using complex data to solve complex problems · related to complex policy and program delivery...

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. . . . . . . . . . . . . . . . . . . Using Complex Data to Solve Complex Problems Scott Sinclair A/Deputy Minister Manitoba Infrastructure

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Page 1: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

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Using Complex Data to Solve

Complex Problems

Scott Sinclair

A/Deputy Minister

Manitoba Infrastructure

Page 2: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

• Manitoba is one of the most data rich and data

experienced provinces in Canada.

– Manitoba Population Research Data Repository

• Government has over 2000 business application

systems generating useable and analyzable data.

• Expertise in using complex data across systems and

sectors to measure outcomes such as factors impacting

children across their lifespan.

– MCHP and Healthy Child Manitoba Office (HCMO) have been

using such data to design programs and deliver public services

for nearly 25 years.

Overview

Page 3: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned
Page 4: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Initiatives in Progress

Data Driven Program Evaluations

Series of on-going quick turnaround data analytics

projects that look at pressing citizen needs and

opportunities to improve public services.

Page 5: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Data Analytics Projects

• Utilization patterns of high-needs clients in multiple

systems.

• Effectiveness of portable housing benefits to achieve

outcomes of reduced reliance.

• Impacts of various child welfare programs on the

outcomes of youth.

• Factors that contribute to the early apprehension of

children.

• The impact of wait lists on the outcomes of children

seeking services from Community Disability Services.

Examples:

Page 6: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Data Analytics Projects

Our Approach

Cross-departmental approach to look at multiple sets of data

related to complex policy and program delivery problems

within short project cycles (Quick Turnaround projects).

• Lessons learned to date:

– Need more resources to develop data capacity

– Focus on data analytics and data science is insufficient

– Conducting data-driven program evaluations and

launching a data science program within Manitoba is

more complexed than anticipated

– Need to mange expectations!

Page 7: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Vision for the Future

• Enhance data by expanding (IT) infrastructure, engaging

data professionals, and identifying program evaluation

needs and opportunities.

• Improve access to data across government (IT and

Legislative).

• Enable access to data while ensuring privacy and security.

• Develop stronger government/non-government

partnerships to increase the province’s data capabilities.

– This includes developing new roles and responsibilities for existing

partners such as MCHP, CHI, and MTP.

• Nurture a data-driven, evidence-based, data science

literate culture within government.

Page 8: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

8

Complex Data Strategy

C h a r l e s B u r c h i l l

R a d y F a c u l t y o f H e a l t h S c i e n c e s

Page 9: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

9

Data Strategy – Development

• Stakeholder survey and full-day workshops

• Strengths, challenges, opportunities, risks

• Current environment• Data Analytics

• Data Management

• Database Infrastructure

Page 10: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

10

Framework, Goals and Objectives

• Framework• To translate complex data into useable knowledge –

Patients, Faculty, Government and Regions, Industry

• Goals and Objectives• Strengthen alignment and engagement

• Enhance data quality and access

• Enhance ability to describe, visualize and model

• Next Steps

Page 11: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

11

Thank You / Questions

umanitoba.ca/centres/mchp

facebook.com/mchp.umanitoba

@um_mchp

Page 12: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

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Provincial Information

Management & Analytics (PIMA)

Transformation in the Manitoba

healthcare system

Panel Presentation to Evidence to

Action Workshop – September 25,

2018

Deborah Malazdrewicz

Page 13: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Manitoba’s Healthcare System

Transformation• Opportunities

– Creation of a provincial health organization

(Shared Health)

– Formation of a Transformation Management

Office

– Re-design of department

• refocus on Policy, Planning, Funding and Oversight

roles

• Modernization of Funding Methods

• Provincial Analytics

Page 14: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Manitoba’s Healthcare System

Transformation

• Need provincially standardized high quality, timely

data

• Business Challenge

o Lack of integration

oComplex governance

o Inability to make evidence informed decisions

o Inefficiencies and duplication

Page 15: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

Key Partners Key Activities ValuePropositions

BeneficiaryRelationships

Beneficiaries

Key Resources v Service Delivery

Cost Structure Performance Outcomes

Adapted from the Business Model Canvas (www.strategyzer.com)

Provincial IM&A – Target State

1. MHSAL

2. SHSM

Planning &

System Mgmt

3. Health

Service

Delivery

Organization

4. Research

Organizations

5.Government

of Manitoba &

Communities

5. Governance &

Compliance

2. Reporting

1. Data Mgmt &

Quality

4. Modelling &

Analytics

3. IM&A Support

6. Whole of

Government

7. Open Data

8. Innovation &

Improvement

6. Whole of Gov’t focus

7.Clinical Service Planning

8. First Nations

9. Research Agreements

7. Gov’t Channel (?)

2. Availability1. Quality3. Accessibility 4. Satisfaction

5. Compliance 6. Adoption 7. Predictive Accuracy

1. Set policies & standards

2. Manage Data & Quality

3. Develop models/reports

4. Consult & Train

5. Measure and Monitor

6. Audit (Quality & Compl)

7. Awareness & Comm

8. Enforce Compliance

9. Strategic Vendor Mgmt

10. Strategic Planning

Support

11. Operational Support

12. Business Mgmt of Tools

1. SHSM

(Digital

Health)

3. MCHP

2. SHSM

(Clinical

Governance)

2. BI Tools1. IM&A Staff

3. EDW

4. C-Orgs

(e.g. CIHI,

Infoway)

1. Data Warehouse

2. Policies & Standards

3. MDM & BI Tools

4. IM&A Portal

5. IM&A Service Staff

6. Source Systems

7. IM&A Practices

8. Executive Champion

9. IM&A Service Desk

10. Brand

5. Fed Gov’t

(Ministries)

6. HSDOs

7. Gov’t of

MB

4. Beneficiary Training

5. Dev & Integration Svcs

6. Analytics Investments

1. Data Governance

Council

2. Community of Practice

3. Data Quality

Committees

4. Info Sharing

Agreements

5. Self-Service

1. Request Service Desk

2. Business Intel Tools

3. Reports/Data Set

Access

4. System Interfaces

5. Senior

Analyst/Consultant

6. Classroom & Online

Training

Hilltop Business Solutions Confidential – Not for Distribution

Page 16: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

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S e p t e m b e r 2 5 t h 2 0 1 8

A l a n K a t z

M a n i t o b a C e n t r e f o r H e a l t h P o l i c y

2EA MCHP’s Evidence to Action

Annual Workshop

Page 17: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

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Page 18: Using Complex Data to Solve Complex Problems · related to complex policy and program delivery problems within short project cycles (Quick Turnaround projects). • Lessons learned

18

Thank You / Questions

umanitoba.ca/centres/mchp

facebook.com/mchp.umanitoba

@um_mchp