Download - Technology to decision analysis

Transcript
Page 1: Technology to decision analysis

BI Functions

• Tie-verify report (QA)

• Ad hoc reports

• Cross-repository

queries

• Standard reports

• Dashboards/Scorecards

• Vendor COTS apps

• Machine learning

metrics

• Defs, pilots & modeling

• ETL Mapping

• Arch. & config.

• Source outliers, dups &

diferences

• DBA tuning & security

• BI portal & metadata

• User training

• Machine learning

Standardized, leveraged, & scalable BI processing

Operations & management

Finance & Productivity

• Pre-service, service

delivery, and post-service

billing & customer service

• Cost budgeting & finance

Payer utilization

• Shared savings attribution

• Bundled pymt contracts

• CAHPS experience

Care affordability

• Variation reduction

• Readmissions

• Generic Rx, IP to OP

• Total cost of care

• End of life UM

Population Health

• Risk prediction, groupers

• HEDIS & core measures

Transformation by matching metric to decision (model)

Formal

productivity

& logistics

method

• SDLC

• PMP

• UML

SysML

• Ad hoc

LOE

intake

Technology to analysis (operating model)

Business choice modeling

Translated into processing

algorithm, math equation, and/or

analysis criteria into a SMART

measurement model that

explains, clarifies & verifies.

• Event frequencies (OLAP root

cause drilldown)

• Pre/post change & differences

• Benchmarking specs (HFMA

MAP Keys, CAHPS, NCQA)

• Workflow cycle time

• Capacity constraint

• Allocation & optimization

• Patient queuing & scheduling

• Prognostics/prediction (rev. at

risk, likely denial cases)

• Conditional probability

• Markov chain

Integration w/ operational activities that capture value

Workflow

handoff?

Formal

productivity &

logistics method

• Lean Six Sig

• Variation

Reduction

• Actuarial

utilization risk

• CMMI-SVC

• Effects

prediction

• Alemi rapid

decision

analysis

• CRSP-DM

Service

exchange?

Levera

ge r

e-u

seable

work

pro

duct to

multip

ly v

alu

e

Re-useable work products, services & social technology to multiply value

(feedback loop emphasizing

failing small & local)

Levera

ge r

e-u

seable

work

pro

duct to

multip

ly v

alu

e

What type of service handoff/exchange will energize, multiply, and amplify model capabilities

(chevron blue shapes) and the people who work in the environment?

Page 2: Technology to decision analysis

Social technology (ways of organizing people to do things that amplifies their talents, such as use of

productivity improvement processes/engineering, definition of roles, measureable goals, multi-

disciplinary reflection, values, etc.)

Goal: Create resources that are re-useable (unsupervised use) to multiply analyst value, a

feedback/contribution by individual analysts of reusable knowledge to the org. to the point where a

decision modeler becomes replaceable. Reusable work products includes OLAP cubes, standard

reports, canned/template SQL for direct access, pseudo code business logic, annotated SQL code,

process maps/models, tables, rev. cycle rules, logical models, BI service specs, outlier exception

handling rule specs.

Future state: Frontline analyst’s choices and dept. management decisions are easy with just in time self-

service information. Outcomes/results are impacted by data modeled events/relationships of a given

problem. The core business choices that are modifiable are illuminated by simplified measurement

models (c.f., universe of all dimensions). Decisions are decomposed into component parts, and a

measurement model connects the computations.

What human factors will amplify a tech-to-

analysis operational model?

Individual contributor to cross-disciplinary partnerships

Lead by example•Active listening &

gratitude•Best analysis recognition•Closing business decision

knowledge gaps

Coaching•I do, we do, you do

•Failures/breakdowns to new inspiring commitments

•Milestone measurement•Positive feedback

Support model•Cross training internally &

across depts•Change mgmt. training

•SME mentoring•Job & goals alignment

Empowering futures•Career skill development

action plans•Supporting personal

commitments•Innovation competition

Page 3: Technology to decision analysis

• Analyst. Transforms error-filled raw data from siloed sources into information that is easily accessible

at the time business decisions and operational activity choices are made. Analysts scope/define

problems, as well as has the ability to compute and derive meaning/insights by comparing trends to

baselines, industry benchmarks, and tacit frontline prior knowledge. Can generate trends, workflow

timeliness metrics, detect errors, finds cost differences, determines root-causes, optimizes revenue

workflow, and finds modifiable gaps.

• Decision Modeler. Is a data/decision scientist that can scale computation of decisions with BI platform

tools so small tactical choices are easy and optimal. Constantly recombines multiple administrative and

clinical data elements to solve problems at the patient account/case or provider level, detect changing

events across functions, distinguish unwarranted variation, and can consult BI and business staff on

performance tuning.

Specific role transformation