- Email: [email protected]
Medicaid caseload for pediatric oral health care
Original Contributions
Medicaid caseload for pediatric oral health care Nicoleta Serban, PhD; Christopher Bush, BA; Scott L. Tomar, DMD, MPH, DrPH ABSTRACT Background. The authors’ aims were to compare, according to strata, dentists’ participation in Medicaid and Medicaid provider-level caseload measured as the number of patients or visits for preventive or restorative care for 2 comparison years. Methods. The data sources were the 2012-2013 Medicaid Analytic eXtract claims and 2013 National Plan and Provider Enumeration System data sets. The authors measured Medicaid participation as the proportion of dentists participating in Medicaid among those in the National Plan and Provider Enumeration System. The authors measured provider-level caseload according to the number of patients or visits. The authors stratified oral health care providers according to state; whether practicing in rural, suburban, or urban communities; and provider type. Results. The differences in participation rates for rural versus suburban and versus urban communities ranged from 4% through 27% and 6% through 37%, respectively. The 2012 state median number of patients per provider for preventive care ranged from 99 through 358. The provider-level caseload increased from rural to urban and from other provider to general dentist to pediatric dentist. The difference in caseload from 2012 to 2013 was not statistically significant except for the pediatric dentist type. Conclusions. This study’s results suggest that the realized caseload for children enrolled in Medicaid varies according to provider type and urbanicity. The state median caseload for preventive care is lower than the 500:1 patient to provider ratio used as the minimum caseload in access estimates from other studies. Practical Implications. This study’s results can assist states in gauging the level of oral health care provided to children insured by Medicaid compared with that in other states, with implications for the specification of oral health policies. Key Words. Dental care caseload; children insured by Medicaid; state variations; access to oral health care. JADA 2019:150(4):294-304 https://doi.org/10.1016/j.adaj.2018.11.020
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esearch on estimating potential access to oral health care for children with public health insurance in the United States (including Medicaid and the Children’s Health Insurance Program [CHIP]) has pointed to a major challenge in measuring accessdspecifically, the specification of the caseload of oral health care providers dedicated to children with public insurance.1-3 The American Dental Association Health Policy Institute (ADA-HPI) has released a report providing estimated Medicaid participation rates by state.4 However, participation according to the ADA-HPI means that a dentist participates in Medicaid if he or she simply is included in the InsureKidsNow.gov database. Investigators in a follow-up research study discussed the level of accuracy of the ADA-HPI’s analysis, pointing out that the data sources available to derive estimated participation of dentists in Medicaid are unreliable.3 They also highlighted the need to examine other measures of provider participation. For example, 1 operational definition of Medicaid participation could be based on a minimum number of children enrolled in Medicaid who are treated by an oral health care provider, such as a minimum caseload of 50 or 100 patients. Ultimately, such measures account for a minimum caseload before considering a provider as participating in public insurance programs and reflect actual clinical engagement by the provider. JADA 150(4)
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The caseload of oral health care providers devoted to children enrolled in Medicaid or CHIP is not only important in providing a more meaningful measure of participation in Medicaid or CHIP but also in providing an accurate estimate of access to oral health care for children who are publicly insured. The most recent state-level access estimates reported by ADA-HPI5 have assumed generic caseload levels for all oral health care providers, regardless of the provider type (for example, general dentists versus pediatric dentists) or location of the dentist’s practice (for example, urban versus rural location). As shown in those reports, potential access can vary significantly depending on the assumed caseload level. For example, for North Carolina, the ADA-HPI reported that 90% of children live within 15 minutes’ travel time to a dentist reported as participating in Medicaid. However, assuming that a dentist’s caseload of children enrolled in Medicaid or CHIP is 500 patients per year, only 42% live within 15 minutes of a participating dentistdless than one-half of the initial estimate.6 Using Medicaid Analytic eXtract (MAX) claims data, we provide in this study a detailed analysis of provider-level outcomes, including Medicaid participation measured according to the proportion of oral health care providers participating in Medicaid recorded in the National Plan and Provider Enumeration System (NPPES) database and provider-level caseload measured according to the number of children enrolled in Medicaid for whom preventive and restorative oral health care claims have been billed and the number of visits by children enrolled in Medicaid within 1 year. We stratified the oral health care providers according to state; whether the practice address was in a rural, suburban, or urban community (urbanicity level); and provider type. We also considered 2 years of data for consistency of the results. We compared the stratified measures across 39 states, which we selected because these states’ claims data provided accurate information about the identification of the oral health care providers needed to derive the caseload measures of interest. Although investigators in other studies have investigated the state-level participation of dentists in Medicaid,3,4 to our knowledge, our study is the first known provider-level analysis of Medicaid caseload with comparison across multiple states and for multiple types of oral health care providers. Medicaid participation and provider-level caseload together can be used to measure geographic access to oral health care accurately and inform policies and interventions for children enrolled in Medicaid. METHODS Data sources The main data source was the 2012-2013 MAX medical claims data acquired from the Centers for Medicare & Medicaid Services (CMS) and consisted of identifiable individual-level claims data for all beneficiaries enrolled in Medicaid. For 2012, we considered data from 39 states, excluding Arizona, California, Florida, Hawaii, Idaho, Michigan, Missouri, North Dakota, Pennsylvania, South Carolina, and South Dakota. The primary exclusion criterion was insufficient provider-level data in the Medicaid claims for the purposes of this study. For 2013, we considered data from 20 states; we included those states because of data availability and sufficient provider-level data. Although we have a reduced number of states, we included 2013 in the analysis to assess the difference in caseload between 2012 and 2013. We obtained institutional review board approval at Georgia Institute of Technology, Atlanta, Georgia, for this research under protocol H11287. All data derived from the MAX files meet a minimum cell size of 11 of patients according to the Data Use Agreement with CMS. The second data source was the 2013 NPPES, consisting of publicly available provider-specific information. NPPES provides detailed information about all health care providers in the United States by using their reported National Provider Identifier (NPI), including billing and service address, taxonomy, and entity. Study population The study population consisted of all beneficiaries aged 0 through 18 years enrolled in the Medicaid program. This population was in the selected states in 2012 and 2013. Service provider identification and stratification We identified the service providers by using the following process. First, we identified the NPIs of all oral health care providers with the taxonomy codes (provided in the Appendix, available online at JADA 150(4)
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ABBREVIATION KEY ADA- American Dental HPI: Association Health Policy Institute. CHIP: Children’s Health Insurance Program. CMS: Centers for Medicare & Medicaid Services. MAX: Medicaid Analytic eXtract. NA: Not applicable. NPI: National Provider Identifier. NPPES: National Plan and Provider Enumeration System. RUCC: Rural-Urban Continuum Code.
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Table 1. Dental care provider participation in children’s state Medicaid programs, according to state, year, provider type, and urbanicity of practice location.* STATE† AND YEAR
OVERALL PARTICIPATION RATE BASED ON MEDICAID CLAIMS
Including All Providers with a Claim, %
Including Providers with a Claim for 11 or More Patients, %
AK 2012
24
35
AL 2012
18
20
AR 2012 AR 2013
PARTICIPATION RATE ACCORDING TO ADA-HPI,‡ %
PROVIDER TYPE
URBANICITY
General Dentists, %
Pediatric Dentists, %
Other Providers, %
Rural, %
Suburban, %
Urban, %
43
26
48
12
32
27
21
74
18
43
8
41
31
15
16 17
30 35
4 5
24 27
24 28
11 11
§
15 17
25 29
NA 61
CO 2012
8
10
53
9
28
3
7
7
8
CT 2012 CT 2013
13 18
18 24
NA 46
14 15
46 48
6 6
9 10
12 12
13 15
DE 2012
21
28
55
24
48
6
0
0
21
GA 2012 GA 2013
14 16
16 17
NA 28
14 14
44 43
7 7
22 22
24 23
13 13
IA 2012 IA 2013
22 24
30 32
NA 86
23 23
57 55
9 9
30 34
29 29
18 17
IL 2012
11
13
30
12
16
1
10
11
11
IN 2012 IN 2013
21 22
37 28
NA 50
20 20
75 50
10 10
31 37
25 24
20 19
KS 2012
12
14
26
12
42
5
21
14
10
KY 2012
20
23
39
22
40
8
44
24
16
LA 2012 LA 2013
22 26
26 43
NA 43
23 25
56 61
8 8
44 50
29 32
21 23
MA 2012 MA 2013
10 12
12 15
NA 39
11 12
30 30
3 3
13 11
6 7
9 9
MD 2012
14
23
25
15
60
3
0
24
14
ME 2012
11
14
42
12
57
6
14
15
13
MN 2012 MN 2013
15 17
26 27
NA 69
17 16
48 46
5 4
29 32
22 21
14 13
MS 2012 MS 2013
26 28
40 32
55 NA
28 27
51 48
7 8
41 42
27 27
21 20
MT 2012
19
30
72
22
42
7
24
19
18
NC 2012
17
21
27
17
50
8
21
24
16
NE 2012
13
27
61
14
44
3
19
12
12
NH 2012
9
17
45
9
46
4
15
13
9
NJ 2012 NJ 2013
8 10
10 13
24 NA
8 9
28 27
3 3
7 7
7 8
8 9
NM 2012
20
25
53
22
64
7
30
17
20
NV 2012
10
23
42
9
58
2
39
15
10
NY 2012 NY 2013
13 15
19 20
NA 38
14 14
34 35
6 6
18 18
15 19
13 13
OH 2012 OH 2013
13 14
15 16
NA 20
13 13
45 44
4 4
26 27
18 19
12 12
* All reported participation rates are based on providers who submitted claims for 11 or more patients during that calendar year. The only exceptions are the participation rates in the column that includes overall rates based on providers with at least 1 claim and the participation rates in the “Participation Rate According to ADA-HPI” column. † Two-letter US zip code abbreviations are used for state names. ‡ ADA-HPI: American Dental Association-Health Policy Institute. Estimates from American Dental Association Health Policy Institute.4 § NA: Not applicable.
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Table 1. Continued STATE† AND YEAR
OVERALL PARTICIPATION RATE BASED ON MEDICAID CLAIMS
Including All Providers with a Claim, %
Including Providers with a Claim for 11 or More Patients, %
OK 2012 OK 2013
30 21
39 24
OR 2012 OR 2013
11 12
RI 2012
PARTICIPATION RATE ACCORDING TO ADA-HPI,‡ %
PROVIDER TYPE
URBANICITY
General Dentists, %
Pediatric Dentists, %
Other Providers, %
Rural, %
Suburban, %
Urban, %
NA 52
32 19
75 41
7 5
36 21
40 24
27 16
16 17
39 NA
13 13
42 42
1 1
13 15
14 13
10 10
8
18
45
7
49
6
0
0
6
TN 2012 TN 2013
17 18
19 20
NA 35
17 18
44 46
12 12
33 31
23 23
16 17
TX 2012
19
21
48
20
43
5
20
19
19
UT 2012 UT 2013
12 13
18 20
NA 60
11 11
51 57
2 3
24 23
20 19
11 11
VA 2012
6
7
31
7
17
3
15
16
6
VT 2012 VT 2013
26 33
33 39
NA 76
27 28
89 89
14 13
27 26
25 24
27 28
WA 2012 WA 2013
20 15
30 18
NA 29
22 14
83 48
4 3
56 36
29 19
19 12
WI 2012
9
15
36
9
42
3
19
13
7
WV 2012 WV 2013
32 35
37 40
NA 71
34 34
67 67
15 14
40 43
41 40
29 29
WY 2012 WY 2013
28 36
41 50
73 NA
30 32
40 40
7 4
39 39
19 22
18 18
the end of this article) in the NPPES data for the states in this study. Second, for all oral health care claims with a procedure code provided in eTables 1 and 2 (available online at the end of this article) and for the study population, we checked the Service Provider Identification Number to match a valid NPI from the NPPES database. If that criterion was not met, we then checked the Billing Provider Identification Number, and, finally, we checked the NPI data field to match to a valid NPI from the NPPES database. The outcome of this procedure was a set of valid NPIs corresponding to the oral health care claims for the study population. We joined the set of unique NPIs for providers who delivered preventive or restorative oral health care identified in the MAX files with NPPES data to examine NPI-specific stratifications, including provider entity, taxonomy, urbanicity of practice business address, and state. According to NPPES, entity 1 corresponded to individual oral health care providers, whereas entity 2 indicated group providers. Providers were able to list multiple taxonomies to describe their business. To ensure that this study included only oral health care providers, we selected only providers who listed any of the oral health care taxonomies as their primary or secondary taxonomy. We classified the provider types into 3 groups: pediatric dentist, general dentist, and other oral health care providers. We used the Rural-Urban Continuum Codes7 (RUCCs) to determine whether the county of the provider’s address provided in the NPPES database was urban (RUCCs 1, 2, and 3), suburban (RUCCs 4, 5, and 6), or rural (RUCCs 7, 8, 9, and 10). We used RUCCs because they have been developed to differentiate urban (not necessarily metropolitan areas) from suburban and rural communities. We derived the stratifications only for providers with 11 or more patients with oral health care claims reported in the MAX data. Provider-level caseload: number of patients and visits We considered multiple claims for the same type of dental service (preventive or restorative) in a single day for the same provider and for the same child enrolled in Medicaid as 1 oral health care visit. JADA 150(4)
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After the aggregation of claims into visits for restorative and preventive oral health care, we identified the number of patients and visits per unique NPI in each state. We considered a patient with at least 1 claim under the preventive or restorative care designation a patient of that type of care. Outcome measures The outcome measures of interest were n Medicaid participation measured according to the proportion of oral health care providers identified with reimbursed Medicaid claims for children among the providers recorded in the NPPES; n provider-level caseload measured according to the number of patients and number of visits per year per provider with unique NPIs, differentiated into preventive and restorative care. We stratified the outcomes according to state, provider type (general dentist, pediatric dentist, and other provider), and urbanicity of the recorded practice address (urban, suburban, and rural). We also differentiated the outcomes for 2012 and for 2013. Statistical analysis All statistical statements for the hypothesis testing procedures are provided at the significance level of a set to .01. In cases of multiple comparison, we used the Bonferroni correction for multiplicity. When comparing percentages or proportions, we performed the test of equal proportions by assuming binomial distribution. When comparing medians, we used the Wilcoxon rank-sum test. RESULTS Service provider identification and stratification: Medicaid participation outcome Table 14 presents the percentage for the oral health care providers identified in the 2012 and 2013 MAX claims data of all oral health care providers within each state. For comparison, we added the participation rates estimated by the ADA-HPI. We also added the providers with fewer than 11 patients in the overall column. All other columns do not include these providers because we cannot report provider-detailed data on providers with fewer than 11 patients. The results from this table4 are n the difference between the overall and the overall with fewer than 11 patients ranged from 1% (Georgia 2013) through 17% (Louisiana 2013); n across all states, the ADA-HPI estimate was larger than the participation estimates derived from the claims data. The difference between the ADA-HPI rates and those based on MAX claims for at least 11 patients ranged from 7% (Ohio) through 64% (Iowa). All differences were statistically significant (P z 0); n the difference in participation rate between general and pediatric dentists was statistically significant except for Illinois, ranging from 4% (Illinois) through 62% (Vermont). Other oral health care providers had a participation rate from 1% (Illinois) through 15% (West Virginia), but the rate generally was lower than 10%; n except for Maryland, which had no providers in rural communities, the difference in participation for rural versus suburban communities ranged from 4% through 27%. Except for Delaware, which had no providers in rural or suburban communities, the difference in participation for rural versus urban communities ranged from 6% through 37%, with only 7 states having lower participation in rural communities than in urban communities. The difference between urban and suburban was statistically significant for 15 states; n comparing the participation estimates from the claims data for 2012 and 2013, we found most differences were less than 5 percentage points, with some exceptions; Louisiana and Utah had a 5 to 6 percentage point increase, and Indiana experienced a 25% decrease in participation for pediatric dentists from 2012 through 2013. Moreover, Oklahoma and Washington had significantly lower participation from 2012 through 2013 across all types of providers and urbanicity. The differences were statistically significant, except for those for Arkansas, Georgia, and Louisiana. Provider-level caseload outcomes: state stratification Table 2 provides the state-level median number of patients and of visits per provider, estimated as the median value across all provider capacities within a state. The results from this table are 298
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Table 2. State-level capacity: median number of dental visits and patients across all providers participating in Medicaid (except those with fewer than 11 patients) within each state according to year.* STATE†
2012
2013
Median No. of Median No. Median No. Median No. Median No. Median No. Median No. Median No. Preventive Care of Preventive of Restorative of Restorative of Preventive of Preventive of Restorative of Restorative Patients per Care Visits per Care Patients Care Visits per Care Patients Care Visits per Care Patients Care Visits Provider Provider per Provider Provider per Provider Provider per Provider per Provider AK
270
903
130
409
NA‡
NA
NA
NA
AL
155
538
76
213
NA
NA
NA
NA
AR
141
453
64
207
109
353
52
162
CO
118
364
46
143
NA
NA
NA
NA
CT
124
424
55
177
128
415
43
135
DE
117
474
51
146
NA
NA
NA
NA
GA
214
759
71
200
170
670
68
193
IA
332
1,048
116
324
302
953
116
311
IL
227
783
81
249
NA
NA
NA
NA
IN
203
684
72
198
115
436
43
110
KS
200
681
73
218
NA
NA
NA
NA
KY
150
564
63
184
NA
NA
NA
NA
LA
141
485
55
169
155
558
63
191
MA
171
651
63
175
183
606
76
215
MD
217
675
102
309
NA
NA
NA
NA
ME
153
487
66
193
NA
NA
NA
NA
MN
191
779
67
180
161
582
61
164
MS
99
358
39
114
175
524
69
182
MT
215
642
72
183
110
330
39
97
NC
116
353
48
140
NA
NA
NA
NA
NE
164
489
58
159
NA
NA
NA
NA
NH
142
837
45
227
NA
NA
NA
NA
NJ
115
615
43
192
NA
NA
NA
NA
NM
218
815
98
279
NA
NA
NA
NA
NV
150
634
56
189
NA
NA
NA
NA
NY
148
491
58
170
163
566
63
173
OH
113
344
42
107
139
447
51
139
OK
124
382
45
119
148
454
52
131
OR
206
741
76
247
242
832
92
267
RI
271
902
83
234
NA
NA
NA
NA
TN
181
596
71
225
237
751
89
267
TX
208
787
83
270
NA
NA
NA
NA
UT
337
1,563
131
537
230
712
95
315
VA
358
1,901
131
518
NA
NA
NA
NA
VT
326
1,639
126
567
161
419
64
154
WA
321
1,670
122
484
192
648
68
181
WI
126
420
46
135
NA
NA
NA
NA
WV
107
375
50
169
195
704
69
180
WY
160
545
66
169
167
563
64
205
* The capacity is differentiated for preventive and restorative services. † Two-letter US zip code abbreviations are used for state names. ‡ NA: Not applicable.
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in 2012, the median number of patients and visits per provider for preventive care ranged from 99 (Mississippi) through 358 (Virginia) and from 344 (Ohio) through 1,901 (Virginia), respectively; n in 2012, the median number of patients and of visits per provider for restorative care ranged from 39 (Mississippi) through 131 (Utah and Virginia) and from 107 (Ohio) through 567 (Vermont), respectively; n in 2012, the caseload for preventive care was statistically significantly higher than for restorative care overall (P z 0), with a difference ranging from 65 through 441 visits per provider; n one-half of the states with 2013 data had a median caseload for preventive and restorative care that was higher in 2013 than in 2012. Vermont had a significant decrease in realized caseload in 2013. The difference in medians between the 2 years across all states was statistically significant only for Louisiana restorative care; Minnesota preventive care; and New York, Oklahoma, and Washington for both types of care (eTable 3, available online at the end of this article). eFigures 1 and 2 (available online at the end of this article) display box plots of the provider-level caseload in number of patients and of visits stratified according to state. The box plots in these figures show not only the wide variation in the median caseload but also the skewedness of the distributions with long right tails, corresponding to providers with higher caseloads. n
Provider-level caseload outcome: urbanicity and provider-type stratification Figure 1 presents the distribution box plots of the provider-level caseload in number of visits according to urbanicity and type of provider. eFigure 3 (available online at the end of this article) presents the same caseload distributions as histograms. eFigure 4 (available online at the end of this article) presents the same box plots and histograms but for caseload in numbers of patients. The results from these figures are n across both strata, the distribution of the provider-level caseload was skewed with a long right tail. Although there were many providers with a low Medicaid caseload, there also were some providers with a large caseload; not all such providers were in the category of entity 2 (group providers) of the provider’s NPI; n comparing the distributions across different levels of urbanicity specified by providers’ practice address according to NPPES, we found that the provider-level caseload increased with the level of urbanicity for both restorative and preventive care (P z 0 for the Wilcoxon rank-sum test of equal medians). The increase was similar for the number of visits and for the number of patients. Comparing the distributions across different provider types, specified by providers’ taxonomy according to NPPES, we found that the provider-level caseload was more than twice as high for general dentists as for other providers (including mostly dental specialists) and more than twice as high for pediatric dentists as for general dentists. The differences were larger for the number of visits than for the number of patients. Figure 2 compares the distributions of the provider-level caseload measured according to the number of preventive oral health care visits for 2012 and 2013, urbanicity level, and provider type. eFigure 5 (available online at the end of this article) presents the same caseload distributions as the histograms. eFigure 6 (available online at the end of this article) compares the provider-level caseload according to state. n The distributions according to urbanicity and provider type had similar shape, median, and spread for the 2 years. The test of the null hypothesis of equal medians, using the Wilcoxon rank-sum test with Bonferroni correction for multiplicity, showed that the difference in medians between the 2 years across all groups in the urbanicity and provider type strata was not statistically significant except for the difference in provider-level caseload for pediatric dentists (P z 0). n The distributions of the provider-level caseloads were different across the states. DISCUSSION In our study, we provide a multistate analysis of the Medicaid caseload of providers who can deliver oral health care services for children. To our knowledge, this is the first such study in which investigators examined Medicaid caseload at the provider level. A first important observation is that the estimated Medicaid participation rates were significantly lower than those ADA-HPI previously reported. One primary reason for this difference is a much larger denominator in the participation rates provided in our study. We considered the universe of all oral health care providers with an NPI, although a proportion of the providers were inactive. For 300
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3,500
NUMBER OF VISITS
3,000 2,500 2,000 1,500 1,000 500 0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN SUBURBAN PREVENTIVE RESTORATIVE TYPE OF URBANICITY
URBAN PREVENTIVE
GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER OTHER RESTORATIVE PREVENTIVE TYPE OF PROVIDER
PEDIATRIC PREVENTATIVE
A
URBAN RESTORATIVE
5,000
NUMBER OF VISITS
4,000 3,000 2,000 1,000 0
B
PEDIATRIC RESTORATIVE
Figure 1. Box plots of the provider-level capacity measured according to the number of visits, for preventive and restorative care separately, and according to urbanicity (A) and type of provider (B). We have reduced the y axis such that approximately 7% to 8% of outlying observations with a large number of patients are excluded.
example, we identified 6,148 oral health care providers in Georgia in the 2012 NPPES database; in contrast, results of a survey by the Georgia Dental Association8 indicated there were 5,881 dentists, among whom only 4,044 reportedly were active. Although for some states the difference in participation rates may be explained by the larger number of providers in the denominator of the participation rates provided by our study, the difference between our rates and those provided by the ADA-HPI are much larger than may be explained by only that factor. Another important finding was the difference in participation rates calculated by limiting the numerator to providers who saw 11 or more patients within the calendar year compared with the estimate based on including providers who accepted fewer than 11 patients. That difference suggests that although some providers accept patients enrolled in Medicaid, their realized caseload is too small to be counted as such. This finding aligns with the recommendation of using multiple measures to impose a minimum caseload to deem a provider as participating in Medicaid, particularly accounting for how extensively dentists treated beneficiaries enrolled in Medicaid.3 Our study fills the gap in stipulating access standards and in deriving access estimates by providing insights on the realized caseload of oral health care providers according to state, provider type, and urbanicity. Investigators in a 2017 study identified New Jersey as being at a lower bound in mandating a 500:1 enrollee to dentist provider ratio in its Medicaid program, whereas other states JADA 150(4)
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NUMBER OF VISITS
4,000
3,000
2,000
1,000
0 RURAL 2012
RURAL 2013
SUBURBAN 2012 SUBURBAN 2013 TYPE OF URBANICITY AND YEAR
URBAN 2012
URBAN 2013
GENERAL DENTIST 2012
GENERAL DENTIST 2013
OTHER OTHER PROVIDER 2012 PROVIDER 2013 TYPE OF PROVIDER AND YEAR
PEDIATRIC DENTISTRY 2012
PEDIATRIC DENTISTRY 2013
A 5,000
NUMBER OF VISITS
4,000 3,000 2,000 1,000 0
B
Figure 2. Box plots of the provider-level capacity for preventive care comparing 2012 (blue box plots) and 2013 (green box plots) according to urbanicity (A) and type of provider (B). We have reduced the y axis such that approximately 7% to 8% of outlying observations with a large number of patients are excluded.
mandate a ratio as high as 2,000:1.9 The ADA-HPI has provided access estimates for varying ratios, assuming a 500:1 patient to provider ratio as the lower bound and unlimited caseload as the upper bound.5 These bounds assume that the Medicaid caseload is the same across all oral health care providers and that on average an oral health care provider will see as many as 500 or more children insured by Medicaid in his or her practice. In contrast to these assumptions, we found that none of the states had a median realized caseload as high as 500 pediatric patients enrolled in Medicaid per provider. Another important finding relevant to estimation of the potential access to oral health care is the wide variation across the strata considered in this study: state, provider type, and urbanicity. We identified a clear trend in the caseload with respect to provider type, with pediatric dentists having the largest caseload, followed by general dentists and then specialists and other licensed professionals. To our knowledge, investigators in only 1 study to date have taken into consideration the provider type in estimating access.10 We also identified substantive differences in caseload across states. The ADA-HPI state reports assumed that all providers have the same caseload regardless of their taxonomy or state. We also found a trend in Medicaid caseload across urbanicity levels of the provider’s business practice address, with practices in urban areas having larger caseload followed by suburban and then by rural areas. This trend, however, may be driven by demand rather than the potential caseload of the oral health care providers. 302
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There are several data limitations in our study. The primary data source used in this analysis consists of claims data submitted by state Medicaid agencies. One limitation of our study is that some claims may not be filed, resulting in a potential underreporting bias of the providers’ caseloads. It is unclear whether some prevention initiatives, such as school-based sealant programs, file claims for services rendered; CMS form 416dused by the ADA-HPI reportdis filed by states to CMS and may include adjustments for these interventions. MAX files may be incomplete, especially for states with large managed care populations.11 Another study limitation is inherent in the NPPES database, the data source that provided the practice and provider characteristics of the oral health care providers included in our study. Although it has been mandatory to enter an NPI for all providers submitting for reimbursements since 2009, there still may be oral health care providers without an NPI, particularly those who provide oral health care within a large group practice. In addition, there may be a large proportion of inactive providers with an NPI. Consequently, the denominator in the Medicaid participation rates may be larger than the actual number of providers, resulting in lower estimated rates of Medicaid participation. Finally, some providers may not have updated their practice address information in the NPPES database. Our definition of preventive dental services included several Current Dental Terminology codes typically classified as diagnostic services, such as D0120 (routine oral evaluation) and D0150 (comprehensive oral evaluation).12 Our rationale was that diagnostic services are an essential part of a preventive visit, even if no other service is delivered. The net effect of including diagnostic codes in our definition of preventive care is more inclusive counting of patients receiving preventive care and visits per provider. Consequently, our calculated caseloads probably err toward more generous estimates of preventive care per provider. CONCLUSIONS Findings from this study suggest that the realized oral health care caseload for children enrolled in Medicaid varies greatly across providers, with some consistent trends across different provider types and urbanicity of the providers’ practices. Although we captured only realized caseload, with the potential caseload being possibly larger, it is still informative in the specification of the providers’ caseloads in potential access estimates for children insured by Medicaid. Investigators in a 2018 study used the realized caseload to specify whether a provider had a low or high Medicaid caseload, and, on this basis, they considered additional excess caseload to specify potential caseload more accurately.10 Differences in how various state Medicaid programs are administered along with state policies on supervision of licensed providers and on reimbursement may affect providers’ Medicaid caseloads greatly and may explain partially the wide variations across states. Thus, this study’s results can assist states in gauging the level of oral health care provided to children insured by Medicaid in comparison with that of other states, with implications for the specification of access standards and oral health policies. n SUPPLEMENTAL DATA Supplemental data related to this article can be found at: https://doi.org/10.1016/j.adaj.2018.11.020.
Dr. Serban is a professor, School of Industrial & Systems Engineering, Georgia Institute of Technology, 765 Ferst St, Atlanta, GA 30332-0205, e-mail [email protected]. Address correspondence to Dr. Serban. Mr. Bush is an undergraduate research assistant, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA. Dr. Tomar is a professor, Department of Community Dentistry and Behavioral Science, University of Florida, CITY, FL. Disclosure. None of the authors reported any disclosures.
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Financial support for this study was provided by Award R01DE028283 from the National Institute of Dental and Craniofacial Research, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The authors are thankful to Richard Starr in assisting with data safeguards and the information technology infrastructure.
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1. American Dental Association Health Policy Institute. Webinars: measuring what matters: a new way of measuring geographic access to dental care services. Available at: https://www.ada.org/en/science-research/health-policyinstitute/publications/webinars/measuring-access-todental-care-in-every-state. Accessed December 12, 2018. 2. Serban N, Tomar SL. ADA Health Policy Institute’s methodology overestimates spatial access to dental care for publicly insured children. J Public Health Dent. 2018; 78(4):291-295. 3. Warder CJ, Edelstein BL. Evaluating levels of dentist participation in Medicaid. JADA. 2016;148(1): 26-32. 4. American Dental Association Health Policy Institute. The oral health care system: a state by state analysis. 2015. Available at: https://www.ada.org/en/science-research/
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health-policy.../oral-health-care-system. Accessed January 1, 2019. 5. American Dental Association Health Policy Institute. Geographic access to dental care. Available at: https://www.ada.org/en/science-research/health-policyinstitute/geographic-access-to-dental-care. Accessed December 12, 2018. 6. Vujicic M. A new way to measure geographic access to dentists in North Carolina. N C Med J. 2017;78(3): 391-392. 7. Morrill R, Cromartie J, Hart G. Metropolitan, urban, and rural commuting areas: toward a better depiction of the United States settlement system. Urban Geogr. 1999; 20(8):727-748. 8. Georgia Health Policy Center. A study of Georgia’s dental workforce 2012. Available at: https://ghpc.gsu.edu/
download/a-study-of-georgias-dental-workforce-2012-8/. Accessed December 12, 2018. 9. Nasseh K, Eisenberg Y, Vujicic M. Geographic access to dental care varies in Missouri and Wisconsin. J Public Health Dent. 2017;77(3):197-206. 10. Cao S, Gentili M, Griffin P, Griffin S, Serban N. Disparities in access to preventive dental care between publicly and privately insured children in Georgia. Prev Chronic Dis. 2018;14:170-176. 11. Byrd VL, Dodd AH. Assessing the usability of MAX 2008 encounter data for comprehensive managed care. Medicare Medicaid Res Rev. 2013;3(1):pii:mmrr.003.01. b01. 12. American Dental Association. CDT 2013. Dental Procedure Codes. Chicago, IL: American Dental Association; 2012.
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APPENDIX
The following list consists of all dental care provider taxonomies specified in the National Plan and Provider Enumeration System database. Along with the taxonomy, we also provided information about the grouping into pediatric dentist, general dentist, specialist, and other licensed professional. For ease of data visualization and analysis, we collapsed 2 of the provider groups, specialist and other licensed professional, into 1 group: other providers. However, our current implementation allows a more granular analysis. Advanced practice dental therapistd125K00000X (other licensed professional) Dental assistantd126800000X (other licensed professional) Dental hygienistd124Q00000X (other licensed professional) Dental laboratory techniciand126900000X (other licensed professional) Dental therapistd125J00000X (other licensed professional) Dentistd122300000X (general dentist) Dental public healthd1223D0001X (other licensed professional) Dentist anesthesiologistd1223D0004X (specialist) Endodonticsd1223E0200X (specialist) General practiced1223G0001X (general dentist) Oral and maxillofacial pathologyd1223P0106X (specialist) Oral and maxillofacial radiologyd1223X0008X (specialist) Oral and maxillofacial surgeryd1223S0112X (specialist) Orthodontics and dentofacial orthopedicsd1223X0400X (specialist) Pediatric dentistryd1223P0221X (pediatric dentistry) Periodonticsd1223P0300X (specialist) Prosthodonticsd1223P0700X (specialist) Denturistd122400000X (other licensed professional) Oral medicinistd125Q00000X (other licensed professional) We chose these taxonomies because they represent the types of providers from whom children enrolled in the Medicaid program would receive preventive or restorative care.
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eTable 1. Restorative dental care procedures used to define restorative care visits.* CODE12
DESCRIPTION
D2140
Amalgamd1 surface
D2150
Amalgamd2 surfaces
D2160
Amalgamd3 surfaces
D2161
Amalgamd4 or more surfaces
D2330
Resind1 surface
D2331
Resind2 surfaces
D2332
Resind3 surfaces
D2335
Resind4 or more surfaces or involving incisal angle (anterior)
D2391
Resin-based composited1 surface
D2392
Resin-based composited2 surfaces
D2393
Resin-based composited3 surfaces
D2394
Resin-based composited4 or more surfaces
D2751
Crowndporcelain fused to predominantly base metal
D2791
Crowndfull cast predominantly base metal
D2930
Prefabricated stainless steel crowndprimary tooth
D2931
Prefabricated stainless steel crowndpermanent tooth
D2932
Prefabricated resin crown
D2933
Prefabricated stainless steel crown with resin window
D2934
Prefabricated esthetic coated stainless steel crowndprimary tooth
D2940
Sedative filling
D2954
Prefabricated post and core in addition to crown
D3110
Pulp capddirect (excluding final restoration)
D3120
Pulp capdindirect (excluding final restoration)
D3220
Therapeutic pulpotomy (excluding final restoration) removal of pulp coronal to the dentinocemental junction and application of medicament
D3221
Pulpal debridement
D3230
Pulpal therapy (resorbable filling)danterior restoration
D3240
Pulpal therapy (resorbable filling)dposterior restoration
D3310
Endodontic therapy
D3320
Endodontic therapy
D3330
Endodontic therapy
D7111
Extraction
D7140
Extraction
D7210
Surgical removal of erupted tooth requiring elevation of mucoperiosteal flap and removal of bone or section of tooth
D7220
Removal of impacted toothdsoft tissue
D7230
Removal of impacted toothdpartially bony
D7240
Removal of impacted toothdcompletely bony
D7250
Surgical removal of residual tooth roots (cutting procedure)
* One visit can include 1 or more such procedures.
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eTable 2. Preventive dental care procedures used to define preventive care visits.* CODE12
DESCRIPTION
Topical Fluoride D1201
Topical application of fluoride (including prophylaxis)dchild
D1203
Topical fluoride for primary dentition
D1204
Topical fluoride for mixed and adult dentition
D1205
Topical application of fluoride (including prophylaxis)dadult
D1206
Topical fluoride varnish
D1208
Topical application of fluoride
Evaluation and Examination D0120
Periodic oral evaluationdestablished patient
D0140
Limited oral evaluationdproblem focused
D0145
Oral evaluation for a patient younger than 3 years and counseling with primary caregiver
D0150
Comprehensive oral evaluationdnew or established patient
D0160
Detailed and extensive evaluation
D0170
Reevaluationdlimited, problem focused (established patient; not postoperative visit)
D0180
Comprehensive periodontal evaluation
Pit-and-Fissure Sealant Application D1351
Sealantdper tooth
D1352
Preventive resin restoration in a patient with moderate to high caries riskdpermanent tooth
Prophylaxis D1110
Prophylaxisdadult
D1120
Prophylaxisdchild
* One visit can include 1 or more such procedures.
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eTable 3. P values for the hypothesis testing procedure for comparing the median of the capacity for 2012 and 2013 differentiated according to type of care. STATE†
RESTORATIVE CARE No. of Visits
PREVENTIVE CARE
No. of Patients
No. of Visits
No. of Patients
AR
.0227
.0393
.0826
.0412
CT
.9700
.5960
.0661
.1468
GA
.1350
.5452
.5766
.6110
IA
.0018
.5677
.3468
.6304
IN
.1445
.0591
.1337
.0223
LA
.0034
.0021*
.0061
.0022*
MA
.2935
.4211
.3282
.6230
MN
0*
.3529
0*
.6985
MS
.6306
.5199
.6134
.6932
NJ
.9981
.7397
.7625
.6825
NY
0*
0*
0*
0*
OH
.9227
.4401
.3540
.1816
OK
0*
0*
0*
0*
OR
.3212
.2094
.4758
.3794
TN
.0798
.4463
0
.5108
UT
.3597
.2989
.3281
.7421
VA
.3945
.4122
.8876
.7975
VT
.3945
.4122
.8876
.7975
WA
0*
0*
0*
0*
WV
.9843
.8883
.8908
.8760
WY
.5078
.4167
.5459
.4705
* Significant at the .05 level with Bonferroni correction for multiplicity. † Two-letter US zip code abbreviations are used for state names.
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1,200
NUMBER OF PATIENTS
1,000
800
600
400
200
Y O H O K O R
RI TN
TX U T VA
VT W A W I W V W Y
RI TN
TX U T VA
VT W A W I W V W Y
V
N
N N
V N Y O H O K O R
N J N M N J N M
E
N M S M T N C N E N H
M
M
A
D
M
LA
M
KS KY
IL IN
IA
CT D E G A
A
K A L A R CO
0
STATE
A 500
NUMBER OF PATIENTS
400
300
200
100
B
LA M A M D M E M N M S M T N C N E N H
KS KY
IN
IL
IA
CT D E G A
A
K A L A R CO
0
STATE
eFigure 1. Box plots show the provider caseload according to state expressed in the number of patients in preventive care (A) and restorative care (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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5,000
NUMBER OF VISITS
4,000
3,000
2,000
1,000
TX U T VA
VT W A W I W V W Y
T VA
VT W A W I W V W Y
TN
LA M A M D M E M N M S M T N C N E N H N J N M N V N Y O H O K O R RI
KS KY
IL
IN
CT D E G A IA
A
K A L A R CO
0
STATE
A 2,000
NUMBER OF VISITS
1,500
1,000
500
B
U
TX
RI TN
Y O H O K O R
V
N
N
N J N M
LA M A M D M E M N M S M T N C N E N H
KS KY
IL IN
IA
CT D E G A
A
K A L A R CO
0
STATE
eFigure 2. Box plots show the provider caseload according to state expressed in the number of visits for preventive care (A) and restorative care (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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200 SUBURBAN RESTORATIVE
400
600
URBAN PREVENTIVE
URBAN RESTORATIVE 60
TOTAL NUMBER OF PATIENTS, %
50 40 30 20 10 0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN PREVENTIVE
60 50 40 30 20 10 0 200
400
600
A
200
400
600
NUMBER OF PATIENTS 200 OTHER RESTORATIVE
400
600
PEDIATRIC PREVENTIVE
PEDIATRIC RESTORATIVE
TOTAL NUMBER OF PATIENTS, %
60 40 20 0 GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER PREVENTIVE
60 40 20 0 200
400
600
B
200
400
600
NUMBER OF PATIENTS
eFigure 3. Histograms of the provider caseload measured according to the number of visits, for preventive and restorative care separately, and according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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NUMBER OF PATIENTS
800
600
400
200
0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN SUBURBAN PREVENTIVE RESTORATIVE TYPE OF URBANICITY
URBAN PREVENTIVE
URBAN RESTORATIVE
GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER OTHER PREVENTIVE RESTORATIVE TYPE OF PROVIDER
PEDIATRIC PREVENTIVE
PEDIATRIC RESTORATIVE
A 1,200
NUMBER OF PATIENTS
1,000 800 600 400 200 0
B
eFigure 4. Box plots show the provider caseload measured according to the number of patients for preventive and restorative care separately and according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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1,000 SUBURBAN 2013
2,000
3,000
4,000
URBAN 2012
URBAN 2013
TOTAL NUMBER OF VISITS, %
40 30 20 10 RURAL 2012
RURAL 2013
0
SUBURBAN 2012
40 30 20 10 0 1,000
2,000
3,000
4,000
A
1,000
2,000
3,000
4,000
NUMBER OF VISITS 1,000 OTHER PROVIDER 2013
2,000
3,000
4000
PEDIATRIC DENTISTRY 2012
PEDIATRIC DENTISTRY 2013 80
TOTAL NUMBER OF VISITS, %
60 40 20 0 GENERAL DENTIST 2012
GENERAL DENTIST 2013
OTHER PROVIDER 2012
80 60 40 20 0 1,000
2,000
3,000
4,000
B
1,000
2,000
3,000
4,000
NUMBER OF VISITS
eFigure 5. Histograms of the provider-level capacity for preventive care comparing 2012 and 2013 according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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NUMBER OF PATIENTS
1,500
1,000
500
A R1 A 2 R1 3 CT 12 CT 1 G 3 A 1 G 2 A 13 IA 12 IA 13 IN 12 IN 13 LA 12 LA 1 M 3 A 1 M 2 A 1 M 3 N 1 M 2 N 1 M 3 S1 M 2 S1 3 N J1 2 N J1 N 3 Y1 N 2 Y1 O 3 H 1 O 2 H 1 O 3 K1 O 2 K1 O 3 R1 O 2 R1 TN 3 1 TN 2 1 U 3 T1 U 2 T1 3 VT 12 VT 1 W 3 A 1 W 2 A 1 W 3 V1 W 2 V1 W 3 Y1 W 2 Y1 3
0
STATE AND YEAR
A 6,000
NUMBER OF VISITS
5,000 4,000 3,000 2,000 1,000
A
R1 A 2 R1 3 CT 12 CT 1 G 3 A 12 G A 13 IA 12 IA 13 IN 12 IN 13 LA 12 LA 1 M 3 A 1 M 2 A 1 M 3 N 12 M N 1 M 3 S1 M 2 S1 N 3 J1 2 N J1 3 N Y1 N 2 Y1 O 3 H 1 O 2 H 13 O K1 O 2 K1 O 3 R1 O 2 R1 TN 3 1 TN 2 1 U 3 T1 U 2 T1 3 VT 12 VT 1 W 3 A 1 W 2 A 1 W 3 V1 W 2 V1 W 3 Y1 W 2 Y1 3
0
B
STATE AND YEAR
eFigure 6. Box plots of the provider caseload according to state expressed in the number of patients (A) and the number of visits (B) for all types of care (preventive and restorative) comparing 2012 (blue bars) and 2013 (green bars). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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Medicaid caseload for pediatric oral health care Nicoleta Serban, PhD; Christopher Bush, BA; Scott L. Tomar, DMD, MPH, DrPH ABSTRACT Background. The authors’ aims were to compare, according to strata, dentists’ participation in Medicaid and Medicaid provider-level caseload measured as the number of patients or visits for preventive or restorative care for 2 comparison years. Methods. The data sources were the 2012-2013 Medicaid Analytic eXtract claims and 2013 National Plan and Provider Enumeration System data sets. The authors measured Medicaid participation as the proportion of dentists participating in Medicaid among those in the National Plan and Provider Enumeration System. The authors measured provider-level caseload according to the number of patients or visits. The authors stratified oral health care providers according to state; whether practicing in rural, suburban, or urban communities; and provider type. Results. The differences in participation rates for rural versus suburban and versus urban communities ranged from 4% through 27% and 6% through 37%, respectively. The 2012 state median number of patients per provider for preventive care ranged from 99 through 358. The provider-level caseload increased from rural to urban and from other provider to general dentist to pediatric dentist. The difference in caseload from 2012 to 2013 was not statistically significant except for the pediatric dentist type. Conclusions. This study’s results suggest that the realized caseload for children enrolled in Medicaid varies according to provider type and urbanicity. The state median caseload for preventive care is lower than the 500:1 patient to provider ratio used as the minimum caseload in access estimates from other studies. Practical Implications. This study’s results can assist states in gauging the level of oral health care provided to children insured by Medicaid compared with that in other states, with implications for the specification of oral health policies. Key Words. Dental care caseload; children insured by Medicaid; state variations; access to oral health care. JADA 2019:150(4):294-304 https://doi.org/10.1016/j.adaj.2018.11.020
R
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esearch on estimating potential access to oral health care for children with public health insurance in the United States (including Medicaid and the Children’s Health Insurance Program [CHIP]) has pointed to a major challenge in measuring accessdspecifically, the specification of the caseload of oral health care providers dedicated to children with public insurance.1-3 The American Dental Association Health Policy Institute (ADA-HPI) has released a report providing estimated Medicaid participation rates by state.4 However, participation according to the ADA-HPI means that a dentist participates in Medicaid if he or she simply is included in the InsureKidsNow.gov database. Investigators in a follow-up research study discussed the level of accuracy of the ADA-HPI’s analysis, pointing out that the data sources available to derive estimated participation of dentists in Medicaid are unreliable.3 They also highlighted the need to examine other measures of provider participation. For example, 1 operational definition of Medicaid participation could be based on a minimum number of children enrolled in Medicaid who are treated by an oral health care provider, such as a minimum caseload of 50 or 100 patients. Ultimately, such measures account for a minimum caseload before considering a provider as participating in public insurance programs and reflect actual clinical engagement by the provider. JADA 150(4)
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The caseload of oral health care providers devoted to children enrolled in Medicaid or CHIP is not only important in providing a more meaningful measure of participation in Medicaid or CHIP but also in providing an accurate estimate of access to oral health care for children who are publicly insured. The most recent state-level access estimates reported by ADA-HPI5 have assumed generic caseload levels for all oral health care providers, regardless of the provider type (for example, general dentists versus pediatric dentists) or location of the dentist’s practice (for example, urban versus rural location). As shown in those reports, potential access can vary significantly depending on the assumed caseload level. For example, for North Carolina, the ADA-HPI reported that 90% of children live within 15 minutes’ travel time to a dentist reported as participating in Medicaid. However, assuming that a dentist’s caseload of children enrolled in Medicaid or CHIP is 500 patients per year, only 42% live within 15 minutes of a participating dentistdless than one-half of the initial estimate.6 Using Medicaid Analytic eXtract (MAX) claims data, we provide in this study a detailed analysis of provider-level outcomes, including Medicaid participation measured according to the proportion of oral health care providers participating in Medicaid recorded in the National Plan and Provider Enumeration System (NPPES) database and provider-level caseload measured according to the number of children enrolled in Medicaid for whom preventive and restorative oral health care claims have been billed and the number of visits by children enrolled in Medicaid within 1 year. We stratified the oral health care providers according to state; whether the practice address was in a rural, suburban, or urban community (urbanicity level); and provider type. We also considered 2 years of data for consistency of the results. We compared the stratified measures across 39 states, which we selected because these states’ claims data provided accurate information about the identification of the oral health care providers needed to derive the caseload measures of interest. Although investigators in other studies have investigated the state-level participation of dentists in Medicaid,3,4 to our knowledge, our study is the first known provider-level analysis of Medicaid caseload with comparison across multiple states and for multiple types of oral health care providers. Medicaid participation and provider-level caseload together can be used to measure geographic access to oral health care accurately and inform policies and interventions for children enrolled in Medicaid. METHODS Data sources The main data source was the 2012-2013 MAX medical claims data acquired from the Centers for Medicare & Medicaid Services (CMS) and consisted of identifiable individual-level claims data for all beneficiaries enrolled in Medicaid. For 2012, we considered data from 39 states, excluding Arizona, California, Florida, Hawaii, Idaho, Michigan, Missouri, North Dakota, Pennsylvania, South Carolina, and South Dakota. The primary exclusion criterion was insufficient provider-level data in the Medicaid claims for the purposes of this study. For 2013, we considered data from 20 states; we included those states because of data availability and sufficient provider-level data. Although we have a reduced number of states, we included 2013 in the analysis to assess the difference in caseload between 2012 and 2013. We obtained institutional review board approval at Georgia Institute of Technology, Atlanta, Georgia, for this research under protocol H11287. All data derived from the MAX files meet a minimum cell size of 11 of patients according to the Data Use Agreement with CMS. The second data source was the 2013 NPPES, consisting of publicly available provider-specific information. NPPES provides detailed information about all health care providers in the United States by using their reported National Provider Identifier (NPI), including billing and service address, taxonomy, and entity. Study population The study population consisted of all beneficiaries aged 0 through 18 years enrolled in the Medicaid program. This population was in the selected states in 2012 and 2013. Service provider identification and stratification We identified the service providers by using the following process. First, we identified the NPIs of all oral health care providers with the taxonomy codes (provided in the Appendix, available online at JADA 150(4)
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ABBREVIATION KEY ADA- American Dental HPI: Association Health Policy Institute. CHIP: Children’s Health Insurance Program. CMS: Centers for Medicare & Medicaid Services. MAX: Medicaid Analytic eXtract. NA: Not applicable. NPI: National Provider Identifier. NPPES: National Plan and Provider Enumeration System. RUCC: Rural-Urban Continuum Code.
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Table 1. Dental care provider participation in children’s state Medicaid programs, according to state, year, provider type, and urbanicity of practice location.* STATE† AND YEAR
OVERALL PARTICIPATION RATE BASED ON MEDICAID CLAIMS
Including All Providers with a Claim, %
Including Providers with a Claim for 11 or More Patients, %
AK 2012
24
35
AL 2012
18
20
AR 2012 AR 2013
PARTICIPATION RATE ACCORDING TO ADA-HPI,‡ %
PROVIDER TYPE
URBANICITY
General Dentists, %
Pediatric Dentists, %
Other Providers, %
Rural, %
Suburban, %
Urban, %
43
26
48
12
32
27
21
74
18
43
8
41
31
15
16 17
30 35
4 5
24 27
24 28
11 11
§
15 17
25 29
NA 61
CO 2012
8
10
53
9
28
3
7
7
8
CT 2012 CT 2013
13 18
18 24
NA 46
14 15
46 48
6 6
9 10
12 12
13 15
DE 2012
21
28
55
24
48
6
0
0
21
GA 2012 GA 2013
14 16
16 17
NA 28
14 14
44 43
7 7
22 22
24 23
13 13
IA 2012 IA 2013
22 24
30 32
NA 86
23 23
57 55
9 9
30 34
29 29
18 17
IL 2012
11
13
30
12
16
1
10
11
11
IN 2012 IN 2013
21 22
37 28
NA 50
20 20
75 50
10 10
31 37
25 24
20 19
KS 2012
12
14
26
12
42
5
21
14
10
KY 2012
20
23
39
22
40
8
44
24
16
LA 2012 LA 2013
22 26
26 43
NA 43
23 25
56 61
8 8
44 50
29 32
21 23
MA 2012 MA 2013
10 12
12 15
NA 39
11 12
30 30
3 3
13 11
6 7
9 9
MD 2012
14
23
25
15
60
3
0
24
14
ME 2012
11
14
42
12
57
6
14
15
13
MN 2012 MN 2013
15 17
26 27
NA 69
17 16
48 46
5 4
29 32
22 21
14 13
MS 2012 MS 2013
26 28
40 32
55 NA
28 27
51 48
7 8
41 42
27 27
21 20
MT 2012
19
30
72
22
42
7
24
19
18
NC 2012
17
21
27
17
50
8
21
24
16
NE 2012
13
27
61
14
44
3
19
12
12
NH 2012
9
17
45
9
46
4
15
13
9
NJ 2012 NJ 2013
8 10
10 13
24 NA
8 9
28 27
3 3
7 7
7 8
8 9
NM 2012
20
25
53
22
64
7
30
17
20
NV 2012
10
23
42
9
58
2
39
15
10
NY 2012 NY 2013
13 15
19 20
NA 38
14 14
34 35
6 6
18 18
15 19
13 13
OH 2012 OH 2013
13 14
15 16
NA 20
13 13
45 44
4 4
26 27
18 19
12 12
* All reported participation rates are based on providers who submitted claims for 11 or more patients during that calendar year. The only exceptions are the participation rates in the column that includes overall rates based on providers with at least 1 claim and the participation rates in the “Participation Rate According to ADA-HPI” column. † Two-letter US zip code abbreviations are used for state names. ‡ ADA-HPI: American Dental Association-Health Policy Institute. Estimates from American Dental Association Health Policy Institute.4 § NA: Not applicable.
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Table 1. Continued STATE† AND YEAR
OVERALL PARTICIPATION RATE BASED ON MEDICAID CLAIMS
Including All Providers with a Claim, %
Including Providers with a Claim for 11 or More Patients, %
OK 2012 OK 2013
30 21
39 24
OR 2012 OR 2013
11 12
RI 2012
PARTICIPATION RATE ACCORDING TO ADA-HPI,‡ %
PROVIDER TYPE
URBANICITY
General Dentists, %
Pediatric Dentists, %
Other Providers, %
Rural, %
Suburban, %
Urban, %
NA 52
32 19
75 41
7 5
36 21
40 24
27 16
16 17
39 NA
13 13
42 42
1 1
13 15
14 13
10 10
8
18
45
7
49
6
0
0
6
TN 2012 TN 2013
17 18
19 20
NA 35
17 18
44 46
12 12
33 31
23 23
16 17
TX 2012
19
21
48
20
43
5
20
19
19
UT 2012 UT 2013
12 13
18 20
NA 60
11 11
51 57
2 3
24 23
20 19
11 11
VA 2012
6
7
31
7
17
3
15
16
6
VT 2012 VT 2013
26 33
33 39
NA 76
27 28
89 89
14 13
27 26
25 24
27 28
WA 2012 WA 2013
20 15
30 18
NA 29
22 14
83 48
4 3
56 36
29 19
19 12
WI 2012
9
15
36
9
42
3
19
13
7
WV 2012 WV 2013
32 35
37 40
NA 71
34 34
67 67
15 14
40 43
41 40
29 29
WY 2012 WY 2013
28 36
41 50
73 NA
30 32
40 40
7 4
39 39
19 22
18 18
the end of this article) in the NPPES data for the states in this study. Second, for all oral health care claims with a procedure code provided in eTables 1 and 2 (available online at the end of this article) and for the study population, we checked the Service Provider Identification Number to match a valid NPI from the NPPES database. If that criterion was not met, we then checked the Billing Provider Identification Number, and, finally, we checked the NPI data field to match to a valid NPI from the NPPES database. The outcome of this procedure was a set of valid NPIs corresponding to the oral health care claims for the study population. We joined the set of unique NPIs for providers who delivered preventive or restorative oral health care identified in the MAX files with NPPES data to examine NPI-specific stratifications, including provider entity, taxonomy, urbanicity of practice business address, and state. According to NPPES, entity 1 corresponded to individual oral health care providers, whereas entity 2 indicated group providers. Providers were able to list multiple taxonomies to describe their business. To ensure that this study included only oral health care providers, we selected only providers who listed any of the oral health care taxonomies as their primary or secondary taxonomy. We classified the provider types into 3 groups: pediatric dentist, general dentist, and other oral health care providers. We used the Rural-Urban Continuum Codes7 (RUCCs) to determine whether the county of the provider’s address provided in the NPPES database was urban (RUCCs 1, 2, and 3), suburban (RUCCs 4, 5, and 6), or rural (RUCCs 7, 8, 9, and 10). We used RUCCs because they have been developed to differentiate urban (not necessarily metropolitan areas) from suburban and rural communities. We derived the stratifications only for providers with 11 or more patients with oral health care claims reported in the MAX data. Provider-level caseload: number of patients and visits We considered multiple claims for the same type of dental service (preventive or restorative) in a single day for the same provider and for the same child enrolled in Medicaid as 1 oral health care visit. JADA 150(4)
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After the aggregation of claims into visits for restorative and preventive oral health care, we identified the number of patients and visits per unique NPI in each state. We considered a patient with at least 1 claim under the preventive or restorative care designation a patient of that type of care. Outcome measures The outcome measures of interest were n Medicaid participation measured according to the proportion of oral health care providers identified with reimbursed Medicaid claims for children among the providers recorded in the NPPES; n provider-level caseload measured according to the number of patients and number of visits per year per provider with unique NPIs, differentiated into preventive and restorative care. We stratified the outcomes according to state, provider type (general dentist, pediatric dentist, and other provider), and urbanicity of the recorded practice address (urban, suburban, and rural). We also differentiated the outcomes for 2012 and for 2013. Statistical analysis All statistical statements for the hypothesis testing procedures are provided at the significance level of a set to .01. In cases of multiple comparison, we used the Bonferroni correction for multiplicity. When comparing percentages or proportions, we performed the test of equal proportions by assuming binomial distribution. When comparing medians, we used the Wilcoxon rank-sum test. RESULTS Service provider identification and stratification: Medicaid participation outcome Table 14 presents the percentage for the oral health care providers identified in the 2012 and 2013 MAX claims data of all oral health care providers within each state. For comparison, we added the participation rates estimated by the ADA-HPI. We also added the providers with fewer than 11 patients in the overall column. All other columns do not include these providers because we cannot report provider-detailed data on providers with fewer than 11 patients. The results from this table4 are n the difference between the overall and the overall with fewer than 11 patients ranged from 1% (Georgia 2013) through 17% (Louisiana 2013); n across all states, the ADA-HPI estimate was larger than the participation estimates derived from the claims data. The difference between the ADA-HPI rates and those based on MAX claims for at least 11 patients ranged from 7% (Ohio) through 64% (Iowa). All differences were statistically significant (P z 0); n the difference in participation rate between general and pediatric dentists was statistically significant except for Illinois, ranging from 4% (Illinois) through 62% (Vermont). Other oral health care providers had a participation rate from 1% (Illinois) through 15% (West Virginia), but the rate generally was lower than 10%; n except for Maryland, which had no providers in rural communities, the difference in participation for rural versus suburban communities ranged from 4% through 27%. Except for Delaware, which had no providers in rural or suburban communities, the difference in participation for rural versus urban communities ranged from 6% through 37%, with only 7 states having lower participation in rural communities than in urban communities. The difference between urban and suburban was statistically significant for 15 states; n comparing the participation estimates from the claims data for 2012 and 2013, we found most differences were less than 5 percentage points, with some exceptions; Louisiana and Utah had a 5 to 6 percentage point increase, and Indiana experienced a 25% decrease in participation for pediatric dentists from 2012 through 2013. Moreover, Oklahoma and Washington had significantly lower participation from 2012 through 2013 across all types of providers and urbanicity. The differences were statistically significant, except for those for Arkansas, Georgia, and Louisiana. Provider-level caseload outcomes: state stratification Table 2 provides the state-level median number of patients and of visits per provider, estimated as the median value across all provider capacities within a state. The results from this table are 298
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Table 2. State-level capacity: median number of dental visits and patients across all providers participating in Medicaid (except those with fewer than 11 patients) within each state according to year.* STATE†
2012
2013
Median No. of Median No. Median No. Median No. Median No. Median No. Median No. Median No. Preventive Care of Preventive of Restorative of Restorative of Preventive of Preventive of Restorative of Restorative Patients per Care Visits per Care Patients Care Visits per Care Patients Care Visits per Care Patients Care Visits Provider Provider per Provider Provider per Provider Provider per Provider per Provider AK
270
903
130
409
NA‡
NA
NA
NA
AL
155
538
76
213
NA
NA
NA
NA
AR
141
453
64
207
109
353
52
162
CO
118
364
46
143
NA
NA
NA
NA
CT
124
424
55
177
128
415
43
135
DE
117
474
51
146
NA
NA
NA
NA
GA
214
759
71
200
170
670
68
193
IA
332
1,048
116
324
302
953
116
311
IL
227
783
81
249
NA
NA
NA
NA
IN
203
684
72
198
115
436
43
110
KS
200
681
73
218
NA
NA
NA
NA
KY
150
564
63
184
NA
NA
NA
NA
LA
141
485
55
169
155
558
63
191
MA
171
651
63
175
183
606
76
215
MD
217
675
102
309
NA
NA
NA
NA
ME
153
487
66
193
NA
NA
NA
NA
MN
191
779
67
180
161
582
61
164
MS
99
358
39
114
175
524
69
182
MT
215
642
72
183
110
330
39
97
NC
116
353
48
140
NA
NA
NA
NA
NE
164
489
58
159
NA
NA
NA
NA
NH
142
837
45
227
NA
NA
NA
NA
NJ
115
615
43
192
NA
NA
NA
NA
NM
218
815
98
279
NA
NA
NA
NA
NV
150
634
56
189
NA
NA
NA
NA
NY
148
491
58
170
163
566
63
173
OH
113
344
42
107
139
447
51
139
OK
124
382
45
119
148
454
52
131
OR
206
741
76
247
242
832
92
267
RI
271
902
83
234
NA
NA
NA
NA
TN
181
596
71
225
237
751
89
267
TX
208
787
83
270
NA
NA
NA
NA
UT
337
1,563
131
537
230
712
95
315
VA
358
1,901
131
518
NA
NA
NA
NA
VT
326
1,639
126
567
161
419
64
154
WA
321
1,670
122
484
192
648
68
181
WI
126
420
46
135
NA
NA
NA
NA
WV
107
375
50
169
195
704
69
180
WY
160
545
66
169
167
563
64
205
* The capacity is differentiated for preventive and restorative services. † Two-letter US zip code abbreviations are used for state names. ‡ NA: Not applicable.
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in 2012, the median number of patients and visits per provider for preventive care ranged from 99 (Mississippi) through 358 (Virginia) and from 344 (Ohio) through 1,901 (Virginia), respectively; n in 2012, the median number of patients and of visits per provider for restorative care ranged from 39 (Mississippi) through 131 (Utah and Virginia) and from 107 (Ohio) through 567 (Vermont), respectively; n in 2012, the caseload for preventive care was statistically significantly higher than for restorative care overall (P z 0), with a difference ranging from 65 through 441 visits per provider; n one-half of the states with 2013 data had a median caseload for preventive and restorative care that was higher in 2013 than in 2012. Vermont had a significant decrease in realized caseload in 2013. The difference in medians between the 2 years across all states was statistically significant only for Louisiana restorative care; Minnesota preventive care; and New York, Oklahoma, and Washington for both types of care (eTable 3, available online at the end of this article). eFigures 1 and 2 (available online at the end of this article) display box plots of the provider-level caseload in number of patients and of visits stratified according to state. The box plots in these figures show not only the wide variation in the median caseload but also the skewedness of the distributions with long right tails, corresponding to providers with higher caseloads. n
Provider-level caseload outcome: urbanicity and provider-type stratification Figure 1 presents the distribution box plots of the provider-level caseload in number of visits according to urbanicity and type of provider. eFigure 3 (available online at the end of this article) presents the same caseload distributions as histograms. eFigure 4 (available online at the end of this article) presents the same box plots and histograms but for caseload in numbers of patients. The results from these figures are n across both strata, the distribution of the provider-level caseload was skewed with a long right tail. Although there were many providers with a low Medicaid caseload, there also were some providers with a large caseload; not all such providers were in the category of entity 2 (group providers) of the provider’s NPI; n comparing the distributions across different levels of urbanicity specified by providers’ practice address according to NPPES, we found that the provider-level caseload increased with the level of urbanicity for both restorative and preventive care (P z 0 for the Wilcoxon rank-sum test of equal medians). The increase was similar for the number of visits and for the number of patients. Comparing the distributions across different provider types, specified by providers’ taxonomy according to NPPES, we found that the provider-level caseload was more than twice as high for general dentists as for other providers (including mostly dental specialists) and more than twice as high for pediatric dentists as for general dentists. The differences were larger for the number of visits than for the number of patients. Figure 2 compares the distributions of the provider-level caseload measured according to the number of preventive oral health care visits for 2012 and 2013, urbanicity level, and provider type. eFigure 5 (available online at the end of this article) presents the same caseload distributions as the histograms. eFigure 6 (available online at the end of this article) compares the provider-level caseload according to state. n The distributions according to urbanicity and provider type had similar shape, median, and spread for the 2 years. The test of the null hypothesis of equal medians, using the Wilcoxon rank-sum test with Bonferroni correction for multiplicity, showed that the difference in medians between the 2 years across all groups in the urbanicity and provider type strata was not statistically significant except for the difference in provider-level caseload for pediatric dentists (P z 0). n The distributions of the provider-level caseloads were different across the states. DISCUSSION In our study, we provide a multistate analysis of the Medicaid caseload of providers who can deliver oral health care services for children. To our knowledge, this is the first such study in which investigators examined Medicaid caseload at the provider level. A first important observation is that the estimated Medicaid participation rates were significantly lower than those ADA-HPI previously reported. One primary reason for this difference is a much larger denominator in the participation rates provided in our study. We considered the universe of all oral health care providers with an NPI, although a proportion of the providers were inactive. For 300
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3,500
NUMBER OF VISITS
3,000 2,500 2,000 1,500 1,000 500 0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN SUBURBAN PREVENTIVE RESTORATIVE TYPE OF URBANICITY
URBAN PREVENTIVE
GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER OTHER RESTORATIVE PREVENTIVE TYPE OF PROVIDER
PEDIATRIC PREVENTATIVE
A
URBAN RESTORATIVE
5,000
NUMBER OF VISITS
4,000 3,000 2,000 1,000 0
B
PEDIATRIC RESTORATIVE
Figure 1. Box plots of the provider-level capacity measured according to the number of visits, for preventive and restorative care separately, and according to urbanicity (A) and type of provider (B). We have reduced the y axis such that approximately 7% to 8% of outlying observations with a large number of patients are excluded.
example, we identified 6,148 oral health care providers in Georgia in the 2012 NPPES database; in contrast, results of a survey by the Georgia Dental Association8 indicated there were 5,881 dentists, among whom only 4,044 reportedly were active. Although for some states the difference in participation rates may be explained by the larger number of providers in the denominator of the participation rates provided by our study, the difference between our rates and those provided by the ADA-HPI are much larger than may be explained by only that factor. Another important finding was the difference in participation rates calculated by limiting the numerator to providers who saw 11 or more patients within the calendar year compared with the estimate based on including providers who accepted fewer than 11 patients. That difference suggests that although some providers accept patients enrolled in Medicaid, their realized caseload is too small to be counted as such. This finding aligns with the recommendation of using multiple measures to impose a minimum caseload to deem a provider as participating in Medicaid, particularly accounting for how extensively dentists treated beneficiaries enrolled in Medicaid.3 Our study fills the gap in stipulating access standards and in deriving access estimates by providing insights on the realized caseload of oral health care providers according to state, provider type, and urbanicity. Investigators in a 2017 study identified New Jersey as being at a lower bound in mandating a 500:1 enrollee to dentist provider ratio in its Medicaid program, whereas other states JADA 150(4)
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NUMBER OF VISITS
4,000
3,000
2,000
1,000
0 RURAL 2012
RURAL 2013
SUBURBAN 2012 SUBURBAN 2013 TYPE OF URBANICITY AND YEAR
URBAN 2012
URBAN 2013
GENERAL DENTIST 2012
GENERAL DENTIST 2013
OTHER OTHER PROVIDER 2012 PROVIDER 2013 TYPE OF PROVIDER AND YEAR
PEDIATRIC DENTISTRY 2012
PEDIATRIC DENTISTRY 2013
A 5,000
NUMBER OF VISITS
4,000 3,000 2,000 1,000 0
B
Figure 2. Box plots of the provider-level capacity for preventive care comparing 2012 (blue box plots) and 2013 (green box plots) according to urbanicity (A) and type of provider (B). We have reduced the y axis such that approximately 7% to 8% of outlying observations with a large number of patients are excluded.
mandate a ratio as high as 2,000:1.9 The ADA-HPI has provided access estimates for varying ratios, assuming a 500:1 patient to provider ratio as the lower bound and unlimited caseload as the upper bound.5 These bounds assume that the Medicaid caseload is the same across all oral health care providers and that on average an oral health care provider will see as many as 500 or more children insured by Medicaid in his or her practice. In contrast to these assumptions, we found that none of the states had a median realized caseload as high as 500 pediatric patients enrolled in Medicaid per provider. Another important finding relevant to estimation of the potential access to oral health care is the wide variation across the strata considered in this study: state, provider type, and urbanicity. We identified a clear trend in the caseload with respect to provider type, with pediatric dentists having the largest caseload, followed by general dentists and then specialists and other licensed professionals. To our knowledge, investigators in only 1 study to date have taken into consideration the provider type in estimating access.10 We also identified substantive differences in caseload across states. The ADA-HPI state reports assumed that all providers have the same caseload regardless of their taxonomy or state. We also found a trend in Medicaid caseload across urbanicity levels of the provider’s business practice address, with practices in urban areas having larger caseload followed by suburban and then by rural areas. This trend, however, may be driven by demand rather than the potential caseload of the oral health care providers. 302
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There are several data limitations in our study. The primary data source used in this analysis consists of claims data submitted by state Medicaid agencies. One limitation of our study is that some claims may not be filed, resulting in a potential underreporting bias of the providers’ caseloads. It is unclear whether some prevention initiatives, such as school-based sealant programs, file claims for services rendered; CMS form 416dused by the ADA-HPI reportdis filed by states to CMS and may include adjustments for these interventions. MAX files may be incomplete, especially for states with large managed care populations.11 Another study limitation is inherent in the NPPES database, the data source that provided the practice and provider characteristics of the oral health care providers included in our study. Although it has been mandatory to enter an NPI for all providers submitting for reimbursements since 2009, there still may be oral health care providers without an NPI, particularly those who provide oral health care within a large group practice. In addition, there may be a large proportion of inactive providers with an NPI. Consequently, the denominator in the Medicaid participation rates may be larger than the actual number of providers, resulting in lower estimated rates of Medicaid participation. Finally, some providers may not have updated their practice address information in the NPPES database. Our definition of preventive dental services included several Current Dental Terminology codes typically classified as diagnostic services, such as D0120 (routine oral evaluation) and D0150 (comprehensive oral evaluation).12 Our rationale was that diagnostic services are an essential part of a preventive visit, even if no other service is delivered. The net effect of including diagnostic codes in our definition of preventive care is more inclusive counting of patients receiving preventive care and visits per provider. Consequently, our calculated caseloads probably err toward more generous estimates of preventive care per provider. CONCLUSIONS Findings from this study suggest that the realized oral health care caseload for children enrolled in Medicaid varies greatly across providers, with some consistent trends across different provider types and urbanicity of the providers’ practices. Although we captured only realized caseload, with the potential caseload being possibly larger, it is still informative in the specification of the providers’ caseloads in potential access estimates for children insured by Medicaid. Investigators in a 2018 study used the realized caseload to specify whether a provider had a low or high Medicaid caseload, and, on this basis, they considered additional excess caseload to specify potential caseload more accurately.10 Differences in how various state Medicaid programs are administered along with state policies on supervision of licensed providers and on reimbursement may affect providers’ Medicaid caseloads greatly and may explain partially the wide variations across states. Thus, this study’s results can assist states in gauging the level of oral health care provided to children insured by Medicaid in comparison with that of other states, with implications for the specification of access standards and oral health policies. n SUPPLEMENTAL DATA Supplemental data related to this article can be found at: https://doi.org/10.1016/j.adaj.2018.11.020.
Dr. Serban is a professor, School of Industrial & Systems Engineering, Georgia Institute of Technology, 765 Ferst St, Atlanta, GA 30332-0205, e-mail [email protected]. Address correspondence to Dr. Serban. Mr. Bush is an undergraduate research assistant, School of Industrial & Systems Engineering, Georgia Institute of Technology, Atlanta, GA. Dr. Tomar is a professor, Department of Community Dentistry and Behavioral Science, University of Florida, CITY, FL. Disclosure. None of the authors reported any disclosures.
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Financial support for this study was provided by Award R01DE028283 from the National Institute of Dental and Craniofacial Research, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report. The authors are thankful to Richard Starr in assisting with data safeguards and the information technology infrastructure.
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1. American Dental Association Health Policy Institute. Webinars: measuring what matters: a new way of measuring geographic access to dental care services. Available at: https://www.ada.org/en/science-research/health-policyinstitute/publications/webinars/measuring-access-todental-care-in-every-state. Accessed December 12, 2018. 2. Serban N, Tomar SL. ADA Health Policy Institute’s methodology overestimates spatial access to dental care for publicly insured children. J Public Health Dent. 2018; 78(4):291-295. 3. Warder CJ, Edelstein BL. Evaluating levels of dentist participation in Medicaid. JADA. 2016;148(1): 26-32. 4. American Dental Association Health Policy Institute. The oral health care system: a state by state analysis. 2015. Available at: https://www.ada.org/en/science-research/
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health-policy.../oral-health-care-system. Accessed January 1, 2019. 5. American Dental Association Health Policy Institute. Geographic access to dental care. Available at: https://www.ada.org/en/science-research/health-policyinstitute/geographic-access-to-dental-care. Accessed December 12, 2018. 6. Vujicic M. A new way to measure geographic access to dentists in North Carolina. N C Med J. 2017;78(3): 391-392. 7. Morrill R, Cromartie J, Hart G. Metropolitan, urban, and rural commuting areas: toward a better depiction of the United States settlement system. Urban Geogr. 1999; 20(8):727-748. 8. Georgia Health Policy Center. A study of Georgia’s dental workforce 2012. Available at: https://ghpc.gsu.edu/
download/a-study-of-georgias-dental-workforce-2012-8/. Accessed December 12, 2018. 9. Nasseh K, Eisenberg Y, Vujicic M. Geographic access to dental care varies in Missouri and Wisconsin. J Public Health Dent. 2017;77(3):197-206. 10. Cao S, Gentili M, Griffin P, Griffin S, Serban N. Disparities in access to preventive dental care between publicly and privately insured children in Georgia. Prev Chronic Dis. 2018;14:170-176. 11. Byrd VL, Dodd AH. Assessing the usability of MAX 2008 encounter data for comprehensive managed care. Medicare Medicaid Res Rev. 2013;3(1):pii:mmrr.003.01. b01. 12. American Dental Association. CDT 2013. Dental Procedure Codes. Chicago, IL: American Dental Association; 2012.
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APPENDIX
The following list consists of all dental care provider taxonomies specified in the National Plan and Provider Enumeration System database. Along with the taxonomy, we also provided information about the grouping into pediatric dentist, general dentist, specialist, and other licensed professional. For ease of data visualization and analysis, we collapsed 2 of the provider groups, specialist and other licensed professional, into 1 group: other providers. However, our current implementation allows a more granular analysis. Advanced practice dental therapistd125K00000X (other licensed professional) Dental assistantd126800000X (other licensed professional) Dental hygienistd124Q00000X (other licensed professional) Dental laboratory techniciand126900000X (other licensed professional) Dental therapistd125J00000X (other licensed professional) Dentistd122300000X (general dentist) Dental public healthd1223D0001X (other licensed professional) Dentist anesthesiologistd1223D0004X (specialist) Endodonticsd1223E0200X (specialist) General practiced1223G0001X (general dentist) Oral and maxillofacial pathologyd1223P0106X (specialist) Oral and maxillofacial radiologyd1223X0008X (specialist) Oral and maxillofacial surgeryd1223S0112X (specialist) Orthodontics and dentofacial orthopedicsd1223X0400X (specialist) Pediatric dentistryd1223P0221X (pediatric dentistry) Periodonticsd1223P0300X (specialist) Prosthodonticsd1223P0700X (specialist) Denturistd122400000X (other licensed professional) Oral medicinistd125Q00000X (other licensed professional) We chose these taxonomies because they represent the types of providers from whom children enrolled in the Medicaid program would receive preventive or restorative care.
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eTable 1. Restorative dental care procedures used to define restorative care visits.* CODE12
DESCRIPTION
D2140
Amalgamd1 surface
D2150
Amalgamd2 surfaces
D2160
Amalgamd3 surfaces
D2161
Amalgamd4 or more surfaces
D2330
Resind1 surface
D2331
Resind2 surfaces
D2332
Resind3 surfaces
D2335
Resind4 or more surfaces or involving incisal angle (anterior)
D2391
Resin-based composited1 surface
D2392
Resin-based composited2 surfaces
D2393
Resin-based composited3 surfaces
D2394
Resin-based composited4 or more surfaces
D2751
Crowndporcelain fused to predominantly base metal
D2791
Crowndfull cast predominantly base metal
D2930
Prefabricated stainless steel crowndprimary tooth
D2931
Prefabricated stainless steel crowndpermanent tooth
D2932
Prefabricated resin crown
D2933
Prefabricated stainless steel crown with resin window
D2934
Prefabricated esthetic coated stainless steel crowndprimary tooth
D2940
Sedative filling
D2954
Prefabricated post and core in addition to crown
D3110
Pulp capddirect (excluding final restoration)
D3120
Pulp capdindirect (excluding final restoration)
D3220
Therapeutic pulpotomy (excluding final restoration) removal of pulp coronal to the dentinocemental junction and application of medicament
D3221
Pulpal debridement
D3230
Pulpal therapy (resorbable filling)danterior restoration
D3240
Pulpal therapy (resorbable filling)dposterior restoration
D3310
Endodontic therapy
D3320
Endodontic therapy
D3330
Endodontic therapy
D7111
Extraction
D7140
Extraction
D7210
Surgical removal of erupted tooth requiring elevation of mucoperiosteal flap and removal of bone or section of tooth
D7220
Removal of impacted toothdsoft tissue
D7230
Removal of impacted toothdpartially bony
D7240
Removal of impacted toothdcompletely bony
D7250
Surgical removal of residual tooth roots (cutting procedure)
* One visit can include 1 or more such procedures.
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eTable 2. Preventive dental care procedures used to define preventive care visits.* CODE12
DESCRIPTION
Topical Fluoride D1201
Topical application of fluoride (including prophylaxis)dchild
D1203
Topical fluoride for primary dentition
D1204
Topical fluoride for mixed and adult dentition
D1205
Topical application of fluoride (including prophylaxis)dadult
D1206
Topical fluoride varnish
D1208
Topical application of fluoride
Evaluation and Examination D0120
Periodic oral evaluationdestablished patient
D0140
Limited oral evaluationdproblem focused
D0145
Oral evaluation for a patient younger than 3 years and counseling with primary caregiver
D0150
Comprehensive oral evaluationdnew or established patient
D0160
Detailed and extensive evaluation
D0170
Reevaluationdlimited, problem focused (established patient; not postoperative visit)
D0180
Comprehensive periodontal evaluation
Pit-and-Fissure Sealant Application D1351
Sealantdper tooth
D1352
Preventive resin restoration in a patient with moderate to high caries riskdpermanent tooth
Prophylaxis D1110
Prophylaxisdadult
D1120
Prophylaxisdchild
* One visit can include 1 or more such procedures.
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eTable 3. P values for the hypothesis testing procedure for comparing the median of the capacity for 2012 and 2013 differentiated according to type of care. STATE†
RESTORATIVE CARE No. of Visits
PREVENTIVE CARE
No. of Patients
No. of Visits
No. of Patients
AR
.0227
.0393
.0826
.0412
CT
.9700
.5960
.0661
.1468
GA
.1350
.5452
.5766
.6110
IA
.0018
.5677
.3468
.6304
IN
.1445
.0591
.1337
.0223
LA
.0034
.0021*
.0061
.0022*
MA
.2935
.4211
.3282
.6230
MN
0*
.3529
0*
.6985
MS
.6306
.5199
.6134
.6932
NJ
.9981
.7397
.7625
.6825
NY
0*
0*
0*
0*
OH
.9227
.4401
.3540
.1816
OK
0*
0*
0*
0*
OR
.3212
.2094
.4758
.3794
TN
.0798
.4463
0
.5108
UT
.3597
.2989
.3281
.7421
VA
.3945
.4122
.8876
.7975
VT
.3945
.4122
.8876
.7975
WA
0*
0*
0*
0*
WV
.9843
.8883
.8908
.8760
WY
.5078
.4167
.5459
.4705
* Significant at the .05 level with Bonferroni correction for multiplicity. † Two-letter US zip code abbreviations are used for state names.
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1,200
NUMBER OF PATIENTS
1,000
800
600
400
200
Y O H O K O R
RI TN
TX U T VA
VT W A W I W V W Y
RI TN
TX U T VA
VT W A W I W V W Y
V
N
N N
V N Y O H O K O R
N J N M N J N M
E
N M S M T N C N E N H
M
M
A
D
M
LA
M
KS KY
IL IN
IA
CT D E G A
A
K A L A R CO
0
STATE
A 500
NUMBER OF PATIENTS
400
300
200
100
B
LA M A M D M E M N M S M T N C N E N H
KS KY
IN
IL
IA
CT D E G A
A
K A L A R CO
0
STATE
eFigure 1. Box plots show the provider caseload according to state expressed in the number of patients in preventive care (A) and restorative care (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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5,000
NUMBER OF VISITS
4,000
3,000
2,000
1,000
TX U T VA
VT W A W I W V W Y
T VA
VT W A W I W V W Y
TN
LA M A M D M E M N M S M T N C N E N H N J N M N V N Y O H O K O R RI
KS KY
IL
IN
CT D E G A IA
A
K A L A R CO
0
STATE
A 2,000
NUMBER OF VISITS
1,500
1,000
500
B
U
TX
RI TN
Y O H O K O R
V
N
N
N J N M
LA M A M D M E M N M S M T N C N E N H
KS KY
IL IN
IA
CT D E G A
A
K A L A R CO
0
STATE
eFigure 2. Box plots show the provider caseload according to state expressed in the number of visits for preventive care (A) and restorative care (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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200 SUBURBAN RESTORATIVE
400
600
URBAN PREVENTIVE
URBAN RESTORATIVE 60
TOTAL NUMBER OF PATIENTS, %
50 40 30 20 10 0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN PREVENTIVE
60 50 40 30 20 10 0 200
400
600
A
200
400
600
NUMBER OF PATIENTS 200 OTHER RESTORATIVE
400
600
PEDIATRIC PREVENTIVE
PEDIATRIC RESTORATIVE
TOTAL NUMBER OF PATIENTS, %
60 40 20 0 GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER PREVENTIVE
60 40 20 0 200
400
600
B
200
400
600
NUMBER OF PATIENTS
eFigure 3. Histograms of the provider caseload measured according to the number of visits, for preventive and restorative care separately, and according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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NUMBER OF PATIENTS
800
600
400
200
0 RURAL PREVENTIVE
RURAL RESTORATIVE
SUBURBAN SUBURBAN PREVENTIVE RESTORATIVE TYPE OF URBANICITY
URBAN PREVENTIVE
URBAN RESTORATIVE
GENERAL PREVENTIVE
GENERAL RESTORATIVE
OTHER OTHER PREVENTIVE RESTORATIVE TYPE OF PROVIDER
PEDIATRIC PREVENTIVE
PEDIATRIC RESTORATIVE
A 1,200
NUMBER OF PATIENTS
1,000 800 600 400 200 0
B
eFigure 4. Box plots show the provider caseload measured according to the number of patients for preventive and restorative care separately and according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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1,000 SUBURBAN 2013
2,000
3,000
4,000
URBAN 2012
URBAN 2013
TOTAL NUMBER OF VISITS, %
40 30 20 10 RURAL 2012
RURAL 2013
0
SUBURBAN 2012
40 30 20 10 0 1,000
2,000
3,000
4,000
A
1,000
2,000
3,000
4,000
NUMBER OF VISITS 1,000 OTHER PROVIDER 2013
2,000
3,000
4000
PEDIATRIC DENTISTRY 2012
PEDIATRIC DENTISTRY 2013 80
TOTAL NUMBER OF VISITS, %
60 40 20 0 GENERAL DENTIST 2012
GENERAL DENTIST 2013
OTHER PROVIDER 2012
80 60 40 20 0 1,000
2,000
3,000
4,000
B
1,000
2,000
3,000
4,000
NUMBER OF VISITS
eFigure 5. Histograms of the provider-level capacity for preventive care comparing 2012 and 2013 according to urbanicity (A) and type of provider (B). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded.
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NUMBER OF PATIENTS
1,500
1,000
500
A R1 A 2 R1 3 CT 12 CT 1 G 3 A 1 G 2 A 13 IA 12 IA 13 IN 12 IN 13 LA 12 LA 1 M 3 A 1 M 2 A 1 M 3 N 1 M 2 N 1 M 3 S1 M 2 S1 3 N J1 2 N J1 N 3 Y1 N 2 Y1 O 3 H 1 O 2 H 1 O 3 K1 O 2 K1 O 3 R1 O 2 R1 TN 3 1 TN 2 1 U 3 T1 U 2 T1 3 VT 12 VT 1 W 3 A 1 W 2 A 1 W 3 V1 W 2 V1 W 3 Y1 W 2 Y1 3
0
STATE AND YEAR
A 6,000
NUMBER OF VISITS
5,000 4,000 3,000 2,000 1,000
A
R1 A 2 R1 3 CT 12 CT 1 G 3 A 12 G A 13 IA 12 IA 13 IN 12 IN 13 LA 12 LA 1 M 3 A 1 M 2 A 1 M 3 N 12 M N 1 M 3 S1 M 2 S1 N 3 J1 2 N J1 3 N Y1 N 2 Y1 O 3 H 1 O 2 H 13 O K1 O 2 K1 O 3 R1 O 2 R1 TN 3 1 TN 2 1 U 3 T1 U 2 T1 3 VT 12 VT 1 W 3 A 1 W 2 A 1 W 3 V1 W 2 V1 W 3 Y1 W 2 Y1 3
0
B
STATE AND YEAR
eFigure 6. Box plots of the provider caseload according to state expressed in the number of patients (A) and the number of visits (B) for all types of care (preventive and restorative) comparing 2012 (blue bars) and 2013 (green bars). The authors reduced the y-axis so that approximately 7% to 8% of outlying observations with a large number of patients were excluded. Two-letter US zip code abbreviations are used for state names.
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