Open Access
Review
Table 3
Literature survery in Epidemiology department
| Author and Year | Details of work done | Types of chart | Variables | Type of study | Country |
|---|---|---|---|---|---|
| Quesenberry [39] | Recommended the use of control charts i.e., Q charts to detect changes in nosocomial infection rates in hospitals. The ultimate aim of the article was to aware the readers about the modern statistical process control methods. With the help of these methods, nosocomial infection surveillance program became more effective because of time warning of the onsets of epidemics. | Q chart | Infections rate | Retrospective study | US |
| Gustafson [40] | The author reduced infection using risk adjusted quality control chart. The results showed that unadjusted control charts (c, p and u charts) were not effective in healthcare as these charts with 3 sigma limits had sensitivity less than 50% and for 2 sigma limits had specificity less than 50%. On the other hand, risk adjusted control chart performed much better based on standardized infection ratio. The author found that XMR Chart were most suitable as having sensitivity and specificity greater than 80%. So in this way, these findings suggested specific techniques and statistics that could make control charts more suitable and vtable and valuable for infection control. | P chart, Run chart, XMRchart | Standardized infection ratio | Retrospective study | US |
| Hanslik et al. [41] | The authors performed a pilot study during 1998 World Football Cup with the help of 553 sentinel general practitioners. The data related to the number of persons refereed to hospital, average number of cases of environmental, communicable and social diseases were collected daily by general practitioners and plotted on u chart. The parameters selected for the study remain under control with the use of control chart. | u chart | Number of patients | Longitudinal study | France |
| Arantes et al. [42] |
Recommended the use of SPC charts for the close monitoring of nosocomial infections (NI) in hospital. Results showed that mean NI incidence was 20 per 1000 patient days. The one out of control point was identified in July 2010 with an infection rate 63 per 1000 patient days which showed the period of epidemic. Finally, it can be concluded that use of SPC for controlling infection allowed for identification of uncommon variations in infection rate. This thing was made possible without the need of hypothesis testing and complicated calculations. | p chart | Number of nosocomial infections per thousand patient days | Longitudinal study | Brazil |
| Grant and Kim [43] | The authors explored the various ways to measure the important function of infection control process. The retrospective study was conducted for seven years. The chart utilized were XMR along with Pearson's correlation coefficient. As a result of seven years of study, consultation process became more efficient. The reason for this increase in efficiency could be attributed to increase in number of questions which lead to decrease in duration to accomplish closure. | XMR chart | Number and duration of infection control consultations | Retrospective study | US |
| Limaye et al. [44] | Identified the utility of control chart for monitoring infections associated with hospital and recommendation on how to use chart for infection surveillance. They recommended the use of u chart for infection control as u chart was simple to construct, easy to interpret. It could also help to deal with condition like varying number of patient days, ventilator days because this chart took into account variable sample size. | CUSUM, g chart, u chart |
Number of Hospital associated infections | Longitudinal study | US |
| Curran et al. [45] | The authors made use of SPC charts in order to reduce meticillin resistant staphylococcus aureus. The authors divided seventy five wards in twenty four hospitals into three categories. First category included ward receiving SPC chart feedback, second category included wards with SPC chart feedback with structured diagnostic tools and finally third category included wards which received neither type of feedback. The authors found that there was decrement of 32.3% and 19.6% and 23.1 for ward receiving SPC feedback, SPC & diagnostic feedback and no feedback respectively. Finally, the authors concluded the control charts as a valuable tool for disseminating hospital infection data. | p chart | Percentage of errors | Retrospective study | UK |
| Harbarth et al. [46] | Investigated the effect of an early Methicillin-Resistant Staphylococcus aureus (MRSA) on the patient's infection rate. The study was conducted between July 2004 and May 2006 among 21,754 patients. The two MRSA control strategies i.e., standard infection control alone and rapid screening on admission with standard infection control were compared. Finally it was concluded that rapid MRSA admission screening strategy does not reduce surgical site infection with low rates of MRSA infection | Run chart | MRSA infections per 1000 patients days | Retrospective Study | Switzerland |
| Wiemken et al. [47] | Suggested the development of the application and demonstrate application using simulated data for infection prevention. It was concluded that process control charts can easily be developed based on individual facility needs using freely available software. They outlined the importance of implementing an easy to use and free available software packages for measuring quality improvement in healthcare. | p chart | Hand hygiene compliant per 100 observations | Retrospective study | US |
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