ASSGN WK 6

The impact of nurse practitioner regulations on population access to care

Donna Felber Neff, PhD, RN, FNAPa,*, Sul Hee Yoon, PhDb, Ruth L. Steiner, PhDc, Ilir Bejleri, PhDb, Michael D. Bumbach, PhD, FNP-BCd, Damian Everhart, PhD, RNe,

Jeffrey S. Harman, PhDf

a College of Nursing, University of Central Florida, Orlando, FL b Department of Urban and Regional Planning, University of Florida, Gainesville, FL

c Center for Health and the Built Environment, Department of Urban and Regional Planning, University Of Florida, Gainesville, FL d College of Nursing, Department of Family, Community, and Health System Science, University of Florida, Gainesville, FL

e Centers for Medicare and Medicaid Services, University of Central Florida, Palm City, FL f Department of Behavioral Sciences & Social Medicine, College of Medicine, Florida State University, Tallahassee, FL

A R T I C L E I N F O

Article history: Received 15 November 2017 Accepted 5 March 2018 Available online 8 March 2018.

Keywords: Nurse practitioner scope of practice Population access to care Drive time State NP practice regulations

A B S T R A C T

Background: By 2025, experts estimate a significant shortage of primary care pro- viders in the United States, and expansion of the nurse practitioner (NP) workforce may reduce this burden. However, barriers imposed by state NP regulations could reduce access to primary care. Purpose: The objectives of this study were to examine the association between three levels of NP state practice regulation (independent, minimum restrictive, and most restrictive) and the proportion of the population with a greater than 30-min travel time to a primary care provider using geocoding. Methods: Logistic regression models were conducted to calculate the adjusted odds of having a greater than 30-min drive time. Findings: Compared with the most restrictive NP states, states with independent practice had 19.2% lower odds (p = .001) of a greater than 30-min drive to the closest primary care provider. Discussion: Allowing NPs full autonomy to practice may be a relatively simple policy mechanism for states to improve access to primary care. Cite this article: Neff, D. F., Yoon, S. H., Steiner, R. L., Bejleri, I., Bumbach, M. D., Everhart, D., & Harman, J. S. (2018, JULY/AUGUST). The impact of nurse practitioner regulations on population access to care. Nursing Outlook, 66(4), 379–385. https://doi.org/10.1016/j.outlook.2018.03.001.

Background

The benefits of an adequate supply of primary care pro- viders on patient health have been well documented in the scientific literature, including improved care coor- dination and better overall patient outcomes (Macinko,

Starfield, & Shi, 2007; Starfield, Shi, & Macinko, 2005). However, a shortage of primary care physicians (MDs) in the United States is estimated to exceed 52,000 by 2025 (Petterson et al., 2012), most notably in key geo- graphic locations, including medically underserved and health professional shortage areas. With only 2% of new physicians choosing primary care or family medicine

* Corresponding author: Donna Felber Neff, College of Nursing, University Of Central Florida, 22012 Research Parkway, Orlando, FL 32826. E-mail address: [email protected] (D.F. Neff).

0029-6554/$ — see front matter © 2018 Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.outlook.2018.03.001

Available online at www.sciencedirect.com

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www.nursingoutlook.org

careers, the shortage of MDs could potentially exceed 200,000 (20% of the needed workforce) by 2025 (Sargen, Hooker, & Cooper, 2011). Furthermore, access to care in rural and poor inner city areas will likely continue to be limited because of shortages of MDs and dispari- ties in geographic practice locations (Huang & Finegold, 2013).

One proposed solution to alleviate the primary care shortage gap is to expand the nurse practitioner (NP) workforce, which has been identified as a key driver to reduce this burden (Faraz, 2017). To date, the supply of NPs is expected to increase over this same time period, with a projected growth of 244,000 NPs by 2025 (Auerbach, 2012). Furthermore, research over several decades has established that NPs provide safe and ef- fective care with patient health outcomes comparable with MDs (Hamric, Worley, Lindebak, & Jaubert, 1998; Lenz, Mundinger, Kane, Hopkins, & Lin, 2004; Mundinger et al., 2000).

Although primary health-care NPs are unequally dis- tributed in the United States, they are the health-care providers who are most likely to practice in rural areas and to provide care to underserved populations (Kaplan, Skillman, Fordyce, McMenamin, & Doescher, 2012). Com- pared with MDs, NPs are significantly more likely to provide primary care in rural counties, particularly in states with the least restrictive NP state regulations (DesRoches et al., 2013). Between 1998 and 2010, there was a 15-fold increase in the frequency of Medicare pa- tients receiving care from NPs practicing in states with the least restrictive NP practice regulations (Kuo, Loresto, Rounds, & Goodwin, 2013).Yet, barriers imposed by state NP regulations impede optimal and independent prac- tice, negatively affecting access to primary care in these underserved areas. In fact, this constraint to NPs’ scope of practice may limit NPs’ geographic spread and thus limit their ability to provide primary care in those areas that already lack access to primary health-care provid- ers. A recent study by Reagan and Salsberry (2013) concluded that restrictive state NP practice regula- tions were associated with a decrease in NP supply, as well as reduced overall growth rate by 25%. However, Reagan and Salsberry did not examine how state NP re- strictions impact a key component of access to care: patient travel time. Our study will build upon this re- search and address these gaps in the literature.

In 2008, the groundbreaking APRN Consensus Model was created by the Advanced Practice Nursing Consen- sus Work Group and the National Council of State Boards of Nursing (NCSBN) APRN Committee to align the struc- ture of licensure, accreditation, certification, and education for all advanced practice registered nurses (APRNs) in the United States (APRN Consensus Work Group & National Council of State Board of Nursing, 2008). This model is endorsed by 41 nursing organiza- tions and considered the gold standard toward consistent NP regulatory practice. In particular, one major recom- mendation in the model focuses on reducing barriers in NP scopes of practice and optimizing the function of NPs within the complex health system to ensure ade-

quate access to primary care, a relevant focus of the present study (Rounds, Zych, & Mallary, 2013).Three cat- egories of NP regulations are derived from the American Association of Nurse Practitioners (AANP) and based on practice laws and regulations specific to each state (AANP, 2018a): (a) independent practice: NPs practice in- dependently (e.g., evaluate patients, diagnose, initiate, and manage treatment); (b) minimum restrictive prac- tice: a regulative collaboration agreement is required with MDs to provide patient care (e.g., requires MDs to pre- scribe Schedule II and III controlled substances); and (c) most restrictive: requires MD hierarchical supervision, delegation, or team management to provide patient care (e.g., diagnose, treat, and prescribe medication). Pohl, Hanson, Newland, and Cronenwett (2010) argue that all 50 states will reap the benefits when NPs practice to their full scope of practice and work in collaborative rela- tionships with physicians. Benefits include increased patient access to health care and cost-effective care (Rudner Lugo, O’Grady, Hodnicki, & Hanson, 2010).

From a national policy perspective, the Affordable Care Act (ACA) (Patient Protection and Affordable Care Act, H.R. 3590, 2010) was designed to provide health-care cov- erage for millions and to alleviate the shortage of primary care providers by providing incentives for primary care. Although the status of federal policy is un- certain, having health insurance does not guarantee access to care, and underlying disparities in health- care access are not fully addressed by the ACA (Patient Protection and Affordable Care Act, H.R. 3590, 2010). For example, 20% of the U.S. population lives in rural areas, but few have access to health-care resources: only 9% of primary care MDs practice in these areas, and com- pared with urban and suburban areas, there are fewer nurses and MDs per capita (Blumenthal & Kagen, 2002; van Dis, 2002). One such barrier to access is the geo- graphic distance to and the availability of a health- care provider. Long travel time to a provider is associated with deleterious patient outcomes. Long driving dis- tances and travel times from home to provider have been shown to be associated with delays in treatment (Scoggins et al., 2012), discontinuity of follow-up care, decreased likelihood of treatment for breast cancer (Shroen, Brenin, Kelly, Knaus, & Slingluff, 2005), emer- gency stroke and myocardial infarction care, psychotherapy (Pfeiffer et al., 2011), and HIV care (Taylor et al., 2014). Moreover, living in a rural area was found to be associated with poor access to needed health care because of increased travel burden (time and dis- tance) (Lack, Carlo, & Marsh, 2013; Stephens et al., 2013).

To better understand the interplay of NP state regu- lations and access (travel time), the present study examines the association between three levels of NP state practice regulation and the proportion of the pop- ulation with a greater than 30-min travel time to the closest primary care provider (NPs or MDs). Based on our review of the literature, we hypothesize that states with restrictive NP state practice regulations will result in a longer travel time burden compared with states with independent NP practice.

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Study Data and Methods

Sample

The study sample includes all practicing MDs (N = 241,618) in the United States identified from the 2011 American Medical Association (AMA) Masterfile and a subgroup sample of NPs (n = 21,211), 2013 members of AANP. The data represent either the home or the work address of NPs, a proxy measure of location, and ad- dresses of MDs’ primary practices, which will be used to pinpoint (geocode) providers’ locations on a geo- graphic information system (GIS) map.

Variables

Dependent Variable The dependent variable was the proportion of popula- tions with a greater than 30-min drive time using the 2012 Census Block Group as the unit of observation. A 30-min travel time threshold was used as an indicator of adequate access to determine the proportion of the population that had adequate access to primary care (travel time !30 min vs. >30 min).

Independent Variable State-level NP practice regulation was operationalized as three categories (AANP, 2018a): (a) independent prac- tice, (b) minimum restrictive practice, and (c) most restrictive practice. See Figure 1 for a graphical repre- sentation of these regulatory state environments.

GIS Procedures

Using GIS and providers’ street addresses, the datasets were geocoded based on the GIS street network. Next, the travel time from the centroid point of each U.S. Census Block to the nearest primary care provider was measured by using GIS origin–destination (O-D) cost matrix analysis to identify the least cost paths along the

street network.The “cost” here refer to impedance factors used to calculate the travel time. These factors include road segment length, speed limit, road connectivity, and road hierarchy.

Statistical Analysis

Logistic regression models were conducted to calcu- late the adjusted odds of having a greater than 30- min drive time using the Census Block Group as the unit of observation (N = 213,555) with the primary indepen- dent variable being the level of NP practice regulation, which is measured at the state level. Potential con- founding variables, such as the built environment (which are human spaces built for people to live, work, and play) and provider supply among states for each level of prac- tice, were addressed in the analysis. To account for such variables, the logistic regression controlled for differ- ences for each level of NP practice regulation, including MD/NP supply as measured by the total number of MDs and NPs per capita, the number of road miles per square mile, the proportion of urban area, the population per square mile, and the average drive time to the closest MD or NP. These variables are associated with access/ travel time and differ between states based on level of practice restriction, such that independent practice states tend to be more rural than the restricted practice states. If these factors were ignored, it would give a biased es- timate of the association between practice restrictions and travel time. To properly assess the association of practice restriction on travel time, it was important to control for these confounding variables.

Findings

Descriptive findings of the main dependent and inde- pendent variables can be found in Table 1. The average proportion of the population with travel time over 30 min to a provider based on each level of NP practice regu- lation was 0.03 (standard deviation [SD] = 0.15) for independent practice, 0.02 (SD = 0.11) for minimum

Figure 1 – U.S. map depicting the practice regulation status for nurse practitioners (AANP, 2013).

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restrictive practice, and 0.02 (SD = 0.10) for most restric- tive practice categories. In addition, descriptive findings for each confounding variable are displayed in Table 1. We found a higher average number of NPs and MDs per 1,000 people and number of road miles per square mile in the most restrictive practice states than in the in- dependent practice states. The average drive time was greater in the independent practice states than in the most restrictive practice states (average 6.1 vs. 4.6 min, respectively) (Table 2).

In the adjusted logistic regression models, when com- paring most restrictive NP practice states, states with independent NP practice had 19.2% lower odds of having a greater than 30-min drive to the closest NPs or MDs (odds ratio [OR] = 0.808, p = .001). Although there were 7.1% lower odds of having a greater than 30-min drive in the states with minimum restrictive NP practices, there was no significant statistical difference in the most restricted NP practice states (OR = 0.929, p = .237). The importance of controlling for the total number of MDs and NPs per capita, the number of road miles per square mile, the proportion of urban areas, and the popula- tion per square mile is represented in our adjusted logistic analysis, where the direction of the associa- tion between practice restriction and travel time flips once we controlled for all confounding variables.

Finally, Figure 2 presents maps of Montana, New York, and Florida, states representing differing NP practice regulations. This graph also depicts geographic loca-

tions of MDs and NPS, as well as the associated travel times in each state. In Montana, a state with indepen- dent NP practice, NPs are in areas of the state where MDs are not present. In Florida and in New York, this is not evident where both states have restrictive levels of practice regulations: Florida NPs are required to have MDs supervise their practice, and New York NPs work in collaborative relationship with MDs.Therefore, in both states, few NPs practice in areas without close approx- imation to their supervising MD, most significantly for NPs in Florida.

Discussion

Overall, our study showed a 19.2% decreased odds of a patient having a 30-min or more drive to NPs or MDs in a state where NPs can practice independently, com- pared with states with a more restrictive NP regulation. States with independent NP regulatory practices are, in general, large, rural states, with wide population dis- tributions by the U.S. Census Block Group: Montana, Wyoming, and Idaho are examples. In contrast, states with the most restrictive NP practice regulatory envi- ronments (AANP, 2013), including Florida, California, and Texas, have more areas that are densely populated based on census data and our GIS mapping, These areas also tended to show clustering of primary care providers. For

Table 1 – Descriptive Findings of the Study Variables Per State Regulatory Status Dependent Variables Independent Variable: State Regulatory NP Practice Status

Independent Practice M (SD)

Minimum Restrictive Practice M (SD)

Most Restrictive Practice M (SD)

Proportion of population with over 30-min drive to provider

0.03 (0.15) 0.02 (0.11) 0.02 (0.10)

Confounding variables Number of NPs + MDs per 1,000 people 10.5 (114.8) 9.6 (121.8) 10.7 (211.2) Average drive time to the closest MD or NP (min) 6.1 (18.1) 5.3 (7.1) 4.6 (6.6) Number of road miles per square mile 19.2 (13.9) 21.6 (28.3) 20.4 (18.1) Number of urban road miles per square mile 66.0 (40.9) 64.5 (44.5) 70.3 (40.4)

Note. MD, primary care physician; NP, nurse practitioner; SD, standard deviation.

Table 2 – Descriptive Findings of Study Variables per NP State Regulatory Status State Regulatory NP Practice Status Independent

Practice M (SD)

Minimum Restrictive Practice M (SD)

Most Restrictive Practice M (SD)

Proportion of population with over 30-min drive to provider

0.03 (0.15) 0.02 (0.11) 0.02 (0.10)

Number of NPs + MDs per 1,000 people 10.5 (114.8) 9.6 (121.8) 10.7 (211.2) Average drive time to the closest MD or NP (min) 6.1 (18.1) 5.3 (7.1) 4.6 (6.6) Number of road miles per square mile 19.2 (13.9) 21.6 (28.3) 20.4 (18.1) Number of urban road miles per square mile 66.0 (40.9) 64.5 (44.5) 70.3 (40.4)

Note. MD, primary care physician; NP, nurse practitioner; SD, standard deviation. Authors’ descriptive analysis of variables used as control variables in the regression model.

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NPs working in those more restrictive practice states, the NPs were essentially reliant on their health-care collaborators.

Although results from of our study reveal an increas- ing patient burden from the moderated geographic health-care access to restrictive state NP policy, there also remains a gap in the NP scope of practice because of variations in each state’s NP legislation. Within the more restrictive NP policy states, NPs face legislation that limits their full scope of practice. For example, states with a more restrictive NP practice policy do not allow NP cer- tification of home health-care visits and patient stays in skilled nursing facilities or hospice care, limit ordering durable equipment, and block general hospital privi- leges for patient admissions while increasing the oversight of care by collaborators, usually MDs (AANP, 2016; Buppert, 2008). This weakened scope of NP prac- tice contradicts the suggested goals of the Institute of Medicine (IOM) and the Robert Wood Johnson Founda- tion (RWJF) (IOM & RWJF, 2010) assessment report, The

Future of Nursing, where the central aim was to enhance health care in the United States by optimally utilizing the nursing workforce. In the 5-year follow-up study on the progress and efficacy of the 2010 IOM and RWJF report, Altman, Stith Butler, and Shern (2015) found that many of the recommendations have not been implemented, largely because of obstructive state policy and limited federal funding.The type of regulatory authority may also limit implementation of recommendations. In states where boards of nursing NP regulatory authority is shared with other professions (e.g., boards of medicine), NPs were not utilized to their full scope of practice, and consum- er access to care was hampered (Rudner Lugo et al., 2010).

Present and future policies regarding NP scope of practice must be weighed with the considerations of the changing MD participation, the potential increase in NP presence in primary care, and the supporting data that reflect on the current legislation that may be oppress- ing those patients who need care the most. A recent Federal Trade Commission report states:

Figure 2 – Example of geographic distribution of NPs and MDs in states with independent, minimum restrictive and most restrictive practice regulations. Source/Notes: Authors Geographic spatial analysis of MD and NP distributions specific to three states and their NP regulatory status: Montana, Independent Practice Regulations; New York, Minimum Restrictive Practice, and Florida, Most Restrictive Practice.

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“Expanded APRN practice is widely regarded as a key strategy to alleviate provider shortages, especially in primary care, in medically underserved areas, and for medically underserved populations. Imposing greater restrictions on APRNs will only exacerbate existing and projected health care workforce shortages by lim- iting the ability of APRNs to fill gaps in patients’ access to primary care services.” (Gilman & Koslov, 2014)

Along with the Federal Trade Commission recom- mendations, Newhouse et al. (2012) concluded that enhancing policy and legislation by widening the NP scope of practice to the “full extent of their knowledge, skills, and competencies” (p. 86) could be an important intervention for potentially closing the patient access gap to primary care. Existing policy and legislation per- taining to NP scope or practice must be evaluated and modernized to reflect the changing U.S. primary care de- livery system and the associated geographic distributions related to the legislative polices associated with NP scope of practice. Furthermore, findings from the present study are consistent with recommendations from the 2008 APRN Consensus Model, particularly highlighting the reg- ulatory model of practice that emphasizes consistency and national uniform standards allowing full scope of nursing practice (National Council of State Boards of Nursing, 2008).

Limitations

The current study has specific limitations that must be considered. First, because national data that represent the populations’ travel behavior or travel mode choice was not available, travel time was estimated by the as- sumption that all populations reached their primary care provider by personal vehicles. To compensate for this limitation, the present study used detailed hierarchi- cal road network data, with speed limit classification, although the lack of understanding of the popula- tions’ travel behavior (e.g., whether patients used public transportation, rode bicycles, or walked) makes defin- itive characterization of physical accessibility difficult (Newhouse et al., 2011).

Second, the present study used only the subgroup of NPs and their addresses who are members of AANP and who noted in their membership profiles they were willing to participate in research. Those NPs not listed as AANP members were not accounted for in the present study and in the GIS mapping. With the implicit as- sumption that patients have access to personal vehicles, we would estimate more patients with a greater than 30-min travel time, because of the missing NP data points; therefore, our estimates could be considered con- servative. In addition, if we assumed these patients had to use public transportation, ride bicycles, or walk to a provider, the level of traffic (e.g., rush hour) could alter the time needed to get to a provider access point. For

instance, a 20-min drive at 11:00 a.m. might take 45 min during a typical rush hour.

Finally, because of data limitations, our subsample ofAANP NPs could not determine whether members were solely primary care NPs. However, approximately 87% of AANP members are certified as primary care, and over three quarters of NPs are reportedly working in primary care (AANP, 2018b). In addition, although the NP subsample consisted of NPs who were members of AAPN, we were unable to ascertain whether they were retired from practice, but we expect that most NPs who are paying dues to AANP are actively practicing clinicians. Lastly, differences when AMA and AANP data sample years were collected may be a potential limitation, but it is unlikely that there would be a significant change from 1 year to the next in clinicians moving or retiring.

Conclusion

To our knowledge, this was the first study assessing the association of NP regulations by state and patient access to care by drive time to primary care providers. Point estimates suggest that states with full NP scope of prac- tice have a lower percentage of the population with a greater than 30-min drive time to receive care com- pared with states that restrict NP practice. NPs practicing in states that require MD supervision are reliant on these practices, limiting their geographic distribution. Allow- ing NPs full autonomy to practice is an essential policy issue to be addressed at the state level to improve access to primary care: consistent with the 2008 APRN Con- sensus Model recommendations for regulatory practice. Also, policy changes moving NP regulatory authority to its board of nursing could be an initial driving force. Future research should be conducted to determine the impact of state NP regulations and access to care uti- lizing more recent datasets that can continue to inform policymakers on this important public health issue.

Funding

This work was supported by Robert Wood Johnson Foun- dation Interdisciplinary Nursing Quality Research Initiative.

R E F E R E N C E S

Patient Protection and Affordable Care Act, U.S.C. 18001 (2010) AANP. (2013). State Practice Environment Online: American

Association of Nurse Practitioners [updated June 4]. Retrieved from http://www.aanp.org/legislation-regulation/state -legislation-regulation/state-practice-environment/66 -legislation-regulation/state-practice-environment/1380-state -practice-by-type.

384 Nur s Out l o o k 6 6 ( 2 0 1 8 ) 3 7 9 – 3 8 5

AANP. (2016). State Practice Environment [Website]. Retrieved from https://aanp.org/legislation-regulation/state-legislation.

AANP. (2018a). State practice environment. Retrieved from https://aanp.org/legislation-regulation/state-legislation/state -practice-environment/.

AANP. (2018b). NP facts: The voice of the nurse practitioner. Retrieved from https://aanp.org/images/documents/about -nps/npfacts.pdf.

APRN Consensus Work Group & the National Council of State Boards of Nursing APRN Advisory Committee. (2008). Census model for APRN regulation: Licensure, accreditation, certification & education. Retrieved from https://ncsbn.org/ aprn-consensus.htm.

Altman, S., Stith Butler, A., & Shern, L. (2015). Assessing Progress on the Institute of Medicine Report The Future of Nursing. Washington, DC: Insitute of Medicine.

Auerbach, D. I. (2012). Will the NP workforce grow in the future? New forecasts and implications for healthcare delivery. Medical Care, 50(7), 606–610.

Blumenthal, S. J., & Kagen, J. (2002). The effects of socioeconomic status on health in rural and urban America. JAMA: The Journal of the American Medical Association, 287(1), 109.

Buppert, C. (2008). Nurse practitioner’s business practice and legal guide/Carolyn Buppert (3rd ed.). Sudbury, MA: Jones and Bartlett.

DesRoches, C. M., Gaudet, J., Perloff, J., Donelan, K., Iezzoni, L. I., & Buerhaus, P. (2013). Using Medicare data to assess nurse practitioner-provided care. Nursing Outlook, 61(6), 400–407.

Faraz, A. (2017). Novice nurse practitioner workforce transition and turnover intention in primary care. Journal of the American Association of Nurse Practitioners, 29(1), 26–34.

Gilman, D. J., & Koslov, T. I. Policy perspectives: Competition and the regulation of advanced practice nurses. Washington, DC: Federal Trade Commission; 2014.

Hamric, A. B., Worley, D., Lindebak, S., & Jaubert, S. (1998). Outcomes associated with advanced nursing practice prescriptive authority. Journal of the American Academy of Nurse Practitioners, 10(3), 113–118.

Huang, E. S., & Finegold, K. (2013). Seven million Americans live in areas where demand for primary care may exceed supply by more than 10 percent. Health Affairs (Project Hope), 32(3), 614–621.

IOM, & RWJF. (2010). The Future of Nursing: Leading Change, Advancing Health. Institute of Medicine, Robert Wood Johnson Foundation; Report No. 9780309158237.

Kaplan, L., Skillman, S. M., Fordyce, M. A., McMenamin, P. D., & Doescher, M. P. (2012). Understanding APRN distribution in the United States using NPI data. The Journal for Nurse Practitioners, 8(8), 626–635.

Kuo, Y. F., Loresto, F. L., Jr., Rounds, L. R., & Goodwin, J. S. (2013). States with the least restrictive regulations experienced the largest increase in patients seen by nurse practitioners. Health Affairs (Project Hope), 32(7), 1236–1243.

Lack, W. D., Carlo, J. O., & Marsh, J. L. (2013). Payer status and increased distance traveled for fracture care in a rural state. Journal of Orthopaedic Trauma, 27(2), 113–118.

Lenz, E. R., Mundinger, M. O., Kane, R. L., Hopkins, S. C., & Lin, S. X. (2004). Primary care outcomes in patients treated by nurse practitioners or physicians: Two-year follow-up. Medical Care Research & Review, 61(3), 332–351.

Macinko, J., Starfield, B., & Shi, L. (2007). Quantifying the health benefits of primary care physician supply in the United States. International Journal of Health Services: Planning, Administration, Evaluation, 37(1), 111–126.

Mundinger, M. O., Kane, R. L., Lenz, E. R., Totten, A.M., Tsai, W.Y., Cleary, P.D., … Shelanski, M.L. (2000). Primary care outcomes

in patients treated by nurse practitioners or physicians: A randomized trial. JAMA: The Journal of the American Medical Association, 283(1), 59–68.

National Council of State Boards of Nursing. (2008). Consensus model for APRN regulations: Licensure, accreditation, certification & Education.

Newhouse, R., Stanik-Hutt, J., White, K., Johantgen, M., Bass, E., Zangaro, G., … Weiner, J.P. (2011). Advance practice nurse outcomes 1990–2008: A systematic review. Nursing Economics, 29, 230–250.

Newhouse, R., Weiner, J., Stanik-Hutt, J., White, K., Johantgen, M., Steinwachs, D., … Bass, E.B. (2012). Policy implications for optimizing advanced practice registered nurse use nationally. Policy, Politics, & Nursing Practice, 13, 81–89.

Petterson, S. M., Liaw, W. R., Phillips, R. L., Rabin, D. L., Meyers, D. S., & Bazemore, A. W. (2012). Projecting US primary care physician workforce needs: 2010–2025. Annals of Family Medicine, 10(6), 503–509.

Pfeiffer, P. N., Glass, J., Austin, K., Valenstein, M., McCarthy, J. F., & Zivin, K. (2011). Impact of distance and facility of initial diagnosis on depression treatment. Health Services Research, 46(3), 768–786.

Pohl, J. M., Hanson, C., Newland, J. A., & Cronenwett, L. (2010). Analysis & commentary. Unleashing nurse practitioners’ potential to deliver primary care and lead teams. Health Affairs (Project Hope), 29(5), 900–905.

Reagan, P. B., & Salsberry, P. J. (2013). The effects of state-level scope-of-practice regulations on the number and growth of nurse practitioners. Nursing Outlook, 61(6), 392–399.

Rounds, L. R., Zych, J. J., & Mallary, L. L. (2013). The consensus model for regulation of APRNs: Implications for nurse practitioners. Journal of the American Association of Nurse Practitioners, 25(4), 180–185.

Rudner Lugo, N., O’Grady, E. T., Hodnicki, D., & Hanson, C. (2010). Are regulations more consumer-friendly when boards of nursing are the sole regulators of nurse practitioners? Journal of Professional Nursing: Official Journal of the American Association of Colleges of Nursing, 26(1), 29–34.

Sargen, M., Hooker, R. S., & Cooper, R. A. (2011). Gaps in the supply of physicians, advance practice nurses, and physician assistants. Journal of the American College of Surgeons, 212(6), 991–999.

Scoggins, J. F., Fedorenko, C. R., Donahue, S. M. A., Buchwald, D., Blough, D. K., & Ramsey, S. D. (2012). Is distance to provider a barrier to care for Medicaid patients with breast, colorectal, or lung cancer? Journal of Rural Health, 28(1), 54–62.

Shroen, A. T., Brenin, D. R., Kelly, M. D., Knaus, W. A., & Slingluff, C. L. (2005). Impact of patient distance to radiation therapy on mastectomy use in early-stage breast cancer patients. Journal of Clinical Oncology, 23(28), 7074–7080.

Starfield, B., Shi, L., & Macinko, J. (2005). Contribution of primary care to health systems and health. The Milbank Quarterly, 83(3), 457–502.

Stephens, J. M., Brotherton, S., Dunning, S. C., Emerson, L. C., Gilbertson, D. T., Harrison, D. J., … Gitlin, M. (2013). Geographic disparities in patient travel for dialysis in the United States. The Journal of Rural Health: Official Journal of the American Rural Health Association and the National Rural Health Care Association, 29(4), 339–348.

Taylor, B. S., Reyes, E., Levine, E. A., Khan, S. Z., Garduño, L. S., Donastorg, Y., … Hirsch, J.S. (2014). Patterns of geographic mobility predict barriers to engagement in HIV care and antiretroviral treatment adherence. AIDS Patient Care and Stds, 28(6), 284–295.

van Dis, J. (2002). Where we live: Health care in rural vs urban America. JAMA: The Journal of the American Medical Association, 287(1), 108.

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