Chelsea Millard
Performance Measures An intensive care unit (ICU), also referred to as a critical care unit, is a healthcare operating unit that treats persons who have been inflicted with life-threatening injuries and illnesses. Patients in an intensive care unit are observed closely by specially trained health care providers. Problems that are treated range from accidents to severe breathing problems. Patients are normally exposed to monitors, intravenous (IV) tubs, feeding tubes, catheters, and breathing machines. These particular items are used to extend a patient’s life, but infection risk can become common also. In an intensive care unit, many patients recover and are moved to a regular hospital room to receive care. Death is a common outcome for patients in an intensive care unit. If a patient’s family and health care providers have to make end-of-life decisions, advance directives will help the individuals come to a final decision (“Critical Care“). In the article “The Competitiveness and Balanced Scorecard of Health Care Companies,” the balanced scorecard has become an idea that has become influential to the business aspect. A balanced scorecard measures employee knowledge, relationship with customers, cultures of innovation, and change generated success. Many businesses has improved their performance by improving processes and becoming more competitive in the market (Mavlutova, Babauska, 2013). In the article “Pabon Lasso and Data Envelopment Analysis: A Complementary Approach to Hospital Performance Measurement,” general hospitals in Iranian Eastern Azerbijan Province applied Data Envelopment Analysis and Pabon Lasso Model to calculate the efficiency of the facilities. These two methods are performance measurements, which are beneficial to health care organizations in terms of quality improvement. The Pabon Lasso Model is used to comparing and understanding the efficiency of the hospital based on bed occupancy rate, bed turnover rate, and average length of stay. It displays four quadrants and the average hospitals are located in the center. The Data Envelopment Analysis is used to compare inputs to outputs. The comparison of inputs and outputs is used to see how efficient a hospital is. If a healthcare organization has a score of one, the organization is efficient. If a healthcare organization has a score less than one and more than zero, the organization is not efficient. The Data Envelopment Analysis is able to handle difficult environments that use various input types, is related to best practice, does not require a relationship between inputs and outputs, assists inefficient hospitals with a sense of efficiency, and can include either constant or variable returns to sale assumption (Mehtrak, Yusefzadeh, & Jaafaripooyan, 2014). In the article “Dashboard Systems: Implementing Pharacometrics from Bench to Bedside,” dashboard systems provide information in a format that is easy to understand. Patient management dashboards could gain information from electronic medical records, laboratories, clinicians, and patients and deliver the information as if it was all gained from the same foundation. Dashboard systems can become important for the improvement of patient outcome, clinical efficiency, and healthcare cost containment. In drug development, dashboard systems limits requirement of resources and increases model updates as more statistics and numbers are collected (Mould, Upton, & Wojciechowski). The intensive care unit has measurement categories of safety, data timeliness, efficiency, and efficacy. Patient safety is the state of being free from accidents and injuries. In an intensive care unit, healthcare employees must make sure patients are not experiencing any accidents or injuries. In order for a health care organization to provide care that puts patient safety first, they must: construct a culture of patient safety, have leadership that establishes a blameless environment, survey and monitor for adverse and tragic events, and continuously engineer patient safety into healthcare procedures (Ralston & Larson, 2005). Three performance measures that can be used for patient safety are safety culture assessment, quality of hospital services, and patient experience of care. Safety culture assessment measure individual and group values, attitudes, perceptions, competencies, and patterns of behavior that determine the commitment to, and the style and proficiency of, an organization’s health and safety management (Neiva & Sorra, 2003). Quality of hospital services measures how well a healthcare organizational department reaches health outcomes. Patient experience of care measures how well a healthcare organization delivers care, based on the patient. Data timeliness is the length of time it takes to compile a data segment. Data timeliness is very important because data that is considered accurate today may not be accurate tomorrow because data is constantly changing. Certain patient information must be updated over time, such as patient name, address, and date of birth. Female patients’ names will be less flexible than male patients. Addresses are flexible, due to the fact that addresses change every few years on average. In order for health care organizations to be measured correctly, the data that is measured must be considered correct via timeliness (Lorence, 2003). Three performance measures that can be used for data timeliness are quality of hospital services, patient experience of care, and disparities in performance. Efficiency is the way in which resources are used in accomplish a certain outcome. Efficiency increases when resources are decreased in accomplishing a certain outcome. Inefficient care uses more resources than needed and is considered wasteful (Ransom, Joshi, Nash, & Ransom, 2008). Three performance measures that can be used for efficiency are cost of healthcare services, disparities in performance, and quality of hospital services. Efficacy is when a clinical intervention has produced a reliable outcome when other puzzling fact are constant (Ransom, Joshi, Nash, & Ransom, 2008). Three performance measures that can be used for efficiency are patient experience of care, quality of physician services, and disparities in performance.
References
Critical Care. (n.d.). In MedlinePlus. Retrieved from http://www.nlm.nih.gov/medlineplus/criticalcare.html
Lorence, D. (2003) Measuring Disparities in Information Capture Timeliness Across Healthcare Settings: Effects on Data Quality. In Journal of Medical Systems. Retrieved from http://link.springer.com/article/10.1023/A:1025655721518
Mavlutova, I. & Babauska, S. (2013). The Competitiveness and Balanced Scorecard of Health Care Companies. In Synergia International Journal of Synergy and Research. Retrieved from http://www.toknowpress.net/ISSN/2083- 0025/vol_2_no_2_pap_4_The_competitiveness.PDF
Mehrtak, M., Yusefzadeh, H., Jaafaripooyan, E. (2014). Pabon Lasso and Data Enveloppment Analysis: A Complementary Approach to Hospital Performance Measurement. In Global Journal of Health Science. Retrieved from http://www.ccsenet.org/journal/index.php/gjhs/article/view/34689/20265
Mould, D., Upton, R., & Wojciechowski, J. (2014). Dashboard Systems: Implementing Pharmacometrics from Bench to Bedside. In The American Association of Pharmaceutical Scientists Journal. Retrieved from http://link.springer.com/article/10.1208/s12248-014-9632-5
Nieva, V. & Sorra, J. (2003). Safety culture assessment: a tool for improving patient safety in healthcare organizations. In BMJ Quality & Safety. Retrieved from http://qualitysafety.bmj.com/content/12/suppl_2/ii17.full
Ralston, J. & Larson, E. (2005). Crossing to Safety: Transforming Healthcare Organizations for Patient Safety. In Center for Health Studies, Group Health Cooperative. Retrieved from http://jpgmonline.com/article.asp?issn=0022- 3859;year=2005;volume=51;issue=1;spage=61;epage=67;aulast=Ralston

Performance Measures