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The American Journal of Managed Care April 2015
Clinical Provider Perceptions of Proactive Medication Discontinuation
Amy Linsky, MD, MSc; Steven R. Simon, MD, MPH; Thomas B. Marcello, BA; and Barbara Bokhour, PhD
Optimizing the Use of Telephone Nursing Advice for Upper Respiratory Infection Symptoms
Rosalind Harper, PhD, RN; Tanya Temkin, MPH; and Reena Bhargava, MD
Redefining and Reaffirming Managed Care for the 21st Century
David Blumenthal, MD, MPP; and David Squires, MA
Managing Specialty Care in an Era of Heightened Accountability: Emphasizing Quality and Accelerating Savings
John W. Peabody, MD, PhD, DTM&H; Xiaoyan Huang, MD; Riti Shimkhada, PhD; and Meredith Rosenthal, PhD
Antibiotic Prescribing for Respiratory Infections at Retail Clinics, Physician Practices, and Emergency Departments
Ateev Mehrotra, MD, MPH; Courtney A. Gidengil, MD, MPH; Claude M. Setodji, PhD; Rachel M. Burns, MPH; and Jeffrey A. Linder, MD, MPH
Persistent High Utilization in a Privately Insured Population
Wenke Hwang, PhD; Michelle LaClair, MPH; Fabian Camacho, MS; and Harold Paz, MD, MS
Self-Efficacy in Insurance Decision Making Among Older Adults
Kathleen Kan, MD; Andrew J. Barnes, PhD; Yaniv Hanoch, PhD; and Alex D. Federman, MD, MPH
Limited Effects of Care Management for High Utilizers on Total Healthcare Costs
Brent C. Williams, MD, MPH
Observation Encounters and Subsequent Nursing Facility Stays
Anita A. Vashi, MD, MPH, MHS; Susannah G. Cafardi, MSW, LCSW, MPH; Christopher A. Powers, PharmD; Joseph S. Ross, MD, MHS; and William H. Shrank, MD, MSHS
Elderly Veterans With Dual Eligibility for VA and Medicare Services: Where Do They Obtain a Colonoscopy?
Ashish Malhotra, MD, MS; Mary Vaughan-Sarrazin, PhD; and Gary E. Rosenthal, MD
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Costs of Venous Thromboembolism Associated With Hospitalization for Medical Illness
Kevin P. Cohoon, DO, MSc; Cynthia L. Leibson, PhD; Jeanine E. Ransom, BA; Aneel A. Ashrani, MD, MS; Tanya M. Petterson, MS; Kirsten Hall Long, PhD; Kent R. Bailey, PhD; and John A. Heit, MD
Functional Status and Readmissions in Unilateral Hip Fractures
Paul Gerrard, MD; Richard Goldstein, PhD; Margaret A. DiVita, PhD; Chloe Slocum, MD; Colleen M. Ryan, MD; Jacqueline Mix, MPH; Paulette Niewczyk, PhD, MPH; Lewis Kazis, ScD; Ross Zafonte, DO; and Jeffrey C. Schneider, MD

Costs of Venous Thromboembolism Associated With Hospitalization for Medical Illness

Kevin P. Cohoon, DO, MSc; Cynthia L. Leibson, PhD; Jeanine E. Ransom, BA; Aneel A. Ashrani, MD, MS; Tanya M. Petterson, MS; Kirsten Hall Long, PhD; Kent R. Bailey, PhD; and John A. Heit, MD
Venous thromboembolism during or after recent hospitalization for medical illness contributes a substantial economic burden to society across all hospital and ambulatory care delivered.
ABSTRACT
Objectives: To determine population-based estimates of medical costs attributable to venous thromboembolism (VTE) among patients currently or recently hospitalized for acute medical illness.
 
Study Design: Population-based cohort study conducted in Olmsted County, Minnesota.
 
Methods: Using Rochester Epidemiology Project (REP) resources, we identified all Olmsted County residents with objectively diagnosed incident VTE during or within 92 days of hospitalization for acute medical illness over the 18-year period of 1988 to 2005 (n = 286). One Olmsted County resident hospitalized for medical illness without VTE was matched to each case for event date (±1 year), duration of prior medical history, and active cancer status. Subjects were followed forward in REP provider-linked billing data for standardized, inflation-adjusted direct medical costs (excluding outpatient pharmaceutical costs) from 1 year before their respective event or index date to the earliest of death, emigration from Olmsted County, or December 31, 2011 (study end date). We censored follow-up such that each case and matched control had similar periods of observation. We used generalized linear modeling (controlling for age, sex, preexisting conditions, and costs 1 year before index) to predict costs for cases and controls.
 
Results: Adjusted mean predicted costs were 2.5-fold higher for cases ($62,838) than for controls ($24,464) (<.001) from index to up to 5 years post index. Cost differences between cases and controls were greatest within the first 3 months after the event date (mean difference = $16,897) but costs remained significantly higher for cases compared with controls for up to 3 years.
 
Conclusions: VTE during or after recent hospitalization for medical illness contributes a substantial economic burden.
 
Am J Manag Care. 2015;21(4):e255-e263
Venous thromboembolism (VTE) during or shortly after hospitalization for acute medical illness contributes a substantial economic burden; VTE-attributable costs are highest in the initial 3 months but persist even 3 years beyond the VTE event date. This finding will help to inform models that assess the cost-effectiveness of alternative interventions to reduce VTE occurrence and guide reimbursement policy.
Venous thromboembolism (VTE)—consisting of deep vein thrombosis (DVT) and its complication, pulmonary embolism (PE)—causes substantial morbidity, disability, and mortality.1 Complete and valid estimates of VTE-associated medical care utilization and costs are essential for informing allocation of scarce resources, targeting efforts toward prevention, identifying best practices, addressing future care needs, and implementing cost-effective treatments.2 However, existing estimates of VTE-associated costs2-5 are problematic. Previous studies typically failed to control for age, sex, comorbid conditions, and other events that place patients at risk for VTE, particularly hospitalization for major surgery or acute medical illness, trauma or major fracture, and cancer.1 Together, these latter risk exposures account for over 75% of all incident VTE in the population.6 Although VTE is increasingly diagnosed and managed solely in office-based settings,7 the majority of population-based cost estimates were limited to patients admitted to the emergency department (ED) and/or hospital; patients diagnosed and managed solely within office-based or chronic care (eg, nursing home) settings were excluded. Moreover, case ascertainment almost always relied on discharge diagnosis codes obtained from billing data or death certificates.4,5 The limitations of discharge diagnosis codes for identifying incident VTE are well recognized.8-11

In those very few cost studies that validated VTE using medical record review, cost estimates were often obtained using self-reported utilization and applying national average estimates of hospital costs per day, ignoring differences in daily costs between persons with and without VTE. Many estimates of VTE-associated medical costs are also limited to costs accrued during the initial encounter.12,13 To address these limitations, we performed a population-based matched-cohort study to estimate the excess medical costs attributable to VTE that occurred during or recently after hospitalization for acute medical illness, independent of potential confounding due to VTE risk factors. We took advantage of Rochester Epidemiology Project (REP) resources, including a previously identified population-based inception cohort consisting of all Olmsted County, Minnesota, residents with objectively diagnosed incident VTE, as well as previously identified matched non-VTE controls drawn from the same population.14 REP resources also afforded provider-linked objective medical cost estimates based on line-item detail for every service and procedure over extended periods of time.15 Combining objectively diagnosed VTE cases and controls with objective cost data for each individual afforded the opportunity to estimate medical care costs attributable to VTE that were: 1) across the full spectrum from symptomatic through fatal events; 2) from before the event until death or emigration from the area; 3) adjusted for age, sex, and calendar year; and 4) adjusted for prevalent comorbid conditions. Thus, we were able to estimate the excess cost of medical care that is attributable to VTE, independent of potential confounding due to VTE risk factors.

METHODS

Study Setting and Design

Olmsted County, Minnesota (2010 census population = 144,248), provides a unique opportunity for investigating the natural history of VTE.6,16,17 Rochester, the county seat, is approximately 80 miles from the nearest major metropolitan area. Mayo Clinic, together with Olmsted Medical Center (OMC) (a second group practice), and their affiliated hospitals, provide over 95% of all medical care delivered to local residents.18 Since 1907, every Mayo patient has been assigned a unique identifier; all information from every provider contact is contained within a unit record for each patient. Diagnoses assigned at each visit are coded and entered into continuously updated files. Under the auspices of the REP, the unique identifiers, diagnostic index, and medical records linkage were expanded to include the few other providers of medical care to local residents, including OMC and the few private practitioners in the area, thereby linking the medical records for community residents at the individual level.14,19 Using REP resources, we performed a cohort study (approved by the Mayo Clinic and OMC Institutional Review Boards).

Study Population

All Olmsted County residents with incident DVT or PE over the 40-year period of 1966 to 2005 were identified as previously described.6 REP records of individuals who refused authorization for use of medical records in research were excluded from review.18,20 The medical records for the remaining individuals were reviewed from date first seen until date last seen at any REP provider to identify, confirm, and characterize each VTE event. Incident events were limited to persons residing in Olmsted County for whom this was a first-in-lifetime symptomatic VTE. Trained, experienced nurse abstractors performed the record review, which included radiological, ultrasound, and nuclear medicine imaging reports, as well as all outpatient general history notes, ED notes and hospitalization records, nursing notes, surgical records, vascular laboratory reports, echocardiography reports, autopsy reports, and death certificates.

Study nurses recorded the method of VTE diagnosis, VTE event type (ie, DVT, PE, or both; and the presence/absence of chronic thromboembolic pulmonary hypertension), date of VTE (ie, index date for cases), location at onset of VTE symptoms and/or signs (ie, hospital, nursing home, or community), sex, age, and active cancer and cancer type as of index date. The present study was limited to “objectively diagnosed” events, as previously described,1,6,9,17 and included all incident VTE cases with recent hospitalization for medical illness (ie, within 92 days [365 days ⁄ 4, or ~3 months] before index); residents admitted to hospital solely for VTE treatment were not included. The hospitalization closest to but before VTE, or the hospitalization during which VTE occurred, was selected as the “index hospitalization.” Cases with a surgical hospitalization within 92 days before index were excluded. REP also provides enumeration of the entire Olmsted County population from which potential controls can be sampled.14 Using this system, we identified all Olmsted County residents with hospitalization for acute medical illness within ± 1 year of each case’s VTE date, similar length of medical record, and no prior VTE.16 For patients with multiple hospitalizations per year, 1 hospitalization was randomly chosen to compose the sampling frame. From this, a random sample of potential controls was identified, of which, 2 were matched on case VTE event year and active cancer status. Of these 2 controls per case, 1 control was randomly chosen for the current study. The hospitalization identified in the sampling frame was selected as the control's “index hospitalization.” Assignment of the control’s index date depended on whether the matched case’s VTE event occurred during or after the case’s index hospitalization (Figure 1). For cases whose VTE occurred during the index hospitalization, the control’s index date was randomly assigned to be a day within the control’s index hospitalization admission and discharge dates. For cases whose VTE occurred within 92 days after discharge from the index hospitalization, the control’s index date was randomly assigned to be a day within 92 days after the control’s index hospitalization discharge date. Medical records of potential controls were reviewed to confirm Olmsted County residency as of index, absence of surgical hospitalizations within 92 days before index, and that they matched the case with respect to active cancer as of index.

 


Collection of Medical Costs

Through an electronic data-sharing agreement between Mayo Clinic and OMC, patient-level administrative data on healthcare utilization and associated billed charges incurred at these institutions are shared and archived within the REP Cost Data Warehouse for use in approved research studies. Data are electronically linked, allowing access to complete information on all hospital and ambulatory care delivered by these providers to area residents from January 1, 1987, through December 31, 2011. The REP Cost Data Warehouse includes information on all Olmsted County residents (ie, both sexes, all ages, and all payer types, including the uninsured) and contains line-item detail on date, type, frequency, and billed charge for every good or service provided. Recognizing discrepancies between billed charges and true resource use, the REP Cost Data Warehouse employs widely accepted valuation techniques to generate a standardized inflation-adjusted estimate of the costs of each service or procedure in constant dollars. Cost estimates in this study were adjusted to 2011 dollars.21 Because cost data have only been available electronically since 1987 and we wished to obtain costs in the year before index, the present study was limited to all Olmsted County residents with a first-in-lifetime objectively diagnosed DVT or PE occurring between 1988 and 2005.1,6 Each case and control was followed forward in time for costs from 1 year before their respective index date to earliest of death, emigration from Olmsted County, or December 31, 2011 (study end date). We ensured similar periods of observation for each case and matched control by censoring both members of each pair as of the shortest length of follow-up for either member.

Pre-Index Comorbid Conditions

To compare baseline characteristics and comorbidities between cases and controls, we obtained all International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes assigned to each individual in Olmsted County Healthcare Expenditure and Utilization Database (OCHEUD) 1 year before index, and categorized every diagnosis code assigned to each individual into the 17 ICD-9-CM chapters and 114 subchapters. A summary measure of medical conditions in the year before index was obtained using Johns Hopkins Adjusted Clinical Groups (ACG) System software.22 ACG software categorizes individuals’ diagnosis codes into groupings based on persistence, severity, and etiology of the condition, as well as diagnostic certainty and need for specialty care.22 ACG software was also used to assign a Resource Utilization Band (RUB) value to each individual. RUB categories are aggregations of ACGs that have similar expected resource use, with values ranging from 0 (no relevant diagnosis codes) to 5 (diagnosis codes associated with very high use).23

Statistical Analyses

 
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