/amia2009/

including citation lists and linksand this PowerPoint