Measurement of health care quality is an important stage on the way of improving health care standards. In most cases, patients are empowered to make reliable decisions and informed choices about where to seek good health care by referring to a hospital’s quality information (Aiken et al., 2012). The information about the quality of care makes the providers of health care improve their services. Many countries across the globe have recently prioritized on quality measurement in hospitals. As a result of the move by the governments to ensure quality in hospitals, many hospitals have begun the process of instituting and developing the requirements that are essential for measuring quality and submitting quality data reports both at the hospital and national level (Jha & Epstein). As the Sunlight Hospital administrator, I therefore envision my duty in ensuring the facility maintains high-quality health care standards that will increase efficiency and create value for the hospital as well as make it a hospital of choice.
Five Quality Measures
Quality measurement embraces the entire health care delivery system. The assessment starts from the physician level up to the health insurance level. The five quality measures include the following.
Structure measures. These measures evaluate the quality of infrastructure within a health care setting (Dimick, 2010). In this aspect, patients will base their choice on certain factors such as the availability of appropriate health care facilities and the sufficient number of staff and medical specialists to run the facilities. A patient may further want to know the staff’s capability and credentials in running the facilities. For example, a patient may be interested in knowing if the ICU or any department that deals with critical health matters has competent staff and intensive care specialists available at any time. Structure measures are further concerned with human resource operations, the structure of the hospital management, and the material resources, all of which are crucial fators in delivering high-quality care (Dimick, 2010). Patients who consider an admission for treating a serious disease may want to know the number of nursing hours that are provided for each patient. The other aspects include the evaluation of technology level in the hospital (Dimick, 2010). For example, a cancer patient may want to know if a given hospital has the latest cancer screening machine and if the machine is in operation before choosing a hospital for his cancer treatment.
Process measures. These measures evaluate various methods of treatment through which healthcare is delivered in a given hospital, such as surgeries, tests etc. (Dimick, 2010). In most cases, a patient will be concerned with the ability of a given hospital to screen, diagnose and manage a particular disease. Process measures enable patients to acquire information on the accuracy and timeliness of a given diagnosis, the appropriateness of the conducted therapies, and the complications that might occur during treatment (Dimick, 2010).
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Outcome measures. These measures provide an overall evaluation of patients’ health based on the health care they have received (Dimick, 2010). The measures give a review of the effect that the given health care has had on the patient’s functions and health status. Furthermore, outcome measures provide reliable feedback on whether the set goals and objectives of a given health care have been delivered (Dimick, 2010). For example, when choosing a hospital, a patient might seek data on the survival rate of those who have been admitted to the hospital with heart-related issues, or look at the outcomes for pneumonia treatments, or the outcomes of treatment for patients suffering from acute myocardial infarction (Dimick, 2010).
Patient experience-based measures. The given measures give adequate feedback on the experiences that the patients had when receiving treatment. Based on these experiences, a patient is able to know how clearly the information on a particular disease is articulated by a doctor, how fast a test result is delivered, how urgent an appointment with a doctor can be made, etc.
Overuse measures. These measures evaluate the extent to which ineffective, wasteful, or unjustified procedures and tests are prescribed to patients when they don’t need them as well as the eventual effects of such medical errors on the patients’ health (Jha & Epstein). For example, the measure will track the number of patients with uncomplicated back pains who were subjected to x-rays and MRIs or those with viral infections who were given antibiotics.
Thus, quality measures provide a good platform for patients in the process of choosing a health care institution.
Features of Health Care Organizations
The features that can be used to design a quality improvement plan in a healthcare organization include the following.
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Identification of the need for quality improvement. It is necessary to determine and evaluate the events that led to the need for improvement of quality before embarking on plan elaboration. The events in this context may include the need for a system upgrade, patient complaints, an increase of medical errors etc., which resulted in the reduction of care quality, which further led to a bad reputation with the community (Kaplan et al., 2010).
Practices and protocols to be adopted. Improving the quality of healthcare requires new practices and protocols to be adopted. These practices include new healthcare delivery procedures as well as adoption and implementation of new technologies (Kaplan et al., 2010). The practices and protocols are mainly geared towards reducing the number of medical errors and managing the flow of information within the organization, which is a vital feature to consider when designing a quality improvement plan.
Outcomes. The aspect of using the expected outcomes to measure the impact of the changes on quality improvement is very important for designing a quality improvement plan. These can include methods for tracking improved outcomes for patients, reduction in errors, among others (Kaplan et al., 2010).
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