Data analytics and Access Program Recommendations

Data analytics and Access Program

1. 1
Current as of 10/19/2020
Phase 1B Recommendations and Roadmap
DAAP –Data Architecture
and Analytical Platform
February 5, 20XX

2. 2
Current as of 10/19/2020
Focus Areas
The Data Driven Organization
Summary of Findings
TOWS Analysis
Voice of the Enterprise
Primary Issues
Data Strategy
Business Requirements
Architecture
Current
Phase 1B
Phase 2 Transition
Phase 3 Transition
Program Definition
Appendix

3. 3
Current as of 10/19/2020
The Data Driven Organization
❑What is it?
ᵒUse of Analytics to make fact-based business decisions
ᵒGather relevant data from all aspects of the business
❑What does it Mean?
ᵒHigh variety of data for analysis
ᵒAccess as needed
ᵒData is centralized and organized
ᵒTools allow for intuitive reasoning and are easy to use
❑How? (Organization and Resources)
ᵒCapabilities are challenged
ᵒCapabilities are transformed

4. 4
Current as of 10/19/2020
Summary of Findings

5. 5
Current as of 10/19/2020
Threats
•Loss of relevance
•Clients taking data and doing
their own analytics
•Lack of interest to pursue
work associated with data
strategy
•Lack of funding available to
implement data strategy
•Client belief that as a captive
malpractice insurance
provider that it is impervious
to outside competition or
changes in the healthcare
industry
Opportunities
•History and Size of current
base can entice new
Institutions to use Client for
business intelligence and
analytics
•Access to large hospital
population provides sizable
denominator base
•Increase in availability of
data from 3
rd
parties allows
for increased analysis and
reporting
•Strong relationships with
current institutional base
•Changes in technology allow
for increased ease and
efficiencies in analysis of data
Weaknesses
•Underlying data structure
and organization does not
support requisite reporting
and business intelligence
•No ‘single source of the
truth”
•Single point of addressing
analytics issues
•Structure on which CRIT was
developed has been retired
by the vendor
•Extensively modified vendor
software inhibits upgrade
path and scalability
•This is the 4
th
time an
assessment of this type has
been undertaken –this may
indicate a lack of
commitment
•Report KPIs have not
changed, differ
•No internal KPIs
Strengths
•Strong analytics base and
understanding of needs of
the customer
•Strong analytics skillset
available in-house
•Repeatable report and query
types make generation of
analytics easier
•Age and size make Client a
perceived force to be
reckoned with
TOWS Analysis

6. 6
Current as of 10/19/2020
Who we Spoke With
Name Department Date
IT
IT
Patient
Safety
IT
IT
CEO
Patient
Safety
Graphics
Patient
Safety
Underwriting
Patient
Safety
Strategies
Name Date
Finance
CFO
Patient Safety
CMO
Claims
Claims
Finance
Patient Safety
IT
CIO
IT
IT
IT

7. 7
Current as of 10/19/2020
Voice of the Customer
What is the right
Analytics tool for
our business?
I rely on institutional
knowledge for data access
& data usage..… wish
there was a better way.
What is this data field?
Has any other team built a similar
metrics that we can leverage?
It takes a long time and
cost a lot to add data to
EDW.
Where should I look for
my data?
There are no guiding
principles for us
(users) to do what we
should be doing!
Wish I could get data
from EDW whenever I
want to and faster!

8. 8
Current as of 10/19/2020
Organizational
•Reluctance to change
•Lack of interest; it’s “Good Enough”
•Reactive rather than Proactive
•Ineffectively align (e.g., silos)
•Lack of effective coordination and collaboration across departments
•Business Units and organizations leery to share data
•Difficult to gain consensus on Assumptions & Parameters
•Difficult to match data to business needs
•Primary Care example
•Difficult to establish business rules and drivers
•Distrust in IT’s ability to serve organization
•“Just give me all the transaction data and I’ll do the analytics…”
Voice of the Enterprise

9. 9
Current as of 10/19/2020
Process
•Lack of governance
•Unknown ownership of data, subject, or application
•Exhaustive manual manipulation required to produce a single report (pervasive observations and comments)
•2—3 months to develop typical report
•1 year to develop Benchmark report
•Ad-hoc, one-off nature of report builds
•No library for standard queries
•Business rules differ
•Business Rules embedded in scripts, ETL, queries
•Business Rules also differ due to latency and developer
•Coding differences
•Manual collection and application data
•3
rd
party provided
•Location
•Practice
•“Be able to predict before it happens”
•“Organization grapple with what it does not know and cannot solve for”
•“Lack of Clarity”
•“Everything requires an analyst.”
Voice of the Enterprise

10. 10
Current as of 10/19/2020
Technology
•Data Architecture that does not support Reporting and Business Intelligence, or move into Advanced Analytics
•No ‘single source of the truth”
•Structure on which CRIT was developed has been retired by the vendor
•Extensively modified vendor software inhibits upgrade path and scalability
•Poor performance of applications, queries, and scripts
•Cannot rollup or aggregate properly
•Cannot apply corrections to source systems
•Confusing mart structures, naming conventions
•Distrust of the quality and veracity of data, reports; irreconcilable differences
•Manual data quality maintenance
•80% time spent cleansing & prepping data
•Difficulty providing historical views, as-of, as-was processing
•Shadow IT (pervasive observations)
•Data held locally that is unavailable to the enterprise
•Individual’s knowledge not shared outside business unit
•Addresses inability of IT to service organization
•Cannot leverage proper resources
•3
rd
Party data
•Locally held data
Voice of the Enterprise

11. 11
Current as of 10/19/2020
Client Data Strategy
Crawl
•“Do better with what we
have…”
•Restructure Data
Architecture to support
initial set of reports
•Bring in initial 3
rd
Party
Data
Walk
•“Use current data in a
way that is more
meaningful…”
•Additional reports
•Iterative and Incremental
Expansion of supporting
Data Architecture
Run
•Systematic use of 3
rd
Party Data
•Additional reports
•Iterative and Incremental
Expansion of supporting
Data Architecture
Fly
•Advanced Analytics
•Predictive and
Prescriptive Analytics
•Data Mining
•Additional Supporting
Technologies required
(e.g., Data Lake, Internet
of Things, Big Data)
Identify Risk
Understand Risk
Mitigate Risk
Predict Risk
Backward Looking Forward Looking

12. 12
Current as of 10/19/2020
❑Providing Consistent, Integrated Data
ᵒA Single Source of Truth
ᵒEliminating the need for individual Departmental Marts
❑Making Data Available Across the Enterprise
ᵒEnsuring that everyone has access to the same information
ᵒEliminating the need for ‘Shadow’ Marts
❑Providing Consistent Reporting
ᵒAllowing for differences in methodology, the same question asked of different people
should yield the same result
❑Governance
ᵒEnsuring the ownership and quality of the data
❑Aging Technologies
ᵒIncreasing functions and features
ᵒReducing costs and maintenance issues
Primary Business Requirements

13. 13
Current as of 10/19/2020
Same Data Used by All Resources Manifestations
Issue Examples •Root Cause People Process Technology Proposed Solution
•Proliferation of
conflicting data
•Terminology
•Methodology
•Business Rules
•Metrics
•SMT cannot make
informed business
decisions
•Incurred Loss (e.g.,
different Incurred
Loss results
produced by CRIT
and BO)
•Case Rates per 100
PCY
•Finance
•Patient Safety
(Claims)
•Lack of Governance
•No Metadata
Management
(e.g., business
glossary;
derivations,
business rules,
and metrics
catalogs)
•No “Single Source
of Truth”
•Tolerance of
substandard
behaviors
•Necessityfor
workarounds
•Locally held and
maintained data
•Data not shared
across
enterprise
•Reports produced
using different
tools leads to
discrepancies that
are difficult to be
adequately
reconciled
•Differing or
inconsistent
definitions and
derivations
•Finance
•Claims
•Patient Safety
•Arbitrary
application of
business rule,
metrics, and
derivations
•Lack of automation
leads to extensive
manual
manipulation of
data
•Lack of integrated
data
•Excel is not an
enterprise
database
•Business rules,
metrics, and
derivations
embedded in ETL,
Scripts, and
Application
customizations
over time,
inconsistently
•Uncouple
embedded
business rules,
metrics, and
derivations from
ETL and script and
queries
•Create Business
Glossary with
conformed, agreed
upon definitions
•Create Metric
Catalog using
conformed
definitions and
establishing
precise derivations
•Create new ETL to
extract source data
•Create new
underlyingdata
structures
Provide consistent, integrated data

14. 14
Current as of 10/19/2020
Data from Same Source AvailableAcross
Enterprise
Create “Single Source of Truth”
Manifestations
Issue Examples Root Cause People Process Technology Proposed Solution
•Inability to
incorporate
additional
departments' data
•Inability to handle
specialized or
boutique
institutions
•SMT cannot make
informed business
decisions
•Underwriting and
Claims difficult to
link
•PremiumCollected
versus Payouts
•Primary Care
•Manually tracking
ofTrial Results
•Locally held
Finance Data
•Lack of governance
•Mastering of
data Location
•Practice
•Reference
Data (e.g.,
Taxonomies,
Classification
Schemes,
Hierarchies)
•Data models
•Ineffectively
structured
database and data
marts
•Tolerance of
substandard
behaviors
•Necessityfor
workarounds
•Locally held and
maintained data
•Data not shared
across
enterprise
•Individual
departments focus
on solvingtheir
critical issues
•Do not
recognize
opportunities
for collaboration
•Necessityfor
workarounds
•Locally held and
maintained data
•Data not shared
across
enterprise
•Improperly
structured data
does not support
historical analyses
•Inability to support
competing
perspectives
•Inability to
properly aggregate
data
•Create “Single
Source of Truth”
•Procurement of
Vendor MDM
Solution
•Restructure data to
support
integrated,
enterprise
reporting
•Aggregations
•History
•Competing
Perspectives
•Dimensional
Make that data available across the enterprise

15. 15
Current as of 10/19/2020
Same underlying data supportsCompeting
Perspectives
Manifestations
Issue Examples Root Causes People Process Technology Proposed Solution
•Lack of integrated
enterprise data
repository
•SMT cannot make
informed business
decisions
•Quarterly Report
•Inability to perform
as-of, as-was
reporting
•Lack of governance
•No Metadata
Management
(e.g., business
glossary;
derivations,
business rules,
and metrics
catalogs)
•Mastering of
data Location
•Practice
•Reference
Data (e.g.,
Taxonomies,
Classification
Schemes,
Hierarchies)
•Data models
•Libraryof
Standard
Reports
•Catalog of
Standard
Metrics
•No “single source
of the truth”
•Tolerance of
substandard
behaviors
•Plethora of tools
and scripting
confounds
ability to
provide
consistent
reporting
•Cobbling
together reports
using data from
various tools
•Necessitates
multiple queries
to satisfy singe
requirements to
avoid inflating
reported values
•Lack of
automation
leads to
extensive
manual
manipulation of
data
•Current
complement
•SAP Business
Objects
•Tableau
•SAS
•Scripts
•Inability to
support
competing
reporting
perspectives
•Inability to
properly
aggregatedata
•Inability to
report on
requisite
dimensions
•Create “Single Source
of Truth”
•Incorporated
governance into SDLC
•Gates
•Create new report
definition,
implementation, and
execution parameters
•Create standardized
parameter-based
reporting structures
•Portal
•Self-service
•Facilitate Ad-hoc
requests
Provide Consistent Reporting

16. 16
Current as of 10/19/2020
Instill Quality, Reliability, and Confidence Manifestations
Issue Examples Root Cause People Process Technology Proposed Solution
•Insufficient Data
Governance in
place
•Ownership
•Accountability
•Metadata
Management
•Mastering of
Data
•Lost Productivity
•Loss of Confidence
in Data
•Governance in-
place
•Business
Analytics
Meetings
•Data
Stewardship
Meeting
•Underwriting
Policy Task
Force
•Prevalent distrust
of quality of data
available
•No data ownership
assigned
•No data-related
accountabilities
assigned
•Relationship
betweenBusiness
and IT
•Lack of intolerance
for substandard
behaviors
•Necessityfor
workarounds
•Locally held and
maintained data
•Data not shared
across
enterprise
•Difficult for teams
to resolve inter-
departmental
issues
•Lack of automation
leads to extensive
manual
manipulation of
data
•Inability to
effectively manage
and change
business
requirements
•Inability to
perform Cross-
business unit
requirements
analysis
•Lack of automation
•Data changes
manually
maintained in
Excel spreadsheet
that reside on a
local machine
•Changes not
reflected in source
systems
•Changes are not
fedback to source
systems for update
•Stand up Data
Governance
Organization
•Automate
Governance
Processes
Governance

17. 17
Current as of 10/19/2020
Ease of Use and Maintenance
Costs Associated
Manifestations
Issue Examples Root Cause People Process Technology Proposed Solution
•CRIT and other
technologies have
reached point of
obsolescence
•Lack of vendor
support
•Lack of upgrade
path
•Can no longer sell
capabilities to
clients
•CRIT
•Has become
ostensibly
unusable
•Suffers from
extremely poor
performance
•Current MDM is
custom developed
software
•No accountability
assigned for tool
usage
•Lack of funding for
upgrades or
replacement
•Tolerance of
substandard
behaviors
•Causes extensive
reliance on manual
manipulations to
provide reporting
•Severely curtails
ability to provide
timely reports
from CRIT-held
data
•CRIT
•Seen as being
accurate
•Extremely poor
performance
•Unsupported
Technology
(Microsoft
ProClarity)
•MDM
•Home-grown,
customsoftware
•Not extensible,
scalable, or
flexible
•Lack of upgrade
path
•Business Objects
•Outof rev
•Thoroughly
decompose CRIT
capabilities and
outputs
•Instantiate CRIT-
provided
capabilities using
Business Objects
•Provide client-
facing portal to
new capabilities
•Articulate and
instantiate proper
security
•Upgrade Business
Objects to current
release
Aging Technologies

18. 18
Current as of 10/19/2020
Architecture

19. 19
Current as of 10/19/2020
Current State

20. 20
Current as of 10/19/2020
Phase 1B State

21. 21
Current as of 10/19/2020
Phase 2 Transition

22. 22
Current as of 10/19/2020
Phase 3 Transition

23. 23
Current as of 10/19/2020
Future State

24. 24
Current as of 10/19/2020
DAAP Program Definition

25. 25
Current as of 10/19/2020
Phase 1B
•Deliver prioritized set of 6
reports targeted for internal
RMF needs
•Build foundational Data
Management components
•Build EDW with focus on
subset of Data entities
(claims, case financials, OPE,
Reference data)
•Bring RMF and strategies
data into EDW for those
entities
•Build basic business glossary
and metrics catalog
(foundation for Data
Governance)
Phase 2
•Deliver next set of 8 reports
for internal RMF needs
•Evaluate and migrate CRIT
reports to EDW
•Build external portal to
deliver CRIT reports
•Bring MMS data into EDW
•Extend and scale
foundational Data
Management components
•Build and Scale data
governance
Phase 3
•Migrate rest of existing BO
reports and Sunset existing
BO reports/environment
•Bring external 3
rd
party ANA
data
•Enhance CBS process to
include 3
rd
party data
•Build CBS as a batch driven
process
DAAP Program Definition

26. 26
Current as of 10/19/2020
Project
/ PhaseProject
Provide
Consistent,
Integrated
Data
Make Data
Available
Across the
Enterprise
Provide
Consistent
Reporting
Governance
Aging
Technologies
1B/A Deliver prioritized set of 6reports targeted for internal RMF needs X
1B/B Build foundational Data Management components X X X X
1B/C
Build EDW with focus on subset of Data entities (claims, case financials,
OPE, Reference data)
X X X
1B/D Bring RMF and strategies data into EDW for those entities X X X
1B/E
Build basic business glossary and metrics catalog (foundation for Data
Governance)
X X
Project-Theme Connection (Phase 1B)

27. 27
Current as of 10/19/2020
Project
/ PhaseProject
Provide
Consistent,
Integrated
Data
Make Data
Available
Across the
Enterprise
Provide
Consistent
Reporting
Governance
Aging
Technologies
2/A Deliver next set of 8 reports for internal RMF needs X X X
2/B Evaluate and migrate CRIT reports to EDW X X X
2/C Build external portal to deliver CRIT reports X X X
2/D Extend and scale foundational Data Management components X X
2/E Build and Scale data governance X X
3/A
Migrate rest of existing BO reports and Sunset existing BO
reports/environment
X X X X
3/B Bring external 3
rd
party ANA data X X
3/C Enhance CBS process to include 3
rd
party data X X
3/D Build CBS as a batch driven process X X X X
Project-Theme Connection (Phase2-3)

28. 28
Current as of 10/19/2020
Enabling Paradigm Definition
Providing
Consistent, Integrated
Data
Making Data
Available
Across the Enterprise Providing Consistent Reporting
Governance
Aging
Technologies
Single source of truth across enterpriseEnsure consistency, currency, meaning, integrity and quality of data used within or across multiple business areas or processes X X
Historical reporting Accurate historical data & DB structures to support “AS-WAS” and “AS-IS” reporting. X X X
RMF and Strategies data stored together.The EDW data model supports multi-tenancy,thereby co-locating RMF and Strategies data X X
Create Metric Catalog/Data DictionaryCreate metric catalog/business glossary using conformed definitions and establishing precise derivations X X
CRIT remediation Design and develop an alternative for CRIT which would satisfy current and future needs of Client and Strategies clients. X X
Parameter Driven Portal
Create two separate parameter driven portals for reporting needs. One portal for RMF (internal) and second for Strategies
client.
X
Loss Abstract document/report in BO Ensure Loss Abstract document is available through SAP Business Objects X X
SAP Business Objects XI R 4.1 Upgrade SAP Business Objects to XI R 4.1 version X X
3
rd
Party Data Create 3
rd
Party Data Integration and Enrichment Capabilities X X
Create Data Quality Engine Metadata driven quality checks on critical data elements. X X
Data Standardization Apply data cleaning and standardization rules. Ensures data from multiple sources are stored in a common format. X X
Audit Balance & Control (ABC) metrics Perform reconciliation at entity level as data processes through different data management functions/processesX X X
Requirements Satisfaction

29. 29
Current as of 10/19/2020
Phase 1B
Project Key Objective Key Deliverables
Architecture
Modification
ReviseArchitecture to support new
components
▪Installation of any necessary hardware
and software components
EDW
Build EDW with focus on subset of Data
entities (claims, case financials, OPE,
Reference data)
▪Initial EDWcapable of supporting
Phase 1B requirements
Reports
Deliver prioritized set of 6 reports targeted for
internal RMF needs
▪Definedreports
DataManagement
Foundation
Build foundational Data Management
components
▪Foundationfor Data Management and
Governance
RMF Strategies Data
Bring RMF and strategies data into EDW for
those entities
▪Inclusion of data in the EDW allowing
for increased reporting and analytics
Business Glossary
Build basic business glossary and metrics
catalog (foundation for Data Governance)
▪BusinessGlossary and Taxonomy

30. 30
Current as of 10/19/2020
Phase 2
Project Key Objective Key Deliverables
RMF Report
Deliver the next set of 8 reportsfor RMF
Needs
▪Defined reports
CRIT Data
Evaluate and migrate CRIT Data and Reports to
the new architecture
▪CRIT data available within the EDW
for analytics and reporting
Portal
Build the external portal to make CRIT reports
available
▪External portal defined and built.
Capable of handling internal and
external report queries. CRIT reports
for external users included
MMS Data
Bring MMS datainto the EDW ▪MMS data now available for reporting
and analytics
Data Management
Extend and scale foundational Data
Management components
▪Data Managementparadigm capable
of supporting all new data within the
EDW
DataGovernance
Build and Scale Data Governance ▪Increased Data Governance
capabilities and functionality

31. 31
Current as of 10/19/2020
Phase 3
Project Key Objective Key Deliverables
Reports
Migrate remaining BO reports and sunset
existing BO reports and environment
▪All reports operating within new
environment. Enhanced reporting
and analyticcapabilities
3
rd
Party ANA
Integrate 3
rd
party ANA data into EDW ▪Increased reporting and analytic
capabilities based on increased data
availability
CBS Enhancements
CBS process enhancedto include 3
rd
part ANA
data
▪Increased reporting and analytic
capabilities based on increased data
availability
CBS Batch
Rebuild of CBS as a batch driven process▪Reduced processing time for CBS data

32. 32
Current as of 10/19/2020
Next Steps
•Ensure DAAP Roadmap and Strategy are aligned with Business Strategy
•Complete Socialization with Executive Stakeholders
•Jump start Phase 1B by:
•Detail design of reports to be delivered
•Begin definition of EDW data model
•Determine resources necessary to support definition of data dictionary and metrics
catalogue
•Define success metrics for Data Governance
•Determine and acquire resourcing

33. 33
Current as of 10/19/2020
Appendix

34. 34
Current as of 10/19/2020
Reporting Business UnitsImpact Results
Finance Underwriting Claims Strategies Patient Safety
Client Quarterly "CEO"
Report
X X X
Exhaustive manual effort required to assemble
Independent data collection form various sources leads to
discrepancies that are unable to be adequately resolved
Different understanding of definitions and derivations
SMT unable to make informed business decisions
Cost of lost productivity (1 month to prepare)
Client Institution
Report
X X X
Inability to incorporate additional departments' data
Inability to handle specialized or boutique institutions
Lack of automation leads to extensive manual manipulation of data
Loss of relevance to clients
Distrust of data presented to clients
Cost of lost productivity (2-3 months to prepare)
Inability to perform Cross-institution analysis
Claims Dashboard X
Manually created Excel spreadsheet that resides on a local machineExcel is not an enterprise database
Need to be institutionalized
Needs to source data from enterprise repositories
SMT cannot make informed decisions about KPIs and Metrics
Primary Care Report XX X
New report meant to ascertain Primary Care Issues
Location and Practice not supported by current data repositories
(Location held locally in Excel Spreadsheet)
SMT cannot make informed business decisions about PSO
opportunities, claims management, case financials, and Underwriting
exposure
Excel is not an enterprise database
Specialty –OB, ED,
Surgery
X
Manually created Excel spreadsheet that resides on a local machine
Distrust of data quality and veracity
Inability to properly ascertain issues pertaining to specialties
Loss of relevance to clients
Excel is not an enterprise database
Claim rates by
specialty, trend report
XX X
Historical exposure of trends and claims Inability to dynamically set premiums
Inability to fully understand trends pertaining to exposures and claims
Inability of SMT to make informed decisions
Phase 1B Reports

35. 35
Current as of 10/19/2020
Report Description Current State Future State Department(s) Contacts
Client
Quarterly
"CEO"
Report
Mark Reynolds sends out quarterly email
report to Board Members and Quality Leaders
--this report includes sections on Claims
Management, Current Financial Standing,
Corporate Achievements of Note. In
particular, the Claims Management section
includes trend data (with comparisons to past
benchmark data) for closed and asserted cases
--for several KPIs, including Closed-With-
Payment; %High-Severity, Payment->$1M.
Data pulled/submitted independently by
Patient Safety, Finance, Claims --collected and
organized by Communications. Some
disagreement between numbers from different
sources. Some philosophical disagreement
about how meaningful it is to report quarterly
numbers and how they should be
projected/interpreted.
Address issues in "Current State." Define
whole-brain consensus spec with
definitions and single source of data
(along with underlying data structures
and data governance).
Patient Safety,
Claims, Finance
Jonathan,
Beth, Sean
Claims (frequency, indemnity,
closed cases)
case financials
trends
coding taxonomy
policy-coverage not needed
billing financials not needed
Client
Institution
Report
Client Patient Safety leadership, along with
data analyst, and Patient Safety Director, meet
with Quality/Safety leadership for each insured
institution 2x/year (~ 20 meetings each time).
The purpose of the meeting is to inform the
institution about trends in their claims data,
highlight any emerging risks or things the
institution "needs to know." And, to align the
presentation with Experience Adjustments
(Spring) and present topics of interest to the
institution (e.g. HIT Risk or Primary Care Risk).
In Spring, data analyst produces "standard"
claims summary Excel book, which is reviewed
with the institution contact. Areas of
interest/focus are identified; further data
queries and analysis done iteratively until data
is presented. In addition, PT Safety Director
reads/reviews specific claim summaries and is
prepared to talk about them. Sometimes, a
Claims Rep presents, too. If there is a specific
topic of interest, data/slides are prepared for
that topic, as well. "Boutique" institutions may
get review of overall Client data or customized
presentations.
In 2016, there will be 2 meetings per
institution. The Spring meeting will
involve both Patient Safety and Finance
and include review of claims data, as
well as Experience Adjustment. Fall
meeting will be more topical. A goal is
to reduce amount of customized work.
Q: Involvement of Claims Department?
Q: How to handle boutique institutions?
An automation opportunity is initial data
pull/reporting book (for each
institution).
Patient Safety,
Finance, Claims
Winnie, Sean,
Carl.
coding taxonomy
contributing factors -
compare to Harvard and CBS
peers
org
claims
case financials
Claims
Dashboard
Provides Claims Department (Beth, Carl, Kay)
with information needed to track claims
activity --includes trends of cases/defendants
over time by different types of dates;
losses/defendant sliced by firm, etc.
Astrid has built SAS data set and uses Microsoft
Excel as front end.
Make Production-ready. Verify what
works well, what doesn't, and what new
KPA's/displays are wanted (by Claims).
Claims Beth
Phase 1B Reports Detail

36. 36
Current as of 10/19/2020
Report Description Current State Future State Department(s) Contacts
Primary
Care
Report
Primary Care is a Strategic focus for Client. The
content of a Primary Care "Report" will need to
be defined--interventions will focus in a
number of areas, but especially Patient
Engagement and Referral Management --
reports could focus on these areas, building on
Diagnostic Process of Care and Referral
Process.
Custom analyses. Inability to know where PCPs
are practicing--currently, Client data does not
include concept of "practice."
A high-level report. What is really
needed is clear understanding of what
business owner (Carol) wants to be able
to know about Primary Care. And, data
definition/acquisition/mapping for PCP,
practice so that we can report on this
data, i.e. a Primary Care Data Mart.
Deliverable here may be a data mart
with Excel/Tableau front end.
Underwriting is another involved
stakeholder here. And, we need to
understand implications for MMS.
Patient Safety,
Underwriting
Carol, Caren-
Elise
Gaps -site & location not available
for enterprise
Claims
Case financials
Org
Claims has location-site stored
either in CMAPS/Excel
Patient Safety -
OPE -also captures primary care
practice sites
UW -also captures location-site
information
Need to identify master record for
location-site and also build
hierarchy
Specialty –
OB, ED,
Surgery
Prepared for Chief's convening. Includes
trend/comparison data for claim rate (per 10K
births), academic versus community.
Benchmarked against CBS
Denominator (and numerator) data required
preparation/cleaning --knowing where birth
occurredversus sponsoring org was key.
Automate this. Note: denominators are
different for different specialties (ED,
Surgery). OB uses births from AHA.
Patient SafetyOB -Lisa,
Tom Beatty
ED –Jay
Scherer
Surgery–Bill,
Kathy Dwyer
Claim rates
by
specialty,
trend
report
In 2015, Elena/Astrid used our Claim Risk
Model to plot observed claim rate trends by
specialty, broken down by
Academic/Community status. Using the
model, they were able to predict what the
claims rate should be (and compare it with the
observed rate). What was most useful about
this exercise was the ability to look at each
specialty's trend lines and see any interesting
or concerning patterns.
Automate this. Patient SafetyJonathan,
Astrid, Elena
Phase 1B Reports Detail

37. 37
Current as of 10/19/2020
Data Layer
Future-state EDW –BI Delivery Framework
Analysts
Power Users/Trading
partner data extracts
Scorecards, Dashboard,
holistic view of business
1 more additional level of
detail plus pre built reports
Detailed data, investigative
analysis, helps setup
reporting capability for user
community
User Community Interest
Detailed base layer
(Atomic 100% data
elements)
Data Refresh Frequency
Monthly
Daily Weekly
Daily
Dashboards
Information
ConsumptionLayer
BO WebI
BO
Universe /
Extracts
Framework
EDW –Single Source of Truth for all Information Consumption needs
Executives
✓AtomicdetaileddataservesPowerUserswhoareinterestedindetaileddatainvestigationservicedthroughBO
Universe/Extractframework
✓MostUseddatalayerservesAnalystswhoareinterestedinprebuiltreportsservicedthroughBOWebI.
✓AggregatedatalayerservesExecutiveswhoareinterestedinscorecards,dashboardsandhigheraggregate
businessmetricsservicedthroughdashboards.
Most Used data layer
(60% data elements)
Aggregate data layer
(20% data elements)
Sandbox