Derivation and Validation of Automated Electronic Search Strategies to Extract Charlson Comorbidities From Electronic Medical Records

Singh, Balwinder; Singh, Amandeep; Ahmed, Adil; Wilson, Gregory; Pickering, Brian; Herasevich, Vitaly; Gajić, Ognjen; Li, Guangxi

doi:10.1016/j.mayocp.2012.04.015

Cited by 187 publications

(150 citation statements)

References 41 publications

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“…This registry seeks to capture all subsequent procedures done at our institution or elsewhere. Additional patient information was collected using validated automated digital algorithms to identify Charlson comorbidities and perioperative factors from the patient's electronic medical records [12]. The outcome measures included postoperative fractures, revision surgical procedures, revision for aseptic distal loosening, reoperations, dislocations, and other complications captured through the registry and confirmed by medical record review.…”

Section: Total Joint Registry and Electronic Medical Recordmentioning

confidence: 99%

What Are the Risk Factors and Complications Associated With Intraoperative and Postoperative Fractures in Total Wrist Arthroplasty?

Wagner

Srnec

Mehrotra

et al. 2017

Clinical Orthopaedics &Amp; Related Research

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Background Total wrist arthroplasty (TWA) can relieve pain and preserve some wrist motion in patients with advanced wrist arthritis. However, few studies have evaluated the risks and outcomes associated with periprosthetic fractures around TWAs. Questions/purposes (1) What is the risk of intraoperative and postoperative fractures after TWAs? (2) What factors are associated with increased risk of intraoperative and postoperative fracture after TWAs? (3) What is the fracture-free and revision-free survivorship of TWAs among patients who sustained an intraoperative fracture during the index TWA? Methods At one institution during a 40-year period, 445 patients underwent primary TWAs. Of those, 15 patients died before 2 years and 5 were lost to followup, leaving 425 patients who underwent primary TWAs with a minimum of 2-year followup. The primary diagnosis for the TWA included osteoarthritis ([OA] 5%), inflammatory arthritis (90%), and posttraumatic arthritis (5%). Indications for TWA included pancarpal arthritis combined with marked pain and loss of wrist function. The mean age of the patients was 57 years, BMI was 26 kg/m 2 , and 73% were females. Six different implants were used during the 40-year period. Mean followup was 10 years (range, 2-18 years). Results Intraoperative fractures occurred in nine (2%) primary TWAs, while postoperative fractures occurred after eight (2%) TWAs. After analyzing demographics, comorbidities, and surgical factors, intraoperative fractures were found to be associated with only age at surgery (hazard ratio [HR], 1.10; 95% CI, 1.03-1.20; p = 0.006) and use of a bone graft (HR, 5.80; 95% CI, p = 0.03). No factors were found to be associated with increased risk of postoperative fractures; specifically, intraoperative fracture was not associated with subsequent fracture development. The 5-, 10-, and 15-year KaplanMeier survival rates free of postoperative fracture were 99%, 98%, and 95%, respectively. The 5-and 10-year revision-free survival rates after intraoperative fracture were 88% and 88%, respectively, compared with 84% and 74% without an intraoperative fracture (p = 0.36). Furthermore, the survival-free of revision surgery rates for aseptic distal loosening at 5 and 10 years were 88% and 88%, respectively, compared with 93% and 87% without a fracture (p = 0.85). Conclusions Intraoperative fractures occur in approximately 2% of TWAs. These fractures do not appear to affect long-term implant survival or risk of fracture. Patient age and the need for bone graft were the only factors in the risk of intraoperative fractures. Postoperative fractures also occur in 2% of TWAs, but often result in revision surgery.

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Section: Total Joint Registry and Electronic Medical Recordmentioning

confidence: 99%

What Are the Risk Factors and Complications Associated With Intraoperative and Postoperative Fractures in Total Wrist Arthroplasty?

Wagner

Srnec

Mehrotra

et al. 2017

Clinical Orthopaedics &Amp; Related Research

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“…Our results add credence to the use of computerized searches of EHRs of large patient cohorts to extract clinical variables, processes, and outcomes of interest. (2,3,(12)(13)(14) The increased perioperative risk that OSA poses for surgical patients is well recognized, (4,5) and the condition has become the topic of clinical management guidelines that call for increased vigilance of affected patients. (11,15) Despite the risk, OSA may present with vague symptoms (eg, increased daytime sleepiness), and population studies have suggested that most (approximately 90%) of OSA cases are undiagnosed, (7) including OSA of surgical patients.…”

Section: Discussionmentioning

confidence: 99%

Derivation and validation of an automated electronic search algorithm to identify patients at risk for obstructive sleep apnea

Olatoye

Wilson

Kashyap

et al. 2017

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Background. Automated extraction of data from electronic health records has allowed high-quality retrospective analyses of large cohorts. Objectives. To derive and validate an automated electronic search algorithm to identify surgical patients with a diagnosis of or at high risk for obstructive sleep apnea (OSA). Methods. From 558 adult patients who underwent surgery from January 1, 2011, through December 31, 2015, we constructed a derivation cohort of 100 subjects selected using the initial search algorithm to have equal numbers of patients with high and low likelihood of having OSA. This algorithm conducted a free-text electronic search of patient diagnoses and interrogated results of a preoperative checklist that specifically queried patients regarding OSA history and screened for OSA risk using Flemons criteria. The derivation cohort was then manually reviewed to identify patients with OSA risk and results were used to refine the algorithm. Second, the algorithm was validated with the other 458 patients (the validation cohort). The sensitivity and specificity were compared again with manual chart review of the respective group. Results. In the derivation cohort, the automated electronic algorithm achieved a sensitivity of 98.2% and a specificity of 100.0% compared with the manual review. In the validation cohort, sensitivity was 100.0% and specificity was 98.4% in this comparison.

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“…The data repository was accessed by investigators using the Data Discovery and Query Builder (DDQB) web-based software, which is maintained collaboratively with IBM (International Business Machines Corp., Armonk, NY) by dedicated information technologists, regularly audited, and validated in the literature as accurate for both International Classification of Diseases, Ninth Revision and free text search. 12,13 The DDQB was queried for both International Classification of Diseases, Ninth Revision E003.1 and free text terms hockey and ice hockey in patient diagnoses. Although coding practices at our institution have not changed over the study period, addition of a free text query helped ensure that injured patients were not missed.…”

Section: Patient Identificationmentioning

confidence: 99%

Youth Ice Hockey Injuries Over 16 Years at a Pediatric Trauma Center

Polites¹,

Sebastian

Habermann

et al. 2014

Pediatrics

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BACKGROUND: Youth ice hockey is an exciting sport with growing participation in the United States. Updated assessment of injury patterns is needed to determine risk factors for severe injury and develop preventive efforts. The purpose of this study was to evaluate our experience as a level 1 pediatric trauma center in Minnesota treating injured youth ice hockey players. METHODS: Children ≤18 years old who presented to our institution from July 1997 to July 2013 with an injury sustained while participating in ice hockey were identified. Patient demographic information, injury characteristics, and outcomes including use of computed tomography, hospital admission, and procedures were obtained. Age- and gender-specific patterns were determined for injuries and outcomes. RESULTS: Over 16 years, 168 injuries in 155 children occurred, including 26 (15.5%) injuries in girls. Extremity injuries were most common, followed by traumatic brain injury. Injuries to the spine, face, and trunk were less common. Traumatic brain injury and injuries to the spine were most common in younger children (≤14 years old) and girls, whereas injuries to the face were most common in older players (≥15 years old). Most injuries resulted from intentional contact. Admission to the hospital was needed in 65 patients, including 14 (8.3%) who needed intensive care. A major procedure was needed by 23.2% of patients because of their injuries. CONCLUSIONS: Youth ice hockey trauma can be severe, necessitating a thorough evaluation of injured children. Injury patterns are influenced by age and gender, providing an opportunity for targeted preventive efforts.

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Derivation and Validation of Automated Electronic Search Strategies to Extract Charlson Comorbidities From Electronic Medical Records

Cited by 187 publications

References 41 publications

What Are the Risk Factors and Complications Associated With Intraoperative and Postoperative Fractures in Total Wrist Arthroplasty?

What Are the Risk Factors and Complications Associated With Intraoperative and Postoperative Fractures in Total Wrist Arthroplasty?

Derivation and validation of an automated electronic search algorithm to identify patients at risk for obstructive sleep apnea

Youth Ice Hockey Injuries Over 16 Years at a Pediatric Trauma Center

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