Lead Analyst's Challenge: Persuading Stakeholders With Data - Free Report Example

Introduction

The lead analysts at the St. Anthony medical hospital has been contacted and given the responsibility of preparing a presentation that persuades the stakeholders to buy-in. It is, however, essential to note although the organization stakeholders have a considerable influence concerning the future of the company, they often face a challenge in determining which data is pertinent to the success of the organization or in what way to utilize it (Davenport, 2013). Therefore, it is the core responsibility of the data analyst to assess this information while breaking it down into simpler, understandable, and usable information that can be used in the success of the organization. The hospital-acquired condition program HAC is described as the Medicare pay for performance scheme that is used by the states to support the healthcare facilities offering both Medicaid as well as Medicare services (Sheetz et al., 2019).

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AHRQ Quality Indicators

Both the inpatients and the outpatients are based on the evidence presented in the quality indicators and therefore, can be used in assessing the variations in the quality of care that they receive. Additionally, there are approximately four models that are utilized in the quality measurement, including “the prevention quality indicators, the inpatient quality indicator, the patient, safety indicators as well as the pediatric quality indicators as stated in the” “AHRQ Quality Indicators Fact Sheet.”

The Prevention Quality Indicators (PQI’s)

The prevention quality indicators describe the current states of the hospital to evaluate the health care system as but more comprehensively on the ambulatory care structure. For instance, in the prevention of medical complications from the acute as well as chronic ailments. The prevention quality indicators play a vital role in helping the care providers tasked with the responsibility of health concerns for a particular population (Ronda, 2008). Therefore, a comparison across local communities, states, and regions is made through employment of the PQI’s, and thus, the hospital quality is not included in the comparison.

The Inpatient Quality Indicators

The inpatient quality indicators or the (IQIs) are a total of 28 provider-level procedures that were established by “the Agency for Healthcare Research and Quality”, and they employ the data from the hospital administration to paint a clear picture of the value of healthcare offered in a healthcare facility for all adults as stated in the “AHRQ Quality Indicators Fact Sheet.”

Patient Safety Indicators

Patient Safety Indicators are an approximation of 20 pointers in inclusion 19 provider-level gauges that are developed by “the Agency for Healthcare Research and Quality”, and offer data on the safety-related hostile situations happening in the health facility resulting from procedures like operations as well as childbirth as stated in the “AHRQ Quality Indicators Fact Sheet.” The PSI employs administrative information from the regular hospitalization and discharges records to assess any potential hospital complications.

The Analysis

Histogram

Histography was developed from the hospital-acquired data. The histogram showed that the present actions of HAC rates would be approximated to be 106 -124. this means that the rates of the diseases acquired from the patients in the hospital is relatively high.

Correlation

To examine the similarities between all of the four variables, a correlation matrix was employed. the results were as follows:

The number of hours that a nurse spent on a patient daily indicated a negative correlation with the hospital-acquired conditions (r= - 0.799)

Similarly, a Skill mix showed a negative correlation as well as recorded at r =-0.305

On the contrary, the average length of time that the patient spent in the hospital showed a positive correlation to the HAC recorded at r= 0.417

Linear Regression

From the analysis, it can be observed that the nursing hours per day, as well as the skill mix correlated to decrease the hospital, acquired conditions rates. The R-square was recorded at 0.6443, which translated to 64.43% of the variance in HAC rates, which was assessed through the HPPD and skill mix. Therefore, it can be concluded that the model was statistically significant.

Summary Narration

The HAC rates = 109.81 – 4.16 model was used in this case. The nursing HPPD + 0.041 skills mix. from the analysis, it was observed that the skill mix had an upward effect on the rates of HAC with an increase of 0.41. it is also evident that the nursing HPPD was significantly feasible with at (92) = -11.94 and p = .000. Therefore, the nursing HPPD was very helpful in decreasing the HAC rates. Thus, from the data, it is recommended that the hospital should increase its qualified staffing by this it means that the nursing staff should be increase since they help in the reduction of the hospital-acquired conditions. Additionally, the effect of HAC rates was assessed by the use of the linear regression, and the model was statistically feasible as well compared to the null model.

Conclusion

Thus, the HAC decrease scheme requires that the secretary of health as to regulate reimbursement to healthcare facilities that are ranked in the poorly performing category following the measures of the HAC quality assessment. In regard to this, a statistical evaluation has been done to determine the factors that influence the hospital-acquired ailments. The data considered in determining the causes as well as the awaits to improve on the HAC include the nursing hours per patient per day, staffing levels, nursing skill mix, the average length of stay in the hospital per patient, and hospital efficiency.

References

AHRQ Quality Indicators Fact Sheet. (n.d.). Retrieved August 8, 2020, from https://www.ahrq.gov/sites/default/files/wysiwyg/professionals/systems/hospital/qitoolkit/complete_qitoolkit.pdf

Sheetz, K. H., Dimick, J. B., Englesbe, M. J., & Ryan, A. M. (2019). Hospital-Acquired Condition Reduction Program Is Not Associated with Additional Patient Safety Improvement. Health Affairs, 38(11), 1858-1865.

Davenport, T. H. (2013, June 18). Data is worthless if you don’t communicate it. Harvard Business Review Digital Articles, 2–3.

Ronda, G.H. (2008). Patient Safety and Quality: An Evidence-Based Handbook for Nurses. Retrieved August 08, 2020, from
https://pubmed.ncbi.nlm.nih.gov/21328752/