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Technology to decision analysis

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John Frias Morales, DrBA, MS
John Frias Morales, DrBA, MS

This document outlines the functions of business intelligence (BI), including standard and ad hoc reporting, dashboards, machine learning metrics, Extract-Transform-Load (ETL) mapping, and user training. It discusses how BI can support operations and management, finance, payer utilization, care affordability, population health, and transformation through matching metrics to decisions. The document proposes leveraging reusable work products, services, and social technology to multiply analyst value through a feedback loop. It also discusses human factors that can amplify the technical model, including individual contribution, coaching, empowerment, and specific role transformations.

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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? Leveragere-useableworkproducttomultiplyvalue Re-useable work products, services & social technology to multiply value (feedback loop emphasizing failing small & local) Leveragere-useableworkproducttomultiplyvalue What type of service handoff/exchange will energize, multiply, and amplify model capabilities (chevron blue shapes) and the people who work in the environment?
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
• 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

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Technology to decision analysis

  • 1. 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? Leveragere-useableworkproducttomultiplyvalue Re-useable work products, services & social technology to multiply value (feedback loop emphasizing failing small & local) Leveragere-useableworkproducttomultiplyvalue What type of service handoff/exchange will energize, multiply, and amplify model capabilities (chevron blue shapes) and the people who work in the environment?
  • 2. 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
  • 3. • 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