Healthcare Quality Outcomes - Assignment Example

In the preliminary study by Cowing, Davino-Ramaya, Ramaya, and Szmerekovsky (2009), a new, comprehensive model correlating healthcare quality outcomes with the psychosocial components of both clinicians and patients, as well as the business management perspective of healthcare organizations has been proposed. This is envisioned to provide organizations with better knowledge of the impact of various operational improvement strategies and to allow them to choose the strategies best suit their goals and resources.

As a result, the model shows that clinical outcomes are not enough to comprehensively define healthcare performance. It recognizes that subjective assessments such as patient satisfaction are also needed to accurately determine healthcare performance. In this case, the establishment of a clinician-patient relationship is of primary importance in building the patient's perception of quality and satisfaction with care. It is thus in the hands of healthcare organizations to create strategies to strengthen this relationship and monitor patient satisfaction. With these findings, the researchers suggest that new healthcare quality outcome survey tools be made to take into account the effect of patient satisfaction and to provide accurate information with regard to healthcare performance.

CURRENT STATE OF OUTCOMES RESEARCH
It is now clear that outcomes research such as the one above is important in accurately measuring performance and subsequently improving healthcare quality outcomes. These are interrelated as identifying indicators of quality and performance are the ultimate goals of outcomes research.

The study of Perrin (2002) looked into the current situation of outcomes research and the strategies that can be implemented to improve it. Although many academicians have been involved in outcomes research, not a lot become successful, because current practice in the healthcare sector overlooks the fact that merely defining and measuring health outcomes does not connote successful outcome research. A significant part of understanding outcomes and arriving at specific outcomes is in knowing how the independent variables, the healthcare organization, patients, or clinicians, can produce these outcomes. It is thus important to come up with models and methods that can infer the relation of specific healthcare systems with healthcare quality outcomes. As such, outcomes research needs to be given resources that are sufficient to develop new methods and models of inference.

The study further suggested that randomized clinical trials (RCT) relating a specific intervention to a predetermined outcome is an example of good outcomes research because it can be designed to answer a cause-and-effect relation. However, conducting RCT needs a significant resource investment, especially when doing it to answer questions about a system as complex as the healthcare system. A large data set is also needed to draw significant conclusions from the data. The data acquisition processes such as response rates and study duration should also be equally extensive.

In conclusion, the limitations in resources are the main deterrents in preventing researchers from making sensible outcomes research that determine the effects of particular components of healthcare systems on outcome measures.

INFORMATION FROM OUTCOME MEASUREMENT SYSTEMS
Healthcare quality outcome measures become more powerful for healthcare organizations as patients are now more equipped in choosing their healthcare providers because of the vast amount of information about the healthcare quality outcomes of hospitals that they have access to.

In an effort by Micheletti, Shalala, and Goodall (1998) to provide ways for quality improvement professionals to better evaluate quality outcomes measurement systems and to stay ahead of the highly critical managed care payers, it was found that more sophisticated risk- and severity-adjusted data instead of raw outcomes data should be used. But before that, the performance outcome measurement system should be able to measure up-to-date not only clinical outcomes but patient satisfaction and financial health as well. This can be in the form of comparative outcomes data, which compares actual and expected outcomes. In addition, merging the clinical and financial outcomes information and selling it to potential patients is a good strategy for ensuring the best healthcare service while maintaining the organization’s financial health. Finally, the data should be more accessible, so that the clinicians’ and payers’ acceptance of the data is increased. Conclusively, a comprehensive, updated, and manipulated outcomes measure is better in allowing healthcare organizations in providing the payers its best image and competitive edge.

CONCLUSION
The three studies are unanimous in recognizing the importance of patient satisfaction and financial status in measuring the performance outcomes of healthcare organizations. Unfortunately, they recognize that the current methods of measuring healthcare quality outcomes need improvement, either by new models that correlate outcomes with its effectors, physicians, patients, and healthcare organization, as suggested by Cowing et al. (2006) and Perrin (2002), or by a more comprehensive measurement system implemented by healthcare organizations.  Read More