The purpose of this study was to examine factors that contribute to adverse incidents by creating a model that included patient characteristics, clinical conditions, nursing unit context of care variables, medical treatments, pharmaceutical treatments, and nursing treatments. Data were abstracted from electronic, administrative, and clinical data repositories. The sample included older adults hospitalized during a four-year period at one, academic medical facility in the Midwestern United States who were at risk for falling. Relational databases were built and a multistep, statistical model building analytic process was used. Total registered nurse (RN) hours per patient day (HPPD) and HPPDs dropping below the nursing unit average were significant explanatory variables for experiencing an adverse incident. The number of medical and pharmaceutical treatments that a patient received during hospitalization as well as many specific nursing treatments (e.g., restraint use, neurological monitoring) were also contributors to experiencing an adverse incident. 1. Background The Institute of Medicine (IOM) report To Err is Human [1] revealed the number and significance of adverse events and errors that occur during hospitalization. The report was a call to action to transform healthcare systems to ensure patient safety and higher quality care. In one step toward healthcare transformation, the Centers for Medicare and Medicaid (CMS) no longer reimburses institutions for the care, or treatment, associated with certain hospital-acquired conditions [2]. Understanding what factors contribute to adverse incidents during hospitalization is essential to developing effective counter measures. In order to improve factors that are modifiable within a hospital structure or with healthcare delivery, it is important to first have an understanding of what is broken. There are a number of potential contributing factors that need to be considered such as the patient’s condition, the care the patient receives, and the environment in which they receive care [3, 4]. Battles and Lilford [3] provide a conceptual model for patient safety that includes antecedent conditions, which would include the patient’s comorbid conditions, the primary reason the patient was admitted to the hospital, and characteristics the patient possessed before entering the hospital. Their model also includes the structure, or environment, in which the patient receives care such as the hospital, or nursing unit. Also acting within the structure are the processes of care (the interventions or treatments)
References
[1]
Institute of Medicine, To Err Is Human: Building a Safer Health System, National Academy of Sciences, Washington, DC, USA, 2000.
[2]
U.S. Department of Health and Human Services Centers for Medicare and Medicaid Services, Hospital Acquired Conditions. http://www.cms.gov/HospitalAcqCond/06_Hospital-Acquired_Conditions.asp.
[3]
J. B. Battles and R. J. Lilford, “Organizing patient safety research to identify risks and hazards,” Quality and Safety in Health Care, vol. 12, supplement 2, pp. ii2–ii7, 2003.
[4]
M. Duckers, M. Faber, J. Cruijsberg, R. Grol, L. Schoonhoven, and M. Wensing, “Safety and risk management interventions in hospitals: a systematic review of the literature,” Medical Care Research and Review, vol. 66, suppement 6, pp. 90S–119S, 2009.
[5]
M. Titler, J. Dochterman, X. J. Xie et al., “Nursing interventions and other factors associated with discharge disposition in older patients after hip fractures,” Nursing Research, vol. 55, no. 4, pp. 231–242, 2006.
[6]
M. Titler, J. Dochterman, D. M. Picone et al., “Cost of hospital care for elderly at risk of falling,” Nursing Economics, vol. 23, no. 6, pp. 290–306, 2005.
[7]
M. Titler, “Nursing interventions and outcomes effectiveness in 3 older populations,” Tech. Rep. NR05331-02, National Institute of Nursing Research (NINR), Rockville, Md, USA, 2000.
[8]
J. M. Dochterman and G. M. Bulechek, Nursing Interventions Classification (NIC), Mosby, St. Louis, Mo, USA, 4th edition, 2004.
[9]
G. K. McEvoy, American Hospital Forumlary Service (AHFS) Drug Information 2000, American Society of Health System Pharmacists, Bethesda, Md, USA, 2000.
[10]
Public Health Service and Health Care Financing Administration, ICD-9-CM: International Classification of Diseases, 9th Revision, Clinical Modification, Public Health Service, Washington, DC, USA, 1994.
[11]
Agency for Healthcare Research and Quality (AHRQ), Healthcare Cost and Utilization Project (HCUP), Clinical Classifications Software (CCS) for ICD-9-CM, Rockville, Md, USA, 2002.
[12]
3M Health Information Systems, All Patient Refined Diagnosis Related Groups (APR-DRGs), 3M Health Information Systems, Wallingford, Conn, USA, 1993.
[13]
A. Elixhauser, C. Steiner, D. R. Harris, and R. M. Coffey, “Comorbidity measures for use with administrative data,” Medical Care, vol. 36, no. 1, pp. 8–27, 1998.
[14]
G. Budreau, R. Balakrishnan, M. Titler, and M. J. Hafner, “Caregiver-patient ratio: capturing census and staffing variability,” Nursing Economics, vol. 17, no. 6, pp. 317–324, 1999.
[15]
M. Titler, J. Dochterman, and D. Reed, Guideline for Conducting Effectiveness Research in Nursing and Other Health Services, The University of Iowa, College of Nursing, Center for Nursing Classification & Clinical Effectiveness, Iowa City, Iowa, USA, 2004.
[16]
D. Reed, M. G. Titler, J. M. Dochterman, L. L. Shever, M. Kanak, and D. M. Picone, “Measuring the dose of nursing intervention,” International Journal of Nursing Terminologies and Classifications, vol. 18, no. 4, pp. 121–130, 2007.
[17]
L. Iezzoni, Risk Adjustment for Measuring Health Care Outcomes, Health Administration Press, Chicago, Ill, USA, 3rd edition, 2003.
[18]
S. H. Cho, S. Ketefian, V. H. Barkauskas, and D. G. Smith, “The effects of nurse staffing on adverse events, morbidity, mortality, and medical costs,” Nursing Research, vol. 52, no. 2, pp. 71–79, 2003.
[19]
N. Dunton, B. Gajewski, R. L. Taunton, and J. Moore, “Nurse staffing and patient falls on acute care hospital units,” Nursing Outlook, vol. 52, no. 1, pp. 53–59, 2004.
[20]
L. M. Hall, D. Doran, and G. H. Pink, “Nurse staffing models, nursing hours, and patient safety outcomes,” Journal of Nursing Administration, vol. 34, no. 1, pp. 41–45, 2004.
[21]
P. Potter, N. Barr, M. McSweeney, and J. Sledge, “Identifying nurse staffing and patient outcome relationships: a guide for change in care delivery,” Nursing Economics, vol. 21, no. 4, pp. 158–166, 2003.
[22]
M. D. Sovie and A. F. Jawad, “Hospital restructuring and its impact on outcomes: nursing staff regulations are premature,” Journal of Nursing Administration, vol. 31, no. 12, pp. 588–600, 2001.
[23]
L. Unruh, “Licensed nurse staffing and adverse events in hospitals,” Medical Care, vol. 41, no. 1, pp. 142–152, 2003.
[24]
G. R. Whitman, Y. Kim, L. J. Davidson, G. A. Wolf, and S. L. Wang, “The impact of staffing on patient outcomes across specialty units,” Journal of Nursing Administration, vol. 32, no. 12, pp. 633–639, 2002.
[25]
J. C. Woolcott, K. J. Richardson, M. O. Wiens et al., “Meta-analysis of the impact of 9 medication classes on falls in elderly persons,” Archives of Internal Medicine, vol. 169, no. 21, pp. 1952–1960, 2009.
[26]
J. V. Agostini, D. I. Baker, and S. T. Bogardus Jr, “Prevention of falls in hospitalized and institutionalized older people,” in Making Health Care Safer: A Critical Analysis of Patient Safety Practices. Evidence Report/Technology Assessment no. 43, K. G. Shojania, B. W. Duncan, and K. M. McDonald, Eds., Agency for Healthcare Research and Quality (AHRQ), Rockville, Md, USA, 2001.
[27]
D. Evans, J. Wood, and L. Lambert, “A review of physical restraint minimization in the acute and residential care settings,” Journal of Advanced Nursing, vol. 40, no. 6, pp. 616–625, 2002.
[28]
T. Hoff, L. Jameson, E. Hannan, and E. Flink, “A review of the literature examining linkages between organizational factors, medical errors, and patient safety,” Medical Care Research and Review, vol. 61, no. 1, pp. 3–37, 2004.
[29]
R. L. Kane, T. Shamliyan, C. Mueller, S. Duval, and T. J. Wilt, “Nurse staffing and quality of patient care,” Evidence Report/Technology Assessment, no. 151, pp. 1–115, 2007.
[30]
D. M. Picone, M. G. Titler, J. Dochterman et al., “Predictors of medication errors among elderly hospitalized patients,” American Journal of Medical Quality, vol. 23, no. 2, pp. 115–127, 2008.