David Auerbach, PhD

Debate continues on whether nurse practitioners (NPs) and physician assistants (PAs) are more likely to order ancillary services, or order more costly services among alternatives, than primary care physicians (PCPs). We compared prescription medication and diagnostic service orders associated with NP/PA versus PCP visits for management of neck or back (N/B) pain or acute respiratory infection (ARI).

 Retrospective, observational study of visits from January 2006 through March 2008 in the adult primary care practice of Kaiser Permanente in Atlanta, Georgia.

Data were obtained from electronic health records. NP/PA and PCP visits for N/B pain or ARI were propensity score matched on patient age, gender, and comorbidities.

On propensity score-matched N/B pain visits (n = 6724), NP/PAs were less likely than PCPs to order a computed tomography (CT)/magnetic resonance image (MRI) scan (2.1% vs 3.3%, respectively) or narcotic analgesic (26.9% vs 28.5%) and more likely to order a nonnarcotic analgesic (13.5% vs 8.5%) or muscle relaxant (45.8% vs 42.5%) (all 

 ≤.05). On propensity score-matched ARI visits (n = 24,190), NP/PAs were more likely than PCPs to order any antibiotic medication (73.7% vs 65.8%), but less likely to order an x-ray (6.3% vs 8.6%), broad-spectrum antibiotic (41.5% vs 42.5%), or rapid strep test (6.3% vs 9.7%) (all 

In the multidisciplinary primary care practice of this health maintenance organization, NP/PAs attending visits for N/B pain or ARI were less likely than PCPs to order advanced diagnostic radiology imaging services, to prescribe narcotic analgesics, and/or to prescribe broad-spectrum antibiotics.

	Practice variation by providers, rather than by provider type, may be more important in understanding differences in management of conditions commonly presented in primary care.

	Nevertheless, concerns have been expressed that nurse practitioners (NPs) and physician assistants (PAs) might more frequently order ancillary services, or more costly services among alternatives, compared with primary care physicians. In this study of a group model health maintenance organization’s primary care practice, we found NPs and PAs were less likely to order: 

		Advanced diagnostic imaging or narcotic analgesics for management of neck or back pain. 

		Broad-spectrum antibiotics or rapid strep tests for management of acute respiratory infections.

Increasing the percentage of nurse practitioners (NPs) and physician assistants (PAs) in the primary care provider workforce has been suggested as one strategy for addressing the United States’ national shortage of primary care physicians (PCPs).

Although NPs/PAs have clinical training and regulated scopes of practice that differ from those of PCPs, they are permitted to manage a range of medical conditions in ambulatory care.

A recent survey of the US national population indicated broad acceptance of NPs/PAs as primary care providers.

Currently, there is interest in how the addition of NPs/PAs to primary care might impact patient outcomes, medical service utilization, and costs.

 Prior studies have been relatively consistent in demonstrating that levels of patient satisfaction with care and quality of care are similar between NPs/PAs and physicians

; however, it is less clear whether care provided by NPs/PAs or PCPs affects medical services use and cost.

An NP/PA visit can be cost saving compared with a PCP visit because salary differentials lower the cost of time for patient evaluation and management.

 However, this cost advantage may be offset if NPs/PAs order ancillary services (ie, laboratory, radiology, pharmacy) at higher rates than PCPs, or order more costly services among alternatives (eg, computed tomography [CT] scan/magnetic resonance image [MRI] vs x-ray).

Studies show mixed results on use of ancillary services by provider type. One study found NPs/PAs ordered significantly more CTs/MRIs for primary care visits than physicians treating Medicare patients

; another found no difference in office-based care using the National Ambulatory Medical Care Survey (NAMCS).

 A study of Veterans Affairs patients with lower back pain found no statistically significant difference in clinical appropriateness of lumbar spine MRIs by provider type (physician, PA, or NP).

 In prescribing medications, rates of prescribing controlled medications

were similar for NPs, PAs, and physicians.

The primary question of our retrospective observational study was: Do NPs/PAs attending visits for neck or back (N/B) pain or acute respiratory infection (ARI) in primary care order ancillary services at different rates than PCPs? We focused on these 2 medical conditions for several reasons. Musculoskeletal pain and respiratory infections are common reasons that adults present for medical care in the United States,

 and visits for N/B pain or ARI are frequently accompanied by orders for ancillary services. There are general concerns that, across all providers, certain types of ancillary services are overused and add cost without value—specifically, CTs/MRIs and narcotic analgesics in management of N/B pain,

and antibiotics (particularly broad-spectrum antibiotics) in management of ARI.

At the time of this study, Kaiser Permanente Georgia (KPGA) provided comprehensive medical services to approximately 240,000 enrollees per year (59% Caucasian, 33% African American) in the Atlanta area. The study protocol was reviewed, approved, and monitored by the KPGA Institutional Review Board.

During the 27-month study period (January 2006 through March 2008), approximately 180,000 KPGA members were empaneled to a PCP in the Adult Medicine department. The study period is limited to these 27 months because, beginning in 2006, an electronic health record (EHR) system was fully implemented—allowing for measurement of providers’ orders for medical services&mdash;and it ends in early 2008 when the multidisciplinary Adult Medicine department became a PCP-only department.

 More recent comparisons of practice variation are not available.

The sample used for analysis consisted of patients 18 years or older at the time of presentation for an “incident” N/B pain or ARI visit in the KPGA Adult Medicine department. An “incident” visit was considered to have occurred if the patient who presented for N/B pain or ARI had no visit in adult ambulatory medicine for N/B pain or ARI, respectively, for at least a period of 30 days prior to the visit. Using this definition, a single patient may have had multiple incident visits during the study period.

A visit for N/B pain or ARI was determined from specific 

International Classification of Diseases, Ninth Revision, Clinical Modification

) diagnosis codes associated with the visit, either designated as a primary or secondary condition (

]). Due to the broad range of ARIs, we selected specific 

 diagnosis codes used in previously published studies as indicative of an ARI.

We used propensity score matching of visits to reduce the effect of patient selection on comparisons of practice variation between NPs/PAs and PCPs when attending a visit for N/B pain or ARI. NPs/PAs tend to treat younger, healthier patients than physicians which, in turn, can affect rates and mix of ancillary service orders.

 Thus, we propensity score-matched NP/PA visits with PCP visits on preexisting patient characteristics to address potential selection issues.

Separate analyses were conducted for N/B pain and ARI visits. First, within each visit class, the propensity for a visit to be attended by a NP/PA

versus PCP was estimated with logistic regression.

 Second, based on the estimated propensity of NP/PA versus PCP attending a visit, each N/B pain or ARI visit attended by an NP/PA was matched with an N/B pain or ARI visit, respectively, attended by a PCP.

All analyses used computerized administrative and EHR databases. Records were linked by unique identifiers and sequenced by event dates. The EHR databases distinguished services ordered by the provider from services completed by the patient. We used services ordered rather than services delivered because rates of services delivered can be affected by factors such as patient access (eg, limited locations for CT/MRI services) or cost sharing (eg, co-payments for prescription medicines).

 Thus, services ordered are more representative of practice style than services delivered.

Services ordered at the time of the visit were linked to the incident N/B pain or ARI visit by unique visit numbers. All services ordered were attributed to the provider attending the visit. Thus, there is no attribution of orders by an NP/PA to a PCP providing practice supervision (as might occur in billing of “incidental to” visits).

We were advised by several senior physicians that some orders related to the incident visit might occur up to 3 to 5 days following conveyance to the attending provider of initial tests or consultation results. Thus, we considered a diagnostic service order or prescription order as related to the incident visit if it occurred within 5 days from the visit date and was ordered by a provider in the adult primary care department at the same primary care facility where the incident visit occurred. Follow-up orders occurred in less than 5% of NP/PA visits and/or PCP visits for either N/B pain or ARI (data available on request).

 The outcomes of interest were the percentages of visits associated with an order for a specific service class. The service order classes defined for N/B pain visits were: N/B x-rays, N/B CTs/MRIs, nonnarcotic analgesic prescriptions, narcotic analgesic prescriptions, and prescriptions for skeletal muscle relaxants. The service order classes defined for ARI visits were: ARI x-rays, ARI CTs/MRIs, rapid strep tests, any systemic antibiotic prescription, any broad-spectrum antibiotic prescription, and any prescription for relief of ARI symptoms (eg, decongestants, expectorants, respiratory system anti-inflammatory medications). We combined CTs with MRIs because preliminary review of the data indicated very low rates of MRIs relative to CTs, and availability of one or the other of these advanced diagnostic imaging services at selected facilities preferred by a patient might have affected a provider’s decision to schedule one or the other of these services.

 The primary independent variable was the type of provider who attended the visit: NP/PA versus PCP.

 Covariates were: age at the time of the visit, gender, years of enrollment with KPGA at the time of the visit, and the presence (vs absence) of several major comorbidities (diabetes, hypertension, hyperlipidemia, cardiovascular disease [coronary artery disease, congestive heart failure, cerebrovascular disease], asthma or chronic obstructive pulmonary disease, or cancer) at the time of the visit.

The initial step in analysis was to compare the distribution of patient characteristics at presentation for a visit for N/B pain or ARI with respect to attending provider type: NP/PA versus PCP. Independence of patient characteristics from attending provider type (ie, NP/PA vs PCP) was assessed using a 

Propensity of a visit for N/B pain or ARI to have been attended by an NP/PA versus PCP was estimated using logistic regression including the patient covariates. This step resulted in a probability estimate of NP/PA versus PCP selection. Matching of 1 NP/PA visit with 1 PCP visit was done using a caliper of 0.25 times the standard deviation (SD); matching was done without replacement. Distributions of patient covariates before and after propensity score matching were compared using a 

 test. Before and after propensity score matching, the percentages of visits with a related diagnostic test or a medication order on an NP/PA versus PCP visit were compared using a 

Several sensitivity analyses were conducted. Results might be sensitive to the granularity of matching of NP/PA to PCP visits. Sensitivity of propensity score matching was tested with a finer caliper of 0.025 times the SD. Second, we examined percentages of visits with diagnostic radiology or medication orders by subgroups of visits classified according to the primacy of codes for presenting conditions, assuming that NPs/PAs or PCPs might use the EHR differently and, therefore, code visits differently according to sequence of “presenting” and “diagnosed” conditions. Finally, we estimated a logistic regression of each service order type as a function of NP/PA versus PCP using PROC GENMOD (SAS Institute, Cary, North Carolina) to evaluate whether clustering of service orders by provider might account for statistical significance of likelihood of a service type order by NP/PA or PCP.

All data management and statistical analyses were conducted using SAS version 9.4 (SAS Institute, Cary, North Carolina).

NPs/PAs attended to 16.2% of the visits (6724 of 41,404) with N/B pain as a primary or secondary diagnosis. NPs/PAs attended to 22% of the visits (24,190 of 109,844) with ARI as a primary or secondary diagnosis.

 displays patient characteristics on visits for N/B pain or ARI. Compared with PCPs, patients on N/B pain or ARI visits attended by NPs/PAs were younger, of shorter enrollment duration, and had lower prevalence of major comorbidities.

 displays the percent of N/B pain visits with orders for diagnostic radiology services and prescription medications by provider type, both before and after propensity score matching. After propensity score matching, PCPs were more likely to order an N/B-related CT/MRI (3.3% vs 2.1%; 

<.01) or a narcotic analgesic (30.1% vs 26.9%; 

<.01). On the other hand, NPs/PAs were more likely to order a nonnarcotic analgesic (13.5% vs 8.5%; 

<.01) or a musculoskeletal relaxant (45.8% vs 42.5%; 

<.01). N/B pain visits with an order for an x-ray did not differ between NPs/PAs or PCPs (21.6% vs 22.1%; 

 displays the percent of ARI visits with orders for diagnostic radiology services and prescription medications by provider type, both before and after propensity score matching. After propensity score matching, there were significant differences in practice between NPs/PAs and PCPs in treatment of ARI. Over all visits, PCPs were more likely to order ARI-related x-rays (8.6% vs 6.3%; 

<.01), a broad-spectrum antibiotic (42.5% vs 41.5%; 

= .03), or a rapid strep test (9.7% vs 6.3%; 

<.01). NPs/PAs, however, were more likely to order any antibiotic (73.7% vs 65.8%; 

<.01). As with N/B pain visits, this difference in practice variation between NPs/PAs and PCPs was the same as that observed before propensity score matching.

In the first sensitivity analysis, matching on a smaller caliper made no difference in the findings. Next, the practice pattern differences between NPs/PAs and PCPs over all visits on which a diagnosis of N/B pain (or ARI) was suggested were basically the same whether the relevant 

 code was primary or secondary (Tables 2 and 3). Finally, there was some clustering by provider, and adjusting for this clustering tended to push the statistical significance of the NP/PA versus PCP effect toward the null (

) in some cases; for example, CT/MRI for back pain pushing significance to nonsignificance (ie, 

>.05). For most comparisons by provider type, however, the NP/PA versus PCP effect was significant whether the model did or did not account for clustering of service orders by provider.

The objective of our study was to ascertain whether NPs/PAs differed from PCPs in frequency of orders for diagnostic services or prescription medications when managing adults presenting with N/B pain or ARI in primary care. We used propensity score matching of visits to adjust for the fact that patients attended by NPs/PAs tended to be younger and have a lower prevalence of comorbidities, which could affect diagnostic or therapeutic treatment choice.

After matching, several important differences by type of primary care provider were noted in management of N/B pain: PCPs were more likely to order CTs/MRIs and narcotic analgesics and NPs/PAs were more likely to order nonnarcotic analgesics and muscle relaxants. Similarly, differences were noted in management of ARI: PCPs were more likely to order CTs/MRIs—although the rate of these orders was low&mdash;as well as x-rays, broad spectrum antibiotics, and rapid strep tests; NPs/PAs were more likely to order any antibiotic. Thus, on balance, PCPs tended to be more likely than NPs/PAs to order diagnostic or therapeutic services related to N/B pain and ARI visits and to order more costly services among alternatives (eg, CTs/MRIs vs x-rays for adults with N/B pain, broad spectrum antibiotics vs first-line general antibiotics for adults with ARIs).

Evidence from this health maintenance organization (HMO), therefore, differs from the results of other studies, suggesting that NPs/PAs might more frequently order diagnostic or therapeutic services for common conditions treated in primary care; or, among alternatives, order more costly services.

 Our study’s findings are, however, consistent with another recent study using data from the National Ambulatory Medical Care Survey (NAMCS), which found no significant differences between NPs/PAs and physicians in office-based practice when ordering “low-value” ancillary services.

 In our study, the pattern of ancillary services use suggests that NPs/PAs might have been more judicious in use of “low-value” ancillary services than PCPs. For management of back pain, overuse of CTs/MRIs and narcotic analgesics is a current concern.

 We found NPs/PAs had lower rates of use of CTs/MRIs and narcotic analgesics in management of N/B pain. In management of an ARI, overuse of antibiotics—particularly broad-spectrum antibiotics&mdash;is a long-standing concern.

 Overuse of rapid strep tests is another concern in management of ARIs,

 and we found NPs/PAs were less likely to order broad-spectrum antibiotics and rapid strep tests.

What factors might have contributed to this NPs/PA practice pattern? Training of NPs/PAs typically emphasizes patient education and self-management over other interventional strategies. Thus, NPs/PAs may be more comfortable in initially managing N/B pain or ARI with fewer ancillary services. It is also possible that NPs/PAs are more compliant than PCPs with clinical practice guidelines in management of N/B pain or ARI in primary care.

Sensitivity analyses suggest this study’s findings are robust. Matching a narrower caliper —one a tenth of that used for the findings discussed in this paper&mdash;yielded similar results. Frequencies of orders by NPs/PAs versus PCPs for visits related to N/B pain (or ARI) did not generally differ by whether N/B pain (or ARI) was indicated as a primary or secondary diagnosis. The clustering analyses do indicate some proportion in outcomes by provider type is due to practice variation among individual providers; however, the persistence of significance of the NP/PA effect after adjusting for provider clustering strongly suggests that practice variation by provider type is important.

Articles

In primary care, nurse practitioners and physician assistants do not necessarily order more ancillary services, or more costly services among alternatives, than physicians.

Provider Type and Management of Common Visits in Primary Care

		Telemedicine offers the potential for better care, lower costs, and increased convenience.

		Expanding existing fee-for-service payment models to include telemedicine may lead to its overuse. Already there are many skeptics among payers and providers regarding this method of payment.

		The greatest potential for effective and efficient use of telemedicine services lies in the use of emerging payment models.

Telemedicine has the potential to reduce healthcare costs, increase access to healthcare, and improve health outcomes.

 However, despite these prospective advantages, telemedicine has been adopted in only limited circumstances, such as for reading radiology reports and remote phone or video visits for minor health issues.

 To promote adoption, some have advocated for telemedicine services to be reimbursed by health plans and many states have issued "parity laws" that force payers to reimburse some forms of telemedicine services at a level equal to in-person care. In this perspective, we explore why health plans are reluctant to cover most telemedicine services as part of current payment arrangements and explain why newer payment models offer greater potential for its expanded and more effective use.

Telemedicine is the delivery of health-related services via telecommunication technologies, such as phones and the Internet. Although some services involve direct interaction between providers and patients.

 Others involve passively collecting patients’ data from their homes and sending the information to healthcare professionals for monitoring.

A central barrier to the adoption of telemedicine is fee-for-service (FFS), the predominant payment method in the United States. In FFS, providers submit a claim to be reimbursed for each clinical service they perform. Providers are not paid for any service not included in the payer’s fee schedule. In many cases, virtual “visits” via phone or the Internet may be as effective in delivering care as in-person visits and require fewer resources to provide.

 However, most healthcare providers who adopt virtual visits will be financially penalized because many types of visits are not reimbursed or are reimbursed at lesser amounts. The few forms of telemedicine that have been widely adopted, such as remote reading of radiology reports, are exceptions. In those cases, the technology does not jeopardize FFS revenue for the provider adopting the technology.

Proponents argue that payers should add telemedicine as a reimbursable service. Some states have enacted parity laws and Congress is considering legislation to expand FFS reimbursement of telemedicine by Medicare. However, arguments in favor of this approach meet resistance from providers and payers alike. Providers are concerned that offering telemedicine (which, other than services covered under a parity law, is usually considered lower intensity compared with in-person visits and therefore reimbursed at a lower rate) will eat up much of their income because it will reduce the need for in-person visits. Payers have the opposite concern: although telemedicine reimbursement may increase use of actual service, inappropriate use will increase costs.

 This concern regarding inappropriate use is consistent with other coverage decisions. For example, when payers expanded coverage of implantable cardiac defibrillators in the 1990s and 2000s, inappropriate use of the devices grew dramatically.

 Telemedicine may be particularly prone to overuse because of its key advantages—convenience and increased access.

Non-FFS payment models offer alternative ways to pay for telemedicine. Under capitation, the strongest form of these new models, providers receive a fixed payment to provide care for each individual. Thus, any reduction in care costs that results from using a lower-cost technology, such as telemedicine, would accrue entirely to the provider organization.

Because pure capitation involves substantial risks for providers, it is not a common payment arrangement. However, emerging models, such as Accountable Care Organizations (ACOs), involve a form of “global payment” in which providers’ payments partially depend on the total health costs that their patients incur. In ACOs, providers must also meet quality-of-care standards, thereby favoring technologies that both improve quality of patient care and reduce costs.

Evidence from health maintenance organizations (HMOs) in the 1980s and 1990s suggests that the new payment models can stimulate adoption of cost-effective technology. HMOs are similar to newer payment models in that they also typically hold providers accountable for the costs of caring for their patients. One study of HMOs found that hospitals in areas with higher concentrations of HMO patients were more likely to use low-intensity heart attack treatment technologies (eg, medical management techniques) and less likely to use high-cost technologies (eg, cardiac catheterization, angioplasty, or bypass surgery), which evidence suggests are overused.

 The HMO experience suggests that new payment models will likely stimulate the adoption of telemedicine, which has advanced considerably in technical capability since the 1990s, and early evidence suggests that this is the case.

By placing incentives for reduced cost and improved quality in the hands of provider organizations rather than insurers, new payment approaches should help foster the efficient use of telemedicine. Under FFS, payers are often faced with blanket coverage/no coverage decisions for all providers in their network, regardless of whether FFS is being used in an appropriate or inappropriate clinical situation.

Under new payment models, adoption decisions are made by the providers, who have the flexibility to experiment with telemedicine and use the technology in a way that maximizes clinical outcomes and minimizes costs.  We provide 2 examples of how this may happen: videoconferencing for outpatient visits, and home telemonitoring.

Real-time video communication between patient and provider allows for many of the same benefits as an inperson visit, without requiring the patient or provider to travel. This form of telemedicine has been evaluated in research studies for decades, and several studies have shown positive effects on patient outcomes even when low-bandwidth, telephone-based Internet connections reduced the quality of the video image.

 Videoconferencing in the form of visits for new acute problems is often covered by health plans, but use of videoconferencing is uncommon, particularly for chronic illness care, where it may have the most benefit. However, provider systems that have non-FFS payment models are already making extensive use of videoconferencing. In the Veterans Health Administration (VHA), videoconferencing is used routinely to deliver mental health services.

Kaiser, a capitated system that is providing 2.5 million “phone visits”each year, is testing videoconferencing for more general use,

and has made more than 350 after-hours video visits to patients who claim they would have otherwise gone to the emergency department.

As more providers adopt new payment models, they will likely also begin to use videoconferencing. As an early example, the Alternative Quality Contract from Blue Cross Blue Shield uses global payments, and providers under that contract have begun piloting a telemedicine platform that enables videoconferencing visits.

 Because of global payments, the pilot practices will be motivated to prevent overuse, perhaps by triaging patient requests for videoconferences, using some form of co-pay, or making the virtual visit available only to patients for whom a physician believes it would be most beneficial.

Many technologies are available that measure health indicators of patients in their homes and transmit the data to an overseeing provider. The provider, who might be a physician, nurse, social worker, or even a non-clinical staff member, can filter patient questions and report to a clinical team when necessary. Several studies show the potential benefit. In a cardiac study at Partners Healthcare, 3000 congestive health failure patients received in-home monitoring of weight, blood pressure, heart rate, and pulse oximetry. Decision support software helped identify high-risk patients. As a result, readmissions dropped by 44%, saving the health plan $10 million in 6 years.

The VHA also implemented a home telemedicine program in which the more than 17,000 patient participants had a 25% reduction in the number of bed days of care and a 20% reduction in the number of hospital admissions compared with usual care.

As new payment models that reward cost savings spread, providers will have incentives to adopt these home monitoring technologies as part of routine care. Early reports suggest that providers are responding to these incentives: ACOs are planning to use home monitoring to prevent more costly hospital visits or emergency care.

As with virtual visits, the new payment models will encourage telemonitoring to be used only for patients who will likely benefit from the service.

Telemedicine technologies have the potential to benefit patients by increasing access to care, promoting convenience, enhancing quality of healthcare, and reducing costs.

 However, payers and providers are unlikely to support adding telemedicine as a reimbursed service because of its uncertain effect on provider payments and its potential for overuse. Direct reimbursement might still be needed for certain telemedicine services, but such payments will likely be the exception, not the rule. Emerging payment models offer the greatest hope that telemedicine will be widely adopted and used in a way that will make it worth the cost.

 From RAND Corporation, Boston, MA (RSR, DA, AM), and Santa Monica, CA (MZ).

Some of this work was funded by a generous gift from Teletracking, Inc.

The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the content of this paper.

 Concept and design (RSR, DA, AM); acquisition of data (MZ); analysis and interpretation of data (MZ); drafting of the manuscript (RSR, DA, MZ, AM); critical revision of the manuscript for important intellectual content (RSR, DA, MZ); obtaining funding (RSR, DA); administrative, technical, and logistic support (RSR, AM, MZ); and supervision (RSR).

 Robert S. Rudin, PhD, RAND Corporation, 20 Park Plaza, Suite 920, Boston, MA 02116. E-mail: 

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With effective methods of promoting telemedicine yet to be established, new risk-based payment models offer the greatest potential for telemedicine's effective and efficient use.

David Auerbach, PhD

Articles

Provider Type and Management of Common Visits in Primary Care

Paying for Telemedicine