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1 CLINICAL INVESTIGATIONS Hospital-Acquired Pressure Ulcers: Results from the National Medicare Patient Safety Monitoring System Study Courtney H. Lyder, ND,* Yun Wang, PhD, k Mark Metersky, MD, # Maureen Curry, MHA, Rebecca Kliman, MPH,** Nancy R. Verzier, MSN, and David R. Hunt, MD OBJECTIVES: To determine the national and state incidence levels of newly hospital-acquired pressure ulcers (PUs) in Medicare beneficiaries and to describe the clinical and demographic characteristics and outcomes of these individuals. DESIGN: Retrospective secondary analysis of the national Medicare Patient Safety Monitoring System (MPSMS) database. SETTING: Medicare-eligible hospitals across the United States and select territories. PARTICIPANTS: Fifty-one thousand eight hundred fortytwo randomly selected hospitalized fee-for-service Medicare beneficiaries discharged from the hospital between January 1, 2006, and December 31, MEASUREMENTS: Data were abstracted from the MPSMS, which collects information on multiple hospital adverse events. RESULTS: Of the 51,842 individuals in the MPSMS 2006/07 sample, 2,313 (4.5%) developed at least one new PU during their hospitalization. The mortality risk adjusted odds ratios were 2.81 (95% confidence interval (CI) = ) for in-hospital mortality, 1.69 (95% CI = ) for mortality within 30 days after discharge, and 1.33 (95% CI = ) for readmission within 30 days. The hospital risk adjusted main length of stay was 4.8 days (95% CI = days) for individuals who did not develop PUs and 11.2 days (95% CI = ) for those with hospital-acquired PUs (P <.001). From the *School of Nursing, University of California at Los Angeles, Los Angeles, California; Health System Patient Safety Institute, University of California at Los Angeles, Los Angeles, California; Qualidigm, Middletown, Connecticut; Centers for Outcomes Research and Evaluation, Yale University, New Haven, Connecticut; k Yale-New Haven Health, New Haven, Connecticut; # Division of Pulmonary and Critical Care Medicine, School of Medicine, University of Connecticut, Farmington, Connecticut; **Office of Clinical Standards and Quality, Centers for Medicare and Medicaid Services, Baltimore, Maryland; and Office of Health Information Technology Adoption, Office of the National Coordinator for Health IT, Washington, District of Columbia. Address correspondence to Courtney H. Lyder, Los Angeles School of Nursing, University of California, 700 Tiverton Avenue, Factor Building, 2 256, Los Angeles, CA DOI: /j x The Northeast region and Missouri had the highest incidence rates (4.6% and 5.9%, respectively). CONCLUSION: Individuals who developed PUs were more likely to die during the hospital stay, have generally longer hospital lengths of stay, and be readmitted within 30 days after discharge. J Am Geriatr Soc 60: , Key words: pressure ulcer; adverse events; hospitalacquired pressure ulcer; patient safety; medical events The development of pressure ulcers (PUs) has been associated with the quality of health care. 1,2 Hence, higher rates of PU development (PUD) may signal overall poor care by the healthcare system. The National Quality Forum (NQF) created hospital Never Events in 2003 events that should never occur during hospitalization. 1 The NQF believes that development of Stage III or IV PUs are such events. In the 13 states that have incorporated Never Events, hospitals can be financially penalized for not reporting individuals who develop Stage III or IV PUs in a timely manner. The federal government has also identified PUD as a public heath concern. 2 Most recently, the Centers for Medicare and Medicaid Services (CMS) made a significant policy decision not to pay for hospital-acquired Stage III and IV PUs. 3 A major limitation of existing PU studies has been their small sample size (<200 participants). Thus, the ability to compare an individual hospital s incidence rate with national or state level data has been lacking. Clinicians and policy makers abilities to determine the effect of specific individual clinical characteristics on the risk of developing hospital-acquired PUs (HAPUs) and the effect of PUs on outcomes (e.g., hospital length of stay and mortality) has also been challenging. Without a good understanding of national and state incidence rates and an understanding of specific clinical characteristics, effective PU prevention in the Medicare population is difficult. There is no large database to help determine incidence of JAGS 60: , , Copyright the Authors Journal compilation 2012, The American Geriatrics Society /12/$15.00

2 1604 LYDER ET AL. SEPTEMBER 2012 VOL. 60, NO. 9 JAGS PUs among hospitalized Medicare beneficiaries as a basis for measuring improvement. Neither are there known published Medicare studies that have reported on HAPUs against which hospitals can benchmark at the national or state level. Given the increasing number of Medicare beneficiaries being admitted to hospitals and the concomitant potential for increases in PU incidence, a Medicare Patient Safety Monitoring System (MPSMS) study capitalized on abstracted data from a large sample of medical records of fee-for-service Medicare beneficiaries discharged in 2006/07 to address these gaps in knowledge. 4 The data for this study came from three national databases: the CMS National Claim History database, the CMS Claims History database, and the MPSMS. The purpose was to explore the overall incidence, prevalence, and clinical characteristics associated with Medicare beneficiaries who developed HAPUs and to determine rates in states and geographic regions. STUDY SAMPLE The MPSMS is a nationwide surveillance system designed to identify rates of specific adverse events within the hospitalized fee-for-service Medicare population. An adverse event is an unintended harm, injury, or loss that is more likely associated with an individual s interaction with the healthcare delivery system than with diseases the individual may have. The MPSMS determines the national rates for Medicare beneficiaries in the following adverse event categories: central venous catheter (CVC)-associated blood stream infections; CVC-associated mechanical adverse events; CVC-associated blood stream infection (BSI) adverse drug events; HAPU- and ventilator-associated pneumonia; hip and knee replacements; and postoperative rates of venous thrombolic event, cardiac events, and pneumonia. 4 The MPSMS PU study uses secondary analyses of the Hospital Payment Monitoring Program (HPMP) sample. 5 The HPMP medical record sample is an existing database, selected randomly each month from the Medicare National Claims History File by CMS from a pool of approximately 1 million fee-for-service Medicare beneficiary hospital discharges. For this study, the records of hospital discharges between January 1, 2006, and December 31, 2007, totaling 51,842 Medicare fee-for-service inpatient discharges across the 50 states, Washington, DC, Puerto Rico, and the U.S. Virgin Islands, were selected for use. Trained medical record abstractors collected documentation describing individuals with HAPUs that developed during their index hospitalizations. The medical record abstractors were trained on model charts. Interrater reliability (between principal investigator and medical abstractors) was established at 90% before the medical abstractors were allowed to abstract the medical records. Charts of individuals with PUs present on admission (prevalence) were reviewed to determine whether new ulcers (incidence) developed during the hospital stay. The National PU Advisory Panels Stage I (2001) and Stage II to IV (1989) definitions of PUs were used to distinguish a PU from another potential skin injury. 6,7 The comorbidities for PUs were defined as congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), cerebrovascular disease (CVD), diabetes mellitus, usage of corticosteroids, obesity, and smoking. These were selected because of their association with PUs in the literature. The PU diagnosis was determined based on physician and nurse documentation in the medical record during admission (prevalence) or at any time during hospitalization. Newly developed PUs (incidence) were also monitored during hospitalization. The abstractors determined whether an individual developed a HAPU based on documentation of a HAPU in the medical record or on the description of ulceration. The locations of PUs, newly acquired and those documented on admission, were also recorded. To further distinguish HAPUs from PUs already present on admission, new PUs found in the same body region as PUs present on admission were not counted as HAPUs. Any individual who developed at least one new PU during the hospitalization was included in the analyses. Participant demographic information (e.g., age, sex, race), International Classification of Diseases, Ninth Revision (ICD-9) diagnoses (707), and other characteristics (e.g., obesity, CHF, COPD as determined by ICD coding) were obtained from the Medicare Enrollment Database. The outcomes of interest were in-hospital mortality rates, readmission or mortality during the 30 days after discharge, and hospital length of stay. The CMS National Claim History database was the source of in-hospital mortality and readmission information. The Medicare Enrollment Database was the source of 30-day mortality information. STATISTICAL ANALYSIS Descriptive and bivariate analyses were conducted to identify participants baseline demographics and medical diagnoses and to compare the observed differences in characteristics and outcomes (mortality, readmission, and length of stay) of participants who developed HAPUs and those who did not. The chi-square test was used to compare dichotomous and categorical variables, and the t-test was used to compare continuous variables. The hierarchal generalized linear modeling (HGLM) approach 8 10 was applied to assess the association between participant characteristics and development of HAPUs by modeling the log-odds of HAPUs as a function of participant demographic and clinical variables. This approach was used to determine whether there was a relationship between the outcomes and development of HAPUs after adjustment for participant characteristics. Two modeling steps were constructed for each outcome. The first step was fitted to a model without adjusting for participant characteristics, and the second step was fitted to a model with adjustments for participant demographics and medical conditions. 11 To examine differences in HAPU rates across states and regions, all HGLMs were fitted with a random state-specific effect to account for within-state correlation of the observed adverse events and outcomes to distinguish between within-state variations from between-state variation. The CMS regions were used to cluster states. A 95% confidence interval (CI) was calculated for each estimate for the models. To take into account differences in

3 JAGS SEPTEMBER 2012 VOL. 60, NO. 9 HOSPITAL-ACQUIRED PRESSURE ULCERS 1605 Medicare fee-for-service volume between states, all HGLMs were weighted by a total number of discharges from each state. All statistical analyses were conducted using Stata version 8.0 (StataCorp., College Station, TX) and SAS version 8.12 (SAS Institute, Inc., Cary, NC). Hierarchical models were estimated using the GLIMMIX macro in SAS. RESULTS Participant Characteristics Fifty-one thousand eight hundred forty-two discharges were included in the final study sample for the combined years 2006 and 2007 (Table 1). The HAPU incidence rate was determined to be 4.5% (2,313/51,842), and PU prevalence on admission was 5.8% (2,999/51,842). Of the 2,999 individuals who entered the hospital with a PU, 16.7% (502/2,999) developed at least one new PU at a different location during their hospitalization. The majority of participants who developed at least one PU were nonwhite and aged 75 to 84. These participants had significantly higher rates of CHF, COPD, CVD, diabetes mellitus, and use of corticosteroids during hospitalization. Obesity was significantly associated with HAPUs (Table 1). The majority of HAPUs were located on the coccyx or sacrum (41%), followed by the hip and buttock region (23%) and the heels (23%). The stages of HAPUs could not be determined because of the wide variability in documentation of description and staging by clinicians. Participant characteristic such as age, diagnosis (cancer, CHF, COPD, CVD, diabetes mellitus), and presence of obesity were all significantly associated with HAPUs (P <.001; Table 2). Overall, the nationwide HAPU incidence rate was 4.5% (95% CI = %). Variance across the nation was statistically significant (Figure 1). The between-state Table 2. Hierarchical Generalized Linear Model Association Between Participant Characteristics and Pressure Ulcer Development Characteristic Odds Ratio (95% Confidence Interval) P- Value Age (reference 85) < ( ) < ( ) < ( ) <.001 Female 0.99 ( ).37 White 1.01 ( ).56 Cancer 1.07 ( ) <.001 Congestive heart failure 1.11 ( ) <.001 Chronic obstructive pulmonary 1.05 ( ) <.001 disease Cerebrovascular disease 1.11 ( ) <.001 Diabetes mellitus 1.07 ( ) <.001 Corticosteroids 1.03 ( ).04 Obese 1.04 ( ).002 Smoking 1.00 ( ).80 variance was 3.2% (standard error 1.2%), the weighted rates drawn from HGLM ranged from 3.1% (95% CI = %) to 5.9% (95% CI = %). The odds of developing PUs if treated in a state 1 standard deviation (SD) above the national average relative to the odds of developing PUs if treated at a state 1 SD below the national average were Higher incidence rates were noted in the Northeast and Missouri. The five states with the lowest HAPU rates were Wisconsin (3.1%), Alabama (3.3%), Tennessee (3.7%), Puerto Rico (3.7%), and North Carolina (3.8%), and the five states with the highest HAPU rates were New York (5.2%), Missouri (5.3%), New Jersey (5.3%), Massachusetts (5.5%) and Pennsylvania (5.9%). Rates in Wisconsin and Alabama were statistically significantly lower than the national average. Table 1. Participant Characteristics Characteristic Total (N = 51,842) Participants with Pressure Ulcers (n = 2,313) Participants without Pressure Ulcers (n = 49,529) P-Value Age, mean ± standard 73.3 ± ± ± 13.0 <.001 deviation Age, n (%) <65 8,878 (17.1) 236 (10.2) 8,642 (17.4) < ,824 (30.5) 494 (21.4) 15,330 (31.0) ,621 (34.0) 879 (38.0) 16,742 (33.8) >84 9,519 (18.4) 704 (30.4) 8,815 (17.8) Nonwhite, n (%) 43,639 (84.2) 1,980 (85.6) 41,659 (84.1).05 Female, n (%) 29,088 (56.1) 1,307 (56.5) 27,781 (56.1).69 Congestive heart 15,071 (29.1) 1,013 (43.8) 14,058 (28.4) <.001 failure, n (%) Chronic obstructive 14,716 (28.4) 810 (35.0) 13,906 (28.1) <.001 pulmonary disease, n (%) Cerebrovascular 11,862 (22.9) 785 (33.9) 11,077 (22.4) <.001 disease, n (%) Diabetes mellitus, n (%) 17,512 (33.8) 971 (42.0) 16,541 (33.4) <.001 Corticosteroids, n (%) 4,154 (8.0) 223 (9.6) 3,931 (7.9).003 Obese, n (%) 6,822 (13.2) 343 (14.8) 6,479 (13.1).02 Smoking, n (%) 8,324 (16.1) 306 (13.2) 8,018 (16.2) <.001

4 1606 LYDER ET AL. SEPTEMBER 2012 VOL. 60, NO. 9 JAGS Figure 1. Pressure ulcer incidence rates according to Centers for Medicare and Medicaid Services Regional Map. Mortality, Readmission, and Length of Stay The mortality data revealed that the development of HAPUs was significantly associated with higher in-hospital mortality (11.2%) and mortality within 30 days after discharge (15.3%). HGLMs were fitted to further understand the association between the development of new HAPUs and hospital outcomes (Table 3), mortality and hospital length of stay (Table 4). Participants with HAPUs were significantly more likely to be readmitted within 30 days after discharge (odds ratio (OR) = 1.33, 95% CI = ), and were more likely to have died in the hospital. The riskadjusted ORs were 2.81 (95% CI = ) for in-hospital mortality and 1.69 (95% CI = ) for mortality within 30 days after discharge. Participants who developed HAPUs had significantly longer hospital lengths of stay (11.6 ± 10.1 days) than those without (4.9 ± 5.2 days). DISCUSSION The data from this study revealed that HAPUs remain a significant problem for hospitalized individuals. Although a 4.5% HAPU incidence rate and 5.8% prevalence rate on admission were found, no other large Medicare studies were located to place these findings into context of the current literature. The between-state incidence rate variance Table 4. Hierarchical Generalized Linear Models Association of Participant Outcomes with Pressure Ulcer (PU) Development Outcome Estimate a (95% Confidence Interval) P- Value Mortality 30 days from discharge 1.69 ( ) <.001 In-hospital 2.81 ( ) <.001 Readmission within 30 days 1.33 ( ) <.001 after discharge Length of stay With PUs 2.11 ( ) <.001 Without PUs 1.25 ( ) a For mortality and readmission, the estimate is odds ratio. For length of stay, the estimate is mean length of stay at the log scale. All estimates were adjusted for participant characteristics (age, sex, congestive heart failure, chronic obstructive pulmonary disease, cerebrovascular disease, diabetes mellitus, obesity, corticosteroids, smoking status, coronary artery disease, and renal failure). was 3.2% (P <.001). Thus, to benchmark appropriately, it is imperative for hospitals to be cognizant not only of the national incidence rate, but also of their own state s rates. Several states mandate that hospitals track and Table 3. Association Between Hospital Outcomes and Pressure Ulcer (PU) Development Outcome Total With PUs Without PUs P-Value Mortality, n (%) Within 30-days after discharge 2,551 (4.0) 353 (15.3) 2,198 (4.4) <.001 In hospital 1,892 (3.6) 258 (11.1) 1,634 (3.3) <.001 Readmission within 9,235 (17.8) 523 (22.6) 8,712 (17.6) < days after discharge, n (%) Length of stay, days, mean ± standard deviation 5.2 ± ± ± 5.3 <.001

5 JAGS SEPTEMBER 2012 VOL. 60, NO. 9 HOSPITAL-ACQUIRED PRESSURE ULCERS 1607 report their PU rates to their state departments of health, but it is often difficult for hospital staff to obtain access to relevant benchmarks for comparison between like minded hospitals within the state. Thus, this study provides a glimpse of PU incidence and presence at the state and national level for Medicare beneficiaries. Most prevalence studies use a 1-day period to determine community-acquired PU rates for the hospital, with some studies reporting hospital PU prevalence rates of as high as 15% The large difference between the 15% reported in the research literature and the 5.8% found in the current study may be because, when a 1-day prevalence is used, individuals with longer hospital lengths of stay are more likely to be counted. Another explanation for this difference is that the majority of prevalence studies reported are completed during hospitalization, versus the current study, which counted on PUs on admission and HAPUs. The findings from the MPSMS have also demonstrated that individuals with HAPUs have much longer hospital lengths of stay. Thus, a 1-day prevalence study (often used by hospitals to determine prevalence rates) may not be an accurate reflection of individuals who developed HAPUs during their stay. The findings of the current study support current literature that suggests that specific chronic diseases such as CHF, COPD, CVD, diabetes mellitus, obesity, and use of corticosteroids may increase vulnerability to the development of HAPUs. 15,16 Thus, individuals entering the hospital with a constellation of these conditions should be identified as being at higher risk for developing HAPUs. The majority of participants developed HAPUs over the coccyx and sacrum, hips and buttocks, and heels. These findings support the analyses by the National Pressure Ulcer Advisory Panel (NPUAP). 14 Obesity was associated with HAPUs. Chronic impairment of systematic perfusion that occurs in individuals who are obese frequently results in chronic skin and wound problems. 17 Blood supply to fatty tissue may not be adequate to provide appropriate oxygen and nutrition. This could be further compounded if the individual s dietary input does not include essential vitamins and nutrients. HAPUs also have been shown to be an important risk factor associated with mortality. The MPSMS PU findings strengthen the body of research that suggests that individuals with HAPUs have higher mortality in the hospital and within 30 days of discharge. Therefore, hospitals should identify individuals at high risk for HAPUs and implement preventative interventions on admissions accordingly. It could be argued that, because of the good PU prevention programs being implemented in hospitals throughout the United States, rates of 4.5% might be acceptable. 18,19 These findings also suggest that HAPUs may develop independent of good care being provided. 20,21 Thus, some HAPUs may be unavoidable, as suggested by the NPUAP 22 and other national associations. 23,24 There were several limitations inherent in the MPSMS PU study. Retrospective abstraction of medical records is a limitation in data collection because it is possible that HA- PUs could have been present and simply not recorded or adequately described. In several cases, the clinician did not document PUs, yet based on clinical characteristics and the location and description of the ulcer, the research team decided to count these as HAPUs. There is a slight possibility (highly unlikely) that these were not HAPUs. Care was taken to exclude all other chronic ulcers based on medical diagnoses in the medical records and using ICD-9 coding (e.g., diabetic ulcers, venous stasis ulcers, arterial ulcers). To distinguish individuals with HAPUs from those with PUs already present on admission, no PUs, new or old, found in the same body region as a PU already present on admission were counted as HAPUs. This approach may have led to undercounting the number of individuals who developed new HAPUs during the hospital stay. The inability to capture the staging of HAPUs was another limitation. The variability of documented staging of HAPUs in the medical record made this variable unreliable. Staging of PUs using the NPUAP staging system is not required. Given the new CMS Hospital-Acquired Conditions, under which hospitals will no longer be reimbursed for Stage 3 and 4 PUs unless they were identified upon admission, accuracy in staging of these ulcers may improve. That is, clinicians may need to be reeducated on staging of PUs using the 2007 NPUAP staging system because correct staging of PUs is necessary to make appropriate choices in their management of the PUs. Although several undesirable outcomes were associated with the development of HAPUs, no assertion is made that there was a causal relationship between the development of HAPUs and these outcomes. Nonetheless, describing these associations is important to help identify high-risk individuals. For example, even though it cannot be stated that HAPUs directly contributed to the longer hospital length of stay, these findings suggest that an individual with a prolonged hospital length of stay is at greater risk of developing HAPUs and that both add financial burden to the hospital. Hospitals should use the MSPMS PU data as one point of comparison, but hospitals may have different rates because of differences in patient acuity, so the data from the current study may or may not indicate that institutional improvement in PU prevention is warranted. The data support that multiple chronic conditions or any combination of these conditions may contribute to the development of HAPUs. Perhaps these conditions lead to readmission and HAPUs are merely a surrogate for identifying very sick people rather than being a causative factor for readmission. Thus, data on the incidence and prevalence of PUs must not simply be collected; understanding of the underlying diseases that may lead to HAPUs must be gained. Regardless of the limitations, the MPSMS PU study has major strengths. To the best of the knowledge of the authors, this is the first study to use data abstracted directly from medical records to assess HAPUs in hospitalized Medicare beneficiaries at the national and state levels. With the use of an evidence-based algorithm developed by nationally recognized experts, the MPSMS is the largest database of its kind. The PU findings have important clinical and public health implications. MPSMS PU findings clearly guide clinicians to anatomical sites where PUs are most likely to develop and identify critical characteristics and conditions that increase the risk of HAPUs in Medicare beneficiaries. The findings suggest that these individuals are more likely to die or be readmitted within 30 days. It was surprising that the Northeast region had higher rates of HAPUs. The aggressive prevention and recognition

6 1608 LYDER ET AL. SEPTEMBER 2012 VOL. 60, NO. 9 JAGS programs occurring in the Northeast region may lead to higher rates being reported than in other regions, which may explain this in part Regardless, with these data, it is now possible for hospitals to benchmark their Medicare beneficiaries HAPU rates at the national and state levels. ACKNOWLEDGMENTS The analyses upon which this publication is based were performed under Contract CToo2C, entitled Utilization Quality Control: Quality Improvement Organization for the State of Connecticut, sponsored by CMS, Department of Health and Human Services. The authors assume full responsibility for the accuracy and completeness of the ideas presented. This article is a direct result of the Health Care Quality Improvement Program initiated by CMS, which has encouraged identification of quality improvement projects derived from analyses of patterns of care and therefore required no special funding on the part of the contractor. Ideas and contributions to the authors concerning experience and engaging with issues presented are welcomed. The authors would like to thank the MPSMS team at Qualidigm for its support and contributions. We specifically thank Nancy Verzier, RN, MSN, CPHQ, and Michael Pineau, RN, MS, for their excellent management of the project and Nancy Morse for manuscript preparation. Conflict of Interest: There are no financial, personal, potential conflicts of interest in the conduct of the study or in the manuscript development. Dr. Lyder had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of data analysis. M. Metersky s employer is remunerated for his quality insurance and safety work with Qualidigm. Author Contributions: Study concept and design: Courtney Lyder, Mark Metersky, Nancy Verzier, David Hunt. Acquisition of subjects and/or data: Courtney Lyder, Maureen Curry, Nancy Verzier. Analysis and interpretation of data: Courtney Lyder, Yun Wang, Mark Metersky, Maureen Curry. Preparation of manuscript: Courtney Lyder, Yun Wang, Mark Metersky, Maureen Curry, Rebecca Kliman, Nancy Verzier, David Hunt. Sponsor s Role: The content of the publication does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. government. REFERENCES 1. Pressure Ulcer Stages Revised by NPUAP [on-line]. Available at Accessed May 31, National Quality Forum. Serious Reportable Events in Healthcare: A Consensus Report. Washington, DC: National Quality Forum, Medicare Program; Changes to the Hospital Inpatient Prospective Payment Systems and Fiscal Year 2008 Rates [on-line]. Available at hhs.gov/acuteinpatientpps/downloads/cms-1533-fc.pdf Accessed October 15, Healthy People [on-line]. Available at Accessed October 15, Hospital Payment Monitoring Program: Monitoring and Reducing Missouri s Payment Error Rate [on-line]. Available at sites/default/files/resources/hpmp/hpmp%20info%20sheet.pdf Accessed September 20, NPUAP Pressure Ulcer Stages [on-line]. Available at npuap.org/positn6.htm Accessed September 20, Ankrom MA, Bennett RG, Sprigle S et al. Pressure-related deep tissue injury under intact skin and the current pressure ulcer staging systems. Adv Skin Wound Care 2005;18: Austin PC, Tu JV, Alter DA. Comparing hierarchical modeling with traditional logistic regression analysis among patients hospitalized with acute myocardial infarction: Should we be analyzing cardiovascular outcomes differently?. Am Heart J 2003;145: DeLong E. Hierarchical modeling: Its time has come. Am Heart J 2003;145: Christiansen CL, Morris CN. Improving the statistical approach to health care provide profiling. Ann Intern Med 1997;127: Coyle YM, Battles JB. Using antecedents of medical care to develop valid quality of care measures. Int J Qual Health Care 1999;2: Robinson C, Gloeckner M, Bush S et al. Determining the efficacy of a pressure ulcer prevention program by collecting prevalence and incidence data: A unit-based effort. Ostomy Wound Manage 2003;49: Whittington K, Patrick M, Roberts JL. A national study of pressure ulcer prevalence and incidence in acute care hospitals. J Wound Ostomy Continence Nurs 2000;27: Cuddigan J, Ayello EA, Sussman C. Pressure Ulcers in America: Prevalence, Incidence, and Implications for the Future. Reston, VA: National Pressure Ulcer Advisory Panel, Lyder CH, Preston J, Grady J et al. Quality of care for hospitalized medicare patients at risk for pressure ulcers. Arch Intern Med 2001;161: Allman RM, Goode PS, Patrick MM et al. Pressure ulcer risk factors among hospitalized patients with activity limitations. JAMA 1995;273: Krasner DL, Kennedy-Evans KL et al. Bariatric wound care: Common problems and management strategies. Bariatric Times 2006;3: Shahin EM, Dassen T, Halfens RG. Incidence, prevention and treatment of pressure ulcers in intensive care patients: A longitudinal study. Int J Nurs Study 2009;46: Gunningberg L, Lindholm C, Carlsson M et al. Reduced incidence of pressure ulcers in patients with hip fractures: A 2-year follow-up of quality indicators. Int J Qual Health Care 2001;13: Langemo D, Brown G. Skin fails too: Acute, chronic and end-stage skin failure. Adv Skin Wound Care 2006;9: Black JM, Edsberg LE, Baharestani MM et al. Pressure ulcers: Avoidable or unavoidable? results of the national pressure ulcer advisory panel consensus conference. Ostomy Wound Manage 2011;57: Pressure Ulcers: Avoidable or Unavoidable? Results of the National Pressure Ulcer Advisory Panel Consensus Conference [on-line]. Available at Accessed February 27, Avoidable versus Unavoidable Pressure Ulcers [on-line]. Available at Accessed February 27, European Pressure Ulcer Advisory Panel [on-line]. Available at epuap.org/ Accessed February 27, Partnering for Prevention A Pressure Ulcer Prevention Collaborative Project [on-line]. Available at Accessed September 24, Massachusetts Pressure Ulcer Collaborative [on-line]. Available at Accessed September 24, Preventing Pressure Ulcers in Hospitals [on-line]. Available at ahrq.gov/research/ltc/pressureulcertoolkit/putoolkit.pdf Accessed September 24, 2011.

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