1. Productivity tools in healthcare IT
systems (HIS & LIMS), their relation with
patient care and developing objectivity
in clinical management
DR CHIRANTAN BOSE MD
VICE PRESIDENT – CLINICAL AFFAIRS
MEDGENOME LABS, BANGALORE
NARAYANA HEALTH CITY
3. The Concept framework
Data entry
into
EMR/LIMS
Matrices /
objective
evidence of
given clinical
scenarios
Meta-Analysis
Change to
management
/ preventive
measures
Clinical
process flow
Modification
in patient
management
Predicting care
management
outcomes
Financial
oversight and
planning
6. Researchers at the University of California at
Davis studied how an EMR implementation at
six primary care offices affiliated with the
same academic medical center affected
physician productivity levels. They found that
after an initial dip in productivity during the
training period -- which is normal -- internists
were able to increase productivity above pre-
EMR rates
Experts stress that implementation is an
ongoing process. Because health care takes
place in a continually changing environment,
the processes used by physicians to navigate
that environment must adapt.
10. • EHR use by office-based physicians rose from 18% in 2001 to 48% in
2009, and finally to 78% in 2013. (Source: CDC)
• Roughly 60% of physicians say they are satisfied with their EHR
system. (Source: Deloitte)
• Use of EHR is associated with significantly higher quality of care for
breast cancer screening, Chlamydia screening, colorectal screening,
and diabetes testing for hemoglobin. (Source: Journal of General
Internal Medicine)
• 67% of physicians report EMRs save them time through e-prescribing,
and that EMRs improve care coordination due to interoperability.
(Source: Deloitte)
11. Proportion of electronic
medical record (EMR) use
and proportion of solo
practitioners by specialty
type. Proportion of solo
practitioners by specialty
was determined by the
number of physicians who
reported being in solo
practice to the National
Ambulatory Medical Care
Survey.
J Am Med Inform Assoc.
2013 Jun; 20(e1): e33–e38.
12. Cumulative frequencies of electronic medical record (EMR) use among 14 different medical specialties from 2003
to 2010. Percentages represent unadjusted frequencies and represent both part and full EMR use combined.
p<0.0001 for the difference between 2003 and 2010 frequencies in all specialties listed. The oncology stratum was
not sampled in 2003.
15. • 37% of physicians see EHR as their number one challenge; tied with
financial issues as their primary concerns. (Source: Hello Health)
• 30% of doctors think EHR implantation would hurt practice finances due to
higher costs and overhead or productivity decreases. (Source: Hello Health)
• 51% of physicians who say financial issues are their primary concern felt
implementing an EHR would help. (Source: Hello Health)
• 54% of physicians are not happy with their EHRs’ interactivity. (Source:
Fierce EMR)
[Note : The survey also found that the brands used by the largest percentage
of respondents are EPIC (22 percent), Allscripts (10 percent) and Cerner (9
percent). However, the top ranked ones were Amazing Charts, Practice
Fusion, VA-CPRS, Medent and e-MDs.]
16. Summarising the challenges
• A single patient – multiple doctors – multiple hospitals/clinics –
multiple labs – multiple medication
• Information in different formats – harmonisation issue !
• Longitudinal tracking is difficult
• Different patients – similar clinical factors – similar scenarios and
outcomes – difficult to be clubbed a trend
18. Longitudinal data becomes simple to
interpret
• Mr A has been suffering from Chronic perennial bronchitis which has been associated with
fluctuant eosinophil counts of 10 – 20% and IgE levels of 150 – 300 since 2003. Drainage
procedures were performed on frontal sinusitis. There have been peaks of deterioration during
winter months. Preventive measures instituted, Vit D measurement and prophylaxis.
0
50
100
150
200
250
300
350
400
Selected parameters
Eosinophil IgE Vit D
19. Each medical centre is different and has
different workflows
• Understanding of the given organisational pattern:
• How they work / What’s their modus operandi ?
• What are they looking to achieve (eg reduced hosp stay; cost effective care;
work as a referring centre)
• What do the leaders wish to monitor?
• How much time do they invest in each workstation ?
• What are their pain points ?
• Where is paper used ?
• Where do communication gaps exist (eg lab and supply chain; ER and lab;
registration desk and report dispatch desk)
20. Some examples of a favourable framework of
a healthcare IT system :
• User can customise the interface on a need based fashion (eg
dropdown selection of symptoms or progression notes)
• User can select parameters of MIS (eg time of patient registration Vs
volume of lab tests ordered vs clinical consultation duration)
55
1023
48
No of OP reg
8 am - 11 am 11 am - 2 pm
2 pm - 5 pm 5 pm - 8 pm
42
35
23
20
No of lab orders
8 am - 11 am 11 am - 2 pm
2 pm - 5 pm 5 pm - 8 pm
14
1625
8
per clinician per consultation
duration (min)
8 am - 11 am 11 am - 2 pm
2 pm - 5 pm 5 pm - 8 pm
21. • Singular user logins – swipe card / biometric
• Ease of patient data retrieval through variable search options
• Categorisation on equipment eg within lab – interface of all data (eg
patient/sample records, scatter plots, photomicrographs, quality
control, references, reflex work-ups
22. IBM Health’s data combined with Truven’s patient records will create an enormous big-data
collection representing 300 million patient lives
IBM said that, post-acquisition, it will have one of the world’s largest and most diverse collections of health
data within IBM Watson Health. Watson Health currently delivers these cloud-based services:
• Analysis of data;
• Interpretation of complex questions; and
• Evidence-based answers to doctors, research, insurers, and others.
“Truven contributes vital payment information on patients.
And payment records include detailed coding on disease
types, diagnosis, drugs prescribed, and clues to outcomes
if, say, a patient does not respond to one treatment and is
given another. It’s a very key cog to give us one of the
most complete data sets on patients and healthcare in the
world.” said John Kelly, PhD IBM’s Senior Vice President of
Cognitive Solutions and IBM Research in a New York Times
article
23. Major Lab related – Operational challenges
• Monitoring Return on Investments
• Inventory Management –
• on-board inventory, productive consumption, QA consumption, wastage, repeats
• Off-board instrument side ; off-board central inventory
• Laboratory personnel behavioural aspects :
• Possessiveness towards assets
• Non-resilience towards new practice adherence
• Continued compliance issues
• Deficit of tools to provide clinical trends pertaining to individual patients or
trends pertaining to disease segments or trends pertaining to
interpretational results
• Deficit of tools to visualise multi-lab location productivity
How much/
where/
commercials/
trend
24. Metrics of Productivity & Efficiency
Heirarchial
interest
Measuring tools /
Indicators
Activity Involved
Corporate
management
Return on Investment /
Gross turnovers
Investment / Capital /
Networking
Lab / Dept
Management
P&L; Overall
performance indicators
eg TAT
Resource management ;
Scientific /clinical
oversight
Technical
workforce
(Supervisory staff)
QA data, Instrument
data, Specimen data,
patient records
Analytical workflow
management
Bench staff Generation of data Specimen management
IncreasingfocusonProductivity
IncreasingfocusonEfficiency
25. Solutions
• Create user interface templates by importing word doc forms
• Import test related or patient information from excel/pdf/jpeg etc
• Realtime access to SOPs
• Unified technology platforms (eg Specimen mgt systems/LIMS + inventory
mgt system + interfaces + billing + document control system + mobility
system)
• Integration between clinical / lab sub specialities
• Customization of rules by end user (eg shoot an email of sub-adequate
specimen qty to client) without vendor involvement
• Enable mobile accessibility
• Customisable BI tools
