compose a paper

G O V E R N M E N T , L A W , A N D P U B L IC H E A L T H P R A C T IC E

M i s s e d P o l i c y O p p o r t u n i t i e s t o A d v a n c e H e a l t h E q u i t y

M i s s e d P o l i c y O p p o r t u n i t i e s t o A d v a n c e H e a l t h E q u i t y b y R e c o r d i n g

D e m o g r a p h i c D a t a in E l e c t r o n i c H e a l t h R e c o r d s | Megan Daugherty Douglas, JD, Daniel E. Dawes, JD, Kisha B. Holden, PhD, MSCR, and Dominic Mack, MD, MBA

T h e s c ie n c e o f e lim in a tin g h e a lth d is p a r it ie s is c o m p le x and de p e n d e n t on d e m o g ra p h ic d a ta . T h e H e a lth I n f o r m a t io n T e c h n o lo g y f o r E c o n o m ic an d C lin ic a l H e a lth A c t (H IT E C H ) e n c o u r a g e s t h e a d o p t i o n o f e le c t r o n ic h e a lth r e c o r d s a n d r e q u ir e s b a s ic d e m o g r a p h ic d a ta c o lle c tio n ; h o w e v e r, c u r­ re n t d a ta g e n e ra te d are in s u ffi­ c ie n t to a d d re s s k n o w n h e a lth d is p a ritie s in v u ln e ra b le p o p u ­ la tio n s , in c lu d in g in d iv id u a ls f r o m d iv e rs e ra c ia l a n d e th n ic b a c k g ro u n d s , w it h d is a b ilitie s , a n d w it h d iv e rs e s e x u a l id e n ti­ ties.

W e c o n d u c te d an a d m in is ­ tr a tiv e h is to ry o f HITECH an d id e n tifie d g a p s b e tw e e n th e p o lic y o b je c tiv e a n d re q u ire d m e a s u re . W e id e n tifie d 20 o p ­ p o r tu n itie s f o r c h a n g e a n d 5 c h a n g e s , 2 o f w h ic h re q u ire d th e c o lle c tio n o f less d a ta .

U ntil health care d e m o g ra p h ic data co lle c tio n re q u ire m e n ts are co n s is te n t w ith p u b lic health re­ q u ire m e n ts , th e n a tio n a l goal o f e lim in a tin g health d isp arities ca n n o t be realized. (Am J Public Health. 2 0 1 5 ;1 0 5 :S 3 8 0 - S 3 8 8 . d o i:1 0 .2 1 0 5 /A J PH.2014.302384)

FEDERAL EFFORTS TO address racial and ethnic health disparities were initiated by the Heckler Report in 198 5.1 Nearly 3 decades later, health disparities persist across racial and ethnic groups and have been estimated to cost $ 3 0 0 billion per year.2 De­ mographic data, the statistical data of a population, is the foundation for identifying disparities, improv­ ing overall quality of health care, improving population health, and measuring progress toward health equity.3 Accurately recording de­ mographic data enables health care providers to identify risk and pro­ tective factors for a large num ber of diseases and conditions and to improve comprehensive care for individual patients.

As understanding of health dis­ parities and contributing risk fac­ tors improves, the need for more granular information has in­ creased.3 Racial and ethnic mi­ nority populations continue to in­ crease, resulting in cultural and linguistic issues that have an im­ pact on delivery of care and treatment. People with disabilities make up 2 0 % of the adult popu­ lation and are burdened by pre­ ventable disparities in health care compared with their nondisabled peers.4 Lesbian, gay, bisexual, and

transgender individuals are be­ coming increasingly visible in our society and have worse outcomes for a num ber of medical condi­ tions than their heterosexual and cisgender (individuals identifying as their birth sex) peers.5

In 1997, the Office of Manage­ m ent and Budget (OMB) revised the government-unique race and eth­ nicity standards to include 5 race and 2 ethnicity categories (Table l).6 Recognition of the diversity within each OMB race and ethnicity category is critical to eliminating health disparities.3 For example, among Asians in California, rates of colorectal screening varied across racial subgroups, with disparities seen in Chinese, Korean, and Viet­ namese individuals compared with Whites, but no disparity seen in other Asian subgroups.7 In this in­ stance, the intervention most effec­ tive in reducing the disparity would target Chinese, Korean, and Viet­ namese patients, rather than all Asian individuals. For this reason, recent health disparity reports con­ sistently call for the collection of more detailed and consistent infor­ mation across the health care and public health systems.7' 9 Under the Affordable Care Act (ACA), the Department of Health and Human Services developed more granular

race and ethnicity standards and added 6 functional questions to assess disability status (Table l).10

THE HITECH ACT

In 2 0 0 9 , Congress passed the Health Information Technology for Economic and Clinical Health Act (HITECH) and invested more than $35 billion to stimulate the adop­ tion and meaningful use of elec­ tronic health records (EHRs) by physicians and hospitals.11 One of the primary goals of HITECH was to reduce health disparities.11 As proof of the law’s reach, by 2013, 69% of physicians intended to or were already participating in the Medicare or Medicaid EHR incen­ tive program.12 Physician EHR adoption increased from 25% in 2010 to 4 0 % in 2012 and hospital adoption rates nearly tripled to 4 4 % during the same time period.13

T he HITECH programs have evolved through a staged rule- making process, resulting in a dense, complex, and convoluted administrative history. No compre­ hensive look at HITECH’s admin­ istrative process with regard to demographic data collection currently exists. Therefore, this study provides much-needed doc­ umentation of the rulemaking

S 3 8 0 | Government, Law, and Public Health Practice | Peer Reviewed | Douglas e t al. American Journal o f Public Health | S upplem ent 3 , 2 0 1 5 , Vol 1 0 5 , No. S3

G O V E R N M E N T , LA W , A N D P U B L IC HEALTH P R A C TIC E

TABLE 1-C o m p ariso n of Race and Ethnicity Collection Standards Adopted by the Office of M anagem ent

and Budget in 1 9 9 7 and the D epartm ent of Health and Human Services in 2 0 1 1

Office o f Management and Budget6 Department of Health and Human Services10 Demographic (Last Revised in 1997) (Adopted in 2011)

Black or African American Black or African American

American Indian or Alaska Native American Indian or Alaska Native Asian Asian Indian

Chinese

Filipino

Japanese

Korean

Vietnamese

Other Asian Native Hawaiian or other Pacific Islander Native Hawaiian

Guamanian or Chamorro

Samoan

Other Pacific Islander White White Non-Hispanic or Latino Non-Hispanic/Latino/Spanish origin Hispanic or Latino Mexican

Cuban

Puerto Rican

Other Hispanic/Latino/S panish origin

process related to recording de­ mographic data.

O ur specific aims w ere (1) to construct a comprehensive ad­ ministrative history of HITECH with regard to recording demo­ graphic data, (2) to determ ine the num ber of opportunities for policy change and policy changes that arose throughout the process, and (3) to identify the reasons for adopting o r declining opportuni­ ties for policy change with regard to recording demographic data.

T he primary purpose of this analysis was to support the col­ lection of enhanced demographic data across various health sectors. It is our intention to unite health care providers, public health practitioners, consumers, EHR

vendors, advocates, and policy­ makers in an effort to develop and adopt robust, forward-thinking policies on the collection of de­ mographic data in EITRs that will lead to the reduction and ultimate elimination of health disparities.

METHODS

W e compiled the HITECH ad­ ministrative history by using the Federal Register’s online advanced search tool. We identified all ad­ ministrative actions taken between February 17, 2009, and February 28, 2014, by using the search term “HITECH." We collected and reviewed for relevancy every article with the search term “demographic” W e excluded articles related to

privacy and security, health care payment and delivery systems, and specific data collection notices.

W e limited our demographic categories of interest to granular race and ethnicity data, preferred language, disability status, sexual orientation, and gender identify. W e conducted a targeted search of each relevant document by using the following key terms: disparit*, demographic, race, ethnicity, lan­ guage, disabilit*, and sexual. Where these terms appeared, we collected the entire section related to the term and additional information neces­ sary for contextual understanding.

W e defined and applied vari­ ables to the relevant sections of each article. “Baseline" was the statutory minimum or final rule

Supplem ent 3 , 2 0 1 5 , Vol 1 0 5 , No. S3 | Am erican Journal o f Public Health Douglas et al. | Peer Reviewed | Government,

from the previous action. W e de­ fined “proposed category” as the categories of demographic data proposed for collection. W e de­ fined “final category” as the cate­ gories adopted in the final rule. “Standard” was the common ter­ minology used to support each dem ographic d ata category. “O pportunity for change” was the explicit consideration by the agency o f m ultiple categories or standards. “Change” was a change in category o r standard from the baseline to the final rule (Table 2).

From these findings, we con­ structed a timeline of every HITECH administrative action relevant to re­ cording demographic data (Figure 1). W e included actions taken in accordance with the ACA’s demo­ graphic data collection standards to allow for temporal comparison.

RESULTS

The administrative history search of the Federal Register resulted in 136 articles. Once we applied the exclusion criteria, 9 regulatory actions rem ained rele­ vant. W e identified 2 HITECH programs: (1) the Medicare and Medicaid EHR Incentive program (the Meaningful Use program [MU]), administered by the Cen­ ters for Medicare and Medicaid Services (CMS) and (2) the Health Information Technology (HIT) Standards and Certification Crite­ ria program (SCC), administered by the Office of the National Co­ ordinator (ONC). Five of the reg­ ulatory actions w ere proposed or interim final rules, 2 for the MU program (stages 1 and 2) and 3 for the SCC program (initial, 2 0 1 4 edition, and 2 0 1 5 voluntary

Law, and Public Health Practice S 381

TA BL

E 2

-O p

p o

rt u

n iti

e s

fo r

P ol

ic y

C ha

ng e

an d

A ct

ua l

C ha

ng es

i n

D em

og ra

ph ic

D at

a R

eq ui

re m

en ts

T hr

ou gh

3 R

ou nd

s o

f H

ea lth

I nf

or m

at io

n Te

ch no

lo gy

f o

r E

co no

m ic

a nd

C lin

ic al

H ea

lth A

ct

A dm

in is

tr at

iv e

A ct

io ns

S382 | Government, Law, and Public Health Practice | Peer Reviewed | Douglas et al. American Journal of Public Health | Supplement 3, 2015, Vol 105, No. S3

Ot he

r c om

m en

te r

No m

en tio

n NA

Ye

s No

Ot

he r c

om m

en te

r No

m en

tio n

Supplement 3, 2015, Vol 105, No. S3 | American Journal of Public Health Douglas et al. | Peer Reviewed | Government, Law, and Public Health Practice S383

G O V E R N M E N T , L A W , A N D P U B L IC H E A L T H P R A C T IC E

o ★ ☆ Jan

2 0 1 0 Aug/Sept

2010 June 2011

M u Stage 1 Initial Standards and C ertification

! O c t March Sept/O ct 2011

_____________ I 2012

I 2012

I ACA M u Stage 2

Standards on 2014 Edition d em ographic Standards and C ertification

data collection

2015 Vo luntary Edition Standards and C ertification

FIG U R E 1 —T im e lin e o f a d m in is tra tiv e a c tio n s u n d e r th e H e a lth In fo rm a tio n Technology fo r Econom ic and

C lin ic a l H e a lth A c t (H IT E C H ) an d th e A ffo rd a b le C a re A c t (A C A ): U n ite d S ta te s , 2 0 1 0 - 2 0 1 4 .

Symbols:

Key

o HITECH Act ☆ A ffo rda ble Care Act Sym bol colors:

0 3 Proposed ru le / In te rim Final rule

□ Final rule

N o te . MU - the Meaningful Use program.

edition). Four were final rules, 2 for the MU program and 2 for the SCC program. In total, there were 2 0 opportunities for policy change. Five changes were made, with 2 of those changes eliminat­ ing a category of demographic data, and a num ber of opportuni­ ties rem ain to be determined. T a­ ble 2 shows all opportunities for change and all actual changes.

Round 1 T he administrative actions for

stage 1 of the MU program and the initial SCC for certified EHRs co­ incided, with the proposed rules published in the Federal Register on January 1 3 ,2 0 1 0 , and the final rules becoming effective on Sep­ tem ber 27, 2 0 1 0 , and August 27, 2 0 1 0 , respectively.

Meaningful Use, stage 1. In the MU proposed rule,14 the recording of demographic data was proposed as a core (required) objective. Within the objective, the proposed cate­ gories were race, ethnicity, gender, date of birth, preferred language, and insurance type. The OMB stan­ dards were proposed for race and ethnicity. No standards were pro­ posed for preferred language.

From the proposed to the final rule,15 there were 3 opportunities for policy change and 1 change: insur­ ance type was eliminated from the requirements (Table 2). Comments on the complexity of defining insur­ ance type and attributing it to pa­ tients in a consistent way merited its elimination as a core measure. Citing the Institute of Medicine report en­ titled “Race, Ethnicity and Language

Data: Standardization for Health Care Quality Improvement,” com- menters recommended more gran­ ular racial and ethnic standards that roll up to the 5 OMB standards; however, the minimal OMB stan­ dards were adopted in the final rule. The agency reasoned that expanding the OMB categories was ‘beyond the scope of the definition of meaningful use to provide additional definitions for race and ethnicity... .”15

Initial set o f Standards and Certification Criteria. T he SCC rulemaking was consistent with the MU rulemaking with regard to recording demographic data.16'1' Commenters recom m ended addi­ tional categories of demographic data, including birthplace, educa­ tion, occupation o r industry, and functional status. Because the

agency did not address each cate­ gory separately, all of these rec­ ommendations were counted as a single opportunity for policy change. In total, there were 4 opportunities for policy change and 1 change: insurance type was eliminated from the requirem ents (Table 2). T he SCC final rule established the OMB standards for race and ethnicity.

Round 2 T he adm inistrative actions for

stage 2 of th e MU program and th e 2 0 1 4 edition SCC for certi­ fied EHRs occurred sim ulta­ neously, w ith the proposed rules published in th e Federal Register on M arch 7, 2 0 1 2 , and the final rules becom ing effective on Sep­ tem ber 4, 2 0 1 2 , and O ctober 4, 2 0 1 2 , respectively.

Meaningful Use, stage 2. From the proposed to the final rule, there was a total of 7 opportunities for change and 1 actual change (Table 2) 18,19 y jje OMB standards for race

were recommended in the pro­ posed rule, and voluntary recording of additional categories was encouraged if they m apped to the 5 OMB categories. T h e CMS requested comments on the collec­ tion of disability status, highlighting the benefits to care coordination from gathering this information in the EFfR. The CMS also sought comment on whether sexual orien­ tation and gender identity should be recorded in EHRs.

In the final rule, CMS reported several comments recommending alternative race and ethnicity stan­ dards, specifically the Centers for Disease Control and Prevention and the US Census Bureau standards. The agency declined to change but

S 3 8 4 | Government, Law, and Public Health Practice | Peer Reviewed | Douglas e t al. Am erican Journal o f Public Health | S upplem ent 3, 2 0 1 5 , Vol 1 0 5 , No. S3

encouraged the voluntary collection of more granular data mapping to the OMB categories. The CMS adopted the term “sex” to replace “gender” on the basis of comments clarifying that “gender” is a soda! construct and “sex” is a physiologi­ cal characteristic at birth.

Many commenters supported the addition of disability status, sexual orientation, and gender identity. Yet some comments questioned the clinical significance of recording this information as demographic data The CMS declined to adopt disabil­ ity status or sexual orientation and gender identify because of the lack of consensus on definitions, lack of agreed-upon standards, data collec­ tion and reporting challenges, and disagreement over where and how to collect this information in an EHR.

Standards and Certification Criteria, 2 0 1 4 edition. From the proposed rule to the final rule, there was a total of 6 opportunities for change and 2 actual changes (Table 2).20'21 T he ONC proposed to maintain the OMB race and ethnicity categories. The ONC proposed to adopt the Interna­ tional Organization for Standardi­ zation’s (ISO’s) language standard ISO 639-1 as the preferred lan­ guage vocabulary standard as op­ posed to the more granular ISO 639-2 standard.22 T he ONC requested comments about incor­ porating disability status into de­ mographic data, citing the many benefits of making this change, from improving access, coordinat­ ing care across multiple providers, and monitoring disparities be­ tween “disabled” and “nondis­ abled” populations. T he ONC did not seek comments on w hether

S upplem ent 3, 2 0 1 5 , Vol 1 0 5 , No. S3

sexual orientation and gender identity data should be collected.

T he final SCC rule clarified the preferred language standards based on the comments received, and ISO 639-2 constrained by 639-1 was adopted because con­ straining ISO 639-2 to only the active languages in 639-1 would permit more granularity and is a better approach than in the pro­ posed rule.22 Commenters sug­ gested 3 alternative race and ethnicity standards based on the Institute of Medicine recommen­ dations, the Centers for Disease Control and Prevention vocabulary standards, and those adopted by the Department of Health and Human Services to comply with the ACA, all of which are more granular than the OMB standards. T he final rule declined this change, reasoning that the OMB categories are a government-unique standard, are easily understood, and are readily available making them the best standards to support the policy goals. The agency stated that EHR technology must have the capabil­ ity to map race and ethnicity to the OMB categories if the technology developer chooses to incorporate more granular race and ethnicity categories. Disability status was not adopted for reasons similar to those of CMS. Commenters rec­ ommended the incorporation of sexual orientation and gender identity, but the agency declined to make this change.

R o u n d 3

On February 26, 2 0 1 4 , the ONC released a notice of proposed rulemaking for the voluntary 2 0 1 5 edition EHR certification criteria (2015 SCC), which lacked

a CMS Meaningful Use program counterpart.23 T he proposed rule anticipated a MU stage 3 proposal in the fall (available as a supple­ m ent to the online version of this article at http://www.ajph.org).

T he proposed rule identified challenges based on the previous action (SCC 2 0 1 4 edition final rule) adopting preferred language standards. Since the final rule’s publication, ONC published a list of frequently asked questions to clarify the standards and ac­ knowledged that the approach taken in the final rule failed to support current languages, includ­ ing sign language and Hmong.24 Because of this oversight, the 2 0 1 5 SCC proposed rule sought comment on 3 options: full adop­ tion of ISO 639-2 codes, adoption of ISO 639-3 codes, or adoption of standards included in “Tags for identifying languages, September 2 0 0 9 ,” a memo describing current best practices for language identi­ fication.22 (ISO 639-1 consists of 2-letter codes representing most of the major languages of the world. ISO 63 9 -2 consists of 3-letter codes representing m ore lan­ guages than ISO 639-1. ISO 639-3 consists of 3-letter codes and is the most comprehensive of the ISO series, including living, extinct, and ancient languages.)

Following the proposed rule, the ONC sought comments on changes to the SCC in anticipation of the 2 0 1 7 edition. Up for con­ sideration were the recording of disability status, sexual orienta­ tion, gender identity, military sta­ tus, and industry or occupation. Comments were sought on the appropriateness of these cate­ gories and ways to include them in

current demographic data re­ quirements. T he rule proposed 6 functional questions currently in­ cluded in the American Commu­ nity Survey with the addition of a question about English profi­ ciency, seeking comment on w hether the questions were ap­ propriate or if better alternatives exist and how to capture this in­ formation in an EHR. Sexual ori­ entation and gender identity stan­ dards were proposed on the basis of the recent IOM report, “Col­ lecting sexual orientation and gender identity data in electronic health records: workshop sum­ mary.” Comments on the collec­ tion of military service history and occupation and industry were requested. T he comment period for this proposed rule closed on April 28, 2 0 1 4 .

D I S C U S S I O N

T here is a gap between the criteria and standards supporting the MU measure recording demo­ graphic data and the policy objec­ tive of reducing health disparities. Medical practices are driven by the MU criteria and, without require­ ments for more informative data, providers are not encouraged through the policy to identify per­ tinent demographics that lead to proper clinical diagnosis and im­ proved outcomes. Evidence-based measures that better support the policy objective exist and are in­ cluded in public health programs and surveys (Table 3).

T he inconsistent demographic data collection standards between the HITECH programs and the ACA programs may exacerbate health disparities and are problematic for

Am erican Journal o f Public Health Douglas e t at. | Peer Reviewed | Government, Law, and Public Health Practice | S 3 8 5

both research and practice. Practice is hindered because public health is collecting information that, in the case of disability status, sexual ori­ entation, and gender identity, has limited clinical comparison, and with regard to race and ethnicity, is more informative than the data being col­ lected in EHRs. Research using public health survey data will pro­ vide specific information that cannot be ad ap ted to the clinical level because of insufficient d ata col­ lection in EHRs. T h e ONC and CMS recognize the importance of

comparable data between EHRs and public health, yet this study shows the agencies have declined nearly eveiy opportunity to align the De­ partment of Health and Human Services data adopted in the ACA with the MU and SCC programs.16

Although ONC and CMS have declined to require expanded de­ mographic data collection, the agencies encourage providers to voluntarily collect additional demo­ graphic data as is appropriate for their practice.16 This suggestion is merely an illusion of flexibility and

expanded data collection efforts as most EHR vendors are solely fo­ cused on building systems compliant with the SCC criteria (Andy Slavitt, chief executive officer, Optumlnsight, stated to the Subcommittee on Healthcare and Technology Sub­ committee on Small Business “[N]ew product development is focused on satisfying those regulatory hurdles, rather than on simple innovations that improve productivity.”25) Therefore, health care providers who wish to collect more informa­ tion must expand their budgets and

payment structures to develop the functionality and infrastructure within their individual EHR system or build the capacity in their own information technology depart­ ments. This is particularly challeng­ ing for health care providers that serve minority and underserved communities who are less likely to have the financial means to build this capacity. Until expanded demo­ graphic data categories are included in the SCC program requirements, vendors lack incentives to build the capacity within their EHRs.

T A B L E 3 - P o l i c y G a p s B e t w e e n D e m o g r a p h i c D a t a R e q u i r e m e n t s P r o p o s e d a n d A d o p t e d in t h e M e a n i n g f u l U s e P r o g r a m a n d T h o s e U s e d in

P u b l i c H e a l t h S u r v e y s

D e m o g ra p h ic D a t a C ateg o ry

P o s s ib le E v id e n c e -B a s e d S t a n d a r d s (E x p lic itly

A c k n o w le d g e d in F in al R ules ) N o . o f C a te g o rie s P ro p o s e d in M U A d o p te d in M U U se d in P u b lic H e a lt h Surveys

R a c e 0 M B 5 X X X D H H S 1 4 " X X CDC V cn CD O X X I0 M L o c a lly re le v a n t c h o ic e s " X NA

E th n ic ity 0 M B 2 X X X D H H S 5 " X X CDC > 3 0 " X X I0 M L o c a lly re le v a n t c h o ic e s X NA

P re fe rre d la n g u a g e IS O 6 3 9 - 1 > 2 0 0 X Xb X IS O 6 3 9 - 2 > 5 0 0 X xb X IS O 6 3 9 - 3 A p p r o x im a te ly 6 0 0 0 X X Tags f o r Id e n tify in g D e v e lo p s u n iq u e id e n tifie rs X NA NA

L a n g u a g e s , S e p te m b e r f o r la n g u a g e s in c lu d e d in

2 0 0 9 IS O 6 3 9 registry

Sex 2 X X X D is a b ility o r fu n c tio n a l A m e r ic a n C o m m u n ity S u rv ey 6 X X

s ta tu s

S e x u a l o r ie n ta tio n H L 7 8 X X G e n d e r id e n tity H L 7 8 X N ote. CDC = C e n te rs f o r D is e a s e C o n tro l a n d P r e v e n tio n ; D H H S = D e p a r t m e n t o f H e a lt h a n d H u m a n S e rv ic e s ; H L 7 = H e a lt h Level S e v e n In t e r n a tio n a l; I 0 M - In s tit u t e o f M e d ic in e ; IS O - In t e r n a tio n a l O rg a n iz a tio n f o r S t a n d a r d iz a t io n ; M U - t h e M e a n in g f u l U se p ro g ra m ; NA = n o t a p p lic a b le ; 0 M B - O ffic e o f M a n a g e m e n t a n d B u d g e t. "A ll s u b c a te g o r ie s ro ll u p t o 0 M B c a te g o rie s . bI S 0 6 3 9 - 2 a lp h a - 3 c o d e s lim ite d t o t h o s e t h a t a ls o h a v e a c o r re s p o n d in g a lp h a - 2 c o d e in IS O 6 3 9 - 1 .

S 3 8 6 | G o v e r n m e n t , L a w , a n d P u b l i c H e a l t h P r a c t i c e | P e e r R e v i e w e d | D o u g l a s e t a l . A m e r i c a n J o u r n a l o f P u b l i c H e a l t h | S u p p l e m e n t 3 , 2 0 1 5 , V o l 1 0 5 , N o . S 3

G O V E R N M E N T, LAW , A N D P U B L IC HEALTH P R A C TIC E

It is difficult to gauge th e like­ lihood for policy change in the MU and SCC programs, b u t the 2 0 1 5 voluntary SCC proposed rule may provide som e insight into future rulemakings. It is thus far the m ost aggressive proposal w ith regard to adding categories of dem ographic data; however, it proposed to m aintain the mini­ mally informative OMB standards for race and ethnicity. T he evo­ lution of the preferred language standards is a prom ising prece­ dent, although the challenges ex­ perienced with adopting a single standard may d eter future ag­ gressive policies.

Limitations T he methodology used in this

study was time-consuming, but it comprehensively collected all ad­ ministrative actions taken within the timeframe of interest. This study did not look at the HITECH legislative history or the recom­ mendations of the subagency HIT Policy Committee or the HIT Standards Committee, which would provide even m ore insight into the policymaking process.

These methods do not include uses of demographic data in EHRs beyond the MU core objective of “record demographics.” Other MU objectives utilize similar informa­ tion. For example, functional sta­ tus was adopted in MU stage 2 as a requirem ent for the care sum ­ mary document. However, limit­ ing these data to the care summary docum ent maintains the long-held view o f disability as m erely a m edical condition and precludes analysis o f prev en tab le health disparities th a t have an im pact on people w ith disabilities.

Conclusions T he use of EHRs to identify and

reduce health disparities is prom­ ising, but limited by the type of demographic data that is currently collected. To recognize HITECH’s policy priority of reducing health disparities, more granular race and ethnicity d a ta disability status, and sexual orientation and gender identity must be collected in EEIRs. The only way to ensure the con­ sistent and comprehensive collec­ tion of this information is to in­ corporate expanded requirements into the MU and SCC programs. Public health leaders have a re­ sponsibility to encourage health care providers, EHR vendors, and policymakers to adopt and effec­ tively implement evidence-based policies and practices necessary to help document and eliminate health disparities. ■

A bo ut th e A uthors Megan D. Douglas and Dominic Mack are with the National Center f o r Primary Care, Morehouse School o f Medicine, Atlanta, GA. Daniel E. Dawes is with the Office o f the President, Morehouse School o f Medi­ cine. Kisha B. Holden is with the Satcher Health Leadership Institute, Morehouse School o f Medicine.

Correspondence should be sent to Megan Daugherty Douglas, National Center fo r Primary Care, 7 2 0 Westview Dr, NCPC Bldg, Ste 3 0 0 , Atlanta, GA 3 0 3 1 0 (e-mail: [email protected]). Reprints can be ordered at http://www.ajph.org by clicking the ‘‘Reprints’’ link.

This article was accepted October 4, 2 0 1 4 .

C on trib u to rs M. D. Douglas was project director for this study and responsible for m ethodol­ ogy developm ent, analysis, an d writing. K. B. Holden contributed to the writing and editing. D. Mack was the principal investigator o f this project and along with D. E. Dawes conceptualized th e study and contributed to the writing.

Acknow ledgm ents T h e p ro je c t d esc rib e d w as su p p o rte d by th e N ational In stitu te on M inority H ealth an d H ealth D isparities g ra n t U 5 4 M D 0 0 8 1 7 3 , a c o m p o n e n t o f th e N ational In stitu te s o f H ealth.

Note. T he article’s contents are solely the responsibility o f the authors and do not necessarily represent the official views of th e National Institute on Minority H ealth and H ealth Disparities o r the National Institutes of Health.

Hum an P a rtic ip a n t P ro tectio n No protocol approval was necessary b e ­ cause all data w ere obtained from pub­ licly available secondary sources.

R eferences 1. R eport of th e Secretary’s Task Force on Black and Minority Health, vol. 1. W ashington, DC: US D epartm ent of H ealth and H um an Services; 1985.

2. LaVeist T, Gaskin D, Richard, P. The Economic Burden o f Health Inequalities in the United States. Washington, DC: Joint Center for Political and Economic Studies; 2009.

3. Institute o f Medicine. Race, Ethnicity, and Language Data: Standardization fo r Health Care Quality Improvement. W ash­ ington, DC: National Academy Press; 2 0 0 9 .

4. Agency for H ealthcare Research and Quality. 2 0 1 3 National Health Care Dis­ parities Report. 2 0 1 4 . Pub. no. 1 4 -0006. Available at: http://w w w .ahrq.gov/ resea rc h /fm d in g s/n h q rd r/n h d rl 3 / 2013nhdr.pdf. Accessed June 26 , 2 0 1 4 .

5. Agency for H ealthcare Research and Quality. 2 0 1 1 National Health Care Dis­ parities Report. 2 0 1 2 . Pub. no. 1 2 -0006. Available at: h ttp://w w w .ahrq.gov/ resea rc h /fm d in g s/n h q rd r/n h d rl 1 / n h d r l l.pdf. Accessed June 26, 2 0 1 4 .

6. Office of Management and Budget: re­ visions to the standards for the classification of federal data on race and ethnicity, 62 Federal Register 36 8 7 3 (notice October 30, 1997).

7. Agency for H ealthcare Research and Quality. 2 0 1 2 National Health Care Dis­ parities Report. 2 0 1 3 . Pub no. 1 3-0003. Available at: http://w w w .ahrq.gov/ research/findings/ n h q rd r/n h d r 1 2 / 2012nhdr.pdf. Accessed June 26 , 2 0 1 4 .

8. Joint C enter for Political and Eco­ nom ic Studies. Patient Protection and Affordable Care Act o f 2 0 1 0 : advancing health equity for racially and ethnically diverse populations. 2 0 1 0 . Available

Supplem ent 3 , 2 0 1 5 , Vol 1 0 5 , No. S3 | Am erican Journal o f Public Health Douglas e t al. | Peer Reviewed | Government,

at: http://csm h .u m ary lan d .ed u /T o o lb ar/ T oolbardocs/reform diversepopulations. pdf. Accessed June 2 6 , 2 0 1 4 .

9. Reducing health care disparities: collec­ tion and use of race, ethnicity and language data Chicago, IL: Health Research and Edu­ cational Trust; 2013. Available at: http:// wwwhpoe.org. Accessed June 26, 2014.

10. D epartm ent o f Health and Human Services. Im plem entation guidance on data collection standards for race, ethnic­ ity, sex, prim ary language, and disability status. 2 0 1 1 . Available at: h ttp ://a s p e . hhs.gov/d a ta c n c l/s ta n d a rd s/a c a /4 3 0 2 / index.pdf. Accessed June 26 , 2 0 1 4 .

11. Am erican Recovery and Reinvest­ m ent Act, Pub L No. 111-5.

12. Hsiao C-J, H ing E. Use and charac­ teristics o f electronic health record sys­ tems am ong office-based physician prac­ tices: United States, 2 0 0 1 - 2 0 1 3 . NCHS d ata brief, no 143. Hyattsville, MD: Na­ tional C enter for H ealth Statistics; 2 0 1 4 .

13. DesRoches CM, Charles D, Furukaw a MF, Joshi MS, Kralovec P, Mostashari F. A doption o f electronic health records grows rapidly, b u t fewer than half o f US hospitals had at least a basic system in 2 0 1 2 . Health A f f (Mill- wood). 2 0 1 3 ;3 2 (8 ): 1 4 7 8 -1 4 8 5 .

14. Medicare and Medicaid Programs: electronic health record incentive p ro ­ gram, 7 5 Federal Register 1 8 4 4 (proposed January 13, 2 010).

15. Medicare and Medicaid Programs: electronic health record incentive pro­ gram, 7 5 Federal Register 4 4 3 1 4 at 4 4 3 4 1 (July 28 , 2 0 1 0 ; codified at 4 2 C F R 4 1 2 , 4 1 3 , 4 2 2 , e t al.).

16. Health information technology: initial set of standards, implementation specifica­ tions, and certification criteria for electronic health record technology, 75 Federal Reg­ ister 2 0 1 4 (proposed January 13, 2010).

17. H ealth inform ation technology: ini­ tial set o f standards, implementation specifications, and certification criteria for electronic health record technology, 7 5 Federal Register 4 4 5 9 0 (July 28 , 2 0 1 0 ; codified at 4 5 CFR p art 170).

18. M edicare and Medicaid Programs: electronic health record incentive program —stage 2, 7 7 Federal Register 1 3 6 9 8 (proposed M arch 7, 2 012).

19. Medicare an d Medicaid Programs: electronic health record incentive program —stage 2, 7 7 Federal Register 5 3 9 6 8 (September 4, 2 0 1 2 ; codified at 4 2 CFR 4 1 2 , 4 1 3 , 4 2 2 , et al.).

Law, and Public Health Practice | S 387

G O V E R N M E N T, LAW , A N D P U B L IC HEALTH P R A C TIC E

20. Health information technology: standards, implementation specifications, and certification criteria for electronic health record technology, 201 4 edition; revisions to the permanent certification program for health information technol- ogy, 77 Federal Register 13832 (proposed March 7, 2012).

21. Health information technology: standards, implementation specifications, and certification criteria for electronic

health record technology, 2 014 edition; revisions to the permanent certification program for health information technol- ogy, 77 Federal Register 54163 (Septem­ ber 4, 2012; codified at 45 CFR part 170).

22. International Organization for Stan­ dardization. Language codes—ISO 639. Available at: http://www.iso.org/iso/ home/standards/language_codes.htm. Accessed June 26, 2014.

23. Voluntary 201 5 edition electronic health record (EHR) certification criteria; interoperability updates and regulatory improvements, 79 Federal Register 10880 (proposed February 26, 2014).

24. HealthIT.gov Web site. ONC Regu­ lations FAQs. Available at: http://www. healthit.gov/policy-researchers- implementers/onc-regulations-faqs. Accessed January 15, 2015.

25. Statement of Andy Slavitt, chief ex­ ecutive officer, Optumlnsight to the Sub­ committee on Healthcare and Technology Subcommittee on Small Business, June 2, 2011. Available at: http://smbiz.house. gov/UploadedFiles/Slavitt_T estimony.pdf. Accessed June 26, 2014.

R e v ie w o f S t a t e L e g is la t iv e A p p r o a c h e s t o E lim in a t in g R a c ia l a n d E th n ic H e a lt h D is p a r i t i e s , 2 0 0 2 - 2 0 1 1 | Jessica L. Young, PhD, MS, Keshia Pollack, PhD, MPH, and Lainie Rutkow, JD, PhD, MPH

W e co n d u cte d a legal m a p ­ p in g s tu d y o f state b ills related to ra c ia l/e th n ic h e a lth d is p a r­ itie s in a ll 50 s ta te s b e tw e e n 2002 a n d 2011.

Forty-five states introduced at least 1 bill th a t specifically targeted racial/ethnic health dis­ parities; w e analyzed 607 total bills. O f these 607 bills, 330 w ere passed into law (54.4%). These b ills a p p ro a c h e d e lim in a tin g racial/ethnic health disparities by developing governm ental infra­ structure, p roviding appropria­ tions, and focusing on specific diseases and data collection. In addition, states tackled em erg­ ing topics that w ere previously lacking laws, particularly His­ panic health.

Legislation is an im p o rta n t p o licy to o l fo r states to advance th e e lim in a tio n o f racial/ethnic health disparities. [Am J Public Health. 2 0 1 5 ;1 0 5 :S 3 8 8 -S 3 9 4 . doi:10.2105/AJPH.2015.302590)

DESPITE DECADES OF re se a rc h a n d aw areness,1-3 a n d in c re a s in g fe d e ra l a tte n tio n a n d a ctio n ,4-7 r a c ia l/e th n ic h e a lth d isp a ritie s p e rs is t th r o u g h o u t US society. It is w ell d o c u m e n te d th a t so m e r a c ia l/e th n ic g ro u p s a re m o re likely to live s h o r te r a n d sic k e r lives.8-10 H e a lth d is­ p a ritie s also v a ry geo g rap h ica lly . F o r e xam ple, r e s e a rc h su g g ests th a t th e r e a re m o re se v e re ra c ia l/e th n ic h e a lth d isp a ritie s a m o n g ru r a l p o p u la tio n s com ­ p a r e d w ith u r b a n d w e llin g p o p ­ u la tio n s.11 T h e s e h e a lth d is p a r­ ities a re th e re s u lt o f m y ria d social, in d iv id u a l, a n d p o litical factors, in c lu d in g h e a lth b e h a v ­ iors, h o u sin g , e d u c a tio n , incom e, a n d access to h e a lth c a re .12-15 B e ca u se o f th e co m p le x n a tu r e of th e d riv e rs o f h e a lth d isp a rities, e lim in a tin g r a c ia l/e th n ic h e a lth d isp a ritie s re q u ir e s in te g ra tin g science, p ra c tic e , a n d policy a t all levels o f g o v e rn m e n t.16

States are well positioned to use th eir policymaking pow ers tow ard eliminating ra cial/ ethnic health

disparities, a n d h ave d o n e so in the past.17 State legislative activities re ­ lated to racial/ethnic health dispar­ ities have focused on developing governm ental infrastructure focused on racial/ethnic health dis­ parities, disease-specific approaches (e.g., lupus task forces), race-specific activities (e.g., African A m erican oral health programs), and increasing awareness of health disparities through special commissions.1'

Few researchers h a v e devoted attention to m apping state legisla­ tive activity regarding racial/ethnic h ealth disparities. By n o t doing so, w e miss opportunities to further o u r u n d erstanding o f ho w states h a v e u sed legislation to elim inate ra cial/ethnic h e alth disparities, and to su p p o rt advocacy and m onitor­ ing efforts related to racial/ethnic health disparities. T o o u r know l­ edge, L adenheim and G rom an published th e first study in this area, by review ing state legislation th at specifically targeted racial/ ethnic disparities in health care a n d access from 1 9 7 5 to 2 0 0 1 .17 W e furthered th e und e rstan d in g o f the

re c e n t state legislative environm ent related to elim inating ra cial/ethnic h ealth disparities. O u r analysis ex­ a m in e d p r o p o s e d a n d enacted state legislation from 2 0 0 2 to 2011 to identify legislative a p p ro a c h e s to elim in a tin g ra c ia l/e th n ic health disparities. O ur research, which considered state bills that w ere pro­ posed and failed along with those that were passed into law, offered insights into states’ legislative agendas related to health disparities, including emerging trends and challenges.

METHODS

W e co n d u cted a legal m apping stu d y o f p ro p o se d a n d e n acted legislation re la te d to ra c ia l/e th n ic h e a lth disparities in all 5 0 states b e tw e e n 2 0 0 2 a n d 2 0 1 1.18 W e e x am ined state-level bills th a t w e re in tro d u c e d a n d failed, a nd those th a t w e re in tro d u c e d and ultim ately b e ca m e law.

Data Collection W e u sed a systematic and struc­

tu red keyw ord search o f introduced

S 3 8 8 | Government, Law, and Public Health Practice | Peer Reviewed | Y oung e t at. American Journal o f Public Health | S upplem ent 3 , 2 0 1 5 , Vol 1 0 5 , No. S3

Copyright of American Journal of Public Health is the property of American Public Health Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use.