This document discusses key concepts in research frames and designs for health informatics and health information management (HIM) research. It defines research and describes the components of a research frame, including theories, models, assumptions, and methodology. The document outlines different types of research designs such as descriptive, correlational, observational, evaluation, experimental, and quasi-experimental designs. It also discusses the distinctions between basic and applied research and quantitative, qualitative and mixed methods approaches.

1. © 2017 American Health Information Management Association
© 2017 American Health Information Management Association
Health Informatics Research Methods:
Principles and Practice, Second Edition
Chapter 1: Research Frame and
Designs

2. © 2017 American Health Information Management Association
Learning Objectives
• Use and explain the terms research, research
frame, theory, model, and research methodology.
• Designate the appropriate placement of a
research project on the continuum of research
from basic to applied.
• Differentiate among research designs.
• Provide appropriate rationales that support the
selection of a research design.
• Use key terms associated with research frames
and designs appropriately.

3. © 2017 American Health Information Management Association
Definition of Research
• Research is a systematic process of
inquiry aimed at discovering or creating
new knowledge about a topic, confirming
or evaluating existing knowledge, or
revising outdated knowledge

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What Are Health Informatics
and HIM Research?
• Health informatics research is the investigation of the
process, application, and impact of computer science,
information systems, and communication technologies
to health services
– Example: Identification of commonly recurring safety
issues related to EHRs
• HIM research is investigation into the practice of
acquiring, analyzing, storing, disclosing, retaining, and
protecting information vital to the delivery, provision,
and management of health services
– Example: Meanings of the term “medical record” in
research forms

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Purposes of Health Informatics
and HIM Research
• Formulate theories and principles of health informatics
and HIM
• Test existing theories, models, and assumptions about
the principles of health informatics and HIM
• Build a set of theories about what works, when, how,
and for whom
• Advance practice by contributing evidence that
decision makers can use
• Train future practitioners and researchers
• Develop tools and methods for the process of health
informatics research and HIM research

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Research Frame
• Research frame: Overarching structure of
a research project, including
– Theory or theories underpinning the study
– Models illustrating the factors and
relationships of the study
– Assumptions of the field and the researcher
– Methods
– Analytical tools

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Theories and Models
• Theory: Systematic organization of knowledge
that explains or predicts phenomena
– Interrelating concepts in a logical, testable way
– Providing definitions, relationships, and boundaries
– Parsimonious
• Model: Idealized representation that abstracts and
simplifies a real-world situation so the situation
can be studied, analyzed, or both
– Visual depiction of theory
– Portrayal with objects, smaller-scaled version, or
graphic representation

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Examples of Theories and
Models Used in Health
Informatics and HIM Research:
• Theories
– Adult learning theories
– Change theories
– Diffusion of innovations
– General systems theory
– Information behavior theories
– Information processing or
cognitive learning theories
– System of systems theory
– User acceptance theories
– And others (table 1.1)
• Models
– AHIMA Data Quality
Management Model
– Dominant design (A-U model)
– Information systems success
model
– Sociotechnical model
– Swiss cheese model
– Systems development life
cycle model
– Technology acceptance
model
– And others (table 1.1)

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Research Methodology and
Research Method
• Research methodology: Study and
analysis of research methods and theories
– Example: Which method of data collection
results in the greatest response rate?
• Research method: Set of specific
procedures used to gather and analyze
data
– Example: Surveys (chapter 2) and focus
groups (chapter 3)

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Continuum of Basic and Applied
Research
• Basic research
– Answer question “Why?”
– Focuses on development
of theories and their
refinement
– “Bench science”
• Applied research
– Answers questions
“What?”, “How?”,
“When?”, or “For
whom?”
– Focuses on
implementation of
theories and models into
practice
– Most health informatics
and HIM researchers are
applied researchers

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Approaches:Quantitative,
Qualitative, and Mixed Methods
Quantitative
• Explanation of
phenomena by
making predictions,
collecting and
analyzing evidence,
testing alternative
theories, and
choosing
the best theory
• Numeric data
• Generalizability
and positivism
• Qualitative
• Investigation to
describe, interpret,
and understand
processes, events,
and relationships as
perceived by
individuals or groups
• Nonnumeric data
• Context
Mixed methods
• Combination of
quantitative and
qualitative theoretical
perspectives, methods,
sampling strategies,
data collection
techniques, data sets,
analytical procedures,
representational modes,
or any combination of
these aspects
• Suited to studies of
healthcare

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Scientific Inquiry
• Scientific inquiry: Way of generating knowledge by
systematically gathering data about phenomena,
critically analyzing the data, proposing
explanations based on evidence, and developing
understanding and knowledge
– Empiricism
– Inductive reasoning (induction): From specific to the
general; drawing conclusions based on a limited
number of observations (“bottom up”)
– Deductive reasoning (deduction): From general to the
specific; drawing conclusions based on
generalizations, rules, or principles (“top down”)

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Rigor
• Rigor establishes the validity and reliability of
a research study’s results and conclusions
– Quantitative definition: Strict application of the
scientific method to ensure unbiased and well-
controlled experimental design, methodology,
analysis, interpretation and report of results and
includes transparency in reporting full
experimental details so that others may
reproduce and extend the findings
– Qualitative definition: Trustworthiness of the
interpretation of the study’s findings

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Research Designs
• Research design: Plan to achieve the researchers’ purpose—
answering a question, solving a problem, or generating new
information
– Infrastructure of the study
– Seven common research designs
• Historical research
• Descriptive research
• Correlational research
• Observational research
• Evaluation research
• Experimental research
• Quasi-experimental research
– Selecting the appropriate research design increases the likelihood that
the evidence collected are relevant, high quality, and directly related to
the research question or problem

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Historical Research
• Historical research: Examines historical materials to explain,
interpret, and provide a factual account of events
– Purposes
• Discovering new knowledge
• Identifying trends that could provide insights into current questions or
problems
• Relating the past to contemporary events or conditions
• Creating official records
– Process of historical research is to systematically collect,
critically evaluate, and analyze and interpret evidence from
historical materials, known as primary and secondary sources
– Example: US National Library of Medicine’s Conversations with
Medical Informatics Pioneers

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Primary and Secondary
Sources
• Primary sources
– First-hand sources
also called primary data
– Examples
• Original documents
• Artifacts
• Oral histories
– Created or collected
for a specific purpose
– Preferable to secondary
sources
• Secondary sources
– Second-hand sources also
called secondary data
– Created by people
uninvolved with the event
– Aggregate, summarize,
critique, analyze, or
manipulate the primary
sources and, thus, are
derived from primary
sources

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Descriptive Research
• Descriptive research determines and reports the
current status of topics and subjects
– Seeks to accurately capture or portray dimensions or
characteristics of people, organizations, situations,
technology, or other phenomena
– Should be chosen to answer questions, such as “what is,”
“what was,” or “how much”
– Is best way to collect information that will demonstrate
relationships and describe the world as it exists
– Some descriptive research studies are also correlational—
detecting relationships
– Example: Study of consumers’ perspectives on the
healthcare environment and use of services

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Correlational Research
• Correlational research detects the existence, direction, and strength
(or degree) of associations among characteristics
– Characteristics can be phenomena, factors, attitudes,
organizational features, properties, traits, indicators,
performance measures, or any other attribute of interest
– Quantitative, exploratory, and indicative of existing associations
– Can be either descriptive or predictive
– Predictive when predicting nonrandom change in one
characteristic (or characteristics) based on change in another
characteristic (or characteristics)
– Example: Patients’ rates of social media usage and their ratings
of providers

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Correlational Research (cont.)
• Strength of
association
– Strength of 0.00 means
absolutely no association
– Strength between 0.00
and +1.00 or between
0.00 and –1.00 means
that the variables
sometimes, but not
always, move together
– Strength of 1.00 or –1.00
means a perfect
association, with the
variables moving exactly
in tandem
• Cannot establish
causal relationship
– Unknown variable could be
creating apparent association
– Confounding variable also
called extraneous or
secondary variable
• Shortcomings of self-
report
– Subjects’ biases
– Selective memory
– Social desirability

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Linear Relationships
• Positive (direct) linear
relationship
– Exists when the scores
for variables
proportionately move in
the same direction
– As one increases, so
does the other; or as
one
decreases, so does the
other
• Negative (inverse)
linear relationship
– Exists when the scores
for variables
proportionately move in
opposite (inverse)
directions
– As one increases, the
other decreases; or as
one decreases, the
other increases

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Examples of Relationships
Positive (direct) linear
relationship
Negative (inverse) linear
relationship
Curvilinear relationship
(s-curve)

22. © 2017 American Health Information Management Association
Observational Research
• Observational research is exploratory research that
identifies factors, contexts, and experiences through
observations in natural settings
– Focus is participants’ perspective of their own feelings,
behaviors, and perceptions
– Provides insights into what subjects do, how they do it,
and why they do it through rich data, artifacts, and
triangulation
– Nonparticipant observation, participant observation, and
ethnography
– Example: Case study of how well portals convey
information to patients

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Observational Research (cont.)

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Evaluation Research
• Evaluation research is the systematic application of
criteria to assess the value of objects
– Can use any of the other research designs; it is the
purpose—evaluation—that classifies the design as
evaluation
– Objects evaluated in terms of merit, worth, quality, or
combination of these attributes
– Evaluated objects include policies, programs, technologies
(including procedures or implementations), products,
processes, events, conditions, organizations, and others
– Evaluation criteria include conceptualization, design,
components, implementation, usability, effectiveness,
efficiency, impact, scalability, and generalizability

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Evaluation Research (cont.)
• Terms for evaluation
research
– Outcomes research
– Health services research
– Health technology assessment
– Comparative effectiveness
research
– Usability testing
• Types of evaluation
research
– Needs assessment
– Process evaluation
– Outcome evaluation
– Policy analysis
Example: Study that evaluated the impact of the Regional
Extension Center program

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Experimental Research
• Experimental research is conducted to establish cause-and-effect
(causal) relationships
– Strict procedures, random assignment of subjects to groups,
manipulation of subjects’ experience, and measurement of
resulting physical, behavioral, or other changes
– Strictly controlled situations and environments
– Four features
• Randomization (random sampling, experimental [study] group [arm])
• Observation before and after treatment (dependent variable)
• Presence of control group(s) (arm)
• Treatment manipulating independent variable
– Test hypotheses following protocols
– Example: RCT evaluating effectiveness of HIT in medication
safety

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Experimental Research (cont.)
• Control environments and subjects
– Control: Processes used to maintain uniform conditions in order
to eliminate sources of bias, variations, and any extraneous
factors that might affect research’s outcome
– Allows researchers to conclude that independent variable
caused change in dependent variable without any other possible
explanations related to bias, variation, or unknown factors

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Experimental Research (cont.)

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Quasi-experimental Research
• Quasi-experimental research searches for plausible
causal factors or indicates that a causal relationship
could exist
– Approximate environment of true experiments
– Investigations of possible cause-and-effect relationships
– Often, randomization, is absent
– Quasi implies design is “similar to” or “almost” experimental
– Also called causal-comparative research or ex post facto
– Example: Study assessing effectiveness of decision support
systems for various diseases

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Quasi-experimental Research
(cont.)
• Quasi-experimental research design appropriate
situations prevent random assignment, such as when
variables
– Cannot be manipulated (gender, age, race, birth place)
– Should not be manipulated (accidental death or injury,
child abuse)
– Represent differing conditions that have already occurred
(medication error, heart catheterization performed,
smoking)
• Lack of randomization creates potential for bias
• Lack of control creates potential for introduction of
confounding variable

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Time Frame as an Element of
Research Design
• Retrospective
– Looks back in time
• Prospective
– Follows subjects into
the future
• Cross-sectional
– One point in time
– Snapshot
– May be
unrepresentative time
• Longitudinal
– Three or more waves
– Days, weeks, months,
years, or lifetimes
– Duration varies
dependent upon topic

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Review
• Research is systematic process of inquiry
• Research frames are overarching structures including theories,
models, assumptions, methods, and analytical tools
• Theories explain or predict phenomena and provide definitions,
relationships, and boundaries
• Models are idealized representations that abstract and simplify
situations
• Basic and applied research are on a continuum
• Scientific inquiry involves inductive and deductive reasoning
• Selection of a research design depends upon the researcher’s
purpose
• Common research designs are historical, descriptive, correlational,
observational, evaluation, experimental, and quasi-experimental
• Time frame is an element of research design