NURS 8302 Assignment 2: Tools for Measuring Quality ANSWER

• Describe the three rate-based measures of quality you selected, and explain why.
• Deconstruct each rate-based measure to include the following:
  • Describe the definition of the measure.
  • Explain the numerical description of how the measure is constructed (the numerator/denominator measure counts, the formula used to construct the rate, etc.).
  • Explain how the data for this measure are collected.
  • Describe how the measurement is compared externally to other like settings, and differentiate between the actual rate and a percentile ranking. Be specific.
  • Explain whether the measure is risk adjusted or not. If so, explain briefly how this is accomplished.
  • Describe how goals might be set for each measure in an aggressive organization, which is seeking to excel in the marketplace. Be specific and provide examples.
• Describe the importance of each rate-based measure to a chosen clinical organization and setting.
  • Using the websites and resources, you can choose a hospital, a nursing home, a home health agency, a dialysis center, a health plan, an outpatient clinic, or private office; a total population of patient types is also acceptable, but please be specific as to the setting. That is, if you are interested in patients with chronic illness across the continuum of care, you might home in a particular health plan, a multispecialty practice setting or a healthcare organization with both inpatient and outpatient/clinic settings.
  • Note: Faculty appointments and academic settings are not permitted for this exercise. For all other settings, consult the Instructor for guidance. You do not need actual data from a given organization to complete this Assignment.
• Explain how each rate-based measure (you selected) relates to patient safety, to the cost of poor quality, and to the overall cost of healthcare delivery. Be specific and provide examples.

Sample Answer for NURS 8302 Assignment 2: Tools for Measuring Quality ANSWER

Irrespective of their health conditions, all patients require timely,

effective, and quality health care services. Overall, achieving the desired state of health care quality remains a leading goal of health care organizations. Processes, procedures, and routine interactions should ensure that patients are excellently served. Satisfaction should be a guiding principle. In health practice, quality of care represents the degree to which health services meet the desired outcomes. To examine whether they are providing quality care, organizations should regularly evaluate their performance using rate-based quality measures. Evaluating performance guided by rate-based quality measures is a practical way of improving care delivery and patient outcomes. This paper describes rate-based measures of quality in health care organizations. It further deconstructs each measure, describes the importance, and explains how each measure relates to patient safety and the cost of healthcare delivery.

Rate-Based Measures: Description

Quality measures are reliable indicators of a healthcare organization’s capacity to deliver optimal care. Rates show the difference between performance and expectations. Appropriate rate-based quality measures for in-depth exploration include readmission rates, complication rates, and post-procedure death rates. These measures have been selected since they directly relate to the type of care that patients receive in health care settings. Their rates are inversely proportional to the quality of care. For instance, high readmission rates indicate that the quality of care does not meet the desired performance levels. The same case applies to complication rates and post-procedure death rates.

The other reason for selecting these measures is their significance in the overall health care provision in the United States. The Centers for Medicare & Medicaid Services (CMS) reports that quality health care is a priority for the President of the United States, Department of Health and Human Services, and CMS (Centers for Medicare & Medicaid, 2020). Due to the significance and interest of quality health care, CMS uses quality initiatives for health improvement in many instances and spends considerable resources in quality enhancement programs. As a result, the rate-based quality measures indicate the extent to which health care organizations align with the President’s and CMS’ expectations as far as quality is concerned.

Health care organizations require tools for quantifying healthcare processes. The selected rate-based measures are used for quantifying outcomes. Quantifying the processes and outcomes shows an organization’s ability to provide high-quality care. Quantifying outcomes by rating them also indicates the areas requiring more attention as the organization adopts new quality improvement mechanisms.

Deconstructing Each Measure

When a patient visits a healthcare organization for medical assistance, the general desire is to get an accurate diagnosis and proper treatment. Such assistance promotes healing and helps the patient to recover within the healthcare facility or at home. Unfortunately, health complications may necessitate readmission. Upadhyay et al. (2019) described readmission rate as hospital admission occurring within a specified time frame after discharge from the first admission. As a result, the readmission rate denotes the percentage of patients readmitted after discharge. Readmission rates may be calculated in terms of weeks, months, or annual readmission.

With hospital-acquired infections (HAIs) a sincere concern in health care delivery, the complication rate should guide health care providers in preventing HAIs. Lim (2019) described the complication rate as the percentage of patients developing complications resulting from care. In most instances, complication rates are high in complex procedures such as surgeries. For instance, the complication rate associated with heart surgeries is often higher than treatment for malaria. Routinely, many health care organizations track the complication rate by a specific timeframe or division. In this case, all complications can be calculated together or segmented according to the type of disease. The extent of complication rate indicates the quality of care that patients receive in a particular health care setting.

After the treatment, patients always look forward to a full and speedy recovery. Healthcare organizations also implement the necessary measures to prevent deaths to ensure that the mortality rates for all illnesses are as low as possible. Despite these efforts, deaths still occur after procedures. According to Lim (2019), the post-procedure death rate is the number of deaths occurring after treatment. The death rate usually varies depending on the procedure. Like readmissions and complication rates, a high post-procedure death rate may be an indicator of low-quality health services.

To construct the readmission rate, the number of readmitted patients (numerator) is divided by the number of patients served during a given period (denominator). The figure is given in percentage. For instance, if five patients were readmitted after 200 discharges, the readmission rate would be (5/200) x 100, giving 2.5%.  The complication rate is constructed by dividing the number of patients who develop complications by the number who received care in a given timeframe. The post-procedure death rate is calculated by dividing the number of deaths by the number of patients who received treatment. The post-procedure death rate is provided for each procedure. Like complication rates, post-procedure death rates differ depending on the type of procedure.

In each case, comparative data analysis occurs to develop the measure and get the necessary meaning to guide decision-making. For readmission rates, health care organizations may opt to record readmission cases for all illnesses after discharge. Alternatively, they may collect data for specific illnesses, which helps to determine illnesses associated with the highest readmission rates. The same approach can be used for collecting data for complication rates. Data may be case-specific or combine all complications over a given timeframe.  Post-procedure death rates’ data can be tracked hospital-wide or for specific divisions and health care teams.

To determine whether a healthcare organization’s performance is within the expected performance levels, data comparison is necessary. According to the Centers for Medicare & Medicaid Services (2020), quality measures should be publicly reported. As a result, health care organizations make their data public when required, implying that their performance is visible to other settings in the same state or different regions. Shah et al. (2019) noted that the availability of such performance data, including readmission rates, allows the Readmissions Reduction Program (HRRP) to incentivize decreased readmissions. A healthcare organization can do comparative performance analysis to reflect on its performance versus other organizations through the publicly reported data.

The rates can be provided as actual figures or percentile ranking. Like illustrated in readmission, complication, and post-procedure death rate calculations, actual rates represent the figures of each measure calculated using historical operating functions and adjustment factors. For instance, the actual readmission rate is the number of readmissions divided by the number of discharges in a given time. Mostly, actual rates are given in percentage. On the other hand, percentile ranking is the percentage of scores in the frequency distribution equal or lower than the score. For instance, if the readmission rate is 65% of a hospital, 65 is the percentile rank. Since readmissions illustrate poor performance, the facility would have performed worse than 65% of other facilities included in the frequency distribution.

Some measures of quality are usually risk-adjusted. For accurate calculations of post-procedure death rate, the measurement must factor the risk level into calculations (Ng-Kamstra et al., 2018). The risk level varies for each procedure. Risk adjustment also applies to complication and readmission rates. Risk adjustment includes risk factors associated with a measure score, allowing fair and accurate healthcare outcomes comparison. A typical risk factor is the health status of a patient.

Healthcare organizations set different goals based on their missions, visions, and performance objectives. For an aggressive organization seeking to excel in the marketplace, a reasonable goal for readmission rate as a measure of quality is to reduce the rates to below the state and nationally minimum allowable levels. As a result, the organization would adopt the necessary measures to reduce the rates, such as bedside patient education and technology adoption in healthcare processes for better communication and patient monitoring.  For complication rate, an aggressive organization would set quality improvement goals focusing on reducing the complication rate. As a result, the organization would initiate measures to prevent complications after a medical procedure. Similar goals apply to the post-procedure death rate. The organization should be motivated to have no death case after a medical procedure. The reference point should always be the state and national performance benchmarks.

References

Brunner-La Rocca, H. P., Peden, C. J., Soong, J., Holman, P. A., Bogdanovskaya, M., & Barclay, L. (2020). Reasons for readmission after hospital discharge in patients with chronic diseases—Information from an international dataset. PloS One, 15(6), e0233457. https://doi.org/10.1371/journal.pone.0233457

Centers for Medicare & Medicaid Services. (2020, Feb 11). Quality measures. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityMeasures

Gupta, S., Zengul, F. D., Davlyatov, G. K., & Weech-Maldonado, R. (2019). Reduction in hospitals’ readmission rates: Role of hospital-based skilled nursing facilities. Inquiry : A Journal of Medical Care Organization, Provision and Financing, 56, 46958018817994. https://doi.org/10.1177/0046958018817994

Lim, R. (2019). Multidisciplinary approaches to common surgical problems. Springer Nature.

Merkow, R. P., Shan, Y., Gupta, A. R., Yang, A. D., Sama, P., Schumacher, M., … & Bilimoria, K. Y. (2020). A comprehensive estimation of the costs of 30-day postoperative complications using actual costs from multiple, diverse hospitals. The Joint Commission Journal on Quality and Patient Safety, 46(10), 558-564. https://doi.org/10.1016/j.jcjq.2020.06.011

Ng-Kamstra, J. S., Arya, S., Greenberg, S. L., Kotagal, M., Arsenault, C., Ljungman, D., … & Shrime, M. G. (2018). Perioperative mortality rates in low-income and middle-income countries: a systematic review and meta-analysis. BMJ Global Health, 3(3), e000810. http://dx.doi.org/10.1136/bmjgh-2018-000810

Shah, R. M., Zhang, Q., Chatterjee, S., Cheema, F., Loor, G., Lemaire, S. A., … & Ghanta, R. K. (2019). Incidence, cost, and risk factors for readmission after coronary artery bypass grafting. The Annals of Thoracic Surgery, 107(6), 1782-1789. https://doi.org/10.1016/j.athoracsur.2018.10.077

SLC Health Saint Joseph. (2021). Our services. https://www.sclhealth.org/locations/saint-joseph-hospital/

Upadhyay, S., Stephenson, A. L., & Smith, D. G. (2019). Readmission Rates and Their Impact on Hospital Financial Performance: A Study of Washington Hospitals. Inquiry : A Journal Of Medical Care Organization, Provision and Financing, 56, 46958019860386. https://doi.org/10.1177/0046958019860386

Warchol, S. J., Monestime, J. P., Mayer, R. W., & Chien, W. W. (2019). Strategies to Reduce Hospital Readmission Rates in a Non-Medicaid-Expansion State. Perspectives in Health Information Management, 16(Summer), 1a. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6669363/

Sample Answer 2 for NURS 8302 Assignment 2: Tools for Measuring Quality ANSWER

Healthcare facilities aim to deliver high-quality medical services to patients. The demand for high-quality patient services is motivated by adjusting to upcoming organizational structures, healthcare system changes, and available procedures. Recently, there has been an increased focus on delivering high-quality medical treatment, as recognized by the government, medical experts, and patients (Palese et al., 2020). Assessing the probability and frequency of encountering quality issues is crucial to determining the provision of high-quality services. This paper identifies three rate-based measures of patient care.

Rate-based Measurements

Rate-based measurements effectively assess healthcare service quality by utilizing data from events at a specific frequency. Different forms can express these measures, including rates and proportions, means, and ratios (Dart & Cunningham, 2023). Using rate-based measurements to assess the quality of care for three patients, focusing on patient safety, timeliness, and patient-centeredness, is recommended. This approach facilitates comparisons of trends over time or among providers, aiding in identifying areas requiring improvement.

Patient Safety Measure

Definition of the Measure

A patient safety measure assesses the quality of care provided in a healthcare setting. This tool evaluates the safety of healthcare settings by analyzing adverse events, including medical errors, infections, and other such incidents. Patient safety measures assess various aspects of care quality, including the proficiency of healthcare professionals, the precision of medication orders, and the safety of the healthcare setting (Elliott et al., 2020). Patient safety measures assess compliance with regulatory standards and guidelines in healthcare settings.

Numerical Description

Quantifying a patient safety measure in a healthcare setting involves calculating the frequency of adverse events within a specific timeframe. The number is divided by the total number of patients seen during the specified period and multiplied by 100 to obtain a percentage. The given study by Palese et al. (2020) found that a hospital with a monthly occurrence of ten adverse events out of 500 treated patients had a safety measure of 2%.

Data Collection

Incident reports, surveillance systems, and patient records are typically used to gather data for patient safety measures. A thorough summary of a patient’s treatment may be found in their medical records, which can also be utilized to spot any possible negative outcomes. To further evaluate the safety of the treatment given, incident reports include comprehensive details about any unfavorable incidents. By recording and observing unfavorable occurrences, surveillance systems provide a more thorough understanding of the safety of the care given (Uddin et al., 2021). Surveys, focus groups, and other data sources, including test results and electronic medical records, may also be used to gather data. The safety of the care being given may then be evaluated, and possible areas for improvement can be found using the data that has been gathered.

Comparison to Other Settings

The effectiveness of a healthcare setting may be assessed by comparing its patient safety measures to those of other environments. The proportion of settings that perform better or worse than the measured setting might be shown in a percentile ranking as part of this comparison (Elliott et al., 2020). Regulatory agencies’ benchmarks for patient safety measures may also be compared to ascertain if the environment is according to norms and requirements.

Risk Adjustment

Any possible variations in patient populations that can impact the outcomes of a patient safety measure can be considered using risk adjustment. The process of risk adjustment involves estimating the seriousness of a negative occurrence. The outcomes of the patient safety measure are then modified using this weight. For instance, the risk-adjusted patient safety measure would be 4% if a hospital had ten adverse occurrences in a month, five of which were deemed serious (Braun & Clarke, 2020).

Goals for Aggressive Organization

An ambitious company looking to dominate its industry would aim higher than the regulatory authorities’ standards for patient safety measures. For example, the company may aim for a 2 percent patient safety measure higher than the 3 percent guideline (Braun & Clarke, 2020). The company can also aim to enhance the standard of treatment and lessen the severity of unfavorable situations.

Importance to a Clinical Organization

A clinical organization prioritizes patient safety measures since they provide valuable information on the quality of care in a medical setting. Furthermore, patient safety metrics may pinpoint improvement areas and establish objectives for better quality standards (Reddy et al., 2019). Furthermore, patient safety precautions may lower the total cost of healthcare delivery and the cost of subpar treatment. Healthcare businesses may save money by minimizing adverse occurrences and enhancing quality by lowering expenditures related to malpractice, medical mistakes, and other adverse events.

Relation to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

Because they provide light on the safety of a medical environment, patient safety measures are intimately tied to patient safety. Patient safety measures may assist healthcare organizations in lowering the cost of subpar treatment by lowering the frequency of adverse occurrences, which can be measured to identify areas for improvement (Uddin et al., 2021). Furthermore, by enhancing the standard of care given and lowering the expense of malpractice and medical mistakes, patient safety measures may assist healthcare companies in lowering the total cost of healthcare delivery.

Timeliness Measures

Definition

Timeliness in healthcare refers to the speed at which healthcare services are delivered to patients, encompassing the period from identifying the need for care to the actual provision of care. This measure evaluates the time patients need to access necessary healthcare services, encompassing clinical and administrative aspects. This measure encompasses various time intervals in the healthcare system, such as the duration between a patient’s request for an appointment with a physician, the time taken for a patient to undergo a diagnostic test or procedure, and the time required for a patient to receive a referral to a specialist (Elliott et al., 2020).

Numerical Description

The numerical representation of the timeliness measure is typically based on the designated service timeframe and the actual timeframe in which the service was delivered. The timeliness measure for a physician appointment can be determined by subtracting the actual appointment duration from the expected appointment duration (Elliott et al., 2020).

Data Collection

The timeliness measure data is obtained from patient surveys and medical and administrative records. Patient surveys are commonly employed to evaluate patients’ time to obtain appointments with healthcare providers and access related services. Haraldstad et al. (2019) utilize medical and administrative records to evaluate the duration of time required for patients to undergo diagnostic tests or procedures, as well as the duration of time needed to obtain a referral to a specialist.

External Comparison

The timeliness indicator may be externally compared to other contexts by quantifying the duration it takes for patients to get treatment at different healthcare institutions. This comparison may be used to discern disparities in the duration it takes for patients to acquire medical attention at various establishments. The external comparison may also assess the real timeliness rate about a percentile rating, quantifying the duration a specific hospital takes to provide care compared to comparable facilities (Haraldstad et al., 2019).

Risk Adjustment

Risk-adjusted timeliness metrics are often adjusted to account for patient characteristics and differences in healthcare needs. Risk adjustment is often used to account for the complexity of the patient’s condition and the possible length of time that treatment may be needed. Giving patients prompt medical attention indicates the staff’s responsiveness and responsibility (Elliott et al., 2020). Patients are more likely to seek further medical care when they and their healthcare practitioner have built trust.

Setting Goals

In an assertive organization, the objectives for a timeliness metric may be established by assessing the duration it takes for a patient to obtain medical attention at various facilities. The aim would be to decrease the duration it takes for a patient to receive treatment at a certain facility. For example, a proactive organization may establish an objective to decrease the duration of a patient’s appointment with a physician by 10% (Agarwal et al., 2019). This objective may be monitored over time to verify that the organization is achieving its target. One of the objectives that might be set to ensure the application of timeliness measures is to reduce the number of in-patient stays by enhancing the dependability and effectiveness of patient treatment. The second objective is to enhance hospital infrastructure to enable healthcare professionals to provide high-quality treatment. The third objective is to alleviate the psychological distress of waiting for medical attention.

Importance to a Clinical Setting

The timeliness metric is of significant value in a clinical environment for two main reasons. Timely access to care is crucial to ensure patients get treatment promptly. This is particularly crucial for individuals requiring immediate medical attention or in danger of a medical crisis. Moreover, prompt access to healthcare might enhance the patient’s experience by decreasing waiting periods and mitigating patient dissatisfaction (Elliott et al., 2020). Furthermore, prompt access to healthcare might enhance patient safety by reducing the likelihood of medical mistakes. This is because prompt access to healthcare may decrease the duration of a patient’s stay in a medical facility, reducing the likelihood of medication errors and other medical mistakes. Moreover, prompt access to healthcare might mitigate the likelihood of nosocomial infections by minimizing the duration of a patient’s hospital stay.

Relationship to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

The timeliness indicator is closely correlated with patient safety, the financial implications of subpar quality, and the total expenses associated with healthcare provision. Timely access to treatment is crucial for patient safety since it minimizes the duration of a patient’s stay in a healthcare facility, minimizing the likelihood of medical mistakes. Moreover, prompt access to healthcare might mitigate the likelihood of nosocomial infections by minimizing the duration of a patient’s hospital stay. Timely access to treatment may mitigate the cost of poor quality by minimizing a patient’s duration in a healthcare facility, hence decreasing the expenses linked to medical mistakes (Dart & Cunningham, 2023). Additionally, timely access to medical treatment may shorten a patient’s hospital stay, saving costs associated with nosocomial infections. In the end, early access to medical care may reduce healthcare costs by shortening the length of time a patient stays in a hospital. This might result in less time spent providing care and less use of available resources. Additionally, early access to healthcare may shorten a patient’s hospital stay, saving hospital treatment costs somewhat.

Patient-Centeredness Measure

Definition

The patient-centeredness metric quantifies the extent to which a healthcare facility, institution, or organization prioritizes the patient’s preferences and requirements in providing treatment. This metric is predicated on the notion that healthcare organizations prioritizing patient-centric treatment, customized to meet each person’s specific requirements, desires, and preferences, are the most efficacious (Al-Fraihat et al., 2020). This care method considers the patient’s unique requirements, beliefs, and choices and utilizes this data to direct the supplied treatment. This encompasses educating patients and encouraging them to actively engage in their treatment, using patient-centered communication, and delivering care customized to each person’s unique requirements.

Numerical Definition

The percentage of patients rated their overall care experience as “excellent” or “very good” on a five-point scale is used to calculate this score. The number of patients who rated their care experience as “excellent” or “very good” is represented by the numerator. In addition, the total number of patients who took part in the survey is represented by the denominator. The following formula is used to compute the rate: Patient-centeredness measure is calculated by dividing the total number of patients who responded to the survey by the number of patients who rated their treatment as “excellent” or “very good,” then multiplying the result by 100. (Al-Fraihat et al., 2020).

Data Collection

Patient and healthcare provider feedback is gathered on this statistic via surveys, focus groups, and interviews. Surveys of patients may be used to learn more about their experiences receiving care from the medical facility and the quality of that care. In order to learn more about healthcare professionals’ direct experiences with the organization’s patient-centered practices, interviews may be conducted (Elliott et al., 2020). In contrast, focus groups may be used by medical professionals and patients to discuss their experiences with the organization’s patient-centered procedures.

Measurement Comparison

By comparing a percentile rating to the actual patient satisfaction rate with the patient-centeredness of their treatment, the Patient-Centeredness metric is compared to different settings. For instance, if a healthcare institution has a Patient-Centeredness rate of 75%, it indicates that 75% of the polled patients expressed satisfaction with the patient-centeredness of their treatment (Enticott et al., 2021). Subsequently, this rate may be juxtaposed with a percentile rating to assess the healthcare facility’s relative performance compared to other settings.

Risk-Adjusted or Not

The Patient-Centeredness Measure lacks risk adjustment. Risk adjustment is a technique used to factor in variations in patient attributes while evaluating healthcare quality. Risk adjustment incorporates variables such as age, gender, and other attributes that may influence the result of healthcare. As the Patient-Centeredness Measure does not evaluate healthcare results, there is no need for risk adjustment (Enticott et al., 2021).

Goals

The objective for this metric in a proactive organization would be to surpass the mean rate of patient-centric practices across comparable organizations. This objective might be accomplished by including supplementary patient-centric measures, such as offering more patient instruction and engaging patients in decision-making. The organization should adopt additional patient-centered practices that surpass the current provision of basic care. This could involve offering resources and support systems to patients with chronic conditions or those requiring assistance managing their health (Agarwal et al., 2019). In addition, the organization should aim to enhance patient-centered communication by offering explicit guidelines to patients on medication adherence, maintaining regular contact with their care team, and diligently adhering to their treatment plans.

Importance of the Measure

The Patient-Centeredness Measure is crucial for a healthcare organization as it offers valuable insights into the quality of patient care they provide. The metric may facilitate the identification of deficient regions in healthcare and can be used to monitor advancements over some time (Enticott et al., 2021). Furthermore, the measure may provide valuable information on patient engagement in their healthcare and the extent of autonomy they are granted. This may be advantageous for both the organization and the patient since it can assist in guaranteeing that the patient is getting optimal treatment.

This measure may also aid in the identification of possible issues related to patient participation or autonomy. If the measure indicates that patients lack sufficient autonomy or have poor participation in their treatment, the organization may take steps to remedy this issue. This may include allocating more resources to enhance patient involvement in their healthcare or additional resources to promote autonomy (Enticott et al., 2021). Ultimately, the metric may be used to monitor the efficacy of patient-centered treatment as time progresses. This facilitates the organization’s identification of areas that need improvement in care and enables the measurement of the effects of implemented changes aimed at enhancing patient-centered care. Implementing this may enable the organization to guarantee optimal patient care and reduce medical mistakes and readmission expenses.

Relation to Patient Safety, Cost of Poor Quality, and Cost of Healthcare Delivery

Since it measures the organization’s capacity to meet patients’ needs and provide all-encompassing care, the patient-centeredness metric has a significant correlation with patient safety. Low patient-centeredness rates in hospitals may indicate that patients are not receiving enough patient-centered care, which might lead to negative outcomes and an overall reduction in patient safety (Agarwal et al., 2019). Because it measures how well an organization can meet patient needs and provide all-encompassing care, the patient-centeredness metric is highly correlated with the price of subpar quality. Inadequate patient-centered care has negative effects and may increase costs for the organization since more treatments or services are required.

The patient-centeredness metric correlates with the overall healthcare cost because it measures how effectively an organization meets patients’ needs and provides a thorough treatment plan. Unfavorable results from inadequate patient-centered care may increase healthcare costs by necessitating more treatments and services (Enticott et al., 2021). Patients who get subpar patient-centered treatment are more likely to be dissatisfied, which lowers patient satisfaction and increases patient turnover rates. As a result, the company may experience increased costs.

Conclusion

The quality of healthcare that is provided is objectively evaluated using quality metrics. To improve patient care, they support the creation of standardized medical care procedures. The active involvement of patients, regulatory agencies, and healthcare professionals is necessary for continuous quality improvement. Patient safety, timeliness measures, and patient preparedness are the three most effective quality measures. To protect patients, all healthcare facilities must implement patient safety procedures. Metrics that measure timeliness are essential for reducing the number of people who die or suffer negative outcomes as a result of receiving subpar medical treatment. It is crucial to prioritize patient-centeredness by considering patient preferences and including family members. Consequently, the main priority should be to evaluate and ensure the quality of care, allocating resources to enhance its quality while minimizing potential damage and expenses.

References

Agarwal, S., Sripad, P., Johnson, C., Kirk, K., Bellows, B., Ana, J., Blaser, V., Kumar, M. B., Buchholz, K., Casseus, A., Chen, N., Dini, H. S., Deussom, R., Jacobstein, D., Kintu, R., Kureshy, N., Meoli, L., Otiso, L., Pakenham-Walsh, N., . . . Warren, C. E. (2019). A conceptual framework for measuring community health workforce performance within primary health care systems. Human Resources for Health, 17(1). https://doi.org/10.1186/s12960-019-0422-0

Al-Fraihat, D., Joy, M., Masa’deh, R., & Sinclair, J. (2020). Evaluating E-learning systems success: An empirical study. Computers in Human Behavior, pp. 102, 67–86. https://doi.org/10.1016/j.chb.2019.08.004

Braun, V., & Clarke, V. (2020). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 18(3), 328–352. https://doi.org/10.1080/14780887.2020.1769238

Dart, S., & Cunningham, S. (2023). Using institutional data to drive quality, improvement, and innovation. In University development and administration (pp. 1–24). https://doi.org/10.1007/978-981-19-9438-8_29-1

Elliott, R. A., Camacho, E., Janković, D., Sculpher, M., & Faria, R. (2020). Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Quality & Safety, 30(2), 96–105. https://doi.org/10.1136/bmjqs-2019-010206

Enticott, J., Johnson, A., & Teede, H. (2021). Learning health systems using data to drive healthcare improvement and impact: a systematic review. BMC Health Services Research, 21(1). https://doi.org/10.1186/s12913-021-06215-8

Haraldstad, K., Wahl, A. K., Andenæs, R., Andersen, J. R., Andersen, M. H., Beisland, E. G., Borge, C. R., Engebretsen, E., Eisemann, M., Halvorsrud, L., Hanssen, T. A., Haugstvedt, A., Haugland, T., Johansen, V. A., Larsen, M. H., Løvereide, L., Løyland, B., Kvarme, L. G., Moons, P., . . . Helseth, S. (2019). A systematic review of quality of life research in medicine and health sciences. Quality of Life Research, 28(10), 2641–2650. https://doi.org/10.1007/s11136-019-02214-9

Palese, A., Navone, E., Danielis, M., Vryonides, S., Sermeus, W., & Papastavrou, E. (2020). Measurement tools used to assess unfinished nursing care: A systematic review of psychometric properties. Journal of Advanced Nursing, 77(2), 565–582. https://doi.org/10.1111/jan.14603

Reddy, S., Allan, S., Coghlan, S., & Cooper, P. (2019). A governance model for the application of AI in health care. Journal of the American Medical Informatics Association, 27(3), 491–497. https://doi.org/10.1093/jamia/ocz192

Uddin, M. G., Nash, S., & Olbert, A. I. (2021). A review of water quality index models and their use for assessing surface water quality. Ecological Indicators, p. 122, 107218. https://doi.org/10.1016/j.ecolind.2020.107218