All-Patient Refined Diagnosis-Related Groups in Primary Arthroplasty

Lavernia, Carlos J.; Laoruengthana, Artit; Contreras, Juan S.; Rossi, Mark D.

doi:10.1016/j.arth.2009.03.008

Cited by 27 publications

(24 citation statements)

References 10 publications

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“…Charnley classification and the preoperative value of the outcome examined contributed most to the models' predictive power rather than the three comorbidity measures tested. Similarly, Lavernia et al [14] found comorbidity scores correlated poorly with patient pain level and functional abilities after total joint arthroplasty. Interestingly, Charnley classification had stronger predictive power than the patient preoperative health state for the EQ-5D index, EQ VAS, and, most evidently, for the postoperative pain VAS.…”

Section: Discussionmentioning

confidence: 91%

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

Greene

Rolfson

Gordon

et al. 2015

Clinical Orthopaedics &Amp; Related Research

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Section: Discussionmentioning

confidence: 91%

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

Greene

Rolfson

Gordon

et al. 2015

Clinical Orthopaedics &Amp; Related Research

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“…33 Finally, we used the EDW to retrieve demographic and other covariates, including age, gender, race, insurance, calendar month of hospitalization, and severity of illness (SOI) using All Patient Refined Diagnosis Related Groups. 34 For PCH, asthma discharges between We included baseline data back to 2003 to take into account any preexisting secular trends.…”

Section: Data Collectionmentioning

confidence: 99%

Improving Pediatric Asthma Care and Outcomes Across Multiple Hospitals

et al. 2015

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BACKGROUND AND OBJECTIVES: Gaps exist in inpatient asthma care. Our aims were to assess the impact of an evidence-based care process model (EB-CPM) 5 years after implementation at Primary Children's Hospital (PCH), a tertiary care facility, and after its dissemination to 7 community hospitals.METHODS: Participants included asthmatics 2 to 17 years admitted at 8 hospitals between 2003 and 2013. The EB-CPM was implemented at PCH between January 2008 and March 2009, then disseminated to 7 community hospitals between January and June 2011. We measured compliance using a composite score (CS) for 8 quality measures. Outcomes were compared between preimplementation and postimplementation periods. Confounding was addressed through multivariable regression analyses.RESULTS: At PCH, the CS increased and remained at .90% for 5 years after implementation. We observed sustained reductions in asthma readmissions (P = .026) and length of stay (P , .001), a trend toward reduced costs (P = .094), and no change in hospital resource use, ICU transfers, or deaths. The CS also increased at the 7 community hospitals, reaching 80% to 90% and persisting .2 years after dissemination, with a slight but not significant readmission reduction (P = .119), a significant reduction in length of stay (P , .001) and cost (P = .053), a slight increase in hospital resource use (P = .032), and no change in ICU transfers or deaths.CONCLUSIONS: Our intervention resulted in sustained, long-term improvement in asthma care and outcomes at the tertiary care hospital and successful dissemination to community hospitals.

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“…The AUC is an effective method for quantifying the discriminatory capacity of a diagnostic test to correctly classify patients with and without infection in which it is defined as Each author certifies that he or she, or a member of his or her immediate family, has no funding or commercial associations (eg, consultancies, stock ownership, equity interest, patent/licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article. [12]. In 2013, the Universal American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator was developed for use across all surgical subspecialties and covering 2500 Current Procedural Terminology (CPT) codes [1].…”

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confidence: 99%

The ACS NSQIP Risk Calculator Is a Fair Predictor of Acute Periprosthetic Joint Infection

Wingert

Gotoff

Parrilla

et al. 2016

Clinical Orthopaedics &Amp; Related Research

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Background Periprosthetic joint infection (PJI) is a severe complication from the patient's perspective and an expensive one in a value-driven healthcare model. Risk stratification can help identify those patients who may have risk factors for complications that can be mitigated in advance of elective surgery. Although numerous surgical risk calculators have been created, their accuracy in predicting outcomes, specifically PJI, has not been tested.

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All-Patient Refined Diagnosis-Related Groups in Primary Arthroplasty

Cited by 27 publications

References 10 publications

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

Standard Comorbidity Measures Do Not Predict Patient-reported Outcomes 1 Year After Total Hip Arthroplasty

Improving Pediatric Asthma Care and Outcomes Across Multiple Hospitals

The ACS NSQIP Risk Calculator Is a Fair Predictor of Acute Periprosthetic Joint Infection

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