HIM discussion (health information management)

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Health Informatics Research Methods: Principles and Practice, Second Edition

Chapter 1: Research Frame and Designs

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.

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aimed at discovering or creating new knowledge about a topic, confirming or evaluating existing knowledge, or revising outdated knowledge

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

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

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

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

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)

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)

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

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

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”)

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

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

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

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

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

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

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

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

Examples of Relationships

Positive (direct) linear relationship

Negative (inverse) linear relationship

Curvilinear relationship (s-curve)

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

Observational Research (cont.)

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

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

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

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

Experimental Research (cont.)

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

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

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

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