Introduction
Healthcare is a vital industry for any country; therefore, the quality of experiences and facilities’ performance must be in control. Data collection tools and measurement technics were developed to timely note and address threats or implement new practices. Quality for healthcare can be defined as the degree of the expected outcomes’ likelihood (Agency for Healthcare Research and Quality, 2018). Measuring it means to explore the structural aspects such as characteristics of the providers’ professionalism or facilities’ equipment, process, and outcomes (Hash et al., 2019). Quality improvement models commonly include problem identification, current performance studying, cause analysis, strategy development, effectiveness evaluation, and modification (Hash et al., 2019). Correct measurements, categories, rates, and criteria are the key to enhancing a healthcare facility’s activity in an optimal manner.
The healthcare industry is strictly tied to clients’ experience, thus problems and weak points identification must start from gaining information from them. Moreover, Hash et al. (2019) claim that “data collected for quality measurements can be grouped into four categories: clinical quality, financial performance, patient, physician, and staff satisfaction, and functional status” (p. 107). These domains address the expected outcomes of healthcare services established by the government and the customers’ demands. Indeed, if staff satisfaction rate is below the set minimum, their productivity and willingness to work would decrease and might lead to severe consequences for a clinic’s overall performance.
Various quality measurements can be applied to different types of healthcare facilities, and the selection must be based on a hypothetic issue to check or certain activities. For instance, acute care hospitals might need to pay more attention to patient experience during the time spent on treatment rather than analyzing particular procedures’ effectiveness. Prioritizing client experience and outcomes of their hospitalizations is a foundation to explore how close the staff and equipment are to the expected outcomes and established standards (Khera et al., 2020). Consequently, readmission rate, percentage of patients leaving against medical advice, and infection control can be the measurements for evaluating a healthcare organization’s quality. Values for the analysis of these factors are tied to the client experience and address critical aspects such as safety and efficiency. This paper aims to explore the quality measurement tools for evaluating readmission rate, percentage of patients leaving against medical advice, and infection control at an acute care facility.
Readmission Rate Measure of Quality
Hospital readmission rating allows facilities to track the number of cases when patients require an unplanned return for receiving treatment and compare it to the average. The measurement is vital for improving quality and optimizing spending on healthcare services. Indeed, readmissions are costly for Medicare patients and might become an additional burden for the budget (Hasan et al., 2020). The rate identifies the quality and efficiency of services delivered because of a high percentage of returns to hospital signals about the poor outcomes of initial treatment (Hasan et al., 2020). Moreover, acute care facilities can analyze the diagnoses with the highest readmission score to develop new preventing practices. The quality measurements based on the rate are necessary for optimizing the average time spent at a hospital after the initial visit and for adjusting the range of procedures performed by staff.
It is essential to identify the criteria of a readmission to be counted because such returns as repeated surgery or the conditions with a high worsening likelihood are inevitable. The indicator for analyzing the rate must be reliable, valid, and based on the evidence about average diseases’ outcomes and patient experiences (Nasiri et al., 2019). As the score is calculated from the number of returns during the first month after the initial hospitalization, it narrows the data to process and makes the measurements more specific (Khera et al., 2020). The quality of an acute care facility’s performance depends on various factors, yet the readmission rate is a profound starting point for searching the quality improvement gaps.
Numerical Description and Data Collection
There are no specific formulas for counting the readmission rate, and it can be changed based on the selected time slot. The calculation is based on subtracting the number of unplanned additional visits from the overall number and dividing it by total for extracting the percentage (Hasan et al., 2020). The benchmarks that can be used for identifying possible quality gaps are the average readmissions per unit per month and the number of cases for a certain disease (Agency for Healthcare Research and Quality, 2018). Data collection for the rate is tied to patient feedback and experience and can be gathered from their appointments’ results. Also, CRM systems that register operations, new visits, hospitalizations, and discharges are useful for noticing the patterns and extracting the information for counting the rate. Accuracy is critical for information selection because the results influence finances, authority, and quality of operations performed by the employees.
Readmission rate can be compared to the overall quantity of returns, certain diseases’ outcomes, or the treatment consequences statistics. However, the score would be more informative if counted independently because it would increase the accuracy and reveal more about the reasons for a larger or smaller percentage of cases (Khera et al., 2020). For instance, data analysis revealed that the readmission rate increased during the last month, and more than one-third of patients are related to the emergency injuries treatment unit (Khera et al., 2020). Tunneling the results to a certain department allows understanding who made the decisions for the affected patients and directly addressing possible issues.
Risks and Goals of Readmission Rate Measuring
Several risks occur during the readmission rate measurement, and they are related to the quality improvement gaps identification and the external factors’ influence underestimation. Indeed, the reasons for the score increase might be explained incorrectly, leading an organization to improve, changing, or restructuring the wrong segment. The risk of excluding the external environment factors severely affects the data analysis’ outcomes (Hasan et al., 2020). For instance, the increased frequency of returning after the infection episode might be considered readmission rate growth, yet in reality, this circumstance is tied to the local spread of a certain contagious disease.
If a healthcare organization aims to excel in its marketplace, analyzing the readmission rates must be the priority goal for them. As the calculation requires analysis for the cases of return, it becomes a foundation for identifying factors that threaten a facility’s efficiency. The goal of addressing these weak points at a certain period can be created to enhance overall performance or to become the best healthcare provider in a certain treatment category (Agency for Healthcare Research and Quality, 2018). For instance, the readmission rate at a region with more diabetes patients than the average can be considered by a facility that would like to be a market leader in diabetes treatment quality. Moreover, identification of practice gaps can be timely found and addressed through additional education for the involved employees. Lastly, an organization with a purpose to improve its position in the market can rely on the readmission rates for analyzing the effectiveness of the quality improvement approaches.
Readmission Rate Measure in Acute Care Organization
Acute care organizations have a significant dependence on the readmission rate because this measurement can be performed in a more precise manner. Indeed, the range of cases of patient’s unplanned returns can be broke down based on hospital departments, diseases, procedures received, and medication is taken (Khera et al., 2020). For example, the Kindred Hospital in San Francisco Bay Area guarantees assistance with chronic diseases and injuries, allows to extend a post-surgery recovery, and provides an objective Medicare spending explanation (Kindred Hospital, n. d.). Indeed, if the facility’s wound care department has 33 total readmissions per month and 12 of them tend to be unexpected. If the number of unplanned returns increases to at least four patients, it is reasonable to investigate if the procedures’ quality decreased.
Influence of Readmission Rate on Healthcare Delivery Quality
Readmission rate directly relates to the cost of poor quality as the increased frequency of visiting an acute care facility is expensive. It influences the overall cost of healthcare delivery because the treatment expansions require additional spending and working hours to address. For example, injuries with surgery have a certain price for the Medicare program participants (Hasan et al., 2020). If the healing process goes unwell and requires additional help, the facility and client would have to use the money they could avoid spending if the procedures were performed correctly from the beginning. Patient safety can also be related to the readmission rates because the increase of percentage means that the clients received healthcare of lower quality than usual, and their welfare could have been threatening.
Percentage Discharge Against Medical Advice Measure of Quality
The percentage of patients leaving a healthcare facility despite the recommendations to stay is also called the Discharge against Medical Advice (DAMA). This rate-based measure of quality addresses clients’ safety because if the quantity of such cases increases, it means that there are certain issues in the services. Besides, DAMA, if not taken under control on time, would lead to higher mortality, readmissions, and additional costs of providing healthcare (Ashrafi et al., 2017). As a quality measurement, the rate can be identified as a premature discharge without a significant reason. DAMA can be influenced by the lack of clear communication between personnel and patient, the lack of respectful treatment, or an unsafe environment (Ashrafi et al., 2017). All these factors define the low quality of services offered by a healthcare facility.
Numerical Description and Data Collection
Although DAMA rate calculation does not include specific formulas, it requires registering each case and including patient’s data and their conditions’ description. In general, to retrieve the DAMA rating, the percent ratio between the total number of discharges and the unadvised cases must be counted (Bhoomadevi et al., 2019). Data collection is crucial for registering and addressing the results of DAMA measurements because accurate information leads to finding and eliminating the root cause of poor healthcare quality. Ashrafi et al. (2017) state that “the information needed to carry out the study including variables related to the patients, as well as the reasons for the DAMA based on a research-made checklist were extracted” (p. 4565). Moreover, personal characteristics such as age, gender, race, socioeconomic status must be collected and checked to identify if the threat of discrimination could occur. The DAMA measurement can be compared to actual rates based on the overall national percentage of the cases and differentiated by the types of facilities and diagnoses. For instance, the patients of lower-income groups tend to leave hospitals against medical advice due to the costs associated with a longer stay.
Risks and Goals of Discharge Against Medical Advice Measuring
DAMA measurement of quality is risk-adjusted because of the outcomes the increasing number of patients who leave has on a facility’s reputation. Moreover, clients who refuse to stay and complete treatment are likely to worsen their conditions or receive incomplete service. Consequently, if an organization aims to take leading positions in its market, it must track each case of DAMA and calculate the rates with a certain frequency. It is necessary to timely notice and address the changes or identify the quality improvement gaps in the current practices (Hash et al., 2019). For instance, an acute care hospital might set a goal to enhance its patient-centered treatment approach. To achieve it, the representatives will receive additional education and practice on the patients who are most likely to leave against advice (Ashrafi et al., 2017). The information about such clients’ characteristics and the efficiency of novel strategies can be identified through the DAMA measurement of quality.
Discharge Against Medical Advice Rate Measure in Acute Care Organization
Acute care organizations are the most affected by the severe outcomes of DAMA among their clients. Indeed, the patients receive longer treatment and stay at a facility for the time sufficient to make conclusions if they need to complete the suggested program or not. Consequently, issues such as lack of support, misunderstanding, poor quality of a certain procedure, or other negative experiences can force an individual to leave regardless of their health conditions (Hash et al., 2019). Bhoomadevi et al. (2019) suggest that “to increase awareness regarding the dangers and consequences of leaving the hospital, effective communication should be established and strengthened between patients, physician, and other medical staff” (p. 3862). For instance, Kindred Hospital is an acute care organization located in San Francisco – an area with a diverse population (Kindred Hospital, n. d.). Miscommunication with a person who represents a minority group can lead to their DAMA and threaten the quality of services offered.
Influence of Discharge Against Medical Advice Rate on Healthcare Delivery Quality
DAMA rate is the measure of quality that directly relates to patient safety as it reveals if staying at a facility is more threatening than being at home with an injury or disease. Moreover, the increased percentage correlates with the costs of healthcare delivery growth, forcing people to try avoiding extra spending (Bhoomadevi et al., 2019). The poor quality of treatment that causes DAMA is a significant challenge for acute care facilities because various factors from client-physician to the quality of nursing services influence it.
Infection Control Measure of Quality
Infection control is crucial because of its influence on the overall conditions, environment, and safety of the patients and staff. The quality improvement gap in that aspect can be displayed in the lack of knowledge about sterilization practices. Thandar et al. (2021) state that many infections occur “due to the use of invasive devices, central lines, urinary catheters and ventilators” (p. e044971). Assessing the quality of control can help prevent the severe consequences and, in the conditions of the COVID-19 pandemic, address the challenge of keeping patients safe. The measure can be defined as the frequency of occurrence of infection cases in a population during a certain period.
Numerical Description and Data Collection
Keeping the cases of contagious diseases outbreaks on track is vital for any healthcare facility’s quality assessment. Infection control measurement is constructed via the identification of the percentage rate between the average census and the number of cases, limited by a certain timeframe (Nasiri et al., 2019). The calculations can also be performed to identify the rating based on the resident days, multiplying the ratio by the necessary duration of hospitalization.
Data collection for infection control is based on the daily analysis of patients’ conditions and timely registration of any deviations. Indeed, the information is gathered from analyses such as body temperature, blood pressure, and basic physical checkups performed and registered every day. Moreover, data aggregation via the internal basis is a modern technology that can help collect information and predict the threat of contagious disease spread based on the changes in patients’ conditions (Nasiri et al., 2019). The measurement is different from other settings because patients with weakened immune systems who receive procedures with invasive devices might catch an infection quicker than in another setting (Jeanes et al., 2020). A facility’s internal rates can be higher or lower than the average, depending on the practices performed among personnel and quality improvement strategies utilized.
Risks and Goals of Infection Control Measuring
The measure of infection control as a quality indicator for a healthcare facility is adjusted to risk because contagious diseases can occur and spread regardless of the preventative practices. Indeed, the COVID-19 outbreak revealed that even extreme hygiene, sterility, and safe procedures performance could not eliminate the chance of the virus spreading (Jeanes et al., 2020). However, the risks related to the lack of the measures listed above must be considered and practiced by all healthcare providers.
Facilities that strive to have a competitive advantage at infection control and seek to excel in the marketplace must address that quality measure from various aspects simultaneously. The personnel would need additional education and practice, sufficient protective equipment must be provided, and the patients must be educated and motivated to maintain hygiene (Jeanes et al., 2020). The goals related to measuring infection control require specific percentage aims and realistic approaches for achievement. For example, it is challenging to predict the respiratory contagious disease prevention effectiveness during the COVID-19 pandemic; therefore, the goal should be to decrease the risk by 5% rather than 20%.
Infection Control in Acute Care Organization
Acute care organizations must maintain the high quality of infection control among all units because otherwise, the patients would be at risk of worsening their conditions. Measuring the rate of disease cases is also critical for noticing the patterns and timely isolating people who might carry infection. For instance, the Kindred Hospital has specialized regulations for contagious disease control and might decline hospitalization if a person threatens the overall safety (Kindred Hospital, n. d.). Acute care facilities have infection units, personnel of which must continuously analyze if the quality of controlled measures requires improvement.
Influence of Infection Control Rate on Healthcare Delivery Quality
The quality rate of infection control is vital for evaluating healthcare delivery at an organization. Indeed, the low risk of developing a caught disease has a direct relation to the patient safety index. Measurement tools and data collection require daily attention, working hours, and sufficient equipment; therefore, it influences the cost of healthcare delivery (Jeanes et al., 2020). In the case of poor quality for infection control, a hospital will not be able to operate properly. Frequent measuring of personnel’s willingness to maintain a safe environment and checking if the patients are motivated to keep hygiene a priority is critical for the healthcare facility.
Conclusion
The proper use of quality measurement tools is crucial for the successful performance of acute care facilities. The rates such as readmission, percentage of patients leaving against medical advice, and infection control are the indicators of how well the patients are treated, what conditions are at the hospital. Measuring quality to identify if there are threats to patient safety, employees satisfaction, or risks of worsening the treatment is the modern approach of maintaining high efficiency in a facility.
References
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