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Living in a medically underserved county is an independent risk factor for major limb amputation

Open ArchivePublished:November 18, 2013DOI:https://doi.org/10.1016/j.jvs.2013.09.037

      Objective

      Despite an increase in the incidence of hospital admissions for comorbid conditions, such as diabetes, the incidence of major limb amputation in North Carolina has decreased. The decline in amputation rate has not been uniformly realized across the state. The objective of this study was to determine the association between major vascular limb amputation and living in an underserved county in North Carolina.

      Methods

      We analyzed discharges aged 18 to 100 years old with a peripheral arterial disease (PAD)-related admission from the North Carolina Inpatient Discharge Database from 2006 to 2009. Medically underserved counties are defined by the United States Health Resources and Services Administration as having too few primary care providers, high infant mortality, high poverty, or high elderly population. The association between major amputation prevalence and medically underserved counties was calculated using a binomial regression model adjusted for sex, age, diabetes, end-stage renal disease, PAD, and critical limb ischemia. Each confounder was assessed using backward elimination modeling.

      Results

      Among the 222,920 discharges with a PAD-related hospital admission from 2006 to 2009, 8601 (3.9%) were from medically underserved counties. There were 7328 major amputations. The adjusted prevalence odds ratio of the association between underserved counties and major vascular limb amputation is 1.29 (95% confidence interval, 1.16-1.44). None of the confounders significantly affected the association between underserved counties and number of amputations.

      Conclusions

      Living in an underserved county in North Carolina is associated with a 29% increase in the odds of undergoing major limb amputation. Gender, age, and comorbidities, including diabetes, end-stage renal disease, and PAD, do not significantly affect the relationship.
      Approximately 10 million Americans (4% of adults) have peripheral arterial disease (PAD).

      Eraso LH, Fukaya E, Mohler ER 3rd, Xie D, Sha D, Berger JS. Peripheral arterial disease, prevalence and cumulative risk factor profile analysis [published online ahead of print June 27, 2011]. Eur J Prev Cardiol doi: 10.1177/2047487312452968.

      • Murabito J.M.
      • Evans J.C.
      • Nieto K.
      • Larson M.G.
      • Levy D.
      • Wilson P.W.
      Prevalence and clinical correlates of peripheral arterial disease in the Framingham offspring study.
      • Selvin E.
      • Erlinger T.P.
      Prevalence of and risk factors for peripheral arterial disease in the united states: results from the National Health and Nutrition Examination Survey, 1999-2000.
      The TransAtlantic Inter-Society consensus statement on PAD identifies smoking and diabetes as the two largest risk factors contributing to PAD.
      • Norgren L.
      • Hiatt W.R.
      • Dormandy J.A.
      • Nehler M.R.
      • Harris K.A.
      • Fowkes F.G.
      • et al.
      Inter-society consensus for the management of peripheral arterial disease (TASC II).
      Critical limb ischemia (CLI), which occurs in ∼3% of PAD patients, is a chronic process that results from poor limb perfusion that threatens limb viability. CLI is measured as a toe pressure of <40 mm Hg with lower extremity rest pain, ulceration, or gangrene.
      • Norgren L.
      • Hiatt W.R.
      • Dormandy J.A.
      • Nehler M.R.
      • Harris K.A.
      • Fowkes F.G.
      • et al.
      Inter-society consensus for the management of peripheral arterial disease (TASC II).
      • Marston W.A.
      • Davies S.W.
      • Armstrong B.
      • Farber M.A.
      • Mendes R.C.
      • Fulton J.J.
      • et al.
      Natural history of limbs with arterial insufficiency and chronic ulceration treated without revascularization.
      Treatment protocols for CLI patients include comprehensive wound care and revascularization to avoid limb amputation. Yet, within 1 year of diagnosis, 30% require major amputation and 25% die.
      • Norgren L.
      • Hiatt W.R.
      • Dormandy J.A.
      • Nehler M.R.
      • Harris K.A.
      • Fowkes F.G.
      • et al.
      Inter-society consensus for the management of peripheral arterial disease (TASC II).
      Factors associated with primary amputation include nonwhite ethnicity, diabetes, end-stage renal disease (ESRD), major tissue loss, and nonambulatory status.
      • Hirsch A.T.
      • Haskal Z.J.
      • Hertzer N.R.
      • Bakal C.W.
      • Creager M.A.
      • Halperin J.L.
      • et al.
      ACC/AHA 2005 practice guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic): a collaborative report from the American Association for Vascular Surgery/Society for Vascular Surgery, Society for Cardiovascular Angiography and Interventions, Society for Vascular Medicine and Biology, Society of Interventional Radiology, and the ACC/AHA task force on practice guidelines (writing committee to develop guidelines for the management of patients with peripheral arterial disease): Endorsed by the American Association of Cardiovascular and Pulmonary Rehabilitation; National Heart, Lung, and Blood Institute; Society for Vascular Nursing; TransAtlantic Inter-Society Consensus; and Vascular Disease Foundation.
      From 2006 through 2009, there were 186,997 hospital discharges with a diagnosis of diabetes and 20,633 with a diagnosis of PAD in North Carolina. PAD is likely to become more prevalent as the population ages and more patients live with comorbid conditions, and there is concern that a higher incidence of CLI will result in an increase in major limb amputations.
      • Golomb B.A.
      • Dang T.T.
      • Criqui M.H.
      Peripheral arterial disease: morbidity and mortality implications.
      However, a previous population-based study showed that from 1998 to 2003, the national per-capita rate of amputations progressively decreased: 13.2% overall reduction and 21.2% reduction for major amputations (P < .0001).
      • Goodney P.P.
      • Beck A.W.
      • Nagle J.
      • Welch H.G.
      • Zwolak R.M.
      National trends in lower extremity bypass surgery, endovascular interventions, and major amputations.
      To date, there have been no studies demonstrating the cause of the decline in amputation rate.
      The purpose of this study was to determine the incidence of major limb amputations in North Carolina from 2006 through 2009 and to identify demographic factors, including the level of medical access, that may contribute to the changing incidence. We also examined if these demographic factors were independently related to amputation rate when accounting for comorbidities including diabetes, ESRD, PAD, and lower extremity ulcers.

      Methods

      A primary source of information for this study was the North Carolina Inpatient Discharge Database, a statewide database that records unique discharge data, including each patient's age, sex, race, insurance provider, county of residence, and up to 24 diagnoses and 24 procedures or operations. This is a database of 100% of discharges from all acute inpatient hospitals in North Carolina. Geographic and demographic information of each discharge from the North Carolina Inpatient Discharge Database is based on each discharged patient's county of residence, not the location of the hospital. The unit of analysis used was each discharge. We calculated the rate of hospital discharges with diabetes, ESRD, PAD, lower extremity ulcer, or major amputation from 2006 to 2009.
      We defined major amputation by International Classification of Diseases (ICD-9) procedure codes, including amputations above the ankle and excluding amputations with codes related to trauma or cancer. Toe and transmetatarsal amputations were not included. Comorbid conditions of interest were also defined using ICD-9 codes (Table I). Diabetic patients and patients with ESRD were included because a significant number of them have PAD and many others have neuropathic diabetic ulcers that put them at risk for amputation. The ICD-9 code for lower extremity ulcer includes ischemic ulcers and neuropathic ulcers but excludes pressure ulcers and venous ulcers.
      Table IInternational classification of diseases, 9th revision codes
      CodeDescription
      84.1Amputation of the lower limb
      84.15Below-knee amputation
      84.17Above-knee amputation
      249.xx, 250.xxDiabetes mellitus
      585.6ESRD
      443.89, 443.9PVD
      440.20, 440.21, 440.22, 440.29Atherosclerosis of the extremity
      440.4Arterial occlusion of extremity
      440.23, 440.24Atherosclerosis with tissue loss/gangrene
      440.3Atherosclerosis/occlusion of bypass graft in extremity
      707.10-19Lower extremity ulcer (except pressure ulcer)
      890.xx, 891.xx, 892.xx, 893.xx, 894.xxOpen wound of lower extremity
      785.4Gangrene
      ESRD, End-stage renal disease; PVD, peripheral vascular disease.
      The North Carolina Health Professions Data System is a database that maintains the licensure information and professional characteristics of many different health care workers. We used this database to define the distribution of cardiovascular specialists, which were defined as vascular surgeons, general surgeons performing vascular operations, interventional radiologists, and cardiologists, and to determine physician density per county. These specialty designations are self-reported, and do not necessarily reflect practice patterns or a focus on the treatment of PAD. The geographic and demographic information from each health professional is based on the county in which they provide care. We used the U.S. Census Bureau Core Based Statistical Areas to determine the demographic characteristics of each county. Like the U.S. Census Bureau, we used the definition of totally underserved counties as set by the U.S. Health Resources and Services Administration, which is based on a weighted score calculated for counties with any one of the following: too few primary care providers, high infant mortality, high poverty, or high elderly population. The weighted score is used to classify counties as best served, partially underserved, or totally underserved. The distribution of cardiovascular specialists is not incorporated into the weighting system; however, we used this widely accepted federal classification to define level of access as an independent risk factor because this is the same definition that potential state and federal initiatives would use to improve health care.
      To determine the association of being from a totally underserved community and the prevalence odds ratio (OR) of major limb amputation, we analyzed data from 222,920 discharges from the North Carolina Discharge database aged 18 to 100 years for PAD-related admissions (as determined by ICD-9 codes in the primary, secondary, or tertiary position). The association between underserved and major limb amputation was calculated using binomial regression to estimate crude and adjusted prevalence ORs. Backward elimination modeling was used to assess confounders of gender, diabetes, CLI (with or without tissue loss), PAD, ESRD, and a five-category age variable (<50, 50-59, 60-69, 70-79, >80 years).

      Results

      From 2006 through 2009, 7328 major amputations occurred in North Carolina. During the study period, the annual number of major amputations decreased 19%, from 2054 to 1668. This decrease was confirmed by a continuously negative trend in the number of yearly amputations during the last decade (Fig 1). Patients undergoing amputation were a median age of 67 years, and most were men or had a diagnosis of diabetes or CLI (Table II). The number of patients hospitalized in North Carolina with relevant comorbid conditions increased during the same time period: diabetes (838 to 906/1000 discharges), ESRD (67 to 69/1000 discharges), and peripheral vascular disease (93 to 104/1000 discharges).
      Figure thumbnail gr1
      Fig 1Downward trend in number of amputations in North Carolina from 2000 to 2009.
      Table IIPopulation characteristics of major amputations in North Carolina, 2006 to 2009
      CharacteristicMajor amputation (n = 7328)
      Median age (interquartile range), years67 (57-78)
      Male, %59
      Diabetes, %60
      ESRD, %18
      PAD, %17
      CLI, %65
      Underserved county residence, %5
      CLI, Critical limb ischemia; ESRD, end-stage renal disease; PAD, peripheral arterial disease.
      As expected, age, PAD, and ESRD were associated with the incidence of amputation (Table III). Patients with CLI had the highest OR for amputation (11.90; 95% confidence interval [CI], 11.20-12.74), followed by ESRD (OR, 3.27; 95% CI, 3.01-3.54) and PAD (OR, 2.07; 95% CI, 1.90-2.25). The study also found men were slightly more likely to undergo amputation (OR, 1.67; 95% CI, 1.52-1.71).
      Table IIIAssociation of comorbidities to major amputation among those with health care access
      ComorbidityOR (95% CI)
      Male gender1.62 (1.52-1.71)
      PAD2.07 (1.90-2.25)
      ESRD3.27 (3.01-3.54)
      CLI11.90 (11.20-12.74)
      CI, Confidence interval; CLI, critical limb ischemia; ESRD, end-stage renal disease; OR, odds ratio; PAD, peripheral arterial disease.
      An unexpected finding was the relationship between living in a totally underserved county and major limb amputation. The prevalence OR of this association was 1.29 (95% CI, 1.16-1.44) and was independent of the effect of the other studied risk factors (Table IV). These results suggest that being from an underserved community is associated with a 30% increase in the odds of undergoing limb amputation among those aged 18 to 100 years admitted to the hospital with a PAD-related ICD-9 code in the primary, secondary, or tertiary position.
      Table IVJoint distribution of major exposure and outcome
      VariableMajor amputation +, No.Major amputation −, No.OR
      Underserved +3578244
      Underserved –697120,7348
      1.3
      OR, Odds ratio.
      There are 11 totally underserved counties, 27 partially underserved counties, and 62 counties with adequate medical access in North Carolina (Fig 2). Of the state's population, ∼37% reside in an underserved county, and 2.8% live in a totally underserved county. Among the 222,920 hospital discharges with a PAD-related condition from 2006 to 2009, 8601 discharges (3.8%) were from totally underserved counties. Totally underserved counties had a disproportionately high number of hospital discharges.
      Figure thumbnail gr2
      Fig 2Map showing the counties in North Carolina with persistent health professionals shortage, 2005-2009.
      The North Carolina Health Professions Data System reported these counties also had significantly fewer practicing registered nurses, primary care physicians, and cardiovascular specialists. No vascular surgeons were practicing in the totally underserved counties (Table V). Combining the partially and totally underserved counties into one category did little to improve the overall difference in access to health care providers because the combined category continued to demonstrate significant deficits in the number of registered nurses, primary care physicians, or vascular surgeons compared with counties with adequate medical access. However, there was no statistical difference in the number of cardiovascular specialists in counties with access (0.92/10,000 persons) vs combined partially and totally underserved counties (0.90/10,000 persons; P = .77). This is likely due to the more uniform distribution of cardiologists, which was the largest group included in the cardiovascular specialist category.
      Table VComparison of the characteristics of North Carolina counties with and without health care access in 2009
      CharacteristicCounties with accessTotally underserved countiesP value
      (n = 62)(n = 11)
      Population size, No. %5,892,243 (62.8)265,740 (2.8)
      Mean annual income, $41,68740,091.15
      Per 10,000 persons
       Registered nurses105.0843.45<.0001
       Primary care physicians9.763.61<.0001
       Cardiovascular specialists0.920.17<.0001
       Vascular surgeons0.0870.0014

      Discussion

      More than a decade ago, the Institute of Medicine (IOM) drew attention to health disparities in the United States when it published Crossing the Quality Chasm.
      • Richardson W.C.
      • Berwick D.M.
      • Bisgard J.C.
      • Bristow G.R.
      • Buck C.R.
      • Cassel C.K.
      • et al.
      In this report, the IOM stated that our health care system is ill prepared to deliver adequate care to our population as it grows and ages. In 2001, heart disease, diabetes, and asthma were the leading causes of disability and death. The IOM described voids in coverage in different population types, including patients living in rural America.
      These findings have been further illustrated by other studies.
      • Joynt K.E.
      • Harris Y.
      • Orav E.J.
      • Jha A.K.
      Quality of care and patient outcomes in critical access rural hospitals.
      • Joynt K.E.
      • Orav E.J.
      • Jha A.K.
      Mortality rates for medicare beneficiaries admitted to critical access and non-critical access hospitals, 2002-2010.

      North Carolina Rural Health Research and Policy Analysis Center. North Carolina rural health snapshot; 2010. Available at: http://www.shepscenter.unc.edu/research_programs/rural_program/pubs/other/RuralHealthSnapshot2010.pdf. Accessed June 28, 2013.

      During the last decade, Medicare beneficiaries who have been admitted to critical access hospitals in rural areas of the United States have had more complications and higher mortality rates.
      • Joynt K.E.
      • Harris Y.
      • Orav E.J.
      • Jha A.K.
      Quality of care and patient outcomes in critical access rural hospitals.
      • Joynt K.E.
      • Orav E.J.
      • Jha A.K.
      Mortality rates for medicare beneficiaries admitted to critical access and non-critical access hospitals, 2002-2010.
      Specifically in North Carolina, patients in rural counties had significantly lower access to health care providers and higher age-adjusted mortality rates secondary to diabetes, heart disease, and overall.

      North Carolina Rural Health Research and Policy Analysis Center. North Carolina rural health snapshot; 2010. Available at: http://www.shepscenter.unc.edu/research_programs/rural_program/pubs/other/RuralHealthSnapshot2010.pdf. Accessed June 28, 2013.

      Consistent with other studies, we found increasing numbers of hospitalizations for chronic conditions such as diabetes and also that age and cardiovascular risk factors, including PAD and ESRD, are risk factors for major amputation. Interestingly, our results show that the number of major limb amputations in North Carolina significantly declined during the last decade despite increases in hospitalizations for comorbid conditions. With increasing numbers of hospitalizations for chronic conditions, it is clear that continued efforts in patient education, disease prevention, and outpatient disease management are important factors in health care delivery overall.
      • Leibson C.L.
      • Ransom J.E.
      • Olson W.
      • Zimmerman B.R.
      • O’fallon W.M.
      • Palumbo P.J.
      Peripheral arterial disease, diabetes, and mortality.
      • Wright D.B.
      • Ricketts T.C.
      The road to efficiency? Re-examining the impact of the primary care physician workforce on health care utilization rates.
      Specifically, outreach to primary care providers to increase awareness of PAD evaluation and management is vital, because physician awareness of PAD has previously been shown to be relatively low and that PAD is undertreated compared with coronary artery disease.
      • Hirsch A.T.
      • Criqui M.H.
      • Treat-Jacobson D.
      • Regensteiner J.G.
      • Creager M.A.
      • Olin J.W.
      • et al.
      Peripheral arterial disease detection, awareness, and treatment in primary care.
      After controlling for significant medical risk factors, we demonstrated that living in a totally underserved county in North Carolina was independently associated with a 30% increase in the odds of undergoing major limb amputation. In North Carolina, these counties have significantly fewer primary care providers, and patients must travel to other counties to access a vascular surgeon. Reduced access to primary care clinicians may mean that patients living in those counties have more difficulty managing their chronic health conditions or undergoing timely interventions. Of interest, we did not find a statistically significant difference in the number of cardiovascular specialists per capita in counties across the state. The data set available to us does not allow us to determine which cardiologists or general surgeons practicing vascular surgery are actively involved in the treatment of peripheral vascular disease, limiting our ability to determine the association between physicians treating PAD and amputation. However, it is important to note that the presence of a cardiovascular specialist does not protect against limb amputation. Reaching out to cardiologists, specifically, may also be an essential step to increasing timely PAD diagnosis and management because they are the most widely and evenly distributed cardiovascular-specialized physician group in the state.
      Although it is unclear whether improved access to vascular surgeons directly relates to a lower incidence of amputation, patients with CLI who have access to vascular surgeons may be more likely to receive aggressive medical optimization, wound care, and intervention (whether open or endovascular), therefore reducing their risk of amputation. Further study is required to substantiate this theory. Determining whether access to vascular surgeons helps slow the progression of asymptomatic PAD to CLI requiring amputation would also be useful. If so, specific screening criteria or treatment modalities could be created to assist with timely referrals from underserved areas.
      This study is limited in that it is based on a large, population-based database that limits the ability to control for confounders when compared with prospective studies. Owing to the data available in the data set, we could not reliably evaluate other factors such as race, smoking status, or type of insurance coverage. The adequacy of medical control of diseases such as diabetes also could not be assessed; however, with increasing numbers of discharges for chronic conditions, it is unlikely that medical control improved during the study period. In addition, our statistical model controlled for diabetes and other comorbidities and still found that there was an association between county of residence and amputation rate.
      Because the unit of measure was hospital discharges rather than unique patient identifiers, multiple hospitalizations for the same comorbidity in the same patient could not be identified. If we were able to use individual patients as the unit of measure, we would be able to account for these repeat hospitalizations, and the denominator in our rate calculations would likely be decreased. Therefore, we may be under-reporting the rates of major limb amputation and the level of disparity across the state.
      We did not include digit or forefoot amputations in the analysis because these are limb-preserving operations, and the focus of this study was on factors affecting limb loss. However, with the recent emphasis on limb preservation, increasing numbers of patients may be undergoing these procedures. It would be interesting to determine whether the decrease in major limb amputations correlates with an increase in forefoot amputations or whether there is also disparity in limb salvage procedures.

      Conclusions

      Living in an underserved county in North Carolina is associated with a 29% increase in the odds of undergoing major limb amputation. Gender, age, diabetes, ESRD, and PAD do not significantly affect the relationship. Underserved counties in North Carolina have significantly fewer practicing primary care physicians and vascular surgeons. Establishing a direct relationship between reduced access to medical care and the amputation rate will require further specific research with information not typically collected by hospital discharge databases.

      Author contributions

      Conception and design: KM, WM
      Analysis and interpretation: KM, CK
      Data collection: Not applicable
      Writing the article: KM, CK, WM
      Critical revision of the article: KM, WM
      Final approval of the article: KM, CK, WM
      Statistical analysis: KM, CK
      Obtained funding: WM
      Overall responsibility: KM

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