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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="1.3" xml:lang="en" article-type="research-article"><?properties manuscript?><processing-meta base-tagset="archiving" mathml-version="3.0" table-model="xhtml" tagset-family="jats"><restricted-by>pmc</restricted-by></processing-meta><front><journal-meta><journal-id journal-id-type="nlm-journal-id">100894201</journal-id><journal-id journal-id-type="pubmed-jr-id">30234</journal-id><journal-id journal-id-type="nlm-ta">Pain Med</journal-id><journal-id journal-id-type="iso-abbrev">Pain Med</journal-id><journal-title-group><journal-title>Pain medicine (Malden, Mass.)</journal-title></journal-title-group><issn pub-type="ppub">1526-2375</issn><issn pub-type="epub">1526-4637</issn></journal-meta><article-meta><article-id pub-id-type="pmid">35482492</article-id><article-id pub-id-type="pmc">11034837</article-id><article-id pub-id-type="doi">10.1093/pm/pnac068</article-id><article-id pub-id-type="manuscript">HHSPA1972666</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Changes in Opioid Dispensing by Medical Specialties After the Release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain</article-title></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid" authenticated="false">http://orcid.org/0000-0001-8305-9056</contrib-id><name><surname>Salvatore</surname><given-names>Phillip P.</given-names></name><degrees>PhD, SM</degrees><xref rid="A1" ref-type="aff">*</xref><xref rid="A2" ref-type="aff">&#x02020;</xref></contrib><contrib contrib-type="author"><name><surname>Guy</surname><given-names>Gery P.</given-names><suffix>Jr.</suffix></name><degrees>PhD, MPH</degrees><xref rid="A2" ref-type="aff">&#x02020;</xref></contrib><contrib contrib-type="author"><name><surname>Mikosz</surname><given-names>Christina A.</given-names></name><degrees>MD, MPH</degrees><xref rid="A2" ref-type="aff">&#x02020;</xref></contrib></contrib-group><aff id="A1"><label>*</label>Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, Georgia, USA</aff><aff id="A2"><label>&#x02020;</label>Division of Overdose Prevention, National Center for Injury Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia, USA</aff><author-notes><corresp id="CR1"><italic toggle="yes">Correspondence to:</italic> Phillip Salvatore, PhD, SM, Division of Overdose Prevention, Centers for Disease Control and Prevention, 4770 Buford Highway NE, Atlanta, GA 30341, USA. <email>Pgx5@cdc.gov</email>.</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>18</day><month>3</month><year>2024</year></pub-date><pub-date pub-type="ppub"><day>29</day><month>10</month><year>2022</year></pub-date><pub-date pub-type="pmc-release"><day>22</day><month>4</month><year>2024</year></pub-date><volume>23</volume><issue>11</issue><fpage>1908</fpage><lpage>1914</lpage><abstract id="ABS1"><sec id="S1"><title>Objective.</title><p id="P1">To identify changes in opioid prescribing across a diverse array of medical specialties after the release of the 2016 CDC Guideline for Prescribing Opioids for Chronic Pain.</p></sec><sec id="S2"><title>Design.</title><p id="P2">Interrupted time-series analysis of data from a commercial prescribing database.</p></sec><sec id="S3"><title>Subjects.</title><p id="P3">De-identified recipients of opioid prescriptions dispensed at U.S. retail pharmacies between 2015 and 2019.</p></sec><sec id="S4"><title>Methods.</title><p id="P4">Opioid dispensing data were obtained from the IQVIA Longitudinal Prescription (LRx) database, representing more than 800 million opioid prescriptions. Monthly dispensing rates, dosage in morphine milligram equivalents (MME), and mean prescription duration were calculated across 29 medical specialties. Changes in dispensing after the release of the 2016 CDC Guideline were assessed through interrupted time-series analysis.</p></sec><sec id="S5"><title>Results.</title><p id="P5">Declining trends in opioid dispensing accelerated in 24 of 29 specialty groups after the release of the CDC Guideline (<italic toggle="yes">P</italic> &#x0003c; 0.05 for 15 groups). Decreases were greatest among family medicine clinicians, where declines accelerated by 4.4 prescriptions per month per 100,000 persons (<italic toggle="yes">P</italic> = 0.005), and surgeons, where declines accelerated by 3.6 prescriptions per month per 100,000 (<italic toggle="yes">P</italic> = 0.003).</p></sec><sec id="S6"><title>Conclusions.</title><p id="P6">These results illustrate that clinicians likely to provide primary care exhibited the greatest decreases in opioid dispensing. However, specialties outside the scope of the CDC Guideline (e.g., surgery) also exhibited accelerated decreases in prescribing. These declines illustrate that specialties beyond primary care could have interest in evaluating opioid prescribing practices, supporting the importance of specialty-specific guidance that balances the individualized risks and benefits of opioids and the role of non-opioid treatments.</p></sec></abstract><kwd-group><kwd>Opioid</kwd><kwd>Drug Prescription</kwd><kwd>Specialization</kwd><kwd>Physicians&#x02019; Practice Patterns</kwd><kwd>Interrupted Time-Series Analysis</kwd><kwd>Practice Guidelines</kwd></kwd-group></article-meta></front><body><sec id="S7"><title>Introduction</title><p id="P7">Since 1999, almost 500,000 deaths in the United States have resulted from opioid overdoses [<xref rid="R1" ref-type="bibr">1</xref>]. Although prescription opioids can be beneficial, their use can also present serious risks, including overdose and opioid use disorder. In 2019, more than 25% of opioid overdose deaths involved a prescription opioid [<xref rid="R1" ref-type="bibr">1</xref>].</p><p id="P8">Opioid prescribing practices have evolved in recent history. Dispensed opioid prescriptions in the United States increased from 72.4 per 100 persons in 2006 to 81.2 in 2010, when mean morphine milligram equivalents (MME) per capita were four times higher than in 1999 [<xref rid="R2" ref-type="bibr">2</xref>]. This period coincided with increases in rates of opioid overdose deaths [<xref rid="R1" ref-type="bibr">1</xref>], emergency department visits related to opioid use [<xref rid="R3" ref-type="bibr">3</xref>], and opioid use disorder [<xref rid="R4" ref-type="bibr">4</xref>].</p><p id="P9">To provide recommendations for pain management for adults in primary care settings, the U.S. Centers for Disease Control and Prevention (CDC) released in 2016 its Guideline for Prescribing Opioids for Chronic Pain (the CDC Guideline) [<xref rid="R5" ref-type="bibr">5</xref>]. The CDC Guideline provides evidence-based recommendations for the use of opioids in treating chronic pain in primary care settings (excluding cancer and palliative care) for patients 18 years of age and older and aims to improve patient&#x02013;clinician communication about opioid therapy, improve the safety and effectiveness of pain management, and reduce the risks associated with long-term opioid use.</p><p id="P10">Although opioid prescribing began to decline in 2012 [<xref rid="R2" ref-type="bibr">2</xref>], the release of the CDC Guideline has been associated with accelerated temporal declines in opioid prescribing at a national level [<xref rid="R6" ref-type="bibr">6</xref>]. During 2012&#x02013;2016, dispensed opioid prescriptions per 100,000 persons declined at a rate of 23 fewer prescriptions per month; after the release of the CDC Guideline, prescribing declined by 57 fewer prescriptions per month, a statistically significant acceleration [<xref rid="R6" ref-type="bibr">6</xref>]. Although this observation might have been related to secular trends in prescribing, accelerated declines in opioid prescribing exceeded changes in prescribing of other medications (e.g., benzodiazepines) during the same time period [<xref rid="R6" ref-type="bibr">6</xref>]. However, substantial variation exists in opioid prescribing by medical specialty [<xref rid="R7" ref-type="bibr">7</xref>]. During 2016&#x02013;2017, the mean number of prescriptions dispensed was 215 per prescriber but ranged as high as 1,314 prescriptions per pain medicine specialist and as low as 14 prescriptions per pediatrician [<xref rid="R7" ref-type="bibr">7</xref>].</p><p id="P11">To date, the extent of prescribing changes among primary care practitioners (the intended audience of the CDC Guideline) and medical specialists after the release of the CDC Guideline has not been examined. In the assessment of policy change interventions, interrupted time-series analysis offers one of the most robust and commonly used statistical approaches for evaluating temporal changes in aggregate data [<xref rid="R8" ref-type="bibr">8</xref>]. Using interrupted time-series analysis, the present study aims to assess changes in opioid prescribing after the release of the CDC Guideline among medical disciplines likely to practice primary care, as well as among a variety of non&#x02013;primary care specialties.</p></sec><sec id="S8"><title>Methods</title><sec id="S9"><title>Study Sample</title><p id="P12">Opioid dispensing data from the IQVIA Longitudinal Prescription (LRx) database were available for 2015 through 2019. The LRx database is comprised of de-identified transaction-level prescription data capturing 92% of dispensed retail pharmacy prescriptions in the United States (representing more than 800 million opioid prescriptions in the time period examined). All prescriptions from clinicians that could not be classified by practice setting or specialty (e.g., nurse practitioners and physician assistants) were excluded from this analysis (detailed in <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Table S1</xref>), as were all prescriptions for buprenorphine-containing and propoxyphene products.</p></sec><sec id="S10"><title>Measures</title><p id="P13">Prescriber specialty was classified into 29 specialty groups based on similarity of practice (detailed in <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Table S1</xref>). Prescriptions were aggregated by specialty and calendar month to define five measures of opioid dispensing. Total MME for each prescription was calculated as the product of prescription quantity (doses), strength/concentration per dose prescribed, and MME conversion factor [<xref rid="R9" ref-type="bibr">9</xref>]; daily MME was calculated as total MME divided by prescription duration (in days). High-dosage prescriptions were defined as any prescription for which daily MME exceeded 90 [<xref rid="R6" ref-type="bibr">6</xref>]. Total and high-dosage dispensing rates were calculated as the number of prescriptions dispensed each month (standardized to a 30-day month length) divided by monthly U.S. population (per 100,000, estimated from the U.S. Census Bureau [<xref rid="R10" ref-type="bibr">10</xref>]), and mean daily MME and prescription durations were calculated by specialty and month dispensed.</p></sec><sec id="S11"><title>Statistical Analysis</title><p id="P14">Changes in opioid dispensing after publication of the CDC Guideline in March 2016 were assessed through interrupted time-series analysis with segmented regressions [<xref rid="R11" ref-type="bibr">11</xref>], a robust quasi-experimental design for evaluating the temporal impact of interventions without a control group. The pre-Guideline period was defined as January 2015 to February 2016, and the post-Guideline period was defined as March 2016 to December 2019. An interim period was not included, as available data suggested that post-Guideline declines have persisted for several years [<xref rid="R6" ref-type="bibr">6</xref>]. Ordinary least-squares regression was used to fit aggregated outcome measures by month, with additional terms for changes in slope (denoted as &#x003b2;<sub>G</sub>) and intercept after the release of the CDC Guideline (March 2016 to December 2019). Changes in level for each outcome (denoted as &#x00394;&#x003b2;<sub>0</sub>) were calculated as the absolute difference in intercept for the post-Guideline period compared with the pre-Guideline period. Prais-Winsten estimation was used to account for serial autocorrelation. Data preparation and aggregation were performed in SAS version 9.4 (SAS Institute Inc., Cary, NC, USA), and statistical analyses were performed in R version 3.6 (R Core Team, Vienna, Austria). This study was reviewed by the CDC and determined to meet the definition of research as defined in U.S. Department of Health and Human Services (HHS) regulation 45 Code of Federal Regulations (CFR) 46.102(l) but did not involve human subjects as defined in 45 CFR 46.103(e). Thus, institutional review board review was not required.</p></sec></sec><sec id="S12"><title>Results</title><sec id="S13"><title>Population Characteristics</title><p id="P15">From 2015 to 2019, approximately 810 million opioid prescriptions in this database were dispensed to more than 38 million patients each year. After exclusion of prescriptions from clinicians who could not be classified by practice setting or specialty (e.g., nurse practitioners and physician assistants), 654 million dispensed prescriptions remained for analysis (see <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Figure S1</xref>). A plurality of dispensed prescriptions were provided by clinicians in the family medicine category (20&#x02013;23% of prescriptions each year), followed by internal medicine, surgery, and pain medicine (<xref rid="T1" ref-type="table">Table 1</xref>).</p></sec><sec id="S14"><title>Pre-Guideline Prescribing Trends</title><p id="P16">Between January 2015 and February 2016 (before publication of the CDC Guideline), total monthly dispensing exhibited declining trends in 25 of 29 specialties (<italic toggle="yes">P</italic> &#x0003c; 0.05 for 15 of 25; <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Figure S2</xref>), largely mirrored by trends in high-dosage dispensing (24 of 29, <italic toggle="yes">P</italic> &#x0003c; 0.05 for 17 of 24), total monthly MME (25 of 29, <italic toggle="yes">P</italic> &#x0003c; 0.05 for 15 of 25), and mean daily MME (21 of 29, <italic toggle="yes">P</italic> &#x0003c; 0.05 for 11 of 21), illustrated for all outcomes in <xref rid="F2" ref-type="fig">Figure 2</xref>. Initial declines in total monthly dispensing were greatest in family medicine (5.4 fewer prescriptions per month per 100,000) and internal medicine (2.9 fewer prescriptions per month per 100,000), and these trends were paralleled by decreases in other measures of dispensing (<xref rid="F2" ref-type="fig">Figure 2</xref>).</p></sec><sec id="S15"><title>Post-Guideline Prescribing Trends</title><p id="P17">Initial trends in total dispensing rates declined faster after the release of the CDC Guideline in 24 of 29 specialties (<italic toggle="yes">P</italic> &#x0003c; 0.05 for 15 of 24). <xref rid="F1" ref-type="fig">Figure 1</xref> illustrates trends in total dispensing, high-dose dispensing, and total monthly MME for the four specialties in which declines accelerated most after the release of the CDC Guideline. Decreases accelerated most in family medicine (&#x02212;4.41 prescriptions per month per 100,000; <italic toggle="yes">P</italic> = 0.005), surgery (&#x02212;3.57 prescriptions per month per 100,000; <italic toggle="yes">P</italic> = 0.003), and internal medicine (&#x02212;2.75 prescriptions per month per 100,000; <italic toggle="yes">P</italic> = 0.003). Additional notable changes were observed in pain medicine, where declining trends in high-dosage dispensing (&#x02212;0.78 prescriptions per month per 100,000; <italic toggle="yes">P</italic> &#x0003c; 0.001) and total MME (&#x02212;0.05 MME per month; <italic toggle="yes">P</italic> &#x0003c; 0.001) accelerated. Slopes and changes in slope results for all five outcomes are illustrated in <xref rid="F2" ref-type="fig">Figure 2</xref> for each specialty. The greatest declines after the release of the CDC Guideline in average MME per prescription were observed in addiction medicine (&#x02212;1.17 MME per prescription per month, <italic toggle="yes">P</italic> &#x0003c; 0.001), and the greatest declines in average prescription duration were observed in neurology (&#x02212;0.10 days per month, <italic toggle="yes">P</italic> = 0.003).</p><p id="P18">Small but significant increases after the release of the CDC Guideline were observed in occupational medicine for total prescriptions per 100,000 (0.04 more prescriptions per month per 100,000, <italic toggle="yes">P</italic> = 0.007) and in neurology for high-dosage prescriptions (0.001 more prescriptions per month per 100,000, <italic toggle="yes">P</italic> = 0.037) and for total MME (0.001 more MME per month, <italic toggle="yes">P</italic> &#x0003c; 0.001) (<xref rid="F2" ref-type="fig">Figure 2</xref>).</p><p id="P19">In addition to changes in monthly trends after the release of the CDC Guideline (changes in slope), changes in the level of prescribing outcomes (changes in intercept) after the release of the CDC Guideline are presented in <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Table S2</xref>. Prescribing by occupational medicine specialists demonstrated the greatest overall decline across multiple outcomes after the release of the CDC Guideline: total monthly prescriptions per 100,000 (&#x02212;0.89 prescriptions per 100,000, <italic toggle="yes">P</italic> &#x0003c; 0.001), total MME (&#x02212;0.01 MME, <italic toggle="yes">P</italic> = 0.004), and average prescription duration (&#x02212;0.54 days, <italic toggle="yes">P</italic> = 0.32).</p></sec></sec><sec id="S16"><title>Discussion</title><p id="P20">This analysis illustrates temporal trends in opioid dispensing among medical specialties in the periods before and after the release of the 2016 CDC Guideline [<xref rid="R5" ref-type="bibr">5</xref>]. Monthly dispensing rates were declining at the time of the CDC Guideline release [<xref rid="R6" ref-type="bibr">6</xref>], with declines observed across most medical specialties. These results demonstrate that accelerated national declines after the release of the CDC Guideline [<xref rid="R6" ref-type="bibr">6</xref>] were driven largely by declines in primary care specialties (i.e., family practice and internal medicine), those specifically targeted by the CDC Guideline; declines in annual opioid dispensing in these two specialties accounted for 50% of reductions across all specialties after the release of the CDC Guideline.</p><p id="P21">The present report represents the first findings of associations between the release of the CDC Guideline and changes in multiple opioid dispensing characteristics by distinct medical specialties. However, this work builds on other recent studies that have examined the impacts of the CDC Guideline. Declining national trends in opioid prescribing were shown to have accelerated after the release of the CDC Guideline, exceeding changes seen in the prescribing of other medications [<xref rid="R6" ref-type="bibr">6</xref>]. Among opioid-na&#x000ef;ve patients with chronic pain, the duration of initial opioid prescriptions (which had been increasing) began decreasing after the release of the CDC Guideline [<xref rid="R12" ref-type="bibr">12</xref>], as did prescribing of doses of at least 50 MME per day [<xref rid="R13" ref-type="bibr">13</xref>]. As declines observed after the release of the CDC Guideline were similar across patients with different chronic pain indications (e.g., chronic headache and osteoarthritis), questions remain about the tailored patient-specific implementation of the CDC Guideline [<xref rid="R14" ref-type="bibr">14</xref>].</p><p id="P22">Additionally, the present findings indicate that specialties beyond primary care (e.g., surgery) also exhibited accelerated declines after the release of the CDC Guideline. These findings corroborate recent reports about declines in specific disciplines (such as surgery [<xref rid="R15" ref-type="bibr">15</xref>] and emergency medicine [<xref rid="R16" ref-type="bibr">16</xref>]) and expand on these findings by evaluating a wide range of specialties with unique and variable perspectives on the benefit&#x02013;risk balance of opioid prescribing (such as addiction medicine, pain management, palliative care, and hematology/oncology). Collectively, these findings suggest that although the CDC Guideline was targeted specifically to primary care practitioners, clinicians in other specialties might have implemented aspects of the CDC Guideline intended for primary care settings (as the result of changes in individual prescribing or health system changes reinforcing the CDC Guideline [<xref rid="R13" ref-type="bibr">13</xref>]), resulting in concurrent accelerated declines. Alternatively, this could indicate that the CDC Guideline and other efforts at that time aimed at curbing excessive opioid prescribing and reducing opioid overdoses might have prompted specialists to independently reexamine their prescribing practices. This highlights the importance of specialty-specific guidance for opioid prescribing.</p><p id="P23">The analyses presented here have limitations. These data capture only prescriptions dispensed from retail pharmacies but do not capture mail-order, long-term care prescriptions, prescriptions dispensed from federally funded facilities (e.g., facilities affiliated with the Indian Health Service or Department of Veterans Affairs), or prescriptions that were written but not filled. Also excluded from this analysis were prescriptions from clinicians for whom a medical specialty could not be categorized (e.g., nurse practitioners and physician assistants), accounting for approximately 19% of dispensed opioid prescriptions. Although a majority of nurse practitioners and physician assistants practice specialties providing primary care [<xref rid="R17" ref-type="bibr">17</xref>, <xref rid="R18" ref-type="bibr">18</xref>], they constitute a minority of all primary care practitioners [<xref rid="R19" ref-type="bibr">19</xref>] and might be unlikely to impact the direction of primary results observed. These data do not capture patient-level indicators, such as the clinical indications for a prescription or whether a patient took a full prescription when dispensed. In the absence of clinical indications, it is not possible to ascertain whether the reductions observed were due to decreases in non&#x02013;evidence-based prescribing. Additionally, these analyses use ecological data to evaluate temporal trends; observed changes in opioid dispensing after March 2016 could be the result of a variety of factors in addition to (or separate from) the CDC Guideline, such as increased attention to opioid prescribing at the federal, state, and local levels during this period. Without a concurrent control group for comparison, this analysis cannot exclude the potential association between secular factors in prescribing trends and the results observed here. Such secular factors could include concurrent changes in opioid policies, such as increased resources funded through the 21<sup>st</sup> Century Cures Act (December 2016) and increased utilization of prescription drug monitoring programs (available in all states by April 2017). Therefore, these results should not be viewed as causal, as historical biases and other trends might have contributed to the differences observed. Finally, this study did not examine trends in non-opioid or nonpharmacological treatments for pain, and therefore it could not assess whether decreases in opioid dispensing were offset by increases in other modalities for adequate pain management.</p></sec><sec id="S17"><title>Conclusions</title><p id="P24">These findings serve to further contextualize changes in national opioid prescribing after the release of the CDC Guideline. This analysis offers evidence that declining trends in opioid dispensing accelerated among specialties likely to provide primary care, the intended audience of the CDC Guideline. These results also suggest that specialties beyond primary care also experienced accelerated declines in opioid dispensing after the release of the CDC Guideline, underscoring the importance of specialty-specific translation materials and trainings. Clinical management of pain requires integrated care, and use of prescription opioids should be based on an individualized assessment that balances the potential risks and benefits of opioid use along with other pain treatment modalities. The CDC Guideline provides a framework to support primary care practitioners in providing optimal care.</p></sec><sec sec-type="supplementary-material" id="SM1"><title>Supplementary Material</title><supplementary-material id="SD1" position="float" content-type="local-data"><label>Supplementary Data</label><media xlink:href="NIHMS1972666-supplement-Supplementary_Data.docx" id="d66e396" position="anchor"/></supplementary-material></sec></body><back><ack id="S18"><title>Funding sources:</title><p id="P25">No funding sources to declare for this report.</p></ack><fn-group><fn fn-type="COI-statement" id="FN1"><p id="P26">Conflicts of interest and financial disclosure: All authors report no conflict of interest. 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<hr/>
</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">Unique patients, n</td><td align="center" valign="bottom" rowspan="1" colspan="1">51,839,740</td><td align="center" valign="bottom" rowspan="1" colspan="1">50,396,992</td><td align="center" valign="bottom" rowspan="1" colspan="1">47,194,550</td><td align="center" valign="bottom" rowspan="1" colspan="1">42,167,675</td><td align="center" valign="bottom" rowspan="1" colspan="1">38,785,488</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Median patient age, years (IQR)</td><td align="center" valign="top" rowspan="1" colspan="1">50 (34&#x02013;63)</td><td align="center" valign="top" rowspan="1" colspan="1">51(35&#x02013;64)</td><td align="center" valign="top" rowspan="1" colspan="1">52 (36&#x02013;65)</td><td align="center" valign="top" rowspan="1" colspan="1">53 (37&#x02013;66)</td><td align="center" valign="top" rowspan="1" colspan="1">54 (38&#x02013;67)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Prescriptions dispensed by clinician specialty,* n (% of year)</td><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/><td align="center" valign="top" rowspan="1" colspan="1"/></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Addiction medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">102,028 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">78,116 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">64,049 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">54,340 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">44,697 (0)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Allergy and immunology</td><td align="center" valign="bottom" rowspan="1" colspan="1">61,265 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">54,803 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">45,401 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">38,519 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">29,817(0)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Anesthesiology</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,897,660 (2.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,878,812 (2.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,833,182 (2.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,703,532 (3.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,515,705 (3.4)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Cardiology</td><td align="center" valign="bottom" rowspan="1" colspan="1">650,224 (0.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">574,224 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">490,889 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">393,354 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">324,330 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Dentist</td><td align="center" valign="bottom" rowspan="1" colspan="1">11,006,821 (5.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">10,509,265 (5.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">9,591,642 (5.8)</td><td align="center" valign="bottom" rowspan="1" colspan="1">8,071,631 (5.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">6,912,110 (5.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Emergency medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">9,941,826 (5.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">8,662,408 (4.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">7,009,580 (4.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">5,339,165 (3.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">4,621,728 (3.5)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Endocrinology</td><td align="center" valign="bottom" rowspan="1" colspan="1">181,765 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">156,568 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">127,774 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">101,395 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">80,045 (0.1)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Family medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">43,187,701 (23.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">40,140,352 (22.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">36,378,414 (22)</td><td align="center" valign="bottom" rowspan="1" colspan="1">31,124,681 (21.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">27,193,125 (20.3)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Gastroenterology/hepatology</td><td align="center" valign="bottom" rowspan="1" colspan="1">481,785 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">427,948 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">366,848 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">316,932 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">271,648 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Infectious disease</td><td align="center" valign="bottom" rowspan="1" colspan="1">283,830 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">248,764 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">213,224 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">177,130 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">153,016 (0.1)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Internal medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">26,172,276 (14.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">24,344,359 (13.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">22,075,183 (13.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">19,040,633 (13)</td><td align="center" valign="bottom" rowspan="1" colspan="1">16,886,394 (12.6)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Nephrology</td><td align="center" valign="bottom" rowspan="1" colspan="1">492,609 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">438,449 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">384,979 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">310,639 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">256,108 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Neurology</td><td align="center" valign="bottom" rowspan="1" colspan="1">26,835 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">22,021 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">19,796 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">17,867 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">15,934 (0)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;OB/GYN</td><td align="center" valign="bottom" rowspan="1" colspan="1">3,659,783 (2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">3,453,439 (1.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">3,078,663 (1.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,671,186 (1.8)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,352,254 (1.8)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Occupational medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">303,899 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">244,420 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">195,519 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">162,524 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">125,450 (0.1)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Oncology and/or hematology</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,508,954 (1.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,427,626 (1.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,308,691 (1.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,131,539 (1.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,992,104 (1.5)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Ophthalmology</td><td align="center" valign="bottom" rowspan="1" colspan="1">317,540 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">296,553 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">272,670 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">239,229 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">207,136 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Other</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,921,288 (1.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,713,280 (1.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,426,311 (1.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,089,162 (1.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,855,075 (1.4)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Pain medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">10,893,243 (5.9)</td><td align="center" valign="bottom" rowspan="1" colspan="1">11,210,359 (6.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">11,198,678 (6.8)</td><td align="center" valign="bottom" rowspan="1" colspan="1">10,684,290 (7.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">9,990,168 (7.5)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Palliative care</td><td align="center" valign="bottom" rowspan="1" colspan="1">183,298 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">184,893 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">194,245 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">216,435 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">234,174 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Pediatric hematology/oncology</td><td align="center" valign="bottom" rowspan="1" colspan="1">39,280 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">37,815 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">36,228 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">33,716 (0)</td><td align="center" valign="bottom" rowspan="1" colspan="1">33,376 (0)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Pediatric subspecialties (other)</td><td align="center" valign="bottom" rowspan="1" colspan="1">186,226 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">161,269 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">135,974 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">106,905 (0.1)</td><td align="center" valign="bottom" rowspan="1" colspan="1">87,751 (0.1)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Pediatrics</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,094,021 (0.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">987,990 (0.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">873,785 (0.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">744,626 (0.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">657,573 (0.5)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Physical medicine and rehabilitation</td><td align="center" valign="bottom" rowspan="1" colspan="1">6,389,513 (3.4)</td><td align="center" valign="bottom" rowspan="1" colspan="1">6,240,101 (3.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">5,941,914 (3.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">5,467,999 (3.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">5,067,217(3.8)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Podiatry</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,372,353 (0.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,308,946 (0.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,191,054 (0.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,033,757 (0.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">949,606 (0.7)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Psychiatry</td><td align="center" valign="bottom" rowspan="1" colspan="1">405,023 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">350,577 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">306,935 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">251,830 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">208,384 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Pulmonary / critical care medicine</td><td align="center" valign="bottom" rowspan="1" colspan="1">487,556 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">448,233 (0.3)</td><td align="center" valign="bottom" rowspan="1" colspan="1">387,558 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">309,139 (0.2)</td><td align="center" valign="bottom" rowspan="1" colspan="1">265,839 (0.2)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Rheumatology</td><td align="center" valign="bottom" rowspan="1" colspan="1">3,032,587(1.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,803,972 (1.6)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,545,385 (1.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">2,237,216 (1.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">1,971,806 (1.5)</td></tr><tr><td align="left" valign="bottom" rowspan="1" colspan="1">&#x02003;Surgery</td><td align="center" valign="bottom" rowspan="1" colspan="1">23,783,222 (12.8)</td><td align="center" valign="bottom" rowspan="1" colspan="1">22,658,351 (12.7)</td><td align="center" valign="bottom" rowspan="1" colspan="1">20,685,321 (12.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">18,296,381 (12.5)</td><td align="center" valign="bottom" rowspan="1" colspan="1">16,810,191 (12.5)</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p id="P33">IQR = interquartile range.</p></fn><fn id="TFN2"><p id="P34">Clinician specialty groups are detailed in <xref rid="SD1" ref-type="supplementary-material">Supplementary Data Table S1</xref>.</p></fn></table-wrap-foot></table-wrap></floats-group></article>