What is Biomedical and Health

Informatics?

William Hersh, MD

Professor and Chair

Department of Medical Informatics & Clinical Epidemiology

Oregon Health & Science University

Portland, OR, USA

Email: hersh@ohsu.edu

Web: www.billhersh.info

Blog: informaticsprofessor.blogspot.com

1

Overview

• Overview of discipline and profession

• Definitions of important terms

• Medical (or clinical) informatics

– Person-specific applications

– Knowledge-based applications

• Bioinformatics

• Education and training

2

A field with supporters in high places

“To improve the quality of our health care

while lowering its cost, we will make the

immediate investments necessary to ensure

that within five years, all of America’s

medical records are computerized … It just

won’t save billions of dollars and thousands

of jobs – it will save lives by reducing the

deadly but preventable medical errors that

pervade our health care system.”

- January, 2009

Health Information Technology for Economic

and Clinical Health (HITECH) Act of American

Recovery and Reinvestment Act (ARRA) of

2009 invested up to $30 billion in health

information technology3

Opportunities are not limited to

healthcare

“Modern biomedical scientists use computers and

robots to separate molecules in solution, read

genetic information, reveal the three-dimensional

shapes of natural molecules like proteins, and take

pictures of the brain in action. All of these

techniques generate large amounts of data, and

biology is changing fast into a science of

information management. There is no way to

manage these data by hand. What researchers

need are computer programs and other tools to

evaluate, combine, and visualize these data.”

- http://nihroadmap.nih.gov/bioinformatics/

Vision for integration into healthcare: Stead, 2010

4

Other areas of opportunity

• Public health – protecting the public and promoting health– e.g., disease surveillance, such as for H1N1 or

bioterrorism

• Consumer health – enabling better management of health– Personal health records for engaged patients and

consumers

• Imaging – use of images and their analysis for biomedical research and clinical care

• And more…

5

It is one of ten “ahead of the

curve” careers

6

Biomedical and

Careers that

are “relatively

new, already

viable, and

promise further

growth…”

(Nemko, 2007)

Among leading centers:

University of Oregon

Medical Center

Should have said:

Oregon Health &

Science University

What is biomedical and health

informatics?

• I get asked this so often that I keep a Web site

– http://www.billhersh.info/whatis/

• I have also written about it

– Overview of “medical informatics” (Hersh, 2002)

– But there are barriers (Hersh, 2004)

– Characterization of and changes in the profession (Hersh, 2006)

– Many career opportunities as well (Hersh, 2008)

– Definitions of field (Hersh, 2009)

– Workforce needs (Hersh, 2010)

7

Let us start by defining “informatics”

• Field concerned with how people use information, usually aided by technology, to improve aspects of the world

• More about information than technology, but technology is essential

• “The science of health service design must be a science of sociotechnical systems, and today that science is called informatics.” (Coiera, 2007)

8

(SUNY Buffalo)

It has a “fundamental theorem”

(Friedman, 2009)

9

Goal of informatics is:

and not:

My current preferred terminology

(Hersh, 2009)• Biomedical and health informatics (BMHI) is the field

concerned with the optimal use of information, often aided by technology, to improve individual health, healthcare, public health, and biomedical research– Differs from information technology (IT) in that

• Is strongly rooted in domains (e.g., health)

• IT is one (of many) tools employed

• Practitioners of BMHI are usually called informaticians(sometimes informaticists)

• Disagreements over terminology in both noun and adjectives preceding it– Has an “adjective problem”

10

Categories of BMHI (Hersh, 2009)

11

Informatics = People + Information + Technology

Biomedical and Health

InformaticsLegal Informatics Chemoinformatics

Bioinformatics(cellular and molecular)

Medical (Clinical)

Informatics(person)

{Clinical field}

Informatics

Public Health

Informatics(population)

Consumer Health

Informatics

Imaging Informatics Research Informatics

Categories of BMHI (cont.)

• Bioinformatics – application of informatics in cellular and molecular biology, often with focus on genomics

• Medical/clinical informatics – application of informatics to individuals– Informatics applied in a more specific healthcare domain is

{X} informatics, e.g., nursing, dental, pathology, primary care, etc.

• Public health informatics – application of informatics in public health

• Over-arching aspects of BMHI– Imaging informatics – focus on images in all categories

– Research informatics – focus on research in all categories

12

Informatics now viewed as a core

competency for health professionals• According to Institute of

Medicine report, the modern health professional must have competency in informatics as part of larger goal to provide patient-centered care (Greiner, 2003)

• Informatics competency is not just computer literacy!– The “Google generation” (aka,

“digital natives”) does not necessarily have good information skills (CIBER, 2008)

13

Some historical perspective on

informatics (Collen, 1994)

• Origin of term from Russia in late 1960s

• Achieved widespread use in France (informatique) and later rest of Europe in 1960s to denote computing issues related to information use– “Medical informatics” first used in 1974

– European perspective documented by Hasman (1996) and Moehr (2004)

• At present, most significant use is in biomedical arena, but it is used by other domains, such as law, chemistry, social sciences, etc.

14

How is informatics distinguished from

related terms?

• Information technology (IT) – computer and related technology

• Health information technology (HIT) – health-related application of IT

• Computer science (CS) is academic discipline that underlies IT (and other technologies)

• Management information systems (MIS) is another field underlying IT (usually in business schools)

15

Other related terms

• Health information management (HIM) –discipline historically focused on management of (paper) medical records (changing in current environment), with three main levels of practice

– Registered Health Information Administrator (RHIA) –highest level, baccalaureate degree

– Registered Health Information Technologist (RHIT) –associate degree

– Certified Coding Specialist (CCS) – usually less then associate degree

16

Other related terms

• Information and communications technology (ICT) – same as IT with added emphasis on telecommunications

• eHealth – use of ICT for health

• Telemedicine – provision of healthcare when participants separated by time and/or distance

– Sometimes applied in specific clinical specialties, e.g., teleradiology, teledermatology

• Telehealth – pursuit of health when separated by time and/or distance

17

Other related terms

• Evidence-based medicine (EBM) – the application of the best scientific evidence in the medical decision-making process

• Evidence-based practice (EBP) – the application of EBM in medical practice

• Comparative effectiveness research (CER) – research that compares one or more diagnostic or treatment options to evaluate effectiveness, safety, or outcomes

• Information retrieval – the field devoted to searching (mostly text, mostly knowledge-based information)

18

Other terms central to medical/clinical

informatics• Electronic health record (EHR) – patient’s health record in

digital form– Has mostly supplanted the term electronic medical record (EMR)

• Personal health record (PHR) – personally controlled health record, which may or may not be tethered to a healthcare organization’s EHR

• Health information exchange (HIE) – exchange of health information across traditional business and other boundaries– Organization managing HIE used to be called a Regional Health

Information Organization (RHIO)

• HITECH Act introduced a new type of organization –Regional Extension Center (REC)

19

Other terms related to the EHR

• Clinical decision support (CDS) – alerts,

reminders, rules designed to improve clinician

decision-making

• Computerized physician/provider order entry

(CPOE) – with or without CDS

• Interoperability and standards

• Privacy, confidentiality, and security

20

Research informatics

• Clinical research informatics (CRI) is area of informatics applied to clinical research (Embi, 2009)

• Increasing recognition that research findings must “translate” into clinical care more quickly and efficiently, leading to NIH investment in clinical and translational research through the Clinical & Translational Science Award (CTSA) program (Zerhouni, 2007)– Difference between IT and informatics very evident in this

domain (Bernstam, 2009)

• Translational bioinformatics (Sarkar, 2011) – increased understanding of human genome may lead to more personalized medicine tailored from one’s genome (Hamburg, 2010)

21

Major applications in medical/clinical

informatics

• Based on two core types of information, with different uses and applications

– Person-specific information is generated in the care of patients

• Applications: electronic health records, telemedicine, etc.

– Knowledge-based information is the scientific literature of biomedicine and health

• Applications: information retrieval systems, evidence-based medicine

22

Person-specific informatics

applications

• Electronic health record (EHR)

– EHR definitions and components

– Secondary use (re-use) of clinical data

– HIE

– Overcoming barriers and spurring adoption

• Telemedicine

– Provision of care over time or distance via

communications technologies

23

Motivations – why do we need more IT

in healthcare?

• Quality

• Safety

• Cost

• Inaccessible information

24

Healthcare quality

• There are many studies to choose from…

• McGlynn, 2003– Sample of nearly 7,000 adults in 12 US metro areas assessed for

30 conditions

– On average, only 54.9% of care was consistent with known quality

• NCQA, 2009 – annual report on quality shows “gaps” to get all health plans to 90th percentile of current quality– 49,400-115,300 avoidable deaths

– $12 billion in avoidable medical costs

• Quality of care for patients with chronic disease no better and in many ways worse in US than for other developed countries (Schoen, 2009)

25

Safety and medical errors

• The IOM “Errors” report: As many as 98,000 Americans die each year due to medical errors, mostly medication errors (Kohn, 2000)– Some have argued that the numbers are too high or too low, but

none argue with the concept

– A decade later, problem persists (Van Den Bos, 2011)

• Lost in the discussion: Most errors are the result of faulty systems; the solution is not in making people smarter or punishing them, but building better “systems” to identify and prevent errors (Berwick, 2003)

• “Medicine used to be simple, ineffective, and relatively safe. Now it is complex, effective, and potentially dangerous.” (Chantler, 1999)

26

Cost

• Healthcare costs continue to rise and outpace inflation (Wilson, 2011)

• US spends more per capita on healthcare but gets less in terms of “products” (OECD, 2006; Angrisano, 2007) and “outcomes” (Banks, 2006; Lasser, 2006)

27

Inaccessible information

• Primary care physicians reported information missing in 13.6% of clinical visits (Smith, 2005)

– In 52% of instances, information was available but outside system

– In 44% of instances, lack of information could adversely effect patients

• As many as 20% of all tests and 1 in 7 hospital admissions may be result of inadequate access to information (David Brailer, unpublished data)

• HITECH investment provides opportunity to achieve the “learning health system” (Friedman, 2010)

28

EHR definitions – key capabilities

(IOM, 2003)

• Health information and data

• Result management

• Order management

• Decision support

• Electronic communication and connectivity

• Patient support

• Administrative processes

• Reporting and population health management

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EHR data flow

Departmental

system

Data

Repository

Data

Warehouse

Additional financial and

administrative data

Departmental

system

Departmental

system

Regional and

national systems

Repository is usual

place for EHR data

to reside and be accessed

30

Benefits and challenges of the EHR

• Benefits

– Improved physician, nursing,

and other documentation and

care

– Personal health records

– Clinical decision support

– Quality assessment

– Public health

– Clinical research

– Health information exchange

• Challenges

– Data quality

– Data usability

– Standards and

interoperability

– Privacy, confidentiality, and

security

– Understanding clinical

narrative text

– Implementation

31

Clinical decision support (CDS)

• CDS uses EHR data to provide context-specific advice, alerts, and reminders, such as– Assisting with choices in diagnosis and therapy

– Detecting problematic situations, such as medication errors or drug-drug interactions

• Types of CDS– Information display – showing information in context of

situation

– Reminder systems – reminding clinicians to perform actions

– Alerts – alerting to critical clinical situations• Though growing concern over “alert fatigue”

– Clinical practice guidelines – guiding treatment to provide normalized care based on best evidence

32

EHRs allow and align “secondary use”

(or “re-use”) of clinical data

• Additional uses of EHR data include (Safran, 2007)

– Personal health records (PHRs)

– Clinical and translational research – generating hypotheses and facilitating research

– Health information exchange (HIE)

– Public health surveillance for emerging threats

– Healthcare quality measurement and improvement

• One important tool for re-use of clinical data is natural language processing (NLP), which has been challenging but is seeing growing successes (Stanfill, 2010; Nadkarni, 2011; Chapman, 2011)

33

Example of an EHR

• Using the Veterans Health Information Systems and Technology Architecture (VistA)

• Why VistA?– A state-of-the-art EHR that has transformed

healthcare in the Veteran’s Health Administration (VHA) (Brown, 2003; Greenfield, 2004)

– Not that pretty, but has all of the modern features of the EHR, e.g., clinical decision support (CDS), computerized provider order entry (CPOE), etc.

– Distributed under open-source model, unlike most other vendors who do not even allow screen shots to be shown outside their customers’ institutions

34

Some details about VistA

• Is available as a demo– http://www.ehealth.va.gov/EHEALTH/CPRS_Demo.asp

– Demo version has following screens but not data

• Application has two components– Server written in M (formerly called MUMPS),

accessed via command-line interface• Runs in commercial Intersystems Cache (on many platforms)

or open-source GT.M (Linux only)

– Client written in Delphi and providers graphical user interface

• Only runs on Windows (just about all versions)

35

Cover sheet – after patient selected

Drilling down to details of a problem

Details of an allergy

38

Viewing vital signs over time

More details on problems

Viewing the patient’s notes

Adding a new note

Viewing labs

Including critical values

Another patient

Clinical decision support: reminders

46

Clinical decision support uses allergy

information

47

Prescribing a medication

How about some amoxicllin?

49

Oops, patient is allergic

50

Maybe erythromycin?

51

No, interacts with statin drugs

52

Drug interactions for another patient

Trying to prescribe nitrates for angina

Oops!

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Some more about VistA

• The pure open-source version is also known as FOIA Vista

• There are two other streams of VistA activity– WorldVistA (www.worldvista.org) follows a more

traditional open-source pathway

– OpenVista(http://sourceforge.net/projects/openvista/) is more commercially oriented, and some vendors have proprietary extensions from the base code (Medsphere, 2010)

• There is a small but growing market for VistA, including in other countries (Conn, 2008)

56

We also need to think beyond the EHR of a

single organization

• Patients are “mobile” – may develop medical problems or receive care away from their physician office or local hospital

– Of 3.7M patients in Massachusetts, 31% visited 2 or more hospitals over 5 years (57% of all visits) and 1% visited 5 or more hospitals (10% of all visits) (Bourgeois, 2010)

– Of 2.8M emergency department (ED) patients in Indiana found 40% of patients had data at multiple institutions, with all 81 EDs sharing patients in common (Finnell, 2011)

• Also greater need in public health sphere with growing threats of emerging diseases, bioterrorism, etc.

57

Beyond the EHR: health information

exchange (HIE; Kuperman, 2011)

• “Anytime, anywhere access to clinical information for the care of patients” – William Yasnoff, MD, PhD

• “Data following the patient” – Carolyn Clancy, MD, Director, AHRQ

• Requires that information seamlessly flow across business boundaries

– Challenges are not only technical, but also financial, legal, etc.

• But there are other successful examples of information exchange, such as ATM cards, wireless networks, etc.

58

Example of HIE: Indiana Health

Information Exchange• (McDonald, 2005)

• www.ihie.org

• Access to clinical information in real time by– Most hospital emergency departments

– Many hospital-based clinicians

– Some primary care providers in community

– Homeless care network

– Public school clinics

– County Health Department

– Indiana State Health Department

59

“Results” of other HIE efforts have

been mixed

• Successful

– Inland Northwest Health System (INHS, www.inhs.org), Spokane, WA

– Massachusetts eHealth Collaborative (www.maehc.org) (Halamka, 2005; Gorroll, 2009)

• Less so

– Santa Barbara County Care Data Exchange –combination of technical, leadership, and funding problems (Miller, 2007; Brailer, 2007)

– Portland, Oregon (Conn, 2007)

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Nationwide Health Information

Network (NwHIN)• http://healthit.hhs.gov/nhin

• HITECH investing $547M in state-level HIE as well as in standards and tools to facilitate NwHIN– e.g., Direct Project, wiki.directproject.org

61

How much progress have we made?

• Systematic reviews (Chaudhry, 2006; Goldzweig, 2009; Buntin, 2011) have identified benefits in a variety of areas

• Although 18-25% of studies come from a small number of ‘health IT leader” institutions

62(Buntin, 2011)

Caveats about progress

• HIT may introduce error (Koppel, 2005) or

other unintended consequences (Ash, 2004)

• Report from National Research Council found

IT had not met its potential in healthcare

(Stead, 2009; good overview in: Conn, 2009

and Conn, 2009)

• Growing area of concern: HIT system safety

(Leviss, 2010; Sittig, 2011)

63

Why are we not there? What are the

barriers? (Hersh, 2004)

64

• Cost

• Technical challenges

• Interoperability

• Privacy and confidentiality

• Workforce

Cost barriers

• Even though there is overall return on investment (ROI), benefit does not accrue to those who pay, especially in small practices (Johnston, 2003)

– Practices only see 11% of ROI – most goes to insurance companies and laboratories

– But they are usually asked to pay the cost of EHRs

• Later data showed physicians achieved positive ROI around 2.5 years after initial investment, although range was wide (Miller, 2005)

65

Technical challenges

• While underlying technology (e.g., networks, relational database systems) is well-established, other technical issues remain, such as– Implementing systems, especially in office settings

(Carter, 2008; Daigrepont, 2011)

– Matching systems to workflow is essential – best systems add time in some areas but make it up in others (Overhage, 2001; Samuels, 2008)

• Most successful implementations have transformed care delivery and not just replaced paper records (Liang, 2010; Schulte, 2011)

66

Need for interoperability

• Clinical data is trapped in “silos,” not easily moved from one system to another (Brailer, 2005)

• Growing push for attention to “secondary use of clinical data,” which can align benefits for quality assessment, clinical research, public health surveillance, etc. (Safran, 2007)

• To achieve this, need standards for data elements, communications, etc. (EHRA, 2009; Benson, 2010)

67

Concerns about privacy and

confidentiality

• Much written, strong opinions (McGraw, 2009; ACP, 2009)

• VERY real, but– Security technologies are well-known and proven

effective

– Paper-based records are at least as insecure as EHRs and probably more so

– Human curiosity will trump even best methods, so we need to consider benefits vs. risks

– HIPAA is a mixed blessing; many argue for modification, e.g., (Ness, 2007; Nass, 2009)

68

HIT workforce – what do we know?

• Not much, other than it is important!

• Case study: implementation of computerized physician order entry (CPOE) showed adverse consequences– Mortality rate increased from 2.8% to 6.6% at Children’s

Hospital of Pittsburgh Pediatric ICU (Han, 2005)

– Increased mortality not seen at other academic centers (Del Baccaro, 2006; Jacobs, 2006)

– Pittsburgh adverse outcome may have been avoided with adherence to known “best practices” (Phibbs, 2005; Sittig, 2006)

• Problematic health IT implementations well-known, with failure often attributable to lack of understanding of clinical environment (Leviss, 2010)

69

Who is the HIT workforce? (Hersh,

2010)

• Three historical groups of HIT professionals

– Information technology (IT) – usually with

computer science or information systems

background

– Health information management (HIM) – historical

focus on medical records

– Clinical informatics (CI) – often from healthcare

backgrounds

70

How many HIT personnel do we have

and do we need?• IT – to reach level of known benefit and meaningful use,

may need 40,000 (Hersh, 2008)

• HIM – from US Bureau of Labor Statistics occupational employment projections 2008-2018 (BLS, 2009)– Medical Records and Health Information Technicians (RHITs and

coders) – about 172,500 employed now, increasing to 207,600 by 2018 (20% growth)

• CI – estimates less clear for this emerging field– One physician and nurse in each US hospital (~10,000) (Safran,

2005)

– About 13,000 in healthcare (Friedman, 2008) and 1,000 in public health (Friedman, 2007)

– Growing role of CMIO and other CI leaders (Leviss, 2006; Shaffer, 2010)

71

What competencies must CI

professionals have? (Hersh, 2009)

72

Health and biological sciences:

- Medicine, nursing, etc.

- Public health

- Biology

Computational and mathematical sciences:

- Computer science

- Information technology

- Statistics

Management and social sciences:

- Business administration

- Human resources

- Organizational behavior

Competencies required in

Biomedical and Health

Informatics

ONC estimated 51,000 needed for

HITECH agenda in 12 workforce roles• Mobile Adoption Support Roles

– Implementation support specialist*

– Practice workflow and information management redesign specialist*

– Clinician consultant*

– Implementation manager*

• Permanent Staff of Health Care Delivery and Public Health Sites– Technical/software support staff*

– Trainer*

– Clinician/public health leader†

– Health information management and exchange specialist†

– Health information privacy and security specialist†

• Health Care and Public Health Informaticians– Research and development scientist†

– Programmers and software engineer†

– Health IT sub-specialist†

(to be trained in *community colleges and † universities)

73

Other important workforce

developments

• Physicians

– Proposal to establish a clinical informatics

subspecialty (Detmer, 2010) based on core

curriculum (Gardner, 2009) and training

requirements (Safran, 2009)

• Other health professionals

– Nursing – TIGER initiative (Gugerty, 2009)

– HIM (Wilhelm, 2007; Dimick, 2008)

– Nutrition (Hoggle, 2010)

74

US has low rates of adoption in

inpatient and outpatient settings• Adoption in the US is low for

both outpatient (Hsiao, 2010) and inpatient settings (Jha, 2010)

• By most measures, US is a laggard and could learn from other countries (Schoen, 2009)

• Most other developed countries have undertaken ambitious efforts, e.g.,– England (Hayes, 2008)

– Denmark (Protti, 2010)

75

99 97 97 96 95 94 94

72 68

4637

0

25

50

75

100

NET NZ NOR UK AUS ITA SWE GER FR US CAN

(Hsiao, 2010)

(Schoen, 2009)

Emerging national consensus is that

we need more – starts at the top

• Started with President George W. Bush

– State of the Union – mentioned every year 2004-2007

• January, 2004 – “Computerizing health records [can] reduce costs, improve care, and lower the risk of medical mistakes.”

• January, 2007 – “We need to reduce costs and medical errors with better information technology.”

– Goal of (EHRs) for all Americans by 2014

• http://www.whitehouse.gov/news/releases/2005/ 01/20050127-2.html

• Was elevated to even higher priority by President Barack Obama in HITECH Act (ARRA, 2009)

76

We are now in a new “ARRA” of health

information technology (HIT)

• HITECH provides financial incentives for

“meaningful use” of HIT

– Incentives for EHR adoption by physicians and

hospitals (up to $29B)

– Direct grants administered by federal agencies

($2B)

• All initiatives overseen by Office of the National

Coordinator for Health IT (ONC,

http://healthit.hhs.gov/)

77

What is “meaningful use” (MU) of an

EHR? (Stark, 2010; Blumenthal, 2010)• Driven by five underlying goals for healthcare system

– Improving quality, safety and efficiency

– Engaging patients in their care

– Increasing coordination of care

– Improving the health status of the population

– Ensuring privacy and security

• Consists of three requirements– Use of certified EHR technology in a meaningful manner

– Utilize certified EHR technology connected for health information exchange (HIE)

– Use of certified EHR technology to submit information on clinical quality measures

78

MU being implemented in three stages

2009 2011 2013 2015

HIT-Enabled Health Reform

Me

an

ing

ful U

se C

rite

ria

HITECH

Policies Stage 1

Meaningful Use

Criteria

(Capture/share

data)Stage 2 Meaningful

Use Criteria

(Advanced care

processes with

decision support)

Stage 3

Meaningful Use

Criteria (Improved

Outcomes)

79

Implementation of MU (Blumenthal,

2010)

• Implemented through increased Medicare or Medicaid reimbursement over five years to

– Eligible professionals (EPs) – up to $44K

– Eligible hospitals (EHs) – $2-9M

• There are differences in definitions of above as well as amounts for Medicare vs. Medicaid reimbursement

• Stage 1 final rules released in July, 2010 by CMS (2010) and ONC (2010)

• Must achieve 14-15 core and 5 of 10 menu criteria

• Summarized in Blumenthal (2010) and many other places

80

Stage 1 core criteria (14 for EH; 15 for

EP)• >30% of unique patients have at least 1 med order entered using

CPOE

• Drug-drug and drug-allergy interaction checks enabled

• >40% of all permissible prescriptions transmitted electronically (EP only, not EH)

• >50% of all unique patients have demographics recorded: preferred language, gender, race, ethnicity, dob

• >80% of all unique patients have at least 1 entry or indication of none on problem list

• >80% of all unique patients have at least 1 entry or indication of none on medication list

• >80% of all unique patients have at least 1 entry or indication of none on medication allergy list

• >50% of patients age 13+ seen have smoking status recorded

81

Stage 1 core criteria (cont.)

• >50% of all unique patients age 2+ have recorded height, weight, blood pressure, calculated BMI, growth charts age 2-20

• Implement 1 clinical decision support rule relevant to specialty or high clinical priority with ability to track compliance

• Report quality measures to CMS – provide aggregate numerator, denominator, and exclusions

• >50% provide patients with an electronic copy of health information upon request within 3 business days

• Provide clinical summaries to patient for more than 50% of all office visits within 3 business days

• Performed at least 1 test of certified EHR technology’s capacity to electronically exchange key clinical information

• Conduct or review a security risk analysis and implement security updates as necessary

82

Stage 1 menu criteria (require five, one

of which must be public health)• Implement drug-formulary checks – at least 1 internal or external drug formulary

for the entire reporting period

• >50% of all unique patients 65 or older have an indication of an advance directive status recorded

• >40% of all clinical lab tests ordered are in EHR as structured data

• Generate lists of patients by specific conditions to use for quality improvement, reduction of disparities, research or outreach

• Use certified EHR technology to identify patient-specific education resources and provide to the patient if appropriate

• >50% of transitions of care and referrals by EH provide summary of care record for each transition of care or referral

• >50% of care transitions perform medication reconciliation

• Capability to submit electronic syndromic surveillance data to public health agencies and actual submission in accordance with applicable law and practice

• Capability to submit electronic immunization data to public health agencies

• Capability to submit electronic laboratory data to public health agencies

83

Quality measures – differ for EP and

EH but required for both• EP (outpatient) – three required or alternate measures

plus three of 13 others, e.g.,– Hypertension – blood pressure measurement

– Tobacco use assessment and cessation intervention

– Adult weight screening and follow-up

• EH (inpatient) – 15 required measures, e.g.,– Diabetes: Hemoglobin A1c, low-density lipoprotein, and

blood pressure control

– Influenza immunization for patients > 50 years old

– Pneumonia vaccination status for older adults

– Breast cancer screening

– Colorectal cancer screening

84

MU is just one of several challenges

85

http://www.aha.org/advocacy-issues/hit/mu/overvw-time.shtml

Other HITECH funding for the HIT

infrastructure• Regional Extension Centers (RECs)

– $677 million for 62 RECs that provide guidance, mainly to small primary care practices and critical access hospitals, in achieving MU

• State-based health information exchange (HIE)– $547 million in grants to states to develop HIE programs

• Beacon communities– $250 million to fund 17 communities that provide

exemplary demonstration of MU of EHRs

• Strategic health information advanced research projects (SHARP)– $60 million for four collaborative research centers

86

Other funding for the infrastructure:

HIT workforce

• A competent workforce is essential to achieve MU

– Based on 12 workforce roles, educated in community colleges and universities

• HITECH funded $118 million for

– Community college consortia ($70M)

– Curriculum Development Centers ($10M)

– Competency testing ($6M)

– University-based training grants ($32M)

87

Community College Consortia to

Educate HIT Professionals Program• Five regional consortia of 82 community colleges to

develop short-term programs to train 10,000 individuals per year in the six community college workforce roles

• Anticipated enrollment of people with healthcare and/or IT backgrounds – probably baccalaureate or higher degrees

88

Curriculum Development Centers

Program• Five universities to collaboratively develop (with

community college partners) HIT curricula for 20 components (courses)– Oregon Health & Science University (OHSU)

– Columbia University

– Johns Hopkins University

– Duke University

– University of Alabama Birmingham

• One of the five centers (OHSU) additionally funded as National Training and Dissemination Center

• Version 2 of curriculum delivered to community colleges in May, 2011, followed by release to all in July, 2011– www.onc-ntdc.info

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Components of the ONC HIT

curriculum1. Introduction to Health Care and Public Health in the U.S.

2. The Culture of Health Care

3. Terminology in Health Care and Public Health Settings

4. Introduction to Information and Computer Science

5. History of Health Information Technology in the U.S.

6. Health Management Information Systems

7. Working with Health IT Systems

8. Installation and Maintenance of Health IT Systems

9. Networking and Health Information Exchange

10. Fundamentals of Health Workflow Process Analysis & Redesign

11. Configuring EHRs

12. Quality Improvement

13. Public Health IT

14. Special Topics Course on Vendor-Specific Systems

15. Usability and Human Factors

16. Professionalism/Customer Service in the Health Environment

17. Working in Teams

18. Planning, Management and Leadership for Health IT

19. Introduction to Project Management

20. Training and Instructional Design

(Lab components using VA VistA EHR)

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Program of Assistance for University-

Based Training (UBT)• Funding for education of individuals in workforce roles requiring

university-level training at nine universities with existing programs– Oregon Health & Science University (OHSU)

– Columbia University

– University of Colorado Denver College of Nursing

– Duke University

– George Washington University

– Indiana University

– Johns Hopkins University

– University of Minnesota (consortium)

– Texas State University (consortium)

• Emphasis on short-term certificate programs delivered via distance learning

• OHSU program run as “tuition assistance” program for existing programs– www.informatics-scholarship.info

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Telemedicine

• Delivery of healthcare where time and/or distance separate participants (Field, 2002)

• Classification of telemedicine (Hersh, 2001)– Store-and-forward– Office/hospital-based– Home-based

• Ongoing problem is quality of evaluation studies, which impedes coverage by insurers (Hersh, 2006; Ekeland, 2010)

• Most promising areas may be– Home telehealth (Darkins, 2008; Shea, 2009)– “Provider-to-provider” communications (Cusack, 2007;

McCambridge, 2010)

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Applications of knowledge-based

information• Information retrieval (IR) systems, aka search

engines, are widely available– Virtually all of the world’s biomedical literature is now

available electronically, but significant challenges still exist to its use (Hersh, 2008)

• Evidence-based medicine (EBM) is a proper framework for finding and applying knowledge in clinical care (Straus, 2005; Guyatt, 2008; Guyatt, 2008)– Although it must be applied properly in the larger

context of healthcare (Haynes, 2002; Cohen, 2004)

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Information retrieval – Hersh, 2009

• Focuses on indexing and retrieval of knowledge-based information

• Historically centered on text in documents, but increasingly associated with multimedia and even patient-specific information

• www.irbook.info

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Search systems are popular icons

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pubmed.gov

www.google.com

But new problems have emerged

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Overview of an IR system

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Metadata

Queries Content

Search

engine

Retrieval Indexing

The intellectual tasks of IR

• Indexing

– Assigning metadata to content items

– Can assign

• Subjects (terms) – words, phrases from controlled vocabulary, e.g.,

Medical Subject Headings (MeSH)

• Attributes – e.g., author, source, publication type

• Retrieval

– Most common approaches are

• Boolean – use of AND, OR, NOT

• Natural language – words common to query and content, usually

ranked by “relevance,” e.g., word counts, links (Google), etc.

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Some IR systems have advanced features,

e.g., Pubmed limits, clinical queries, etc.

Growing role of IR and related areas in

knowledge discovery

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All literature

Possibly relevant

literature

Definitely relevant

literature

Actionable

knowledge

Information

retrieval

Information

extraction,

text mining

(Hersh, 2009)

The life-cycle of knowledge-based

information – many roles for informatics

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Original

research

Write up

results

Submit for

publication

Publish

Secondary

publications

Peer

review

Public data

repository

Relinquish

copyright

Revise

Reject

Accept

Some major IR challenges

• “Open access” publishing, especially to taxpayer-funded research (Björk, 2009)

– NIH Public Access Policy aims to disseminate taxpayer-funded research better (publicaccess.nih.gov)

– Includes deposit of papers or final submitted manuscripts into PubMed Central (pubmedcentral.gov)

– Publishers’ alternative approach is DC Principles for Free Access to Science (www.dcprinciples.org)

• Linkage across “silos” and other applications, e.g.,

– Digital Object Identifier (DOI) – www.doi.org

– CrossRef project – www.crossref.org

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IR challenges (cont.)

• What are best approaches for users to enter

queries and for systems to provide output, e.g.,

– Google works well for Web searches, but is it best for

biomedicine and health?

– What about the needs of biomedical researchers, who

collect increasing amounts of data and whose

research touches on many other areas?

– What are best approaches for consumers with

different levels of education, medical knowledge, etc.

(Fox, 2011)?

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Applying EBM

• Steps of EBM

– Phrasing a clinical question that is pertinent and answerable

– Identifying evidence to address the question

– Critically appraising the evidence to determine if it applies to the patient

• There are some of the criticisms of the EBM approach (Cohen, 2004)

• This has led to growing advocacy for

– Evidence-based practice (Slawson, 2005; Dawes, 2005)

– Practical clinical trials (Tunis, 2003; Luce, 2009)

– Comparative effectiveness research (McGinnis, 2007; Murray, 2010)

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Hierarchy of knowledge-based

information (evidence)

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Systems –

actionable

knowledge

Synopses – concise evidence-

based abstractions

Syntheses – systematic reviews

and evidence reports

Studies – original articles published in journals

(Haynes, 2001)

Where does the best evidence come

from?

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Studies

Syntheses

Synopses

Systems

MEDLINE,

e.g., Pubmed

Journal

articles

Textbooks, compendia, guidelines

Guidelines, rules, order sets

Systematic reviews

Bioinformatics

• Area of informatics focused on cellular and molecular level– Usually associated with genomics, proteomics,

metabolomics, and other –omics

– Genome is the collection of all genes in an organism

• Translational bioinformatics focuses on application in human health and disease (Sarkar, 2011), presaging “personalized medicine” (Collins, 2010)

• New areas emerging due to changing nature of bioscience (Gibson, 2009; www.genome.gov)– Gene expression microarrays (Bier, 2008)

– Genome-wide association studies (GWAS) (Hardy, 2009)

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Informatics challenges become more

complex as science advances

• It used to be so simple – the central dogma

– DNA → mRNA → protein

– Genes in exons; rest is “non-coding” (used to be called “junk,” but is found to be increasingly important)

– Growing understanding of role of microRNAs (Hanrahan, 2011)

• Increased recognition that genomic variation plays important roles in disease, consisting mainly of

– Single-nucleotide polymorphisms (SNPs) (Lupski, 2007)

– Copy-number variations (CNVs) (Redon, 2006; Chen, 2011)

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Informatics challenges (cont.)

• Key focus now is genetic variation and its impact on health and disease (Hardy, 2009)

– Constant discovery of new genetic variants associated with development of common and uncommon diseases

– But need to be careful of spurious associations, e.g., the “incidentalome” (Kohane, 2006), and apply evidence-based approaches (Attia, 2009 – three papers)

• “High-throughput” technologies generate much data … and information needs, e.g., need for information retrieval and text mining (Cohen, 2005; Krallinger, 2008)

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Increased understanding of molecular

basis of disease impacts bioinformatics• And vice versa

• Case in point: cancer– “Hallmarks” of cancer point to cellular activities that

reduce cell death while increasing invasiveness (Hanahan, 2011; Johnson, 2011)

– Growing evidence that these changes enabled by changes in genome and its function (Cowin, 2010)

– These changes are manifested temporally (Durinck, 2011) and more readily measured with newer sequencing technologies (Meyerson, 2010)

– New resources, such as the Cancer Genome Atlas (Chin, 2008) and PharmGKB (Thorn, 2010), will guide research, diagnosis, and treatment

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Melding of bioinformatics and clinical

informatics: eMerge Network• Consortium aiming to link growing number of

biorepositories with sequenced DNA to data in EHR systems for “large-scale, high-throughput genetic research” (McCarty, 2011; Wilke, 2011)– Map the phenotype (EHR and tissue) to the genotype

(DNA sequences) using informatics

• Some early work includes use of NLP for– Replicating finding of known gene-disease associations

from research data in EHR data (Denny, 2010)

– Discovering new associations (Denny, 2010)

– Mapping to the phenotype, including controlled terminologies (Pathak, 2011)

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Informatics education and training

• Since a highly multi-disciplinary field, no standard curriculum or accreditation

– Listing of US programs on Web site of American Medical Informatics Association

• http://www.amia.org/education/programs-and-courses

– Description of OHSU program to follow as an example; consult other programs’ Web sites for details on their programs

– International perspective from International Medical Informatics Association (IMIA) recommendations (Mantas, 2010)

• Education has historically focused on academics but is evolving to meet the needs of practitioners and users

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Career pathways have diverse inputs

and outputs

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Health care professions, e.g.,

medicine, nursing, etc.

Natural and life sciences, e.g.,

biology, genetics, etc.

Computer science (CS), IT, and

undergraduate informatics

Health information

management (HIM)

Others, e.g., business, library

and information science

Jobs in:

• Health care systems

• Biomedical research

• Industry

• Academia

• Others

Graduate-

level

biomedical

informatics

education

Biomedical informatics education

at OHSU• http://www.ohsu.edu/informatics/• All at graduate level• Academic

– Predoc/Postdoc Fellowship funded by NLM and VA– PhD in Biomedical Informatics degree– Master of Science in Biomedical Informatics degree for postdocs

from other fields

• Professional– Master of Science and Master of Biomedical Informatics degrees– Graduate Certificate Program (distance learning)

• Liaison– OHSU-AMIA 10x10 program

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Informatics curriculum at OHSU –

general principles• Aims to cover the “full spectrum” of biomedical and

health informatics (Hersh, 2005; Hersh, 2007)

• Curriculum centered around “knowledge base”– Core knowledge at master’s level

– PhD adds advanced courses and research

– “Building block” approach allows progression to higher levels

• Have established three “tracks”– Clinical informatics

– Bioinformatics and computational biology

– Health information management

– Aiming to establish others, e.g., public health informatics

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“Knowledge base” and its “domains”

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Evaluative Sciences

Computer Science

Bioinformatics and

Computational Biology

Health Care Biomedical Sciences

Organizational and

management sciences

Biomedical

Informatics

Clinical Informatics Track Bioinformatics Track

Biostatistics

Electives and graduation

requirements

PhD

- Knowledge Base

- Advanced Research

Methods

- Biostatistics

- Cognate

- Advanced Topics

- Doctoral Symposium

- Mentored Teaching

- Dissertation

Building block approach to curriculum

Graduate Certificate

- Tracks:

- Clinical Informatics

- Health Information Management

Masters

- Tracks:

- Clinical Informatics

- Bioinformatics

- Thesis or Capstone

10x10

- Or introductory course

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Educating the liaisons – 10x10

• Partnership with American Medical Informatics Association (AMIA) to meet Safran’s (2005) stated need to educate one physician and one nurse from each of the 6000 US hospitals in informatics– Original goal to educate 10,000 healthcare professionals by 2010

• Course consists of introductory on-line course and adding one-day face-to-face session– Initial offerings well-received (Hersh, 2007; Feldman, 2008)

– Over 1000 have completed by 2010• About 15% going on to further study

– Program has continued beyond 2010

– Other partners are also offering courses

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Topics of OHSU 10x10 course

• Overview of Field and Problems Motivating It

• Biomedical Computing

• Electronic and Personal Health Records (EHR, PHR)

• Standards and Interoperability; Privacy, Confidentiality, and Security

• Meaningful Use of the EHR

• EHR Implementation and Evaluation

• Evidence-Based Medicine and Medical Decision-Making

• Information Retrieval and Digital Libraries

• Imaging Informatics and Telemedicine

• Translational Bioinformatics and Personalized Medicine

• Organizational and Management Issues in Informatics

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Educating beyond OHSU – distance

learning

• (Hersh, 2001)

• Initially in Graduate Certificate, later master’s

• Teaching modalities include

– Voice-over-Powerpoint lectures

– Threaded discussions

– Readings, virtual projects, etc.

• Courses are not correspondence courses; interaction is a core component

• Have created a virtual community

– Meet at AMIA, HIMSS, OHSU, etc.

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New models for education can be

developed with this technology

• Delivery to many parts of the globe, e.g., South America, Africa, etc.

• Translation of 10x10 course into Spanish for Latin American audience (Otero, 2010)

• Offered in partnership with Hospital Italiano of Buenos Aires, Argentina

• Over 600 participants from across Latin America have completed course

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Current and future directions

• OHSU program continues to innovate and grow

– Over 600 have matriculated since inception

– Over 300 alumni with jobs in healthcare settings,

academia, industry, and elsewhere

• Funding for study of clinical informatics available

for eligible students through, among others,

– ONC UBT program – winding down with end of

HITECH funding

– National Library of Medicine Training Grant

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Bringing it all together

• To achieve the vision of BMHI, we cannot lose focus of the information as well as the scientific processes to determine how to use it most effectively

• Informatics-trained professionals will lead the use of IT to improve healthcare and biomedical research

• Exciting research areas on the horizon– Improving healthcare delivery

– Enabling of patients and consumers in healthcare

– Genomics, bioinformatics, and personalized medicine

– Mining data to analyze and generate hypotheses for future biomedical research

• And how will the grand experiment of HITECH play out?

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For more information

• Bill Hersh– http://www.billhersh.info

• Informatics Professor blog– http://informaticsprofessor.blogspot.com

• OHSU Department of Medical Informatics & Clinical Epidemiology– http://www.ohsu.edu/informatics

– http://oninformatics.com

– http://www.informatics-scholarship.info

• What is BMHI?– http://www.billhersh.info/whatis

• Office of the National Coordinator for Health IT– http://healthit.hhs.gov

• American Medical Informatics Association– http://www.amia.org

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