CIN: Computers, Informatics, Nursing
& Vol. 32, No. 10, 475–481 & Copyright B 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
F E A T U R E A R T I C L E
The Relationship Between Electronic Nursing Care Reminders and Missed Nursing Care RONALD J. PISCOTTY JR, PhD, RN-BC BEATRICE KALISCH, PhD, RN, FAAN
The implementation of healthcare information technology (HIT) is occurring at an astonishing rate in healthcare settings in the US, supported by seminal works from the Institute of Medicine such as To Err Is Human and Crossing the Quality Chasm.1,2 These two works encouraged the use of technology to improve patient safety and healthcare outcomes. In addition, the American Recovery and Reinvestment Act of 2009 provided more than 36 billion in funding for the rapid implementation and adoption of HIT.3 The premise that HIT be used as a national strategy to contain healthcare costs and improve quality and safety of care may be premature, as few studies have supported HIT’s positive impact on nursing practice.4–6 Furthermore, the evidence base regarding the cost-effectiveness and qualityenhancing properties of HIT remains inconclusive.7,8 Because RNs, who rely on care support systems to perform their jobs, make up the largest group of healthcare workers in the nation, a stronger evidence base for HIT is needed, especially within nursing practice. Clinical decision support (CDS) systems are a variety of HIT designed to improve the decision-making abilities of providers. In this regard, the application of HIT can be viewed as a potential intervention to decrease missed nursing care. Nursing care reminders, items that nurses are expected to complete before the end of their shift, are considered one output of CDS. The care reminders are delivered to nurses in a variety of methods such as ‘‘dashboard’’ alerts, work lists or queues, order lists, pop-up reminders, and/or reminders integrated into other modules of the electronic health record (EHR) such as an intervention list in the care planning documentation. Despite their increasing presence in the clinical setting, electronic nursing care reminders
The purpose of the study was to explore relationships between nurses’ perceptions of the impact of health information technology on their clinical practice in the acute care setting, their use of electronic nursing care reminders, and episodes of missed nursing care. The study aims were accomplished with a descriptive design using adjusted correlations. A convenience sample (N = 165) of medical and/or surgical, intensive care, and intermediate care RNs working on acute care hospital units participated in the study. Nurses from 19 eligible nursing units were invited to participate. Adjusted relationships using hierarchical multiple regression analyses indicated significant negative relationships between missed nursing care and nursing care reminders and perceptions of health information technology. The adjusted correlations support the hypotheses that there is a relationship between nursing care reminder usage and missed nursing care and a relationship between health information technology and missed nursing care. The relationships are negative, indicating that nurses who rate higher levels of reminder usage and health information technology have decreased reports of missed nursing care. The study found a significant relationship between nursing care reminders usage and decreased amounts of missed nursing care. The findings can be used in a variety of improvement endeavors, such as encouraging nurses to utilize nursing care reminders, aid information system designers when designing nursing care reminders, and assist healthcare organizations in assessing the impact of technology on nursing practice. KEY WORDS Clinical decision support & Missed care & Nursing & Reminders
Author Affiliations: College of Nursing, Wayne State University, Detroit, MI (Dr Piscotty), and School of Nursing, University of Michigan, Ann Arbor, MI (Dr Kalisch). The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Ronald J. Piscotty Jr, PhD, RN-BC, College of Nursing, Wayne State University, 5777 Cass Ave, 364 Cohn, Detroit, MI 48202 ([email protected]). DOI: 10.1097/CIN.0000000000000092
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
475
have not been well studied, and this is a noted gap in the literature. The purpose of the present study was to explore relationships between nurses’ perceptions of the impact of HIT (I-HIT) on their practice in the acute care setting, their use of electronic nursing care reminders, and episodes of missed nursing care.
Background and Significance Dykes and colleagues4 hypothesized a number of potential positive effects of HIT systems on nursing practice. First, systems designed to improve interdisciplinary communication and CDS may improve outcomes. Through improved interdisciplinary communication and CDS, enhanced communication within the healthcare team may occur. Clinical decision support may also improve the ability of the nurse to monitor patient conditions and detect changes earlier. It may be provided in the form of alerts, reminders, and/or recommendations to guide nursing practice. The prompts from these systems are typically designed with evidence-based suggestions to improve clinical decision making and reasoning. However, poorly implemented HIT systems can result in ‘‘unintended consequences’’ that lead to new errors. These errors can negatively affect patient safety and quality of care.9–11 Unintended consequences related to HIT use have been associated with one or more conflicts between technology design, implementation, and support of clinician workflow.12,13 Previous studies have indicated that reminders are used in the acute care environment, but these clinical supports tend to be verbal or paper based (eg, laminated cards, paper checklists, or paper printouts).14–16 Hatler and colleagues15 recommended as evidence-based practice the use of laminated cards to remind nurses to clean the hubs of central venous catheters before medication administration or blood draws to prevent catheter-related blood stream infections. Reminders have been found effective in decreasing the length of time urinary catheters are in place and in reducing catheter-associated infections.14,16 In addition, reminders have been found effective in reducing charting deficiencies.17 Although nonelectronic reminders appear effective, the healthcare industry is moving ever closer to a ‘‘paperless’’ system. The inclusion of electronic reminders in the EHR needs to be studied for its impact on positive outcomes, as nurses are expected to use these systems in their daily practice. It is intuitive to think that an electronic system that has nursing reminders should result in decreased missed nursing care, but scientific evidence is needed. This study is a first step in determining if there is a relationship between electronic nursing care reminders and missed nursing care. Missed nursing care is a measure of nursing process and is considered an error of omission (failing to do the right thing) versus an error of commission (doing the wrong 476
thing).15,16 The Agency for Healthcare Research and Quality suggests that errors of omission are often unreported and much more common than errors of commission.18 In several studies, the primary reason for missed nursing care was related to nurse staffing adequacy, specifically labor resources (eg, unexpected rise in patient acuity).19–22 One of the major negative effects of decreased labor resources on nursing practice centers on its potential to cause distractions and interruptions.23 Distractions and interruptions are commonplace in the acute care setting.24 Brixey and colleagues25 noted that interruptions in work settings such as aviation, nuclear power plants, and healthcare delivery could result in catastrophic failures including loss of life. Interruptions and distractions can have an impact on nurses’ working memory. When a deficit in the adequacy of nursing labor resources is present, this may lead to missed nursing care. Regardless of underlying cause, however, the CDS with electronic reminders may effectively decrease instances of missed care. In the hospital setting, missed nursing care has been related to patient and organizational outcomes, including staff satisfaction. For example, missed nursing care was found to be a mediating factor in increasing patient falls.26 In another study, care rationing (a form of missed nursing care) was a significant predictor of patient outcomes that included medication errors, nosocomial infections, and pressure ulcers.27 Organizational outcomes such as ineffective teamwork, higher staff turnover, and low job satisfaction have also been associated with missed nursing care.28–30
Objectives The objectives of this descriptive correlational study were to (1) examine relationships between interventions supported by CDS and reduced missed nursing care and (2) examine relationships between nurses’ perceptions of I-HIT on their work and their reports of missed nursing care. Thus, the first hypothesis tested in this study was to determine whether nurses who use reminders more frequently will have fewer reports of missed nursing care. The second hypothesis tested was to determine whether nurses who have more positive perceptions of I-HIT on their practice would have fewer reports of missed nursing care.
METHODS Design and Sample The specific aims of this study were accomplished with a descriptive design using adjusted correlations. A convenience sample (N = 165) of medical and/or surgical, intensive care, and intermediate care RNs working on acute care hospital units participated in the study. The sample was obtained
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
from a large teaching hospital in the Midwestern US. Nurses from 19 eligible nursing units were invited to participate.
Power Analysis Multiple regression analysis was conducted with four predictor variables, with a power of 0.80 and a medium effect size of 0.15. Power analysis for the regression analysis was evaluated with G*Power 3.1 (Heinrich Heine Universitat, Dusseldorf, Germany)31,32 and indicates a minimum sample size of 92 for each model; however, the plan was to collect data on 150 participants.
Inclusion/Exclusion Criteria Inclusion criteria for the study were that participants be a staff RN and take a daily patient assignment on the unit in which they work. The EHR must have been implemented for least 6 months, with nursing care reminders present in the EHR. Excluded from this study were unit employees who were non-RN employees (eg, LPN, PCA, clerks, etc), RNs without a patient assignment (eg, managers, case managers, educators, nursing instructors), and student nurses.
yond the .05 significance level.4 Principal components analysis (PCA) with varimax rotation and Kaiser normalization was used for factor analysis of the data to test for construct validity. Four factors emerged from the PCA explaining 58.5% of total variance.4 Internal consistency using Cronbach’s " was .95 for the 29-item scale. Internal consistency of the four subscales ranged from 0.80 to 0.89. The survey took approximately 10 minutes to complete. MISSED NURSING CARE SURVEY The Missed Nursing Care Survey (MISSCARE) is a twopart survey.33 Part A, used in this study, contains 22 items designed to measure elements of missed nursing care. This part asks the participants to rate the frequency of missed nursing care on their unit, including their own lapses. The rating is based on a 5-point scale with anchors of ‘‘rarely’’ and ‘‘always.’’ Content validity has been established through testing by three panels of staff nurses with a CVI of 0.89. Reliability for Part A of the tool was established using test-retest reliability; the Pearson product-moment correlation coefficient was 0.87. The survey took approximately 10 minutes to complete. DEMOGRAPHICS AND OTHER VARIABLES
Instrumentation NURSING CARE REMINDER USAGE SURVEY A nursing care reminder usage survey developed by the investigators was used in this study. The instrument contained 12 questions regarding usage and perceptions of nursing care reminders, with rated responses based on a 5-point scale with anchors of ‘‘never’’ and ‘‘always’’ and an additional ‘‘not applicable’’ (N/A) choice. The face validity of the survey was established with a group of informatics experts (two nursing faculty members from the University of Michigan and the University of Iowa and one public health faculty member from the University of Michigan) and was found to have more than adequate reliability with a Cronbach’s " of .84. The survey took approximately 5 minutes to complete. Example statements from the survey include: ‘‘How frequently do you utilize the following types of nursing care reminders to assist you in completing nursing care activities: (1) electronic list of reminders in EHR (ie, task list, documentation checklist, documentation form, work queue, work list), (2) alert or reminder message pop-ups in the EHR?’’ I-HIT SCALE The I-HIT is composed of 29 items contained in four subscales.4 The I-HIT scale is scored using a 6-point (strongly disagree to strongly agree) Likert-type scale and an N/A choice. Content validity assessment indicated a content validity index (CVI) of 1.0. The scale achieved a CVI be-
The MISSCARE Survey33 also contains a demographic questionnaire. This questionnaire was used to collect data regarding nurse characteristics. The demographic questionnaire was modified by the investigators, as two characteristics of interest in the proposed study are not included in the survey: number of years working as an RN and amount of experience with current EHR. In addition, data were collected on staffing adequacy and acuity.
Procedure Institutional review board (IRB) approval was obtained from the affiliated university and the study hospital. The IRB application received an expedited review as no participant-identifying information was being collected, and there was minimal chance for harm with the anonymous online surveys. Survey data were downloaded into SPSS 21 (IBM Corp, Armonk, NY) for later analysis. The data were stored on a password-protected computer accessible only to the principal investigator (PI). Once the data were downloaded to computer storage, the completed online surveys were deleted. Implied consent from participants was obtained if the nurses completed the online surveys. An information-only consent form describing the study was included in the participant e-mail and survey directions, but participants were not required to sign and return the form. The online survey included the study instruments, consent information,
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
477
and detailed directions. The surveys were administered as an online survey with a link sent to participants via e-mail. The survey was administered using the Qualtrics survey software (Qualtrics, Provo, UT), which supports anonymous distribution and collection. Employee e-mail addresses were used to send the survey to each participant. The e-mail addresses were obtained with assistance from the hospital research sponsor. Respondent burden was minimal. As a reminder to the nurses to complete the survey, flyers were placed in high-visibility areas. Also, a reminder e-mail was sent to the nurses twice a week via e-mail. All surveys were due at 4 weeks.
Data Analysis Data were analyzed using SPSS 21. The data were cleaned, and descriptive analysis was conducted to examine normality and linearity of variables. This was accomplished through interpretation of descriptive statistics and visual examination of graphs and plots. Assumptions for regression were also assessed (ie, independence, normality, linearity, and multicolinearity). Stepwise regression entry was used to determine nurse characteristics to include in the regression models. Analysis indicated that only gender was a significant predictor of missed nursing care. The remaining nurse characteristic variables were not significant predictors of missed nursing care and thus were excluded from the analysis. Hierarchical multiple regression analysis with control variables was used to determine adjusted relationships between the variables of interest. Significance tests and $ coefficients were analyzed and interpreted to determine the study outcomes. Control variables were entered into the model first to control for the effect of these variables, and then the primary independent variables were entered.34
T a b l e 1 Demographic Characteristics of the Sample (N = 165) Characteristics Age G25 y 25–34 y 35–44 y 45–54 y 55–64 y 965 y Gender Male Female Experience in role Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Experience as RN Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Experience with current EHR Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Highest education level Associate’s degree Bachelor’s degree Graduate degree Employment status Full-time Part-time
n
%
23 61 38 26 16 1
13.9 37.0 23.0 15.8 9.7 0.6
20 145
12.1 87.9
8 40 35 23 59
4.8 24.2 21.2 13.9 35.8
8 36 35 25 61
4.8 21.8 21.2 15.2 37.0
5 45 78 25 12
3.0 27.3 47.3 15.2 7.3
44 114 7
26.7 69.1 4.2
154 11
93.3 6.7
RESULTS Demographics Participants (N = 165) were staff nurses employed at a local hospital in the Midwestern US during the fall of 2012. The majority held a bachelor’s degree as their highest level of education (n = 114, 69.1%), and 66.7% (n = 110) held a BSN. The gender majority was female (n = 145, 87.9%), and age majority between the ages of 25 and 34 years (n = 61, 37.0%). More than half of the participants (n = 104, 63.0%) worked on a medical surgical unit. Table 1 shows further descriptive analysis of demographic characteristics.
Hypotheses 1 and 2 Adjusted relationships using hierarchical multiple regression analyses indicated significant negative relationships 478
between missed nursing care and nursing care reminders and perceptions of I-HIT. Preliminary analyses were conducted to ensure there was no violation of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. The first regression model was calculated to determine if there was a significant adjusted relationship between missed nursing care and nursing care reminders. Case mix index (CMI), RN hours per patient day (RNHPPD), and gender were included as covariates in Step 1 of the equation and explained 8.3% of the variance in missed nursing care. After entry of nursing care reminders at Step 2, the total variance explained by the model as a whole was 15.2%, F4,160 = 7.15, P G .001. Nursing care reminders explained an additional 7% of the variance in missed nursing care after controlling for CMI, RNHPPD, and gender, R2 change = 0.07, F4,160 change = 12.94, P G .001. In the final model, only CMI ($ = j.40, P = .001), gender ($ = .16, P = .034), and
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
nursing care reminders ($ = j.28, P G .001) were statistically significant. The second regression model was calculated to determine if there was a significant adjusted relationship between missed nursing care and I-HIT. Case mix index, RNHPPD, and gender were included as covariates in Step 1 of the equation and explained 8% of the variance in missed nursing care. After entry of I-HIT at Step 2, the total variance explained by the model as a whole was 18.8%, F4,153 change = 8.85, P G .001. Impact of HIT explained an additional 11% of the variance in missed nursing care after controlling for CMI, RNHPPD, and gender, R2 change = 0.11, F4,153 = 20.33, P G .001. In the final model, only CMI ($ = j.34, P = .003) and I-HIT ($ = j.34, P G .001) were statistically significant.
CDS systems and have improved outcomes. This is consistent with the findings in this study. Nurses who used the reminders had fewer episodes of missed nursing care. An alternate explanation for this finding may be that nurses who were more likely to use the EHR were more likely to complete their nursing care activities. As a comparative illustration, some nurses may be less accountable and neither use the EHR consistently nor make sure they complete all nursing care activities needed for their patients. An additional explanation for the findings is that this study was conducted in one hospital. The hospital culture may have had an effect on the use of the EHR reminders. In short, the nurses in this study may have been more likely to use the reminders because of organizational pressures and also may have had few episodes of missed nursing care to begin with.
Instrument Reliabilities and Validity Test-retest reliability of the MISSCARE Survey was not conducted in the current study. Reliability of the Nursing Care Reminder Usage Survey in the current study was calculated using Cronbach’s ". The Cronbach’s " was .84, indicating more than adequate reliability. Reliability of the I-HIT scale for the current study was calculated using Cronbach’s ". The Cronbach’s " was .94, indicating more than adequate reliability.
DISCUSSION The adjusted correlations support the hypotheses that there is a relationship between nursing care reminder usage and missed nursing care, and a relationship between perceptions of I-HIT and missed nursing care. The relationships are negative, indicating that nurses who report higher levels of reminder usage and favorable perceptions of I-HIT have fewer reports of missed nursing care. This makes sense as those who had higher scores on the I-HIT had positive perceptions about the impact of technology on their practice. The findings are significant as nursing care reminders may be an effective intervention to decrease episodes of missed nursing care. Although missing one instance of care may not affect overall patient outcomes, the cumulative effects may have a negative impact on patient outcomes. The use of nursing care reminders to alert nurses to cumulatively missed care may be an intervention to significantly reduce the amount of missed nursing care. In addition, nurses with higher scores for perception of I-HIT may be more apt to use nursing care reminders that may decrease episodes of missed care. The present study was the first to explore these relationships. It was hypothesized by Dykes et al4 that nurses who scored higher on the I-HIT would be more likely to use the
Implications The findings from this study have many practical implications. First, the I-HIT instrument can be used to assess the impact of technology on nursing practice. This information can then be used to evaluate HIT to determine where changes need to occur to be better aligned with clinician workflow. Workflow alignment is important, as it has been suggested that poor workflow alignment has resulted in unintended consequences of HIT.12,13 The unintended consequences can result in new errors that may not have occurred before the implementation of the HIT.9–11 A second implication is that properly designed nursing care reminders may influence usage and thus decrease the amount of missed nursing care. Reminders that nurses find helpful may result in increased usage of the reminders. There must be a balance between the quality and quantity of nursing care reminders. Reminders that are redundant or not seen as important may be missed or ignored. Missed or ignored reminders may then result in an increase in missed nursing care. One suggestion is that future designers of electronic reminders may need to consider the potential of cumulative effects of missed nursing care rather than individual instances of missed care. To illustrate, patients who are not ambulated once may not be at a disadvantage in their healing compared with a patient who has missed multiple instances of ambulation. This cumulative effect needs to be further investigated as it relates to the design of supportive technologies. A third implication drawn from the present study is that nurses need to be taught and encouraged in the proper usage of nursing care reminders. Nursing care reminders are adjuncts to clinical reasoning, and not a replacement for nurses’ knowledge and reasoning. Although a patient may have many reminders in the EHR, they may still require additional nursing care that is at the discretion of the individual nurse. The proper use of reminders by nurses
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
479
may result in fewer epiosides of missed nursing care. This may be especially true with novice nurses who may need the reminders to serve as cues of which nursing activities are appropriate for a particular patient. At the same time, more seasoned nurses may find reminders useful in validating their clinical reasoning. The reminders may be helpful for seasoned nurses who are encountering a patient with a unique or unfamiliar plan of care. This is consistent with findings from the study conducted by Dowding et al,35 in which they found novice nurses used the CDS system more frequently and more experienced nurses used the system when they encountered an unfamiliar or complex case.
Limitations and Anticipated Problems Limitations of this study include threats to internal and external validity. A threat to internal validity is that the sample size was not very large. The investigator addressed this by determining sample size a priori using a small effect size and limiting analysis to no more than four independent variables in regression analysis. Selection bias is also a possible threat to internal validity for this study, as a convenience sampling method was used. Therefore, the relationships examined in this study could be attributed to sample characteristics rather than a true relationship between the variables of interest. This threat has been addressed by determining sample size a priori as stated above and including nurse characteristics as covariates in the analyses. Instrumentation may also be a threat to internal validity of this study. The PI has addressed this by selecting instruments with proven validity and reliability and specifically designed to be used with RNs. Threats to external validity are present because of the fact that the sample may not be representative of the national RN population, and therefore the results may not be generalizable beyond the sample. The PI has taken this into consideration and has addressed this by examining the possible relationship of the nursing care reminders and missed nursing care in more than one nursing unit.
Future Research This study was a first step in establishing a link between the uses of nursing care reminders and missed nursing care. This study must be repeated with a larger sample to determine if the relationship holds. Second, the study needs to be repeated in multiple hospitals. The study hospital may have been extremely adept at using reminders, but other hospitals may have a different performance record. The present study was also conducted with only one format of the EHR; examining the relationships in organizations that use different styles of EHRs is recommended. 480
Furthermore, a concept analysis on what constitutes nursing care reminders is needed for future studies. The extant literature is void on this concept. A concept analysis should be conducted to determine the types of nursing care reminders and their empirical definitions in order to adequately measure these support tools. Reminders are not unique to nursing, so literature from other disciplines may also need to be investigated. This future research needs to be conducted to determine if there are similar or different concepts associated with reminders. Ultimately, the goal of nursing care reminder research is to develop investigator-designed reminders as interventions. These interventions will target specific missed care items. This is a challenging goal and a long-term endeavor as the different types of reminders that nurses use must be clearly defined. Also, before this progress can occur, exploratory research needs to be conducted to determine which types of reminders are effective in decreasing the specific types of missed nursing care.
CONCLUSION This study was a first step in determining if HIT has an impact on nursing care process. The study found a significant relationship between nursing care reminder usage and decreased frequency of missed nursing care. The findings can be used in a variety of improvement endeavors, such as encouraging nurses to utilize nursing care reminders, aid information system designers when designing nursing care reminders, and assist healthcare organizations in assessing the impact of technology on nursing practice. It is imperative that episodes of missed nursing care decrease in order to improve patient and organization outcomes. Nursing care reminders may be a viable solution to reduce the incidence of missed nursing care in a technology-rich healthcare environment.
REFERENCES 1. Institute of Medicine of the National Academies. To Err Is Human: Building a Safer Health System. Washington, DC: National Academies Press; 1999. 2. Institute of Medicine of the National Academies. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001. 3. Healthcare Information and Management Systems Society. HIMSS health information exchange: ARRA, HITECH FAQs related to HIE. 2009. http://www.himss.org/files/HIMSSorg/content/files/12_ 04_09_ARRAHITECHHIE_FactSheet.pdf. Accessed December 3, 2010. 4. Dykes PC, Hurley A, Cashen M, Bakken S, Duffy ME. Development and psychometric evaluation of the Impact of Health Technology (I-HIT) scale. J Am Med Inform Assoc. 2007;14(4):507–514. 5. Dykes P, Collins S. Building linkages between nursing care and improved patient outcomes: the role of health information technology. Online J Issues Nurs. 2013;18(3):1–17.
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
6. Goldsack J, Robinson E. The impact of health information technology on staffing. J Nurs Adm. 2014;44(2):117–120. 7. Kellermann A, Jones S. What it will take to achieve the as-yetunfulfilled promises of health information technology. Health Aff. 2013;32(1):63–68. 8. Goldzweig CL, Towfigh A, Maglione M, Shekelle PG. Costs and benefits of health information technology: new trends from the literature. Health Aff (Millwood). 2009;28(2):282–293. 9. Ash J, Sittig DF, Poon EG, Guappone K, Campbell E, Dykstra RH. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2007; 14(4):415–423. 10. Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2005;116(6):1506–1512. 11. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. J Am Med Assoc. 2005;293(10):1197–1203. 12. Aarts J, Ash J, Berg M. Extending the understanding of computerized physician order entry: implications for professional collaboration, workflow and quality of care. Int J Med Inform. 2007;76(1):S4–S13. 13. Harrison MI, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care: an interactive sociotechnical analysis. J Am Med Inform Assoc. 2007;14(5):542–549. 14. Chen YY, Chi MM, Chen YC, Chan YJ, Chou SS, Wang FD. Using a criteria-based reminder to reduce use of indwelling urinary catheters and decrease urinary tract infections. Am J Crit Care. 2013; 22(2):105–114. 15. Hatler C, Hebden J, Kaler W, Zack J. Walk the walk to reduce catheterrelated bloodstream infections. Am Nurse Today. 2010;5(1):26–30. 16. Huang WC, Wann SR, Lin SL, et al. Catheter-associated urinary tract infections in intensive care units can be reduced by prompting physicians to remove unnecessary catheters. Infect Control Hosp Epidemiol. 2004;25(11):974–978. 17. Oniki TA, Clemmer TP, Pryor TA. The effect of computer-generated reminders on charting deficiencies in the ICU. J Am Med Inform Assoc. 2003;10(2):177–187. 18. Agency for Healthcare Research and Quality. AHRQ Patient Safety Network: Glossary. http://psnet.ahrq.gov/glossary.aspx. Accessed April 11, 2011. 19. Kalisch BJ, Landstrom G, Williams RA. Missed nursing care: errors of omission. Nurs Outlook. 2009;57(1):3–9.
20. Gravlin G, Phoenix Bittner N. Nurses’ and nursing assistants’ reports of missed care and delegation. J Nurs Adm. 2010;40(7–8): 329–335. 21. Kalisch BJ. Nurse and nurse assistant perceptions of missed nursing care: what does it tell us about teamwork? J Nurs Adm. 2009; 39(11):485–493. 22. Lawless J, Wan L, Zeng I. Patient care ‘rationed’ as nurses struggle under heavy workloads—survey. Nurs N Z. 2010;16(7):16–18. 23. Bittner NP, Gravlin G, Hansten R, Kalisch BJ. Unraveling care omissions. J Nurs Adm. 2011;41(12):510–512. 24. Kalisch BJ, Aebersold M. Interruptions and multitasking in nursing care. Jt Comm J Qual Patient Saf. 2010;36(3):126–132. 25. Brixey JJ, Robinson DJ, Johnson CW, Johnson TR, Turley JP, Zhang J. A concept analysis of the phenomenon interruption. ANS Adv Nurs Sci. 2007;30(1):E26–E42. 26. Kalisch BJ, Tschannen D, Lee KH. Missed nursing care, staffing, and patient falls. J Nurs Care Qual. 2012;27(1):6–12. 27. Schubert M, Glass TR, Clarke SP, et al. Rationing of nursing care and its relationship to patient outcomes: the Swiss extension of the International Hospital Outcomes Study. Int J Qual Health Care. 2008;20(4):227–237. 28. Kalisch BJ, Lee KH. The impact of teamwork on missed nursing care. Nurs Outlook. 2010;58(5):233–241. 29. Kalisch B, Tschannen D, Lee H. Does missed nursing care predict job satisfaction? J Healthc Manag. 2011;56(2):117–131. 30. Tschannen D, Kalisch BJ, Lee KH. Missed nursing care: the impact on intention to leave and turnover. Can J Nurs Res. 2010; 42(4):22–39. 31. Faul F, Erdfelder E, Lang A.-G, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–191. 32. Faul F, Erdfelder E, Lang A.-G, Buchner A. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149–1160. 33. Kalisch BJ, Williams RA. Development and psychometric testing of a tool to measure missed nursing care. J Nurs Adm. 2009;39(5): 211–219. 34. Polit DF. Statistics and Data Analysis for Nursing Research. 2nd ed. Upper Saddle River, NJ: Pearson Education; 2010. 35. Dowding D, Randell R, Mitchell N, et al. Experience and nurses use of computerised decision support systems. Stud Health Technol Inform. 2009;146:506–510.
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
481
& Vol. 32, No. 10, 475–481 & Copyright B 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins
F E A T U R E A R T I C L E
The Relationship Between Electronic Nursing Care Reminders and Missed Nursing Care RONALD J. PISCOTTY JR, PhD, RN-BC BEATRICE KALISCH, PhD, RN, FAAN
The implementation of healthcare information technology (HIT) is occurring at an astonishing rate in healthcare settings in the US, supported by seminal works from the Institute of Medicine such as To Err Is Human and Crossing the Quality Chasm.1,2 These two works encouraged the use of technology to improve patient safety and healthcare outcomes. In addition, the American Recovery and Reinvestment Act of 2009 provided more than 36 billion in funding for the rapid implementation and adoption of HIT.3 The premise that HIT be used as a national strategy to contain healthcare costs and improve quality and safety of care may be premature, as few studies have supported HIT’s positive impact on nursing practice.4–6 Furthermore, the evidence base regarding the cost-effectiveness and qualityenhancing properties of HIT remains inconclusive.7,8 Because RNs, who rely on care support systems to perform their jobs, make up the largest group of healthcare workers in the nation, a stronger evidence base for HIT is needed, especially within nursing practice. Clinical decision support (CDS) systems are a variety of HIT designed to improve the decision-making abilities of providers. In this regard, the application of HIT can be viewed as a potential intervention to decrease missed nursing care. Nursing care reminders, items that nurses are expected to complete before the end of their shift, are considered one output of CDS. The care reminders are delivered to nurses in a variety of methods such as ‘‘dashboard’’ alerts, work lists or queues, order lists, pop-up reminders, and/or reminders integrated into other modules of the electronic health record (EHR) such as an intervention list in the care planning documentation. Despite their increasing presence in the clinical setting, electronic nursing care reminders
The purpose of the study was to explore relationships between nurses’ perceptions of the impact of health information technology on their clinical practice in the acute care setting, their use of electronic nursing care reminders, and episodes of missed nursing care. The study aims were accomplished with a descriptive design using adjusted correlations. A convenience sample (N = 165) of medical and/or surgical, intensive care, and intermediate care RNs working on acute care hospital units participated in the study. Nurses from 19 eligible nursing units were invited to participate. Adjusted relationships using hierarchical multiple regression analyses indicated significant negative relationships between missed nursing care and nursing care reminders and perceptions of health information technology. The adjusted correlations support the hypotheses that there is a relationship between nursing care reminder usage and missed nursing care and a relationship between health information technology and missed nursing care. The relationships are negative, indicating that nurses who rate higher levels of reminder usage and health information technology have decreased reports of missed nursing care. The study found a significant relationship between nursing care reminders usage and decreased amounts of missed nursing care. The findings can be used in a variety of improvement endeavors, such as encouraging nurses to utilize nursing care reminders, aid information system designers when designing nursing care reminders, and assist healthcare organizations in assessing the impact of technology on nursing practice. KEY WORDS Clinical decision support & Missed care & Nursing & Reminders
Author Affiliations: College of Nursing, Wayne State University, Detroit, MI (Dr Piscotty), and School of Nursing, University of Michigan, Ann Arbor, MI (Dr Kalisch). The authors have disclosed that they have no significant relationship with, or financial interest in, any commercial companies pertaining to this article. Corresponding author: Ronald J. Piscotty Jr, PhD, RN-BC, College of Nursing, Wayne State University, 5777 Cass Ave, 364 Cohn, Detroit, MI 48202 ([email protected]). DOI: 10.1097/CIN.0000000000000092
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
475
have not been well studied, and this is a noted gap in the literature. The purpose of the present study was to explore relationships between nurses’ perceptions of the impact of HIT (I-HIT) on their practice in the acute care setting, their use of electronic nursing care reminders, and episodes of missed nursing care.
Background and Significance Dykes and colleagues4 hypothesized a number of potential positive effects of HIT systems on nursing practice. First, systems designed to improve interdisciplinary communication and CDS may improve outcomes. Through improved interdisciplinary communication and CDS, enhanced communication within the healthcare team may occur. Clinical decision support may also improve the ability of the nurse to monitor patient conditions and detect changes earlier. It may be provided in the form of alerts, reminders, and/or recommendations to guide nursing practice. The prompts from these systems are typically designed with evidence-based suggestions to improve clinical decision making and reasoning. However, poorly implemented HIT systems can result in ‘‘unintended consequences’’ that lead to new errors. These errors can negatively affect patient safety and quality of care.9–11 Unintended consequences related to HIT use have been associated with one or more conflicts between technology design, implementation, and support of clinician workflow.12,13 Previous studies have indicated that reminders are used in the acute care environment, but these clinical supports tend to be verbal or paper based (eg, laminated cards, paper checklists, or paper printouts).14–16 Hatler and colleagues15 recommended as evidence-based practice the use of laminated cards to remind nurses to clean the hubs of central venous catheters before medication administration or blood draws to prevent catheter-related blood stream infections. Reminders have been found effective in decreasing the length of time urinary catheters are in place and in reducing catheter-associated infections.14,16 In addition, reminders have been found effective in reducing charting deficiencies.17 Although nonelectronic reminders appear effective, the healthcare industry is moving ever closer to a ‘‘paperless’’ system. The inclusion of electronic reminders in the EHR needs to be studied for its impact on positive outcomes, as nurses are expected to use these systems in their daily practice. It is intuitive to think that an electronic system that has nursing reminders should result in decreased missed nursing care, but scientific evidence is needed. This study is a first step in determining if there is a relationship between electronic nursing care reminders and missed nursing care. Missed nursing care is a measure of nursing process and is considered an error of omission (failing to do the right thing) versus an error of commission (doing the wrong 476
thing).15,16 The Agency for Healthcare Research and Quality suggests that errors of omission are often unreported and much more common than errors of commission.18 In several studies, the primary reason for missed nursing care was related to nurse staffing adequacy, specifically labor resources (eg, unexpected rise in patient acuity).19–22 One of the major negative effects of decreased labor resources on nursing practice centers on its potential to cause distractions and interruptions.23 Distractions and interruptions are commonplace in the acute care setting.24 Brixey and colleagues25 noted that interruptions in work settings such as aviation, nuclear power plants, and healthcare delivery could result in catastrophic failures including loss of life. Interruptions and distractions can have an impact on nurses’ working memory. When a deficit in the adequacy of nursing labor resources is present, this may lead to missed nursing care. Regardless of underlying cause, however, the CDS with electronic reminders may effectively decrease instances of missed care. In the hospital setting, missed nursing care has been related to patient and organizational outcomes, including staff satisfaction. For example, missed nursing care was found to be a mediating factor in increasing patient falls.26 In another study, care rationing (a form of missed nursing care) was a significant predictor of patient outcomes that included medication errors, nosocomial infections, and pressure ulcers.27 Organizational outcomes such as ineffective teamwork, higher staff turnover, and low job satisfaction have also been associated with missed nursing care.28–30
Objectives The objectives of this descriptive correlational study were to (1) examine relationships between interventions supported by CDS and reduced missed nursing care and (2) examine relationships between nurses’ perceptions of I-HIT on their work and their reports of missed nursing care. Thus, the first hypothesis tested in this study was to determine whether nurses who use reminders more frequently will have fewer reports of missed nursing care. The second hypothesis tested was to determine whether nurses who have more positive perceptions of I-HIT on their practice would have fewer reports of missed nursing care.
METHODS Design and Sample The specific aims of this study were accomplished with a descriptive design using adjusted correlations. A convenience sample (N = 165) of medical and/or surgical, intensive care, and intermediate care RNs working on acute care hospital units participated in the study. The sample was obtained
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
from a large teaching hospital in the Midwestern US. Nurses from 19 eligible nursing units were invited to participate.
Power Analysis Multiple regression analysis was conducted with four predictor variables, with a power of 0.80 and a medium effect size of 0.15. Power analysis for the regression analysis was evaluated with G*Power 3.1 (Heinrich Heine Universitat, Dusseldorf, Germany)31,32 and indicates a minimum sample size of 92 for each model; however, the plan was to collect data on 150 participants.
Inclusion/Exclusion Criteria Inclusion criteria for the study were that participants be a staff RN and take a daily patient assignment on the unit in which they work. The EHR must have been implemented for least 6 months, with nursing care reminders present in the EHR. Excluded from this study were unit employees who were non-RN employees (eg, LPN, PCA, clerks, etc), RNs without a patient assignment (eg, managers, case managers, educators, nursing instructors), and student nurses.
yond the .05 significance level.4 Principal components analysis (PCA) with varimax rotation and Kaiser normalization was used for factor analysis of the data to test for construct validity. Four factors emerged from the PCA explaining 58.5% of total variance.4 Internal consistency using Cronbach’s " was .95 for the 29-item scale. Internal consistency of the four subscales ranged from 0.80 to 0.89. The survey took approximately 10 minutes to complete. MISSED NURSING CARE SURVEY The Missed Nursing Care Survey (MISSCARE) is a twopart survey.33 Part A, used in this study, contains 22 items designed to measure elements of missed nursing care. This part asks the participants to rate the frequency of missed nursing care on their unit, including their own lapses. The rating is based on a 5-point scale with anchors of ‘‘rarely’’ and ‘‘always.’’ Content validity has been established through testing by three panels of staff nurses with a CVI of 0.89. Reliability for Part A of the tool was established using test-retest reliability; the Pearson product-moment correlation coefficient was 0.87. The survey took approximately 10 minutes to complete. DEMOGRAPHICS AND OTHER VARIABLES
Instrumentation NURSING CARE REMINDER USAGE SURVEY A nursing care reminder usage survey developed by the investigators was used in this study. The instrument contained 12 questions regarding usage and perceptions of nursing care reminders, with rated responses based on a 5-point scale with anchors of ‘‘never’’ and ‘‘always’’ and an additional ‘‘not applicable’’ (N/A) choice. The face validity of the survey was established with a group of informatics experts (two nursing faculty members from the University of Michigan and the University of Iowa and one public health faculty member from the University of Michigan) and was found to have more than adequate reliability with a Cronbach’s " of .84. The survey took approximately 5 minutes to complete. Example statements from the survey include: ‘‘How frequently do you utilize the following types of nursing care reminders to assist you in completing nursing care activities: (1) electronic list of reminders in EHR (ie, task list, documentation checklist, documentation form, work queue, work list), (2) alert or reminder message pop-ups in the EHR?’’ I-HIT SCALE The I-HIT is composed of 29 items contained in four subscales.4 The I-HIT scale is scored using a 6-point (strongly disagree to strongly agree) Likert-type scale and an N/A choice. Content validity assessment indicated a content validity index (CVI) of 1.0. The scale achieved a CVI be-
The MISSCARE Survey33 also contains a demographic questionnaire. This questionnaire was used to collect data regarding nurse characteristics. The demographic questionnaire was modified by the investigators, as two characteristics of interest in the proposed study are not included in the survey: number of years working as an RN and amount of experience with current EHR. In addition, data were collected on staffing adequacy and acuity.
Procedure Institutional review board (IRB) approval was obtained from the affiliated university and the study hospital. The IRB application received an expedited review as no participant-identifying information was being collected, and there was minimal chance for harm with the anonymous online surveys. Survey data were downloaded into SPSS 21 (IBM Corp, Armonk, NY) for later analysis. The data were stored on a password-protected computer accessible only to the principal investigator (PI). Once the data were downloaded to computer storage, the completed online surveys were deleted. Implied consent from participants was obtained if the nurses completed the online surveys. An information-only consent form describing the study was included in the participant e-mail and survey directions, but participants were not required to sign and return the form. The online survey included the study instruments, consent information,
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
477
and detailed directions. The surveys were administered as an online survey with a link sent to participants via e-mail. The survey was administered using the Qualtrics survey software (Qualtrics, Provo, UT), which supports anonymous distribution and collection. Employee e-mail addresses were used to send the survey to each participant. The e-mail addresses were obtained with assistance from the hospital research sponsor. Respondent burden was minimal. As a reminder to the nurses to complete the survey, flyers were placed in high-visibility areas. Also, a reminder e-mail was sent to the nurses twice a week via e-mail. All surveys were due at 4 weeks.
Data Analysis Data were analyzed using SPSS 21. The data were cleaned, and descriptive analysis was conducted to examine normality and linearity of variables. This was accomplished through interpretation of descriptive statistics and visual examination of graphs and plots. Assumptions for regression were also assessed (ie, independence, normality, linearity, and multicolinearity). Stepwise regression entry was used to determine nurse characteristics to include in the regression models. Analysis indicated that only gender was a significant predictor of missed nursing care. The remaining nurse characteristic variables were not significant predictors of missed nursing care and thus were excluded from the analysis. Hierarchical multiple regression analysis with control variables was used to determine adjusted relationships between the variables of interest. Significance tests and $ coefficients were analyzed and interpreted to determine the study outcomes. Control variables were entered into the model first to control for the effect of these variables, and then the primary independent variables were entered.34
T a b l e 1 Demographic Characteristics of the Sample (N = 165) Characteristics Age G25 y 25–34 y 35–44 y 45–54 y 55–64 y 965 y Gender Male Female Experience in role Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Experience as RN Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Experience with current EHR Up to 6 mo 96 mo to 2 y 92–5 y 95–10 y 910 y Highest education level Associate’s degree Bachelor’s degree Graduate degree Employment status Full-time Part-time
n
%
23 61 38 26 16 1
13.9 37.0 23.0 15.8 9.7 0.6
20 145
12.1 87.9
8 40 35 23 59
4.8 24.2 21.2 13.9 35.8
8 36 35 25 61
4.8 21.8 21.2 15.2 37.0
5 45 78 25 12
3.0 27.3 47.3 15.2 7.3
44 114 7
26.7 69.1 4.2
154 11
93.3 6.7
RESULTS Demographics Participants (N = 165) were staff nurses employed at a local hospital in the Midwestern US during the fall of 2012. The majority held a bachelor’s degree as their highest level of education (n = 114, 69.1%), and 66.7% (n = 110) held a BSN. The gender majority was female (n = 145, 87.9%), and age majority between the ages of 25 and 34 years (n = 61, 37.0%). More than half of the participants (n = 104, 63.0%) worked on a medical surgical unit. Table 1 shows further descriptive analysis of demographic characteristics.
Hypotheses 1 and 2 Adjusted relationships using hierarchical multiple regression analyses indicated significant negative relationships 478
between missed nursing care and nursing care reminders and perceptions of I-HIT. Preliminary analyses were conducted to ensure there was no violation of the assumptions of normality, linearity, multicollinearity, and homoscedasticity. The first regression model was calculated to determine if there was a significant adjusted relationship between missed nursing care and nursing care reminders. Case mix index (CMI), RN hours per patient day (RNHPPD), and gender were included as covariates in Step 1 of the equation and explained 8.3% of the variance in missed nursing care. After entry of nursing care reminders at Step 2, the total variance explained by the model as a whole was 15.2%, F4,160 = 7.15, P G .001. Nursing care reminders explained an additional 7% of the variance in missed nursing care after controlling for CMI, RNHPPD, and gender, R2 change = 0.07, F4,160 change = 12.94, P G .001. In the final model, only CMI ($ = j.40, P = .001), gender ($ = .16, P = .034), and
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
nursing care reminders ($ = j.28, P G .001) were statistically significant. The second regression model was calculated to determine if there was a significant adjusted relationship between missed nursing care and I-HIT. Case mix index, RNHPPD, and gender were included as covariates in Step 1 of the equation and explained 8% of the variance in missed nursing care. After entry of I-HIT at Step 2, the total variance explained by the model as a whole was 18.8%, F4,153 change = 8.85, P G .001. Impact of HIT explained an additional 11% of the variance in missed nursing care after controlling for CMI, RNHPPD, and gender, R2 change = 0.11, F4,153 = 20.33, P G .001. In the final model, only CMI ($ = j.34, P = .003) and I-HIT ($ = j.34, P G .001) were statistically significant.
CDS systems and have improved outcomes. This is consistent with the findings in this study. Nurses who used the reminders had fewer episodes of missed nursing care. An alternate explanation for this finding may be that nurses who were more likely to use the EHR were more likely to complete their nursing care activities. As a comparative illustration, some nurses may be less accountable and neither use the EHR consistently nor make sure they complete all nursing care activities needed for their patients. An additional explanation for the findings is that this study was conducted in one hospital. The hospital culture may have had an effect on the use of the EHR reminders. In short, the nurses in this study may have been more likely to use the reminders because of organizational pressures and also may have had few episodes of missed nursing care to begin with.
Instrument Reliabilities and Validity Test-retest reliability of the MISSCARE Survey was not conducted in the current study. Reliability of the Nursing Care Reminder Usage Survey in the current study was calculated using Cronbach’s ". The Cronbach’s " was .84, indicating more than adequate reliability. Reliability of the I-HIT scale for the current study was calculated using Cronbach’s ". The Cronbach’s " was .94, indicating more than adequate reliability.
DISCUSSION The adjusted correlations support the hypotheses that there is a relationship between nursing care reminder usage and missed nursing care, and a relationship between perceptions of I-HIT and missed nursing care. The relationships are negative, indicating that nurses who report higher levels of reminder usage and favorable perceptions of I-HIT have fewer reports of missed nursing care. This makes sense as those who had higher scores on the I-HIT had positive perceptions about the impact of technology on their practice. The findings are significant as nursing care reminders may be an effective intervention to decrease episodes of missed nursing care. Although missing one instance of care may not affect overall patient outcomes, the cumulative effects may have a negative impact on patient outcomes. The use of nursing care reminders to alert nurses to cumulatively missed care may be an intervention to significantly reduce the amount of missed nursing care. In addition, nurses with higher scores for perception of I-HIT may be more apt to use nursing care reminders that may decrease episodes of missed care. The present study was the first to explore these relationships. It was hypothesized by Dykes et al4 that nurses who scored higher on the I-HIT would be more likely to use the
Implications The findings from this study have many practical implications. First, the I-HIT instrument can be used to assess the impact of technology on nursing practice. This information can then be used to evaluate HIT to determine where changes need to occur to be better aligned with clinician workflow. Workflow alignment is important, as it has been suggested that poor workflow alignment has resulted in unintended consequences of HIT.12,13 The unintended consequences can result in new errors that may not have occurred before the implementation of the HIT.9–11 A second implication is that properly designed nursing care reminders may influence usage and thus decrease the amount of missed nursing care. Reminders that nurses find helpful may result in increased usage of the reminders. There must be a balance between the quality and quantity of nursing care reminders. Reminders that are redundant or not seen as important may be missed or ignored. Missed or ignored reminders may then result in an increase in missed nursing care. One suggestion is that future designers of electronic reminders may need to consider the potential of cumulative effects of missed nursing care rather than individual instances of missed care. To illustrate, patients who are not ambulated once may not be at a disadvantage in their healing compared with a patient who has missed multiple instances of ambulation. This cumulative effect needs to be further investigated as it relates to the design of supportive technologies. A third implication drawn from the present study is that nurses need to be taught and encouraged in the proper usage of nursing care reminders. Nursing care reminders are adjuncts to clinical reasoning, and not a replacement for nurses’ knowledge and reasoning. Although a patient may have many reminders in the EHR, they may still require additional nursing care that is at the discretion of the individual nurse. The proper use of reminders by nurses
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
479
may result in fewer epiosides of missed nursing care. This may be especially true with novice nurses who may need the reminders to serve as cues of which nursing activities are appropriate for a particular patient. At the same time, more seasoned nurses may find reminders useful in validating their clinical reasoning. The reminders may be helpful for seasoned nurses who are encountering a patient with a unique or unfamiliar plan of care. This is consistent with findings from the study conducted by Dowding et al,35 in which they found novice nurses used the CDS system more frequently and more experienced nurses used the system when they encountered an unfamiliar or complex case.
Limitations and Anticipated Problems Limitations of this study include threats to internal and external validity. A threat to internal validity is that the sample size was not very large. The investigator addressed this by determining sample size a priori using a small effect size and limiting analysis to no more than four independent variables in regression analysis. Selection bias is also a possible threat to internal validity for this study, as a convenience sampling method was used. Therefore, the relationships examined in this study could be attributed to sample characteristics rather than a true relationship between the variables of interest. This threat has been addressed by determining sample size a priori as stated above and including nurse characteristics as covariates in the analyses. Instrumentation may also be a threat to internal validity of this study. The PI has addressed this by selecting instruments with proven validity and reliability and specifically designed to be used with RNs. Threats to external validity are present because of the fact that the sample may not be representative of the national RN population, and therefore the results may not be generalizable beyond the sample. The PI has taken this into consideration and has addressed this by examining the possible relationship of the nursing care reminders and missed nursing care in more than one nursing unit.
Future Research This study was a first step in establishing a link between the uses of nursing care reminders and missed nursing care. This study must be repeated with a larger sample to determine if the relationship holds. Second, the study needs to be repeated in multiple hospitals. The study hospital may have been extremely adept at using reminders, but other hospitals may have a different performance record. The present study was also conducted with only one format of the EHR; examining the relationships in organizations that use different styles of EHRs is recommended. 480
Furthermore, a concept analysis on what constitutes nursing care reminders is needed for future studies. The extant literature is void on this concept. A concept analysis should be conducted to determine the types of nursing care reminders and their empirical definitions in order to adequately measure these support tools. Reminders are not unique to nursing, so literature from other disciplines may also need to be investigated. This future research needs to be conducted to determine if there are similar or different concepts associated with reminders. Ultimately, the goal of nursing care reminder research is to develop investigator-designed reminders as interventions. These interventions will target specific missed care items. This is a challenging goal and a long-term endeavor as the different types of reminders that nurses use must be clearly defined. Also, before this progress can occur, exploratory research needs to be conducted to determine which types of reminders are effective in decreasing the specific types of missed nursing care.
CONCLUSION This study was a first step in determining if HIT has an impact on nursing care process. The study found a significant relationship between nursing care reminder usage and decreased frequency of missed nursing care. The findings can be used in a variety of improvement endeavors, such as encouraging nurses to utilize nursing care reminders, aid information system designers when designing nursing care reminders, and assist healthcare organizations in assessing the impact of technology on nursing practice. It is imperative that episodes of missed nursing care decrease in order to improve patient and organization outcomes. Nursing care reminders may be a viable solution to reduce the incidence of missed nursing care in a technology-rich healthcare environment.
REFERENCES 1. Institute of Medicine of the National Academies. To Err Is Human: Building a Safer Health System. Washington, DC: National Academies Press; 1999. 2. Institute of Medicine of the National Academies. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001. 3. Healthcare Information and Management Systems Society. HIMSS health information exchange: ARRA, HITECH FAQs related to HIE. 2009. http://www.himss.org/files/HIMSSorg/content/files/12_ 04_09_ARRAHITECHHIE_FactSheet.pdf. Accessed December 3, 2010. 4. Dykes PC, Hurley A, Cashen M, Bakken S, Duffy ME. Development and psychometric evaluation of the Impact of Health Technology (I-HIT) scale. J Am Med Inform Assoc. 2007;14(4):507–514. 5. Dykes P, Collins S. Building linkages between nursing care and improved patient outcomes: the role of health information technology. Online J Issues Nurs. 2013;18(3):1–17.
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
6. Goldsack J, Robinson E. The impact of health information technology on staffing. J Nurs Adm. 2014;44(2):117–120. 7. Kellermann A, Jones S. What it will take to achieve the as-yetunfulfilled promises of health information technology. Health Aff. 2013;32(1):63–68. 8. Goldzweig CL, Towfigh A, Maglione M, Shekelle PG. Costs and benefits of health information technology: new trends from the literature. Health Aff (Millwood). 2009;28(2):282–293. 9. Ash J, Sittig DF, Poon EG, Guappone K, Campbell E, Dykstra RH. The extent and importance of unintended consequences related to computerized provider order entry. J Am Med Inform Assoc. 2007; 14(4):415–423. 10. Han YY, Carcillo JA, Venkataraman ST, et al. Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system. Pediatrics. 2005;116(6):1506–1512. 11. Koppel R, Metlay JP, Cohen A, et al. Role of computerized physician order entry systems in facilitating medication errors. J Am Med Assoc. 2005;293(10):1197–1203. 12. Aarts J, Ash J, Berg M. Extending the understanding of computerized physician order entry: implications for professional collaboration, workflow and quality of care. Int J Med Inform. 2007;76(1):S4–S13. 13. Harrison MI, Koppel R, Bar-Lev S. Unintended consequences of information technologies in health care: an interactive sociotechnical analysis. J Am Med Inform Assoc. 2007;14(5):542–549. 14. Chen YY, Chi MM, Chen YC, Chan YJ, Chou SS, Wang FD. Using a criteria-based reminder to reduce use of indwelling urinary catheters and decrease urinary tract infections. Am J Crit Care. 2013; 22(2):105–114. 15. Hatler C, Hebden J, Kaler W, Zack J. Walk the walk to reduce catheterrelated bloodstream infections. Am Nurse Today. 2010;5(1):26–30. 16. Huang WC, Wann SR, Lin SL, et al. Catheter-associated urinary tract infections in intensive care units can be reduced by prompting physicians to remove unnecessary catheters. Infect Control Hosp Epidemiol. 2004;25(11):974–978. 17. Oniki TA, Clemmer TP, Pryor TA. The effect of computer-generated reminders on charting deficiencies in the ICU. J Am Med Inform Assoc. 2003;10(2):177–187. 18. Agency for Healthcare Research and Quality. AHRQ Patient Safety Network: Glossary. http://psnet.ahrq.gov/glossary.aspx. Accessed April 11, 2011. 19. Kalisch BJ, Landstrom G, Williams RA. Missed nursing care: errors of omission. Nurs Outlook. 2009;57(1):3–9.
20. Gravlin G, Phoenix Bittner N. Nurses’ and nursing assistants’ reports of missed care and delegation. J Nurs Adm. 2010;40(7–8): 329–335. 21. Kalisch BJ. Nurse and nurse assistant perceptions of missed nursing care: what does it tell us about teamwork? J Nurs Adm. 2009; 39(11):485–493. 22. Lawless J, Wan L, Zeng I. Patient care ‘rationed’ as nurses struggle under heavy workloads—survey. Nurs N Z. 2010;16(7):16–18. 23. Bittner NP, Gravlin G, Hansten R, Kalisch BJ. Unraveling care omissions. J Nurs Adm. 2011;41(12):510–512. 24. Kalisch BJ, Aebersold M. Interruptions and multitasking in nursing care. Jt Comm J Qual Patient Saf. 2010;36(3):126–132. 25. Brixey JJ, Robinson DJ, Johnson CW, Johnson TR, Turley JP, Zhang J. A concept analysis of the phenomenon interruption. ANS Adv Nurs Sci. 2007;30(1):E26–E42. 26. Kalisch BJ, Tschannen D, Lee KH. Missed nursing care, staffing, and patient falls. J Nurs Care Qual. 2012;27(1):6–12. 27. Schubert M, Glass TR, Clarke SP, et al. Rationing of nursing care and its relationship to patient outcomes: the Swiss extension of the International Hospital Outcomes Study. Int J Qual Health Care. 2008;20(4):227–237. 28. Kalisch BJ, Lee KH. The impact of teamwork on missed nursing care. Nurs Outlook. 2010;58(5):233–241. 29. Kalisch B, Tschannen D, Lee H. Does missed nursing care predict job satisfaction? J Healthc Manag. 2011;56(2):117–131. 30. Tschannen D, Kalisch BJ, Lee KH. Missed nursing care: the impact on intention to leave and turnover. Can J Nurs Res. 2010; 42(4):22–39. 31. Faul F, Erdfelder E, Lang A.-G, Buchner A. G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods. 2007;39(2):175–191. 32. Faul F, Erdfelder E, Lang A.-G, Buchner A. Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses. Behav Res Methods. 2009;41(4):1149–1160. 33. Kalisch BJ, Williams RA. Development and psychometric testing of a tool to measure missed nursing care. J Nurs Adm. 2009;39(5): 211–219. 34. Polit DF. Statistics and Data Analysis for Nursing Research. 2nd ed. Upper Saddle River, NJ: Pearson Education; 2010. 35. Dowding D, Randell R, Mitchell N, et al. Experience and nurses use of computerised decision support systems. Stud Health Technol Inform. 2009;146:506–510.
CIN: Computers, Informatics, Nursing & October 2014 Copyright © 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins. Unauthorized reproduction of this article is prohibited.
481
