Tag: Clinical-Nursing

Describe The Definition Of Nursing As Put Forward By The American Nurses Association. How Does It Address The Metaparadigm Theories Of Nursing?

Describe how the concepts of leadership and management differ from each other. In what areas do they overlap? Explain how the goals of management and leadership may sometimes overlap. As a nurse leader, do you believe you can expand your influence to create change by taking advantage of this overlap? Explain your answer.

Characteristics of a population appropriate to use mean/median/mode

What are the characteristics of a population for which it would be appropriate to use mean/median/mode? When would the characteristics of a population make them inappropriate to use?

The article titled “Who has higher readmission rates for heart failure, and why?: Implications for efforts to improve care using financial incentives” by, Joynt, K. and Jha, A. (2010), will be reviewed and critiqued for this paper. The purpose of this article was to explore factors, which allow some hospitals more successful outcomes at preventing heart failure readmissions than others. The authors evaluated hospital characteristics in the hopes of determining how to “most effectively facilitate quality improvement initiatives to decrease heart failure readmissions.”  (Joynt&Jha, 2010).  The authors imply that understanding what hospital characteristics influence heart failure readmissions can aid in the development of programs to avoid pay-for-performance (P4P) penalties.  Joynt&Jha (2010) also hypothesize hospitals with limited monetary and medical resources will experience higher penalties.

Evaluation of the Concept

Patient Protection and Affordable Care Act of 2010 implemented P4P as a method for influencing quality improvement initiatives for hospitals by offering rewards for those who are highly successful (Medicare.gov, 2015).  Designed to improve quality, these payment programs contain the potential to penalize hospitals who are already resource limited and experiencing financial hardships.  According to the authors, heart failure is the most common cause of admissions and readmissions among Medicare patients costing the nation more than 17 billion dollars a year (Joynt&Jha, 2010).  Estimates claim that one in four patients with heart failure will be readmitted to the hospital within 30 days of discharge.  “These rates suggest tremendous opportunity for improvement.”  (Joynt&Jha, 2010).

Reviewing the literature, the authors found studies have looked at patients at risk for readmission due to heart failure, but little work has evaluated the hospitals themselves (Joynt&Jha, 2010).  Joynt&Jha (2010) found two studies that concluded no difference between types of hospitals; however, the authors felt both studies used a method designed to reduce variability that could unduly influence the findings of the study.  These hypothesizes are written to lead the reader to believing variability may be the answer to what influences readmission rates among hospitals and support the idea of the study.  With little data to define which hospitals would experience higher readmission rates and would face penalties, the authors furtherconsidered physical resources in an attempt to establish a link to readmitted patients.  In order to establish which hospitals to evaluate for limited resources, Joynt and Jha (2010) appraised public hospitals, hospitals in poor counties nationally, as well as, hospitals without cardiac services.  Small hospitals were also gauged based on the assumption they have few financial and clinical resources and face challenges similar to public and poor hospitals (Joynt&Jha, 2010).  In 2014, Anderson wrote a commentary that discussed the first year of the Hospital Readmissions Reduction Program which issued penalties totaling more than 227 million dollars.  This had the greatest impact on of poorest hospitals in the country and further confirmedJoynt&Jha’sconcern written in 2010.

Utilizing Medicare Provider Analysis Review (MedPAR) data, the authors examined heart failure patient hospitalizations for 23 months and each patient for thirty days post discharge excluding federal hospitals, those outside the United States, and the District of Columbia.  23 months was used as the study took place over two physical years and required a full 30 day review.  Recommendations from the Joint Commission advised that hospitals with less than 25 discharges over the specified time frame also be excluded leaving a total of 4091 hospitals for analysis, a significant sample size (Joynt&Jha, 2010).  Using published survey results from the American Hospital Association of 2007, characteristics of those 4091 hospitals were collected “including hospital size, cardiac services, ownership, nurses on staff, and proportion of hospitalized patients with Medicaid or Medicare insurance, membership in the Council of Teaching Hospitals, location, and region.” (Joynt&Jha, 2010).  Staffing ratios and county median income where the hospital was physically located was also collected to include in the analysis.  Providing analysis around this number of characteristics gave the authors the ability to look at how variable resources may affect readmission rates versus a methodology that normalizes the data in an effort to equalize hospital performance for public reporting (Joynt&Jha, 2010).  Ash, Fienberg, Louis, Normand, Stukel, and Utts (2012) discussed how the Bayesian shrinkage model used by CMS eliminates volume or the ability to adapt for low volumes placing smaller capacity hospitals at higher risk for failure related to performance.  A metric measure where small hospitals are not truly equal or capable to other hospitals; however, are judged in the same manner again echoesJoynt and Jha concerns from 2010.

The authors chose to create “a set of multivariate logistic regression models, using generalized estimating equations, in which the response probability distribution was binary; allowed us to use logistic regression but also to account for clustering of patients within hospitals.” (Joynt&Jha, 2010).  Logistic regression methodology allowed for evaluation of each of hospital characteristics and to then compare the findings to hospitals that would be at risk for penalties.  Both the Bayesian shrinkage model and the multivariable model was used to run the data setting up a compare and contrast.  Differences were obvious and confirmed the author’s hypothesis that the Bayesian shrinkage model penalized smaller hospitals when volume is eliminated.  Joynt&Jha (2010) found that performance was likely to remain in the worst quartile if the hospital was public or lacked the clinical and financial resources just as they had predicted.  All of these characteristics demonstrated a statistical significance when outlined in themultivariate analysis giving the study more credibility and confirming the hypothesis of Joynt and Jha (2010).

Application of Concept

           
About five million people are currently diagnosed with heart failure in the United States according to the Centers for Disease Control and Prevention (2014).  Due to the dynamics of heart failure, more than 32 billion dollars will be spent in an effort to provide care and medications for these patients each year (CDC, 2014).  Based upon these costs, Centers for Medicaid and Medicare Services passed a rule identifying heart failure readmissions within 30 days as an element for penalty under the Hospital Readmissions Reduction Program (CMS, 2015).  Using the findings of Joynt&Jha (2010) hospitals at risk for penalties should evaluate hospitals that were considered resource-poor or financially poor and performed well on avoiding readmissions.  Identifying these differing hospital characteristics allows a smaller organization or an organization with limited financial resources to restructure or redesign their approach to avoiding readmissions.  In an article by Bradley et al. (2013), six strategies were identified which may require little fiscal investment such as medication reconciliation by a registered nurse, arranging a follow up appointment prior to discharge, and partnerships with community physicians to develop solutions to avoid readmissions.As pay-for-performance matures, patients, physicians, and nurses must urge legislation to evaluate the impact of penalties.  Communities with financial and clinical resource limitations must demand that investments be made to enrich the opportunity to obtain quality care in their town or city.  According to James (2012), if resources are not allocated to lower income areas, P4P penalties will only exacerbate the lack of care provided to the patients who need it most.

 

References

Anderson, A. (2014).  The impact of the affordable care act on the healthcare workforce.
The

Backgrounder 2887
:  1-20.

Ash, A., Fienber, S., Louis, T., Norman, S., Stukel, T., and Utts, J. (2012).  Statistical issues in

assessing hospital performance. 
Quantitative Health Sciences Publications and Presentations
.  Paper 1114.  Retrieved on September 8, 2015 from http://escholarship.umassmed.edu/qhs_pp/1114.

Bradley, E., Curry, L., Horwitz, L., Sipsma, H., Wang, Y., Walsh, M…Krumholz, H. (2013).

Hospitals strategies associated with 30-day readmission rates for patients with heart failure. 
Circulation:  Cardiovascular Quality and Outcomes 2013
(6):  444-450.  doi:  10.1161/CIRCOUTCOMES.111.0001.01.

CDC (2014).  Division for heart disease and stroke prevention:  heart failure fact sheet.

Retrieved on September 9, 2015 from http://www.cdc.gov/dhdsp/data_statistics/fact_sheets/fs_heart_failure.htm.

CMS (2015).Readmissions reduction program.  Retrieved on September 9, 2015 from

https://www.cms.gov/medicare/medicare-fee-for-service-payment/acuteinpatientpps/readmissions-reduction-program.html
.

James, J. (2012).  Pay for performance: new payment systems reward doctors and hospitals for

improving the quality of care, but studies to date show mixed results. 
Health Policy Brief 2012
:  1-6.

Joynt, K., and Jha, A. (2010).  Who has higher readmission rates for heart failure, and why?:

implications for efforts to improve care using financial incentives. 
Circulation:  Cardiovascular Quality Outcomes 2011
(4):  53-39.  doi:  10.1161/CIRCOUTCOMES.110.950964.

Medicare.gov (2015).  Hospital Compare:  linking quality to payment.  Retrieved on September

8, 2015 from
https://www.medicare.gov/hospitalcompare/linking-quality-to-payment.html
.

Walden University NURS 6330 Curriculum Development, Assessment, & Evaluation

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Walden University NURS 6330 Curriculum Development, Assessment, & Evaluation Required Course Readings

 The links are for required readings found in the Walden databases 
ONLY
. For all other readings, see your course resources.

Enter your myWalden user name and password at the prompt.

Behar-Horenstein, L. S., Guin, P., Gamble, K., Hurlock, G., Leclear, E., Philipose, M., et al. (2005). Improving patient care through patient-family education programs.
 Hospital Topics, 83
(1), 21–27.

Habanek, D. V. (2005). An examination of the integrity of the syllabus. 
College Teaching, 53
(2), 62–64.

Jordan, S. (2000). Educational input and patient outcomes: Exploring the gap.
 Journal of Advanced Nursing, 31
(2), 461–471.

Lee, V., Fletcher, K., Westley, C., & Fankhauser, K. (2004). Competent to care: Strategies to assist staff in caring for elders.
MEDSURG Nursing,13
(5), 281–289.

Messner, E. R., Reck, D. L., & Curci, K. M. (2005). Effectiveness of a patient education brochure in the emergency department. 
Topics in Emergency Medicine, 27
(4), 251–255.

Silvestrone, J. M. (2004). Performance-based assessment: Improving the value of laboratory and skills examinations.
 New Directions for Teaching & Learning
, 100, 65–71.

Slattery, J. M., & Carlson, J. F. (2005). Preparing an effective syllabus: Current best practices. 
College Teaching, 53
(4), 159–164.

Westley, C. (2004). Pain: Geriatric self-learning module. 
MEDSURG Nursing, 13
(6), 399–404.

Walden University NURS 6331 Teaching Learning Strategies: Integrating Technology into Nursing Education

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Walden University NURS 6331 Teaching Learning Strategies: Integrating Technology into Nursing Education Required Course Readings

 The links are for required readings found in the Walden databases 
ONLY
. For all other readings, see your course resources.

Enter your myWalden user name and password at the prompt.

Hickey, M. T., Forbes, M., & Greenfield, S. (2010). Integrating the Institute of Medicine competencies in a baccalaureate curricular revision: Process and strategies. 
Journal of Professional Nursing, 26
(4), 214–222.

Isaacson, J. J., & Stacy, A. S. (2009). Rubrics for clinical evaluation: Objectifying the subjective experience. 
Nurse Education in Practice, 9
(2), 134–140.

Shank, P. (2005). Writing learning objectives that help you teach and students learn (Part 1). 
Online Classroom
, 4–7.

Truemper, C. M. (2004). Using scoring rubrics to facilitate assessment and evaluation of graduate-level nursing students. 
Journal of Nursing Education, 43
(12), 562–564.

NURS 6340 The Nurse Educator: Roles, Responsibilities, & Relationships

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NURS 6340 The Nurse Educator: Roles, Responsibilities, & Relationships Required Course Readings

The links are for required readings found in the Walden databases ONLY. For all other readings, see your course resources.

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Blauvelt, M.J. & Spath, M.L. (2008). Passing the torch: A faculty mentoring program at one school of nursing.
 Nursing Education Perspectives, 29
(1), 29-33.

DeGroft, S. (1998). CHES: Committed to education. 
Nursing Management, 29
(11), 65–66.

Hohler, S. E. (2004). Tips for better patient teaching. 
Nursing, 34
(7), 32.

Thorpe, K. & Kalischuk, R.G. (2003). A collegial mentoring model for nurse educators. 
Nursing Forum, 38
(1), 5-14.

Walden University NURS 3005 Context of Healthcare Delivery

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Walden University NURS 3005 Context of Healthcare Delivery Required Course Readings

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Please 
Ask a Librarian
 if you have any questions about the links.

Adler-Milstein, J. Kvedar, J., and Bates D. W. (2014). Telehealth among US hospitals: Several factors, including state reimbursement and licensure policies, influence adoption. 
Health Affairs, 33
(2), 2207-215. 
NOTE: This article is not available in the Walden Library. Please use Talbot (below)

Abiola, S. E., Colgrove, J., and Mello, M. M. (2013). The politics of HPV vaccination policy formation in the United States. Journal of Health Politics, Policy & Law Aug; 38(4): 645-81.

Auerbach, D., Staiger, D. O., Muench, U., and Buerhaus, P. I. (2013). The nursing workforce in an era of health care reform. The New England Journal of Medicine april; 368: 1470-1472

Avila, R. and Bramiett, M. (2013). Language and immigrant status effects on disparities in Hispanic children’s health status and access to health care. Maternal & Child Health Journal Apr; 17(3): 415-23.

Battie, R. and Steelman, V. (2014). Accountability in nursing practice: Why it is important for patient safety. Association of perioperative Registered Nurses Journal,100(5), 537-541. 
NOTE: This article is not available in the Walden Library. Please use
Oestberg or Fuchs.

Brown, Lawrence D. and Gusmano, M. K. (2013). Introduction: Evaluation in analytic theory and political practice. Journal of Health Politics, Policy & Law Dec; 38(6): 1071-9.

Chandra, A., Dalton, M., and Holmes, J. (2013). Large increases in spending on postacute care in medicare point to the potential for cost savings in these settings. Health Affairs May; 32(5): 864-72.

Collins, S., Piper, K. B., and Owens, G. M. (2013). The opportunity for health plans to improve quality and reduce costs by embracing primary care medical homes. American Health & Drug Benefits Jan-Feb; 6(1): 1-7

Cosgrove, D. M., Fisher, M., Gabow, P., Gottlieb, G., Halvorson, G. C., James, B., C., Kaplan, G. S., Perlin, J. B., Petzel, R., Steele, G. D., and Toussaint, J. S. (2013). Ten strategies to lower costs, improve quality, and engage patients: The view from leading health system CEOs. Health Affairs, Feb; 32(2): 321-7.

Dennis, A., Blanchard, K., Cordova, D., Wahlin, B., Clark, J., Edlund, K., McIntosh, J., and Tsiktas, L. (2013). What Happens to the Women Who Fall through the Cracks of Health Care Reform? Lessons from Massachusetts. Journal of Health Politics, Policy & Law Apr; 38(2): 393-419.

Eaton, M. K. (2012). Professional advocacy linking Virginia’s story to public policy-making theory, learning from the past and applying it to our future. Policy, Politics, & Nursing Practice,13(2), 105-112.

Ewing, M. (2013). The patient-centered Medical home solution to the cost-quality conundrum. Journal of Healthcare Management Jul-Aug; 58(4): 258-66.

Faiman, J. and D’Antonio (2013). History counts: How history can shape our understanding of health policy. Nursing Outlook Sept-Oct; 61(5): 346-352.

Fuchs, J. The legislative process (2014). AAACN Viewpoint Jan-Feb; 36(1): 14-5.

Grob, R., Schlesinger, M., Davis, S., Cohen, D., and Lapps, J. (2013). The affordable care act’s plan for consumer assistance with insurance moves states forward but remains a work in progress. Health Affairs 32(2): 347-356.

Herrera, A.P., George, R., Angel, J. L., and Markides, K., Torres-Gil, F. (2013). Variation in older Americans act caregiver service use, unmet hours of care, and independence among Hispanics, African Americans, and Whites. Home Health Care Services Quarterly Jan-Mar; 32(1): 35-56.

Nickitas, D. M. (2013). Health care spending: The cold, hard facts on cost, quality, and care. Nursing Economic$ Jan-Feb; 31(1): 5-11.

Oestberg, F. Policy and politics: Why nurses should get involved (2012). Nursing Dec; 42(12): 46-49.

Primomo, J. and Bjoling, E. (2013). Changes in political astuteness following nurse legislative day. Policy, Politics, & Nursing Practice May; 14(2): 97-108.

Ruiz-Casares, M., Rousseau, C., Laurin-Lamothe, A., Rummens, J., Zelkowitz, P., Crepeau, F., and Steinmetz, N. (2013) Access to Health Care for Undocumented Migrant Children and Pregnant Women: The Paradox Between Values and Attitudes of Health Care Professionals. Maternal & Child Health Journal Feb; 17(2): 292-8.

Sabella, D. (2012). PTSD among our returning veterans. How to recognize and assist veterans with this increasingly common mental health disorder. American Journal of Nursing, 112 (11), 48-52.

Sarna, L., Bialous, S. A., Chan, S., Hollen, P., and O’Connell, K. A. (2013). Making a difference: Nursing scholarship and leadership in tobacco control. Nursing Outlook Jan-Feb; 61(1): 31-42.

Spetz, J., Parente, S. T., Town, R. J., and Bazarko, D. (2013). Scope-of-practice laws for nurse practitioners limit cost savings that can be achieved in retail clinics. Health Affairs Nov 32(11): 1977-1984.

Stuart, B., Loh, F., Roberto, P., and Miller, L. (2013). Increasing medicare part d enrollment in medication therapy management could improve health an lower costs. Health Affairs Jul; 32(7): 1212-20.

Talbot, J., Coburn, A., Croll, X., Ziller, E. (2013). Rural considerations in establishing network adequacy standards for qualified health plans in state and regional health insurance exchanges. Journal of Rural Health,  29(3), 327-35.

Walden University Exams & Assignments – NURS 6201 Leadership in Nursing & Healthcare

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Walden University Exams & Assignments – NURS 6201 Leadership in Nursing & Healthcare Required Course Readings

The links are for required readings found in the Walden databases ONLY. For all other readings, see your course resources.

Enter your myWalden user name and password at the prompt.

Abraham, M., & Moretz, J. (2012). Implementing patient- and family-centered care: Part I—Understanding the challenges. 
Pediatric Nursing, 38
(1), 44–47.

Auer, C., Schwendimann, R., Koch, R., De Geest, S., & Ausserhofer, D. (2014). How hospital leaders contribute to patient safety through the development of trust. Journal of Nursing Administration, 44(1), 23–29. 

Daly, R. (2014). Building blocks for organizational change. Healthcare Financial Management: Journal of the Healthcare Financial Management Association, 68(5), 68–73.

Davis, P., Milne, B., Parker, K., Hider, P., Lay-Yee, R., Cumming, J., and Graham, P. (2013). Efficiency, effectiveness, equity (E3). Evaluating hospital performance in three dimensions. Health Policy, 112, 19–27

Dekker, S. & Nyce, J. (2013). Just culture: “Evidence, power and algorithms. Journal of Hospital Administration, 2(3), 73–78.

Falkheimer, J. (2014). The power of strategic communication in organizational development. International Journal of Quality and Service Sciences, 6(2/3), 124–133. 

Faulkner, J., & Laschinger, H. (2008). The effects of structural and psychological empowerment on perceived respect in acute care nurses. Journal of Nursing Management, 16(2), 214–221. 

Fry, B. (2013). Power up your leadership: Straight talk for nurse managers. Canadian Nurse, 109(5), 32–33.

Gittner, L.S.,Husaini, B.A., Hull, P.C., Emerson, J.S., Tropez-Sims, S. Reece, M., Zoorah, R. and Levine, R.S. (2015). Use of Six Sigma for eliminating missed opportunities for prevention services.Journal of Nursing Care Quality. DOI: 10.1097/NCQ.0000000000000113

Gleich, S.J.M.,Nemergut, M.E., Stans, A.A.,  Haile, D.T.,  Feigal, S.A.,  Heinrich, A.L., Bosley, C.L., Wardand, J.W., and  Tripathi, S.. (2015). Lean Six Sigma handoff process between operating room and pediatric ICU: improvement in patient safety, efficiency and effectiveness. Critical Care 2015, 19 (Suppl 1): P523. DOI:10.1186/cc14603

Groysberg, B., & Slind, M. (2012). Leadership is a conversation. Harvard Business Review, 90(6), 76–84. 

Huston, C. J. (2013, May 2013). The impact of emerging technology on nursing care: Warp speed ahead.The Online Journal of Issues in Nursing, 18(2) Manuscript 1. DOI: 10.3912/OJIN.Vol18No02Man01.

Kumar, S., Deshmukh, V., & Adhish, V. S. (2014). Building and Leading Teams. Indian Journal of Community Medicine : Official Publication of Indian Association of Preventive & Social Medicine, 39(4), 208–213. doi:10.4103/0970-0218.143020

Leach, L., & McFarland, P. (2014). Assessing the professional development needs of experience nurse executive leader. Journal of Nursing Administration 44(1), 51062. 

Mclean, C. (2011). Change and transition: Navigating the journey. British Journal of School Nursing,6(3), 141–145.

Mitchell, G. (2013). Selecting the best theory to implement planned change. Nursing Management-UK, 20(1), 32–37. 

Ng, G., Leung, G., Johston, J., and Cowling, B. (2013). Factors affecting implementation of accreditation programmes and the impact of the accreditation process on quality improvement in hospitals: a SWOT analysis. Hong Kong Medical Journal, 19, 434–46. DOI: 10.12809/hkmj134063

Perkins, M., Grey, A., and Remmers, H. (2013). What do we really mean by “Balanced Scorecard”? International Journal of Productivity and Performance Management, 63(2). DOI 10.1108/IJPPM-11-2012-0127

Radtke, K., (2013). Improving patient satisfaction with nursing communication using bedside shift report.Clinical Nurse Specialist, 27(1), 19–25.

Reiman, T., Rollenhagen, C., Pietikäinen, E., Heikkilä, J. (2015). Principles of adaptive management in complex safety–critical organizations. Safety Science, 71, 80–92.

Salmela, S., Eriksson, K., & Fagerström, L. (2013). Nurse leaders’ perceptions of an approaching organizational change. Qualitative Health Research, 23(5), 689–699.

Shirey, M. R. (2012). Cultivating strategic thinking skills. JONA: The Journal of Nursing Administration, 42(6), 311–314. 

Shirey, M. R. (2013). Lewin’s theory of planned change as a strategic resource. The Journal of Nursing Administration 43(2), 69–72.

Simons, T., & Leroy, H. (2014). Issues in researching leadership in health care organizations. Leading in Health Care Organizations: Improving Safety, Satisfaction and Financial Performance (Advances in Health Care Management, Volume 14) Emerald Group Publishing Limited, 14, 221–234. 

Spreitzer, G., & Porath, C. (2012). Creating sustainable performance. Harvard Business Review, 90(1/2), 92–99. 

Stetler, C. B., Ritchie, J. A., Rycroft‐Malone, J., & Charns, M. P. (2014). Leadership for Evidence‐Based Practice: Strategic and Functional Behaviors for Institutionalizing EBP. Worldviews on Evidence‐Based Nursing, 11(4), 219–226.

Top, M., Akdere, M., & Tarcan, M. (2014). Examining transformational leadership, job satisfaction, organizational commitment and organizational trust in Turkish hospitals: public servants versus private sector employees. The International Journal of Human Resource Management, (ahead-of-print), 1–24. 

Trivella, P., Gerogiannis, V., & Svarna, S. (2013). Exploring Workplace Implications of Emotional Intelligence (WLEIS) in Hospitals: Job Satisfaction and Turnover Intentions. Procedia-Social and Behavioral Sciences 73(27). 701–709.

van der Kam, N. A., van der Vegt, G. S., Janssen, O., & Stoker, J. I. (2014). Heroic or hubristic? A componential approach to the relationship between perceived transformational leadership and leader–member exchanges. European Journal of Work and Organizational Psychology, (ahead-of-print), 1–16.

Van der Linden, D., Tsaousis, I., & Petrides, K. V. (2012). Overlap between General Factors of Personality in the Big Five, Giant Three, and trait emotional intelligence. Personality and Individual Differences, 53(3), 175–179.

Wong, C. A., Cummings, G. G., & Ducharme, L., (2013). The relationship between nursing leadership and patient outcomes: a systematic review update. Journal of Nursing Management, 21(5), 709–724.

Walden University NURS 3010 Information Management in Nursing & Healthcare

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NURS 3010 Required Course Readings

The links are for required readings found in the Walden databases ONLY. For all other readings, see your course resources.

Enter your myWalden user name and password at the prompt.

Bokur, D. (2012). To ‘EACH’ its own incentive payment: New CCHIT program rewards groups with EHR systems. 
MGMA Connexion
, 12(2), 33–34.

Bolla, Y. (2011). Meaningful use 101. 
Nursing Management
, 42(8), 18–22.

Early, C., Riha, C., Martin, J., Lowdon, K. W., & Harvey, E. M. (2011). Scanning for safety: an integrated approach to improved bar-code medication administration. CIN: Computers, 
Informatics, Nursing
, 29(3), 157-164.

Egelstaff, R., & Wells, M. (2013). Data governance frameworks and change management. 
Studies In Health Technology And Informatics,
 193, 108-119.

Hebda, Toni, RN,PhD., M.S.I.S., & Patton, Carol, DrPH, RN, FNP-BC,C.R.N.P., C.N.E. (2012). Application of the relationship-based care model to improve health outcomes via the electronic personal health record. 
Creative Nursing
, 18(1), 30-3.

HIMSS Nursing Informatics Awareness Task Force. (2007). An emerging giant: Nursing informatics. 
Nursing Management
, 38(3), 38–42.

Hunter, K. M., McGonigle, D. M., & Hebda, T. L. (2013). TIGER-based measurement of nursing informatics competencies: The development and implementation of an online tool for self-assessment. 
Journal of Nursing Education and Practice, 3
(12), p70. 

Huryk, L.A. (2011). Interview with an informaticist. 
Nursing Managemen
t, 42(11), 44–48.

Jones, S. S., Rudin, R. S., Perry, T., & Shekelle, P. G. (2014). Health Information Technology: An Updated Systematic Review With a Focus on Meaningful Use. 
Annals Of Internal Medicine, 160
(1), 48-54.

Kiel, J. M., Thede, L. Q. (2012). HIPAA and its effect on informatics. Computers, Informatics, 
Nursing Volume, 
30(1) 1-5.

Levy, S., & Heyes, B. (2012). Information systems that support effective clinical decision making. 
Nursing Management – UK, 19
(7), 20-22.

Liu, W. (2014). Clinical knowledge management: Using Extensible Markup Language to characterize clinical decision support.
American Journal Of Health-System Pharmacy
, 71(12), 994-997.

Matney, S., Brewster, P. J., Sward, K. A., Cloyes, K. G., & Staggers, N. (2011). Philosophical approaches to the nursing informatics data-information-knowledge-wisdom framework. 
Advances in Nursing Science
, 34(1), 6-18.

McGonigle, D., Hunter, K., Sipes, C., & Hebda, T. (2014). Why nurses need to understand nursing informatics. Association of Operating Room Nurses.
AORN Journal, 100
(3), 324-327. doi:http://dx.doi.org/10.1016/j.aorn.2014.06.012

Mitchell, J. K. (2011). Nursing informatics 101: Using technology to improve patient care. 
ONS Connect
, 26(4), 8–12.

Murphy, J. (2010). Nursing informatics: the intersection of nursing, computer, and information sciences. 
Nursing Economic$
, 28(3), 204-207.

Murphy, J. (2011). The nursing informatics workforce: Who are they and what do they do?
 Nursing Economic$
, 29(3), 150–153.

O’Sullivan, D., Fraccaro, P., Carson, E., & Weller, P. (2014). Decision time for clinical decision support systems. 
Clinical Medicine
, 14(4), 338-341. 

Penoyer, D. A., Cortelyou-Ward, K. H., Noblin, A. M., Bullard, T., Talbert, S., Wilson, J., … & Briscoe, J. G. (2013). Use of electronic health record documentation by healthcare workers in an acute care hospital system. 
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