Quality and Infection Prevention: Partnering for Improved Outcomes
Introduction
Prevention of healthcare-associated infections (HAIs) is considered the model for patient safety and quality of care. According to the Institute of Medicine(IOM) report “To Err is Human” in 1999, hospital adverse events including HAIs are responsible for 44,000-98,000 deaths annually in the United States (US). The IOM 2003 publication “Transforming Health Care Quality” included prevention of HAIs as one of the priorities for national action.
HAIs burden patients, complicate treatments, prolong hospital stays, increase costs, and can be life-threatening. Up to 15% of patients develop an infection while hospitalized. The Centers for Disease Control and Prevention (CDC) report “Antibiotic Resistance Threats in the United States, 2013” highlights that at least 2 million Americans acquire severe antibiotic-resistant infections each year, which results in 23,000 deaths annually. Most deaths occur in health care settings such as hospitals. This CDC report recommends attempting to prevent these infections through appropriate antibiotic use and infection prevention practices. HAIs are now the fifth leading cause of death in US acute-care hospitals. The human suffering and financial burden associated with these infections are significant. Recent reports have estimated that US health care system direct costs that can be attributed to HAIs range from $9.8 billion to $45 billion. Beyond direct financial costs, HAIs also contribute to significantly to indirect societal costs and reduced quality of life.
We now know that a significant percentage of HAIs can be prevented by use of evidence-based strategies. One of the first studies was the CDC’s Study on the Efficacy of Nosocomial Infection Control (SENIC) project published in 1985 which estimated 30-50% of most HAIs were preventable with effective surveillance and control programs. More recent studies have involved simultaneous implementation of evidence-based practices called “bundles”. A bundle is best defined as a grouping of evidenced-based practices that individually improve care, but collectively achieve a much greater reduction. Bundles have been used successfully in reducing catheter line associated bloodstream infections (CLABSIs), ventilator-associated pneumonia (VAPs), catheter-associated urinary tract infections (CAUTIs), and surgical sites infections (SSIs). In 2011, Umscheid and colleagues estimated that as many as 65-70% of cases of CLABSIs and CAUTIs were preventable and up to 55% of cases of VAPs and SSIs were also preventable. CAUTI was considered to be the most preventable with CLABSIs the highest number of preventable deaths and the highest cost impact.
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Federal, State, and Regulatory Response
During the last decade promotion of patient safety has encouraged regulators to target HAIs as a preventable adverse event. In March 2008, the Governmental Accountability Office (GAO) released a report which concluded that there was a lack of coordination among agencies in the Department of Health and Human Service (HHS) to monitor and prevent HAIs. In response to the GAO report, HHS lead an effort to develop a national action plan to prevent HAIs. For acute care the 5-year HHS Action Plan target called for a 50% reduction in CLABSIs, 25% reduction in CAUTIs, MRSA bacteremia, and SSIs. For CDI a 30% reduction was set for the target.
As a result, in the last several years, major changes in the US healthcare have impacted HAI prevention. These developments include improved interdepartmental coordination of federal efforts aimed at HAI prevention, posting of hospital-specific HAI rates on public websites to promote transparency, and linking of hospital-specific HAI performance to financial reimbursement as a strategy to motivate hospitals’ HAI prevention efforts. As a consequence of the Deficit Reduction Act of 2005 and the Affordable Care Act of 2010, hospitals participating in the Centers for Medicare and Medicaid Services (CMS) Inpatient Prospective Payment System (IPPS) have been required since 2011 to report CLABSIs among patients in intensive care units (ICUs) to the CDC’s National Healthcare Safety Network (NHSN) in order to qualify for annual payment updates. Since 2012, hospital-specific CLABSI rates have been publicly reported. Additional data reported through NHSN to CMS is occurring including SSI rates following abdominal hysterectomy and colon surgery, CAUTI in the ICU, methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections, Clostridium difficile infections (CDI), receipt of influenza vaccination by healthcare personnel and in 2015 CLABSI and CAUTI house wide. All these are now publicly reported.
State health department involvement has also increased including passage of mandatory state HAIs reporting many exceeding CMS requirements. Although individual facilities are ultimately responsible for execution in preventing HAIs, public health can play a vital role in developing regional responses and support. Passage of the 2009 Omnibus Bill required states receiving Preventive Health and Health Services (PHHS) block grant funds to certify they will submit a plan to secretary of HHS no later than January 2010 consistent with the HHS Action Plan to prevent HAIs. This would include developing a plan to build and improve health department workforce, training, and tools necessary to meet HAI prevention and control needs.
With help from CDC, all 50 states developed and implemented state action plans. Federal funds provided for dedicated staff within the state health department including HAI coordinators to oversee implementation of the state HAI action plan. As a result of these actions, the state expanded activities to not simply setting targets but to help with implementation prevention efforts. State health departments have become important partners working with CDC to advance the science of HAI surveillance and provide data validation to improve confidence in the data. In addition, the model for financing healthcare delivery is undergoing significant changes. The old fee-for-service model is transitioning to a value-based payment system. Along with other quality metrics, HAI data will be used to determine hospital-specific CMS reimbursement levels as part of value-based purchasing, thereby shifting some of the costs associated with HAIs from CMS to hospitals.
Measurement
In the past healthcare has lacked the ability to accurately measure harm including HAIs. Measuring the quality of care and using measurement to promote improvement is critical. Chassin et al proposed criteria for accountability measures. Firstly, a measure must have strong evidence that the care process leads to better outcomes. Knowledge must be available linking the relationship between process and outcomes. Secondly, the measure accurately captures whether the evidenced-based process was in fact provided. Lastly, implementing the measure should have little chance of creating unintended consequences.
In terms of HAIs, monitoring performance is necessary in evaluating effectiveness of interventions. Standardization of surveillance methods, definitions, and outcomes risk-adjusted are key for meaningful information. Based on the HHS national action plan there has been increased harmonization of state and federal HAI reporting. For HAIs, the CDC has created valid and reliable risk-adjusted outcome measures that can provide meaningful comparisons. Most of these measures have been approved by the National Quality Forum (NQF) for public reporting. CDC’s NHSN is the nation’s most widely used HAI tracking system. NHSN provides facilities, states, regions, and the nation with data needed to identify opportunities, measure progress of prevention efforts, and ultimately eliminate preventable HAIs. NHSN now serves over 17,000 medical facilities tracking HAIs. Current participants include acute care hospitals, long-term acute care hospitals, psychiatric hospitals, rehabilitation hospitals, outpatient dialysis centers, ambulatory surgery centers, and nursing homes, with hospitals and dialysis facilities representing the majority of facilities reporting data.
The CDC has developed the standard infection ratio (SIR), a statistic used to track HAIs over time to compare observed number of infections over predicted number of infections based on national aggregate data risk adjusted for key risk factors. A SIR over 1 indicates rates greater than predicted while a SIR less than 1 represent rates below predicted. Baseline periods for acute care hospitals were 2006-2011 for CLABSI and SSIs, 2009 for CAUTIs, and 2010-2011 for CDI. Among long-term acute care hospitals (LTAHs) and inpatient rehabilitation facilities the baseline period was 2013 for both CLABSIs and CAUTIs. The current HAI data is being shared with CMS and is now part of the healthcare quality measurement dataset made publicly available on the CMS Hospital Compare website.
HAI Prevention Progress Report
The most recent HAI report was published in 2016 based on 2014 data. For acute care hospitals, CLABSIs decreased by 50% – the only HAI meeting the HHS Action Plan target. The mean SIR is currently 0.495. For CAUTIs, unfortunately, there was no change compared to baseline, but there was a 5% reduction from 2013-2014. There was a 13% reduction for MRSA bacteremia but only 8% reduction for CDIs compared to baseline. For CDI, more concerning was an increase of 4% between 2013-2014. For SSIs for 10 selected procedures there has been a 17% overall reduction. For hysterectomies and colons which are nationally mandated and publicly reported, there has been a 17% and 2% reduction respectively. For hip and knee arthroplasties there has been a 22% and 41% reduction and for coronary artery bypass surgery there has been a 45% reduction in SSIs.
For LTACH, for the first year there was a 9% reduction in CLABSIs and a 11% reduction in CAUTIs. For inpatient rehabilitation facilities there was a 14% reduction in CAUTIs compared to baseline.
Translating Evidence into Practice and Behavioral Change
Understanding the evidenced-based interventions for each HAI forms the foundation for HAI prevention. However, equally important is how to translate these interventions into reliable and sustainable practices. To improve compliance, we need to consider both the technical and adaptive work including human behavioral science. Adaptive work means changing healthcare worker attitudes, beliefs, and behavior, with behavior best described as a function of healthcare worker’s perceptions. Understanding these variables is important to foster a culture of safety and improving healthcare worker engagement. Therefore, translating knowledge into routine reliable sustainable practices requires an approach to address both the technical and the adaptive which fosters both engagement and ownership at the local level.
The group at John Hopkins have proposed the “Four Es.” Engagement to inspire key healthcare leaders to take ownership and to support the evidenced-based interventions. Education to motivate healthcare workers so they understand why these interventions are so important. Execution to assure that evidence-based interventions are hard wired at the local level and become standardized care processes. Lastly, evaluation to measure whether in fact the intervention is successful. Programs that address these principles combined with improved teamwork and safety culture have been associated with reduced HAIs, decreased mortality, decreased costs, higher employee satisfaction, and lower healthcare worker turnover rates.
Future Directions and Conclusion
Along with HAI prevention, healthcare facilities must implement effective antimicrobial stewardship programs (ASPs) across the continuum of care. The primary goal of ASPs is to optimize outcomes and reduce adverse events. This can be accomplished using antibiotics for an appropriate indication, dose, and duration. Antibiotic exposure is recognized as the most important modifiable risk factor for CDI and as well as in selecting for antimicrobial resistance.
It is estimated that ~25% of HAIs reported from LTACHs were caused by multi-drug resistant organisms (MDROs). In addition, the incidence of CDI is higher in LTACHs compared to acute care. One factor is patient transfer from acute care hospitals to LTACHs and back again. LTACHs can also transmit or amplify AR within the community. Therefore, the CDC has recommended facilities on a community or regional basis work together for detection, prevention, and response to emerging pathogens including MDROs. Through collaboration, communities can have a larger impact on preventing transmission and infections with MDROs than hospitals working alone.
Lastly, the CDC and its partners have published new HHS suggested targets for HAI reduction by December 2020 using 2015 HNSN HAI rates as the new baseline. The targets will be a 50% reduction in CLABSIs and MRSA bacteremia, a 30% reduction in CDIs and SSIs, and a 25% reduction in CAUTIs.
In conclusion, we now know a significant proportion of HAIs are preventable. The improvement using evidenced-based strategies has been impressive, but significant opportunities exist especially with CDIs and CAUTIs. We must continue to strive to execute effectively and continue to translate existing knowledge into reliable, sustainable, and widespread practice. Prevention of HAIs continues to be the model for patient safety and quality of care.
References
Yokoe, DS, Classen, D. “Improving patient safety through infection control: A new healthcare imperative”. Infect Control Hosp Epidemiol. vol. 29. 2008. pp. S3-S11.
Magill, S. S.. “Multistate point-prevalence survey of health care-associated infections”. N Engl J Med. vol. 370. 2014. pp. 1198-1208.
“Hospital Value-Based Purchasing”.
Umscheid, CA, Mitchell, MD, Doshi, JA. “Estimating the proportion of healthcare-associated infections that are reasonably preventable and the related mortality and costs”. Infect Control Hosp Epidemiol.. vol. 32. 2011. pp. 101-114.
Zimlichman, E.. “Health care-associated infections: a meta-analysis of costs and financial impact on the US health care system”. JAMA Intern Med. vol. 173. 2013. pp. 2039-2046.
Septimus, E, Yokoe, DS, Weinstein, RA. “Maintaining the momentum of change: the role of the 2014 updates to the compendium in preventing healthcare-associated infections”. Infect Control Hosp Epidemiol. vol. 35. 2014. pp. 460-463.
Lo, E., Nicolle, LE, Coffin, SE. “Strategies to prevent catheter-associated urinary tract infections in acute care hospitals: 2014 update”. Infect Control Hosp Epidemiol. vol. 35. 2014. pp. 464-479.
Marschall, J, Mermel, LA, Fakih, M. “Strategies to prevent central line-associated bloodstream infections in acute care hospitals: 2014 update”. Infect Control Hosp Epidemiol. vol. 35. 2014. pp. 753-71.
Klompas, M.. “Strategies to prevent ventilator-associated pneumonia in acute care hospitals: 2014 update”. Infect Control Hosp Epidemiol.. vol. 35 Suppl 2. 2014. pp. S133-154.
Anderson, DJ, Podgorny, K, Berrios-Torres, SJ. “Strategies to prevent surgical site infections in acute care hospitals: 2014 Update”. Infect Control Hosp Epidemiol.. vol. 35. 2014. pp. 605-627.
Dubberke, ER, Carling, P, Carrico, R. “Strategies to prevent clostridium dif?cile infections in acute care hospitals: 2014 Update”. Infect Control Hosp Epidemiol.. vol. 35. 2014. pp. 628-645.
Chassin, MR, Loeb, JM, Schmaltz, SP, Wachter, RM. “Accountability measures-Using meaurement to promote quality improvement”. N Eng J Med. vol. 363. 2010. pp. 683-688.
“Centers for Diseases Control and Prevention. Antibiotic Resistance Threats in the United States, 2016 Pages 54 of 114”.
Srinivasan, A, Craig, M, Cardo, D. “The power of policy change, federal collaboration, and state coordination in healthcare-associated infection prevention”. Clin Infect Dis. vol. 55. 2012. pp. 426-431.
Jeeva, RR, Wright, D. “Healthcare-associated infections: A national patient safety problem and coordinated response”. Med Care. vol. 52. 2014. pp. S4-S8.
Weiner, KM, Fridkin, SK, Aponte-Torres, Z. “Vital Signs: Preventing antibiotic-resistant infections in hospitals-United States, 2014”. MMWR. vol. 65. 2016. pp. 235-241.
Pronovost, P. “Navigating adaptive challenges in quality improvement”. BMJ Qual Safety.. vol. 20. 2011. pp. 560-563.
Sexton, JB, Berenholtz, SM, Goeschel, CA. “Assessing and improving safety climate in a large cohort of ICUs”. Crit Care Med. vol. 39. 2011. pp. 1-6.
Pronovost, PJ, Cleeman, JI, Wright, D, Srinivasan, A. “Fifteen years after To Err is Human: A success story to learn from”. BMJ Qual Safet. vol. 25. 2016. pp. 396-399.
Slayton, RB, Toth, D, Lee, BY. “Vital Signs: Estimated effects of a coordinated approach for action to reduce antibiotic-resistant infections in health care facilities-United States”. MMWR. vol. 64. 2015. pp. 826-831.
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This article originally appeared on Infectious Disease Advisor