[ANSWERED 2023] You work at a small community-based hospital as a manager in the quality assurance department. One function of your job is to analyze internal data such as medical records

You work at a small community-based hospital as a manager in the quality assurance department. One function of your job is to analyze internal data such as medical records, patient surveys

You work at a small community-based hospital as a manager in the quality assurance department. One function of your job is to analyze internal data such as medical records, patient surveys, and incident reports to track trends and help improve patient care delivery

[ANSWERED 2023] You work at a small community-based hospital as a manager in the quality assurance department. One function of your job is to analyze internal data such as medical records.

You work at a small community-based hospital as a manager in the quality assurance department. One function of your job is to analyze internal data such as medical records, patient surveys, and incident reports to track trends and help improve patient care delivery.

Your supervisor just came back from a seminar on quality benchmarking and has asked about your thoughts on analyzing secondary data from the health care industry as a way to benchmark and measure the organization’s quality performance against its peers. You have been asked to prepare a report on the use of both secondary data and internal data as way to improve quality in your organization. Complete the following:

  • Write a paper comparing and contrasting the collection of secondary data and their uses versus the analysis of current health care records and internal data such as incident reports and patient surveys.
  • Explain how health care organizations use secondary data as a comparison to internal data.
  • Assess the validity and reliability of primary and secondary data in conducting health care research.

>expert answer

Expert Answer and Explanation

Healthcare Information System Management

Benchmarking is one of the recent healthcare trends that is being accepted across many care continuums, where hospitals and departments analyze their competitors so as to find a ground for improvement. Similarly, hospital managers work hard to assess internal data and operations and to try to achieve improvement using these analyses.

Small community-based facility

Some experts refer to the process as internal benchmarking, as the facilities seek to improve their operations against their own set internal standards (Feibert, Andersen, & Jacobsen, 2019). In the analyses of my small community-based facility where my supervisor arrives from a seminar on quality benchmarking, there are several ideas I would help him understand about the use of secondary data to measure the performance of the organization against its peers.

Both benchmarking and internal analyses are important in organizational growth and healthcare managers should focus in the specific strengths of these strategies to efficiently integrate them in healthcare.

Contrasting Secondary Data and Uses with Internal Data and Current Healthcare Records

Benchmarking as a way to set the Quality Standards

Competitive benchmarking involves analyzing the processes of another organization and comparing its operations, goals, and standards with its own. For most small healthcare facilities, it is not easy to achieve growth without comparing their operations with larger and better-performing organizations (Buckmaster & Mouritsen, 2017).

In some of the cases, people in small organizations believe that they are performing efficiently until they perform such benchmarking operations and realize that their peers have set higher standards in care which should be targets for their achievement.

A good example is comparing the wait times that patient have in emergency rooms with those of other emergency rooms in different facilities. In the case where other organizations have generally smaller amounts of time spent in the ER waiting rooms, healthcare givers can borrow information such as the individual elements that help in reducing the wait time.

This could be possibly factors that are present among the staff members such as their ability to be more focused in serving patients or other factors in the system such as the presence of better infrastructure to help serve the patients faster (Gonzalez, 2019). A collection of this kind of data helps the organization to drive the different ways in which they can set improvement strategies internally.

Facility understands

This way, the facility understands the threshold of different elements and standardizes them to be the target-setters in the organizations.

Internal Healthcare Data Helps in Individualized Improvement

While external benchmarking drives the achievement of different societal standards in healthcare, internal healthcare is useful in guiding healthcare managers to perform specific improvement of certain procedures (Purushotham et al., 2018). This is especially the case when a facility is known to have its own principles or strategies of operation which it believes to be effective.

A good example of how internal healthcare data helps in individualized improvement in a healthcare firm is when the facility chooses to break down nursing shifts in unique timelines to try and solve the problem of staff fatigue and burnout.

The problem may be specific for the firm, where its peers do not face the same difficulty, and hence utilizing a technique that is specific to the organization could be the most rational decision in driving improvement in the healthcare facility. Internal data that can be collected to aid in individualized improvement include patient records, administrative data, and healthcare giver reports.

Healthcare Organizations Usage of Secondary Data as a Comparison to Internal Data

Compare internal data elements

Both secondary and internal data is crucial in organizational development and should be integrated into care facilities in a systematic way. One of the ways in which healthcare organizations use secondary data to compare internal data elements is assessing the societal standards by assessing performance among its peers.

It would be useless to perform such analyses without comparison to internal data as it would lead to exaggerations or misplacement of the levels of action by the individual organizations.

Among the advantages of integrating external benchmarking data in the facilities is the fact that it helps the healthcare providers to realize the value of the existing resources and how they can use them to achieve organizational growth. Very often, healthcare managers do not realize that they are endowed with numerous resources and that they have no reason to fail in the delivery of proper patient care.

Unfortunately, problems in organizations make them believe that the organization is insufficient in driving the achievement of various goals of care. A close analysis of what their peers do to achieve the organizational standards they are in could serve a long way in opening their eyes to the resource endowment that is present in the organization.

For example, in some of the healthcare organizations, there are no special operation officers such as surgeons, yet they manage to contract these officers at certain times of the week to accomplish scheduled tasks. It is possible that a facility with such permanently employed officers may not find their true value until they attend benchmarking operations in a firm where these officers are limited.

After such a benchmarking operation, the healthcare managers would possibly advocate for better ways of compensation of such people so as to maintain them as valuable assets for the organization.

>competitive benchmarking data

Competitive benchmarking data also helps to convince members of the management about the achievability of some of the goals in healthcare. While not every healthcare goal is achievable, there are times when people dismiss some goals to improve the firm on the basis that it would not possibly run efficiently to the end.

A good example is the full application of Artificial Intelligence in the management of patients’ condition. Most of the AI systems are capable of assessing the vitals of patients and recommending medications for them just like human physicians. However, the high risk involved often reduces the chances of applying such techniques in practice.

Benchmarking a facility which performs such operations could boost the confidence of the healthcare managers of a healthcare institution, as this would be a conviction that what they thought was too technical can be integrated in the healthcare system and serve efficiently (Brandão et al., 2016). During such a benchmark procedure, they should be careful to assess the challenges of implementation of the system, so as to address them right from the beginning of the set up.

Benchmarking can therefore be a way of bringing out reality in what seemed to be applicable only in the future.

Another key advantage of benchmarking data is that it helps to cultivate the process of standardization in order to achieve well-refined results in care. Most healthcare organizations set their standards of operations based on their healthcare budget and their knowledge or trust of the outcomes from operations.

Giving patient care

With benchmarking data, it becomes easy to have an overview of what other companies believe is standard, and hence allow the organization to rise above its fears in standardization (Hibbert et al., 2020). A good example for such is the assessment of the data that is asked during the triage process when a patient presents to a healthcare institution.

There is always a debate over what should be included in the triage information of patients, and the value of this triage process to the later stages of giving patient care.

When healthcare givers assess what other organization views as crucial in the triage process, it becomes easy to rule out other hypotheses about how to perform the entire process and hence to set a standard for the same. The same standardization can be set in other operations in the facilities that are doing the benchmarking operations.

The Reliability and Validity of Secondary and Primary Data in Performing Research on Healthcare

Both internal and benchmarking data can be used to perform research on healthcare improvement, but some of the situations call for the application of specific data types because of the disadvantages posed by the other. The use of alternate forms of data in such cases could lead to faulty applications and results, and hence there is need for specificity in choosing the type of data to use.

Primary Internal Data is Valid in Organization-level Operations

Some research operations entail internal organization growth, and it is only prudent for the organization managers to use internal data to aid in such practices (Agarwal et al., 2016). This is especially when a comparison with other bigger or smaller organizations could be misleading. In a facility where the emergency department nurses often present their reports to an improvement committee at the end of every month, it would be only right for them to consult internal sources about how they can improve the operations based on the reports.

Organization-level operation

The use of benchmarking data from bigger organizations could provide with a different style of reporting in their ED that could devalue the internal reports, which is not the goal of the benchmarking process. It should be understood that such monthly reporting by the ED nurses in the organization is an organization-level operation that is not a requirement of any state law or hospital standard, and hence the organization should use its internal data to improve it.

External Benchmarking Data is Reliable in Identifying the Strengths and Weaknesses of Facility Operations

Among the biggest values of external benchmarking is that it helps the organization to identify some of the weaknesses that could be deterrents to organization development (Choi, Leite, & de Oliveira, 2018). When a facility, for instance, has too outdated systems that consume time in processing patient information, it becomes hard to achieve the necessary care timelines as there is increased patient delays.

Visiting a better-performing organization with more updated systems could help to identify this weakness and hence help in making recommendations for strategic actions on the same. The weakness of the organization identified in this case would be the absence of updated information systems, and the strategic action from this decision would be research about how to implement better systems to improve organizational growth.

In a similar way, secondary benchmarking data helps facilities to realize some of the strengths they have in realizing proper healthcare among the patients. It should be understood that well-performing facilities also have their own weaknesses which prevent them from achieving even better systems. During the benchmark operations, healthcare managers should be careful to identify some of the techniques that the host organization should do to improve on their weaknesses.

Such an analyses would also be an indirect show of the specific strengths of the organization that it should focus on to ensure positive organizational growth.

Field-specific Reliability of External Benchmarking Data

Some departments are likely to perform better through the assistance provided by the analysis of benchmarking data as compared to others. Buckmaster and Mouritsen (2017) state that emergency departments and eye departments are among the primary beneficiaries of external benchmarking, mainly because almost all hospitals assume similar processes in these units.

External benchmarking data

In other departments where facilities integrate their own operations, it external benchmarking data is less reliable as the operations in the organization could be entirely different from that one in which benchmarking is taking place.


Both internal and external benchmarking data are useful in the improvement of organizational standards and driving growth. Internal data also helps to achieve individualized improvement as well as to perform internal assessments of crucial organizational procedures that can help in improving the position of the facility in the market.

There are numerous benefits of external benchmarking data such as helping organizational managers to realize the presence of crucial resources in the firm as well as to identify some of their hidden strengths and weaknesses. Healthcare managers should be keen to apply internal and external data that is only valid and reliable to the operations of their facilities.


Agarwal, R., Green, R., Agarwal, N., & Randhawa, K. (2016). Benchmarking management practices in Australian public healthcare. Journal of health organization and management.

Brandão, A., Pereira, E., Esteves, M., Portela, F., Santos, M. F., Abelha, A., & Machado, J. (2016). A benchmarking analysis of open-source business intelligence tools in healthcare environments. Information7(4), 57.

Buckmaster, N., & Mouritsen, J. (2017). Benchmarking and learning in public healthcare: Properties and effects. Australian Accounting Review27(3), 232-247.

Choi, J., Leite, F., & de Oliveira, D. P. (2018). BIM-based benchmarking system for healthcare projects: Feasibility study and functional requirements. Automation in Construction96, 262-279.

Gonzalez, M. E. (2019). Improving customer satisfaction of a healthcare facility: reading the customers’ needs. Benchmarking: An International Journal.

Hibbert, P., Saeed, F., Taylor, N., Clay-Williams, R., Winata, T., Clay, C., & Braithwaite, J. (2020). Can benchmarking Australian hospitals for quality identify and improve high and low performers? Disseminating research findings for hospitals. International Journal for Quality in Health Care32(Supplement_1), 84-88.

Benchmarking deep learning models

Purushotham, S., Meng, C., Che, Z., & Liu, Y. (2018). Benchmarking deep learning models on large healthcare datasets. Journal of biomedical informatics83, 112-134.4

Feibert, D. C., Andersen, B., & Jacobsen, P. (2019). Benchmarking healthcare logistics processes–a comparative case study of Danish and US hospitals. Total Quality Management & Business Excellence30(1-2), 108-134.

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Why is data entry important in healthcare?

Data entry in healthcare is of paramount importance for several reasons, as it plays a crucial role in maintaining high-quality patient care, efficient operations, and informed decision-making. Here’s why data entry is vital in healthcare:

  1. Patient Care: Accurate and timely data entry ensures that a patient’s medical history, diagnoses, treatments, and medications are up to date and readily accessible. This information is vital for healthcare providers to make informed decisions about patient care.
  2. Medical Records Management: Data entry is essential for creating and maintaining electronic health records (EHRs) or paper medical records. These records are the foundation of a patient’s medical history and are crucial for continuity of care, treatment planning, and legal documentation.
  3. Patient Safety: Accurate data entry helps prevent errors and patient safety incidents. Ensuring that the right patient receives the right treatment or medication is a fundamental aspect of healthcare.
  4. Billing and Reimbursement: Healthcare facilities rely on precise data entry to bill patients and insurance companies correctly. Accurate documentation of services provided is vital for financial sustainability.
  5. Clinical Decision Support: EHRs and other health information systems use data to provide clinical decision support, such as drug-drug interaction alerts, allergy notifications, and evidence-based guidelines, to aid healthcare providers in making safe and effective treatment choices.
  6. Research and Public Health: Aggregated and de-identified healthcare data supports medical research, public health initiatives, and epidemiological studies. It helps identify health trends, disease outbreaks, and areas for improvement in healthcare delivery.
  7. Healthcare Planning: Accurate data is vital for healthcare planning and resource allocation. It enables healthcare organizations and policymakers to identify areas of need, allocate resources effectively, and plan for future healthcare demands.
  8. Quality Improvement: Data entry is integral to quality improvement initiatives in healthcare. Continuous monitoring of performance data helps identify areas where processes can be improved, leading to better patient outcomes.
  9. Legal and Regulatory Compliance: Accurate and complete data entry is crucial for complying with legal and regulatory requirements, including those related to patient privacy (HIPAA), meaningful use of EHRs, and Medicare and Medicaid regulations.
  10. Emergency Situations: In emergency situations, such as natural disasters or pandemics, rapid and accurate data entry is essential for tracking patients, managing resources, and coordinating healthcare services effectively.
  11. Telemedicine and Remote Monitoring: With the growth of telemedicine and remote monitoring, data entry is critical for capturing patient data from remote locations and ensuring that healthcare providers have access to real-time patient information.
  12. Transparency and Accountability: Accurate data entry supports transparency in healthcare, allowing patients to access their own health records and hold healthcare providers accountable for the care they receive.

How data can be used in patient care?

Data plays a crucial role in patient care, enhancing the quality and safety of healthcare delivery. Here’s how data can be used in patient care:

  1. Clinical Decision Support: Data, including a patient’s medical history, test results, and diagnostic information, is used to provide clinical decision support to healthcare providers. This includes alerts for drug interactions, potential allergies, and evidence-based treatment guidelines, helping doctors make informed decisions about patient care.
  2. Patient Identification and Verification: Accurate patient identification is crucial to ensure that the right patient receives the right treatment. Data, such as name, date of birth, and medical record number, is used for patient verification to prevent errors and ensure patient safety.
  3. Treatment Planning: Data is used to develop treatment plans tailored to a patient’s specific needs and medical history. This includes selecting appropriate medications, therapies, and interventions based on the available patient data.
  4. Monitoring and Surveillance: Data from medical devices, such as vital sign monitors, helps healthcare providers monitor a patient’s condition in real-time. It allows for early detection of changes that may require immediate intervention.
  5. Electronic Health Records (EHRs): EHRs provide a comprehensive view of a patient’s medical history, including past diagnoses, treatments, and test results. EHRs facilitate care coordination among different healthcare providers and improve the continuity of care.
  6. Telemedicine and Remote Monitoring: Patient data is used in telemedicine and remote monitoring to assess and manage patients’ health from a distance. Remote monitoring devices can transmit data on vital signs, symptoms, and medication adherence, enabling healthcare providers to intervene when necessary.
  7. Patient Engagement: Patients can access their health data through patient portals, empowering them to actively participate in their care. They can review test results, schedule appointments, and communicate with healthcare providers, leading to better engagement and adherence to treatment plans.
  8. Preventive Care: Data is used to identify patients at risk for certain medical conditions, allowing healthcare providers to implement preventive measures and health screenings. For example, a patient’s family history and lifestyle data can inform recommendations for preventive care.
  9. Chronic Disease Management: For patients with chronic diseases, data is used to track their condition over time. Continuous monitoring and data analysis help healthcare providers adjust treatment plans and improve disease management.
  10. Population Health Management: Aggregated patient data is used to assess the health of a population, identify health trends, and implement public health interventions. This can lead to improved community health and better care delivery.
  11. Patient Safety: Data is used to improve patient safety by identifying and addressing errors or near misses. For example, incident reporting systems can collect data on safety incidents, leading to corrective actions that prevent future errors.
  12. Outcome Evaluation: Healthcare data is used to assess the outcomes of different treatments and interventions. This informs evidence-based practices and helps healthcare providers choose the most effective treatments for their patients.
  13. Clinical Trials and Research: Patient data is essential for clinical research, allowing scientists to develop new treatments, medications, and medical procedures. Patients can also participate in clinical trials to advance medical knowledge.
  14. Billing and Insurance: Data supports the financial aspect of patient care, including billing and insurance claims, ensuring that patients receive the necessary coverage and services.
  15. Care Coordination: Data is shared among healthcare providers, improving care coordination. This ensures that all members of a patient’s care team have access to the same information and can work collaboratively.

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