i am working on a task. i need assistance. My topic is analyzing the impact of EHR (Electronic Health Records) on healthcare quality, safety and efficiency. i have my research questions and hypothesis. now i need the datasets for data description and data visualization.
Abstract
This proposal outlines an investigation into the ramifications of implementing Electronic
Health Record (EHR) systems regarding delivering high quality healthcare; specifically
analyzing effects pertaining to patient safety standards, documentation accuracy
completeness and timeliness as well as overall efficiency measures. Our methodology entails
collecting information through secondary data sources such as medical and administrative
databases alongside surveys conducted regarding staff experiences with post implementation
periods – including any potential benefits or drawbacks experienced. Our approach includes
statistical techniques such as regression analysis or hypothesis testing which will offer
insights into possible relationships between EHR implementation and healthcare outcomes.
This study has the potential to add significant value to current knowledge bases within health
informatics and help in supporting decision makers worldwide towards EHR adoption with
informed understandings of effects on various aspects of care delivery. This research adds to
the body of healthcare informatics literature by drawing on publicly accessible secondary
data to examine the influence of EHR systems on vital components of healthcare delivery.
Keywords: Electronic Healthcare Record Systems, Healthcare Delivery, Patient Safety,
Healthcare Quality, Healthcare Efficiency
Introduction
By offering digital platforms for securely storing, managing, and distributing patient
data, the implementation of EHR systems has radically altered the healthcare context.
Improved documentation accuracy, augmented patient safety, and augmented operational
efficiency are some potential advantages of EHR systems (Lavin et al., 2015). As more
healthcare organizations adopt EHR systems, it is vital to scrutinize their influence on
healthcare quality, patient safety, and efficiency. Gaining insights into these effects is
crucial for smart decision-making, facilitating superior healthcare outcomes, and
optimizing patient care.
The shift from conventional paper-based medical records to electronic health
record systems has been motivated by the acknowledgement that EHR systems possess the
capability to transform the delivery and management of healthcare (Aguirre et al., 2019). The process
of digitizing patient records enables healthcare practitioners to promptly retrieve extensive
patient data, thereby enhancing the precision of diagnoses, treatment choices, and care
management (Wheatley, 2013). Electronic Health Record systems offer advantages that go beyond
individual patient visits. They facilitate the smooth exchange of data across various
healthcare environments, guaranteeing consistency of care and minimizing the likelihood of
medical errors that may result from inadequate or disjointed information.
The primary rationale behind the analysis of the influence of Electronic Health
Record systems on healthcare quality is to guarantee precise and comprehensive
documentation. The absence of precise or comprehensive documentation can result in grave
implications for the provision of healthcare to patients, such as medical inaccuracies,
postponed diagnoses, and jeopardized patient welfare. According to Evans (2016), Electronic
Health Record systems have the potential to improve documentation accuracy by reducing
errors resulting from illegible handwriting, lost or misplaced records, and incomplete data.
Examining how the adoption of EHRs has affected documentation accuracy enables
healthcare providers to better target their resources and develop strategies for delivering
better care.
In addition, the promptness of documentation plays a crucial role in guaranteeing
effective and synchronized provision of care. The prompt and efficient retrieval of patient
data is a critical component for healthcare practitioners to make well-informed judgments,
administer suitable therapies, and effectively track patient advancement (Adane, 2019).
Electronic Health Record systems facilitate instantaneous retrieval and updating of patient
data, thereby enabling healthcare providers to access real-time information (Wheatley, 2013). The
implementation of technology in healthcare not only optimizes the speed and effectiveness of
medical procedures, but also facilitates expeditious correspondence between healthcare
professionals, resulting in enhanced patient results and diminished healthcare expenditures.
The adoption of electronic health record systems presents favorable prospects for
augmenting patient safety and mitigating the incidence of avoidable harm. Electronic health
record systems offer a range of features, including medication reconciliation, tools for
decision-support, and clinical alerts, that can assist medical professionals in making more
educated and safer decisions (Lindén-Lahti et al., 2022). Health care facilities may determine
areas where electronic health record systems have significantly improved patient safety by
studying the impact of EHR deployment on medication mistakes, negative outcomes, and
hospital-acquired infections. They may then create plans to tackle any unresolved problems
or risks.
Influence Of Electronic Health Record Systems on Healthcare Workflow and
Productivity
The effective adoption of Electronic Health Record systems within healthcare
establishments holds the capacity to optimize operational processes, elevate output, and
augment overall efficacy. Electronic Health Record systems provide a range of capabilities
and characteristics that mechanize and digitalize diverse administrative and clinical duties,
thereby diminishing the dependence on manual and paper-oriented procedures (Aguirre et al.,
2019). Comprehending the effects of electronic health record implementation on healthcare
processes and productivity is of paramount importance for healthcare entities seeking to
enhance their operational efficiency and provide superior patient care.
Optimizing Administrative Processes
Appointment scheduling, invoicing, and the filing of insurance claims may all be
handled more efficiently with the help of an electronic health record system. These systems
offer centralized databases for the storage of patient data, thereby negating the need for input
of data manually and diminishing the probability of errors (Ehrenstein et al., 2018). The
automation of administrative tasks within healthcare organizations has the potential to
optimize workflows, enhance resource allocation, and boost productivity. Electronic Health
Record systems facilitate the process of appointment scheduling by enabling healthcare
providers to access and review available time slots, reserve appointments, and dispatch
automated notifications to patients. The implementation of an automated appointment
scheduling system alleviates the task of manual schedule management and mitigates the
potential for scheduling conflicts or overlooked appointments (Howard et al., 2020).
Furthermore, faster and accurate billing procedures are made possible by the connection of
EHR systems with billing and claims processing activities. Billing forms automatically
include patient information, saving time and effort by eliminating the need for human data
input. EHR systems also offer capabilities for verifying insurance coverage and submitting
claims, minimizing paperwork and speeding up payment procedures.
Optimization of Data Retrieval and Information Sharing Processes
EHR systems facilitate the expedient retrieval of data and the sharing of information
among medical professionals, resulting in increased productivity and work efficiency. In the
past, healthcare practitioners were dependent on tangible paper charts or the transmission of
documents via facsimile for the purpose of exchanging information (Evans, 2016). Electronic
health record systems make patient information easily available at the point of treatment,
doing away with the need for manual searches while also cutting down on time wasted.
By utilizing modern technology, medical practitioners are able to swiftly retrieve
comprehensive medical records, laboratory findings, and radiographic assessments,
facilitating prompt clinical decision-making and optimizing operational productivity.
Electronic health record systems provide extensive search functionalities, enabling healthcare
professionals to swiftly access particular data or monitor changes in patient status throughout
the course of treatment (Quinn et al., 2019). The prompt availability of patient information
empowers healthcare practitioners to make informed judgments, devise therapeutic strategies,
and deliver prompt interventions.
In addition, electronic health record systems facilitate the secure exchange of patient
data among various healthcare settings, thereby promoting efficient care coordination and
mitigating communication barriers. In the past, the exchange of patient records among
healthcare providers necessitated laborious procedures, such as transmitting physical records
via facsimile or postal mail (Ajami & Bagheri-Tadi, 2013). Electronic health records systems
facilitate the electronic interchange of patient data, making it accessible to authorized
healthcare professionals (Ajami & Bagheri-Tadi, 2013). The optimization of information
sharing facilitates effective communication, minimizes redundant testing, and amplifies
workflow
efficiency
in
diverse
healthcare
environments,
including
medical
centers, pharmacies, and, hospitals.
Workflow Integration and Clinical Decision Support
Electronic Health Record systems frequently integrate clinical decision support
mechanisms that offer healthcare providers real-time notifications, prompts, and evidencebased recommendations (Lavin et al., 2015). The utilization of these tools facilitates the
process of clinical decision-making and increases the efficacy of workflow (Sutton et al.,
2020). Medication-related adverse events may be avoided, for instance, if electronic health
record systems are used to highlight the possibility of drug interactions, allergies, or dosing
mistakes.
The EHR’s built-in clinical decision support capabilities examine the patient’s medical
history, including their prescriptions, allergies, and diseases, and then provide warnings or
suggestions based on these analyses. These cautions might be anything from reminders about
preventative screenings or vaccines to warnings about interactions between medications
(Sutton et al., 2020). By incorporating decision support tools into electronic health record
systems, medical professionals are able to make choices that are better informed, hence
lowering the risk of making errors and increasing the possibility that patients will be safe.
Electronic Health Record systems have the capability to enhance workflow
integration by establishing connections among different departments and healthcare
practitioners who are engaged in providing patient care. When a physician requests
laboratory tests using an EHR system, for example, the request is transmitted electronically to
the laboratory. This eliminates the requirement for manual order input and reduces the
amount of time it takes to complete the tests (Wheatley, 2013). The findings are subsequently
sent in a computerized way to the EHR system, where they are made immediately available
to the physician who placed the prescription. The integration of various care teams results in
a reduction of time and effort needed for coordination and communication, leading to
streamlined workflows and increased productivity (Wheatley, 2013).
Workforce Productivity and Job Satisfaction
Healthcare workers’ levels of job satisfaction and productivity may change with the
introduction of electronic health record systems. Medical professionals generally report more
work satisfaction and less administrative stress after mastering electronic health records,
despite the fact that the switch from paper-based systems sometimes need training and
adjustment periods (Ajami, 2013). Electronic health record systems have the potential to
streamline documentation procedures through the provision of drop-down menus,
templates, and voice recognition functionalities, thereby facilitating accelerated and precise
documentation. As opposed to using handwritten or transcribed information, healthcare
personnel may immediately enter patient interactions into the EHR system, eliminating the
risk of mistakes caused by handwriting that is indecipherable or missing information (Evans,
2016). In addition, electronic health record systems come with features like copy-and-paste
and auto-fill, both of which help to simplify paperwork even more and save time.
In addition, electronic health record systems allow for quicker data retrieval, since they
do away with the need to physically find documents or sift through piles of paper charts. The
ability for medical professionals to swiftly access patient information, go through patients’
medical histories, and evaluate test results enables them to make more effective clinical
decisions (Manca, 2015). The provision of instantaneous data additionally facilitates
enhanced communication and collaboration amongst healthcare teams, thereby promoting
synchronized patient care.
The aforementioned factors are conducive to enhanced job satisfaction, as healthcare
professionals are able to allocate more attention towards patient care and minimize the
amount of time dedicated to administrative duties. The alleviation of paperwork and
administrative duties enables healthcare practitioners to devote additional time and focus to
face-to-face patient engagements, improving their sense of fulfillment and purpose (Barello et
al., 2015). Improved satisfaction with work, in turn, may boost employee productivity,
resulting in higher-quality treatment for patients and improved medical results.
Influence of Electronic Health Record Systems on Patient Safety and Quality of Care
The adoption of Electronic Health Record systems within healthcare institutions has
resulted in notable progressions in patient safety and the general standard of care. EHR
systems include features and functions that help with timely and accurate documentation,
better drug control, fewer adverse events, and improved provider communication (Evans,
2016). Comprehending the effects of EHR implementation on the safety of patients and care
quality is imperative for healthcare institutions seeking to improve patient outcomes and
establish a safe environment for care.
Improved Medication Administration
EHR systems are essential for enhancing drug administration and minimizing
pharmaceutical errors, which may have detrimental effects on patient safety. Healthcare
practitioners may electronically prescribe pharmaceuticals using EHR systems, eliminating
the dependence on handwritten prescriptions, which are prone to mistakes (Porterfield, et al., 2015).
The incorporation of e-prescribing functionalities in electronic health record systems is
accompanied by inherent safety protocols, including drug-drug interaction notifications,
allergy advisories, and dosage suggestions, that facilitate the informed decision-making of
healthcare practitioners in the course of prescribing medication.
In addition, electronic health record systems enable precise reconciliation of
medication through the provision of a comprehensive overview of a patient’s medication
history, encompassing present medications, previous prescription drugs, and drug allergies
(Gildon et al., 2019). This data assists healthcare professionals in verifying the suitability of
prescribed medications, preventing redundancy, and reducing the likelihood of negative drug
responses. EHR systems improve patient safety and the provision of high-quality care by
lowering medication mistakes and managing medications better.
Reduced Adverse Events and Infections Acquired in Hospitals
The adoption of electronic health record systems has demonstrated potential in
mitigating the incidence of unfavorable incidents and nosocomial infections, thereby
enhancing patient safety. Electronic Health Record systems facilitate healthcare providers’
access to current patient data, such as laboratory findings, diagnostic assessments, and vital
signs, during the provision of care (Ehrenstein et al., 2019). The swift availability of crucial
patient information enables healthcare practitioners to make well-informed decisions rapidly,
resulting in the prompt detection and intervention of declining patient conditions.
Furthermore, EHR systems include clinical decision support technologies that give
healthcare practitioners with real-time alerts and reminders. These alerts may let medical
professionals know about possible safety hazards including allergies, contraindications, or
unexpected test results, allowing for prompt attention and the right course of action (Lavin et
al., 2015). The integration of clinical decision support into electronic health record systems
enables healthcare organizations to enhance patient safety by reducing the number of adverse
occurrences that may have been avoided.
EHR systems can enhance care coordination by improving communication between
healthcare providers. Healthcare providers have the ability to electronically exchange patient
data, such as treatment plans, notes on progress, and summaries of discharge, to facilitate
comprehensive and collaborative care delivery involving all pertinent stakeholders (LindénLahti et al., 2022). This all-encompassing and well-coordinated approach to patient care
decreases the risk of making mistakes, boosts patient safety, and increases the quality of
treatment as a whole.
This research uses electronic healthcare records datasets from Kaggle, the UCI
Machine Learning Repository, and the Harvard Dataverse databases to examine the effects of
deploying Electronic Health Record systems on the quality of healthcare, safety for patients,
and efficiency. The EHR datasets should contain an exhaustive compilation of electronic
medical records from a variety of healthcare facilities. It consists of the patient’s demographic
information as well as their medical diagnoses, treatments, test findings, prescription records,
and any other pertinent information that has been documented inside EHR systems. This
dataset is a valuable source of data that may be used to investigate the links between the
implementation of EHR systems and the results of healthcare.
Research Questions:
Using the datasets obtained, this study aims to examine the following questions:
1. How does the implementation of EHR systems affect the overall quality of healthcare
services provided, including the accuracy, completeness, and timeliness of documentation?
2. What are the specific improvements in patient safety observed after the adoption of EHR
systems, such as reductions in medication errors, adverse events, or hospital-acquired
infections?
3. How does the implementation of EHR systems impact healthcare efficiency measures,
such as the time spent on documentation, patient wait times, or resource utilization?
4. What are the perceived benefits and drawbacks reported by healthcare providers following
the implementation of EHR systems, and how do they influence workflow, productivity, and
job satisfaction?
Methods
Through use of descriptive analysis, inferential statistics and regression modelling
methods, this research seeks an elaborate understanding concerning how implementing
Electronic Health Record impacts various aspects within healthcare delivery such as quality,
patient safety, and efficiency. Datasets derived from sources like Kaggle, Harvard Dataverse,
and UCI Machine Learning Repository provide essential details concerning patient histories
inclusive but not limited to medication records, laboratory results and other relevant details.
Data
The present investigation will acquire the requisite data from the designated data set
from the EHR, which is accessible on Kaggle, Harvard Dataverse, and UCI Machine
Learning Repository. The electronic healthcare records in this collection, which come from
multiple healthcare institutions, include in-depth data on demographics of patients, health
diagnoses, treatments, test findings, prescription records, and other pertinent factors. The data
set will include a large number of patient records, enabling for a thorough examination of the
effect of EHR deployment on healthcare quality, safety for patients, and efficiency.
Predictors
The present investigation will center on the determinants pertaining to EHR systems
implementation. The potential determinants of EHR system adoption may encompass factors
such as the implementation timeline, the extent of EHR system employment, and
supplementary attributes or capabilities incorporated into the systems (Aguirre et al., 2019).
Additional factors that may serve as predictors include the degree of training and support
afforded to healthcare personnel during the implementation phase, the level of
interoperability among various electronic health record systems, and the general preparedness
of healthcare organizations to adopt EHRs.
Outcome
The quality of medical treatment, the safety of patients, and how efficiently resources
are used are going to be the key focus measures of this study. The evaluation of these
outcomes will be conducted through the utilization of diverse indicators, including but not
limited to preciseness, comprehensiveness, and documentation timeliness, to gauge the
quality of care delivered. Medication mistakes, adverse events, and hospital-acquired
infections will be examined to determine patient safety improvements. The efficiency metrics
will prioritize factors such as the duration of documentation, the duration of patient wait
times, and the utilization of resources. Furthermore, secondary outcome measures like the
perceived advantages and negative aspects indicated by healthcare personnel, such as
productivity, workflow, and job satisfaction, will be taken into consideration.
Data Analytic Plan
For the purpose of this investigation, we will do an analysis of the data that combines
descriptive analysis, inferential statistical modeling, and regression modeling. The utilization
of descriptive statistics is intended to provide a summary of the dataset’s features,
encompassing the variables distribution and measures of summary. The study will employ
inferential statistics, specifically chi-square tests and t-tests, to analyze the associations
between the implementation of electronic health record systems and the resultant variables
related to healthcare efficiency, quality, and safety for patients. Regression modeling, which
accounts for possible confounding variables, will be used to evaluate the relationships
between the determinant variables (EHR implementation factors) and the variables that
determine the outcome.
In order to guarantee the reliability of the outcomes, proper statistical methods will be
used, taking into account the characteristics of the variables and the inquiries posed by the
study. The potential for EHR implementation’s effects to vary among populations or
environments may be investigated using sensitivity and subgroup studies. A determination
will be made on the statistical significance of the relationships as well as the size of the
effects, and any assumptions or limitations regarding the research will be evaluated and
explained.
References
Adane, K., Gizachew, M., & Kendie, S. (2019). The role of medical data in efficient patient
care delivery: a review. Risk Management and Healthcare Policy, 67-73.
Aguirre, R. R., Suarez, O., Fuentes, M., & Sanchez-Gonzalez, M. A. (2019). Electronic
health record implementation: a review of resources and tools. Cureus, 11(9).
Ajami, S., & Bagheri-Tadi, T. (2013). Barriers for adopting electronic health records (EHRs)
by physicians. Acta Informatica Medica, 21(2), 129.
Barello, S., Triberti, S., Graffigna, G., Libreri, C., Serino, S., Hibbard, J., & Riva, G. (2016).
eHealth for patient engagement: a systematic review. Frontiers in psychology, 6, 2013.
Ehrenstein, V., Kharrazi, H., Lehmann, H., & Taylor, C. O. (2019). Obtaining data from
electronic health records. In Tools and technologies for registry interoperability,
registries for evaluating patient outcomes: A user’s guide, 3rd edition, Addendum 2
[Internet]. Agency for Healthcare Research and Quality (US).
Evans, R. S. (2016). Electronic health records: then, now, and in the future. Yearbook of
medical informatics, 25(S 01), S48-S61.
Gildon, B. L., Condren, M., & Hughes, C. C. (2019, April). Impact of electronic health
record systems on prescribing errors in pediatric clinics. In Healthcare (Vol. 7, No. 2, p.
57). MDPI.
Howard, F. M., Gao, C. A., & Sankey, C. (2020). Implementation of an automated
scheduling tool improves schedule quality and resident satisfaction. Plos one, 15(8),
e0236952.
Lavin, M. A., Harper, E., & Barr, N. (2015). Health information technology, patient safety,
and professional nursing care documentation in acute care settings. Online Journal of
Issues in Nursing, 20(2).
Lindén-Lahti, C., Kivivuori, S. M., Lehtonen, L., & Schepel, L. (2022, May). Implementing a
new electronic health record system in a university hospital: the effect on reported
medication errors. In Healthcare (Vol. 10, No. 6, p. 1020). MDPI.
Manca, D. P. (2015). Do electronic medical records improve quality of care?: Yes. Canadian
Family Physician, 61(10), 846-847.
Porterfield, A., Engelbert, K., & Coustasse, A. (2014). Electronic prescribing: improving the
efficiency and accuracy of prescribing in the ambulatory care setting. Perspectives in
health information management, 11(Spring).
Quinn, M., Forman, J., Harrod, M., Winter, S., Fowler, K. E., Krein, S. L., … & Chopra, V.
(2019). Electronic health records, communication, and data sharing: challenges and
opportunities for improving the diagnostic process. Diagnosis, 6(3), 241-248.
Sutton, R. T., Pincock, D., Baumgart, D. C., Sadowski, D. C., Fedorak, R. N., & Kroeker, K.
I. (2020). An overview of clinical decision support systems: benefits, risks, and
strategies for success. NPJ digital medicine, 3(1), 17.
Wheatley, B. (2013). Transforming care delivery through health information technology. The
Permanente Journal, 17(1), 81.
Title: Analyzing the Impact of Implementing EHR Systems on Healthcare Quality,
Patient Safety, and Efficiency
Short Title: Impact of EHR Systems
Pranitha Pittala
PPittala@my.harrisburgu.edu
Harrisburg University of Science and Technology
Analyzing the impact of electronic health record (EHR) systems can involve various
aspects, such as patient outcomes, healthcare provider efficiency, cost-effectiveness,
and overall quality of care. While I cannot provide you with specific datasets, I can
suggest some potential sources where you can explore and access relevant datasets
for your analysis:
1. Healthdata.gov: This U.S. government website provides a wide range of
health-related datasets, including EHR-related data. You can search for
datasets related to EHR systems and their impact on healthcare outcomes.
2. Research Data Assistance Center (ResDAC): ResDAC provides access to various
Medicare and Medicaid datasets. These datasets may include EHR data, which
can be used to analyze the impact of EHR systems on healthcare utilization,
costs, and quality.
“Analyzing the impact of implementing EHR systems on healthcare quality,
patient safety, and efficiency.”
Research Questions:
• How does the implementation of EHR systems affect the overall quality
of healthcare services provided, including accuracy, completeness, and
timeliness of documentation?
• What are the specific patient safety improvements observed after the
adoption of EHR systems, such as reductions in medication errors,
adverse events, or hospital-acquired infections?
• How does the implementation of EHR systems impact healthcare
efficiency measures, such as time spent on documentation, patient wait
times, or resource utilization?
• What are the perceived benefits and drawbacks reported by healthcare
providers following the implementation of EHR systems, and how do
they affect workflow, productivity, and job satisfaction?
• Hypothesis 1: There is a positive correlation between the implementation
of Electronic Health Record systems in healthcare organizations and
healthcare quality.
• Hypothesis 2: The implementation of EHR systems improves patient
safety in healthcare settings.
• Hypothesis 3: The adoption of EHR systems in healthcare delivery
positively impacts efficiency by streamlining administrative tasks,
reducing paperwork, and eliminating duplicate data entry.
• Hypothesis 4: The successful implementation of EHR systems is
influenced by several factors, including organizational readiness,
adequate training and support for healthcare professionals, effective
change management strategies, and interoperability between different
EHR systems.
Data Description:
Update your Methods section (particularly the Data subsection).
◦Detail any processing steps used for the data
◦Cleaning steps (e.g. cleaning text data, transforming variables) should go in Data
Analytic Plan subsection
◦Include summary statistics and concrete details about the data
Data Visualization:
Construct at least one table or figure for your project and list the tables and figures you plan
to include in your final paper. Your list may change but consider now what parts of your
project would benefit from a visualization. You can either insert these in your paper and
submit that or use a Word document to just submit your visualization and list.
Methods Section Revision
This assignment is part of an unpublished module and is not available yet.
Results Section Draft
This assignment is part of an unpublished module and is not available yet.
Discussion Section Draft
This assignment is part of an unpublished module and is not available yet.
Abstract Draft
This assignment is part of an unpublished module and is not available yet.
Final Project
—
title : “The title”
shorttitle : “Title”
author:
– name : “First Author”
affiliation : “1”
corresponding : yes
address : “Postal address”
email : “my@email.com”
affiliation:
– id : “1”
institution : “Harrisburg University of Science and Technology”
authornote: |
Add complete departmental affiliations for each author here. Each new line herein must be indented, like this line.
Enter author note here.
abstract: |
blahblahblah
keywords : “keywords”
wordcount : “X”
bibliography : [“Bibliography.bib”]
figsintext : yes
figurelist : no
tablelist : no
footnotelist : no
lineno : yes
lang : “english”
class : “man”
output : papaja::apa6_pdf
citation_package : biblatex
nocite : |
@*
—
“`{r setup, include = FALSE}
library(“papaja”)
library(“knitr”)
r_refs(“Bibliography.bib”)
“`
***Instructions for Troubleshooting Code [DELETE INSTRUCTIONS AFTER]***
If problems knitting, try these solutions in order:
1. Run in console: tinytex::install_tinytex()
2. Download: https://miktex.org/download
3. Run in console: devtools::install_github(“crsh/papaja@devel”)
***Instructions for Troubleshooting Code [DELETE INSTRUCTIONS AFTER]***
Introduction paragraph. [Introduce topic, why is it important, why should your reader care]. The goal of this project is …
## Subheading 1
## Subheading 2
The purpose of this study is … Using data X, I address the following research questions by …
H1:
H2:
# Methods
## Data
## Predictors
## Outcome
## Data Analytic Plan
# Results
# Discussion
\newpage
# References
\setlength{\parindent}{-0.5in}
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Formatting
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