Organizational and Systems Leadership for Quality Improvement NURS 8300

In an 8 to 10 page paper, describe three rate based measurements of quality. Select three rate based measurements of quality that you will use as the primary basis for this paper. These measurements must relate to some aspect of clinical or service quality that directly relates to patient care or the patient’s experience of care. For the purposes of this assignment, an analysis of staffing levels is not permitted. You can find useful information on quality indicators that are of interest to you on these websites and resources. You may choose only one of the three measures to be some form of patient satisfaction measure. Deconstruct each measure to include descriptions of the following: • The definition of the measure • The numerical description of how the measurement 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; differentiate between the actual rate and a percentile ranking. • 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. Describe the importance of each measure to a chosen clinical organization and setting.  Organizational and Systems Leadership for Quality Improvement NURS 8300.Using these 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 hone in a particular healthplan, a multispecialty practice setting or a healthcare organization with both inpatient and outpatient/clinic settings. 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. Relate each measure to patient safety, to the cost of poor quality, and to the overall cost of healthcare.

Measuring Quality Guidelines

Quality as defined by the Webster’s dictionary is “a degree of excellence” (Webster, 2020). In healthcare quality refers to the degree of which an organization can provide care, maintain positive patient satisfaction, and reduce the occurrence of negative affect. Quality indicators are the tools used in healthcare measure quality.  They determine if the care is effective, timely, and clinically significant.  The US Department of Health and Human Services in conjunction with the National Commission on Quality Assurance (NCQA) have provided quality indicators and guidance through the Agency for Healthcare Research and Quality (AHRQ) to the Centers for Medicare and Medicaid Services (CMS). These quality indicators are the standards for which the American healthcare system measures quality. The quality indicators, as published by AHRQ (ARHQ, 2019) are divided into two levels of analysis, the Area Level Indicators (ALI) and Hospital Level Indicators (HLI), (AHRQ,2019). The ARI include potentially preventable complications that occur in given populations.  These are situations found in communities that lead to hospitalization.  For example an ALI might consider a chronic condition that treated correctly would have avoided a hospitalization or condition that may have been avoided if the patient’s area of residence had appropriate access to healthcare or better quality of healthcare. The HLI captures preventable complications or adverse events that are specifically linked to medical conditions or surgical procedures occurring within a healthcare institution in which there is evidence that suggests that there is deficiency in care.

The AHRQ quality indicators are then broken into domains or subsets. The domains are prevention quality indicators (PQIs), inpatient quality indicators (IQIs), patient safety indicators (PSIs) and pediatric quality indicators (PDI’s and neonatal quality indicators (NQIs). Of these domains PQI’s, PDIs, and PSIs, are ALIs and IQIs, PSIs, PPP, PQIs and NQIs are HLIs (AHRQ, 2019).  These quality indicators are used by healthcare organizations to monitor the quality of their care and determine what concerns and issues may exist within the organization. They further use these indicators to assist them in improving quality patient care and outcomes.

This paper will discuss three measures, provide definitions of the measures, explain how the measure is assessed and constructed in statistical data. It will also discuss each the use of each measures in different care settings. Finally, the paper will describe how an agency might use the data to improve care. The measures chosen for discussion in this paper are the hypertensive admissions rate, fracture mortality rate, and postoperative sepsis rate. Organizational and Systems Leadership for Quality Improvement NURS 8300.

Hypertension Admission Rate (Definition of Measure)

Hypertension is defined by the American Heart Association is blood pressure greater than 140/90 (American Heart Association, 2019).

This indicator counts individuals 18 years of age and older with an ICD 10 diagnosis code for hypertension. There are several primary diagnoses that cause secondary hypertension that are not considered in the numerator for this ratio. Diagnoses that are excluded are hypertension related to kidney disease, heart procedures, and obstetrics. Additionally, hospitals do not need to include individuals transferred to their facility with hypertension (ARHQ, 2019).

Numerical Description of Measurement/Formula

The total number of discharges from the hospital, who are 18 years of age and older with a principal ICD 10 diagnostic code for hypertension makes up the numerator. The answer is then multiplied by 100,000 population, 18 years of age and over. The population is based on a specific area. This can be in town or metropolitan, a county or state (ARHQ, 2019).

Collection of Data

The data for this measure is collected by choosing discharges from the hospital with primary ICD 10 code of hypertension, eliminating all cardiac related disorders and procedures, kidney disease and obstetrics patients (ARHQ, 2019). It is then compared to the population of the area which is included in this data set.  The AHRQ usually includes a metropolitan area or state for this denominator (ARHQ, 2019).

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Measurement Compared to like Settings

This measurement is designed to capture access to quality of care and wellness of the population in a given region. It is an estimation of community health. It uses hospital administrative data to identify the hospitalization for a condition which should be able to be treated without the need for hospitalization (AHRQ, 2019). Appropriate treatment for hypertension does not require hospitalization. This measure is influenced greatly by community issues such as disease prevalence, environmental factors, physical health concerns (poverty, pollution, access to appropriate foods, and housing).  This indicator is not highly compared to individuals but rather compared to communities, states, or regions. The benchmark for the overall population of the United States is 49.19 (AHRQ, 2016).

The overall admission rate in 2016 for the United States was 54.27. This accounts for an overall rate for females of 62.9 and males 45.15. When broken down by age the rate in 18 to 39-year-old individuals was 12, 40 to 64-year-old individuals 58.41, in 65 to 74-year-olds the rate was 91.29 and in 75 years of age and older the rate was 185.66 in 2016 (AHRQ, 2016).  The variation as noted above, relates only to age and not specific to a community or setting. This allows for public health and community health programs to assist in a wide variety of age-based considerations to assist in reducing these numbers to meet the benchmark.  Organizational and Systems Leadership for Quality Improvement NURS 8300.

Risk Adjustment

Healthcare facilities are required to report data as set in the guidelines by the centers for Medicare and Medicaid services (CMS). Those facilities do not adjust for risk with this indicator (Centers for Medicare and Medicaid Services, 2017).  There is risk adjustment knowledges differences in geographic areas to allow or consideration of community resources, exposures and the environment and demographic composition of residence. The expected rate would prevail if demographics variances are removed. If the risk adjusted rate is higher than the reference rate it means that the admission rate for a given geographical area is higher than would be expected.

Importance

Hypertension as a disease process, can be a standalone diagnosis or a diagnosis that can lead to multiple comorbidities. The comorbidities relate specifically to the amount of control of the hypertension. When an individual is diagnosed with hypertension and utilizes methods (diet, exercise, or medications) to control the severity of the disease process, they can minimize the systemic damage because of the hypertension. Even when the damage is minimized, hypertension will over time damage the cardiovascular system. This is a large factor in the increased incidence rate related to increasing age.

The comorbidities and secondary damage, such as stroke, that occurs because of hypertension can result in dramatic healthcare expenditures across the healthcare spectrum. Those patients who are monitored routinely and encouraged to gain and maintain a healthier lifestyle can maintain stability in their disease process and reduce the damage to their cardiovascular system which in turn will reduce their chance of comorbidities and potentiate longevity and a reduced negative effects. This results in savings to the healthcare system.

Hip Fracture mortality rate

fracture mortality rate is a inpatient quality indicator. The inpatient quality indicators are set measures that look specifically at quality of care in a hospitalized setting. They can be used to assist hospitals in finding areas for improvement. For this measure, the population is limited to hospitals, all nonfederal short-term general and other specialty hospitals. This excludes the hospital units within institutions, rehabilitation hospitals, and long-term care hospitals (ARHQ, 2017).

Numerical Measurement/Formula

The formula for constructing this data takes the total number of cases of in hospital deaths per thousand hospital discharges with hip fracture as a principal diagnosis for patients 65 years of age and older (CMS, 2019). The numerator for this ratio is the number of deaths among cases meeting inclusion and not meeting exclusion criteria. The exclusion criteria are carried prosthetic fracture, transferring to another short-term hospital, cases of hospice, and individuals who are pregnant or are admitted for childbirth. The denominator then is discharges for patients 65 years of age and older with hip fracture being their primary diagnosis (AHRQ, 2019).

Data Collection

The data is collected using ICD 10 code for any of the diagnosis codes for hip fracture. The patient information is then tracked and kept up to date for CMS and other agencies to follow during the reporting of the data.  Organizational and Systems Leadership for Quality Improvement NURS 8300.

Measurement Compared to like Settings

The measures are calculated using the same formula across like organizations.   Using the same formulas, it is easier to see and compare the clinical data of the other hospitals providing similar care. The rate of adverse event would be expected to be zero if the hospital has provided the required level of care to the reference population. If the observed ratio is less than one there is reason to believe that the hospital is performing better than average on this indicator (AHRQ, 2019).

Risk Adjusted Measurement

The risk adjustments are carried out by the Centers for Medicare and Medicaid Services (CMS, 2017). The risk adjusted rate for this indicator is found by multiplying the ratio of the observed rate and expected rate with reference population observed rate.  If the risk adjusted rate is higher than the reference rate it indicates the performance of the hospital is worse than would be expected based on the reference population (AHRQ).

Importance

As a hospital level indicator, this measure reflects quality of care. This ratio can be found to be skewed higher when the reference population has low quality care within the community. This indicator can vary based on demographics, severity of illness, and comorbidities

Every healthcare organization is aware of and concerned with issues that resulted in death. When an organization is striving for excellence in their community, such as magnet status they are even more aware of and concerned with reducing this ratio (CMS, 2019).  Poor scores on hospital level indicators can affect reimbursement from CMS and third-party payers (AHRQ, 2019).

Postoperative Sepsis Rate

Sepsis is defined as an overwhelming systemic infection which can lead to shock /death. Postoperative sepsis rate is a patient safety indicator. Patient safety indicators are a set of indicators that provide information on safety-related adverse events occurring during a hospitalization.   Patient safety indicators define information that can be used to help hospitals identifying areas for improvement to reduce adverse events. These indicators include only cases where a secondary diagnosis code flags the potential preventable complications.

Numerical Measurement and Formula

The numerator is determined by the total number of observed cases of sepsis, as found within ICD 10 codes following hospital discharge, in postoperative patients. The denominator is scaled to rate per 1000 persons at risk (AHRQ, 2018).

Measurement Compared to like Settings

The overall benchmark rate for postoperative sepsis rate is 4.26. The rate for females is calculated at 3.32, in males 5.5. In patients 18 to 39 years of age the benchmark rate is.18 40 to 64 years of age the benchmark is 3.36, in individuals 65 to 74 years of age benchmark is 4.81, in individuals 75 years of age and older the benchmark is 6.73 (AHRQ, 2018).  AHRQ has additional rates in private pay hospitalizations the overall rate of incidence is 2.57, Medicare payer source 5.75, Medicaid payer source 5.38, other insurance 2.83, and uninsured 3.70.

As an indicator postoperative sepsis rate is a clear and specific indication of postoperative inpatient care. Not meeting the benchmark scores for this indicator can specifically lead to reduction in payments from Medicare, Medicaid, and third-party payers (CMS, 2019).  

Risk Adjustment

The Centers for Medicare and Medicaid Services do not risk adjust for this indicator. The hospital follows CMS and its recommendations.

Importance

A hospital organization seeking to excel in the market or gain Magnet status would want to work toward the goal of reducing this score.  Having a score higher than the benchmark would indicate poor quality postoperative care.  It could reduce desire to seek surgical consultation from a surgeon or give a surgeon cause to seek surgical time in other settings or facilities.  The hospital organization could face lost revenue because of surgeons seeking a different surgical and post-operative setting as well as loss due to litigation from patients and family members.

In conclusion, the need for quality in healthcare is critical.  It leads patient populations to continue to believe that healthcare will help them in their time of need.  Quality indicators give us measures that indicate how well we are doing across the continuum (Campbell, 2000). They give quantifiable data that supports positive patient satisfaction in concluding that healthcare in a community or region is sufficiently protecting the patient population from harm.

References

Agency for Healthcare Research and Quality. (2019). Get to know the AHRQ quality indicators. https://www.qualityindicators.ahrq.gov/

The Agency for Healthcare Research and Quality. (2019). Triggers and trigger tools. https://psnet.ahrq.gov/primer/triggers-and-trigger-tools

Agency for Healthcare Research and Quality. (2018). Patient safety indicators v6.0 benchmark data tables. https://www.qualityindicators.ahrq.gov/Downloads/Modules/PSI/V60-ICD09/Version_60_Benchmark_Tables_PSI.pdf

Agency for Healthcare Research and Quality. (2017). Inpatient quality indicators v6.0 benchmark data tables. https://www.qualityindicators.ahrq.gov/Downloads/Modules/IQI/V60/Version_60_Benchmark_Tables_IQI.pdf

Agency for Healthcare Research and Quality. (2016). Prevention quality indicators v6.0 benchmark data tables. https://www.qualityindicators.ahrq.gov/Downloads/Modules/IQI/V60/Version_60_Benchmark_Tables_IQI.pdf.ahrq.gov/

American Heart Association. (2017). Controlling your blood pressure. http://www.Americanheartassociation.org

Campbell, S. M., Roland, M. O., & Buetow, S. A. (2000). Defining quality of care. Social Science & Medicine, 51(11), 1611–1625.

Naik, S., Voong, S., Bamford, M., Smith, K., Joyce, A., Grinspun, D.(2020). Assessment of the nursing quality indicators for reporting and evaluation (NQIRE) database using a data quality index. Journal of the American Medical Informatics Association, 27(5), 776–782. https://doi-org.ezp.waldenulibrary.org/10.1093/jamia/ocaa031

Webster’s dictionary, 2020.  Webster’s American Dictionary. http://www.webstersamerican dictionary.org

Quality guidelines are often statements that recommend or try to optimize patient care in different health care scenarios. Some of these scenarios may include but are not limited to hospitals, home health care agencies, doctors, and health and drug plans. In my opinion, clinical practice guidelines have the potential to prevent or reduce unwanted clinical errors and improve patient safety and satisfaction. These guidelines provide recommendations for a variety of clinical treatments that can avoid mistakes of treatment. A guideline based on scientific evidence has the potential to improve care if it is implemented correctly. Organizational and Systems Leadership for Quality Improvement NURS 8300. In the past decades, quality has become an essential topic for all health care agencies and researchers. Domains such as effectiveness, efficiency, equity, patient-centeredness, safety, and timeliness are vital for all healthcare agencies. According to the Agency for Healthcare Research and Quality (AHRQ) (2020), the Institute of Medicine has defined quality care as “the degree to which health care services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge.”

This assignment will discuss three different quality measures, and it will provide a definition of the measure, a numerical description of how the measure is constructed. It will also explain how the data is collected, compared, and whether the measure is risk-adjusted or not. Finally, the paper will describe how goals are set for each of the discussed measures. For this assignment, I have chosen a Medicare Advantage health care plan setting; my selected measures are collected by the Health Effectiveness Data and Information Set (HEDIS). HEDIS is a standardized measure designer that provides purchasers and consumers information about health care plan performance (National Committee for Quality Assurance (NCQA), 2017). The selected quality measures are colorectal cancer screening, controlling high blood pressure (CBP), and medication reconciliation post-discharge.

Colorectal Cancer Screening (Definition of Measure)

According to the NCQA (2020), the treatment for colorectal cancer (COL) in early stages may lead to a 90 percent survival rate after its five years. COL in asymptomatic adults may cause polyps before they become cancerous. More than a third part of adults between ages 50-75 do not get recommended screenings (NCQA, 2020). COL represents 8 percent of cancer cases being the second cause of cancer deaths in the United States

Numerical Description of Measurement/Formula

The denominator, patients 50-75 years of age on the date of encounter during the measurement period or patients age 65 or older who are in an Institutional Special Needs Plans (SNP) or patients residing in a long-term care facility (NCQA, 2019).

Numerators are classified by performance met or performance not achieved in patients with one or more COL screenings (NCQA, 2019). Any of the following defines appropriate screening:

• A fecal occult blood test (FOBT) during the measure year.
• A flexible sigmoidoscopy during the measure year.
• A colonoscopy during the measure year.
• A computed tomography (CT) during the measure year.
• A fecal immunochemical DNA test (FIT-DNA) during the measure year.

Collection of Data

The measure is submitted to NCQA using HEDIS measures once per performance period for clients seen during the performance period. The data can be collected and submitted by Merit-based Incentive Payment System (MIPS) eligible clinicians, groups, and third-party intermediaries (NCQA, 2019).

Measurement Compared to like Settings

Compared to other settings, COL screening is only required and submitted by organizations that participate in HEDIS. However, this will depend on the participation of patients with Medicare Advantage health plans, and if the patient complies with the requirements indicated in the measure.

Risk Adjustment

According to the Centers for Medicare & Medicaid Services (CMS) (2015), this quality measure has no risk adjustment.

Setting of Goals for Measure in an Aggressive Organization

An aggressive organization like a Medicare Advantage health plan, where the budget can be affected if the organization doesn’t comply with the CMS measure, it is essential to understand what the measure means and what we need to obtain from it to meet requirements. An aggressive organization must be focused on understanding HEDIS measures and ensuring that providers are ordering these types of tests in the correct time and period of the year.

Controlling High Blood Pressure (CBP) (Definition of Measure)

According to NCQA (2020), High blood pressure (HBP) is often known as the “silent killer”; it increases the risk of heart disease, which is the leading cause of death in the USA. CBP prevents heart attacks, stroke, and kidney disease. Health care physicians can help patients to manage their HBP by requiring low-sodium diets and prescribing medications (NCQA), 2020).

Numerical Description of Measurement/Formula

The denominator requires a drawn sample from an eligible age group for each product line with a confirmed HBP diagnosis. The organization can reduce the sample size by using the prior year’s audit (NCQA, 2017).

The numerator is the number of patients in the denominator, whose blood pressure (BP) is controlled during the measurement year (NCQA, 2017).

Collection of Data

The data collection is done by submitting information obtained by the physician or organization from patients whose members are between ages 18-85 years of age and have had a diagnosis of hypertension (HTN) (NCQA, 2017).

Measurement Compared to like Settings

As stated before, CBP is only required and submitted by organizations that participate in HEDIS. However, this will depend on the participation of patients with Medicare Advantage health plans, and if the patient complies with the requirements indicated in the measure. Organizational and Systems Leadership for Quality Improvement NURS 8300.

Risk Adjustment

According to the Centers for Medicare & Medicaid Services (CMS) (2020) this quality measure has no risk adjustment.

Setting of Goals for Measure in an Aggressive Organization

As mentioned previously, in an aggressive organization like a Medicare Advantage health plan, where the budget can be affected if the organization doesn’t comply with the CMS measure, it is essential to understand what the measure means and what we need from it to meet the requirements.

Medication Reconciliation Post-Discharge (Definition of Measure)

Medication Reconciliation Post-Discharge (MRP) is a type of review where the discharge medications of a patient are reconciled with a recent medication list in an outpatient medical record (NCQA, 2019). MRP is care coordination for patients who use prescribed medications. An estimated 82% of adults in the USA take at least one prescribed medicine, and an estimated 29% take five or more (NCQA, 2020b). A high amount of prescriptions may have negative consequences for patients if these prescriptions are not controlled and monitored.

Numerical Measurement/Formula

The denominator includes all patients discharged from an inpatient facility who are 18 years of age and older and have been seen within 30 days following discharge in the office by a doctor (NCQA, 2019).

The numerator includes an MRP conducted by an authorized prescribing practitioner, registered nurse on or within 30 days of discharge (NCQA, 2019).

Data Collection

Data is collected after an outpatient visit within 30 days of each discharge during the measurement period. This data may be submitted by Merit-based Incentive Payment System (MIPS) eligible clinicians, groups, and third-party intermediaries (NCQA, 2019).

Measurement Compared to like Settings

As stated before, MRP is only required and submitted by organizations that participate in HEDIS. However, this will depend on the participation of patients with Medicare Advantage health plans, and if the patient complies with the requirements indicated in the measure.

Risk Adjustment

According to the National Quality Forum (2020) MRP has no risk adjustment.

Setting of Goals for Measure in an Aggressive Organization

As mentioned before, in an aggressive organization like a Medicare Advantage health plan, where the budget can be affected if the organization doesn’t comply with the CMS measure, it is essential to understand what the measure means and what we need to obtain from it to meet requirements. An aggressive organization must be focused on understanding HEDIS measures and being sure that providers are ordering these types of tests in the correct time and period of the year.

In conclusion, quality indicators (QI) are evidence-based measures available to all healthcare organizations for a track and measure of clinical outcomes. Participating in programs like HEDIS can improve the quality of care that organizations offer to the population. QI are capable of highlighting quality concerns and identify areas of need in a health care organization.

References

Centers for Medicare & Medicaid Services (CMS). (2015). Colorectal cancer screening. https://qpp.cms.gov/docs/ecqm-specs/2017/EC_CMS130v5_NQF0034_Colorectal_Cancer_Screen/CMS130v5.html

Centers for Medicare & Medicaid Services (CMS). (2020). Controlling high blood pressure. https://qpp.cms.gov/docs/ecqm-specs/2017/EC_CMS165v5_NQF0018_High_Blood_Pressure/CMS165v5.html

National Committe for Quality Assurance (NCQA). (2017). Medicare special need plans performance results: HEDIS 2016. https://www.cms.gov/Medicare/Health-Plans/SpecialNeedsPlans/Downloads/2016-HEDIS-Report.pdf

National Committee for Quality Assurance. (2019). Colorectal cancer screening. National quality strategy domain: Effective clinical care. https://qpp.cms.gov/docs/QPP_quality_measure_specifications/CQM-Measures/2019_Measure_113_MIPSCQM.pdf

National Committee for Quality Assurance. (2020). Colorectal cancer screening (COL). https://www.ncqa.org/hedis/measures/colorectal-cancer-screening/

National Committee for Quality Assurance (NCQA). (2017). Controlling high blood pressure (CBP). https://www.ncqa.org/hedis/measures/controlling-high-blood-pressure/

National Committee for Quality Assurance (NCQA). (2019). Medication reconciliation post-discharge. https://qpp.cms.gov/docs/QPP_quality_measure_specifications/CQM-Measures/2019_Measure_046_MIPSCQM.pdf

National Committee for Quality Assurance (NCQA). (2020a). Controlling high blood pressure (CBP). https://www.ncqa.org/hedis/measures/controlling-high-blood-pressure/

National Committee for Quality Assurance (NCQA). (2020b). Medication reconciliation post-discharge (MRP). https://www.ncqa.org/hedis/measures/medication-reconciliation-post-discharge/

National Quality Forum. (2020). Quality positioning system (QPS) measure description display information. http://www.qualityforum.org/Qps/MeasureDetails.aspx?standardID=441&print=0&entityTypeID=1

Rate based measurements in healthcare are critical in determining the quality of care for patients within healthcare facilities. Examples of these measurements include patient wait times, patient mortality ratio, and hospital readmission rates. This paper will explore these measurements, how they are calculated, how the data is collected, the risk adjustment used in calculating these rates, and the goals that healthcare facilities can set to ensure these rates depict quality healthcare for patients.

Patient Wait Times

            Patient wait time is a significant indicator of the quality of service offered in healthcare settings for patients. This quality indicator refers to the time between a patient waiting in the clinic before seeing the medical staff, such as the nurse or the doctor, and when they leave the healthcare facility. Patient wait time is a critical indicator of the level and quality of service offered to patients in healthcare facilities. Keeping patients waiting in the queues for extended periods increases patient stress levels because of worsening health situation or increased anxiety levels, as Oche & Adamu (2013) contend. The longer a patient waits for medical services within a healthcare setting, the lower their satisfaction levels. For instance, consider a patient in the queue, suffering from bouts of migraines. They come having taken painkillers, but are worried if the various causes of migraines, such as tumors, could be what is afflicting them. Keeping such a patient long in the waiting queue affects their health because of enhanced stress levels since they continuously imagine the worst as their health condition. Therefore, to limit such outcomes, that could also be detrimental to the patient’s recovery rate, it is critical that healthcare facilities look into minimizing the length of patient waiting time by instituting a variety of measures such as increasing the number of healthcare personnel available, and proper queue management, which ensures that patients suffering from different ailments queue in the correct hospital department waiting for areas.

Calculating Patient Wait Times

            There is no specifically identified patient wait time formula because a variety of factors influences it. However, the simplest way to calculate this formula is to consider the amount of time a patient spends in the facility between their arrival and departure time. This formula applies to outpatient patients only because their visits end within the same day.  Therefore, the easiest calculation of patient wait time, going by the definition of this rate, is as follows:

Patient wait time= Time Patient Leaves- Time Patient Arrived.

Therefore, if the patient arrived and queued in the hospital at 9 am and left the hospital at 3 pm, their average patient wait time is 6 hours.

            To collect this data, the best approach is simply recording the patient entry time and their leaving time. This formula is simple because it involves simple subtraction of the patient reports to the hospital, to the time they leave. Therefore, hospitals should consider recording the time patients enter the outpatient area seeking medical attention, to the time they leave. A hospital may want to evaluate its average patient wait times, which would be calculated as follows:

Average patient wait times= Total patient wait times/ total number of patients

The patient wait time is a simple calculation that shows the average amount of time that a patient takes within their hospital visit. Introducing other settings such as the actual rate and percentile ranking would require a comparison between the patient wait times among various healthcare facilities. The actual rate would entail calculating the average patient wait time in a hospital using the formula above. The percentile ranking would require comparing numerous patient wait times from different hospitals and assessing the rank of a hospital, based on the averages of patient wait times of other healthcare facilities. Organizational and Systems Leadership for Quality Improvement NURS 8300.

Risk Adjustment

            Patient wait times are not risk-adjusted because this measure does not consider the health status of an individual and their health spending. Patient wait times are entirely contingent upon hospital staff logistics, including the number of physicians and nurses available, the size of the hospital, and the number of patients in the waiting area, among other variables (McGuire & Kleef, 2018). These variables are in no way related to patient spending and their underlying health status.

Setting Goals for Patient Wait Times

            Patient wait time is an indicator of the quality of health services provided in a healthcare facility because it affects the patient health outcomes because of increased anxiety and stress levels or worsening of health conditions while in the queue. To reduce the patient wait times in healthcare settings, the following are recommendations for hospitals:

• Collecting patient information beforehand using patient portals to reduce time spent by nursing gathering information
• Streamlining the clinical workflow by automating processes such as vitals collection, enhancing the communication of medical teams, and delegating the documentation process to other staff members to reduce the burden on the nurse and physicians (Wickramasinghe, 2019)
• Survey to identify the bottlenecks from the patients’ and staff members’ perspectives. This survey is critical because it directly identifies the challenges within the hospital system that require improvement
• Ensuring there is adequate staffing within the facility and the proper management of practitioner shifts. Having adequate staff members drastically reduces patient wait times because more staff members attend to more patients, reducing the time spent in the hospital.

Readmission Rate

            The patient or hospital readmission rate refers to the percentage of patients who return to the healthcare facility seven days after discharge. An example of readmission would be when a patient admitted for an illness is discharged, and on their way out of the hospital, slip falls, and breaks their neck, hence requiring additional readmission. Another example is a surgical patient discharged and develops an infection on the surgical site or wound, requiring readmission to address the new healthcare issue.

Calculating Readmission Rate

            The hospital readmission rate is calculated as follows:

Readmission rate= Total Number of Admissions within 30 Days of Discharge

                                    Total number of admissions

            The numerator is the total number of admissions within 30 days of discharge. The hospital collects this information on its database, such that when a patient is readmitted, the hospital has its information from the previous admission. The denominator is the number of patients admitted to the facility during the month. Sometimes some patients may have had more than one 30-day readmission, each of these admissions should be counted in the denominate, and each readmission counted in the numerator for accuracy.

            Readmission rates are actual rates, and just as the patient wait times discussed above, can be assessed as a percentile when comparing the readmission rates among hospitals. This rate is expressed as a percentage, which is an actual rate. To calculate the percentile of readmission rates, one needs to compare the percentages of readmission rates for different hospitals. For instance, if the Jackson Memorial Hospital has a readmission rate of 12% and is compared with other hospitals, it would be considered that the hospital is within the 20^th percentile of readmission rates.

Risk Adjustment

            The patient readmission rate is risk-adjusted to account for the differences in the hospital patients’ characteristics, affecting the readmission rate. Some of the factors that affect readmission rates within a healthcare facility include patient medical history, underlying and co-morbid conditions, age, gender, and type of ailment from which the patient suffers (Adam et al., 2017). For instance, if a patient has osteoporosis as an underlying condition, is admitted for a bone fracture, and is readmitted for the same illness, the osteoporosis should be considered a risk when calculating the readmission rate because this incident may not be related to the quality of healthcare provided within a healthcare facility.

            To perform risk adjustment for patient readmission rates, one should consider the clinical risk factors, the age of the patient, and the underlying risk of readmission for the patient. There are five different cohorts used for the calculation of readmissions based on patient performance. This calculation is automated whereby, for each cohort, the composites compare the predicted performance on readmission and the expected readmissions based on the factors identified before, such as age and underlying health conditions that could trigger readmission (Adam et al., 2017). This figure is then weighted on the number of hospital admissions within the identified cohorts. It is necessary to risk adjust this rate because numerous factors exist that could erroneously present a faulty readmission rate, while it is affected by external factors beyond hospital control.

Reducing Readmission Rates

            Patient readmission has adverse impacts such as worsened patient health outcomes, increased healthcare costs for the patient and the healthcare organization, decreased patient satisfaction levels, lowered practitioner morale, and negative healthcare facility reputation, among other adverse effects. The following are some of the measures that hospitals could undertake to lower the readmission rates and enhance patient outcomes:

• Intensifying and improving patient education. Some of the readmissions originate from poor or lack of patient education on managing their ailment while at home. For instance, a patient discharged for osteoporosis should understand they need additional mobility support before they regain their strength. Failure to provide the patient with such information could lead to readmission within 30 days from falls. Therefore, hospital staff should invest in conducting patient education and enhance the communication systems for the discharged patients and their caregivers to easily access them in case they require important medical information on patient management at home. Additionally, patient education enhances patient compliance with interventions and drug prescriptions. Patient non-compliance contributes to readmission rates because of practices, which contravene doctor instructions. For instance, a patient who undergoes caesarian section surgery requires pain management and antibiotic medication to prevent pain and wound infection. Poor wound care and failure to take the medication could lead to readmission because of wound infection, and all that is preventable through patient education.
• From a leadership perspective, setting the mission and vision of the organization and enabling the hospital team members to provide quality care to patients would reduce the readmissions rate (Warchol et al., 2019). A hospital team leader should enhance the coordinated effort among the hospital staff members by ensuring they have the required resources and skills to provide quality care to admitted patients. For instance,

Patient Mortality Ratio

            The patient mortality rate, also referred to as mortality ratio, is a ratio that compares the patient mortality and their expected mortality. The patient mortality ratio in a healthcare facility is a significant indicator of the quality of healthcare services offered within the facility, considering some of the factors, which influence patient mortality, are hospital-related. Factors that affect patient mortality ratio include underlying untreated health conditions, the complexity of the health condition from which the patient suffers, quality of care provided within the hospital or other healthcare facilities, and patient compliance and adherence to interventions provided by the doctors.

Calculating Patient Mortality Ratio

            To calculate patient mortality ratio, use the following formula:

Number of patient deaths

Number of admitted patients

            The numerator is the number of patient deaths for the patients admitted within the healthcare facility. These deaths are caused by some factors, such as those discussed above. The denominator is the number of admitted patients, which is important for this calculation to reveal the ratio of the patients who die within healthcare facilities. This ratio is critical in determining the quality of care provided because a significant factor associated with patient mortality is the quality of care. For instance, a hospital that lacks support bars along its corridors would experience a high rate of patient falls, some that could be fatal. Lack of support bars is an indication of poor quality of care provided in the healthcare facility.

            A ratio of 1.0 means that the patient mortality rate is as expected, safe for healthcare organizations. A ratio of <1.0 means that the mortality rate is lower than expected, which is a positive outcome for the healthcare facility. If the mortality ratio is 0.25, it means that it is 25% lower than the expected mortality. Healthcare organizations strive to attain a <1.0 mortality rate because it means that they provide quality care and reduce the incidence of patient death while admitted. Organizational and Systems Leadership for Quality Improvement NURS 8300.

Risk Adjustment

            Patient mortality ratio is a risk adjustment ratio because of other factors beyond the hospital’s scope, such as underlying health conditions and patient non-compliance. To risk adjust the patient mortality ratio, use the observed mortality ratio, which refers to the rate of patient death each quarter. The observed mortality rate is a risk adjustment measure because it ensures the ratio calculation excludes the factors beyond the hospital’s scope of control. For instance, the observed mortality ratio should be calculated to eliminate the impact of underlying health conditions in a patient before admission. This factor affects the mortality ratio and may be unrelated to the quality of care provided in the healthcare facility.

Reducing Patient Mortality Ratio

            The following are measures that a healthcare facility could implement to reduce patient mortality ratio:

• Strengthen inter-professional collaboration, especially between the nurses and the physicians, to optimize the healthcare available to the patients (McCoy & Das, 2017).
• Apply readmission reduction strategies such as intensifying patient education and improving the leadership structure within the hospital (Rutkove, 2016).
• Identifying the most common causes of patient mortality and focusing on addressing this problem within the hospital would reduce patient mortality ratio. For instance, if most of the patients in a healthcare facility die out of heart attacks or septic wounds, the management within a healthcare facility should invest in determining the solutions to heart attacks and invest in wound care, and train nurses in the management of patients and reduction of sepsis incidence.

Conclusion

            Rate based measurements of quality in healthcare are visceral rates that reveal the quality of healthcare in a healthcare facility. This paper explored patient mortality, hospital readmission rates, and patient wait times as significant rate based measurements that indicate the quality of care in hospitals. These measurements are risk-adjusted because of the causal factors beyond the hospital’s scope and management. Some of these risks include underlying medical conditions and patient non-compliance. Solutions to these problems include management adjustment, investing in patient education, available resources for patients, and strengthening inter-professional collaboration among the hospital staff members.

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References

Adam, S., Osborne, S., & Welch, J. (2017). Critical care nursing. Oxford University Press.

Howard-Anderson, J., Busuttil, A., Lonowski, S., Vangala, S., & Afsar-manesh, N. (2016). From discharge to readmission: Understanding the process from the patient perspective. Journal Of Hospital Medicine, 11(6), 407-412. https://doi.org/10.1002/jhm.2560

McCoy, A., & Das, R. (2017). Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units. BMJ Open Quality, 6(2), e000158. https://doi.org/10.1136/bmjoq-2017-000158

McGuire, T., & Kleef, R. (2018). Risk adjustment, risk sharing and premium regulation in health insurance markets. Elsevier Science.

Oche, M., & Adamu, H. (2013). Determinants of patient waiting time in the general outpatient department of a tertiary health institution in north Western Nigeria. Annals of medical and health sciences research, 3(4), 588–592. https://doi.org/10.4103/2141-9248.122123

Rutkove, S. (2016). Biomedical Research. Springer.

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. Organizational and Systems Leadership for Quality Improvement NURS 8300.

Wickramasinghe, N. (2019). Handbook of research on optimizing healthcare management techniques. IGI Global.

Assignment 1: Measuring Quality Guidelines and Grading Rubric

By Day 7 in Week 5

In an 8 to 10 page paper, describe three rate based measurements of quality.

Select three rate based measurements of quality that you will use as the primary basis for this paper.

These measurements must relate to some aspect of clinical or service quality that directly relates to patient care or the patient’s experience of care.  For the purposes of this assignment, an analysis of staffing levels is not permitted.  You can find useful information on quality indicators that are of interest to you on these websites and resources.  You may choose only one of the three measures to be some form of patient satisfaction measure.

Deconstruct each measure to include descriptions of the following:

• The definition of the measure
• The numerical description of how the measurement 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; differentiate between the actual rate and a percentile ranking.
• 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.

Describe the importance of each measure to a chosen clinical organization and setting.

Using these 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 hone in a particular healthplan, a multispecialty practice setting or a healthcare organization with both inpatient and outpatient/clinic settings. 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.

Relate each measure to patient safety, to the cost of poor quality, and to the overall cost of healthcare. Organizational and Systems Leadership for Quality Improvement NURS 8300.