Use of Electronic Health Information Technology in a National Sample of Hospitals That Provide Specialty Substance Use Care
Abstract
Objective:
Most U.S. acute care hospitals have adopted basic electronic health record (EHR) functionality and health information exchange (HIE) (84% and 88%, respectively, in 2017). This study examined whether rates of EHR and HIE adoption by hospital-based substance use disorder programs are lower than rates by acute care hospitals.
Methods:
Data from the 2017 National Survey on Substance Abuse Treatment Services were analyzed to examine adoption of basic EHR functionality (i.e., assessment, progress monitoring, discharge, labs, and prescription dispensing) and use of HIE by hospital-based programs. Analyses used weighted multivariable models of EHR and HIE outcomes, adjusted for nonresponse.
Results:
Of 894 hospital-based substance use disorder programs with EHR information, two-thirds (N=606, 68%) reported use of basic EHR functionality. Psychiatric hospitals were less likely than acute care hospitals to have adopted EHR (odds ratio [OR]=0.49, 95% confidence interval [CI]=0.35–0.71). Compared with nonprofit hospitals, for-profit (OR=0.23, 95% CI=0.16–0.35) and government-owned (OR=0.52, 95% CI=0.33–0.83) hospitals were less likely to use basic EHR functionality. Hospital-based programs providing medications for alcohol or opioid use disorders were more likely than those not providing such medications to use basic EHR (OR=1.95, 95% CI=1.31–2.90). Of 839 hospitals with information on HIE use, 598 (71%) reported using electronic HIE. Adoption of basic EHR functionality was the strongest predictor of HIE use (OR=4.73, 95% CI=3.29–6.79).
Conclusions:
Hospital-based substance use disorder programs trail behind U.S. acute care hospitals in adoption of basic EHR and electronic HIE. Findings raise concerns about missed opportunities to improve hospital-based substance use disorder care quality and performance measurement.
• In 2017, 68% of hospital-based substance use disorder programs reported basic electronic health record functionality, and 71% report using electronic health information exchange.
• These rates were markedly lower than reported rates from acute care hospitals in the same year.
• Findings raise concerns about missed opportunities to improve hospital-based substance use disorder care quality and performance measurement.
Substance use disorders cause significant morbidity and mortality (1). Individuals receiving specialty substance use disorder care in hospital settings are often among those with the most severe conditions and associated health complications. Furthermore, the risk of drug interactions between alcohol and drugs and prescribed medications (2–4)—including increased risk of death (5)—is considerable. These safety risks are heightened when medications used to treat substance use disorders are not listed in the medical record (6). Indeed, managing these risks requires not only accurate documentation in the health record but also robust health care coordination and communication among providers caring for patients in the hospital and those providing postdischarge care.
Electronic health records (EHRs) offer opportunities to improve the quality and safety of health care. They have been demonstrated to significantly reduce medication errors and adverse drug events, improve guideline adherence, and facilitate communication with patients (7–11). Recent evidence has also shown that they are associated with reduced hospital mortality (12). Additionally, use of electronic health information exchange (HIE) has been associated with improved health care quality and safety and reductions in unnecessary utilization and costs (13); use also facilitates timely information exchange to providers at the next level of care.
As of 2015, 84% of acute care hospitals had adopted at least basic EHR functionality in at least one unit of a hospital (14). As of 2017, 88% of acute care hospitals electronically sent HIE to providers at the next level of care (15). Recognizing the importance of HIE for the quality and safety of health care, the 21st Century Cures Act requires the Office of the National Coordinator (ONC) for Health Information Technology to promulgate regulations to further support the exchange of health information. In May 2020, the ONC published its final rule to advance this goal (16).
However, use of basic EHR functionality and electronic HIE by hospital-based specialty substance use programs may be lower than the national estimates of EHR adoption and use of HIE in acute care hospitals. One reason may be that providers of specialty substance use disorder treatment are subject to a federal health privacy law (42 Code of Federal Regulations Part 2) that is considerably stricter than the Health Insurance Portability and Accountability Act (HIPAA), and EHRs have limited ability to manage these additional privacy requirements. Furthermore, Part 2–covered programs may be disproportionately located in psychiatric hospitals—hospitals identified as having much lower basic EHR adoption rates (14).
Information about EHR adoption at acute care hospitals—specifically, at least basic EHR functionality adoption and use of electronic HIE—is derived from hospital responses to the American Hospital Association’s Annual Survey Information Technology (IT) Supplement. The functional features that constitute basic EHR adoption were determined by expert consensus (17), are considered the standard definition of basic adoption (18–21), and have been used by the ONC in its national estimates (14, 22). The IT Supplement also provides the ONC with national estimates of hospital-based electronic HIE. However, it cannot provide estimates for specific programs within hospitals, because it asks hospital respondents to report on adoption “in at least one unit” of the hospital. Thus, for programs within hospitals that are subject to additional federal privacy requirements (such as substance use disorder specialty programs), EHR adoption or use of HIE in these programs may not match the EHR adoption or use of HIE at the hospital overall.
The aim of this study was to estimate the use of basic EHR technology and electronic HIE by using data from the Substance Abuse and Mental Health Administration’s (SAMHSA) National Survey of Substance Abuse Treatment Services (N-SSATS) and determine hospital characteristics that predict use of EHR technology and electronic HIE within these settings. We hypothesized that the rate of basic EHR functionality adoption and electronic HIE use in these programs would be lower than national estimates for hospitals overall.
Methods
Data Source
The N-SSATS is an annual census of all specialty providers of substance use treatment services in the United States. It is administered to specialty providers at all levels of care (e.g., inpatient, residential, partial hospital, and outpatient) and, in the case of hospitals, among acute care general hospitals, psychiatric hospitals, and other specialty hospitals (e.g., alcoholism and maternity). The 2017 survey is the most recent N-SSATS that asked respondents about EHR adoption and electronic HIE use; it had an overall response rate of 89.2%. The study reported here was not human subjects research, and thus it did not require approval by an institutional review board.
Primary Outcomes of Interest
We examined two primary outcomes reported by hospital-based substance use disorder programs in the 2017 N-SSATS: adoption of basic EHR functional features and use of electronic HIE. The N-SSATS EHR adoption questions corresponded with those of the ONC but did not entirely match. Therefore, we used the N-SSATS responses to create an indicator of basic EHR adoption that approximated the ONC’s definition as closely as possible. We defined basic EHR features in the N-SSATS as electronic-computer sources to accomplish the following five clinical tasks: assessment, client progress monitoring, discharge, issue and receive lab results, and medication prescribing and dispensing (see Table 1 for a comparison of the functional features examined based on the ONC definition and the N-SSATS items). In contrast, the definition of HIE in the N-SSATS is the same as the ONC’s (i.e., “Do you use HIE to send client health and/or treatment information to providers or sources outside of your organization?”).
| ONC definition | Corresponding N-SSATS feature |
|---|---|
| Electronic clinical information | |
| Patient demographic data | Not included |
| Physician notes | Assessment |
| Nursing assessments | Treatment plan and client progress monitoring |
| Problem lists | Not included |
| Medication lists | Not included |
| Discharge summaries | Discharge |
| Computerized provider order entry | |
| Medications | Medication prescribing and dispensing |
| Results management of information (view) | |
| Lab reports | Issue and receive lab reports |
| Radiology reports | Not included |
| Diagnostic test results | Not included |
A further difference between the ONC and the N-SSATS is that the ONC definition asks about adoption in “at least one unit of the hospital,” whereas the N-SSATS asks respondents to “indicate if staff members routinely use computer or electronic resources, paper only, or a combination of both to accomplish their work” in their program. In the N-SSATS, electronic resources are defined as “includ[ing] tools such as electronic health records and web portals,” and paper documents are defined as “PDFs, scanned documents, or e-fax.” To approximate the ONC’s definition of “in at least one unit of the hospital,” we defined adoption of basic EHR or electronic HIE as occurring if a hospital used “any” computer-electronic source (i.e., computer-electronic only or both paper and electronic-computer) in a substance use disorder program. We used “any” for our definition, because a hospital may have more than one substance use disorder treatment program or unit (e.g., in different levels of care) and it is possible that EHR features were adopted in one but not (or not yet) in all of the programs (hence a mix of paper and computer use).
Explanatory Variables
Explanatory variables examined included hospital type (general acute care hospitals, psychiatric hospitals, and other specialty hospitals), hospital profit status (nonprofit, for profit, and government hospitals), whether the program accepts Medicaid, and whether it provides medication treatment for opioid or alcohol use disorders (methadone, naltrexone, buprenorphine, acamprosate, or disulfiram). Hospital characteristics, such as hospital type and profit status, have been shown to be associated with EHR adoption and HIE use in previous studies (including in behavioral health hospital settings) (18, 20, 23, 24). We examined whether a program accepts Medicaid, because Medicaid is a predominant payer of substance use disorder services (25). Finally, we examined whether a program provides medications to treat alcohol or opioid use disorders, because of the important role of EHRs in health care safety and quality associated with medication use and prescribing and because access to medication treatment is a measure of the quality of a substance use disorder program in general. We also created a variable that described the highest level of substance use disorder care provided by the organization (inpatient, residential, intensive outpatient or partial hospitalization, and regular outpatient), because health information technology (HIT) is likely to be most beneficial in managing care for patients with complex medical needs and who are the sickest.
Statistical Analysis
We calculated descriptive statistics of the characteristics of hospital-based substance use disorder programs and conducted bivariate analyses of associations between the explanatory variables and each primary outcome. We then fit multivariable logistic regression models for our two outcomes. In the model of electronic HIE, we also included the indicator for EHR adoption as a predictor. To address respondents with missing outcome information, we followed a missing value approach used in prior research on EHR adoption (24). Specifically, we estimated the probability of each respondent’s having a missing outcome and then weighted respondents without missing data by 1/(1−probability of having missing outcome). Using this approach, respondents with nonmissing outcomes compensated for similar respondents with missing outcomes and thus reduced the risk of bias. We estimated predicted probabilities (PPs) for significant predictors following each model. We tested the sensitivity of our specifications of the outcomes by fitting models where missing values on the outcome variables were forced into the “no” category.
Results
There were 1,024 hospitals with substance use disorder programs in the 2017 N-SSATS. In unadjusted analyses, we excluded 130 (13%) hospitals from the EHR analyses and 185 hospitals (18%) from the HIE analyses because of missing outcome information. Of the 894 facilities with outcome information that were included in the EHR adoption analysis, two-thirds (N=606, 68%) met our study criteria for having adopted basic EHR functionality (Table 2). Of the 839 hospitals with outcome information on use of HIE, 598 (71%) reported using electronic HIE. (A CONSORT diagram in an online supplement to this article shows differences in characteristics by missingness.) Compared with hospital-based substance use disorder programs that did not adopt basic EHR functionality, those that did were more likely to be in acute care general hospitals and nonprofit hospitals and to provide substance use disorder medications and offer routine outpatient care as their highest level of care. The patterns for use of electronic HIE were similar across facility types and ownership categories, as well as in having routine outpatient treatment or intensive outpatient or partial hospitalization as the highest level of care. When we limited the analysis to hospital-based programs in acute care general hospitals, EHR and electronic HIE adoption were 75% and 74%, respectively (data not shown).
| EHRa | ||||||||
|---|---|---|---|---|---|---|---|---|
| Total | Yes | No | ||||||
| (N=894) | (N=606) | (N=288) | ||||||
| Characteristic | N | Column % | N | Row % | N | Row % | χ2b | p |
| Facility type | ||||||||
| Psychiatric hospital | 268 | 30 | 137 | 51 | 131 | 49 | 48.7 | <.001 |
| General hospital | 589 | 66 | 441 | 75 | 148 | 25 | 39.7 | <.001 |
| Other hospital | 37 | 4 | 28 | 76 | 9 | 24 | 1.1 | .29 |
| Ownership | ||||||||
| For profit | 196 | 22 | 82 | 42 | 114 | 58 | 77.4 | <.001 |
| Nonprofit | 576 | 64 | 446 | 77 | 130 | 23 | 69.0 | <.001 |
| Governmentc | 122 | 14 | 78 | 64 | 44 | 36 | 1.0 | .33 |
| Accepts Medicaidd | 726 | 81 | 503 | 69 | 223 | 31 | 2.8 | .10 |
| Provides substance use disorder medicationse | 729 | 82 | 511 | 70 | 218 | 30 | 9.7 | <.001 |
| Highest level of care | ||||||||
| Inpatient | 420 | 47 | 282 | 67 | 138 | 33 | .2 | .70 |
| Residential | 51 | 6 | 32 | 63 | 19 | 37 | .6 | .43 |
| Intensive outpatient or partial hospitalization | 280 | 31 | 183 | 65 | 97 | 35 | 1.1 | .29 |
| Routine outpatient | 143 | 16 | 109 | 76 | 34 | 24 | 5.6 | .02 |
| HIE | ||||||||
| Total | Yes | No | ||||||
| (N=839) | (N=598) | (N=241) | ||||||
| N | Column % | N | Row % | N | Row % | χ2b | p | |
| Facility type | ||||||||
| Psychiatric hospital | 227 | 27 | 146 | 64 | 81 | 36 | 7.4 | .01 |
| General hospital | 563 | 67 | 417 | 74 | 146 | 26 | 6.5 | .01 |
| Other hospital | 49 | 6 | 35 | 71 | 14 | 29 | .0 | .98 |
| Ownership | ||||||||
| For profit | 174 | 21 | 103 | 59 | 71 | 41 | 15.7 | <.001 |
| Nonprofit | 543 | 65 | 402 | 74 | 141 | 26 | 5.7 | .02 |
| Governmentc | 122 | 15 | 93 | 76 | 29 | 24 | 1.7 | .19 |
| Accepts Medicaidd | 674 | 80 | 479 | 71 | 195 | 29 | .1 | .79 |
| Provides substance use disorder medicationse | 631 | 75 | 450 | 71 | 181 | 29 | .0 | .96 |
| Highest level of care | ||||||||
| Inpatient | 351 | 42 | 251 | 72 | 100 | 29 | .0 | .90 |
| Residential | 56 | 7 | 42 | 75 | 14 | 25 | .4 | .52 |
| Intensive outpatient or partial hospitalization | 294 | 35 | 197 | 67 | 97 | 33 | 4.0 | .05 |
| Routine outpatient | 138 | 16 | 108 | 78 | 30 | 22 | 4.0 | .05 |
a
Excludes hospitals with missing information on basic EHR adoption (N missing=130).
b
df=1 for all comparisons.
c
Includes state; local, county, and community; tribal; and federal government. The sample did not include Veterans Affairs hospitals.
d
Data on Medicaid payment were missing for 10 programs, and these 10 are missing from the denominator in the percentages shown.
e
Includes medications for alcohol or opioid use disorder (naltrexone, buprenorphine, methadone, acamprosate, or disulfiram).
Programs in psychiatric hospitals had lower odds of basic EHR adoption, compared with acute care general hospitals (odds ratio [OR]=0.49 [Table 3]; psychiatric hospitals, PP=0.56; acute care general hospitals, PP=0.73 [Table 4]). Compared with nonprofit hospitals, programs in for-profit or government-owned hospitals also had lower odds of basic EHR adoption (for profit, OR=0.23; PP=42; government owned, OR=0.52; PP=0.56). Greater odds of basic EHR adoption were associated with provision of substance use disorder medications (OR=1.95; provides such medications, PP=0.70; does not provide such medications, PP=0.57). Lower odds of basic EHR adoption was associated with having intensive outpatient or partial hospitalization as the highest level of care, compared with having routine outpatient care as the highest level (OR=0.49; intensive outpatient or partial hospitalization, PP=0.62; routine outpatient care, PP=0.75). In the logistic model predicting use of HIE, only adoption of basic EHR functionality was associated with electronic HIE use (OR=4.73; has basic EHR, PP=0.81; does not have basic EHR, PP=0.48) (Table 4). The results of the sensitivity analysis were qualitatively unchanged from our primary analysis.
| Basic EHRb | HIE with EHRc | |||||
|---|---|---|---|---|---|---|
| Variable | OR | 95% CI | p | OR | 95% CI | p |
| Hospital type (reference: general acute care hospital) | ||||||
| Psychiatric hospital | .49 | .35–.71 | <.001 | .84 | .56–1.27 | .41 |
| Other hospital | 1.18 | .46–3.06 | .73 | 1.10 | .46–2.67 | .83 |
| Ownership (reference: nonprofit) | ||||||
| For profit | .23 | .16–.35 | <.001 | 1.02 | .64–1.63 | .92 |
| Government | .52 | .33–.83 | .01 | 1.51 | .88–2.57 | .13 |
| Accepts Medicaid (reference: does not accept) | 1.21 | .80–1.81 | .37 | .89 | .56–1.41 | .61 |
| Provides substance use disorder medications (reference: does not provide) | 1.95 | 1.31–2.90 | <.001 | .86 | .56–1.32 | .49 |
| Highest level of care (reference: routine outpatient) | ||||||
| Intensive outpatient or partial hospitalization | .49 | .29–.81 | .01 | .70 | .41–1.21 | .20 |
| Residential | .73 | .32–1.66 | .46 | 1.05 | .46–2.38 | .91 |
| Inpatient | 1.14 | .69–1.89 | .61 | .95 | .54–1.66 | .85 |
| Basic EHR | 4.73 | 3.29–6.79 | <.001 | |||
| Constant | 2.52 | 1.37–4.63 | <.001 | 1.31 | .64–2.70 | .46 |
a
The analyses adjusted for all variables shown in the table.
b
For use of basic EHR, the total number of hospital-based substance use programs in the analysis was 886 (not 894) because eight additional hospitals were missing information on Medicaid payment.
c
For use of HIE, the total number of hospital-based substance use programs in the analysis was 742 (not 839) because 92 hospitals were missing information on basic EHR adoption and five additional hospitals were missing information on Medicaid payment.
| Variable | PP | 95% CI |
|---|---|---|
| Use of EHR | ||
| Psychiatric hospital | .56 | .50–.63 |
| General acute care hospital | .73 | .69–.77 |
| For-profit hospital | .42 | .34–.50 |
| Nonprofit hospital | .75 | .72–.79 |
| Government hospital | .56 | .47–.64 |
| Provides substance use disorder medications | .70 | .67–.73 |
| Does not provide substance use disorder medications | .57 | .49–.64 |
| Highest level of care is intensive outpatient or partial hospitalization | .62 | .56–.67 |
| Highest level of care is routine outpatient treatment | .75 | .68–.82 |
| Use of electronic HIE | ||
| Has basic EHR | .81 | .78–.85 |
| Does not have basic EHR | .48 | .42–.55 |
Discussion
In this national sample of hospital-based substance use disorder treatment programs, we found that adoption of basic EHR functionality and electronic HIE to send information to outside providers lagged behind EHR adoption and HIE use in acute care hospitals (14, 15). About two-thirds (68%) of the hospital-based substance use treatment programs reported adopting basic EHR functionality, compared with 84% of acute care hospitals, and 71% of the substance use treatment programs reported sending electronic HIE to outside providers, compared with 88% of acute care hospitals. Prior work has found that psychiatric hospitals have low rates of basic EHR adoption (14, 24). Because the programs in our sample were disproportionately located in psychiatric hospitals, it is not surprising that an overall estimate of basic EHR adoption among hospital-based substance use disorder programs was lower than the ONC estimates. However, even when we limited our analyses to hospital-based programs in acute care general hospitals, EHR adoption and HIE use were lower (75% and 74%, respectively), compared with previously reported rates of basic EHR adoption and HIE use in acute care hospitals overall (84% and 88%, respectively) (14, 15).
Our findings suggest that compared with adoption at the overall hospital level, there are unique barriers to EHR adoption and HIE use among hospital-based substance use disorder programs. Patients with substance use disorders are known to experience stigma related to their illness, including by health care professionals (26). Possibly these experiences have led some programs to be reluctant to implement EHRs. Another potential barrier, as noted above, may be that the federal 42 CFR Part 2 privacy requirements are more stringent than HIPAA. Additionally, some states have privacy laws that are more stringent than Part 2 (27). Part 2 has been criticized as making it difficult for substance use disorder treatment information to be documented in EHRs (28, 29). In February 2017, and more recently (July 2020), SAMHSA updated the Part 2 regulations to address these concerns (30, 31). Our data, from the 2017 N-SSATS, is unlikely to reflect any changes that may have occurred because of these updates to Part 2. Future research is needed to understand whether, or to what extent, the updates to Part 2 have enabled broader adoption of EHRs and HIE use in substance use disorder treatment settings.
Compared with substance use disorder programs based in nonprofit hospitals, those based in for-profit and government hospitals were less likely to have adopted basic EHR functionality, which reflects similar patterns in EHR adoption more broadly (18). This finding is notable considering the rise of for-profit substance use disorder treatment programs in the United States. Although most concerns about for-profit substance use disorder treatment programs have focused on lack of evidence-based treatments, elements such as use of a basic EHR and electronic HIE are foundational to a wide range of quality assessment and improvement activities. However, we did not find ownership to be a significant predictor of HIE use, mirroring a similar finding from a recent study of electronic HIE use among inpatient psychiatric units of acute care hospitals (23). Differences by ownership among hospital-based providers, therefore, appear to be related to initial investment in HIT infrastructure and not necessarily to the use of existing HIT for information sharing at discharge.
Hospital-based substance use disorder treatment programs that provided medications for alcohol or opioid use disorders were more likely than those that did not provide such medications to have adopted basic EHR functionality. Given the medication safety benefits of EHRs, this is a welcome finding. Still, a note of caution in interpreting these results is that the N-SSATS asks only about a single component of EHR-based medication information functionality—that is, prescribing or dispensing. An important EHR safety and quality feature that is also a part of the ONC definition of basic EHR functionality, but is not part of the information collected in the N-SSATS, is the presence of a medication list. Surprisingly, we did not find that organizations offering higher intensity levels of substance use disorder care were more likely than those offering routine outpatient care to adopt basic EHR or electronic HIE. In fact, providers offering intensive outpatient treatment or partial hospitalization were less likely than those offering only routine outpatient care to adopt basic her. Further research is needed to understand reasons for this finding.
The strongest predictor of electronic HIE use in hospital-based substance use disorder programs was having adopted basic EHR functionality. This finding is not surprising, given that EHRs would be a primary vehicle by which patient electronic health information could be exchanged. Nevertheless, it highlights that if policy makers want to increase opportunities to improve the quality and safety of care enabled by electronic HIE in substance use disorder programs, more efforts will be needed to encourage EHR adoption among specialty substance use disorder treatment providers. Additionally, EHR adoption by psychiatric hospitals faces challenges. Psychiatric hospitals were ineligible for the incentives available to general acute care hospitals from the federal Health Information Technology for Economic and Clinical Health (HITECH) Act. The HITECH Act, which provided hospitals with financial assistance and incentives to adopt EHRs, was credited as a success in spurring HIT adoption by eligible hospitals (19). No such similar program has been specifically enacted for psychiatric hospitals, but the 2018 Support Act could potentially provide the means to investigate such a policy. It allows the Center for Medicare and Medicaid Innovation to test incentive demonstration models for EHR adoption in behavioral health settings (32). As yet, no demonstration program of this type has been announced.
An important limitation of this study is that the N-SSATS HIT items did not entirely align with the definitions of basic EHR adoption and HIE use specified by the ONC. To the extent that this study misclassified whether a program had adopted basic EHR technology or used electronic HIE, we expect our estimates are an overestimate, compared with the ONC’s. Another limitation is that we were limited to hospital characteristics available in the N-SSATS. The N-SSATS database does not include hospital identifiers. Therefore, we were unable to supplement the data with other publicly available hospital and facility data, including information previously associated with EHR adoption and HIE use in hospitals and psychiatric units—e.g., hospital size (20, 21, 23) or participation in an accountable care organization (23). Finally, as we noted above, these data were from 2017—the most current year available—which might not reflect current rates of EHR and HIE adoption.
The differences between the N-SSATS and the ONC definitions are problematic from a health policy perspective. The N-SSATS is a missed opportunity to better compare adoption of electronic technology in hospital-based substance use disorder treatment programs with adoption in acute care hospitals overall. Recent work by members of our team has identified a similar issue in the Centers for Medicare and Medicaid Services’ (CMS’s) Inpatient Psychiatric Facility Quality Reporting Program (23). In addition to N-SSATS, SAMHSA’s National Mental Health Services Survey has similar limitation for measuring EHR adoption and HIE use. Given the importance of HIT in the quality and safety of health care, important future policy efforts should not only encourage adoption in behavioral health treatment settings but also apply consistent definitions of adoption to behavioral health settings, as are used elsewhere in health care settings and by policy makers.
Conclusions
The adoption of HIT that could improve the quality and safety of hospital-based substance use disorder specialty care lags behind adoption in hospital-based treatment settings more broadly. This finding was not entirely accounted for by HIT adoption in psychiatric hospitals (which is known to lag behind adoption in acute care hospitals), but it appears that there are additional barriers to EHR and HIE use in substance use disorder treatment programs based in acute care general hospital settings (possibly related to 42 CFR Part 2). Understanding the extent to which HIT adoption lags in specialty behavioral health programs would be improved by better alignment across the ONC, CMS, and SAMHSA surveys that examine such adoption.
Footnote
The authors gratefully acknowledge funding from grant P30 DA035772 from the National Institute on Drug Abuse, grant T32 AA007567 from the National Institute of Alcohol Abuse and Alcoholism, and grant T32MH109433 from the National Institute of Mental Health.
Supplementary Material
File (appi.ps.202000816.ds001.pdf)
- View/Download
- 274.18 KB
References
1.
Opioid Basics: Understanding the Epidemic. Atlanta, Centers for Disease Control and Prevention, 2020. https://www.cdc.gov/drugoverdose/epidemic/index.html. Accessed Aug 10, 2020
2.
Cone EJ, Fant RV, Rohay JM, et al: Oxycodone involvement in drug abuse deaths: II. Evidence for toxic multiple drug-drug interactions. J Anal Toxicol 2004; 28:217–225
3.
Pringle KE, Ahern FM, Heller DA, et al: Potential for alcohol and prescription drug interactions in older people. J Am Geriatr Soc 2005; 53:1930–1936
4.
Schaper E, Padwa H, Urada D, et al: Substance use disorder patient privacy and comprehensive care in integrated health care settings. Psychol Serv 2016; 13:105–109
5.
Phillips DP, Barker GE, Eguchi MM: A steep increase in domestic fatal medication errors with use of alcohol and/or street drugs. Arch Intern Med 2008; 168:1561–1566
6.
Walley AY, Farrar D, Cheng DM, et al: Are opioid dependence and methadone maintenance treatment (MMT) documented in the medical record? A patient safety issue. J Gen Intern Med 2009; 24:1007–1011
7.
Amarasingham R, Plantinga L, Diener-West M, et al: Clinical information technologies and inpatient outcomes: a multiple hospital study. Arch Intern Med 2009; 169:108–114
8.
Furukawa MF, Eldridge N, Wang Y, et al: Electronic health record adoption and rates of in-hospital adverse events. J Patient Saf 2020; 16:137–142
9.
Radley DC, Wasserman MR, Olsho LEW, et al: Reduction in medication errors in hospitals due to adoption of computerized provider order entry systems. J Am Med Inform Assoc 2013; 20:470–476
10.
Campanella P, Lovato E, Marone C, et al: The impact of electronic health records on healthcare quality: a systematic review and meta-analysis. Eur J Public Health 2016; 26:60–64
11.
King J, Patel V, Jamoom EW, et al: Clinical benefits of electronic health record use: national findings. Health Serv Res 2014; 49:392–404
12.
Lin SC, Jha AK, Adler-Milstein J: Electronic health records associated with lower hospital mortality after systems have time to mature. Health Aff 2018; 37:1128–1135
13.
Menachemi N, Rahurkar S, Harle CA, et al: The benefits of health information exchange: an updated systematic review. J Am Med Inform Assoc 2018; 25:1259–1265
14.
Henry J, Pylypchuk Y, Searcy T, et al: Adoption of Electronic Health Record Systems Among US Non-Federal Acute Care Hospitals: 2008–2015. Washington, DC, Office of the National Coordinator for Health Information Technology, 2016
15.
Pylypchuk Y, Johnson C, Henry J, et al: Variation in Interoperability Among US Non-Federal Acute Care Hospitals in 2017. Washington, DC, Office of the National Coordinator for Health Information Technology, 2018
16.
21st Century Cures Act: interoperability, information blocking, and the ONC Health IT Certification Program. Fed Reg 2020; 85:25642–25961
17.
DesRoches CM, Campbell EG, Rao SR, et al: Electronic health records in ambulatory care—a national survey of physicians. N Engl J Med 2008; 359:50–60
18.
Adler-Milstein J, DesRoches CM, Kralovec P, et al: Electronic health record adoption in US hospitals: progress continues, but challenges persist. Health Aff 2015; 34:2174–2180
19.
Adler-Milstein J, Jha AK: HITECH Act drove large gains in hospital electronic health record adoption. Health Aff 2017; 36:1416–1422
20.
Jha AK, DesRoches CM, Campbell EG, et al: Use of electronic health records in US hospitals. N Engl J Med 2009; 360:1628–1638
21.
Jha AK, DesRoches CM, Kralovec PD, et al: A progress report on electronic health records in US hospitals. Health Aff 2010; 29:1951–1957
22.
Charles D, Gabriel M, Searcy T: Adoption of Electronic Health Record Systems Among US Non-Federal Acute Care Hospitals: 2008–2014. ONC Data Brief 23. Washington, DC, Office of the National Coordinator for Health Information Technology, 2015
23.
Shields MC, Ritter G, Busch AB: Electronic health information exchange at discharge from inpatient psychiatric care in acute care hospitals. Health Aff 2020; 39:958–967
24.
Walker D, Mora A, Demosthenidy MM, et al: Meaningful use of EHRs among hospitals ineligible for incentives lags behind that of other hospitals, 2009–13. Health Aff 2016; 35:495–501
25.
Mark TL, Yee T, Levit KR, et al: Insurance financing increased for mental health conditions but not for substance use disorders, 1986–2014. Health Aff 2016; 35:958–965
26.
van Boekel LC, Brouwers EP, van Weeghel J, et al: Stigma among health professionals towards patients with substance use disorders and its consequences for healthcare delivery: systematic review. Drug Alcohol Depend 2013; 131:23–35
27.
Disclosure of Substance Use Records Without Patient Consent: 50 State Comparison. Washington, DC, George Washington University, Hirsh Health Law and Policy Program, Health Information and the Law, 2020. http://www.healthinfolaw.org/comparative-analysis/disclosure-substance-use-records-without-patient-consent-50-state-comparison. Accessed Oct 31, 2020
28.
The Impact of 42 CFR Part 2 on Care Coordination by Health Plans for Members With Substance Use Disorders. Washington, DC, Association for Community Affiliated Plans, Jan 2016
29.
Confidentiality of Patient Records and Protections Against Discrimination. Archived Public Policy Statement. Rockville, MD, American Society of Addiction Medicine, 2010. https://www.asam.org/advocacy/find-a-policy-statement/archived-public-policy-statements/public-policy-statements/2011/12/15/confidentiality-of-patient-records-and-protections-against-discrimination. Accessed Oct 31, 2020
30.
Confidentiality of substance use disorder patient records. Fed Reg 2017; 82:6052–6127
31.
Confidentiality of substance use disorder patient records. Fed Reg 2020; 85:42986–43039
32.
Substance Use-Disorder Prevention That Promotes Opioid Recovery and Treatment for Patients and Communities (SUPPORT) Act. HR 6, Public Law 115-271, 2018
Information & Authors
Information
Published In
History
Received: 9 November 2020
Revision received: 5 February 2021
Accepted: 18 February 2021
Published online: 15 April 2021
Published in print: December 01, 2021
Keywords
Authors
Competing Interests
The authors report no financial relationships with commercial interests.
Metrics & Citations
Metrics
Citations
Export Citations
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
For more information or tips please see 'Downloading to a citation manager' in the Help menu.
View Options
View options
PDF/EPUB
View PDF/EPUBLogin options
Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.
Personal login Institutional Login Open Athens loginNot a subscriber?
PsychiatryOnline subscription options offer access to the DSM-5-TR® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.
Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).