Article, Emergency Medicine

Using process indicators to optimize service completion of an ED drug and alcohol brief intervention program

a b s t r a c t

Objective: The strongest evidence for effectiveness of screening, brief intervention, and referral to treatment (SBIRT) programs is in Primary care settings. Emergency department (ED) studies have shown mixed results. Implementation of SBIRT into ED settings is complicated by the type of patients seen and the fast-paced, high- throughput nature of the ED environment that makes it difficult to reach patients flagged for SBIRT services. This study uses data from an ED-based SBIRT program to examine the relationship between screen-positive rate, ED patient flow, and SBIRT service delivery.

Methods: Data for the study (N = 67137) were derived from weekly reports extracted directly from one hospital’s electronic health record. Measures included time and day of patient entry, drug/alcohol screen result (positive or negative), and whether the patient was reached by SBIRT specialists. Factorial analysis of variance compared variations in screen-positive rates by day and time and the percentage of patients reached by SBIRT specialists during these periods.

Results: Overall, 56% of screen-positive patients received SBIRT services. Only 5% of patients offered SBIRT services refused. Day and time of entry had a significant interaction effect on the reached rate (F12,14166 =3.48, P b .001). Although patient volume was lowest between 11 PM and 7 AM, screen-positive rates were highest during this period, particularly on weekends; and patients were least likely to be reached during these periods.

Conclusions: When implementing an ED-based SBIRT program, thoughtful consideration should be given to patient flow and staffing to maximize program impact and increase the likelihood of sustainability.

(C) 2014

  1. Introduction
    1. Background and importance

Screening, brief intervention, and referral to treatment (SBIRT) for alcohol and drug use is an effective and evidence-based protocol by which assessment and treatment services are delivered to patients who have been identified as unhealthy users of alcohol or drugs via systematic screening [1]. It is widely regarded as a promising strategy to combat the Disease burden resulting from substance use [1-3]. The strongest evidence for SBIRT’s effectiveness comes from randomized controlled trials conducted in primary care settings [4-8]. The SBIRT studies in emergency departments (EDs) and trauma centers have shown both positive [9-14] and null [15,16] results, leading some experts in the field to question the push toward widespread dissemina- tion of SBIRT in emergency settings [17].

Deemed a “teachable moment” in much of the alcohol intervention literature [18-20], an ED visit presents an opportunity to intervene

* Corresponding author. Tel.: +1 404 413 6323.

E-mail addresses: [email protected] (J. Akin), [email protected]

(J.A. Johnson), [email protected] (J.P. Seale), [email protected] (G.P. Kuperminc).

with patients exhibiting unhealthy alcohol or drug use who might otherwise go undetected. Estimates suggest that 1.2 million to 5.1 million ED visits annually may be attributed to excessive alcohol use and drug use [21,22], whereas an SBIRT program implemented in an Urban academic ED found that 20% to 30% of patients presenting to the ED used alcohol and/or drugs at harmful levels [23]. High propor- tions of ED patients are uninsured or publicly insured, have significant health issues, and report a general lack of access to other health care providers including primary care [24,25]. So, despite the mixed evidence for SBIRT’s effectiveness, ED-based SBIRT programs likely serve a population of patients that would not receive advice and feedback about their substance use in other health care settings [26].

Successful implementation of an SBIRT program in an ED environment can be challenging. Patients presenting to EDs are often very sick or in a great deal of pain and, as a result, may not be receptive to a brief interven- tion for their substance use. Likewise, urban EDs are often fast paced and overcrowded [27] with tremendous pressure placed on providers to im- prove Patient throughput, leaving little time for alcohol/drug interven- tions, which may last from 5 to 30 minutes. Regardless of setting, health professionals frequently cite time constraints as a major barrier to alcohol screening and intervention implementation [28,2]. Because inefficient ED throughput negatively influences both the quality of care and the

http://dx.doi.org/10.1016/j.ajem.2014.10.021

0735-6757/(C) 2014

economics of the hospital [29], SBIRT program administrators must structure programs to avoid slowing down ED throughput while maximizing program service delivery.

Despite the challenges, near universal screening (97%) for harm- ful alcohol and drug use can be achieved by embedding a short screening tool into an ED’s electronic triage system [30]. Reaching those patients who screen positive and delivering a brief interven- tion are more difficult. A review of ED-based screening and brief intervention (SBI) randomized controlled trials found that the percentage of eligible, screen-positive patients enrolled ranged from 35% to 68% [12,16,31,32]. A cross-site evaluation of Substance Abuse and Mental Health Services Administration (SAMHSA)-funded SBIRT programs in a variety of health care settings found that, of those recommended for SBIRT services, 63% actually received them [33]. Failing to reach screen-positive patients limits SBIRT program impact and negatively affects program success. Ethical questions may also arise because health systems are obligated to intervene if screening identifies health- compromising behaviors. Although Peterson and colleagues (2012)

[34] developed a replicable staffing model for future ED-SBIRT pro- grams allowing for a coverage rate between 28% and 54%, analysis was limited to patients with alcohol-related discharge diagnoses. Previous studies have shown that most patients who could benefit from a brief intervention are undetected by ED staff (ie, the medical record would not reflect an alcohol diagnosis) [23,35,36]. As future ED-SBIRT programs are implemented, it is important that administrators understand the factors that impact the ability to serve SBIRT-eligible patients and adjust staffing and program protocols to ensure that the maximum number of eligible patients is served.

Purpose

This report uses data from one site of the SAMHSA-funded Georgia Brief Assessment, Screening, Intervention, and Continuum of Care System project to inform future ED-SBIRT practitioners on ways to optimize the service coverage of their respective programs. The report addresses the following questions: (1) How did the characteristics of patients screening positive for harmful drug or alcohol use differ from those screening negative? (2) What percentage of screen-positive patients were reached by SBIRT service providers, and what were the outcomes of those interactions? (3) Were there variations in the percentage of patients screening positive by day and time of ED admission? (4) How could this information coupled with ED patient volume inform SBIRT program staffing? This study expands the study of Peterson et al that relied on patient discharge records with mentions of alcohol by using records of patients identified through an alcohol and drug brief screening instrument successfully administered to 97% of adult ED admissions.

  1. Method

As part of a federally funded, dual-site ED-SBIRT implementation effort, all patients 18 years or older entering the ED of a single urban

hospital site were screened by Triage nurses using a three-item screen- ing tool (Fig. 1). Screening questions were integrated into the facility’s electronic triage system and designed to detect patient’s Tobacco use, unhealthy alcohol use, illicit drug use, and/or prescription drug misuse. Patients were considered screen positive if they reported drinking more than the National Institute of Alcohol and Alcoholism daily limits for alcohol use on one or more occasions in the past 12 months, that is, 4 or more standard drinks per day for women and 5 or more per day for men [37]. Patients reporting past-year illicit drug use or use of prescription drugs in a way other than as prescribed were also deemed screen positive [38]. Screen-positive patients were flagged in the ED’s electronic Tracking system, indicating a need for a more comprehensive assessment and delivery of appropriate intervention and/or referral services by SBIRT specialists who provided 24/7 ED coverage. A complete description of this process and the resulting high screening

rates has been previously published [30].

The brief intervention component of this SBIRT program was based on motivational interviewing (MI), a nonconfrontational, nonjudgmental, patient-directed counseling style [39]. Specialists delivering the brief intervention often held master’s level counseling degrees or an equivalent degree and were trained in both data collection and MI. Administrators of SBIRT monitored data collection and service delivery by recording and analyzing specialists’ sessions with patients and providing feedback from both program evaluators and MI coaches.

Data source

Data derived from one ED-SBIRT site were compiled in weekly reports automatically generated by the electronic health record and emailed to the SBIRT project director. Reports contained information on every adult patient entering the ED during the 7-day period including whether or not the 3-question screen was administered at triage, screen result (whether the screen was positive or negative based on responses to alcohol and drug screening questions), and the disposition of screen-positive patients’ interaction with a specialist (if any). Based on these data, the SBIRT administration team monitored weekly reports and implemented quality improvement efforts designed to address perceived barriers to assessment completion and maximize the percentage of screen-positive patients receiving SBIRT services. In addition to screening and assessment information, weekly reports included information on patient age, race, sex, length of time in ED (hours), and date/time/day of entry into the ED.

This study uses data from weekly reports generated between January 1, 2011, and May 5, 2012 (N = 67137) to systematically examine ED patient flow, differences in screen-positive rates over time, and the impact of these factors on specialists’ ability to reach patients and deliver SBIRT services. This 16-month period was selected because it represented the midpoint of the 5-year project. During this period, early implementation issues would have been addressed, the ED staff would have become accustomed to the screening process and

Have you used any tobacco products in the past 12 months? Yes No
  • (a) WOMEN: How many times in the past 12 months have you had 4 or more drinks in a day?
  • 25 or more times 13-24 times 6-12 times 1-5 times None

    (b) MEN: How many times in the past 12 months have you had 5 or more drinks in a day?

    25 or more times 13-24 times 6-12 times

    1-5 times

    None

    In the past twelve months, did you smoke pot (marijuana), use another street drug, or use a prescription painkiller, stimulant, or sedative for a non-medical reason?

    No Yes

    If yes, Which ones?

    Patient gives: Drug Name, Drug Amount, Drug Frequency, Drug Route, Drug Last Used

    Fig. 1. Screening questions.

    the presence of specialists, and the delivery of services would not be affected by the loss of staff that often occurs as projects near completion.

    Measures

    Whether or not the patient was screened at triage was coded yes or no. The result of the screen was also dichotomous (positive or negative) based on patients’ response to the single alcohol and drug screening questions. An affirmative response to one or both of the questions was considered a positive screen. The disposition of the interaction between patient and specialist (if any) was categorized as follows: Complete, Incomplete, Refuses, Unable to Communicate, and Denies Positive Prescreen (see Table 1 for category descriptions). The time of entry into the ED was divided into the 3 SBIRT work shifts: 7 AM to 3 PM, 3 PM to 11 PM, and 11 PM to 7 AM. Most patients (~ 98%) were white or African American; thus, Patient race was categorized as white and nonwhite for use in bivariate analyses.

    Screening rates were calculated by dividing the number of patients screened by the total number of patients in the sample. Screen- positive rates were calculated by dividing the number of patients screening positive by the number of patients screened. The patient- reached rate is the number of patients approached by a specialist, regardless of final disposition, divided by the number of patients screening positive.

    Data analysis

    Bivariate analyses compare characteristics of screen-positive and screen-negative patients, and descriptive statistics are used to examine the final disposition of patients’ interactions with specialists. Factorial analysis of variance (ANOVA) compares screen-positive rates and reach rates by day of week and time of day. It was expected that night and weekend patients would differ from day and weekday patients in both screen-positive rate and reach rate. Thus, 1-way ANOVA compares the screen-positive rate and the reach rate over 6 groups of patients divided by 2 variables: work shift and weekend vs weekday, with week- end defined as 7 AM Saturday to 7 AM Monday. Welch adjusted F ratio is robust to violations in homogeneity of variance [40] and thus was obtained if Levene F test failed. For investigating main effects, Games- Howell post hoc comparisons were performed because this procedure does not assume group sizes and sample variances are equal and because it controls the inflated type 1 error rate [41]. All analyses were performed using IBM SPSS Statistics 21. This research was approved by the Institutional Review Boards at Georgia State University and the Medical Center of Central Georgia.

    Table 1

    Outcomes of screen-positive patients reached in the ED (n =7910)

    Outcome Explanation Percentage (n)

    1. Results
      1. Characteristics of study participants

    Between January 1, 2011, and May 5, 2012, 97% (65151/67137) of adult patients entering the ED of one Georgia Brief Assessment, Screening, Intervention, and Continuum of Care System SBIRT site were screened at triage, with 21.8% (14187) screening positive for unhealthy alcohol or drug use. Patients had a mean age of 48.6 years. Screen-positive patients were 9 years younger, on average, than those screening negative (t = 59.58, P b .001). Although women comprised a majority of adults entering the ED, men were significantly more likely than women to screen positive (30.1% vs 13.8%, ?2 = 2657.62, P b .001). The sample was largely biracial, with whites making up 43% of the sample, African Americans about 55% of the sample, and other races/ethnicities representing less than 2% of the sample. white patients were less likely than nonwhite patients to screen positive (19.9% vs 22.0%, ?2 = 44.84, P b .001).

    Main results

    Fifty-six percent (7910/14187) of screen-positive patients were reached by specialists. Most patients (81.8%) reached by a specialist completed the full assessment and received a brief intervention. Only a small percentage of patients (5.3%) refused to engage in services. Other specialist/patient interactions are described in Table 1.

    Fig. 2 displays the mean number of patients entering the ED (volume) and screen-positive rates for the 3 standard 8-hour work shifts (time) for each day of the week. There were significant main effects of both time (F2,67113 = 72.71, P b .001) and day of patient entry into the ED (F6,67113 =2.59, P = .016) and a significant interaction between day and time (F2,67113 =3.19, P b .001) on the screen-positive rate. To further explore the effects of time and day on the screen- positive rate, we used a 1-way ANOVA to compare the screen-positive rates of 6 groups: the 7 AM to 3 PM,3 PM to 11 PM, and 11 PM to 7 AM shifts of weekdays (7 AM Monday to 7 AM Saturday) and the same 3 shifts of weekends (7 AM Saturday to 7 AM Monday). The results are presented in Table 2. The groups were significantly different in screen-positive rates (Welch F5,18186.0 =29.95, P b .001). Post hoc tests were performed using the Games-Howell procedure because the 6 groups had unequal sample sizes and variances. The screen-positive rate during the weekend 11 PM to 7 AM shift (27.8%) was significantly higher than that of all other shift rates, which ranged from 20% to 24% (P b .01 for all comparisons). The screen-positive rate during the weekday 11 PM to 7 AM shift (24.3%) was significantly higher than the weekday and weekend 7AM to 3 PM/3 PM to 11 PM shifts (P b .01 for all comparisons). Likewise, day and time had a significant interaction effect on reach rate (the percentage of positive screens reached by a specialist) (F12,14166 =3.48, P b .001). Comparing the reached rate over the 6 groups described above (Section 3.2) revealed a significant difference in reach rates by group (Welch F5,4356.3 =61.45, P b .001, Table 2). The reach rate was lowest during the 11 PM to 7 AM shift for both weekdays

    Complete Specialist performed assessment and delivered appropriate SBIRT services.

    Incomplete Specialist reached patient and began

    assessment but was unable to complete either assessment or SBIRT service.

    Refuses Specialist reached patient, but patient declined to participate.

    81.8% (6,469)

    0.2% (15)

    5.3% (417)

    (47.5%) and weekends (38.0%), with the highest reach rate observed

    during the weekday 7 AM to 3 PM shift (63.3%). Post hoc comparisons using the Games-Howell procedure revealed that the reach rate during the 11 PM to 7 AM shift on Saturday and Sunday (38%) was significantly less than the reach rate during any other weekday or weekend shift (P b .001 for all comparisons).

    Unable to Communicate

    Denies Positive Screen

    Specialist reached patient but determined that patient was unable to communicate because of mental state (intoxication, sleeping), disability,

    or severe illness/injury.

    Specialist reached patient but did not continue with assessment or services because patient denied answering alcohol and/or drug screen affirmatively.

    5.8% (463)

    6.9% (546)

    Patient volume also varied by day and time (Fig. 2), with less than

    half as many patients entering the ED during the 11 PM to 7 AM shift compared to the 7 AM to 3 PM and 3 PM to 11 PM shifts (22.6 vs 60.3 vs 53.7 patients per shift per day, respectively); and total patient volume was lower on Saturday and Sunday, averaging 124.9 patients per day, than on weekdays, which averaged 141.6 patients per day. The patients’ average length of stay peaked during the 3 PM to 11 PM shift during both weekends (7.0 hours) and weekdays (7.5 hours).

    160

    Number of Patients entering the ED and % Screening Positive by Day and Time

    140

    120

    100

    80

    60

    40

    20

    0

    Monday Tuesday Wednesday Thursday Friday Saturday Sunday

    30%

    27%

    24%

    21%

    18%

    15%

    12%

    9%

    6%

    3%

    0%

    Volume 11pm-7am Volume 3pm-11pm Volume 7am-3pm

    % Positive 11pm-7am

    % Positive 3pm-11pm

    % Positive 7am-3pm

    Fig. 2. ED patient volume and percentage screen positives by day and time.

    1. Limitations

    The study has several limitations. First, the data on patient flow and screen-positive rates are limited to a single ED. Although many EDs, particularly in urban areas, may have similar patterns, SBIRT protocol and staffing should be based on data collected from the ED in which it will be implemented rather than relying on the results shown here. Furthermore, the reached rate could have been affected by untested factors such as specialists’ individual work efficiency, the time spent enrolling patients, or environmental characteristics of the hospital; and although these factors are discussed, the authors did not systematically assess them.

    1. Discussion

    Over the past decade, there have been significant efforts to support adoption and implementation of SBIRT into general health care settings including over $300 million in funding from SAMHSA to support both SBIRT services and training of health professionals [42,43]. In 2011, the Hospital SBI Initiative, a national initiative based at the University of Chicago’s National Opinion Research Center, was founded for the purpose of preparing the nation’s hospitals to screen, prevent, and treat patients’ unhealthy alcohol, drug, and tobacco use; and in 2012, SAMHSA funded a national SBIRT Addiction Technology Transfer Center to disseminate information on SBIRT to health care providers [44]. In addition, the Joint Commission has adopted measures for screening and brief intervention as part of its National Hospital Inpatient Quality Measures [45].

    If these efforts are successful in disseminating SBIRT into general health care, maximizing the number of patients seen in these programs will be critical to program sustainability. Because recommended

    Table 2

    Comparing SBIRT process indicators by work shift and weekday vs weekend (N = 67137)

    Group % Screen positive (SD) % Reached (SD) Volumea LOSb

    payment rates for SBI services are relatively low ($24 for Medicaid patients, $34 for patients with private insurance for services lasting 15-30 minutes and rates approximately twice these amounts for services lasting more than 30 minutes) [46], SBIRT program administra- tors need to identify optimal times for seeing patients in the ED and schedule staff accordingly. Likewise, specialists staffing the ED must work quickly and efficiently to see as many patients as possible if the program is to be financially sustainable. This report aligns with a previous recommendation that additional SBIRT resources are needed to treat patients presenting during late night to early morning hours and on weekends in the ED [34]. It strengthens that recommendation by including not only patients with alcohol-related discharges in the analysis but also patients reporting any drug or alcohol misuse during the year before ED presentation. This study builds on previous research by analyzing actual reach rates of an ED-SBIRT program and coupling that information with overall ED patient volume, screen-positive rate, and recorded outcomes of patient-specialist interactions.

    In this single-site study, 1 in 5 (21%) ED patients older than 18 years reported unhealthy alcohol or drug use. Although few patients (only 5%) refused to discuss their substance use with SBIRT staff, reaching patients in the ED proved challenging. In the time period studied, just over half (56%) of patients needing services were successfully approached by specialists and given the opportunity to talk about their substance use. Similarly low rates have been reported in other studies [12,16,31-33]. Program staff described numerous challenges that impacted their ability to reach higher percentages of patients. Because reduction of ED Waiting times was viewed by ED administra- tion as a high priority to improve patient satisfaction and compete successfully with other local EDs, SBIRT services were viewed as an op- tional service rather than an essential one. As a result, there were no des- ignated space for conducting SBIRT assessments and no designated point in patient flow for completing the process; and specialists spent signifi- cant amounts of time searching for patients and waiting for other health professionals to complete their tasks. In addition, there were significant reporting requirements from the grant’s funding agency that reduced specialists’ efficiency including mandatory assessment questions, consent forms for patients selected for long-term follow-up, logs of patients receiving services, and the types of service delivered.

    Weekday (M-F) 7 AM-3 PM

    20.7 (0.41)

    63.3 (0.48)

    63.8

    6.2

    3 PM-11 PM

    19.7 (0.40)

    55.1 (0.50)

    55.8

    7.5

    11 PM-7 AM

    Weekend (S-S)

    24.3 (0.43)

    47.5 (0.50)

    22

    6.5

    7 AM-3 PM

    20.4 (0.40)

    59.2 (0.49)

    51.1

    5.8

    One area of particular interest is this program’s low rate of comple-

    tion when screen-positive rates were highest. During day shifts (7 AM- 3 PM), when patient volumes and SBIRT staffing ratios (specialists to

    3 PM-11 PM

    20.4 (0.40)

    52.4 (0.49)

    48.9

    7.0

    entering patients) were highest, specialists completed SBIRT services

    11 PM-7 AM

    27.8 (0.41)

    38.0 (0.50)

    24.9

    6.6

    with almost two-thirds of patients. On the other hand, between the

    a Volume = average ED admissions.

    b LOS = length of stay in hours.

    hours of 11 PM and 7 AM, when fewer patients presented to the ED and screen-positive rates were highest, SBIRT reach rates were lowest

    (38% on both Saturday and Sunday). Although one important contribut- ing factor was reduced staffing during nights and on weekends due to low overall patient volumes, other factors may also have contributed such as increased likelihood of patients being asleep or intoxicated, decreased energy and efficiency of staff during the night and early morning hours, a more relaxed work pace during times of low patient volumes, or more rapid overall ED throughput due to lower patient volume. In an examination of patients reached by weekly volume (results not shown), the percentage of patients reached declined during weeks when ED volume decreased. The SBIRT specialists described that although there were fewer screen-positive patients who needed their services during these periods, patient turnover was faster during lower-volume periods, meaning that more patients were discharged from the ED before program staff were able to deliver services. Qualitative data collection such as direct observation of SBIRT service delivery during varioUS time periods could elucidate the most important contributing factors to SBIRT service completion and suggest how to address them.

    Potential solutions

    This study suggests that strong consideration should be given to providing adequate staffing during times when patient needs are highest, for example, nights and weekends. Another remedy to low SBIRT completion rates would be to implement a standing order requiring SBIRT services to be completed for all screen-positive patients before patient discharge. Because of the importance of minimizing patient waiting times in the ED, such an order would have to be careful- ly implemented to maximize SBIRT efficiency and patient throughput. With or without such a standing order, other measures that could im- prove SBIRT completion rates include identifying one or more designat- ed points during the patient’s care when they would receive SBIRT services, for example, immediately after triage, and providing one or more designated areas for providing SBIRT services. Technology could also be used to improve efficiency. Electronic tracking of patients could help SBIRT specialists locate patients more quickly. Equipping specialists with tablets containing screening questions and with a link directly to the electronic health record to allow for real-time patient charting would allow specialists to move from room to room quickly without having to return to an office or nursing station to retrieve screening materials or record services delivered. Targeted quality improvement measures involving both ED and SBIRT staff and provid- ing Real-time feedback could also be used to improve performance.

    Although barriers to SBIRT service delivery in the ED are numerous,

    this study demonstrates that unhealthy alcohol and drug use among ED patients is high and that, when reached by specialists, the overwhelm- ing majority of patients will engage in and complete SBIRT services. Thoughtful consideration of patient flow, program staffing, and efficien- cy can increase the number of screen-positive patients receiving SBIRT services. With careful planning, support from the ED staff, and collabo- ration with ED administration to make the intervention a priority, SBIRT programs can be an integral and sustainable component of hospital EDs.

    Acknowledgments

    This research was funded by a grant from the Substance Abuse and Mental Health Services Administration (T1019545).

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