1. Innovation with
Commercial EHRs
Ken Ong, MD, MPH
CMIO, New York Hospital Queens

2. Queens is the most ethnically
diverse urban area in the world
with a population of over 2.2
million, 48% of whom are
foreign‐born,representing over
100 different nations and
speaking over 138 different
languages.

4.  Salvation Army opened the Rescue Home for Women in 1892 as a haven for
unmarried mothers in a humble house on East 123rd Street in Manhattan.
 During World War I, the facility opened a free medical service for the dependents
of enlisted men.
 In 1950’s, Salvation Army noticed a shortage of local general hospital facilities in
the vast farmland communities located to the east of the East River: Queens.
 In 1992, the hospital became an affiliate of the New York Hospital‐Cornell
Medical Center, which merged with Presbyterian Hospital in 1997 to form the
NYP Healthcare System.
 New York Hospital Queens has grown to become a 519‐bed acute care hospital,
that last year admitted more than 35,000 patients, had more than 139,000
outpatient visits, and treated 115,000 people through the emergency
department.
New York Hospital Queens

5. What’s an Innovation?

6. Everett Rogers,
Diffusion of Innovations
"an idea, practice,
or object that is
perceived as new
by an individual or
other unit of
adoption".

7. Everett Rogers, Diffusion of Innovations

8. How Far Have We Come?

9. Office‐Based Physicians Are Responding To Incentives And Assistance By Adopting And Using Electronic Health Records
By Chun‐Ju Hsiao, Ashish K. Jha, Jennifer King, Vaishali Patel, Michael F. Furukawa, and Farzad Mostashari. HEALTH AFFAIRS 32, NO. 8 (2013): 1470–1477

10. Office‐Based Physicians Are Responding To Incentives And Assistance By Adopting And Using Electronic Health Records
By Chun‐Ju Hsiao, Ashish K. Jha, Jennifer King, Vaishali Patel, Michael F. Furukawa, and Farzad Mostashari. HEALTH AFFAIRS 32, NO. 8 (2013): 1470–1477

11. 72 percent of physicians had adopted some type of
system and that 40 percent had adopted capabilities
required for a basic EHR system.
As of 2012, physicians in rural areas had higher rates of
adoption than those in large urban areas, and
physicians in counties with high rates of poverty had
rates of adoption comparable to those in areas with
less poverty.
However, small practices continued to lag behind larger
practices.
Office‐Based Physicians Are Responding To Incentives And
Assistance By Adopting And Using Electronic Health Records
By Chun‐Ju Hsiao, Ashish K. Jha, Jennifer King, Vaishali Patel, Michael F. Furukawa, and Farzad Mostashari. HEALTH AFFAIRS 32, NO. 8
(2013): 1470–1477

12. Adoption Of Electronic Health Records Grows Rapidly, But Fewer Than
Half Of US Hospitals Had At Least A Basic System In 2012
By Catherine M. DesRoches, Dustin Charles, Michael F. Furukawa, Maulik S. Joshi, Peter Kralovec,
Farzad Mostashari, Chantal Worzala, and Ashish K. Jha. HEALTH AFFAIRS 32. NO. 8 (2013): 1478–1485

13. Adoption Of Electronic Health Records Grows Rapidly, But Fewer Than
Half Of US Hospitals Had At Least A Basic System In 2012
By Catherine M. DesRoches, Dustin Charles, Michael F. Furukawa, Maulik S. Joshi, Peter Kralovec,
Farzad Mostashari, Chantal Worzala, and Ashish K. Jha. HEALTH AFFAIRS 32. NO. 8 (2013): 1478–1485

16. Adoption Of Electronic Health Records Grows Rapidly, But Fewer Than
Half Of US Hospitals Had At Least A Basic System In 2012
By Catherine M. DesRoches, Dustin Charles, Michael F. Furukawa, Maulik S. Joshi, Peter Kralovec,
Farzad Mostashari, Chantal Worzala, and Ashish K. Jha. HEALTH AFFAIRS 32. NO. 8 (2013): 1478–1485

17. The US health care system is in the midst of an enormous change in the way health care
providers and hospitals document, monitor, and share information about health and
care delivery. Part of this transition involves a wholesale, but currently uneven, shift
from paper‐based records to electronic health record (EHR) systems. We used the most
recent longitudinal survey of US hospitals to track how they are adopting and using EHR
systems. Only 44 percent of hospitals report having and using what we define as at
least a basic EHR system. And although 42.2 percent meet all of the federal stage 1
“meaningful‐use” criteria, only 5.1 percent could meet the broader set of stage 2 criteria.
Large urban hospitals continue to outpace rural and nonteaching hospitals in adopting
EHR systems. The increase in adoption overall suggests that the positive and negative
financial incentives currently in place across the US health care system are working as
intended. However, achieving a nationwide health information technology
infrastructure may require efforts targeted at smaller and rural hospitals.
Adoption Of Electronic Health Records Grows Rapidly, But Fewer Than
Half Of US Hospitals Had At Least A Basic System In 2012
By Catherine M. DesRoches, Dustin Charles, Michael F. Furukawa, Maulik S. Joshi, Peter Kralovec,
Farzad Mostashari, Chantal Worzala, and Ashish K. Jha. HEALTH AFFAIRS 32. NO. 8 (2013): 1478–1485

18. Some Hospitals Are Falling Behind In Meeting ‘Meaningful
Use’ Criteria And Could Be Vulnerable To Penalties In 2015
By Catherine M. DesRoches, Chantal Worzala, and Scott Bates. HEALTH AFFAIRS 32, NO. 8 (2013): 1355

19. Some Hospitals Are Falling Behind In Meeting ‘Meaningful
Use’ Criteria And Could Be Vulnerable To Penalties In 2015
By Catherine M. DesRoches, Chantal Worzala, and Scott Bates. HEALTH AFFAIRS 32, NO. 8 (2013): 1355
 Our analysis of Medicare data found a substantial increase in the percentage
of hospitals receiving EHR incentive payments between 2011 (17.4 percent)
and 2012 (36.8 percent). However, this increase was not uniform across all
hospitals, and the overall proportion of hospitals receiving a payment for
meaningful use was low.
 Critical‐access, smaller, and publicly owned or nonprofit hospitals appeared
to be at particular risk for failing to meet Medicare’s meaningful‐use criteria,
and the overall proportion of hospitals receiving a payment for meaningful
use was low.
 Starting in 2015, hospitals that fail to meet the criteria will be subject to
financial penalties. To address the needs of institutions in danger of incurring
these penalties, policy makers could implement targeted grant programs
and provide additional information technology workforce support. In
addition, the capacity of EHR system vendors should be carefully monitored
to ensure that these institutions have access to the technology they need.

20. Meaningful Information ExchangeMeaningful Information Exchange

21. Operational Health Information Exchanges Show
Substantial Growth, But Long‐Term Funding Remains A
Concern
By Julia Adler‐Milstein, David W. Bates, and Ashish K. Jha. HEALTH AFFAIRS 32, NO. 8 (2013): 1486

22. 30 percent of hospitals and 10 percent of ambulatory
practices now participate in one of the 119 operational
health information exchange efforts
However, we also found that 74 percent of health
information exchange efforts report struggling to
develop a sustainable business model. Our findings
suggest that despite progress, there is a substantial
risk that many current efforts to promote health
information exchange will fail when public funds
supporting these initiatives are depleted.
Operational Health Information Exchanges Show Substantial
Growth, But Long‐Term Funding Remains A Concern
By Julia Adler‐Milstein, David W. Bates, and Ashish K. Jha. HEALTH AFFAIRS 32, NO. 8 (2013): 1486

23. Innovation with a Commercial E.H.R.

24. NYHQ live with Eclipsys Sunrise CPOE in 2006
Attesting to Meaningful Use Stage 1, Year 2,
in October 2013
Upgrading to 2014 certified Allscripts Sunrise
in December 2013
E.H.R. Adoption at NYHQ

25. Order Sets
Clinical Documentation
Medical Logic Modules (MLMs)
Clinical Analytics
Clinical Decision Support
Interventions to Improve Quality

26.  Alert Physician that there are no allergies documented for Drugs or Drug
Categories
 Alerts clinician ‐ when a hematocrit is falling rapidly, not when a hematocrit is
low or falling slowly
 Alerts clinician ‐ when a high glucose result is received for a patient ‐ this can
alert when an order for such medication is placed AND patient has recent high
glucose.
 Alerts clinician ‐ when a high potassium result is received for a patient ‐ when
there is a high potassium AND patient is receiving medications that can continue
to elevate potassium further ‐ when an order for such medication is placed AND
patient has recent high potassium.
 Alerts clinician ‐ when a high sodium result is received for a patient ‐ this can
alert when an order for such medication is placed AND patient has recent high
sodium.
 Alerts clinician ‐ when a low creatinine clearance result is received for a patient
and the patient has current orders for conflicting medications ‐ when an order
for such medication is placed AND patient has recent low creatinine clearance
A Sample of Our 229 MLMs

27.  Alerts clinician ‐ when a low glucose result is received for a patient ‐ this can alert
when an order for such medication is placed AND patient has recent low
glucose, but default is set to NOT alert on order entry.
 Alerts clinician ‐ when a low potassium result is received for a patient ‐ when a
potassium is falling ‐ when there is a low potassium AND patient is receiving
medications that can continue to lower potassium further ‐ when an order for
such medication is placed AND patient has recent low potassium.
 Alerts clinician ‐ when a low sodium result is received for a patient ‐ when a
sodium is falling ‐ this can alert when an order for such medication is placed AND
patient has recent low sodium.
 Alerts clinician ‐ when the platelets are falling AND patient is receiving
medications that can continue to lower platelets further ‐ when there are a low
platelets AND patient is receiving medications that can continue to lower
platelets further ‐ when an order for such medication is placed AND patient has
recent low or falling platelets.
 Calculate ingredients for TPN Order
 Calculates Padua Model DVT risk assessment score
A Sample of Our 229 MLMs

28.  Chemical & mechanical restraints
 Create ED pediatric sepsis alert in ED Nursing Triage Note
 Critical lab values post a flag in the 'Unacknowledged Alerts'
column. Clicking on the alert shows the lab result and provides
an opportunity to document the response.
 Fires 'Name Alert' in 'Similar Name' column of patient list
 Generate an alert to prevent duplicate diet order
 Heparin dosing related
 If a previous echocardiogram was ordered, the following alert
is given: "Please note: a previous transthoracic echocardiogram
was ordered on [date]".
A Sample of Our 229 MLMs

29.  If carboplatin is selected, the following alert is given: "AUC
Cockgraft‐Gault calculator is defaulted to utilize IDEAL body
weight. Choices for ACTUAL and ADJUSTED body weight are
available by changing the default in the dose calculator. Please
utilize 'AUC (Cockgraft‐Gault actual)' when a patient's actual
body weight is LESS than their ideal body weight to ensure
appropriate dose."
 Insulin dose calculated
 Place an CDiff +ve result comment in the header at the time of
result posting.
 Provide INR Lab Results and Prior Dosing History on the Order
Set Form
 Pulls in any infection control precautions into the radiology
requisition order form
A Sample of Our 229 MLMs

30.  Pulls in current insulin dose into a new Endocrinology consult or
progress note.
 Pulls urine or blood HCG results into the radiology order form for
women between the ages of 9 and 55. If the HCG is positive, an alert is
tiggered: "WARNING: Patient with positive HCG on [date]. This may
indicate pregnancy. Please be aware when ordering radiographic
studies." If the pregnancy status is unknown, the following alert is
given: "NOTE: No pregnancy test is charted on this patient. Please
indicate the pregnancy status and consider pregnancy testing if
appropriate."
 Requires reasons for omission if no DVT prophylaxis is ordered
 Retrieves hemoglobin and platelet results when either a blood or
platelet transfusion is ordered.
 RxWriter (discharge medication app): Alert to user when dosage
amount is zero or missing Alert to user when Frequency is zero or
missing Alert to user when Quantity is zero or missing
A Sample of Our 229 MLMs

31.  Start ExitCare application from a document list radio button.
 The ED Nurse Triage assessment places a flag on the ED display board
and fires an alert ("This patient has met modified SIRS criteria and may
be at risk for serious infection.") if the temperature, pulse, respirations
or blood pressure are more or less than defined parameters for
children for particular ages.
 This MLM will create C‐Diff infection alert header when patient
readmitted and he had that infection in most recent visit.
 To pull active DNR order list and insert in DNR order section of
Summary of Care|Discharge|Transfer Note
 To warn the person ordering NPO or dc tube feeding, that the patient
is on hypoglycemic drug(s) and may require supplementation.
 tPA dose calculation
 Warn user that concurrent use of anticoagulants, antiplatelets, and
thrombolytic medications are prohibited with indwelling neuraxial
catheters
A Sample of Our 229 MLMs

32. NYHQ’s New York City Designated Stroke Center

33. Stroke P.I. Initiative 2012‐2013
 From paper to electronic documentation, i.e., NIH
Stroke Scale
 Stroke coordinator hired
 Modified Rankin Scale added to nursing note
 VTE prophylaxis order set improved
 Branching logic added to core measure section in
Summary of Care note

34. Summary of Care Note:
Branching Logic to Capture Hospital Inpatient Quality
Reporting Core Measures

35. NIH Stroke Scale
Total Score Automatically Calculated

36. DVT Risk Assessment: Padua Model
Total Score Automatically Calculated

37. Stroke Measures Improved
Measure Nov‐12 Dec‐12 Jan‐13 Feb‐13 Mar‐13 Apr‐13 May‐13 Jun‐13 4 Months Pre 4 Months Post Change
Modified Rankin Scale at Discharge 17.9% 18.9% 37.5% 10.5% 22.8% 43.0% 72.1% 76.7% 21.2% 53.7% 153.1%
VTE Prophylaxis 62.5% 71.9% 59.5% 72.9% 90.7% 93.4% 91.1% 100.0% 66.7% 93.8% 40.6%
Dysphagia Screen 52.6% 38.1% 52.9% 41.3% 39.1% 58.0% 63.5% 64.9% 46.2% 56.4% 22.0%
Stroke Education 89.7% 78.9% 100.0% 82.6% 95.2% 100.0% 95.9% 100.0% 87.8% 97.8% 11.4%

38. Protected
Health
Information
Redacted

41. Adopting MU2 Innovations:
Inpatient
 View, Download, & Transmit (VDT)
 Medication Reconciliation Application
 Bar Code Medication Administration
 Electronic Transmission of Summary of Care to
HIE (Healthix)
 Reporting MU2 compliant Syndromic
Surveillance & Reportable Diseases

42. Adopting MU2 Innovations:
Ambulatory
View, Download, & Transmit (VDT)
Expanding Patient Engagement
Patient‐Provider Secure Health
Messaging
Appointment requests
Medication refill requests

43. Ken Ong, MD, MPH
e‐mail = keo9016@nyp.org
Twitter = @kenongmd
URL = kenongmd.com