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Department of Veterans Affairs

Building Analytics CapacityTraining Plan

Version 2.4

May 2012

Revision History

Date Revision Description Author

2/27/2011 1.0 Initiation of Building Analytics Capacities Training Plan

Diane Montella, Denise Harrison

2/28/2011 1.1 Updated Section 3.2 and section 5 Elizabeth S. Chapman

3/3/2011 1.2, 1.3 Added comments for consideration Workstream C (WSC) Advisory Group

3/3/2011 1.4 Revisions based upon comments in v1.3

Diane Montella

3/8/2011 1.5 Revisions Peter Woodbridge, Denise Harrison

3/10/2011 1.6 Review and Revision Diane Bedecarré, Diane Montella

3/10/2011 1.7 Formatting Revisions Diane Montella

3/10/11 1.8 Revision Diane Bedecarré, Diane Montella

3/20/11 1.9 Revision Diane Montella

3/21/11 2.0 Revision Peter Woodbridge, Diane Montella

3/21/2011 2.1 Review and Revision WSC Leads Group

3/24/2011

3/25/2011

2.1.1, 2.1.2 and 2.1.3

Review and Revision Maureen Khung, Michelle Lucatorto, Peter Woodbridge, and WSC Leads Group

3/25/2011 2.2 Review and Revision WSC Leads Group

3/30/2011 2.3 Revision Hi2 Collaborative Program Team Members

WSC Leads Group

5/22/2012 2.4 Review and Update Diane Bedecarré

Katherine Gianola

Elizabeth S. Chapman

Building Analytics Capacity May 2012Training Plan

Table of Contents(Highlight the table of contents below, then press F9 key to automatically update)

1. Plan Summary.....................................................................................................................11.1. Purpose............................................................................................................11.2. Background......................................................................................................11.3. Stakeholders and Key Personnel.....................................................................31.4. Target Audience...............................................................................................3

2. Plan Scope, Goals, & Objectives.......................................................................................42.1. Scope...............................................................................................................42.2. Goals................................................................................................................42.3. Objectives........................................................................................................52.4. Critical Success Factors...................................................................................52.5. Training Tracking.............................................................................................5

3. Training and Development Life Cycle...............................................................................53.1. Needs Analysis................................................................................................53.2. Modalities.........................................................................................................63.3. Evaluation and Update.....................................................................................6

4. Training Deliverables.........................................................................................................75. Resources...........................................................................................................................8

5.1. Training Resources..........................................................................................85.2. Instructors/Facilitators......................................................................................85.3. Media...............................................................................................................8

6. Metrics.................................................................................................................................87. Risks and Constraints........................................................................................................9

7.1. Risks................................................................................................................97.2. Constraints.....................................................................................................10

7.2.1. Availability of Faculty.............................................................................107.2.2. Funding for development and delivery of Essential micro-analytics knowledge education and EMAK (Essential Micro-analytics Knowledge) education specialists training...............................................................................107.2.3. Coverage for Student Time Commitment...............................................107.2.4. Funding for Travel and Tuition...............................................................107.2.5. Communication Gaps............................................................................10

APPENDIX A: CONCEPTUAL MODEL FOR A DATA DRIVEN ORGANIZATION..................11APPENDIX B: Sample Curriculum Descriptions....................................................................12APPENDIX C: Basic and Intermediate Level Analytics Education......................................13APPENDIX D: Advanced and Expert Level Analytics Education, Sample Curricula.........14APPENDIX E: PRE-ASSESSMENT STUDENT SURVEY........................................................16APPENDIX F: ACKNOWLEDGEMENTS..................................................................................17

Building Analytics Capacity May 2012Training Plan

1. Plan Summary1.1. Purpose

Advance the Veterans Health Administration (VHA) national goal of creating a “data driven” organization (see Appendix A) by developing field-based, multi-level analytics education in support of the Building Analytics Capacities effort of the VA Health Informatics Initiative Workforce Development project. The specific goals of this initiative are to:

Develop an education program for field-based, analytics experts Develop an education program for field-based, Essential Micro-analytics Knowledge

(EMAK) Education Specialists Develop educational materials for EMAK education specialists to use when training

frontline staff to use data to improve and monitor their work

1.2. BackgroundThe Department of Veterans Affairs (VA) historically has been a leader in the adoption of digital technology and use of data. The Veterans Health Administration (VHA) was the first major health care organization to adopt an electronic health record which it has continually improved and enhanced. VHA has implemented a variety of innovative technologies to collect and use clinical data at the bedside, e.g., the barcode medication administration system.VA’s energy and resources related to data are largely expended on acquisition and storage, with little emphasis on efficient reporting or meaningful analysis. While many of VA’s 240,000 employees generate and use large amounts of data on a daily basis, most do not know how to analyze data or how to use data in a meaningful way.[Final Report of the VHA Managing Data Work Group, September 2010] To improve its capacity to leverage data and analysis to provide efficient high quality health care to Veterans, VA must improve at every level the capacity of its workforce to analyze the vast amounts of data that it collects. VA must develop a workforce that is comfortable interpreting and applying data routinely as a part of daily activities. In other words, the VA must become a “data driven” organization.We recognize that health care systems need education in and application of different kinds of analytics. A workforce that is competently engaged in continuous improvement and well-versed in analytic techniques will be better equipped to use data to prioritize tests of change, to quantify effects, and to communicate findings. Currently, VA has a pressing organizational need to fill knowledge gaps with respect to VA capacity with field based analytics (also referred to as micro-analytics). The VA Nebraska Western Iowa Health Care System (NWIHCS) has developed a conceptual model with which to categorize micro-analytic competency consisting of four levels:

1. Basic (“Data Providers”) – able to browse, sort, and review simple data sets within their work units, proficient in basic Microsoft Excel™ (Excel) arithmetic and charting functions

2. Intermediate (“Information Explorers”) – able to analyze national data sets using advanced Excel functions such as pivot tables; capable of communicating a “story” through the use of intermediate Excel charting functions

3. Advanced (“Insight Analysts”) – able to interrogate a range of data sources; analyzes data so as to match data found with information needs; generates insights based on information generated; communicates insights efficiently and effectively

4. Expert (“Knowledge Synthesizers”) – able to perform complex data extracts and analyses; translates information into knowledge that is adopted by others; leads teams in identifying relevant data; coaches and mentors others.

Building Analytics Capacity May 2012Training Plan Page 1

Figure 1. Levels of Analytical Competence

These levels represent individuals at all levels of the organization that are distributed throughout the organization. They collectively contribute to the flow of knowledge throughout the organization (Figure 1).

Using this conceptual model, VA Nebraska Western Iowa Health Care System (NWIHCS) has developed a successful two-tiered curriculum to train individuals within the delivery system to achieve the levels of analytical proficiency described above and depicted in Figure 1.

The first tier training curriculum, referred to as Basic Analytics Learning Modules offer essential micro-analytics training directed at creating data providers and information explorers. These modules are comprised of a series of “just-in-time” teaching modules directed at conveying essential analytics knowledge to all employees. The modules cover a range of topics from basic Excel through “chartology”, to use of pivot tables. This curriculum differs from other basic analytics training offered in the VA in its hands-on, bidirectional educational approach. Bidirectional education and support leverages the “teachable moment” (“just in time teaching”) when students attempt to apply knowledge through educator mediated hands-on mentoring to guide the individual through solving their work-related analytical problems.

First tier training is provided by essential micro-analytics knowledge (EMAK) education specialists who are both proficient in applying adult education tools and principles, and knowledgeable in micro-analytics. By being both educators and analytics practitioners, they are able to provide bidirectional education (classroom based, instructor led education) and support.

The second tier training curriculum, the VA NWIHCS Healthcare Analytics Certificate Course, directed at developing staff with more advanced levels of analytics capability as insight analysts and knowledge synthesizers, is a four-course, graduate-level certificate program in operational analytics (also referred to as micro-analytics). The four courses in this curriculum are:

o Healthcare Data Analysis – an introduction to statistical methods useful in continuous improvement

o Healthcare Systems Improvement – an introduction to systems redesign methods and tools with an emphasis on the analytical tools used in defining the current state, measuring improvement, and documenting sustainability

o Healthcare Data Mining – an overview of VHA databases useful in continuous improvement efforts

o Healthcare Project Management – a major systems redesign capstone project that incorporates knowledge acquired during the three other courses.

The current training plan addresses resources and planning required to scale up analytics training delivery throughout the VA.


1.3. Stakeholders and Key PersonnelThe stakeholders and key personnel overseeing this training plan are:

Table 1 - Stakeholders & Key Personnel

Stakeholder/Key Personnel

Organization Contact

Business Owner Workstream C of the VA Health Informatics Initiative (hi2) Team

Diane Montella (Past)

Elizabeth S. Chapman (Present)

Project Management Staff VA Nebraska Western Iowa Healthcare System (NWI HCS) and MidWest Mountain Veterans Engineering Resource Center (MWM VERC) Healthcare Analytics Training Development Team

Denise Harrison

Peter Woodbridge

Education Project Manager Employee Education System

Jerry Rutherford (Past)

Rick Shew (Present)

1.4. Target AudienceFive target audiences have been identified:

Basic Analytics Learning Modules Target Audience Includes:1) Data Providers – Includes, but is not limited to, front line supervisors, clinical staff (such

as nurses, physicians, pharmacists, psychologists, social workers, and administrative staff (such as techs, clerks, and program assistants) whose role requires them to perform limited data analysis and reporting.

2) Information Explorers – Includes, but is not limited to, supervisors and managers, clinical staff, and administrative staff who need to achieve a functional proficiency level sufficient to apply data analysis and reporting skills effectively to improve and monitor systems Examples of such staff includes, but is not limited to, Clinical Application Coordinators, VANOD (VA Nursing Outcomes Database) Site Coordinators, Automated Data Processing Application Coordinators (ADPAC), Bar Code Medication Administration (BCMA) Coordinators, Health Information Management (HIM) Staff, Program Analysts, and Program Support staff.

Graduate Level Analyst Certificate Program Target Audience Includes:3) Insight Analysts – Includes, but is not limited, to Clinical Application Coordinators,

Program Analysts, Program Support Staff, Decision Support Services staff, Administrative Officers, Management Analysts, VANOD Site Coordinators, ADPACs, BCMA Coordinators, HIM staff, Quality Management Specialists, Systems Redesign staff, and Health System Specialists who need to achieve in-depth proficiency levels sufficient to assist, consult with, or lead others in data analysis and reporting.


4) Knowledge Synthesizers – Includes, but is not limited to, Veterans Integrated Service Network (VISN) Support Service Center staff, Decision Support Services staff, Administrative Officers, Management Analysts, Quality Management Specialists, Systems Redesign staff, and Health System Specialists who need to achieve a broad-based and in-depth level of proficiency sufficient to be recognized as an authority or master performer in the application of data analysis and reporting.

5) Essential Micro-analytics Knowledge (EMAK) Education Specialists – Includes but is not limited to, trained Insight Analysts and Knowledge Synthesizers who demonstrate micro-analytics and information technology proficiency.o A long-term expectation is that Knowledge Synthesizers and Insight Analysts will

complete additional training in adult learning theory, coaching, and mentoring to also become EMAK education specialists who are responsible for developing data providers and information explorers at their facility.

2. Plan Scope, Goals, & Objectives 2.1. Scope

The scope of this plan encompasses the design, development and delivery of Analytics training to educate staff at all VA care delivery sites in basic and advanced micro-analytics methods.

2.2. GoalsThe plan supports the following goals:

Leverage the VA Nebraska Western Iowa Health Care System (NWIHCS) Basic Analytics Learning Modules and Healthcare Analytics Certificate Course to provide analytics curriculum and training to VA staff nationally.

Develop and maintain a national VA staff that are proficient in the ability to apply basic micro-analytics methods to their routine daily activities Increase the number of VA staff at all VA care delivery sites that have essential micro-analytics knowledge so that they may apply basic micro-analytics methods to their routine daily activities.

Develop and maintain VA staff at every facility that have advanced analytics capabilities. A long-term goal is to have at least one to ten Knowledge Synthesizers at each VA medical center (depending on size of the center), and one to two Knowledge Synthesizers at each VISN office. Increase the number of VA staff at all VA care delivery sites that are proficient in advanced analytics techniques (Knowledge Synthesizer).

Develop and maintain a cadre of VA personnel who are trained to provide on-site education in essential micro-analytics knowledge to other staff. Increase the number of staff at all VA care delivery sites as EMAK educational specialists. The long-term goal is for each medical center to have at least one trained EMAK educational specialist.

o These individuals not only must be trained in adult education theory and basic analytics methods but also must have a strong operational knowledge of the use of basic tools so as to provide mentoring support.

o The EMAK education specialists would be responsible for developing data providers and information explorers.


2.3. ObjectivesThe plan supports the following objectives:

1. Develop Data Providers and Information Explorers: Increase the number of personnel at every VA care facility who are educated in and able to apply essential (basic) micro-analytics techniques.

2. Develop Insight Analysts and Knowledge Synthesizers: Increase the number of VA personnel who are certified or formally educated in Advanced Analytics techniques, including VHA data set mining.

3. Increase the number of staff at all VA care delivery sites that are trained as EMAK educational specialists.

a. These individuals not only must be trained in adult education theory and basic analytics methods, but also must have a strong operational knowledge of the use of basic tools so as to provide mentoring support.

b. The essential analytics knowledge education specialists would be responsible for developing data providers and information explorers.

2.4. Critical Success FactorsThe factors (dependencies) that ensure the successful implementation of the training plan are:

Adequate funding for the design, development, delivery, and coordination of training Adequate staff to develop, implement and support delivery of training plan Access to an online education environment (e.g., Blackboard™) Adequate support from local facilities to fund tuition and educational materials for each

Knowledge Synthesizer trainee Adequate time and resources for training of identified target audiences Proper identification and application of identified training modalities Effective scheduling of training in order to avoid conflict with work schedules Tracking training results regularly to assess the effectiveness of the training

2.5. Training TrackingTraining will be tracked through functionality offered by online delivery modalities such as Blackboard™ and the VA Learning Management System (LMS), and through accounting of students who formally enroll in the Healthcare Analytics Certificate Course.

3. Training and Development Life Cycle3.1. Needs Analysis

VA Nebraska-Western Iowa Health Care system (NWIHCS) leadership identified a need to move their local organization forward as a data-driven culture for decision-making and accountability. In considering transformational strategy for the local facility, NWIHCS consulted national VHA subject matter experts who concurred that this same need exists throughout VHA. In response, NWIHCS developed its essential analytics education and the Healthcare Analytics Certificate programs with capability for national scale-up.


The NWIHCS Healthcare Analytics Certificate program collects baseline data in the form of surveys regarding student proficiency with organizing, managing, and interpreting data. The survey is administered when the student first enrolls in the first course of the program’s 4-course series. This provides a descriptor of baseline proficiency of students naive to the course, and over time may provide a wider snapshot of baseline analytics proficiency of a qualitative sampling of VA staff nationally.

Future needs analysis may include a survey to the field to identify analytics training inconsistencies, education gaps, knowledge deficits, preferred training methods, and to prioritize training opportunities for the VA community. Both formal and informal approaches to needs assessment can be used to determine future training needs of target audiences. Expertise of the VA Product Effectiveness Team can be leveraged regarding administration of a future survey.

3.2. Modalities Essential micro-analytics knowledge education is conducted through a bidirectional

education model. That is, a trained education specialist conducts small group, hands-on (e.g., in the facility computer training room), teaching. This is followed by one-to-one mentoring when students attempt to apply acquired knowledge to solving data analysis problems in their work areas.

Knowledge synthesizer training is conducted through an online education environment (Blackboard™). Each course has assigned readings and homework. While lectures are available asynchronously, the course is moderated by a university professor. Students receive course content by listening to and viewing class presentations, and reading assigned text. Students also participate in practical learning exercises.

EMAK (Essential Micro-analytics Knowledge) education specialists training will be conducted through an online education environment (Blackboard™) supplemented by LiveMeeting™ and VA National Teleconference System (VANTS) conference calls. Students receive course content via these modalities, and also perform independent homework exercises.

3.3. Evaluation and UpdateEvaluation is an important part of any training plan to determine whether or not programmatic and individual learning goals have been met. Various approaches to evaluation will be employed to assess the effectiveness of VA’s analytics training and education activities and to identify opportunities for improvement. Competency is the pairing of knowledge with skill acquisition. Evaluation methods will include, where appropriate, measurement of learners’ ability to effectively apply new analytics capabilities.Evaluation assesses the strengths and weaknesses of programs, policies, personnel and products. Evaluation will give consideration to a program’s or individual learning activity’s purpose, intended audience, and kinds and sources of information needed for decision-making. Reporting results in a meaningful and useful way enhances the ability to evolve and improve the effectiveness of educational offerings over time.Tiers on which evaluation may take place include:

Individual learning experience (e.g., learner satisfaction) Faculty effectiveness and course offering (were the course objectives met) Effectiveness of training plan (were training plan objectives met).


Evaluation activities for analytics education may include: Course evaluations soliciting student feedback will be performed at the mid-point and

at the end of each course. Evaluation of student knowledge acquisition and proficiency. Knowledge acquisition

and proficiency will be evaluated during education by evaluating (“grading”) homework assignments, by the administration and grading of tests, and by course faculty during bidirectional education sessions.

Evaluation of organizational impact can be conducted through periodic audits to measure progress of medical centers toward becoming data-driven organizations. Subject to available human and budgetary resources (see section 7.1 “Risks and Mitigations”), evaluation methods are being explored to measure the overall impact of course offerings. Potential metrics include leadership and management attitudinal and data usage surveys, number of staff trained, cataloging reports routinely used, An example of this would be to evaluate change in staff performance and skill set after completing the Healthcare Analytics Certificate Course. Such evaluation would require measurement of baseline skills prior to course registration, and a second measure of skill set following successful course completion. Although more difficult to evaluate, other potential metrics of organizational impact include: 1) business impact – e.g., Did some measure of performance in the workplace rise or lower as a result of the learners receiving training?; 2) return on investment – e.g., What was the cost savings, increase in efficiency or reduction in overhead as a result of the training?

4. Training DeliverablesTable 2 - Training Deliverables

Project Deliverables Responsible Party

Near-term Deliverables

Analytics Training Plan Health Informatics Initiative Workstream C

Healthcare Analytics Certificate Courses1 VA NWIHCS in conjunction with University of Nebraska Lincoln and Health Informatics Initiative Workstream C

Long-term Deliverables

Basic Analytics Learning Modules2 VA NWIHCS in conjunction with MWM VERC and VHA Office of Informatics and Analytics

Essential Micro-analytics Knowledge Education Specialist Courses3

VA NWIHCS in conjunction with MWM VERC and VHA Office of Informatics and Analytics

1See Appendices B, D, and E2See Appendix C3See Appendix B


5. Resources5.1. Training Resources

a. Basic Analytics Learning Modulesb. HealthCare Analytics Certificate Coursesc. Essential Micro-Analytics Knowledge Education Specialists coursesd. Blackboard™ online learning environmente. Learning Management System (LMS) Skillsoft™ training modulesf. VA eHealth University (VeHU) training modulesg. VHA Support Service Center (VSSC) training classesh. Inpatient Evaluation Center (IPEC): Analytics Academy, analytic training, and reportsi. Books 24x7j. Region 2 SharePoint training modulesk. VA Nebraska Western Iowa Healthcare System (NWI HCS) N-Tracks SharePoint

5.2. Instructors/FacilitatorsCourse faculty will include subject matter experts from within VA staff, as well as other agencies and affiliated universities.

5.3. MediaCourse content will be delivered as: 1) onsite, hands-on classroom teaching; 2) one-to-one mentoring; 3) distance learning using Blackboard™, Microsoft LiveMeeting™ and other web based media as well as live and recorded videoconferences and telephone audio conferencing (VANTS). Students will be encouraged to use their own data sets so that they may learn by solving analytics problem that are meaningful to them and worthwhile for their service.

6. MetricsFor the purpose of this training plan, metrics will be reported based on delivery of the VHA Healthcare Analytics Certificate Course, and on development and delivery of the Essential Micro-analytics Knowledge (EMAK) Education Specialist Education.

For Healthcare Analytics Certificate Training (Knowledge Synthesizer training): Total number of training hours available Total number of participants Number of participating sites Total number of hours of training completed Total continuing professional education (e.g., CEU, CME) hours awarded, where

applicable Total number of participants who successfully completed each individual course,

reported for each of the four courses in the Healthcare Analytics Certificate training track.

Total Healthcare Analytics Course Certificates issued to those learners who complete successfully all four courses required for the certificate training.

Customer evaluation of course content delivered

For EMAK Education Specialist Education:Building Analytics Capacity May 2012Training Plan Page 8

Total number of online training hours available Total number of participants Number of participating sites Total number of hours of online training completed Total continuing professional education (e.g., CEU, CME) hours awarded, where

applicable

For Overall Program Effectiveness Number of Knowledge Synthesizer and EMAK Education Specialists Trained

7. Risks and Constraints7.1. Risks

The Health Informatics Initiative Workstream C team and VA Employee Education System (EES) staff have identified the following risks associated with the implementation of this training plan. For each risk, mitigation strategies are identified. (Mitigation – activities undertaken to prevent or reduce the negative impact of an unfavorable risk event.)

RISK MITIGATIONLack of a standardized definition of Analytics capability in the VA

1) Leverage the work done by VA NWI HCS as well as the MMVERC to clearly identify types and levels of analytics knowledge needed in various capacities throughout the VA.

Difficulty identifying all personnel who perform analytics functions within VA

1) Utilize the VA Product Effectiveness team to assist in gathering accurate information about the VA workforce.

2) As laid out in this document, leverage work done by VA NWIHCS as well as the MWM VERC to define analytics functions.

Employee barriers to participating in educational activities (such as: time, budgetary, supervisory approval, lack of knowledge of availability of training, lack of perceived value of analytics training on part of employee or supervisors)

1) Leverage work done by the hi2 Public Relations group to raise the perceived value of analytics via the hi2 web portal and other communication modalities.

2) Promote Analytics certifications within professional disciplines.

3) Organize, advertise, and promote the availability of Analytics education opportunities.

4) Leverage the momentum from the Health Informatics Initiative to get leadership support that endorses Analytics education and training for all target audiences.

Lack of sufficient resources to provide essential knowledge micro-analytics education at VA facilities during the scale-up time required to train Knowledge Synthesizers (who will then become educators in basic analytics education)

1) Leverage opportunities to provide Analytics support and mentoring through existing staff capable in basic and advanced Analytics functions.


RISK MITIGATIONThe numbers of VA Staff who need and / or want Analytics Education may exceed VA capacity to deliver training

1) Expand capacity of Basic Analytics Education.2) Expand capacity of Healthcare Analytics

Certificate Course.3) Leverage opportunities to provide Analytics

support and mentoring through existing staff capable in basic and advanced Analytics functions.

Lack of sufficient resources, both human and budgetary, to conduct evaluation of the organizational impact of analytics educational course offerings

1) Various methods can be explored to achieve measure of organizational impact. Methods may be chosen based on ability to implement them meaningfully with existing resources.

7.2. ConstraintsThe Health Informatics Initiative Workstream C project team and EES have identified the following specific constraints with respect to the implementation of this training plan:

7.2.1. Availability of FacultyThe number of students who may enroll in the VHA Healthcare Analytics Certificate Course to achieve a certificate of full four-course completion will be constrained by the availability of faculty to provide the necessary support for assistance and evaluation of homework assignments.

7.2.2. Funding for development and delivery of Essential micro-analytics knowledge education and EMAK (Essential Micro-analytics Knowledge) education specialists training

The ability to develop and deliver training programs for Essential micro-analytics knowledge education and for EMAK specialist education may be constrained by availability of funding and of resources (both human and operational) to develop and deploy each type of training in a pilot site environment, and subsequently to perform national scale-up of these educational programs.

7.2.3. Coverage for Student Time CommitmentThe availability of coverage for students’ routine duties will constrain the amount of time that students have available to participate in elective training.

7.2.4. Funding for Travel and TuitionParticipation in training that may require travel and/or tuition payment may be constrained by the availability of funds.

7.2.5. Communication GapsParticipation in training may be limited by incomplete distribution of information throughout the organization regarding training availability to all potentially interested staff.


APPENDIX A: CONCEPTUAL MODEL FOR A DATA DRIVEN ORGANIZATION


APPENDIX B: Sample Curriculum Descriptions

Knowledge Synthesizer Training (Healthcare Analytics Certificate Training)Knowledge synthesizer training is conducted through an online education environment (Blackboard™). The education consists of four ten-week-long courses. Each course has assigned readings and homework. While lectures are available asynchronously, the course is moderated by a university professor. On average, students spend six to eight hours per week in listening and viewing class presentations, reading the assigned text, completing homework, and participating in learning exercises. The course is taught at the graduate school level.

The knowledge synthesizer training includes curricula aimed at developing “data diggers” who also can also mentor teaching others where to find problem specific data. During the third course of the 4-course Healthcare Analytics certificate training program, a whole semester is directed at VHA data set mining, including leveraging existing training available through VHA Support Service Center and Inpatient Evaluation Center (IPEC).

Essential Micro-analytics Knowledge Education Specialist TrainingEMAK (Essential Micro-analytics Knowledge) education specialists training will be conducted through an online education environment (Blackboard™) supplemented by LiveMeeting™ and VANTS conference calls. The preliminary training plan is designed to consist of six modules: 1) Adult Education Theory and Practice (10 hours class and homework); 2) Teaching “Data Management with Excel” (four hours class and homework); 3) Teaching “Basic Data Analysis with Excel” (four hours class and homework); 4) Teaching “Visualizing Data in Excel” (four hours class and homework); 5) Teaching Pivot Tables (four hours class and homework); 6) Teaching “Using SharePoint to Manage Data” (six hours class and homework).

Training of the EMAK education specialists aims to educate staff not only to teach tools but to work with students one-to-one as they work through their own real-life analytical problems. Trained EMAK educators will be able to mentor their students how access the data they need for their own roles at VA. The model for front line education is just-in-time training consistent with adult education theory and practice.


APPENDIX C: Basic and Intermediate Level Analytics Education


APPENDIX D: Advanced and Expert Level Analytics Education, Sample Curricula

Healthcare Data Analysis Course


Healthcare Systems Improvement Course


APPENDIX E: PRE-ASSESSMENT STUDENT SURVEY

Healthcare Data Analysis course - Fall 2010Employee Assessment(Optional) So as to explore the impact that this course will have on an employee, please rate your employee’s abilities for data analysis by answering the following questions. Next spring, after the completion of the course, we will ask you to again rate your employee’s abilities. The goal of these questions is not for evaluative purposes of the employee, but rather to measure impact of the course. Your answers will not be shared with your employee.

Please rate your employee's...

1 = Novice 2 = Good 3 = Advanced 4 = Expert N/A - do

not know

Ability to organize data

Ability to define a question that can be answered by a set of data

Familiarity with statistical terminology and jargon

Ability to perform data analysis with a spreadsheet

Ability to answer questions using data analysis

Following a defined process when analyzing a set of data

Ability to share the results of a data analysis

Ability for explaining/justifying conclusions from a data analysis


APPENDIX F: ACKNOWLEDGEMENTS

Workstream C Advisory Group Workstream C Competency Group

Barbara Andrzejewski Diane Bedecarre

Diane Bedecarre Kimberly Bishop

Steven H. Brown Elizabeth S. Chapman

Mark Cecil Jeff Fahner

Elizabeth S. Chapman Denise Harrison

Jeremy Gebhard Russell Jacobitz (ad hoc)

Marlene Haddad Maureen Khung

Judy Ingebritson Toni King

Sally Kellum Michelle Lucatorto

David Lin Deborah Ludke

Michelle Lucatorto Molly Manion (ad hoc)

Margaret (Molly) Manion Diane Montella

Mildred Manning-Joy Ebele Okwumabua

Sean McFarland Joseph (Gus) O'Neil

Diane Montella Adelaide Quansah

Robert O’Hara Jerry RutherfordRick Shew

Joseph (Gus) O'Neil Peter A. Woodbridge

Ebele Okwumabua

Jerry Rutherford

Adelaide Quansah

Katherine Gianola


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