Question:
Answer:
MS Access Form for Collecting monitoring and analyzing data for physicians’ reappointment to the medical staff of a general hospital
Q 2. Assessing Quality of Medical Records for 20 Patients
The proposed tool to be used is audit where audits on key indices for data will be measured to establish a baseline and then follow up audits undertaken in subsequent periods and the percentage changes recorded. The audits are proposed to be undertaken quarterly using the tool shown below;
| Yes | No | Not Applicable | Total | |||||
| Number | % | Number | % | Number | % | Number | % | |
| Accuracy of names used in AMR records | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Birth Place data | 18 | 90 | 1 | 5 | 1 | 5 | 19 | 95 |
| Ethnicity | 17 | 85 | 3 | 15 | 0 | 0 | 17 | 85 |
| Directive to physician | 19 | 95 | 0 | 0 | 1 | 5 | 20 | 100 |
| Personnel authorizing release | 16 | 80 | 2 | 10 | 2 | 10 | 18 | 90 |
| Description of Discharge Summary | 8 | 40 | 1 | 5 | 11 | 55 | 19 | 95 |
| ID Number of Payor | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Marital Status | 11 | 55 | 3 | 15 | 6 | 30 | 17 | 85 |
| Gender | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Acknowledgement of patient rights | 10 | 50 | 10 | 50 | 0 | 0 | 10 | 50 |
| Occupation | 12 | 60 | 5 | 25 | 3 | 15 | 15 | 75 |
| Tests done | 14 | 70 | 0 | 0 | 6 | 30 | 20 | 100 |
| Diagnosis | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Treatment Plan ID | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Medication reactions noted and considered | 4 | 20 | 8 | 40 | 8 | 40 | 12 | 60 |
| Treatment/ Intervention Given | 19 | 95 | 1 | 5 | 0 | 0 | 19 | 95 |
| Past medical history | 15 | 75 | 4 | 20 | 1 | 5 | 16 | 80 |
| Clinical order with full text | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Care and treatment plan (full text) | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Treatment Plan in text form | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Time and Date of Order | 8 | 40 | 12 | 60 | 0 | 0 | 8 | 40 |
| Provider details | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Universal health patient number | 20 | 100 | 0 | 0 | 0 | 0 | 20 | 100 |
| Religion | 6 | 30 | 14 | 70 | 0 | 0 | 6 | 30 |
| Date of the earliest held entry | 15 | 75 | 0 | 0 | 5 | 25 | 20 | 100 |
The overall level of compliance in the 20 medical records evaluated is 91% while non compliance is 9%. The medical records are mostly up to date but three key areas stand out for non compliance; medication reactions consideration had just 60% compliance, yet it is a crucial record in modern clinical management. Many people have had adverse effects because their reactions to medication records are not taken cognizance of. Religious affiliation had the least compliance with 14 records missing this information. In many records (12), the dates were up to date when orders were given but the time not updated or fields left blank.
Click image below to launch PowerPoint
Q3. T Test of Significance
The t value was found to be 8.0000
While the df used was 4\
Standard error of difference was 0.667
Using the t test, the P value obtained was 0.0013 which demonstrates that the level of significance is statistically very high (meaning a very statistically significant) level of satisfaction with the quality of service, based on the survey results. The test of significance was done at 95% levels of confidence
Frequency distribution refers to a table displaying the various outcomes frequency within a sample; every entry within the table contains the count of all the value occurrences count within a specific interval. In this way the distribution of the values found within a sample are summarized (Gravetter et al., 2016).
Pareto Charts
The Pareto chart is an important quality control tool to show cumulative frequency and is useful in showing what problems or issues in quality control are the most significant and should therefore, be given greater focus (Provost & Murray, 2011). The Pareto analysis chart works on the 80/ 20 principle which posits that 80 % of problems are caused by 20% of causes (Martz, 2016).
Satisfaction level with Program
Description of program
How well program fit their needs
Rating of Quality Program
Q 4. Click on Image to launch PPT
Statistics
Gravetter, Frederick J, Wallnau, Larry B., & Forzano, Lori-Ann B. (2016). Essentials of
for the Behavioral Sciences. Cengage Learning.
Martz, E. (2017). When to Use a Pareto Chart | Minitab. Blog.minitab.com. Retrieved 24
November 2017, from http://blog.minitab.com/blog/understanding-statistics/when-to-use-a-pareto-chart
Provost, L. P., & Murray, S. K. (2011). The health care data guide: Learning from data for
improvement. San Francisco, CA: Jossey-Bass.
