Advertising Disclaimer »

Discover Pediatric Collections on COVID-19 and Racism and Its Effects on Pediatric Health

Article

Fully Capitated Payment Breakeven Rate for a Mid-Size Pediatric Practice

Steven A. Farmer, Joel Shalowitz, Meaghan George, Frank McStay, Kavita Patel, James Perrin, Ali Moghtaderi and Mark McClellan
Pediatrics August 2016, 138 (2) e20154367; DOI: https://doi.org/10.1542/peds.2015-4367
Download PDF

Abstract

BACKGROUND AND OBJECTIVES: Payers are implementing alternative payment models that attempt to align payment with high-value care. This study calculates the breakeven capitated payment rate for a midsize pediatric practice and explores how several different staffing scenarios affect the rate.

METHODS: We supplemented a literature review and data from >200 practices with interviews of practice administrators, physicians, and payers to construct an income statement for a hypothetical, independent, midsize pediatric practice in fee-for-service. The practice was transitioned to full capitation to calculate the breakeven capitated rate, holding all practice parameters constant. Panel size, overhead, physician salary, and staffing ratios were varied to assess their impact on the breakeven per-member per-month (PMPM) rate. Finally, payment rates from an existing health plan were applied to the practice.

RESULTS: The calculated breakeven PMPM was $24.10. When an economic simulation allowed core practice parameters to vary across a broad range, 80% of practices broke even with a PMPM of $35.00. The breakeven PMPM increased by 12% ($3.00) when the staffing ratio increased by 25% and increased by 23% ($5.50) when the staffing ratio increased by 38%. The practice was viable, even with primary care medical home staffing ratios, when rates from a real-world payer were applied.

CONCLUSIONS: Practices are more likely to succeed in capitated models if pediatricians understand how these models alter practice finances. Staffing changes that are common in patient-centered medical home models increased the breakeven capitated rate. The degree to which team-based care will increase panel size and offset increased cost is unknown.

  • Abbreviations:
    APM —
    alternative payment model
    APP —
    advanced practice provider
    CDPHP —
    Capital District Physicians Health Plan
    EPCI —
    Enhanced Primary Care Initiative
    FFS —
    fee-for-service
    FTE —
    full-time equivalent
    PCMH —
    primary care medical home
    PMPM —
    per-member per-month

    • What’s Known on This Subject:

    Payers are introducing alternative payment models nationwide in the hopes of improving quality and reducing costs. Although previous studies have evaluated their effects on spending and outcomes, few have explored how they affect practice finances.

    What This Study Adds:

    This study calculates the breakeven capitated payment rate for a midsize pediatric practice, provides a tool for practices to estimate their own breakeven rates, and models the relationship between attributed patient volume and payment rates under several practice scenarios.

    Health care spending continues to grow at an unsustainable rate and is increasingly unaffordable for many Americans.1,2 The fee-for-service (FFS) payment method that dominates health care payments contributes to inefficiency by rewarding volume and ignoring quality.3⇓⇓⇓–7 To address these deficiencies, public and private payers are experimenting with alternative payment models (APMs) that attempt to align payments with improved value. More than 21 million lives are covered through primary care medical homes (PCMHs), where FFS payments are increasingly augmented with partially capitated per-member per-month (PMPM) payments.8 As of 2014, >40% of all commercial in-network payments are value based.9

    Pediatricians must understand APMs and their implications for practice financials. These payment models can be confusing, they often lack transparency, and there is limited evidence to guide providers in understanding them.10 To address this knowledge gap, we present a simplified financial model, which converts a hypothetical, independent, midsize, general pediatric practice from FFS to full capitation. The analysis calculates the aggregated capitated rate necessary for the practice to break even compared with FFS, provides a financial analysis tool for practices, and investigates the relationship between the breakeven capitated rate and variations in practice parameters including panel size, overhead, physician salary, and staffing ratio. Finally, mean payment rates from a real-world payer are applied to assess practice viability.

    Methods

    Model and Data Sources

    This analysis constructs income statements for a practice with 6 clinicians, including 5 full-time equivalent (FTE) physicians and 1 FTE advanced practice provider (APP); FTEs may be allocated between multiple part-time providers. The outcome variable of interest is the breakeven comprehensive capitated rate inclusive of shared savings and quality incentive payments.

    The income statement was developed after interviews with 3 public and private payers and 2 practice administrators from midsize practices. Multiple data sources were used to establish model assumptions, including published medical literature, the Bureau of Labor Statistics, the Centers for Disease Control and Prevention, the Medical Group Management Association, surveys from the American Academy of Pediatrics and American Academy of Family Physicians, and proprietary data from 200 independent pediatrics practices across 40 states. As a robustness check, the final model was reviewed by 2 additional practice administrators, 1 commercial payer, and a pediatric practice consultant.

    For simplicity, the model imposes a number of constraints. First, it makes a direct conversion from FFS to full capitation, inclusive of quality and cost incentive payments. Second, it shifts all patients in the practice to capitated payments simultaneously. Third, the capitated rate holds the panel size constant throughout the year and includes only responsibility for basic point-of-care testing, such as rapid strep, hemoglobin, and urinalysis. Fourth, any revenues from hospital consultations or circumcisions are excluded. Finally, the model simulates a 50/50 payer mix between Medicaid and commercial payers.11,12

    Expense and Revenues Under FFS and Capitation

    Published panel sizes vary widely, depending on practice style and the age distribution of the panel.13⇓⇓⇓⇓–18 The model assumes a panel size of 1700 and an average of 3.24 visits per patient per year.15,19,20 Table 1 summarizes the core model assumptions, along with the range for each variable identified from multiple sources.

    View this table:
    TABLE 1

    List of Core Model Assumptions and Practice Parameters

    Total expenses are often reported as 60% of actual revenue in pediatrics and family medicine.14,21⇓⇓–24 To increase transparency and generalizability, the model separates staff salary and fringe benefit expenses from other overhead. Pediatricians’ salaries vary with differences in practice ownership, payer mix, productivity, and geographic location.14,25,26 The model uses the Bureau of Labor Statistics national median salary of $180 000.25 Practice administrator salaries varied for similar reasons, and the model uses a salary of $92 000.27,28 The median salaries for APPs and registered nurses are consistently reported at $95 000 and $65 000, respectively.29⇓–31 Median salaries for administrative and clinical support staff vary based on duties but converge ∼$34 000.32⇓⇓–35 Fringe costs as a percentage of staff salary are 15% for clinicians and the practice administrator and 30% for support staff.14,36 The model assumes a support staff to physician ratio of 3.2.14,20,37 Overhead excluding staff expenses was set at 30% of revenue, resulting in total overhead of 62% of revenue.

    Overhead costs excluding staff expenses are calculated as a percentage of total revenue in the capitated model. The model increases nonstaff overhead costs from 30% to 35% to allow for additional expenses such as electronic health record upgrades and reinsurance.38⇓–40 Fewer resources may be needed for billing-related administrative functions in capitated environments, but staff must still confirm valid insurance coverage, and detailed quality reporting is required. Because total expenses are calculated as a percentage of payments collected (not receivable) in the FFS model, the total expenses account for a similar proportion of revenues in the capitated model (63%).

    Vaccines are a large expense for practices. Given the Centers for Disease Control and Prevention vaccine schedule for children 0 to 18 years of age and current vaccine prices, average vaccination cost is ∼$135 per patient per year.41,42 Practices typically break even or gain small profits from vaccinations billed to commercial payers, whereas the opposite is true for those billed to Medicaid.43 Because the modeled practice is a 50/50 payer mix, vaccines are excluded from both the FFS and capitation models.

    Copayments may contribute meaningfully to practice revenues in both FFS and capitation. The model incorporates an average patient copayment of $8. This amount is calculated by multiplying the average commercial copays ($23) by the proportion of commercial patients (50%) and the likelihood that commercial plan requires copayments (66%).44 Many states allow (or will soon allow) nominal copayments for Medicaid beneficiaries, but these have been excluded from the model.45,46

    In the FFS model, practice revenues are tied to physician and APP encounters. Practice revenues are calculated by multiplying the average number of visits per day, the number of providers, the number of clinical days per year, and the average payment per encounter.47 The hypothetical practice assumes 25 patients per day per provider, 220 clinical days annually, and $100.00 average payment per visit.14,48⇓–50 APPs may independently bill at 85% of physician fees, although APP roles may vary by practice.51 The FFS model accounts for rejected claims, no-shows, and uncompensated visits by writing off 10% of expected revenue. The model includes a 5% practice margin in both the FFS and capitated scenarios so that the practice is able to build and maintain financial reserves for upgrades or unexpected expenses.

    In the capitated model, practice revenue is driven by attributed panel size and the average capitated payment. Instead of billing payers for individual patient encounters, capitated practices receive a risk adjusted base PMPM payment for each attributed patient. Particularly in pediatrics, the capitated rate should account for the age of covered patients.52 The model excludes vaccination, but if included in capitated payments, rates must be substantially higher and must allow for vaccine price increases, which occur annually if not more frequently.

    Providers typically receive incentives for performance relative to quality and cost benchmarks. Quality and cost bonuses are paid when practices reach predetermined performance thresholds and as a percentage of spending compared with targets, respectively. For transparency, our model converts quality and shared savings payments into PMPMs. Incentive payments and copayments are added to the base PMPM to calculate total revenue.

    In capitation: Net Income = Patient Co-payments + Capitation Base Rate + Utilization Incentives + Quality − Operating Expenses.

    Sensitivity Analysis

    Practices vary widely in organization and style. Our model presents an “average” practice, but several core assumptions may vary significantly between practices, including physician salary, panel size, and overhead. As a robustness check, an economic simulation was constructed where physician salary, panel size, and overhead less staff expenses were allowed to vary across the range of values in Table 1. Each simulation generated 500 different practices. The model was iterated 50 times to generate a total of 25 000 practices.

    Practice Transformation

    Because revenues are not tied to face-to-face physician or APP encounters, capitation models allow providers greater clinical autonomy than FFS, and all practice staff may contribute to patient care at the level to which they are legally entitled.13,37,53⇓⇓–56 We modified the practice’s staffing ratios to reflect 2 published PCMH transformations to assess its effect on the PMPM.37,54 In 1 example, an additional APP mental health provider, 2.5 nurses, 1.5 clinical support staff, 0.5 administrative support staff, and 0.5 of a practice administrator were added. These additions increased the staffing ratio by 37% (3.2 to 4.4). In a second example, 2 nurses and 2 clinical support staff were added. These additions increase the staffing ratio by 25% (3.2 to 4.0).

    Capitated Rates for a Real-World Payer

    For illustrative purposes, we obtained capitated rates and program information for Capital District Physicians Health Plan (CDPHP), a health plan in upstate New York that serves nearly a half million commercial and Medicaid members.57 CDPHP provided data from 2013, including the base capitated rate, quality incentives, and shared savings incentives payments. We applied Medicaid, commercial, and 50:50 blended rates to our model with and without staffing changes, to assess the financial impact on our hypothetical practice.

    Results

    In Fig 1, the left-side income statement is FFS, and the right side is capitation. With attributed patients, staffing, and salaries held constant, the minimum breakeven aggregated capitated rate for the hypothetical, independent, midsize practice was $24.10. This number may be reached in several ways. For example, a base PMPM rate of $20.60 could be supplemented with $1.50 PMPM quality incentive and a $2.00 PMPM cost incentive. Figure 2 illustrates the relationship between the panel size and the breakeven aggregated capitated payment rate. Practices that receive a PMPM above the line (in the green) generate higher revenues than the FFS scenario, whereas practices that receive a PMPM below the line (in the red) generate lower revenues than the FFS scenario.

    FIGURE 1
    FIGURE 1

    Simplified financial model.

    FIGURE 2
    FIGURE 2

    Relationship between PMPM rates, attributed patient population, and profitability. Breakeven is defined as the rate at which the practice is as profitable as it was under FFS. Without staffing or other operational changes, the model predicts a $24.10 PMPM; a lower PMPM would result in operational losses, and a higher PMPM would lead to increased revenues.

    Figure 3 illustrates the findings of the sensitivity analysis for 500 practices. The figure shows the impact of random combinations of model inputs across the range of assumptions drawn from Table 1 on the breakeven aggregated capitated rate. In the simulation, 80% of practices would break even at an aggregated capitated rate between $16.12 and $35.00.

    FIGURE 3
    FIGURE 3

    Sensitivity analysis of breakeven aggregated capitation rates with varied practice assumptions. An economic simulation allowed model assumptions to vary across the range of values shown in Table 1. These values were drawn from multiple sources.

    With physician and staff salaries again held constant, Fig 4 illustrates the relationship between breakeven aggregated capitated rates and the 2 PCMH staffing transformations described above. The blue line represents the breakeven aggregated PMPM with no staffing adjustments. The red line reflects the first staffing transformation (38% staffing increase), and the green line reflects the second practice transformation (25% staffing increase).

    FIGURE 4
    FIGURE 4

    Relationship between the breakeven aggregated capitated rate, panel size, and PCMH staffing variations. As staffing ratios change, the breakeven PMPM rate will also vary. This figure shows the impact of 2 staffing changes on the breakeven PMPM. The first (red) adds an APP mental health provider, 2.5 nurses, 1.5 clinical support staff, .5 administrative support staff, and .5 of a practice administrator were added. The second (green) adds 2 nurses and 2 clinical support staff. To the extent that staffing changes increase efficiency, the cost of additional staff may be offset by increased panel size.

    Table 2 presents CDPHP’s mean capitated rates for both its Medicaid and commercial populations, and program details including performance metrics and covered services. CDPHP began transitioning practices to full capitation in 2008 as part of its Enhanced Primary Care Initiative (EPCI).57 Many of CDPHP’s EPCI participating practices are also certified PCMHs. As in our model, vaccines are paid separately on an FFS basis in the CDPHP model. Age-, sex-, and risk-adjusted capitated rates range from $13 to $65 and depend in part on whether the patient is in a commercial or Medicaid plan. The maximum incentive payment available is $5.32, but on average, practices earn 33% ($1.77) of the potential maximum.

    View this table:
    TABLE 2

    CDPHP Enhanced Primary Care Capitated Payment Rates for Pediatric Patients

    Holding all assumptions constant in the FFS and capitation financial statements, the model applies the mean capitated payments of $22 (base Medicaid PMPM rate) and $36 (base commercial PMPM rate) plus $1.77 PMPM incentive payments (all patients). Our model resulted in a 4% and 25% margin in the Medicaid and commercial plans, respectively. A practice that blended 50% Medicaid and 50% commercial patients resulted in a base capitation rate of ∼$29. After the $1.77 incentive payment, the blended practice earned a 17% margin; this rate was sufficient to support either of the 2 PCMH staffing transformations.

    Discussion

    Given unsustainable growth in US health spending, public and commercial payers are transitioning to APMs that are intended to better align payment with value. Although many physicians have hesitated to participate in APMs, future participation in new payment models will probably be unavoidable. Thirty percent of Medicare payments are already tied to APMs.58 Pediatricians need to understand the implications of emerging payment models for practice organization and finances. Our model calculates the aggregated capitated rate where a pediatric practice would break even relative to FFS across a range of panel sizes, describes how that point would differ between practices, and illustrates the impact of staffing changes. Mean payment rates from a real-world capitated payment model, CDPHP, are applied as an illustration.

    To our knowledge, no study has examined the practice financials of a transition from FFS to capitation in pediatrics. Kuo et al59 recently estimated primary care expenditures by Medicaid patients at $19 PMPM, 25% below our breakeven capitated rate. However, most commercial plans reimburse at higher rates than Medicaid plans, and our breakeven rate reflects the average of all patients in the practice.60

    Practice style and organization vary in important ways. The sensitivity analysis presented in Fig 3 demonstrates a wide variation in breakeven rates based on these differences. The income statement shown in Fig 1 may be adapted to calculate the breakeven capitated rate for specific practice circumstances. Even so, most practices will need technical assistance from payers to identify the number of attributed patients (panel size), assess performance on utilization and quality metrics, and project revenues.61 Capitation model designs also differ, as do eligibility and participation requirements; practices should pay careful attention to program terms when assessing the financial impact of participation. If vaccinations are included in the capitated payments, a new calculation is needed.

    PCMH models are often paid through capitation at rates intended to support a team-based care approach that may lower costs and improve outcomes.8,62,63 In these models, physicians may elect to spend more time with the most complex patients while delegating simple visits to a broader team. For example, in the case of a pediatric patient with asthma, simple but important tasks such as teaching nebulizer technique and reviewing asthma action plans may be performed by nurses or medical assistants.64,65 Some clinicians may work with patients by phone, e-mail, Web chat, or even video call, potentially improving efficiency, access, and patient satisfaction.49,66 However, not all PCMH models perform better than traditional primary care models. Studies of the effects of APMs and APM-supported delivery reforms on health care expenditures and patient outcomes find mixed effects.67⇓⇓⇓⇓⇓–73

    PCMH practices often change staffing ratios to optimize the care team and extend services. The optimal staffing mix should be driven by practice and community needs.13,74⇓–76 Many of these staffing changes will increase the breakeven capitated rate. Our findings are consistent with a recent review that found that PCMH staffing changes increase the breakeven capitated rate by ∼$5.00 PMPM.54 Our first staffing model resulted in an increase of $5.50 (23%), and our second staffing model resulted in an increase of $3.00 (12%). Under capitation, practices may increase revenue by increasing panel size, increasing quality incentives, or increasing utilization incentives. There is therefore a dynamic relationship between staffing choices, practice efficiency, and the breakeven capitation rate. The mix of providers and services that optimizes efficiency and performance remains undefined.77

    This study has several limitations. We modeled a midsize, independent, general pediatric practice, but many other practice configurations are possible. Practices differ in the number and type of providers, support staff ratios, overhead costs, and panel sizes. The model does not account for varying ratios of new to established patient visits or the time and payment differences between well and sick visits.

    We based our practice on average data drawn from >200 pediatric practices distributed across a broad geographic area, the medical literature, and published surveys. Although our model illustrates important considerations in transitioning to capitation, our sensitivity analysis demonstrates wide variation in the breakeven capitation rate when assumptions are varied. Individual practices should use the income statement as a guide to calculate the breakeven capitated rate for their specific circumstances. Lastly, the assumption that all patients simultaneously transition from FFS to capitation is not typical, and most practices will participate in several payment models simultaneously.

    Conclusions

    Practices are more likely to succeed financially in APMs, such as capitation, if they understand how these models alter practice finances and how to calculate the breakeven rate and if they take advantage of the added flexibility to improve efficiency and value. Additional work should focus on analyzing practices in blended payment models and the relationship between differing staffing ratios, patient panel size, and patient outcomes.

    Acknowledgments

    The authors thank CDPHP’s Bruce Nash, Eileen Wood, and Ali Skinner for providing us with data, model support, and invaluable editorial comments. We also thank Cheryl Arnold, Theresa Cleveland, Sunnah Kim, and Chip Hart for their helpful comments on this manuscript.

    Footnotes

      • Accepted May 18, 2016.
    • Address correspondence to Steven A. Farmer, MD, PhD, Center for Healthcare Innovation and Policy Research, George Washington University, 2100 Pennsylvania Ave, Office 316, Washington, DC 20037. E-mail: safarmer{at}email.gwu.edu

    • FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.

    • FUNDING: Supported by the Merkin Family Foundation.

    • POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.

    References

    1. ↵
      1. Centers for Medicare & Medicaid Services
      . National Health Expenditures 2013 Highlights. Available at: www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/downloads/highlights.pdf. Accessed April 7, 2015
    2. ↵
      1. Roehrig C
      . A Brief History of Health Spending Since 1965. Available at: http://healthaffairs.org/blog/2011/09/19/a-brief-history-of-health-spending-since-1965/. Accessed April 7, 2015
    3. ↵
      1. Bureau of Labor Statistics
      . Features and Associated Costs of Fee-for-Service Medical Plans. Available at: www.bls.gov/opub/btn/archive/program-perspectives-on-fee-for-service-plans-pdf.pdf. Accessed October 2010
    4. ↵
      1. Berenson RA,
      2. Rich EC
      . US approaches to physician payment: the deconstruction of primary care. J Gen Intern Med. 2010;25(6):613–618pmid:20467910
      OpenUrlCrossRefPubMed
    5. ↵
      1. Hadley J,
      2. Reschovsky J,
      3. Corey C,
      4. Zuckerman S
      . Medicare fees and the volume of physicians’ services. Inquiry. 2009-2010;46(4):372–390pmid:20184165
      OpenUrlPubMed
    6. ↵
      1. Miller HD
      . From volume to value: better ways to pay for health care. Health Aff (Millwood). 2009;28(5):1418–1428pmid:19738259
      OpenUrlAbstract/FREE Full Text
    7. ↵
      1. Scamperle K
      . The fee-for-service shift to bundled payments: financial considerations for hospitals. J Health Care Finance. 2013;39(4):55–67pmid:24003762
      OpenUrlPubMed
    8. ↵
      1. Edwards ST,
      2. Bitton A,
      3. Hong J,
      4. Landon BE
      . Patient-centered medical home initiatives expanded in 2009–13: providers, patients, and payment incentives increased. Health Aff (Millwood). 2014;33(10):1823–1831pmid:25288429
      OpenUrlAbstract/FREE Full Text
    9. ↵
      1. Catalyst for Payment Reform
      . National Scorecard for Payment Reform. Available at: http://www.catalyzepaymentreform.org/images/documents/nationalscorecard2014.pdf. Accessed June 16, 2016
    10. ↵
      1. Ryan AM,
      2. Shortell SM,
      3. Ramsay PP,
      4. Casalino LP
      . Salary and quality compensation for physician practices participating in accountable care organizations. Ann Fam Med. 2015;13(4):321–324pmid:26195675
      OpenUrlAbstract/FREE Full Text
    11. ↵
      1. American Academy of Pediatricians; Division of Health Services Research
      . Pediatricians' Practice and Personal Characteristics: US only, 2015. Table 6: Estimated Percent of Patients by Health Insurance Source - All Pediatricians (Excluding Residents). Available at: https://www.aap.org/en-us/PublishingImages/surveys_periodic_2015_practice_char_table6.png. Accessed June 16, 2016
    12. ↵
      1. Mirel LB,
      2. Carper K
      . Trends in Health Care Expenditures for Children Under Age 18: 2001, 2006, and 2011. Statistical Brief #428. Rockville, MD: Agency for Healthcare Research and Quality, 2014.
    13. ↵
      1. Altschuler J,
      2. Margolius D,
      3. Bodenheimer T,
      4. Grumbach K
      . Estimating a reasonable patient panel size for primary care physicians with team-based task delegation. Ann Fam Med. 2012;10(5):396–400pmid:22966102
      OpenUrlAbstract/FREE Full Text
    14. ↵
      1. Medical Group Management Association (MGMA)
      . MGMA DataDive 2014: Cost and Revenue Module. Available at: www.mgma.com/store/surveys-and-benchmarking/online/datadive-2014-cost-and-revenue-module
    15. ↵
      1. Murray M,
      2. Davies M,
      3. Boushon B
      . Panel size: how many patients can one doctor manage? Fam Pract Manag. 2007;14(4):44–51pmid:17458336
      OpenUrlPubMed
    16. ↵
      1. Balasubramanian H,
      2. Banerjee R,
      3. Denton B,
      4. Naessens J,
      5. Stahl J
      . Improving clinical access and continuity through physician panel redesign. J Gen Intern Med. 2010;25(10):1109–1115pmid:20549379
      OpenUrlCrossRefPubMed
    17. ↵
      1. Agency for Healthcare Research and Quality
      . Module 20. Facilitating Panel Management. 2013. Available at: www.ahrq.gov/professionals/prevention-chronic-care/improve/system/pfhandbook/mod20.html. Accessed March 10, 2016
    18. ↵
      1. Crane M
      . Are you too busy to accept new patients? Why closing your panel is a bad idea, and how to find the time and space to squeeze in new patients. Med Econ. 2013;90(24):51–54
      OpenUrl
    19. ↵
      1. Ashman J,
      2. Hing E,
      3. Talwalker A
      . Variation in physician office visit rates by patient characteristics and state, 2012. In: US Department of Health and Human Services, ed. Vol Data Brief No. 212: Centers for Disease Control and Prevention, National Center for Health Statistics; 2015
    20. ↵
      1. AAP Department of Practice
      . Median practice size, patient caseloads highlighted in AAP report. AAP News. 2009;30(6)
    21. ↵
      1. Forrest BR
      . Breaking even on 4 visits per day. Fam Pract Manag. 2007;14(6):19–24pmid:17598630
      OpenUrlPubMed
    22. ↵
      1. Keegan DW
      . Five key benchmarks that could make or break your practice. Medscape Business of Medicine. Available at: www.medscape.com/viewarticle/765783. Accessed June 15, 2012
    23. ↵
    24. ↵
      1. Tinsley R
      . The 12-step way to reduce practice expenses: part 1, staffing efficiencies. Fam Pract Manag. 2010;17(2):38–43pmid:20222637
      OpenUrlPubMed
    25. ↵
      1. Bureau of Labor Statistics
      . 29-1065 Pediatricians, General. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    26. ↵
      1. Medscape
      . Medscape Pediatrician Compensation Report 2014. Available at: www.medscape.com/features/slideshow/compensation/2014/pediatrics?src=emailthis#2. Accessed April 15, 2014
    27. ↵
      1. Indeed
      . Practice Administrator Salary. 2016. Available at: www.indeed.com/salary/Practice-Administrator.html
    28. ↵
      1. Bureau of Labor Statistics
      . 11-9111 Medical and Health Services Managers. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    29. ↵
      1. Bureau of Labor Statistics
      . 29-1111 Registered Nurses. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2012
    30. ↵
      1. Bureau of Labor Statistics
      . 29-1171 Nurse Practitioners. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    31. ↵
      1. Bureau of Labor Statistics
      . 29-1071 Physician Assistants. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    32. ↵
      1. Bureau of Labor Statistics
      . 43-6013 Medical Secretaries. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    33. ↵
      1. Bureau of Labor Statistics
      . 43-3021 Billing and Posting Clerks. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    34. ↵
      1. Bureau of Labor Statistics
      . 29-2071 Medical Records and Health Information Technicians. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    35. ↵
      1. Bureau of Labor Statistics
      . 43-4171 Receptionists and Information Clerks. Occupational Employment Statistics. Washington, DC: US Department of Labor; 2015
    36. ↵
      1. Bureau of Labor Statistics
      . Employer Costs for Employee Compensation. Washington, DC: US Department of Labor; 2016
    37. ↵
      1. Peikes DN,
      2. Reid RJ,
      3. Day TJ, et al
      . Staffing patterns of primary care practices in the comprehensive primary care initiative. Ann Fam Med. 2014;12(2):142–149pmid:24615310
      OpenUrlAbstract/FREE Full Text
    38. ↵
    39. ↵
      1. Martsolf GR,
      2. Kandrack R,
      3. Gabbay RA,
      4. Friedberg MW
      . Cost of transformation among primary care practices participating in a medical home pilot [published online ahead of print December 29, 2015]. J Gen Intern Med. 2015pmid:26714484
      OpenUrlPubMed
    40. ↵
      1. Nocon RS,
      2. Sharma R,
      3. Birnberg JM,
      4. Ngo-Metzger Q,
      5. Lee SM,
      6. Chin MH
      . Association between patient-centered medical home rating and operating cost at federally funded health centers. JAMA. 2012;308(1):60–66pmid:22729481
      OpenUrlCrossRefPubMed
    41. ↵
      1. Centers for Disease Control and Prevention
      . Vaccines for Children Program (VFC). CDC Vaccine Price List. Available at: www.cdc.gov/vaccines/programs/vfc/awardees/vaccine-management/price-list/. Accessed September 14, 2015
    42. ↵
      1. Centers for Disease Control and Prevention
      . Figure 1. Recommended Immunization Schedule for Persons Aged 0 Through 18 Years: United States, 2015. Available at: www.cdc.gov/vaccines/schedules/downloads/child/0-18yrs-schedule.pdf
    43. ↵
      1. Coleman MS,
      2. Lindley MC,
      3. Ekong J,
      4. Rodewald L
      . Net financial gain or loss from vaccination in pediatric medical practices. Pediatrics. 2009;124(6 suppl 5):S472–S491
      OpenUrlAbstract/FREE Full Text
    44. ↵
      1. Sommers JP,
      2. Crimmel BL
      . Co-pays, Deductibles, and Coinsurance Percentages for Employer Sponsored Health Insurance in the Private Sector, by Firm Size Classification, 2006. Statistical Brief #209. Rockville, MD: Agency for Healthcare Research and Quality; 2008
    45. ↵
      1. Selden TM,
      2. Kenney GM,
      3. Pantell MS,
      4. Ruhter J
      . Cost sharing in Medicaid and CHIP: how does it affect out-of-pocket spending? Health Aff (Millwood). 2009;28(4):w607–w619pmid:19491137
      OpenUrlAbstract/FREE Full Text
    46. ↵
      1. Smith VK,
      2. Gifford K,
      3. Ellis E,
      4. Rudowitz R,
      5. Snyder L,
      6. Hinton E
      . Medicaid Reforms to Expand Coverage, Control Costs, and Improve Care: Results From 50-State Medicaid Budget Survey for State Fiscal Year 2015 and 2016. Menlo Park, CA: The Kaiser Family Foundation, and National Association of Medicaid Directors; 2015
    47. ↵
      1. Miller HD; Center for Healthcare Quality and Payment Reform
      . Ten Barriers to Healthcare Payment Reform and How to Overcome Them. Available at: www.chqpr.org/downloads/OvercomingBarrierstoPaymentReform.pdf. Accessed December 2012
    48. ↵
      1. PedSource
      . Revenue per Visit. Available at: www.pedsource.com/library/revenue-per-visit. Accessed April 7, 2015
    49. ↵
      1. American Academy of Pediatrics
      . Practice Transformation. Available at: https://www.aap.org/en-us/professional-resources/practice-support/Pages/Practice-Support.aspx. Accessed April 7, 2015
    50. ↵
      1. AAFP
      . Table 5: Average Number of Weeks Family Physicians Practiced in the Last Twelve Months (as of December 2014). Leawood, KS: American Academy of Family Physicians; 2014
    51. ↵
      1. Nicoletti B
      . How to bill for services performed by nonphysician practitioners. Fam Pract Manag. 2006;13(5):45–46, 48pmid:16736904
      OpenUrlPubMed
    52. ↵
      1. Chung S,
      2. Eaton LJ,
      3. Luft HS
      . Standardizing primary care physician panels: is age and sex good enough? Am J Manag Care. 2012;18(7):e262–e268pmid:22823555
      OpenUrlPubMed
    53. ↵
      1. Robert Wood Johnson Foundation
      . Four Innovative Strategies to Help Providers Succeed Under Payment Reform. Available at: www.academyhealth.org/files/HCFO/Innovative%20Strategies%20Under%20Payment%20Reform%2008-2014.pdf. Accessed August 2014
    54. ↵
      1. Patel MS,
      2. Arron MJ,
      3. Sinsky TA, et al
      . Estimating the staffing infrastructure for a patient-centered medical home. Am J Manag Care. 2013;19(6):509–516pmid:23844711
      OpenUrlPubMed
    55. ↵
      1. Bitton A,
      2. Schwartz GR,
      3. Stewart EE, et al
      . Off the hamster wheel? Qualitative evaluation of a payment-linked patient-centered medical home (PCMH) pilot. Milbank Q. 2012;90(3):484–515pmid:22985279
      OpenUrlCrossRefPubMed
    56. ↵
      1. Marlowe DP,
      2. Manusov EG,
      3. Teasley D
      . A team-building model for team-based care. Fam Pract Manag. 2012;19(6):19–22pmid:23317128
      OpenUrlPubMed
    57. ↵
      1. Nash B
      . Enhanced Primary Care: The CDPHP Medical Home. Paper presented at: Patient-Centered Medical Home: Research Results Mixed, Experience Yields Optimism 2013
    58. ↵
      1. Centers for Medicare and Medicaid Services
      . Better Care. Smarter Spending. Healthier People: Improving Quality and Paying for What Works [press release]. March 3, 2016
    59. ↵
      1. Kuo DZ,
      2. Hall M,
      3. Agrawal R, et al
      . Comparison of health care spending and utilization among children with Medicaid insurance. Pediatrics. 2015;136(6). Available at: www.pediatrics.org/cgi/content/full/136/6/e1521pmid:26574588
      OpenUrlAbstract/FREE Full Text
    60. ↵
      1. Zuckerman S,
      2. Goin D
      . How Much Will Medicaid Physician Fees for Primary Care Rise in 2013? Evidence From a 2012 Survey of Medicaid Physician Fees. Kaiser Family Foundation. Washington, DC: The Urban Institute; 2012
    61. ↵
      1. Golden W,
      2. Thompson JW,
      3. Olson S, et al.
      Patient-Centered Medical Homes in Arkansas. Health Aff Blog. 2014.
    62. ↵
      1. Friedberg MW,
      2. Rosenthal MB,
      3. Werner RM,
      4. Volpp KG,
      5. Schneider EC
      . Effects of a medical home and shared savings intervention on quality and utilization of care. JAMA Intern Med. 2015;175(8):1362–1368pmid:26030123
      OpenUrlCrossRefPubMed
    63. ↵
      1. Kern LM,
      2. Edwards A,
      3. Kaushal R
      . The patient-centered medical home and associations with health care quality and utilization: a 5-year cohort study. Ann Intern Med. 2016;164(6):395–405pmid:26882534
      OpenUrlCrossRefPubMed
    64. ↵
      1. Postma J,
      2. Karr C,
      3. Kieckhefer G
      . Community health workers and environmental interventions for children with asthma: a systematic review. J Asthma. 2009;46(6):564–576pmid:19657896
      OpenUrlCrossRefPubMed
    65. ↵
      1. Woods ER,
      2. Bhaumik U,
      3. Sommer SJ, et al
      . Community asthma initiative: evaluation of a quality improvement program for comprehensive asthma care. Pediatrics. 2012;129(3):465–472pmid:22351890
      OpenUrlAbstract/FREE Full Text
    66. ↵
      1. Wagner EH,
      2. Coleman K,
      3. Reid RJ,
      4. Phillips K,
      5. Sugarman JR
      . Guiding Transformation: How Medical Practices Can Become Patient-Centered Medical Homes. New York, NY: The Commonwealth Fund; 2012
    67. ↵
      1. Sorbero ME,
      2. Damberg CL,
      3. Shaw R, et al
      . Assessment of Pay-for-Performance Options for Medicare Physician Services: Final Report. Santa Monica, CA: RAND Corporation; 2010
    68. ↵
      1. Rosenthal MB,
      2. Frank RG,
      3. Li Z,
      4. Epstein AM
      . Early experience with pay-for-performance: from concept to practice. JAMA. 2005;294(14):1788–1793pmid:16219882
      OpenUrlCrossRefPubMed
    69. ↵
      1. Mechanic RE,
      2. Altman SH
      . Payment reform options: episode payment is a good place to start. Health Aff (Millwood). 2009;28(2):w262–w271pmid:19174388
      OpenUrlAbstract/FREE Full Text
    70. ↵
      1. Hussey PS,
      2. Mulcahy AW,
      3. Schnyer C,
      4. Schneider EC
      . Bundled Payment: Effects on Health Care Spending and Quality. Rockville, MD: Agency for Healthcare Research and Quality; 2012
    71. ↵
      1. Balkrishnan R,
      2. Hall MA,
      3. Mehrabi D,
      4. Chen GJ,
      5. Feldman SR,
      6. Fleischer AB Jr
      . Capitation payment, length of visit, and preventive services: evidence from a national sample of outpatient physicians. Am J Manag Care. 2002;8(4):332–340pmid:11950128
      OpenUrlPubMed
    72. ↵
      1. US Government Accountability Office
      . Medicare: Results From the First Two Years of the Pioneer Accountable Care Organization Model. Washington, DC: US GAO;2015
    73. ↵
      1. McClellan M,
      2. Kocot SL,
      3. White R
      . Medicare ACOs Continue to Show Care Improvements - And More Savings Are Possible. Health Affairs Blog. Available at: http://healthaffairs.org/blog/2015/11/04/medicare-acos-continue-to-show-care-improvements-and-more-savings-are-possible/. Accessed June 16, 2016
    74. ↵
      1. Peterson Center on Healthcare. Standford Medicine Clinical Excellence Research Center
      . America’s Most Valuable Care. Available at: http://petersonhealthcare.org/sites/default/files/images/media_library/Peterson%20Center%20on%20Healthcare_Stanford%20Overview.pdf. Accessed April 7, 2015
    75. ↵
      1. Adler-Milstein J,
      2. Huckman RS
      . The impact of electronic health record use on physician productivity. Am J Manag Care. 2013;19(11 spec no. 10):SP345–SP352
      OpenUrlPubMed
    76. ↵
      1. Hopkins K,
      2. Sinsky CA
      . Team-based care: saving time and improving efficiency. Fam Pract Manag. 2014;21(6):23–29pmid:25403048
      OpenUrlPubMed
    77. ↵
      1. Friedberg MW,
      2. Schneider EC,
      3. Rosenthal MB,
      4. Volpp KG,
      5. Werner RM
      . Association between participation in a multipayer medical home intervention and changes in quality, utilization, and costs of care. JAMA. 2014;311(8):815–825pmid:24570245
      OpenUrlCrossRefPubMed
    Back to top

    In this issue

    Pediatrics
    Vol. 138, Issue 2
    1 Aug 2016
    View this article with LENS
    Email Article
    Request Permissions
    Article Alerts
    Citation Tools
    Fully Capitated Payment Breakeven Rate for a Mid-Size Pediatric Practice
    Steven A. Farmer, Joel Shalowitz, Meaghan George, Frank McStay, Kavita Patel, James Perrin, Ali Moghtaderi, Mark McClellan
    Pediatrics Aug 2016, 138 (2) e20154367; DOI: 10.1542/peds.2015-4367
    del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
    Print
    Download PDF
    Insight Alerts

    Jump to section

    Subjects