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The purpose of this study was to examine reciprocal relationships between behavioral, environmental and personal factors related to UC nurses’ documentation of diabetes pay for performance (P4P) data in the current Electronic Health Record (EHR) system.
Research Questions
- What is the relationship between Urgent Care (UC) nurse’s attitudes towards the EHR and their compliance with documenting diabetes P4P data in the EHR?
- What is the relationship between UC nurse’s perceptions of positive formative feedback from their supervisor and their average percentage compliance of P4P data entered?
- What is the relationship between the UC nurse’s attitudes towards the EHR and their perceived formative feedback from their supervisor?
- What other personal or environmental factors influence an UC nurse’s documentation within the EHR?
Background and Significance
Diabetes is a deleterious disease affecting 347 million people worldwide (WHO, 2012). Diabetes mellitus is one of the top twenty reasons patients sought outpatient care (CDC, 2009). Sixty-seven percent of type two diabetics have elevated blood pressures (BP) (Suh et al., 2009). The projected prevalence of diabetes mellitus will increase by two-thirds between 2008-2030 (WHO, 2012).
Through the Affordable Care Act (ACA), UC visits could increase exponentially (UC Association of America, 2012). UCs can offer episodic care to diabetic patients. They have the potential of easing burdens on Emergency Rooms (ER), saving patients and insurance companies money while upholding the same quality.
Research demonstrates that nurses contribute to improved diabetes outcomes (Philis-Tsimikas & Walker, 2001; Philis-Tsimikas et al., 2004; Ishani et al., 2011). Available research regarding the role of ambulatory care nurses on diabetes quality of care is minimal. Research regarding the impact that UC nurses have on diabetes quality of care could not be located.
Nurses play the most important role in documenting patient’s care because they are at the patient’s side most (Langowski, 2005). Nowadays, nurses are responsible for documenting patients’ care in an EHR. In California alone, $124.6 million is budgeted for health care IT (HHS, 2011). There are conflicting reports on whether EHR-using sites fair better in diabetes patient care and outcomes than those without EHRs. JCAHO endorses the use of EHRs (2007) because they can enhance the accuracy of patient data collection and ease of retrieval (Green & Thomas, 2008).
No published research could be located that focused on EHR usage in UCs and amongst UC nurses. Furthermore, it has been more than ten years since research has examined the attitudes of nurses towards EHRs. Technology has since progressed and more organizations have thus adopted EHRs. Lacey (1993) wrote that, “As with any type of innovation, change is more easily facilitated if end-users have positive attitudes about the change”. Huryk & Eneh have demonstrated that positive feedback from management led to more positive attitudes amongst employees (2010; 2012).
UC nurses can have a strong impact on the documentation of and quality of outpatient diabetes care within the EHR, but have been neglected in current research literature. It would be prudent to have a current study on the attitudes of these nurses towards EHRs as well as what motivates or demotivates them to document important diabetes data.
Research Design and Methods
A descriptive correlational design was used to examine the reciprocal relationships between behavioral, environmental and personal factors as they relate to the quality of diabetes care rendered by UC nurses. The target population included all RNs who have worked in one of the UCs within the past year. The UC leadership team as well as employees who have assisted with the development of the EHR were excluded.
The research was approved by the UC and University Institutional Review Board (IRB). Written approval was obtained from all related leaders. Email invitations were extended to all full-time, part-time per-diem, and internal staffing UC RNs. The invitations provided an overview of the study, including potential risks, benefits, inclusion and exclusion criteria, as well as details about provisions undertaken to ensure participant privacy. RNs who participated completed the attached secretly coded surveys.
Surveys included the researcher-developed demographic questionnaire, Stronge & Brodt’s (1985) Nurses’ Attitudes Towards Computerization (NATC) questionnaire as well as Palomo’s (2010) Supervisory Relationship Questionnaire (SRQ). Completed surveys were returned to the researcher in person, via fax, email or interoffice mail. Four weeks were provided for participants to complete and return questionnaires. However, due to low enrollment, the researcher extended the enrollment period another four weeks upon IRB approval.
The researcher then audited charts of diabetic patients who had been seen in the UC and triaged by the nurse participants within the past year. The researcher assessed whether or not the UC nurse met the diabetes P4P BP quality data such as: was (1) a baseline BP taken, (2) patient’s BP greater than 140/90, (3) patient’s BP rechecked manually after at least 5 minutes rest and (4) did the nurse inform the provider of abnormal BPs within 5 minutes of identification. Patient charts were excluded that had the following active diagnoses, which are usually exempt from P4P guidelines (IHA, 2012): polycystic ovary disease, steroid induced diabetes and gestational diabetes.
Data Analysis
Currently in progress. However, descriptive statistics will be used to describe the sample of UC RNs. Some of the descriptors about the population under study that will be reported include, but are not limited to: the percentage of males versus females, percentage of regular staff versus registry as well as the numbers of full time, part time and per diem RN participants.
Inferential statistics will be utilized to help make educated generalizations about the UC RNs in the health care organization that was studied. Furthermore, the researcher will also test for correlations between variables. These statistics will uncover whether variables such as gender, age, education, employment status, computer experience and number of years working in the UC affect an employee’s attitude towards the EHR, their propensity of recording P4P data within the EHR and whether they perceive receiving formative feedback from their supervisor.
The two instruments that were used in this study have previously established reliability and validity. However, the SRQ is a fairly new tool and it’s psychometrics have not yet been verified amongst U.S. nurses. Additionally, the researcher could not locate any research publications where the SRQ and NATC have been used in combination. Therefore, the researcher will do psychometric testing on the two tools in this study.
An improved understanding of the relationships, if any, between the trifecta of behavioral, personal and environmental factors surrounding EHR usage may improve a healthcare organization’s investments in outpatient EHR adoption, training and technology. All of which can ultimately impact the quality of care rendered amongst the increasing number of outpatient facilities using EHRs.