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Surgical Clinic Module of HughesRiskApps
1. Beyond the EHR
Kevin S.Hughes, MD, FACS
Co-Director, Avon Comprehensive Breast Evaluation Center
Massachusetts General Hospital
Surgeon
The Newton-Wellesley Hospital Breast Center
2. EHR and productivity varies by specialty
100 internists, pediatricians and family practitioners
• Initial implementation
– 25 to 33 percent drop in MD productivity
• Over time
– Internists
• Slightly above original productivity
– Pediatricians and family practitioners
• Remained below original productivity
• Explanations
– Internists review data entered by others
• EMRs more efficient
– Pediatricians/family practitioners data entry and documentation
• EMR more time-consuming
Hemant Bhargava, UC Davis Graduate School of
Management
3. • Quote from a breast surgeon recently on a new EHR
• …our productivity is down 28%
• Everyone attributes this to the learning curve of xxxx EHR.
• I am the highest paid transcriptionist in the state
• Each cancer patient chart takes me apprx 1 hour
• For the first time in my career, I turned down an add-on patient
from one of my outside referrers because I just could not spend one
more hour putting a new patient into the computer
• I spent 5 hours on Saturday and 4.5 on Sunday catching up on charts
from Thurs and Friday and backloading charts of return patients for
Tuesday
4. The EHR is a filing cabinet, not a database. The interface is the same for a
pediatrician, a neurosurgeon, a cardiologist, and everyone else, as if every
specialist wanted data presented the same way.
EHR
Generic
Database
Filing Cabinet Interface
Or
Document Management System
5. Anesthesia, pathology and breast imaging
have set up their own databases and
interfaces to deal with their unique needs.
They send free text reports into the EHR as
the EHR lacks the ability to accept data.
EHR
Anesthesia Pathology
Interface Interface
Filing Cabinet
Or
Document Management System
Generic
Mammography Interface
Interface
7. Less work + CDS = Higher Quality
Patient enters data :
Tablet PC
iPad
Website
Patient
education
Clinical Decision al
Support materials
EHR Reviews Report &
Pedigree
Clinical Decision
Reviews suggested
Support Documents and
management
Orders
9. EHR
Breast RT Interface
Surgery
Interface
Breast MedOnc
Interface
10. Breast Surgery Module as the prototype
Can be adapted to other disciplines and other
cancers easily
• Designed to decrease clinician workload
• Increase quality by facilitating appropriate course of action
– Examples:
• Risk algorithms run real-time
• Referral letters generated real-time
• Improve patient satisfaction
– Provide educational materials real-time
• Store data needed for certification by NAPBC, ACoS, QOPI, and
others
– Easily retrieves most data needed for certification with minimal work
• Decrease cost
– Per above, savings in staff and workload
– Decrease in transcription costs of $6000 or more per clinician per year
11. HughesRiskApps modules follow a simple workflow
Existing data Patient data entry
Clinical Decision Support (CDS)
Printout with suggested actions
Clinician editing/enhancing
Clinical Decision Support (CDS)
Generate orders and documents
12. Choose how much data you want
the patient to enter via the Tablet
by choosing the type of survey
• Standard
– Basic risk information
• MGH Standard
– Basic risk information plus an extended medical
history
13. Using the HughesRiskApps Tablet questionnaire
(With added questions for the Surgery Clinic), a
patient can enter her own data
• Requiring little or no help from the
staff, patients enter their own data.
• 5th Grade Reading Level
• Available in English, Spanish and Italian
Sample screenshots follow
22. Patient data is downloaded from the
LMR (MGH home grown EMR) allowing
correlation with patient entered data
• Problem List
• Medications
• Allergies
• Procedures
Upload of data being developed. Interfaces with other EMRs in development.
23. Patient data is downloaded from the
LMR (MGH home grown EMR) allowing
correlation with patient entered data
Upload of data being developed. Interfaces with other EMRs in development.
24. Patient data is downloaded from the
LMR (MGH home grown EMR) allowing
correlation with patient entered data
Upload of data being developed. Interfaces with other EMRs in development.
25. Patient data is downloaded from the
LMR (MGH home grown EMR) allowing
correlation with patient entered data
Upload of corrected data being developed. Interfaces with other EMRs in development.
30. Entered by patient via tablet, Clinician/Staff can edit and enhance
SubTabs for Risk Factors, Family History (As Table), Pedigree, and Risk Analysis under
Tab for specific disease
31. Entered by patient via tablet, Clinician/Staff can edit and enhance
Can view/edit Family History via table or pedigree(See next slide)
32. Entered by patient via tablet, Clinician/Staff can edit and enhance
Can view/edit Family History via pedigree or table (See Prior slide)
33. Data entered by patient via tablet is used to run risk models
37. If the Impression includes surgery, Surgical Scheduling screen opens with appropriate
procedure pre-chosen.
Clinician can edit or change procedure as needed
38. Orders are pre-filled based on impression and procedures
Clinician can add/edit orders
39. A choice of letters and information
sheets are pre-chosen based on orders
42. At post operative visits, pathology data is entered and
the computer organizes and summaries
43. Table (Above gray area) shows the procedures and a pathologic summary of the results
The more detailed pathology view (Below gray area) relates to the SELECTED procedure
45. Future timeline
Will soon also include Timelines for Breast Imaging, Chemotherapy, RT, and Hormonal Therapy
In development
Not yet available
46. Breast Surgery Module as the prototype
Can be adapted to other disciplines that treat breast cancer, as
there is significant overlap of data collected
47. When the final surgery is completed, the cancer summary is derived from the pathology of
the individual procedures that had been entered by MD
The source of this data can be seen at
the procedures tab
48. After the final surgery, letters are generated to PCP summarizing
care, and to Med and Rad Onc, asking for consultation/opinion
49. Summary of surgery is sent to primary and as part of referral letters to
Medical Oncology and Surgical Oncology
50. Data needed for certification by
NAPBC, ACoS, QOPI, and others shown as a report
at any time
51. Breast Surgery Module as the prototype
Can be adapted to other disciplines that treat breast cancer, as
there is significant overlap of data collected
52. Breast Surgery Module as the prototype
Can be adapted to other cancers
• Ideally will serve as a module to any EHR