An Introduction to Social Networks Methods in Health Services

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					  An Introduction to Social Networks
  Methods in Health Services Research

            AcademyHealth Annual Meetings, 2007

Doug Wholey
Health Policy & Management, School of Public Health, University of Minnesota

David Krackhardt
The H. John Heinz III School of Public Policy and Management, Carnegie Mellon
University


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Presentation Organization

      Introduction to social networks
       methods
      Three examples of social networks
       research in health services research




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Presenters

      Doug Wholey
           Professor, Division of Health Policy &
            Management, School of Public Health,
            University of Minnesota
      David Krackhardt
           Professor of Organizations at the Heinz School
            of Public Policy and Management and the
            Tepper School of Business, Carnegie Mellon
            University
           Center for Computational Analysis of Social and
            Organizational Systems (CASOS)
               2007 Summer Institute, June 25 - July 1, 2007

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Handouts

      Social Networks Resources
      Life in the Pentagon
      Presentation




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  Introduction to Social Networks
  Methods


            David Krackhardt




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  Examples of Social Network Studies in
  Health Services Research



            Doug Wholey




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Examples

      Evaluating the Minnesota Cancer Alliance
           Collaborator: Michael Pfeffer, MPH candidate
      Evaluating an intervention to coordinate
       agencies providing services to people in
       prostitution in North Minneapolis
           Collaborator: Kate Downing, MPH candidate
      Teams and sub-teams in medical practice
           Collaborators: David Knoke, Bill Riley, and Amy
            Wilson
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Issues in Studying Networks:
Identifying Network Boundaries

      Realist
           Network exists as a social object, there is a defined
            boundary and membership, there is shared knowledge
           Minnesota Cancer Alliance, medical groups, associations,
            rural health networks, assertive community treatment
            teams
      Nominalist
           Network membership is defined by research interests
           Agencies serving people in prostitution agencies
           Public health systems – organizations providing public
            health related services in a geographic area


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Issues in Studying Networks: Which
Relationships?

      Types of relations
           Collaboration
      Levels of collaboration
           Who do you share information with about
            program development?
           Who do you work with to develop
            programs?
           Who are you collaborating with to obtain
            funding for programs?
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Issues in Studying Networks:
Relational, Attribute, & Event Data

      Relational data
           N (actor) x N (actor) matrix
           Who interacts with who?
      Attribute data
           N (actor) x A (attribute)
           Can use to construct a relational matrix showing similarity
            between two actors (same gender, difference in age)
      Event/Affiliation data
           N (actor) x A (event) matrix
           Can use to construct a relational matrix to who who
            attends the same meetings

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 Issues in Studying Networks: Event
 Data to Relational Data
                Attended Meeting
                1       2           3           4
 George         0       1           1           1              = A (Event Matrix)
  Sam           1       0           1           1
    Jane        1       0           0           0
                                                                             G   S    J
                                                                   George    2   2    0
AxA‟ (Common Attendance) =                                          Sam      2   3    1
Use UCINET‟s /Data/Affiliations tool                                  Jane   0   1    1
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The Minnesota Cancer Alliance

      A coalition of health care organizations
       founded in 2005 with the goals of
           Reducing disparities in cancer screening and
            treatment
           Improving access to information about locally-
            available services for cancer patients and their
            families
           Increasing colorectal cancer screening
           Increasing the tobacco excise tax and
            expanding clean indoor air
           http://www.cancerplanmn.org/The_Minnesota_C
            ancer_Alliance.html
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Comprehensive Cancer Control
Collaborative
     For cancer prevention and treatment in a
      community,
         Develop a shared comprehensive vision
         Eliminate duplications, integrate efforts, reduce
          organizational and programmatic fragmentation
         Plan and implement an evidence based program
         Identify gaps and prioritize action
         Reallocate resources
         Advocate with one voice
         “Increased coordination of partner activities and enhanced
          collaboration” (6).
     Leslie S. Given, Bruce Black, Garry Lowry, Philip Huang, &
      Jon F. Kerner, 2005, Collaborating to conquer cancer: A
      comprehensive approach to cancer control, Cancer Causes
      and Control 16(Suppl): 3-14.
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Alliance Evaluation and Committees

            Evaluation                                            Committees
      Who is active where?                                 Community Health Worker
           People                                          Cervical Cancer Screening
           Organizations                                   Colorectal Cancer
      How does participation                                Screening
       evolve?                                              Access to Information
      Who is central in each                               Health Disparities
       committee?                                           Steering Committee
      Who is central across                                Evaluation Committee
       committees?
      What is the structure of                             Communications
       interaction                                           Committee
           Structure = repeated                            Finance Committee
            patterns of interaction                         Membership Committee

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Methods

      Data Source: Meeting Archives
           Meeting Attendance
           Individual - Organizational
      Methods:
           Used UCINET to translate affiliation data
            (copmmon meetings attended) to relational data
           Number of meetings attended by both members
            of a dyad is strength of attachment to committee


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Health Disparities Committee
(Three or More Meetings)




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Health Disparities Committee
(Four or More Meetings)




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Health Disparities Committee
(Four or More Meetings)




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Colorectal Cancer Committee
(1 or More Meetings)




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Colorectal Cancer Committee
(6 or More Meetings)




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Colorectal Cancer Committee
(14 or More Meetings)




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Further Analyses: Which actors are
central across committees?




                                             …
                                    Disparities
                                  Access to Information
                                Cervical
                              Colorectal



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What Can We Learn from Meeting
Attendance

      Which members within the committee?
           Are there core and peripheral members?
           How stable are relationships?
      Which actors coordinate/bridge across
       committees?



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Next Steps

      Initial analyses took advantage of
       unobtrusive measures: Meeting attendance
      Why are some members more involved than
       others in a committee?
           What is the content of the relationship?
            Watching? Collaborating?
      Research to develop a better understanding
       of committees and involvement
           Field experience by Michael Pfeffer
      Develop a survey to understand
       involvement and describe networks better
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    Improving Service Delivery for People
    in Prostitution
       Research and Intervention led by
        Folwell Center for Urban Initiatives
               North Minneapolis, MN
               Lauren Martin, Ph.D.
               Kate Downing, MPH Candidate




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The Problem – North Minneapolis and
Prostitution

      Poverty
      Population of Color
      Mental Health and Substance Abuse
      A doubly stigmatized, vulnerable
       population


                                        Project Focus Area, North Minneapolis
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The Problem: Service Delivery

      Access to Services
           Few prostitution specific services
      Politics of Delivery
           Ideological Barriers
           Funding Scarcity
      A difficult context to organize


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The Evaluation

      Evaluate an intervention to coordinate
       agencies
      Network Analysis
           Understanding the mechanism
           Pre-Post Evaluation
               Funding search in progress for intervention
                and evaluation


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The Evaluation

      What does Collaboration really mean?
           What does it mean to „work with?‟
           Asking probing questions:
               Do you go to the same meetings?
               Do you collaborate on programs?
               Do you go after funding together?




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The Intervention:
Northside Women‟s Space

      A point of connection:
           For service providers to work together
           For women involved in prostitution to find safety,
            community and services
      The space will offer:
           Resource guide
           Non-judgmental referral services
           Workshops
           Safe sex supplies, snacks, etc.
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The Intervention:
Northside Women‟s Space

      One central actor managing the space
           Folwell Center for Urban Initiatives
           Kate Downing
               Support development and research
      Other agencies will staff the space
           Adhering to soon available best practices



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Challenges

      The questions we can‟t ask…
      Maintaining neutrality and building
       bridges
      Developing trust and keeping it
      Unknown, invisible population size
           A barrier to political will, funding
      Identifying agencies to survey
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Expected Outcome:
Northside Women‟s Space

      More network ties                            Success means:
                                                            Greater visibility of the
      Central node for                                      problem
       the Northside                                         Improvement in
       Women‟s Space                                         service delivery
                                                            Continuing needs
      Care integration                                      assessment
      Improved quality of                                  Advocacy for change
                                                             through collaboration
       care and service
                                                            Shift from crisis
      Improved                                              oriented care to primary
       outcomes                                              prevention


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Care Teams in Medical Practice
            The Context & Argument                                       The Mechanism

      Health care is becoming more                           Care teams
       differentiated                                             Interdisciplinary teams
            New technologies and                                  serving a population
             technicians                                          Task work (service provision)
            Professional jurisdictions                            coordinated with team work
             shifts                                                (systems, coordinating
      Care is shifting towards chronic                            service delivery)
       rather than acute conditions                           Hope
      Chronic conditions require                                 Integrated care
       integration of a large variety of                          Greater productivity through
       services: Social, mental, and                               reduced waste (lean
       medical services                                            management, QI)
      Lack of care integration results in                        Better patient outcomes
       inadequate care for individuals                            Better team member
       with chronic conditions                                     outcomes


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Care Team Examples

      Chronic Care Teams
       http://www.improvingchroniccare.org /
      Assertive Community Treatment (ACT)
       Teams
       (http://www.actassociation.org/actModel/ )
      Prepared Practice Teams
       (http://www.ihi.org/IHI/Topics/ChronicConditi
       ons/AllConditions/ImprovementStories/Purs
       uingPerfectionReportfromHealthPartnerson
       PreparedPracticeTeams.htm)
      Medical Homes and Patient Homes
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Teams
      “A team can be defined as
           (a) two or more individuals who
           (b) socially interact (face-to-face or, increasingly, virtually);
           (c) possess one or more common goals;
           (d) are brought together to perform organizationally relevant
            tasks;
           (e) exhibit interdependencies with respect to workflow, goals,
            and outcomes;
           (f) have different roles and responsibilities; and
           (g) are together embedded in an encompassing organizational
            system, with boundaries and linkages to the broader system
            context and task environment.”
      Steve W. J. Kozlowski and Daniel R. Ilgen. 2006. "Enhancing
       the Effectiveness of Work Groups and Teams." Psychological
       Science in the Public Interest 7:77-124 (79).


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Issues in Identifying Care Teams

      Boundary specification – who is a team
       member?
           Floaters? Visiting consultants? Anyone who has
            anything do do with care delivery?
      Teams and sub-teams
           Assertive Community Treatment & Individual
            Treatment Teams
           Football teams
      Formal and informal teams
           Emergent teams
           Inertial teams
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Identifying Teams and Sub-teams


                     Structural                                       Individual

                                                                   Team
     Realist
                   ACT teams                                    membership
(Social Fact)
                                                                perceptions
Nominalist          Top                                        Groups of
(Researcher      management                                 interdependent
  Defined)      teams, Clinics                                   actors
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Using Interdependence to Identify
Teams

      Organizational theory and complexity theory: “Organizing at the edge
       of chaos”
           Tim Carroll and Richard M. Burton. 2001. "Organizations and
            Complexity: Searching for the Edge of Chaos." Computational &
            Mathematical Organization Theory 6:319-337.
           David Krackhardt, 1994, "Constraints on the Interactive Organization as
            an Ideal Type." In Charles Heckscher & Anne Donnellan (eds.), The
            Post-Bureaucratic Organization. Beverly Hills, CA: Sage, p. 211-222.
      Who do you work with to provide patient care?
           Work with means that you and the other person are interdependent
            during work – your actions affect each other directly. It does not refer to
            the situation where you and the other person contribute separately to
            clinic performance while you work in the same location. Please answer
            these questions for all others with whom you work (e.g., physicians,
            rooming nurses, staff, laboratory technicians, and receptionists).
           Patient care means all direct patient care and patient care related
            activities (e.g., ordering tests, calling in prescriptions, talking with patients
            on phone).

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Identifying Teams Using Structural
Equivalence
      (g) are together embedded in an encompassing organizational system, with
       boundaries and linkages to the broader system context and task environment.
           Groups based on structurally equivalence: “Two nodes are said to be exactly
            structurally equivalent if they have the same relationships to all other nodes.”
      (a) two or more individuals who
           At least two actors
      (e) exhibit interdependencies with respect to workflow, goals, and outcomes;
           Dense interdependence
      (f) have different roles and responsibilities;
           Occupational heterogeneity
      (b) socially interact (face-to-face or, increasingly, virtually)
           Informal consulting
      Inferred
           (c) possess one or more common goals;
           (d) are brought together to perform organizationally relevant tasks;




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       A Work With Sociomatrix:
       Pediatrics Clinic
           MD08    MD21   MD25    MD54      MD64       MD82      N00     N08     N21   N25   N54   N71   N79    N82
MD08          0     0      0        0          0         0         3       1       2    2     3     0     3         2
MD21          0     0      2        0          0         2         3       2       2    3     3     0     3         2
MD25          0     2      0        0          0         3         3       1       2    3     3     0     3         2
MD54          0     0      0        0          0         0         1       3       0    0     0     0     0         1
MD64          0     0      0        0          0         0         3       2       0    2     2     0     2         2
MD82          0     2      3        0          0         0         2       2       1    2     2     0     2         2
N00           3     3      3        1          3         2         0       1       1    1     3     2     2         2
N08           1     2      1        3          2         2         1       0       2    2     2     2     2         1
N21           2     2      2        0          0         1         1       2       0    1     2     1     1         1
N25           2     3      3        0          2         2         1       2       1    0     2     1     2         1
N54           3     3      3        0          2         2         3       2       2    2     0     3     2         2
N71           0     0      0        0          0         0         2       2       1    1     3     0     3         2
N79           3     3      3        0          2         2         2       2       1    2     2     3     0         2
N82           2     2      2        1          2         2         2       1       1    1     2     2     2         0

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Graphing the Full Sociomatrix:
Pediatrics Clinic




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   Structurally Equivalent Actors:
   Pediatrics Clinic
                    2N
Occupational
Grouping                                                                            6 MDs, 1 N




               4N


                                                                               1N


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Graphing the Full Sociomatrix:
Family Practice Clinic




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  Structurally Equivalent Actors:
  Family Practice Clinic
                                                           2 MD, 1 ST               Teams

     2 MD, 2 N

                                                                              2 MD, 5 N




4 ST


                                                                              2 MD, 1 N,
                                                                              2 ST, 1 T
                                                          N, 3 ST, T
                 2 ST
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Predictive Validity for Interdependence
Method for Identifying Teams

      Informal consulting
           is more likely to occur within teams than
            between teams
           Is greater in more cross-functional and
            interdependent teams
      Teams consistent with clinic staffing rules
           Pediatrics – pool staffing
           Family practice – practice teams
      Consistent with organizational and
       complexity theory
           Organizing at the edge of chaos
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Usefulness of Methodology

      Where are sub-teams in
               Chronic care teams?
               Primary care practices?
               Assertive community treatment teams?
      How are sub-teams connected?
           Is it too many? Process loss and
            perturbations?
           Is it too few? So loosely coupled system
            is not integrated.
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Social Networks Research Challenges
(And Benefits)

      Observing relations rather than actors
      Defining network boundaries
      Defining relations to measure
           Friendship? Respect? Work-with?
            Helping?
           Level of detail
      Obtaining high response rates
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Managerial Benefits of a Social
Network Approach

      Managing relations is a key function of
       management
           Relations can be managed with relatively
            simple interventions (staffing)
      Measuring networks supports
           Accurate understanding of network
            structure, which supports effective
            management
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Research Benefits of a Network
Approach

      Evaluate interventions designed to
       integrate care
      Understand the black box between
       formal and informal structure
           Paths (or lack of paths) for information
            flow
           Disconnects
           Too many connections
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