title: Impact of business infrastructure on financial metrics in departments of surgery.
abstract: BACKGROUND
  In the current environment, pressure is ever increasing to maximize financial performance in surgery departments. Factors such as physician extenders, billing and collection, payor mix, contracting, incentives from the Centers for Medicare and Medicaid Services, and administrative incentives may greatly influence financial performance. However, despite a plethora of information from the University HealthSystem Consortium and the Association of American Medical Colleges, best-practice information for business infrastructure is lacking. To obtain a sampling of current practices, we conducted a survey of departments of surgery.
  
  
  METHODS
  An anonymous 30-question survey addressing demographics, productivity, revenue and expense profile, payor mix, physician extender and staff personnel, billing and collections methodology, and financial performance was distributed among members of the Society of Surgical Chairs via SurveyMonkey. This was approved by the Loyola Institutional Research Board. Multivariate linear regression analyses and t tests/rank-sum tests were performed, as appropriate. Data are presented as mean ± SEM.
  
  
  RESULTS
  A total of 25 (19%) departments responded; 14 were integrated with the hospital/health system, and 11 were integrated with the medical school. In 60% (n = 15), the main hospital had 500 to 1,000 beds; 48% (n = 12) had >4 hospitals in their system. For FY10, MD clinical full-time equivalents (FTEs) were 49 ± 10; total work relative value units (wRVUs) were 320 ± 8 k; and total billed cases were 43 ± 16 k. A total of 23 of 25 used physician-extenders with an average of 18 ± 5 per department and in 22 of 23, the physician extenders billed. On average, there were 18 ± 6 clinical-support staff, 25 ± 11 front-office staff, and 13 ± 3 back-office support staff FTEs. Among these FTEs, there were 16 ± 5 devoted to business operations (billing, coding, denial/claims management, financial oversight). Collections/wRVUs were $60 ± 3 (range, 39-80). Regression modeling demonstrated that total wRVUs were determined by the number of MD FTEs (P = .01), number of physician extenders (P = .01), number of front-office staff (P = .01), number of back-office staff (P = .02), and number of total business staff (P = .01). Collections/wRVUs were predicted by number of hospitals (P = .04), number of MD FTEs (P = .03), number of physician extenders (P = .01), and number of cases/total business staff (P = .02). Interestingly, wRVUs/MD was predicted by number of MD FTEs (P = .01) but were not greatly impacted by numbers of clinical or business support staff. In 4 of 25, the billing and coding staff were incentivized and had a Collections/wRVU = 64 ± 5 whereas nonincentivized staff had collections/wRVU = 59 ± 3. (P = NS) Also, %Accounts receivable >90 days (15% vs 25%) were not substantially different. Only 48% (12/25) have departments have recouped Centers for Medicare and Medicaid dollars for Physician Quality Reporting Initiative, Meaningful Use, Patient-Centered Medical Homes, or other Accountable Care-like programs. One-half (13) of the departments had both an inpatient and outpatient electronic medical record. Finally, on a scale of 1-10 (10 = highest), the average level of satisfaction with billing and collections processes was 6.
  
  
  CONCLUSIONS
  Our results indicate that the physician extender, clinical support staff, and business staff environment can impact surgeon productivity, and there is opportunity for improvement. Determining best practices for ratios of support staff/MD and optimizing the role of electronic medical record in workflow and billing/collections are critical in the current environment. Our pilot study requires extension across more institutions for validation.
authors.affiliation: Department of Surgery, Loyola University Chicago, Health Sciences Division, Maywood, IL 60163, USA.
authors.forename: Philip Y
authors.initials: PY
authors.lastname: Wai
authors.forename: Tim
authors.initials: T
authors.lastname: O'Hern
authors.forename: Dave O
authors.initials: DO
authors.lastname: Andersen
authors.forename: Marissa C
authors.initials: MC
authors.lastname: Kuo
authors.forename: Cynthia E
authors.initials: CE
authors.lastname: Weber
authors.forename: Lindsay J
authors.initials: LJ
authors.lastname: Talbot
authors.forename: Paul C
authors.initials: PC
authors.lastname: Kuo
mesh_terms: D017598:Efficiency, Organizational; D005377:Financial Management, Hospital; D006801:Humans; D010865:Pilot Projects; D012955:Societies, Medical; D013503:Surgery Department, Hospital / Q000191:economics* / Q000458:organization & administration; D011795:Surveys and Questionnaires; D014481:United States; D000078329:Workforce