The Multiple Chronic Condition Measurement Framework

For a home health nurse, however, a more practicable metric would be the Multiple Chronic Condition Measurement Framework. Even though this metric was designed for use with people with multiple chronic illnesses, it is also effective in managing single chronic illness cases. It is applicable to a home health nurse because individuals can choose to receive care in various sites. Examples of these sites, and which make it most applicable to a home health nurse are nursing homes, community places (includes workplace and school), and formal and informal homes (National Quality Forum, 2012). The nurse could use these visits as an opportunity to conduct an assessment of factors around the home that could affect the proper management of the disease. This way, proper care, and advice would be given.

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How These Metrics Facilitate and Improve Management of Chronic Diseases

One of the many results of Health IT for Improved Chronic Disease Management is that healthcare providers will have quality information that is easily accessed to provide optimum care to their patients. Since this information can even be shared between several facilities, patient records will be available wherever the patient is receiving care from.

On the other hand, Multiple Chronic Condition Measurement Framework metric used by a home care nurse can lead to a 50% reduction in cases of unplanned hospital admissions. This would also result in 50% reduction in bed day rates for patients with chronic diseases (Department of Health & Children, n.d.).

Efficiency of Current Automated Trigger Systems

Automated trigger systems are systems used to safely detect and measure events in a health care system. One of the biggest advantages of these systems is that supervision can be done retrospectively or prospectively (Batalden & Davidoff, 2007). While greatly effective in giving timely alerts that could mean the difference between life and death, these systems could cause alert fatigue, which is a situation where users become overwhelmed and thus become unresponsive to alerts (Lee, Mejia, Senior & Jose, 2010). These systems enable proactive responses that are useful when educating patients on disease management.

Conclusion

Managing chronic diseases is within reach only if interest is spurred within all parties. This is a war that cannot be won without considerable input. If the trends remain uncontrolled, future generations stand to suffer even more consequences from these diseases.

Automated systems have been designed to help in detection, management, and treatment of chronic diseases. Their capacity is however greatly underutilized. More work needs to be done if we are to tame chronic diseases.

References

AHRQ National Resource Center,. (2014). Health IT for Improved Chronic Disease Management. AHRQ National Resource Center. Retrieved 26 December 2015, from https://healthit.ahrq.gov/ahrq-funded-projects/emerging-lessons/health-it-improved-chronic-disease-management

Batalden, P., & Davidoff, F. (2007). What is "quality improvement" and how can it transform healthcare?. Quality And Safety In Health Care, 16(1), 2-3. http://dx.doi.org/10.1136/qshc.2006.022046

CDC,. (2015). Chronic Disease Prevention and Health Promotion. Retrieved 26 December 2015, from http://www.cdc.gov/chronicdisease/

Department of Health & Children,. Tackling Chronic Disease: A Policy Framework for the Management of Chronic Diseases (p. 16). Hawkins House Dublin 2.

Lee, E., Mejia, A., Senior, T., & Jose, J. (2010). Improving Patient Safety through Medical Alert Management: An Automated Decision Tool to Reduce Alert Fatigue (pp. 417421). AMIA Annual Symposium Proceedings.

National Quality Forum,. (2012). Multiple Chronic Conditions Measurement Framework (1st ed., pp. 9-10). Washington: National Quality Forum. Retrieved from http://www.qualityforum.org/Publications/2012/05/MCC_Measurement_Framework_Final_Report_document.aspx