Epidemiology can be applied not only to health, disease, and behaviors but the concepts can be applied to patient care! All healthcare organizations are responsible for monitoring quality-related incidents and collecting data to continuously improve care. Not only does the healthcare administrator want to discharge healthy patients, but quality is also tied to the financial health of the organization. Patient satisfaction, pain management, medication errors, 30-day readmissions, nosocomial infections, etc. must be monitored continuously so that decisions can be made quickly to resolve the problem.

FIRST students need to Complete Case Study 9.2. Explain your answers in full sentences (i.e. do not just answer "yes" or "no").

CASE STUDY 9.2: Impact of a Rapid Response System on Inpatient Mortality and Length of Stay

Deterioration of a patient's clinical condition in general medical units happens from time to time. Rapid response systems (RRSs) implemented to identify and treat deteriorating patients can make a big difference in health outcomes. This study examined the potential impact of an RRS that used an automated real-time clinical deterioration alert (RTCDA) in eight general medicine units at the Barnes-Jewish Hospital, a 1,250-bed academic medical center in St. Louis, Missouri. The RRS was implemented in 2006. The RTCDA was implemented in a staged manner in 2009.

The rapid response team comprises a registered nurse, a medical resident physician, and a respiratory therapist. The nurse on the rapid response team carries a hospital-issued mobile phone to which the automated system sends RTCDAs directly. The nurse must respond to an alert within 20 minutes to do triage and take necessary follow-up action. The RTCDA uses 398 clinical variables from the real-time central data repository and operates around the clock, 7 days a week to generate automated alerts regarding "at-risk" patients. To avoid "alert fatigue" resulting from a system that generates too many false positive alerts and to have a manageable number of alerts per hospital unit per day, the RTCDA is set to achieve 40% sensitivity of detection- that is, 40% of those patients who are truly at risk of clinical deterioration are correctly identified by the RTCDA.

The outcomes of interest in this study were a year-to-year decrease in mortality rate, cardiopulmonary arrests, and median LOS. Based on data from the eight general medicine units, retrospective statistical analysis used linear regression models to assess the strength of association between the intervention and each of the health outcomes while adjusting for extraneous factors such as comorbidities and patients' age and sex. To evaluate the impact of RRS and RTCDAs, the yearly hospital mortality, incidence of cardiopulmonary arrests, and median LOS data were compared from 2003 to 2014.

FIGURE 6.3 and FIGURE 9.4 show some of the findings of this study. FIRST students need to Complete Case Study 9.2 Explain your answers in full sentences (i.e. do not just answer "yes" or "no").

Questions

Question 1. Looking at FIGURE 9.3, what impact, if any, did the RRS and RTCDA system have on hospital mortality?

Question 2. Looking at FIGURE 9.4, what impact, if any, did the RRS and RTCDA system have on median hospital length of stay?

After answering questions for case study 9.2 using Figure 9.3 and 9.4, students need to visit this link or theAgency for Healthcare Research and Quality (AHRQ) State Snapshots(Links to an external site.)

This is the link: https:/hqrnet.ahrq.gov/inhqrdr/state/select

and follow the direction below to answer the questions below:

• Select one stateand select "dashboard" on the right
• Scroll down to "Priority Areas" and click on the different priority areas for detailed information.
• Indicate which state you chose and make at least three detailed observations concerning any areas in which this state has improved, stayed the same, or declined in healthcare quality since the baseline year.Where does this state need to devote resources for the improvement of quality?

Below is a screenshot of both FIGURE 9.3 and FIGURE 9.4 to answer questions for case study 9.2:

ons on 1. Looking at Figure 9.3, what impact, if any, did the RRS and on 2. Looking at Figure 9.4, what impact, if any, did the RRS and RTCDA system have on median hospital length Delete . . . 3.25 3.00 2.75 Hospital Mortality ( 2.50 Lens 2.25 2.00 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Study Year Solid line represents the mean value with the dotted lines depicting the upper and lower limits of the 95% confidence intervals. P = .002 for the year-to-year decrease in hospital mortality for patients admitted to the general medicine units. Edit E 9.3 Hospital mortality for January 1, 2003, through December 31, 2014, for the 8 general medicine units. d from. Kotel Mi, Heand I, Chen Y, Lu C. Martin N, Bailey T. Mortality and length of stay trends for tosion of SAGE Publications, Inc. 3.80 3.60 Median Hospital Length of Stay (Days) 3.40 Share .20 3.00 Hospital length of stay sho 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 FIGURE 94 Hospital length period for patients admitte