Unit 3: Finances
Unit 5. Finances

Section 1. Financial Viability

Estimating Patient-Care Revenue

Two key pieces of information that predict patient-care revenue are needed for each payer source:

  • The number of patient visits or encounters
  • The average reimbursement per visit or encounter

Number of Patient Visits or Encounters

The interactive budget-planning workbook estimates the number of patient visits by payer type using the anticipated number of patient visits for the year and the percentage of patient visits for each payer type. Safety net dental clinics that are expanding have the benefit of their past experience to help generate their patient-visit or -encounter estimates. New clinics with a pre-existing medical clinic counterpart have the benefit of a historical payer mix that will require adjustment for the percentage that is funded by Medicare, which does not cover oral health care. New clinics, however, must rely on information from other sources, such as safety net dental clinics that are willing to share information. A clinic's mission and objectives may influence the percentages (for example, children vs. adults, access-focus vs. self-sufficiency focus, emergency services vs. preventive or restorative services). This number is a key component of the workbook; adjust it as necessary to best describe your situation.

How to Estimate of Number of Encounters per Year
In an efficient safety net dental clinic, each dentist has two dental assistants and 2.5 dental chairs. The clinic would have 2,500–3,200 encounters (visits) per full-time-equivalent (FTE) dentist and approximately 1,300–1600 encounters per FTE dental hygienist, annually. The number of encounters per year for a clinic is computed based on these expectations of the respective encounter rates for dentists and dental hygienists and the number of FTEs of each. This example uses the numbers shown in the expenses tab of the interactive workbook:

  • 0.8 FTE dental hygienist with 1,300 encounters per FTE per year.
  • 1.5 FTE dentists with 2,600 encounters per dentist per year. (This includes a reduction of 0.2 FTE dental director time in which patients are not being treated and an addition of 0.2 FTE contractor time.)
  • Total of 4,940 encounters: [0.8 x 1,300= 1,040] + [1.5 x 2,600 = 3,900] = 4,940.

The ratio of dental assistants and chairs per dentist provided here is ideal. For many clinics, this staffing level may not be within their means initially. Therefore, lower ratios (like 1.5 dental assistants and two chairs per dentist) may be used when a clinic opens or when a new oral health professional is added, with planned future movement toward the ideal ratios.

When estimating the cost of a startup program or of the addition of new health professionals, it’s important to factor in a startup process. The first year a clinic is operational, it is likely to underperform from expected visit projections, while the expenses will be close to where they were predicted. As a result, the first year’s financials may be negative, with each subsequent year showing an increase in revenue. The ramp-up process should not take longer than 12 months; most health professionals will achieve expected productivity within 6 months provided that clinic operations are efficient.

New clinics often over-estimate revenue from patient care in the planning phase. Be practical, be realistic, and use data to determine payer mix, with particular attention to Medicaid and sliding fee. Use this simple worksheet to calculate your own expected productivity

Average Reimbursement per Visit or Encounter

The average reimbursement per visit by payment source is the product of a number of factors, including clinic fee schedule, structure of sliding fee schedule and nominal fee level established, Medicaid rates and coverage for state, structure of CHIP program in state, patient mix by age, service mix (such as emergency, diagnostic or preventive, and restorative), managed care, eligibility for cost-based or PPS Medicaid reimbursement, and success in billing and collections.

Your ability to predict patient-care revenue will vary with the quality of the information about visits and reimbursement you have. Safety net dental clinics or health centers that have operated for a few years will have an advantage over new clinics, which must rely on information that others are willing to share. If you need to estimate revenue, err toward the conservative side in your projections.

Clinics differ in their payer mixes. Patient eligibility, the sliding-fee schedule, and nominal-fee policies of your clinic, along with the demographics of your catchment area, shape your clinic's payer mix. It is common for at least half visits of a safety net dental clinic that emphasizes financial sustainability to be for patients who participate in Medicaid. A large network of city government dental clinics that emphasizes access and offers a nominal fee and a generous sliding-fee schedule, however, reports that over two-thirds of patient visits are generated by nominal-fee or sliding-fee patients and less than 20 percent by patients who participate in Medicaid.

If the clinic treats patients covered by capitation plans, reimbursement information would be necessary on a patient basis rather than on a visit or encounter basis.

Finally, you must deduct the bad debt that you expect. Bad debt is the portion of uncompensated care that results from unpaid charges to patients, whether they are full-fee, sliding-fee-schedule, or nominal-fee patients. The difference between your full charges and your collections represent uncompensated care. Uncompensated care comes in the form of adjustments to your full fees that are due to either agreed-upon fee reductions (such as PPO, Medicaid, or Delta plans), charity care (such as sliding-fee schedule) or bad debt (unpaid bills by self-pay patients).

Once you have determined your estimates, enter them in the interactive budget-planning workbook.

CAUTION! New clinics often overestimate revenue from patient care in the planning phase. Be practical, be realistic, and use data to determine payer mix, with particular attention to patients who participate in Medicaid and sliding-fee-schedule patients. Be realistic!!

Factors That Affect Patient-Care Revenue

Within the parameters of their mission and goals, clinic administrators generally want to and are expected to appropriately maximize the amount of revenue derived from patient care. The following major factors influence patient-care revenue:

  • Fees: Establishing fees is a delicate balance of maximizing access and clinic revenue. Full fees should be set at prevailing rates, with nominal- and sliding-fee schedules discounted according to a patient's ability to pay for care. Guidance on fees and on both nominal- and sliding-fee schedules appear in this unit.
  • Patient scheduling: Efficient patient scheduling permits health professionals to work at maximum productivity. Poor scheduling creates unproductive down time. Unit 4 discusses scheduling policies.
  • Broken appointments: Broken appointments (patient doesn't show for appointment or call in advance to cancel) tend to be more common for the patient population targeted by safety dental net clinics than for the patient population targeted by private dental offices. Unit 4 provides strategies for minimizing the impact of broken appointments.
  • Efficiency of the oral health team: A dentist cannot effectively work alone. In fact, experience has shown that a dentist is most efficient with the right mix of dental assistants and dental chairs, as discussed in Unit 2.
  • Billing and collections system: A billing and collections system that captures revenue for all oral health services provided to patients is required to maximize patient-care revenue. Furthermore, the clinic wants to minimize bad debt from unpaid charges. Unit 4 discusses billing and collections systems.
  • Payer mix: Since different payers reimburse the clinic at different levels, patient-care revenue will be influenced by the relative proportion of patients in each payer category. See the discussion on influencing payer mix earlier on this page and in this section.