Data Analytics for Healthcare Decision Making 4

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Getting Started With Assessment #4: Presenting Statistical Results for Decision Making

Lecture: Presenting Statistical Results for Decision Making Introduction to Case Analysis In this 4th assessment, the statistical data results are provided to you in an Excel spreadsheet. Therefore, you do not need to run statistics, but you do need to review and interpret the ones provided. The Excel spreadsheet tabs:

• Review the statistical output and focus on how it supports the reduction of HACs.

• Select 2–3 key statistics and discuss cost implications for detailed analysis and your presentation, using appropriate charts and tables to enhance clarity and impact.

If you have any questions regarding these notes, please feel free to reach out to me by email or phone. My contact info is located in the announcements. You may also reach out to the course Graduate Assistants (tutors) by scheduling a meeting or submitting a question to “Ask the Graduate Assistant” as needed. Thank you.

Assessment Step by Step

STEP 1. Case Review You must go through the Assessment 4 simulation video, Vila Health: Presenting Statistical Results and then download the Excel spreadsheet with the statistics provided; HAC Analysis [XLSX]. Focus on interpreting statistical data provided to assess and reduce hospital- acquired conditions (HACs). The assessment leverages various statistical techniques learned throughout the course, including descriptive statistics, hypothesis testing, correlation, and regression analysis. Your objective is to determine the best way to reduce HACs with the information provided. Use the data to identify key statistics that highlight cost implications and support your analysis. Utilize charts and tables to enhance clarity and impact in your presentation.

Key Variables and Their Importance

• HAC Rate: This measures the number of hospital-acquired conditions per 1,000 discharges, providing insight into the extent of hospital errors.

• Nursing HPPD: Represents the number of nursing staff hours per patient day, which is a critical measure of nurse staffing levels and their potential impact on HACs.

• Skill Mix: Indicates the percentage of nursing staff hours provided by registered nurses (RNs), reflecting the skill mix of nursing staff and its influence on patient care

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quality. • ALOS: Measures the average length of stay per hospital discharge, which is an

indicator of hospital efficiency and its relationship to HAC rates. Financial Assumptions The dataset includes key financial assumptions that are necessary for understanding the cost implications of HACs:

• Hospital discharges: 10,000 • Nursing cost per year: $72,000 • RN cost per year: $85,000 • LPN cost per year: $52,000 • Hospital cost per inpatient day: $2,600 • Hospital penalty per HAC: $5,700

STEP 2. Statistical Interpretation

• Evaluate Descriptive Statistics: Understand the central tendencies and variability in the data.

• Examine Correlations: Assess the strength and direction of relationships between variables, such as the negative correlation between Nursing HPPD and HAC rates.

• Review Regression Analyses: Interpret the regression output to understand how different variables predict HAC rates and costs. Two regression analyses are provided, each offering insights into different dependent variables.

• Research and Support: Substantiate your analysis with thorough research, referencing current benchmarks and studies related to HAC reduction. Use evidence-based journal articles and primary sources to strengthen your recommendations.

STEP 3. Summarize Your Initial Conclusions This assessment integrates all the statistical techniques you have learned throughout the course. By thoroughly analyzing the provided data and making data-driven recommendations, you will demonstrate your ability to apply statistical analysis to real-world healthcare management challenges. Focus on understanding the relationships between variables and their impact on reducing HACs to make informed and effective recommendations for hospital administration. STEP 4. Critical Thinking: Use the table below as a guide to ensure that you have addressed key issues impacting your hospitals desired outcome of lower HACs and costs.

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SCORING GUIDE COMMENTS OUTLINE

Evaluates the data collection, measurement, and analysis tools and techniques used in the data analysis. Ensures the evaluation is complete, provides significant details, and includes assessment of strengths and limitations.

Review the data assumptions and data., then the charts and statistics provided to determine what they are relaying to you regarding how to reduce Hospital Acquired Conditions (HACs). Which of the statistics (2-3) are worthy of reporting in your presentation and paper?

Introduction What is this case problem? What is your approach to addressing the problem? What might your readers, hospital Leadership, expect to hear in your presentation?

Interprets statistical results used in the data analysis and ensures the interpretation is complete, provides a perceptive and clearly articulated conclusion, and includes assessment of caveats and limitations.

1. What do the case descriptive statistics tell you?

2. What do histograms tell you? 3. What does the correlations

table tell you? 4. What does the regression

analysis results tell you? 5. What does the cost analysis

tell you?

Statistical Results Showcase 2-3 statistics using both visualization [charts, graphs, or tables] and critical to your analysis for your presentation and executive summary.

Presents statistical results used in the data analysis to support a health care recommendation. Ensures the presentation describes how results can help managers support a recommendation and provides significant details and justification for the recommendation.

This study examines the correlation between HACs and three critical nursing metrics: hours per patient day (HPPD), skill mix (RNs vs. LPNs), and average length of stay (ALOS). What assumptions support your interpretation of the data?

Interpretation Interpret the relationship strength and effect on HACs from the assumptions provided for each of your 2-3 chosen metrics and your cost analysis.

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Recommends solution based on results of the data analysis, which includes practical, administration- related implications, is fully justified, and is well supported by scholarly literature.

What assumptions and metrics support your recommendations and action plan?

What are the Administrative Implications for reducing HAC, in regard to HPPD, skill, and Costs?

What benchmarks can you find to support your interpretation and action plan, such as Lawton (2020, AHRQ (2019)?

Action Plan

For this assessment, you have the role of an internal consultant. Therefore, a real-world consultant presents findings and recommendations in that order for an action plan. They will list findings based on highest impact to lowest impact.

Findings Recommendations Conclusion

Uses media and technology to convey ideas and information. Ensures the ideas and information are well organized and coherent and include appropriate tables and visualizations.

Best practice for PowerPoints include key words and phrases, not full sentences. Full sentences go into notes. Well- branded and professional with complete title slide, agenda, core content (2-7 slides), thank you to your audience, Any Questions?; and APA reference slides (s).

Professional, polished, and well branded PowerPoints using best practices.

Presenter notes under each slide, or voice-over-PowerPoint, or video.

Executive summary required.

Writes clearly and concisely. Ensures grammar, mechanics, and APA formatting are error free.

Use evidence-based journal articles, primary sources, and industry benchmarks that may help your presentation’s impact.

All major concepts, statistics, numbers, data supported with scholarly references, APA in-text citations and References.

Course Summary Throughout this course, you have learned to run, interpret, and apply various statistical analyses in your assessments. This summary highlights the statistical techniques that you are now equipped to apply in practical and research settings, enhancing your analytical capabilities in various domains.

A. Quantitative and Descriptive Statistics: You've become proficient in using histograms and other descriptive tools to demonstrate central tendency, variance, mean, median, mode, standard deviation, and skewness.

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B. Hypothesis Testing and P-Values: You have learned how to conduct hypothesis testing, interpret p-values (0.05, 0.01, etc.), and understand their significance, particularly in research requiring a high level of sensitivity, such as studies involving human subjects.

C. Regression Analysis: We explored both linear and multiple regression analysis, focusing on the goodness of fit (ranging from 0 to 1) and the use of coefficients in standard regression formulas for predictive analytics.

D. Correlation Analysis: You've studied how to measure the strength of relationships using correlation coefficients (greater than 0.30, 0.50, 0.70), which are crucial for assessing the feasibility of successful interventions in operational or marketing research.

E. Effect Size: The course also covered how to calculate and interpret effect sizes (small h = 0.2, medium h = 0.5, large h = 0.8) to demonstrate the magnitude of the effect between variables, supporting logical decision-making in business plans and project management.

Case Resource Examples Agency for Healthcare Research and Quality. (2019, January). AHRQ national

scorecard on hospital- acquired conditions updated baseline rates and preliminary results 2014–2017. https://www.ahrq.gov/sites/default/files/wysiwyg/professionals/quality- patient- safety/pfp/hacreport-2019.pdf

Agency for Healthcare Research and Quality. (2010). Methods to estimate the baseline 2010 PFP national hospital-acquired condition rate. https://www.ahrq.gov/sites/default/files/wysiwyg/professionals/quality-patient- safety/pfp/pfphac.pdf

Centers for Medicare and Medicaid. ( n.d.). Hospital-Acquired Condition Reduction Program. https://www.cms.gov/medicare/payment/prospective-payment-systems/acute-inpatient- pps/hospital- acquired-condition-reduction-program-hacrp

Lawton, E. J., Sheetz, K. H., & Ryan, A. M. (2020). Improving the Hospital-Acquired Condition Reduction Program through rulemaking. JAMA Health Forum, 1(5), 1–3. https://doi.org/10.1001/jamahealthforum.2020.0416

Nghiem, S., Afoakwah, C., Scuffham, P., & Byrnes, J. (2021). Benchmarking hospital safety and identifying determinants of hospital-acquired complication: The case of Queensland cardiac linkage longitudinal cohort. Infection Prevention in Practice, 4(1), 1–9. https://doi.org/10.1016/j.infpip.2021.100198