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1.
Hand (N Y) ; : 15589447221142893, 2022 Dec 23.
Article in English | MEDLINE | ID: mdl-36564989

ABSTRACT

BACKGROUND: Diabetes mellitus often exists for many years prior to diagnosis, and very little is known about the role of the prediagnosis stage of metabolic impairment in contributing to hand and upper-extremity pathology. The goal of this study is to determine the prevalence of undiagnosed glucose dysregulation in patients presenting with the 2 most commonly treated conditions of the hand and wrist. METHODS: A retrospective study was performed of hand surgery patients with no established diagnosis of prediabetes or diabetes referred for a 2-hour glucose tolerance test according to American Diabetes Association criteria. Patients were divided into 3 groups: peripheral neuropathies, trigger finger, and controls with various upper-extremity diagnoses. Rates of undiagnosed prediabetes and diabetes were compared between groups, including subgroup analysis of patients based on unilateral or bilateral presentation. Binary logistic regression analysis was also used to calculate odds ratios for multiple variables. RESULTS: Patients with neuropathy had a significantly higher incidence of undiagnosed dysglycemia compared with the control group. Of those patients, 51.3% were prediabetic and 12.8% were diabetic. The control group had significantly lower rates. Within the bilateral neuropathy patients, 59.6% had prediabetes and 15.4% had diabetes, versus 34.6% with prediabetes and 7.7% with diabetes in the unilateral group. CONCLUSIONS: Hand surgeons encounter a patient population with high rates of undiagnosed prediabetes and diabetes, with some presentations as much as 6 times higher than the general population. Certain patient presentations should prompt appropriate diagnostic testing and referral, especially those presenting with bilateral compression neuropathy and elevated body mass index.

2.
J Vasc Surg ; 73(6): 2144-2153, 2021 06.
Article in English | MEDLINE | ID: mdl-33359847

ABSTRACT

BACKGROUND: Surgical procedures account for 50% of hospital revenue and ∼60% of operating costs. On average, <20% of surgical instruments will be used during a case, and the expense for resterilization and assembly of instrument trays ranges from $0.51 to $3.01 per instrument. Given the complexity of the surgical service supply chain, physician preferences, and variation of procedures, a reduction of surgical cost has been extremely difficult and often ill-defined. A data-driven approach to instrument tray optimization has implications for efficiency and cost savings in sterile processing, including reductions in tray assembly time and instrument repurchase, repair, and avoidable depreciation. METHODS: During a 3-month period, vascular surgery cases were monitored using a cloud-based technology product (OpFlow, Operative Flow Technologies, Raleigh, NC) as a part of a hospital-wide project. Given the diversity of the cases evaluated, we focused on two main vascular surgery trays: vascular and aortic. An assessment was performed to evaluate the exact instruments used by the operating surgeons across a variety of cases. The vascular tray contained 131 instruments and was used for the vast majority of vascular cases, and the aortic tray contained 152 instruments. Actual instrument usage data were collected, a review and analysis performed, and the trays optimized. RESULTS: During the 3-month period, 168 vascular surgery cases were evaluated across six surgeons. On average, the instrument usage per tray was 30 of 131 instruments (22.9%) for the vascular tray and 19 of 152 (12.5%) for the aortic tray. After review, 45.8% of the instruments were removed from the vascular tray and 62.5% from the aortic tray, for 1255 instruments removed from the versions of both trays. An audit was performed after the removal of instruments, which showed that none of the removed instruments had required reinstatement. The instrument reduction from these two trays alone yielded an estimated costs savings of $97,781 for repurchase and $97,444 in annual resterilization savings. Annually, the removal of the instruments is projected to save 316.2 hours of personnel time. The time required for operating room table setup decreased from a mean of 7:44 to 5:02 minutes for the vascular tray (P < .0001) and from 8:53 to 4:56 minutes for the aortic tray (P < .0001). CONCLUSIONS: Given increasing cost constraints in healthcare, sterile processing remains an untapped resource for surgical expense reduction. A comprehensive data analytics solution provided the ability to make informed decisions in tray management that otherwise could not be reliably performed.


Subject(s)
Hospital Costs , Operating Rooms/economics , Surgical Instruments/economics , Vascular Surgical Procedures/economics , Vascular Surgical Procedures/instrumentation , Cloud Computing , Cost Savings , Cost-Benefit Analysis , Equipment Reuse/economics , Humans , Machine Learning , Pilot Projects , Sterilization/economics , Time Factors , Workflow
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