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The Working Hours of Hospital Staff Nurses and Patient Safety

16 Feb 2017Health Essays

Problem

Rogers et al (2004) attempted to identify and correlate the effect of the work shifts and overtime of registered nurses (RNs) on patient safety and health care delivery. Nurses are an indispensable member of the healthcare arena (or institutions). Unfortunately, healthcare, according to medical statistics, are undergoing crisis in terms of the number of health-providers and the legalities of palliative care; many health practitioners have been a victim or recipient of the Medical Tort Bill owing to their “carelessness,” “ineptitude,” “incompetence,” etc. The Board of Regents has liability for regulating the flows in nursing practice although the number of hours is not within the scope of their department.

The hours of ‘voluntary’ work on a per day or a per week basis in not regulated either at a state level either, with only a few states such as California, Maine, New Jersey, and Oregon following the strict non-mandatory overtime bills. It has been generally recognized by the medical workforce that a stressful, short-staffed working environment can promote circumstances of medical malpractice resulting from negligence. The Regents argued over this subject comprehensively from 1996-97 within a report on the probable effects of the environment on medical malpractice acts by the RNs. The reactionary or the report was more of a response due to increase of litigation charges involving medical negligence [of the nurses], web/media-hyped medical errors, bad rumors comments/complaints on palliative care and of course, decreasing number of nurses (2000 New York State Board of Regents Strategic Plan). The lack of protectorate policies recognizing the importance ‘job hours maxima’ is a huge concern since it creates a potential hazard, specifically, to patient safety and to the overall quality of health care delivery system. Resident physicians, from their elicited perspective on patient-safety related events indicate that there is a direct correlation between the excessive work hours, sleep deprivation and work-related mistakes.

Prior to the conduction of Rogers et al (2004), the study on the effect of work hours is limited with several literatures focusing on ‘shift-working’ analysis, hence the presumed ‘gray’ area for the study. Study Purpose The general purpose of the study is to determine if there is a correlation between the working hours of hospital staff nurses and their frequency of work-related errors. Staffing patterns are also analyzed. The effect of factors like age, sex, marital status, working experience, ethnicity and working environment—hospital size, type, localization—were also assessed in relation to error-related frequency.

Research Question(s)

The main research query of is “Is there a correlation between the working hours of hospital staff nurses and their frequency of work-errors?” There is also if the following factors — age, sex, marital status, working experience, ethnicity and working environment — have an effect on the work-related errors.

4. Hypothesis/hypotheses

Although the authors did not explicitly indicate the hypotheses of the study, the following alternative and null-hypotheses can be gleaned from their work:

H0: There is a correlation between the working hours of hospital staff nurses and their frequency of work-related errors.

HA: There is no correlation between the working hours of hospital staff nurses and their frequency of work-related errors.

H0: The following variables: (a) age, (b) sex, (c) marital status, (d) working experience, (d) ethnicity and (e) working environment which includes the hospital size, type, and localization have no effect on the work-related errors.

HA: The following variables: (a) age, (b) sex, (c) marital status, (d) working experience, (d) ethnicity and (e) working environment which includes the hospital size, type, and localization have no effect on the work-related errors.

5. Study Variables

The correlational study on working hours and patient safety involved the independent variable, the ‘nursing hour’ shift, classified as 8.5 hour-, 12.5-, and overtime shift; and the dependent variable, binary response of the nurses, near-error and error incidents. The relation between the real duration of the shift and overtime and risk-incidents was estimated using logistic regression models. The multiple work shifts were then analyzed using Generalized Estimating Equation to estimate the Odds Ratio (two-sided; α=0.05).

Likewise the occurrence of ‘near error’ and ‘error’ [dependent v.] was associated with the following variables —age, sex, marital status, working experience, ethnicity and working environment [independent v.] using a multivariance analysis.

6. Conceptual Model/Theoretical Framework

Logbooks, recording the frequency of errors, were the main method for the conceptual framework of the study. Rogers et al (2004) adopted the method of Luna, French and Mitcha (1997) on the USAF air traffic controller shiftwork and work performance. It is noted that there is no direct analysis between the variables that was constructed— the rapid rotation shifting with sleep, fatigue, activity, and mood—in the study and it relied weakly on computerized cognitive performance battery and completed the Profile of Mood States questionnaire.

Such ‘logbooks’ which estimates the frequency of each full-time nurse and the ‘multi-variance’ conceptual framework for the paper is relatively weak. Mutivariance framework for the study is narrowed to the only errors and the non-errors committed by full-time working nurses during their study.

7. Review of Related Literature

The literature on the ‘lack’ of studies on ‘longevity’ of work correlated to patient safety acknowledges the basis of the study. Logbook methods were ‘adapted’ not from nursing studies but from reviews on air-traffic controllers. The author did not indicate if there are ‘nursing shortage’ studies that used the ‘logbook’ analyses. Throughout the discussion and the results, the author cited several literatures on the nature of the error and near-error incidents committed during work, which the adopted method type does not entirely support/supply. Several studies on fatigue-related incidents, shifting pattern, and mandatory overtime contribute to the development of the discussion and results.

8. Study Design

The study design used is a two way ANOVA on the frequency of errors and near-errors on the actual hours of work and overtime (GEE estimated) and multi-variance analysis on the variable association of age, sex, marital status, working experience, ethnicity and working environment to error and near error frequency.

Statistical analyses is highly suitable for the demographic analyses except that it is highly subjected to errors which may be a result of the ‘logbook’ analyses. The indirect estimation, using mainly recordings from the subjects, is highly prone to errors because the nurses neglect to completely detail or estimate the errors and near-errors during their busy schedule. Time estimation and adjustments and logistic regression may also negatively effect the internal validity of the design. An external variable which may affect the validity of the study and lends weakness which the design noticeably lacks is the ‘monitoring of the department’ of full-time nurses.

9. Sample and Setting

The sample subjects are not large enough with only 8 % of the ANA members complying with the two-week logbook analyses that formed the entire basis of the research. Undeniably, this is just a minute of the total population of nurses within the States. Also, there are also nurses which are not ANA members that are not included in the study. Sampling subjects are those that worked only full time. Even though there is a return rate of 40 % for logbook completion and that there is specificity and regularity in terms of “only full time”, this is still a far-cry from the number of RNs in the States. Non-random sampling, for the whole US, is performed and not at a per-state level. This precludes the idea of studying frequency of work-related error per state level.

10. Identification and Control of Extraneous Variables

The extraneous variable for the study is non-full time and this was controlled by not including them in the study. Another variable is the multiple work shifts which were controlled by the Generalized Estimating Equation.

11. Study Instruments/Tools

Extraneous elements like the multiple work shifts were controlled using statistical instruments like the Generalized Estimating Equation. Other instruments like univariance using logistic regression analyses and multiple variance analyses connect the relations between the independent and independent variables.

13. Data Analysis Procedures

Data analysis procedure for calculating the probability of errors preceded by regression analyses, a two-tail analyses (α=0.05) and multi-variance which connects the relation between total shift hours (either as overtime or not), the error fractions and other variables like: (a) age, (b) sex, (c) marital status, (d) working experience, (d) ethnicity and (e) working environment.

14. Strengths/Limitations

The merits for the study are that the statistical tool used is highly flexible and commended for descriptive studies such as this. However, this seems to be the only merit of the study as it is confounded by multiple limitation which contribute to its general weakness as a paper. Foremost among the error is ‘the logbook’ method of analyses which is not 100% reliable when it comes to real ‘recording’ of incidents and events. Failure to note, under and over-estimation of errors may contribute to a faulty data which may otherwise effect the whole paper.

Also, the duration of the sampling time is very small; two-week sampling time is not a good representative for sampling the errors committed by the subjects. It is better if longitudinal analyses be conducted. Longitudinal analyses covering longer period of time and tracing work routes of subjects can provide for a more reliable data. Additionally, the subjects utilized for the study is very small and is not a representative of the whole States’ RNs thus precluding the reliability of studying the following variables: (a) age, (b) sex, (c) marital status, (d) working experience, (d) ethnicity and (e) working environment. More males and younger nurses should be utilized for the study. Also, the departments/specialization (e.g. CCU) for the nurse subjects was excluded as a variable. It would also be better to conduct a randomized stratified sampling for each component state instead of randomizing it as a whole. The study should have not limited itself to ANA members; the influx of RNs that are non-ANA and non-American have increased over the years.

References

  • Buerhaus , P. (2000) Implications of an aging registered nurse workforce. Journ. of the Amer. Med. Assoc., 283 2948-54.
  • K.-Y. Liang and S.L. Zeger. (1986) Longitudinal Data Analysis using Generalized Linear Models, Biometrika, 73, 113–22.
  • Rogers, Ann E., Wei-Ting Hwang, Linda D. Scott, Linda H. Aiken and David F. Dinges. The Working Hours of Hospital Staff Nurses and Patient Safety. Health Affairs, 23, 2202. -2212
  • Schott, A. (2001). Nurse Recruiters Confront New Shortages and New Breed of RNs. Report. New York State Nurses Association., Feb, , p.4.
  • S.M. Kelly et al. (1993). Flight Controller Alertness and Performance during MOD Shiftwork Operations," Seventh Annual Workshop in Space Operations, Applications, and Research , 405–416;

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