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Using Data to Drive Daily Practice and Program Success. Gabrielle Bargerstock, MPH Business Development Manager Nurse-Family Partnership National Service Office. Florida Association of Infant Mental Health/MIECHV Conference Many Paths to Enhancing Parent Child Relationships April 25, 2014.

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using data to drive daily practice and program success

Using Data to Drive Daily Practice and Program Success

Gabrielle Bargerstock, MPH

Business Development Manager

Nurse-Family Partnership National Service Office

Florida Association of Infant Mental Health/MIECHV Conference

Many Paths to Enhancing Parent Child Relationships

April 25, 2014

presentation overview
Presentation Overview
  • Brief discussion of data as a concept
  • Data types and usage
  • Context: MIECHV Program & Benchmarks
  • Data Analysis Tools and Strategies
  • Activities
  • Resources
what is data
What is Data?
  • Facts or information used usually to calculate, analyze, or plan something
  • Factual information (as measurements or statistics) used as a basis for reasoning, discussion, or calculation
  • Information output …that includes both useful and irrelevant or redundant information and must be processed to be meaningful.
what is data1
What is Data?

According to Russell Ackoff: the content of the human mind can be classified into five categories:

  • Data: symbols
  • Information: data that are processed to be useful; provides answers to "who", "what", "where", and "when" questions
  • Knowledge: application of data and information; answers "how" questions
  • Understanding: appreciation of "why“
  • Wisdom: evaluated understanding.
challenges in prevention
Challenges in Prevention

The work requires:

  • Substantial knowledge and skill
  • Entails many steps (ex: assessing need, setting priorities, planning/delivering programs, monitoring, and evaluation.)
  • Implementation in varied settings and communities
    • Requiring tailoring
  • Adherence to model fidelity
other complicating factors
Other Complicating Factors
  • Getting enough data vs. being a burden
  • Credible numbers vs. “we know things are better”
  • Determining the right focus at the right time
    • process vs. outcomes
    • quantitative vs. qualitative
types of data
Types of Data


  • Process evaluation looks at a program’s implementation and establishes whether quantifiable targets have been achieve and strategies implemented as planned.
  • Can be useful determining whether a program should be refined continued, expanded, or eliminated.
  • Process data includes information such as the total program participants, demographics, how many homevisits have been completed per client, etc.


  • Outcome evaluation measures the change that has occurred as a result of a program.
  • An outcome evaluation would tell you how many program participants demonstrated changed behaviors as a result of programmatic activities i.e. initiated breastfeeding, quit using drugs or alcohol, improved test scores, returned to school or work, etc.
types of data1
Types of Data:



  • Data that can be accurately represented numerically.
  • Data that can be measured.
  • Mathematic measurements, frequency of events, or categorical surveys (Yes/No, or rate a response on a 1-5 scale, etc).
  • Length, height, area, volume, weight, speed, time, temperature, humidity, sound levels, cost, members, ages, etc


  • Descriptions
  • Data can be observed but not measured.
  • Colors, textures, smells, tastes, appearance, beauty, etc.
  • Includes things like verbal interviews or surveys that ask questions that are open ended
maternal infant early childhood home visiting miechv program
Maternal, Infant, &Early Childhood Home Visiting (MIECHV) Program
  • Facilitates collaboration and partnership to improve health and development outcomes for at-risk children through evidence-based home visiting programs.
  • Program Purposes:
    • Strengthen and improve the programs and activities carried out under Title V of the Social Security Act;
    • Improve coordination of services for at-risk communities; and
    • Identify and provide comprehensive services to improve outcomes for families who reside in at-risk communities.
  • MIECHV includes grants to states and six jurisdictions; as well as grants to tribes and tribal organizations.
maternal infant early childhood home visiting miechv program1
Maternal, Infant, & Early Childhood Home Visiting (MIECHV) Program
  • MIECHV is an evidence-based policy initiative.
    • Requires that the majority of grant funds (75% or more) to be spent on programs to implement evidence-based home visiting models. 
    • Up to 25 percent may be spent on promising approaches that must be rigorously evaluated
  • Currently, 14 home visiting models meet the HHS criteria for evidence-based home visiting.
  • Florida Association of Healthy Start Coalitions oversees in Florida. Ten sites funded.
florida s benchmark plan
Florida’s Benchmark Plan
  • Legislation authorizing MIECHV funding requires that all programs collect data to evaluate program performance and outcomes across six benchmark areas for all enrolled families:
    • Maternal and child health;
    • Childhood injuries and abuse and neglect;
    • School readiness;
    • Domestic violence;
    • Family economic self-sufficiency; and
    • Coordination of services.
  • Florida’s online data collection system – Florida Home Visiting Information System (FLOHVIS)
  • For more information contact Virginia Holland, Data Manager (
data in daily practice
Data In Daily Practice
  • Using data on a day to day basis doesn’t have to be complicated or difficult to understand
    • You do it already, many times a day
  • Goal: Move from informal usage of data, to conscious focus on analysis
  • In other words: Ongoing Quality Improvement or CQI
types of analyses
Types of Analyses
  • Root Cause Analysis (RCA) is the formal search for an individual or group of true causes of a problem and not just the symptoms.
    • more than just one root cause to a problem often exists and they can interact with each other.
  • RCA can capture both the big-picture perspective and the details. It can also be pointed at any problem, both simple and complex.
  • Simplest technique: Ask ‘Why’ five times…
types of analyses1
Types of Analyses

The Plan-Do-Study-Act (PDSA) cycle is a simple yet powerful tool for accelerating quality improvement. The PDSA cycle is shorthand for testing a change—by planning it, trying it, observing the results, and acting on what is learned. This is the scientific method, used for action-oriented learning.

The steps in the PDSA cycle are:

  • Step 1: Plan--Plan the test or observation, including a data collection plan
  • Step 2: Do -- Try out the test on a small scale
  • Step 3: Study--Set aside time to analyze data and study the results
  • Step 4: Act--Refine the change, based on what was learned from the test
real life example
Real Life Example:
  • Home visiting staff weren’t entering data into the program and state’s reporting systems in a timely fashion, resulting in negative actions by the state oversight agency and payment penalties.
    • Core Reason Why:
      • Staff didn’t adequately understand or have comfort with operating the computers and subsequently the database system.
    • Response: Training AND modification of hiring practices
organizational example nfp
Organizational Example - NFP

Continuous Improvement

Quality Framework


Quality Improvement Process






Measure, Analyze & Evaluate

activities to consider
Activities to Consider
  • Have a two hour meeting to review current work (no more, no less)
    • Identify all key areas
    • Reflect on data, resources, and results
    • Chose 1 or 2 initiatives to stop and/or start
    • Set ‘by when’
    • Identify three points in time where you can report out on your efforts
      • Ex: Team Meeting, Staff event, Board Presentation, Community Meetings
activities to consider1
Activities to Consider
  • Make daily operations more efficient, easier, rewarding….
    • Survey employees, clients, etc. for processes/activities that are duplicative, time-consuming, nonsensical.
    • Identify one activity (or more) you could eliminate immediately and then stop doing it.
    • For activities that are necessary are there areas for potential streamlining?
activities to consider2
Activities to Consider
  • Elevator speeches and key statistics statements
    • If you don’t have them, create them as a team or ask individual team members to each develop one then discuss
  • Set a ‘What by when’ goal or create a 100 day challenge