BHA FPX 4106 Assessment Benchmarks and Quality Measures – Diabetes 

Sample Answer for BHA FPX 4106 Assessment Benchmarks and Quality Measures – Diabetes  Included After Question


Step One: Preparation

Locate data related to quality measures relevant to your topic from one or more of these websites:

Step Two: Data Collection

Using the Data Collection Spreadsheet Guide [XLSX] Download Data Collection Spreadsheet Guide [XLSX]as an example, create a spreadsheet containing three tabs: Dashboard Tracking, Data Collection, and Trending.

On the first tab, Dashboard Tracking, draw from the information you gathered in Step One as part of your preparation for this assessment:

  • Identify the specific benchmark data you will compare with your office data. Remember it is up to you to establish your benchmarks.
  • Organize or create a spreadsheet to display the totals, percentages, averages, and so on of your office data and of the national or state data you will be using for comparison. Note: Your Office Data column will be blank because you are not collecting any office data. This is only a proposal to do an information review of the quality of care provided by the physician group. Data does, however, need to appear in the Benchmark (national/state) data column.
  • Include at least one comparison graph of your choice on this tab.
BHA FPX 4106 Assessment Benchmarks and Quality Measures - Diabetes 
BHA FPX 4106 Assessment Benchmarks and Quality Measures – Diabetes 

On the second tab, Data Collectiondraw from the information you gathered in Step One as part of your preparation for this assessment:

  • Create a form you will use to collect specific data from the patients’ records.
  • Include a row for each patient.
  • Provide a column for each data collection point (quality measure) you will be comparing.

Step 3: Data Compatibility

Write a short section to add to the proposal you will complete in Assessment 3. Be sure this section of your proposal includes all of the following headings and your narrative addresses each of the bullet points.


PHI FPX 3200 Assessment 2 A Right to Experimental Drugs?

A Sample Answer For the Assignment: BHA FPX 4106 Assessment Benchmarks and Quality Measures – Diabetes 

Title: BHA FPX 4106 Assessment Benchmarks and Quality Measures – Diabetes  

Data compatibility is a key aspect of data quality as it allows easier data integration, data analysis, and storage. Therefore, it is important for professionals to ensure that their data meet compatibility standards whenever there is a need to use multiple data sets or data obtained from various sources during analysis (Pramanik et al.,2022). Besides, it is important that professionals take into account various methods applied in the data collection and analysis to prevent any problems that may come later, especially when there is a need to integrate data. Therefore, the purpose of this assignment is to explore data compatibility.

Data Compatibility

It is important that the data obtained from external databases be consistent and compatible with the office data. As such, one of the strategies that can be used to ensure that the data from different sources are compatible is to ensure that all the data specifics from these sources are the same. Some of the specifics to be considered include gender and only. The implication is that such compatibility between the external data and office data can be obtained through standardization. One can know whether the data used for comparison is compatible with office data when the same statistical approaches as the office data (Pramanic et al.,2022). There are various challenges associated with standardization. For example, the costs involved in standardization can be huge as huge amounts of money may be needed in its initial stages. It also needs comprehensive coordination from various players and the government.

Effects of Health Information Quality On the HIE

There is always a need to share quality data between various healthcare professionals and players to enhance operations and efficiency for better patient outcomes. Therefore, it is important to use effective strategies to exchange data. Health information exchange refers to the direct sharing of health-related information electronically between authorized individuals (Janakiraman et al.,2023). HIE is different from a national database since a national database is a collection of various health information put in a central place that can be electronically accessed.

Various problems can develop if facilities submit incomplete or inaccurate information to an HIE. One of the potential problems is that such data can negatively impact research as researchers may engage in skewed research, which, again, could lead to inaccurate and erroneous medical practices. Such practices can put patients’ lives in danger. In addition, it can lead to improper procedures, medications, and care (Provost & Murray, 2022). Information sent and placed in the national databases is important. Therefore, various problems may occur if facilities submit incomplete or inaccurate data information to the national database. One of the potential problems is inappropriate decision-making by the national health team. Such teams depend on the data sent to make decisions regarding health and populations; hence inaccurate and incorrect data can easily lead to inappropriate decisions. The national government can also come up with erroneous support recommendations. Another potential problem is that the health team may fail to issue an important alert which they could have done if they accessed accurate and complete data.

Inaccurate and incomplete data may also affect my proposal in several ways. One such way is that it can lead to underbudgeting or overbudgeting. Proposals usually need financial support to succeed; hence complete and accurate data should be used. However, in the absence of such, the budget may exclude vital aspects or include unnecessary information (Provost & Murray, 2022). The proposal can also be rejected by the committee as they may notice inaccurate or incomplete data.


Quality measures play a role in goal setting for better patient outcomes; therefore, they should be known relative to a condition. Sharing data regarding the same is equally important. Therefore, this write-up has explored quality measures, data compatibility, and the importance of accurate and complete data.


Janakiraman, R., Park, E., M. Demirezen, E., & Kumar, S. (2023). The effects of health information exchange access on healthcare quality and efficiency: An empirical investigation. Management Science69(2), 791-811.

 Pramanik, P. K. D., Pal, S., & Mukhopadhyay, M. (2022). Healthcare big data: A comprehensive overview. Research Anthology On Big Data Analytics, Architectures, And Applications, 119–147.

Provost, L. P., & Murray, S. K. (2022). The health care data guide: learning from data for improvement. John Wiley & Sons.