The Efficacy of Quiet Zone In Reducing Medical Errors
Evidence-based practice (EBP) has garnered momentum as a transformative ideology in the healthcare industry. Nurses who possess Doctor of Nursing Practice (DNP) credentials conduct EBP, integrate research evidence into their consultancy, unite the evidence with a patient’s history, and merge everything back to the patient’s values. EBP has been shown to improve outcomes and reduce costs. EBP can be so radical that it can discard standards and practices that have existed for decades. One of the best ways to conduct EBP is through the PICOT question methodology. PICOT is an acronym for population, intervention, outcomes, and time. The population is the desired group for research, while the intervention is the treatment administered to the group. The comparison is the untreated group as in the classical control group in experimental research. The outcomes are the desired results based on the hypothesis, while the time is the investigation period. Typically, PICOT studies are conducted using existing literature such as journal databases.
Medical errors are one of the greatest threats to the healthcare industry. The most common medical errors include adverse drug effects, misdiagnosis, improper transfusions, falls, burns, mistaken patient identities, surgical injuries, and over/under treatment. Medical errors are a leading cause of hospital-acquired infections and have been shown to raise the cost of healthcare levels in billions of dollars. Causes of medical errors include communication problems, the inadequate flow of information, distractions, human error, patient-related sources, staffing workflow patterns, technical issues, organizations knowledge transfer, and flawed policies (Izadpanah et al., 2018). Nurses spend the most patient with the patient, and, naturally, the reduction of errors by nurses could significantly reduce overall medical errors in the industry.
Among the most affected nursing units in terms of medical errors are the acute units. According to Hague et al. (2018), hospital-acquired infections cause 100000 deaths in America annually. Four percent of patients in the US reported having acquired HCAIs out of a survey of 11282. The Patient Safety Authority, an organization that oversees patient data, said over 2.2 million medical error cases between 2004 and 2014 (Silva & Krishnamurthy, 2016). Since human error is a significant contributor to medical errors, it seems practical that reducing disruptions in nursing units could significantly reduce errors.
Hospitals have strived to improve quality and efficiency for several decades through various strategies. Still, many Americans die annually due to preventable medical errors. Medical errors cost the US 19.5 billion dollars in 2008, with 17 billion coming from associated additional medical bills (Cakmak et al., 2017). These are staggering numbers that could hypothetically be avoided using evidence-based practice. Much literature has been written about the causes and the cost because it is a severe problem. Nurses constitute the biggest proportion of healthcare workers; nurses spend the most time with the patient, much of which includes intimate contact. Some medical errors, such as mistaken patient identity, could be alleviated by eliminating distractions when nurses carry out sensitive activities.
Current State of Practice
The contribution of distractions and interruptions to human error has been well documented. Various methods have been employed in reducing distractions, but there is not much literature on the efficacy of such practices. According to Flynn (2016), strategies that have been implemented include hourly patient rounds, signage to indicate no interruption, ‘quiet zones’ in medication rooms, limiting calls to nurses during medication administration, and phone call triage scripts. The quiet zone experiment was implemented in 2 progressive cardiac care units (PCCUs) with controls. The research showed that interruptions dropped from 24% to 4%, with medication errors falling to 3% from 11% (Flynn et al., 2016). Unfortunately, in my unit, many medical errors have been reported, including by myself. The hospital has implemented various strategies to reduce medical errors but not specifically on reducing distractions. Evidence of the efficacy of quiet zones would help raise awareness for acute care units.
Picot Question and Purpose of the Paper
A PICOT question is used to provide evidence-based research solutions to a problem. Therefore, the first step in delivering EBP is identifying the problem and formulating it into a PICOT question (Eriksen & Frandsen, 2018). In this case, the population identified is acute care nurses, while the intervention is the introduction of quiet zones with the desired outcome of reducing medical errors. Even though the time component is never mandatory, this intervention would be administered for one month. Therefore, the PICOT question is, does the introduction of quiet zones for one month help reduce medical errors for acute care nurses? The purpose of the study is to provide evidence that practice has been tried elsewhere and shown to provide the desired outcomes.
The key term for the population of interest was acute care since adding the word ” nurse ” would be too specific. Searching acute care in PubMed yielded 203,881 results. No alternative terms were used for this result. The key search term for the intervention was quiet zone or no interruption zone as a synonym. Combining these two terms using the AND operator yielded two results. On the other hand, using a no interruption zone in place of a ‘quiet zone’ gave eight results. Adding the third term of “medical error” yielded no results.
In searching the Cochrane Library, the UI provided input options for each picot item using AND, OR, and NOT operators. Searching “acute care” yielded 244 Cochrane reviews, 30cochrane protocols results, and 2080 trials. A combination of “acute care” and “quiet zone” OR “no interruption zone” yielded only one result that had nothing to do with the topic of investigation. As one would expect, adding a third term into the search criteria on Cochrane would deliver zero results
CINAHL had the most well-developed UI for conducting an advanced search. For a PICOT option such as population, the option for entering alternative terms using the OR operand could be added horizontally. For example, the results for searching the key term “acute care” alone yielded 278300 search results. After refining and adding “quiet zone” OR “no interruption zone,” the results narrowed down drastically to just 6. After adding the search term for outcome in “medical error,” the search results were zero.
Web of Science
The search on the Web of Science can be conducted on the core databases but can also be refined using specific databases such as biological databases, Medline, or Russian Science. For this particular problem, the core database was used. For example, searching “acute care” yielded 78344 results, and after combining with “quiet zone,” using the AND operator yielded eight results. A more refined search with key terms “acute care” AND “quiet zone or no interruption zone” AND “reduced medical error” or “medical error” yielded no results indicating that it was too specific.
The above search results highlight the weaknesses of advanced database searches. Sometimes it is easier to obtain an article that suits a specific need without an advanced database search by simply typing a phrase such as “quiet zones reduce medical errors” on Google Scholar or even on a general Google search. This search on Google yields beneficial results that provide more evidence of the usefulness of quiet zones than the more advanced databases. This is likely because Google search utilizes AI and can generate results from a general idea as opposed to Boolean logical operands that require exact results.
Evidence-based research is a vital tool in medicine and, more specifically, nursing. EBP has been recognized as crucial in enhancing healthcare quality and improving patient outcomes. EBP may differ from nursing research in the end goal, with the latter aiming to augment the body of knowledge, but research is being conducted to translate evidence into practice. One of the most trusted methodologies of conducting EVB research is using the PICOT strategy. This paper attempted to demonstrate how the methodology could be used to provide evidence that quiet zones are essential in reducing medical errors in acute care units. Four databases were used: PubMed, Cinahl, Cochrane Library, and Web of Science. It was demonstrated that adding more search terms provided lesser results as the search narrowed down. While the search did not yield specific evidence for the use of quiet zones for acute care units, there is documented evidence that the practice works, but the advanced features would not find evidence of application in the population of choice.
Cakmak, C., Demir, H., & Kidak, L. B. (2017). A research on examination of medical errors through court judgments. Journal of Turgut Ozal Medical Center, 24(4), 443-449.
Eriksen, M. B., & Frandsen, T. F. (2018). The impact of patient, intervention, comparison, outcome (Pico) as a search strategy tool on literature search quality: A systematic review. Journal of the Medical Library Association, 106(4). Web.
Flynn, F., Evanish, J. Q., Fernald, J. M., Hutchinson, D. E., & Lefaiver, C. (2016). Progressive care nurses improving patient safety by limiting interruptions during medication administration. Critical Care Nurse, 36(4), 19–35. Web.
Haque, M., Sartelli, M., McKimm, J., & Abu Bakar, M. (2018). Healthcare-associated infections – an overview. Infection and drug resistance, 11, 2321–2333. Web.
Izadpanah, F., Nikfar, S., Bakhshi Imcheh, F., Amini, M., & Zargaran, M. (2018). Assessment of Frequency and Causes of Medication Errors in Pediatrics and Emergency Wards of Teaching Hospitals Affiliated to Tehran University of Medical Sciences (24 Hospitals). Journal of medicine and life, 11(4), 299–305. Web.
Silva, B. A., & Krishnamurthy, M. (2016). The alarming reality of medication error: A patient case and review of Pennsylvania and National data. Journal of Community Hospital Internal Medicine Perspectives, 6(4), 31758. Web.