Fluent Essays

research in health informatics is stimulating, dynamic, and varied. Provide reasons why you agree or why you disagree with the statement. 2. Identify the difference between a positive (direct) relationship and a negative (inverse relationship. 3. Why is evaluation research the "workhorse" of health informatics research? i attached a powerpoint to help. minimum of 100 words Health Informatics Research Methods: Principles and Practice, Second Edition Chapter 11: Selecting the Research Design and Method and Collecting Data © 2017 American Health Information Management Association © 2017 American Health Information Management Association Learning Objectives Select a research design and method appropriate to the research question. Articulate the processes of data collection. Identify a data collection instrument appropriate to the research question. Determine standard and suitable tools and techniques to collect data. Select a sampling technique appropriate to the research question. Explain how data collection procedures affect studies’ timelines and the quality of their collected data. Use key terms associated with instruments, sampling, samples, and data collection appropriately. © 2017 American Health Information Management Association Selecting a Research Design and Method Purpose of the research (most important) Internal validity and external validity Internal: Extent to which researchers’ design and processes are likely to have prevented bias and increased accuracy of results External: Extent to which results can be applied to other settings, populations, or other phenomena Other factors in selection Skills Time Money and resources Potential subjects © 2017 American Health Information Management Association 3 Collecting Data Planning Selecting an instrument Determining a collection method Deciding upon a collection strategy and sample Performing pre-collection procedures Collecting data © 2017 American Health Information Management Association Plan for Data Collection What, how, by whom, and when Also includes timelines for obtaining approvals, training collectors, and performing pilot study Detail necessary for other researchers to replicate and reproduce Important to document plan and its execution to support validity of studies’ results © 2017 American Health Information Management Association Plan for Data Collection (cont.) Quantitative Detailed and step-by-step Conjunction with statistical analysis plan All necessary data collected Sufficient numbers of cases Qualitative Less structured than quantitative, dependent upon Time available Knowledge of phenomenon Available instruments Planned analyses Researcher’s experience © 2017 American Health Information Management Association 6 Selection of an Instrument Instrument: Standardized, uniform way to collect data Using a well-designed instrument minimizes bias and maximizes the certainty of the independent variable’s effect on dependent variable © 2017 American Health Information Management Association 7 Types of Instruments Checklists Coding schemes and manuals Clinical screenings and assessments Educational tests Index measures Interview guides Personality tests Projective techniques Psychological tests Questionnaires Rating scales Scenarios Vignettes And many others © 2017 American Health Information Management Association Sources of Instruments Electronic databases Health IT Survey Compendium Human Factors: Workbench Tools HaPI (Health and Psychosocial Instruments) Mental Measurements Yearbook with Tests in Print Articles found during literature review © 2017 American Health Information Management Association 9 Validity of Instruments Validity (of instruments): Extent to which the instrument measures what it is intended to measure Face validity Subject matter experts Content validity CVR Essential, useful but not essential, not necessary CVI Construct validity Construct Convergent, discriminant, concurrent Criterion validity © 2017 American Health Information Management Association 10 Reliability of Instruments Reliability: Extent to which a procedure or an instrument yields similar results over repeated trials, over time, across similar groups, within individuals, and across raters Dependable and consistent in measurement Consistency, dependability, and reproducibility characterize reliable instruments Types Interrater reliability and intrarater reliability Test-retest reliability Internal consistency reliability © 2017 American Health Information Management Association 11 Reliability of Instruments (cont.) Interrater reliability and intrarater reliability Intraclass correlation coefficient Cohen’s kappa coefficient Test-retest reliability Pearson product-moment correlation coefficient Intraclass correlation coefficient Internal consistency reliability Split-half reliability coefficient (Spearman-Brown correction) Kuder-Richardson formula Cronbach’s alpha © 2017 American Health Information Management Association 12 Factors in Selecting an Instrument Purpose: Match between researcher’s purpose and instrument’s purpose Theoretical underpinnings Operational definitions Most important to assure that the data collected are relevant to the research question Satisfactory ratings for validity and reliability in a developed instrument Style and format of the instrument Clear and direct Formats Delivery medium Language Age groups © 2017 American Health Information Management Association 13 14 Attributes of Items Structured questions Closed-ended Choice from list of possible responses Advantage Easier for subject to complete Easier for researcher to tally and analyze Example: What is your gender? ___Male ___Female © 2017 American Health Information Management Association 14 Attributes of Items (cont.) Unstructured questions Open-ended Free-form responses Advantage: Collect in-depth data Discover potentially unknown aspects of issue Example: What barriers prevent you from exercising? © 2017 American Health Information Management Association 15 Attributes of Items (cont.) Semi-structured questions Begin with structured question and followed by unstructured to clarify Advantages of structured and unstructured questions Would you consider yourself physical fit? ___Yes ___No Why or why not? © 2017 American Health Information Management Association 16 Attributes of Items Numerical Respondent enters number Metric data Specify unit of measure Categorical Respondent selects category or grouping Nominal or ordinal data All-inclusive Mutually exclusive Form meaningful clusters Sufficiently narrow or broad © 2017 American Health Information Management Association 17 Attributes of Items (cont.) Scales: Form of categorical item that uses progressive categories, such as size, amount, importance, rank, or agreement Scale Points (2, 3, 4, 5-verbal frequency, 7-expanded Likert) Likert scale (5-point) Reliability improves from 2 to 7, but then improvement trivial Semantic differential scale Perspectives and images Words that are polar opposites on ends of continua © 2017 American Health Information Management Association 18 Attributes of Items (cont.) Standardized categories found during literature review or obtained from authoritative sources Races, age groups, and other subpopulations Allow comparisons to other researchers’ results © 2017 American Health Information Management Association 19 Attributes of Items (cont.) Feasible logistics Public domain items can be copied and used freely Proprietary items must be purchased and cannot be copied Hidden costs Scoring Users manual or scoring guide © 2017 American Health Information Management Association 20 Examples of Instruments Used in Health Informatics and HIM System Usability Score (SUS) Software Usability Measurement Inventory (SUMI) Questionnaire for User Interaction Satisfaction (QUIS) © 2017 American Health Information Management Association 21 Techniques and Tools of Data Collection Survey: Systematic collection of self-report data through interviews or questionnaires Census survey: All members of the population Sample survey: Representative members of the population Observation: Collection of data by noting and recording Tools developed prior to use Transcription prior to coding and analysis Rich data Saturation © 2017 American Health Information Management Association Techniques and Tools of Data Collection (cont.) Elicitation: Collecting data by evoking, bringing out, or drawing out through interview or review of documents Purpose of obtaining unarticulated or tacit knowledge is what classifies a technique as elicitation Uncover informants’ unarticulated knowledge Used to obtain users’ and experts’ views © 2017 American Health Information Management Association Techniques and Tools of Data Collection (cont.) Data sources Primary Secondary Data access Approval or permission Individual or aggregate data Public or proprietary data Location of data Data mining: use of various analytical tools to discover new facts, valid patterns, and relevant relationships in large databases © 2017 American Health Information Management Association 24 Target Population, Sample, and Sampling Target population: Set of individuals (or objects) of interest to the researchers Sample: Set of units, such as portion of a target population Sampling: Process of selecting the units to represent the target population Sampling frame Coverage error Sampling error © 2017 American Health Information Management Association Methods of Sampling Random sampling Quantitative Unbiased selection of subjects from target population in which all members have equal and independent chance of being selected Underpins many statistical tests Nonrandom sampling Qualitative No use of statistical methods of probability to select samples No equal or independent chance of selection © 2017 American Health Information Management Association 26 Types of Samples RANDOM NONRANDOM Simple Convenience* Stratified Purposive Systematic Snowball Cluster Quota Theoretical *Also sometimes used in quantitative research studies © 2017 American Health Information Management Association 27 Sample Size and Sample Size Calculation Sample size Number of subjects determined by researcher to be included in order to represent the population Should be large enough to support statistical tests Sample size calculation Quantitative and qualitative procedures to estimate the appropriate sample size Best guess Considerations Purpose Relationships among level of significance, power, effect size, statistical test, and sample size Information about target population Others © 2017 American Health Information Management Association 28 Response Rate Response rate: Number of people who completed or interviewed divided by total number of people in the sample Adequacy of response rate Review literature for typical response rates and factors affecting response rates Mixed mode approach Response bias: Systematic difference between responders and nonresponders © 2017 American Health Information Management Association Data Collection Procedures Data collection procedures common to both quantitative studies and qualitative studies Approvals of oversight committees Training and testing Pilot study Assembling and storing data © 2017 American Health Information Management Association Review Selecting the appropriate research design and method increase the likelihood that the data collected are relevant, high quality, and directly related to the research question Factors in selecting a research design and method include purpose, internal and external validity, and others Supporting the quality of the data and the study’s results are the processes of data collection, planning, selecting an instrument, determining techniques and tools, deciding upon a sampling strategy and sample, performing pre-collection procedures, and collecting data An instrument is a standardized, uniform way to collect data Factors in selecting an instrument are its validity and reliability of which there are multiple, the researcher’s purpose, and others Techniques and tools of data collection vary by the method Random sampling and nonrandom sampling are methods of sampling and several types of samples exist Procedures associated with collecting data should be taken into account © 2017 American Health Information Management Association