Journal Entry #3: Lessons Learned

                       Journal Entry #3: Lessons Learned

 

                                                                                                                                 Alanna M. Schauer

                                                                                                             Module 3: Standard Databases Used

                                                                                                                                 in Healthcare Delivery

Van Le, H., Beach, K., Powell, G., Pattishall, E., Ryan, P., & Mera, R. (2013). Performance of a semi-

                automated approach for risk estimation using a common data model for longitudinal

                healthcare databases. Statistical Methods In Medical Research, 22(1).   

                doi:10.1177/0962280211403599
                                             

                                                       Lessons Learned

            This week's discussion really demonstrated the adaptability, significance and importance of databases. The article I reviewed demonstrates the adaptability of databases to meet the needs of many healthcare and research entities especially pharmaceutical companies. Drug safety signals affect patient care and determining patterns in drug interactions or adverse reactions can save lives.   This database creation took a passive data collection system and converted it to current active database with real time complications and improved patient outcomes.  

            Joy taught me that the benefits of taking every day data and placing it in a platform that is useful for involved practitioners'. Determining if your practice is appropriate and above par, benchmarking remains the fairest manner in which to identify your national ratings. Benchmarking is crucial for regulating and accrediting agencies requirements and to ensure you are providing quality patient care and can back it up with data. You need to ensure they are accurate and reliable so that quality health content is presented.  

            Fiona's article brought us exciting news that the CDC, AHA, and the NIH will be joining forces in order to pool their statistics and provide a large population of people and data. The database information collected will be massive and bring forth increased statistical analysis for researchers, clinicians, health care policy makers and media personnel. This will reduce the duplication of services and make the data collection more accurate. A database with a large compilation will ensure that collecting processes are similar and the vocabulary is similar for consistency.

            Rita supplied us with some helpful databases to increase the time to look up and research a topic while staying close to the evidence based information needed. I learned that it functions like EBSCOhost and CINAHL and uses the Boolean phrases which make the process simpler. TRIP blog and saves your searches for a period of time and hyperlinks to full text, abstracts, or sites such as AHRQ when you require the full article or want to review the AHRQ criteria. Clinicians like Me allow you to search while staying close to your specialty using keywords.

            Adam focused on the Population Health Management (PHM) topic and the necessity for the control and containment of the escalating health care costs. They are trying to use research and evidence based practice to make these financial changes and that they compared the participants costs and savings and their statistical difference. The concerns of PHM are the management of chronic health conditions and educate the patients and their families to improve patient outcomes and improve quality of life.