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CPT coding patterns at nurse-manned health centers: data from a national survey.

IN TODAY'S DYNAMIC HEALTH care environment of limited resources and greater demands from payers and affiliated universities for efficiency while providing high-quality care, nurse-managed health centers (NMHCs) must monitor internal data and benchmark their performance against comparable external data. Traditionally, NMHCs provide a unique model of primary care emphasizing health promotion and disease prevention with a family and community-centered focus. Many NMHCs are safety net providers serving populations that might otherwise have little to no health care service (Pohl, Vonderheid, Barkanskas, & Nagelkerk, 2004). In addition, NMHCs serve as sites for student clinical experiences, faculty practice, and research as schools of nursing and universities fulfill their missions. Unfortunately, despite the successes of NMHCs, such as the delivery of high-quality care (Barkauskas, Pohl, Benkert, & Wells, 2005), too often centers struggle or fail to succeed financially (Hansen-Turton, Line, O'Connell, Rothman, & Lanby, 2004; Vincent, Mackey, Pohl, Oakley, & Hirth, 1999).

Given the importance of NMHCs, strategies are needed to support the long-term sustainability of these centers. Examination of coding patterns using Current Procedural Terminology (CPT) codes is one key strategy to help providers better understand the services rendered, actual and potential revenue generated, and adherence to federal coding guidelines. Coding patterns refer to the distribution of CPT codes, the health care industry's standard for describing services provided. The expected cost of resources needed to provide a service described in a CPT code are included (Grimaldi, 2002; U.S. Department of Health and Human Services, 2007). The Centers for Medicare and Medicaid Services (CMS) and other payers use these codes to determine reimbursement. Examining coding patterns is also a risk management strategy to protect against a time-consuming and costly audit (Stavrakas-Souba, 2005). Providers need to be informed to determine whether their coding practices might need improvement or be considered "red flags" to auditors, and accurately reflect patients served. Despite the importance of coding, little is known about coding patterns at NMHCs.

The purpose of this study was two-fold: (a) compare coding patterns of NMHCs delivering primary care with national data of nurse practitioners (NPs) and family physicians (FPs) from the Medical Group Management Association (MGMA) and CMS; and (b) compare coding patterns between aggregated national NMHC data and individual centers. The comparisons can help providers identify reasons for variations in coding patterns in their individual centers.

Review of Evaluation and Management Literature

Assessment of coding patterns is important to ensure that coding accurately represents providers in databases at all levels. Equally important, accurate coding reflects the level of adherence to federal coding guidelines. One strategy to examine coding is to analyze distributions of office visits, which are expected to form a normal bell-shaped curve (Decision Health, 2003). There are five levels of CPT codes for office visits: new patient office visit codes range from 99201 to 99205 and established patient office visit codes range from 99211 to 99215. A higher code number indicates a higher level of service (a more resource-intensive service) that is associated with a higher level of payment (e.g., reimbursement). Studies of coding practices have focused on comparisons across type of provider and accuracy of coding based on chart review, and support the credibility of comparing the utilization of CPT codes by NPs and FPs. More than a decade ago, Horner, Paris, Purvis, and Lawler (1991) found that the accuracy of billing and coding was comparable across faculty physicians, residents, and family NPs; all consistently undercoded services. Sullivan-Marx and Maislin (2000) found no significant differences between provider estimates of relative value units, a key component of a CPT code, between NPs and FPs for the level of service for three office visit evaluation and management (E&M) codes (99203, 99213, 99215). Allen, Reinke, Pohl, Martyn, and McIntosch (2003) compared CPT codes extracted from records by reviewers, using federal guidelines, with actual NP coding. While 40% (n=4) of the reviewer and NP codes matched, 40% (n=4) were coded higher by NPs than the reviewers and 20% (n=2) were coded lower by the NPs. The higher-coded visits tended to be new patient rather than established patient visits. Lastly, Vonderheid, Pohl, Schafer, McIntosh et al. (2004) compared coding practices of six NMHCs across Michigan, NP data from CMS, and FP data from MGMA; NMHCs used the two lowest level codes for office visits more than NPs and FPs. Level 2 (99202) and 3 (99203) codes composed 63% of all new patient visit codes for NMHCs compared to 36% and 29% for CMS and MGMA, respectively. No published studies reported CPT codes for NMHCs nationwide. There is a need to better understand coding practices at NMHCs.


Study design. A descriptive, retrospective study was conducted to compare frequency distributions of E&M codes (office visit codes 99201-99215) between NMHCs delivering primary care and national data sets of NPs and FPs from the MGMA and CMS. The study analyzed first-year survey data in a national NMHC database developed at the Institute for Nursing Centers (www.nursing

Nurse-managed health center data. A NMHC was defined as a legal entity providing primary care services in a center with the following characteristics: was managed by nursing; utilized APNs, namely NPs, to provide the majority of care; had a defined mission/purpose and goals; and maintained financial records. Primary care refers to the provision of integrated, accessible health care services by clinicians who are accountable for addressing a majority of personal health care needs, developing a sustained partnership with patients, and practicing within the context of family and community (Institute of Medicine, 1994).

A standardized survey was distributed via email to 122 NMHCs listed in a national directory or recruited at national NP conferences (Figure I shows the sampling process for data collection and analysis). The survey requested information on ownership and location of the NMHC; patient volume, demographics, and diagnoses; services provided; and financial data for the 2004/2005 fiscal year. The NMHCs were also asked to submit frequencies of all CPT codes. Telephone interviews were conducted with center representatives to clarify responses, minimize reporting errors, and obtain missing data.


Thirty of 42 NMHCs expressing the intention to participate completed the survey; a 26% response rate based on 122 contacted. Sixteen additional centers gave reasons for not participating, such as not providing primary care services, not having time to complete the survey, and having insufficient data tracking mechanisms. Thirteen NMHCs (11% of centers listed in the directory or 43% of centers reporting data for the national survey) provided valid CPT code data; two centers provided data for fiscal year 2003/2004. The two NMHCs with data for 2003/2004 were both centers that participated in the pilot test of the survey. These two centers were not able to submit data for the subsequent year (2004/ 2005) (the first year of formal data collection for the survey) because of time constraints. These two centers were included in this analysis for a few reasons: they provided valid and reliable data, their providers and patient populations were stable across the 2 years, and coding guidelines were stable across the 2 years. These reasons supported comparisons of the two centers in the pilot survey with the 11 centers in the subsequent year of formal data collection. Data from these 13 NMHCs are summarized in this article.

Characteristics of NMHCs varied. Eight centers served patients of all ages, three served college/ university students, one served only adults, and one was a pediatric practice. All 13 centers provided community education and/or screening services. Seven offered group services, most commonly related to health promotion and mental health. The 13 centers had a total of 157,572 encounters (range 1,022 to 87,638) for the report period. Of 186,622 procedure codes reported, 130,675 (70%) were E&M codes. The centers varied greatly in the extent to which revenues were primarily derived from reimbursement for patient care versus subsidy and grants. On average, patient care revenue accounted for just under half of total revenues. Total revenues from patient care reimbursement represented 20% or less at three centers and 90% to 100% at three centers; and three centers reported generating patient care revenue primarily from capitated contracts. Patients insured through Medicaid ranged from 0 to 71% (average 27%) and uninsured patients accounted for 0 to 52% (average 23%) across NMHCs. Characteristics (setting, clients served, and codes) of the three centers highlighted in this report are described in Table 1.

MGMA data. The MGMA is a national professional association for medical group practice administrators with over 22,000 individual members. For over 50 years, MGMA has collected information on cost efficiency, productivity, and compensation; the annual cost survey has used consistent definitions and a questionnaire format since 1979. Two databases on group practice activities have information that parallels data submitted by NMHCs; data from the Cost Survey 2006 Report Based on 2005 Data (MGMA, 2006) were used in this study. These data are based on responses from 143 family practice medical groups with 644 full-time equivalent physicians. The MGMA database of CPT codes consists of over 74.8 million records, including 19.5 million records that relate to procedures reported for over 550 FPs and 185 NPs.

Sources of revenue reported on the cost survey (MGMA, 2006) included third-party reimbursement (fee-for-service [FFS] and capitated plans) from private insurers, government payers, and self-pay patients, as well as medical revenue from other sources (e.g., sales of goods and services, professional service contract payments). The majority of revenue for family practice single specialty groups (n=49) came from FFS sources and patient payments. Only five practices (3.4%) reported capitation revenue as being more than 20% of total practice income. The mean payer mix based on charges showed that the highest amount was from commercial (58%), followed by Medicare (23%), Medicaid (11%), self-pay (6%), charity (1%), and other government (1%).

Centers for Medicare and Medicaid data. Additional comparison data were obtained from the CMS database of all Medicare Part B services provided by FPs and NPs for calendar year 2004 in the E/M Bell Curve Data Book (Decision Health, 2005). These data show the national distribution of E&M data by specialty and E&M category. Distributions repre sent the average E&M utilization percentage for a subcategory of codes. We examined the distributions of FPs and NPs codes within the subcategories of office visit codes: new (99201-99205) and established (99211-99215) patient office visit codes. Medicare beneficiaries generally fall into one of three groups: individuals aged 65 years and older, individuals younger than 65 years with certain disabilities, and individuals of all ages with end-stage renal disease.

Analysis. Data were entered into Microsoft Excel spreadsheets for analysis. Frequency distributions of CPT codes for outpatient visits 99201 to 99215 were compared between NMHCs, CMS, and MGMA; and between individual centers and aggregate NMHCs.


Figures 2 and 3 illustrate the distribution of new and established patient office visit codes, respectively, for NMHCs, CMS, and MGMA.

NMHCs aggregate national data. Among NMHCs, E&M codes composed 70% of all procedure codes. The 10 E&M office visit codes 99201 to 99215 composed 72% of all E&M codes. New patient office visit codes for NMHCs showed high utilization of codes representing lower resource intensive services (99201 and 99202 or levels 1 and 2) compared to higher resource-intensive services (99204 and 99205 or levels 4 and 5). Forty-one percent of new patient codes were the two lowest resource-intensive services (99201 and 99202), while only 11% of new patient codes were the highest resource-intensive services (99204 and 99205). About half (48%) of new patient codes were the mid resource-intensive code (99203). For established patient office visit codes, the distribution was closer to a normal curve, yet continued to show higher utilization of codes representing lower resource-intensive services. Twenty-five percent of established patient codes were the two lowest resource-intensive services (99211 and 99212), 70% were the mid resource-intensive code (99213), and the remaining 5% was a higher resource-intensive service code (99214). No codes for the highest level of service (99215) were reported.



Comparisons among national data: NMHCs, MGMA, and CMS. Compared to MGMA, NMHCs were more similar to FPs than NPs in physician practices. For new patients, NMHCs had higher utilization (48%) of the mid resource-intensive service code 99203 (level 3) than FPs (43% CMS, 41% MGMA) and NPs (41% CMS, 34% NPs); and MGMA NPs had higher utilization of level 1 and 2 codes (99201, 11% and 99202, 44%) than NMHCs (99201, 7% and 99202, 34%) and FPs (99201, 8% and 99202, 37%). Distributions for established patients were similar, but NMHCs had lower use of 99214 (5%), a higher resource-intensive service code, than MGMA providers (13% NPs and 16% MDs). For NPs in NMHCs, the ratio of new to established patients was 1:10 at

NMHCs (for every one new patient visit there were 10 established patient visits) compared to a 1:19 ratio for MGMA NPs, and a 1:16 ratio for MGMA FPs. Data were not available for CMS.

Comparisons between individual NMHCs and NMHC aggregate national data. Examination of individual NMHCs found distributions shifted to the left, that is, high use of the two lowest resource-intensive codes (levels 1 and 2) and little to no use of the highest resource-intensive codes (levels 4 and 5). Three centers (A, B, and C) exhibited extremes in coding patterns compared to national NMHC data. Figures 4 and 5 illustrate the distribution of new and established patient office visit codes, respectively, for these individual clinics compared to national NMHCs data. We report the distributions for these three centers to illustrate how individual centers might differ from national data, and to highlight the importance of routine monitoring of coding. Understanding how a center differs and then identifying reasons for these differences can help providers and administrators understand the accuracy of their center's coding practices, make improvements when needed, and avoid external audits.



Center A. For new patients (see Figure 4), Center A did not use 99202 (a lower resource-intensive code) compared to 8% found in national NMHCs data. Additionally, Center A had higher use of 99203 (the mid resource-intensive code) compared to national NMHC data (73% vs. 48%, respectively). In contrast, for established patients (see Figure 5), Center A did not use 99211 (the lowest resource-intensive code), compared to 5% for national data. Center A also had lower use of 99213 (the mid resource-intensive code) than national NMHC data (35% vs. 70%, respectively). Conversely, Center A had higher use of 99214 (a higher resource-intensive code) than national NMHCs data (40% vs. 5%, respectively).

Staff identified reasons for coding patterns. Patients in Center A represented a primarily young, healthy population. New patients often presented with multiple episodic complaints, all of which the NP would address during one visit. Most complaints individually did not require high-level decision making, but the interaction of several diagnoses and treatment plans had to be considered, thereby creating a higher level of decision making that had be coded accordingly. The center did not see patients for chronic disease management. The frequent use of a high resource-intensive code (level 4) was perplexing given the patient population and most likely represented the incorrect interpretation of time spent with a patient. The NPs were inclined to spend more time with established patients, and counseling for psychosocial issues used more time than medical management. Inaccurate coding might have also been a reflection of prior experiences of NPs who had worked as a NP only in Center A, making their reference point for complexity less realistic given the relatively healthy population. The lowest resource-intensive code 99211 was not used for established patients because it was not listed on the super bill although it was an option in the billing program. A billing consultant created the form more than 10 years previously and the NPs had followed the recommendation to bill 99212 for a follow-up visit and 99213 for a new problem. The NPs had not questioned this (omission) after the initial set-up even though all had participated in subsequent continuing education on billing and coding. No one in Center A, clinical or administrative staff, received formal preparation in billing and coding procedures.

Center B. Distributions of codes for Center B differed from national NMHC data and there were striking differences between new and established codes within this center. At Center B the most frequently used new patient codes were the two higher resource-intensive codes (99204 and 99205), composing 64% of all new patient codes. In contrast, these higher resource-intensive codes (99204 and 99205) composed only 12% of new codes in the national NMHCs data. The greatest difference was found in the use of the highest resource-intensive code 99205 (level 5), which was 43% of all new patient codes at Center B compared to only 6% in the national NMHCs data. For established patient codes, 55% of Center B's established patient codes were the two lowest resource-intensive codes (99211 and 99212), compared to 25% in the national NMHC data. Within Center B, a comparison of new and established patient codes showed a marked difference in the use of level 5 codes (99205 and 99215). Whereas a level 5 code for new patients (99205) composed 43% of all new patient codes, a level 5 code for established patients (99215) composed only 6% of all established patient codes.

The NP staff offered reasons for this difference in distributions. Patients had multiple co-morbidities that included both mental and physical health problems (e.g., depression, posttraumatic stress, neglected/uncontrolled diabetes, and hypertension) as well as social problems (e.g., homelessness and adolescent pregnancies). While the history and examination components of E&M coding contributed to assigning the highest level (99205), NPs viewed the decision-making component as highly complex. Other contributory factors included counseling, coordination of care, nature of the presenting problem, and time. Staff developed a more accurate understanding of coding guidelines following a review by a Medicaid auditor and discussion with the auditor and collaborating physician. Established patient visits were coded at the two lowest levels of service (99211 and 99212) because those visits had not required an NP (e.g., blood pressures, blood draws for psychotropic medication and glucose monitoring, and weights) or were for reassurance and health education. Because Center B was located in the same building as public housing and the center was perceived as warm and welcoming, patients sometimes returned with minor complaints to receive attention when they were lonely; or they returned for acceptance when they were being teased or harassed by others.

Center C. For new patient visits, only two out of five levels of codes were used by Center C 99201 and 99202. All new patients at Center C were the two lowest-level codes - 99201 (62%) and 99202 (38%)--compared to only 8% (99201) and 34% (99202) at national NMHCs, respectively. The distribution for established patient codes was closer to a normal curve with four out the five levels of codes (99211, 99212, 99213, and 99214) assigned to visits. Center C, however, continued to use more level i codes (99211 at 17%) and level 2 codes (99212 at 30%) compared to national NMHCs data where level 1 codes (99211) and level 2 (99212) codes composed 5% and 20%, respectively. Compared to the national NMHCs data, Center C had very high use of the lowest-level codes 99201 (62% Center C vs. 8% national NMHCs) and 99211 (17% Center C vs. 5% national NMHCs). Staff explained that case manager visits were automatically assigned at level 1, as well as some primary care visits; they acknowledged that a RN could appropriately manage a level 1 visit and a NP was not necessary. The clinic planned to separate case manager visits from primary care visits when examining their data in the future.


Nurse-managed health centers play an important role in delivering health care services to a wide range of communities and often serve as our nation's safety net providers. Unfortunately, NMHCs struggle to remain in business for a variety of reasons, including underdeveloped business practices. In the health care industry, CPT is a standard language that documents services rendered and is linked to reimbursement for these services, making CPT codes a cornerstone of revenue, particularly in a FFS environment. The codes are also important in a managed care environment, because they describe the level of complexity of services a population requires and can be used to negotiate contracts that adequately cover the cost of providing services to the target population. Providers need to possess financial acumen to remain open for business. Assessment of CPT coding patterns is a key strategy to support long-term sustainability.

Until now, NMHCs had only data from CMS and MGMA for comparison with coding patterns in individual centers. This article is the first published report of national data for NMHCs that is available for comparison. Important lessons for financial success have been identified.

Among NMHCs, office visit codes compose the majority of E&M codes. Greater use of office visit codes rather than other E&M codes was expected for several reasons: NMHCs focus on ambulatory care services, the use of office visit codes rather than preventive medicine codes generates more revenue, and patients typically wait to seek care until there is a health problem rather than obtaining preventive care. Among NMHCs, the distribution of new patient visit codes showed markedly high utilization of codes representing less resource-intensive services. For established patient visit codes, the distribution was closer to a normal curve yet continued to show higher utilization of codes representing lower-intensity services compared to higher-intensity services. Findings are consistent with previous research (Vonderheid, Pohl, Schafer, McIntosh et al., 2004).

Comparisons of NMHCs with other national data found that for new patients, NMHC coding distributions fell in between CMS and MGMA providers and were more similar to MGMA physicians than other providers. For established patients, distributions were similar; however, NMHCs had less use of higher-level codes than CMS and MGMA data. High use of lower resource-intensive codes by NMHCs compared to CMS and FP data from MGMA is consistent with previous research (Vonderheid, Pohi, Schafer, McIntosh et al., 2004).

Compared to NMHC and MGMA providers, CMS providers had notably higher use of the two highest resource-intensive codes for patient visits (99114 and 99215). Whereas CMS data were for Medicare patients who were generally over 65 and likely to have more chronic and complex problems, NMHC primary care providers and MGMA family practice NPs and FPs typically served a much more diverse population. Payer mix analysis showed that Medicare composed only 4% of total revenue at NMHCs and 23% of charges for MGMA FPs. Differences in coding patterns appear to be practice specific rather than provider specific. In some MGMA FP practices, NPs might play a support role rather than have their own panel of patients. It is also possible that NPs are assigned patients that require less-intensive services so that FPs are available for patients needing more intensive services.

Based on analysis of the three NMHCs, reasons for variations in coding patterns included population-specific differences, undercoding, overcoding, and lack of sound business practices. Inaccurate coding was impacted by NP deficiencies in knowledge of accurate coding parameters, understanding of time in coding, misinterpretation of the complexity of clinical decision making, and problematic training from a consultant.

Centers cited a lack of formal preparation in billing and coding procedures for clinical and administrative staff and inadequate administrative oversight. It is common for excellent clinicians to take administrative positions without any formal business administration education and training; but this decision might place the practice at risk for future financial problems. Staff identified a need for more finance and business content, including coding skills, in NP curricula. Sa, Cohen, and Marculescu (2001) previously identified the need to improve the education of NPs and other APNs related to coding.

The NMHCs had a lower ratio of new to established patient visit codes than NPs and FPs in the MGMA data. This might indicate that NMHCs have more new patients seeking care, that NMHCs are newer and are open to new patients, or that for various reasons patients have fewer return visits (e.g., they may be healthier and need fewer visits) leaving room for new patients compared to medical practices. It is important for providers in NMHCs to know the growth rate of their community. If the new patient office visits as a total of all office visits is below the growth rate of the community, then the center should increase marketing efforts (Decision Health, 2003).

While a wealth of literature describes how to start a NMHC, little is known about how to become a financially successful center (Vonderheid, Pohl, Schafer, Forrest et al., 2004). Importantly, NMHCs need to focus more on a business model for practice. Providers need to accurately code services using the most current guidelines. Providers admitted to undercoding to reduce the patient's out-of-pocket costs, especially when payment was based on a sliding scale. Inaccurate undercoding undervalues the service performed and contributes to lost revenue, present and future, as contracts would be negotiated based on current coding patterns. Likewise, the impact of overcoding must be understood. Centers that overcode are subject to audit and civil penalties if documentation does not support coding. Accurate documentation helps centers obtain the reimbursement deserved. Over the long term, centers need to receive payment for services rendered to remain open for business.

The importance of frequent and regular assessment of an individual center's data cannot be overemphasized. Every NMHC needs to understand its own data by asking whether coding patterns make sense based on patient demographics, the relationships among E&M codes and categories, and comparison with national benchmarks. Administrators and auditors will seek answers to why a center's data might differ from year to year or differ from benchmarks. Understanding your center's data will prepare you to answer any questions as well as develop strategies for increasing revenue or minimizing loss. Strategies to understand coding practices include chart review to compare recommended with actual chart documentation, use of a software program such as Excel or the E&M Template Software (Decision Health, 2003), and in-services and continuing education opportunities that focus on coding to educate staff.

In conclusion, to be competitive and sustain center operations, managers and practitioners need to understand the financial data of their own centers and implement care and business practices associated with high-performing centers. Specifically, administrators and providers need to monitor use of CPT codes, identify codes that accurately represent their practice, and identify center characteristics and business practices affecting their use and revenue (potential and actual) generated by these codes. Financial performance monitoring and its comparisons against individual center goals and industry benchmarks are essential to improve the long-term survival of NMHCs.

ACKNOWLEDGMENT: This research was supported by the W.K. Kellogg Foundation grant, Dr. Joanne Pohl, PI.
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This continuing nursing educational (CNE) activity is designed for nurses leaders and other health care professionals who are interested in CPT coding patterns at nurse-managed health centers (NMHCs). For those wishing to obtain CNE credit, an evaluation follows. After studying the information presented in this article, the nurse leader will be able to:

1. Explain the importance of proper CPT coding to the viability of NMHCs.

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3. Discuss reasons for variations in coding patterns of the NMHCs studied.

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Allen, K.R., Reinke, C.B., Pohl, J.M., Martyn, K.K., & McIntosch, E.P. (2003). Nurse practitioner coding practices in primary care: A retrospective chart review. Journal of the American Academy of Nurse Practitioners, 15(5), 231-236.

Barkauskas, V.H., Pohl, J.M., Benkert, R., & Wells, M.A. (2005). Measuring quality in nurse-managed centers using HEDIS measures. Journal of Healthcare Quality, 27(1), 4-14.

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Pohl, J.M., Vonderheid, S.C., Barkauskas, V.H., & Nagelkerk, J. (2004). The safety net: Academic nurse-managed centers' role. Policy, Politics, & Nursing Practice, 5(2), 84-94.

Sa, T.L., Cohen, J., & Marculescu, G. (2001). Nurse practitioners' attitudes and knowledge toward current procedural terminology (CPT) coding. Nursing Economic$, 19(3), 100-106.

Sullivan-Marx, E.M., & Maislin, G. (2000). Comparison of nurse practitioner and family physician relative work values. Journal of Nursing Scholarship, 32(1), 71-76.

Stavrakas-Souba, L. (2005). Avoiding audits by benchmarking your E/M coding. Journal of Medical Practice Management, 21(1), 51-53.

U.S. Department of Health and Human Services. (2007). Medicare program: Revisions to payment policies under the physician fee schedule. Federal Register, 72(227), 66221-66577.

Vincent, D., Mackey, T., Pohl, J. M., Oakley, D., & Hirth, R. (1999). A tale of two nursing centers: A cautionary study of profitability. Nursing Economic$, 17(5), 257-262.

Vonderheid, S., Pohl, J., Schafer, P., Forrest, K., Barkauskas, V., & Mackey, T.A. (2004). Using FTE and RVU performance measures to assess financial viability of academic nurse-managed centers. Nursing EconomicS, 22(3), 124-134.

Vonderheid, S.C., Pohl, J.M., Schafer, P., McIntosh, E.P., McCargar, P., George, N. et al. (2004, October). Assessing coding practices: Comparing academic nurse-managed centers and national nurse practitioner data. Paper presented at the meeting of the National Nursing Centers Consortium Conference, Nashville, TN.

SUSAN C. VONDERHEID, PhD, RN, is a Research Assistant Professor, College of Nursing, University of Illinois at Chicago, Chicago, IL.

JOANNE M. POHL, PhD, RN, ANP-BC, FAAN, is Professor and Associate Dean, Office for Community Partnerships, School of Nursing, University of Michigan at Ann Arbor, Institute for Nursing Centers, Ann Arbor, MI.

CLARE TANNER, PhD, is Database Manager, Institute for Nursing Centers, and Director, Center for Collaborative Research in Health Outcomes and Policy, Michigan Public Health Institute, Okemos, MI.

JAMESETTA A. NEWLAND, PhD, RN, FNP-BC, FAANP, DPNAP, is Clinical Associate Professor and Nurse Practitioner, College of Nursing, New York University, New York, NY.

DAVE N. GANS, MSHA, FACMPE, is Vice President, Practice Management Resources, Medical Group Management Association, Englewood, CO.
Table 1.
Characteristics of Individual NMHCs with Major Differences in
Coding Patterns Compared to Aggregate NMHCs

Center     Setting          Clients

Center A   Rural/           882 clients and 1,022 visits
             residential,   Students, faculty, staff,
             campus based   alumni, all ages
                            Primarily episodic care

Center B   Urban,           622 clients and 4,558 visits
             community      Underserved, low income, all ages
             based          Episodic and chronic care
                            Multiple co-morbidities
                            (mental and physical health)

Center C   Urban,           602 clients and 2,404 visits
             community      Some underserved and low income
             based          All ages
                            Episodic and chronic
                            (mental and physical health)

            Total CPT Codes/
           Codes 99201-99225
Center        (Frequency)

Center A          782/451

Center B      7,019/3,347

Center C      3,456/1,996
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Title Annotation:CNE SERIES; current procedural terminology
Author:Vonderheid, Susan C.; Pohl, Joanne M.; Tanner, Clare; Newland, Jamesetta A.; Gans, Dave N.
Publication:Nursing Economics
Article Type:Survey
Geographic Code:1USA
Date:Jul 1, 2009
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