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We live in a time of rapid and profound change. New organizations emerge and try to succeed, existing organizations reorganize, combine, disappear, linger, or grow. We are moving, for better or worse, from an economy that provides material things to one that produces ideas, the information economy.

There is an prophetic story about the dawning of the airline industry. In this story the railroaders wanted nothing to do with the new industry. After all, they were in the railroad business which, at the time, was THE most effective and efficient method of getting people and things from place to place. What they missed was that they were not in the railroad business at all but rather in the transportation business. They failed to recognize the applicability of their well developed and effective skills in managing and coordinating the movements of large numbers of people and things. Today we can easily see where that failure has gotten them.

The Institute is currently in a similar position. Not for the first time in our 50 year history, we have experienced rapid and profound changes in our funding and our University affiliation. As a result, we are looking at ourselves and our environment to understand what we have done and, more importantly, what MIMH version 4.0 will do.

Part of those discussions has been what and how we should share what we do publically – that is on our various web sites. Over the years there has been a disinterest in sharing information publically. When asked for information to feed our sites we hear, “I have real work to do, work that pays for our salaries and supports our partners, and I have more real work to do than I have hours in the day to accomplish.” This is certainly true. Most of us work long hours just to keep up with our projects’ required products and tasks. This attitude believes that we are in the support business. That our primary function is to provide evaluation, project management, grant writing, prevention, … support to our partners. With this view, sharing information publically is really far down on the priority list. It is something that can be relegated to others as we work on the important things.

It seems to me, however, that this is a “railroad” view and misses the opportunity to revision ourselves more broadly.

MIMH As Curator

From a broader perspective, I believe that we are in the business of knowledge curation. We collect facts and bits of information, we combine and recombine them into knowledge and skills, and we share the results with our partners and the broader public.

For example, in our MOSBIRT grant we reviewed the treatment literature for effective brief interventions, found relevant evidence based models in the adolescent substance use literature, modified those to fit within the context of medical settings, developed an evaluation based on the grant requirements and local interests, and supported it all through an information system that combined current state-of-the-art infrastructures that created assessment and feedback models refined by the current literature and our rich set of experiences in  previous projects.

In looking at our other projects, I think that this process is repeated again and again. We look at the data, which is generally the scientific literature, to develop an understanding of the issues and possibilities. We use that curated knowledge to develop potentially effective and innovative programs. And we use that same process to design evaluations to help hone those into effective, efficient, and sustainable programs.

Sharing our information broadly is the key to this new view. If we limit sharing to one person/agency, then our value is only apparent to that individual/agency. Sharing broadly lets more folks know what we have to offer. Sharing broadly shows our skills and innovations. Sharing broadly increases our value to the community. Sharing broadly is our best advertisement. Our current web presence provides support for this idea. The pages where we share most freely are those where we also get the most interest.

If we accept the notion of curation as our core business then sharing broadly is not something that we relegate to others. It is key to what we do, how we do it, and who we are becoming.

Today I am live blogging from the 2012 Guze Symposium on Alcoholism at Washington University. Focused on College-Aged drinking, it features speakers looking at the topic from a variety of perspectives. Because this is live blogging please excuse any ungrammatical utterances incorrect words, etc..

Richard Grucza's, WU Canceler, provided introductions. Use among student is a huge problem. Every week he receives a “litany” of alcohol related reports Friday morning (college weekends starts Thursday evening) and the following Saturday and Sunday mornings. This problem has been going on for years and has been consistent. The progress is slow but this is something that needs continued commitment. WU is working with the National College Health Improvement Project (with Dartmouth) focusing on improving students’ health.

Aaron White, PhD, NIAAA, "College-Age Drinking: Trends and Emerging Concerns"

Trends

• This is a global concern. US teens drinking less than teens in dozens of European countries.
• The concerns as with heavy drinking
• In a two week period full time college students (40%) binge more than post high school students (35%) and 12th graders (25%)
• The average drinker in the 12-20 drinks at the binge level
• 58% are not drinking at risk BUT only 15% who do drink do not binge
• 60% of college student drinkers have 10 or more drinks on an occasion

Emerging concerns

• Alcohol-induced amnesia
  • Alcohol interferes with long term memory storage
  • In a blackout you still act you just do not remember. Typically what you did was risky and a poor choice
  • Blackouts DO occur in non-alcoholics AND are common in that group (with high levels of binge drinking)
  • Students which drink have blackouts commonly - 51% lifetime, 40% in last year, and 9% in the last two weeks.
  • Males tend to ignore this because the act on the world. Females are frightened because things get done to them.
  • Fragmentary blackouts, grey outs, remember only bits and pieces of the time. this is the most common. Occurs with a .2 BAC. (full blackout is 50% likely with a .3 BAC.
  • Females are more sensitive to alcohol and may be more likely to have these. Alcohol is the date rape drug.
  • What will increase BAC (and these blackouts)
    • chugging
    • highly concentrated drinks
    • empty stomach
• Overdoses
  • Toxic dose – in two hours, 10/140 lb woman, 13/160 lb male
  • Do not have good statistics for this.
  • Hospitalizations for this are on the rise.
• Overdoses with other drugs
  • Pain medication overdoses 122% increase between 1999-2008
  • 3/4 of drug overdoses are related to suicide
  • This combination increase the risks quite significantly.

Kenneth J. Sher, PhD, UM-C, "College Student Drinking: Person and Environmental Contributions"

Students see blackouts as “fun” and get together the next day to figure out what they did.

Aspects of college associated with problematic drinking.

• There a higher prevalence of abuse/dependence is highest 18-25 and drops steadily after than. This even if there is no obsessive use.
• Major individual and contextual transition
• College students drink less in HS, more in college, and the rate drops back to the non-college group after college. While this is positive in that it does not necessarily lead to alcoholism it is very risky.
• Drinking is higher for on-campus students why does this happen
  • selection – bingers seek binging environments
  • socialization – living in Greek housing also increases binging for initial non drinkers.
• In the first year, about half of the variance in heavy drinking is related to pre-college behaviors.
• Lots of data with regards to Greek membership. One interesting thing is that those who later join a Greek organization increase their level of drinking and those who drop out decrease their levels.
• Class schedules also impact drinking earlier class attendees have lower drinking levels.
• Trying to increase classes on Fridays do not decrease drinking on Thursdays.

Kim Fromme, PhD, University of Texas at Austin, "A Story about Drinking and Risky Behaviors from High School through College"

• 70-90% of college students drink
• In college 56% of men and  35% of females binge drink
• Normative beliefs increase use (the beliefs are more impactful for drinking than are actual drinking behavior)
  • descriptive norms - individual beliefs about peer drinking levels
  • injunctive norms- individual beliefs per approval of drinking

UT Experience

• 6 year longitudinal study of incoming students at UT Austin
• 49% abstention in HS, 36% after freshman year
• In HS - peer drinking and drinking values have a direct effect on alcohol use
• College students have higher levels of drinking, pot, sex, and morbidity then non-college peers
• People who drink more in HS select higher risk groups and peers. They also showed greater increases from HS to sophomore years.
• High sensation students whose parents kept a close eye on them during HS showed rapid increases in risky use when the entered collect. However, high parental supervision in HS did lead to overall lower level of problems. 
• Underage drinkers drink more per occasion but with fewer occasions. Legal drinkers drink more often but at lower levels per occasion.
• Social motives are more powerful predictors of alcohol use than were academic motives (though both were significant).
• No surprise, students are more likely to do stupid (risky) things when they are drinking.
• Aggression increase
  • A BAC .01 increase lead to a 6% increase in odds of aggression
  • A 10 point increase in subjective drunkenness had a 15% increase in the odds of aggression
• DUI increases
  • BAC does not impact this
  • Subjective drunkenness does predict (lower levels lead to higher levels of DUI)

Mary E. Larimer, PhD, University of Washington, "Brief Interventions for Alcohol Problems in the College-Age Population"

2002 NIAAA task force recommendations that work. She has published three reviews about brief interventions the last in 2011.

• Cognitive behavioral skills with norms clarifications and motivational enhancement
• Brief motivational enhancement
• Alcohol expectancy challenge
• Education only did not work
• Common ingredients
  • challenge alcohol expectancies
  • teach moderate drinking and management skills
  • enhance motivation to change
  • correct misperceived norms (you drink x, you thought other drink y, others really drink z)
• Personalized feedback part of the BASICS program
  • personalized feedback intervention (PFI)
  • personalized normative feedback (PNF)
• The effects are emergent and improves over time (PNF). (This may be also may be an effect
• Just standalone reports alone have good outcomes with reduced drinking but not as much with negative effects. This may be because of a relatively short follow-up.
• Trial of personalized normative feedback (PNF) – only tested descriptive norms (drinking behaviors not attitudes towards those behaviors).
  • Students think others drink more than they do
  • Important because this normative belief is associated with more drinking
  • Use a “typical” student – but what is the most effective comparison group? Study compared
    • the similarity of the individuals
    • the magnitude of the discrepancy in judgment
    • *** Typical student feedback worked the best (basically the lower use norm is better)
  • Compared just a PNI with the full BASICS web program (none of which take more than 15 minutes.)
    • There were no significant differences between these two groups.
  • Generally speaking the effect sizes are small to medium (in the .3 range). But they also have relatively small costs.
• Drinkers and non drinkers both misperceive the level of college drinking (over estimate its use).
• Results for normative information specific for women show additional impact but it is mediated by gender identity. The effect is only for those that are more closely identified with female identity. (MGH comment: What this suggests is that “objective” distinctions are not as impactful as perceived identities and that relying on those may actually decrease the impact of the information.)

Mary M. Heitzeg, PhD, University of Michigan, "Risk, Reward and Impulsivity: Neuroimaging Vulnerability in College-Aged Drinkers"

Vulnerability for alcoholism based on neural activity

• Family history 4-10 times the likelihood of becoming alcoholism. It is thought to be 50% genetic.
• There are clear impacts of alcohol ad alcoholism in behavioral regulation circuitry. Her question – are there problems with these areas before alcoholics.
• Risk group shows reduced activation in the ventral striatum. They may be less likely to anticipate negative outcomes and act impulsively.

Richard Grucza, PhD, Washington University, "The Unexpected Public Health Effects of the 21 Drinking Age"

• Secular trends in binge drinking and the (im)moderating effects of college
  • For men binge drinking have been reducing steadily and significantly across all age groups from the 1980s to 2005
  • For women there have been no reductions with an increase in the 21-23 group.
  • However these differences are for non-students. For students there is no reduction in men and a significant increase for women.
• Is the “21” policy delay or prevention
  • Reduced <21 consumption
  • Reduced DUIs
  • Most countries have 18 as a legal drinking age. 21 is very conservative.
  • We have a much lower rate of <13 year old first drink than do many other countries.
  • Drinking age exposure at younger ages (< 21) increases risk of alcohol abuse and does so across the lifetime (30% elevation in odds)
• Distinguishing heavy (binge) drinking from non-heavy drinking
  • J shaped curve. Lower levels of drinking improve mortality more drinks decrease mortality.
  • non heavy days = drinking days – great than 5 drink days (so they compared these two rates)
  • The J shaped curve fits for non-heavy drinking days. But, with heavy drinking days there is a linear relationship with increased mortality risk at all levels.
  • Looking at this with age of exposure. It may prevent binge drinking and promote moderate drinking. test

What does all this suggest for MOSBIRT and tailoring our message to college students?

• We are in a University health center and the students have complained that our norms really do not fit with their experience. This is true – they drink a lot more then the the drinking limits. However, Typical student feedback worked the best in reducing behaviors so using real norms from the U would be very useful.
• The level of drinking is often dangerously high. Perhaps highlighting the actual dangers associated with their use would be helpful particularly with reference to blackouts.
• What alternative might we suggest to alcohol use that folks could use to get socialization needs met.
• Talk about the difference between actual use and feelings of drunkenness. (subjective feeling “No I’m OK to drive.” is not reality based and is associated with DUI)
• Alcohol and caffeine leads to more errors in cognitive tasks (though they report feeling more “drunk”).
• The social factors belief in how much peers drink and in how positive their attitudes are toward drinking are more impactful than other influences. What sort of messages would help address and change those. (Then again, the amount of drinking and positive attitudes toward that behavior might well be reality so we might need to explicitly compare with save average behaviors.)
• Use heavy vs non heavy drinking days to discuss increased risks.

I have managed a number of different web sites using various tools (e.g., DotNetNuke, Drupal) With those tools comes a role based security system. It is easy to create various roles and assign permissions (create/read/update/delete). Individual users are given roles with their preassigned permissions. This greatly simplifies adding new users to the system.

This works great for simple sites but in many real world situations the roles are much more complex.

For example, a training site has various programs available each with the positions of teacher, student supervisor and student. The site has pages available based on which program you are enrolled in and what your position is in that program. Additionally, each program/position combination has certain materials that are accessible only to them. So for three programs and three positions we need to create 15 different roles (see the list below).

• Program A-Student
• Program A-Student Supervisor
• Program A-Teacher
• Program B-Student
• Program B-Student Supervisor
• Program B-Teacher
• Program C-Student
• Program C-Student Supervisor
• Program C-Teacher
• Program A
• Program B
• Program C
• Teacher
• Student
• Student Supervision

After creation, each of these 15 roles needs to be assigned appropriate access. Adding a new program requires adding four new roles and assigning permissions for each. (This would get even crazier if we added another level – semester. With three semesters we would need 45 individual roles to cover the possibilities.)

In this example, all users are given three roles – program, position, and program/position.

Obviously, this approach is both tedious and error prone. The underlying problem is that we are using a flat file to do something that would be much more appropriate for a relational database.

The Relational Approach

Using a relational approach participants would be assigned to a position role and a program role (two assignments rather than three).

Specific page access would be managed by simple logical statements

With a relational approach we dramatically cut our role count from 15 to 6 and adding a new program required just one entry – that the new program (Program D). Additionally we cut the role needed by each user by 1/3rd. This is clearly easier to understand, much easier to manage, and because of both of these, much less prone to mistakes.

We moved a long time ago from flat files to relational databases because of their simplicity and flexibility. How ‘bout doing the same thing for the assignment and use of user roles?

Over the past few days I have been participating the 2011 CSAT GPRA grantee meeting in DC. One of the presentation was by NIDA concerning their SBIRT efforts.

In a nut shell NIDA, through the Center for Clinical Trials Network (CCTN), has developed “an expert-defined and consensus based set of clinically-relevant standardized measures” particularly related SBIRT for substance use disorders. The effort has resulted in prescreening/assessment/service approach using a single prescreen item, the 9-item DAST, and some additional questions. Associated with that is a rather elaborate service flow and follow-up recommendations. Additionally, they have also been working on developing a model EMR in which to hold this (and presumably other) information. It was clear from their presentation that they have put in a great deal of careful thought and effort into these suggestions and they are in the advanced stages of getting formal approval from the ???

What was not clear, from the presentation, is that NIDA actually understands that SBIRT is a prevention model. In our MOSBIRT project, and as we hear from other State grantees, the focus is on the sub-clinical individuals whose health outcomes can be improved by reducing their level of use. The person who drinks a 6-pack every Friday, Saturday, and Sunday night because “everybody” drinks a 6-pack every Friday, Saturday, and Sunday night. While we do catch dependent/addicted individuals (around 3$ of those receiving SBIRT screens) that is not the focus. For us,  because it is so different the tradition focus of screening on identifying those with a diagnosis and those in need of specialized treatment services, this has been a very difficult distinction for providers to keep in mind.

The problem with the NIDA model is that it is really focused on the dependent/addicted individuals. Most of the decision tree and questions are directed to identifying these individuals and getting them into services. There was no attention to services that would lower an individual’s health risks. Perhaps the have take this traditional screening approach because there  is little evidence that it works. This lack is the reason that the US Preventive Task Force does not recommend SBIRT screening/services for substances than alcohol. When asked at the meeting if they were not out ahead of the evidence the response was that if they waited for that the rules would be written and they would not have a place at the SBIRT table.

It seems possible to me that SBIRT services could well reduce the health risks for individuals who misuse substances (e.g., by lowering dosages, decreasing frequency, or altering the route of administration). For example, needle exchange programs do reduce the risks associated with injection drug use. Our results, albeit without a control group comparison, do show that MOSBIRT services do reduce use. But as a field, we could use some solid research to identify those at risk and to evaluate the impact of programs to reduce those risks. It would be ideal if NIDA would lead the way in this effort. However, because the use of these substances is illegal, it is possible that risk reduction programs, like needle exchanges, would be politically controversial and restricted. If that were the case then in fact NIDA would not have a place the SBIRT table.

Over the past few days I have been participating the 2011 CSAT GPRA grantee meeting in DC. Much of the conference was focused on sustainability, an issue that has been increasingly in our thoughts. There were interesting presentations on the systematic development of messaging that is being done by the consultant group Penn Schoen Berland and the elegant work of the SBIRT Colorado team.  One area that was of particular interest to me was a discussion of how to involve businesses lead by Rich Brown leader of the Wisconsin SBIRT project.

One of the basic ideas of this is that we should locate people who are in “pain” and for whom SBIRT would serve to lessen that pain. Business may find themselves hit in various ways. For example, one State  talked about the difficulties their businesses are having actually getting employees who can pass pre-employment drug screens. (I do not know is Missouri business have this difficulty but it had never even crossed my mind as something to question.)

A more common plight is that businesses are burdened with ever rising insurance costs. This is true for smaller employers who must purchase group plans and to the larger self-insured businesses. SBIRT has been shown to reduce healthcare costs ($4 for every $1 spent) and to improve both safety and productivity. This is a clear way to reduce pain/ This is evident as businesses increasingly added these services to their employee assistance programs spurred on by staffing benefits and the BIG effort.

In the MOSBIRT we have paid little attention to these employers. So some of the points that came up in the discussion include: what would be some steps that we could take to address this group?

• Give talks to the business community in he meetings they attend and the organizations to which they belong.
• Add business representatives to our steering committee. These might be the State Chamber of Commerce, Safety council and/or State Manufacturing association.
• While Safety officers will like these messages they are not high enough in the organization to effect change. The CEO of the business needs to push the CEO of the insurance provider/manager to add these services. (Lower level folks can help get us to those who can make something happen.)
• Focus discussions on SBIRT’s ability to
  • Decreased costs
  • Increased productivity
  • Increased safety
• An insurance provider/manager may say "Yes but we will need to charge you more." The response is that this will save the group at risk (either the insurer or the self insured business) dollars so this should cost us nothing more.
• Find business thought leaders who are interested in and knowledgeable about healthcare and let them to present with you.
• Look for groups of small employers who have banded together to purchase insurance. Since they will be heavily cost driven SBIRT should component of their services.
• Wisconsin will soon have sample benefit language that others could use.

These seemed like great ideas. Indeed, since MOSBIRT is now experienced in providing these services perhaps we could even sell those capabilities to business or care organizations that would like to benefit from our expertize.

The day started of with a bang as Linda Sobell from Nova Southeastern University in Florida presented Self-Change: Findings and Implications for the Treatment of Addictive Behaviors. I have been citing the Sobells’ (Linda and Mark) work for a number of years in projects we have done in self change. She reported finishing their second large NIAAA study which found that a sizable number of people change on their own (75%) and that they maintain that change over the long term.

To me one of the most interesting aspects of her presentation was an evidence based description of why SBI researchers of “treatment seeking” programs often find no significant differences. These studies include individuals who are seeking some information or assistance about alcohol use (e.g., a web site, advertisement in a paper or billboard). Frequently, in these studies, there are no significant differences between treatment and control groups because BOTH groups have lower follow-up usage rates. Sobell’s group uses a one-year timeline follow-back measure of substance use which provides information on the individual’s alcohol use behavior over the last year. Looking closely at that data they found that in both the experimental and control groups the participants reduced their own drinking behaviors in the month preceding their participation in the intervention seeking project. That is, change occurred BEFORE intervention which would mean that the intervention it self was not responsible for change.

These results engendered some interesting lunch time conversations with questions about the validity of post-hoc self reports. But to me what it suggests that in these interventions what we should focus on is not initial change but on teaching people how to maintain and strengthen the changes that they have already made.

The other major presentation of the day was a description of England's SIPPS study Effectiveness and cost effectiveness of SBI from the SIOS research programme in England. This was a set of three clustered randomized control trials in primary care, emergency departments, and probation where they examined various screens,  targeted vs. universal screening and various interventions; Patient information "leaflet" (How much is too much?), Brief advice - 5 min based on WHO model, and 20 min MI lifestyle counseling (at a separate meeting). Each intervention contains the previous condition's information. The results were consistent across all three groups – while there were significant reductions in drinking there were no significant differences between the three interventions.

The question of universal vs. targeted screening was explicitly addressed in this work. They targeted individuals with mental health issues, GI problems, hypertension, injuries, new patient registrations, and patients of smoking clinics. They found that the prevalence rates for each are higher than the base rate so targeting had a higher positive hit rate making it more efficient. However, 65% of those found in the non-targeted group DID NOT have one of the target behaviors. So targeting will miss a LOT of people. Practitioners are fearful of false positives which they think may injure their doctor-relationship. So for the practitioners specificity is very important.

In sum this was the most interesting and exciting conference I have attended in a long time. I learned much. Developed new contacts. Came up with a variety of interesting questions to ask about my current work and ideas for future efforts. What more could one ask of three days.

Other posts from the 2011 INEBRIA conference:

• Day 1
• Day 2
• Day 3
• Computer supported SBI

Most impactful point of day 2 was a presentation by Richard Saitz from Boston University, What we know and don’t know about BI effectiveness. To adequately understand the focus it is important to understand the purpose of INEBRIA - the scientific study of brief interventions. By science they mean not just carefully controlled randomized designs and the more powerful of the quasi-experimental designs but the systematic review and analysis, including meta analysis, of a sufficiently large number of those base studies. That is, multiple studies showing similar results. This sets the bar much higher than most (any?) of the other meetings which I have attended.

Richard Saitz (the conference chair) started with a series of quotes from various web sites about SBI. I do not know if ours was included but if not its language was certainly consistent with those that were. Each touted the evidence base of SBI for alcohol and other drugs in various settings. The evidence, however does not support these contentions. There is good evidence for the application of these services in primary care for individuals with relatively low severity when provided by physicians. As for the rest there is insufficient, contradictory, and negative evidence to support these others.

Much of the literature seems to show that BOTH experimental and control groups reduce their use and that there is little if any difference between those reductions. (This is also described and discussed by many other presentations.) He argued that the results of experiments by Bernstein which used a non-assessed control did not support the idea that this was caused by the assessment itself.

While sobering the presentation also provided a rich set of questions and areas where additional high quality research is needed.  For example:

• what is the link between assessment, intervention, and outcomes
• how much training is needed
• what is the difference in impact for people identified by a screening assessment as opposed to those that self-identify
• is there a difference in outcomes based on who provides the service
• what are the minimal interventions needed to secure a change
• what impact does dosage (e.g., time, number of sessions) have on outcomes
• what settings, other than general practices, can be identified
• is there a difference between a teachable moment and a learnable one

Stacy Sterling (Kaiser Permanente) presented on Screening adolescent alcohol and drug use in pediatrics: Predictors and implications for practice and policy. Her review suggested that BI would work for adolescents and that the youth has a positive opinion of such activities. While screening of youth is recommend by all groups it is seldom done. Few pediatric practitioners have had training in school or continuing education and they find it more difficult to discuss with their patients than risky sexual behaviors. Screening programs have identified difficulties predominantly depression, anxiety, and school/family problems. Further assessment did identify substance use difficulties as well. Kaiser is currently doing a study using the CRAFFT in a randomized trial comparing primary care providers providing the SBI services vs. a behavioral health specialist vs. treatment as usual.

Jonathan Chick (University of Edinburgh) presented Paying primary care practitioners to deliver alcohol brief interventions: The Scottish experience. The Scottish government has supported target screening and brief interventions paying for the screening and follow-up as well as the electronic systems to track these services. While there is no outcome data (yet?) the did find that practitioners

• Generally supported of an active roll
• Thought that primary care is a valid setting
• Disliked time constraints, training requirements, nature of contracts
• GPs were comfortable raising the issue

and that the patients

• Thought it was tactful and sensitive
• Thought this was appropriate for the health worker's role in this context
• Most were able to identify reasons for alcohol being raised in the consultation
• Some thought they changed and others did not

But in this national implementation there was no test of intervention fidelity (this intervention only needed to be a few words and the physician would get paid). Physicians were told in training that it should be 5-10 minutes but time was not measured.

Katharine Bradley from the Group Health Research Institute in Seattle presented Implementation of SBI in the US Department of Veterans Affairs Health Care System: Lessons Learned. In the VA 96% of patients have been screened and 76% of those who were positive got a BI. However, they also sent out the screening measure (AUDIT-C) with follow-up satisfaction measures and found that many more people responded positively to that than was recorded in the EMR. Following up this researchers found that staff were using a validated screen but were not using it correctly. The screen became "You don't drink do you honey?"

For quality purposes Bradley recommended measuring not

(Number of BIs)/(Number of Positives)

but the

(Number of BIs/(Number of Screened)

this way sites that do not effectively and appropriate screen (finding few positives) are not rewarded for providing BIs for those few individuals more that groups that do identify many more in need of intervention but may not be able to provide all of the needed services. (It seems to me that perhaps you could establish a based rate of expected positives. Only sites meeting that rate would receive quality measures based on BI provision.)

All in all a great second day of the conference.

Other posts from the 2011 INEBRIA conference:

• Day 1
• Day 2
• Day 3
• Computer supported SBI

One of the consistent messages during the conference was that there is little time available for physicians (and sometimes other medical staff) to engage in screening and brief interventions (SBI). So the search is on for alternatives to that model. This post describes a variety of these alternatives as described by various conference presenters.

Jennifer McNeely from the NYU School of Medicine (Can patients screen themselves? Pilot study of an audio guided computer assisted self interview (ACASI) approach to screening for substance use in primary care) developed a simple tablet computer administered ASSIST in which the questions were read as well as being presented on the screen. As with my previous research, she found that patients accepted and liked this approach and is now evaluating the validity of this approach relative to the normal interview based administration.

Daniel Alford from the Boston University Medical center mentioned in his presentation on the the Massachusetts SBIRT project (MASBIRT) the failure of their interactive voice recognition (IVR) system. We had heard of this effort early in of our SBIRT meetings but never heard of it again. In a sidebar conversation I asked about that system. It was an elegant and costly effort. Integrated in their medical records system it would know, from the medial record who was do for a screen. A week ahead of their next appointment the IVR system would call the patient and collect the necessary screening information. The responses were stored in the EMR their health coaches knew a week ahead of time who would be needing assessment/intervention and the physicians would also have that information at their fingertips in the record. The system worked flawlessly except for one factor – patients hated it and would hang up without responding. Patients complained to their doctors about being asked these questions (they did not do this with any of the other methods) and the system was eventually turned off.

Kypros Kypri from University of Newcastle, Australia (Electronic forms of alcohol screening and brief intervention: What the reviews tell us) reviewed reviews that included results of studies of interventions less than 30 minutes long conducted via telephones or computer. What seemed to work included:

• normative feedback (feedback on problems is less effective),
• multiple sessions were more effective than fewer,
• greater doses lead to larger effects,
• commercial applications were less effective than open applications, and
• college students change less than do help seeking individuals.

More importantly he identified a number of question and methodological difficulties that would bear closer examination:

• what are the differences between help seekers vs. non-help seekers
• alcohol distributions are highly skewed and the statistics used do not (but should) take this into account
• there are large numbers of missing cases in these studies and the intent to treat analyses should be informed by this fact
• are there groups in which normative feedback will have more or less impact?
• social desirability may account for some of the small changes that have been found – is there explicitly take this into account.

One question was repeated across a number of presentations concerned the consistent finding control groups also significantly reduce their drinking. It is this effect which limits the significance of many studies. Preben Bendtsen from Linkoping University in Sweden used a Solomon 3 group design in a pilot test and randomly emailed students either:

• an assessment (with follow-up)
• an assessment + feedback (with follow-up)
• follow-up assessment only

Their findings of no significant differences between the groups suggested that there was no sensitization due to pretesting. The intervention did have an impact of the grams of alcohol consumed and they will be continuing the effort with a larger study.

Shanthi Ameratunga from the University of Auckland in New Zealand reported a pilot study on the patient perceived feasibility of mobile phone delivered intervention among trauma patients. The patients suggested getting text messages would be good if there were:

• not to many messages,
• not confrontational, and that
• they needed to know that the sender was authoritative

Gail Rose from the University of Vermont College of Medicine described a Interactive Voice Response (IVR) system that is going live next week. Unlike the MASBIRT effort this one has people call it to respond to assessment questions and then to get tailored feedback and advice on reducing their risks.

Emily Williams from the VA Puget Sound and the University of Washington described the limitation of alcohol screening electronic clinical reminder in the VA. In the VA the AUDIT-C is built into their EMR and information is entered into it in 96% off the records. This study was based on a finding that when the AUDIT-C was completed as part of a mailed in satisfaction survey the positive rates were much higher that those in the clinical reminder. Doing a series of ethnographic observations they fond that:

• there was great variability in how patients were screened (paper, verbal, laminated forms)
• clinicians “disowned” the questions
• non-verbatim screening was the norm
• question 3 (number of binge drinking occasions) was often omitted
• almost all staff did not provided the response set
• a patient’s general response was categorized by the staff into a response
• the staff explicitly acknowledged their discomfort at asking these questions
• screens collected on paper or laminated forms seemed to get more accurate responses because they required minimal interaction.

All in all a great set of presentations that provide a lot of food for thought.

• Day 1
• Day 2
• Day 3
• Computer supported SBI

Recently I had the opportunity to attend the 2011 International Network on Brief Interventions for Alcohol Problems (INEBRIA) conference in Boston. Founded by researchers (who had been collaborating on alcohol reduction related World Health Organization projects) from around the world to study and promote screening and brief interventions (SBI) for alcohol abuse. Attendees included many of top the researchers in the field (Nick Heather, Linda Sobell, Edward and Judith Bernstein, John Higgins-Biddle, …) and individuals from 30 countries.

Day one of the conference, sponsored by NIDA, focused on SBI for a broader range of issues, most notably legal and illegal drugs. What follows are some of my notes and thoughts relating to the presentations of the day.

Wilson Compton from NIDA (Mainstreaming addictions in medicine: Screening and Brief Intervention for Illicit Drugs - Research Directions) discussed a variety of efforts in drug abuse prevention and treatment but focusing on SBI encouraged individuals to work on developing the literature to support its effectiveness. He described a recent world wide study that found positive results in every country included except the US. Speculating as to why this was he suggested that the improvements found in the control group may have been reactive to the protocol. In the US the informed consent took 15 minutes but the intervention only took 5 minutes. (This is an interesting issue that gets mentioned by a number of speakers. What is the minimum intervention needed to actually produce a reduction in substance use?)

One of his most interesting (to those of us involved in research) was of NIDA’s Research priorities. These include:

• Develop and test models for implement addiction services (both treatment and prevention) in health settings
• Testing training and sustainability models
• Testing the use of technology to improve the quality of care
• Testing different organizational and financing strategies
• How do you attract people to web sites that offer services. Developing system that can be appealing in the face of very attractive substance use

Richard Brown – from the Wisconsin SBIRT project talked about their lack of success with masters level clinically trained educators and their positive experiences with bachelors level individuals who were warm enthusiastic, and nonjudgmental. He also described their difficulty getting folks to actually attend additional services was later echoed in the meeting but with a twist as it was suggested that a more long term repeated contact approach may be quite effective in eliciting change.

Jennifer Mertens from Kaiser Permanente described an experiment (cluster randomized control) which contrasted BI services provided by physicians (PP) with those provided by non-physician providers (NPP; viz., behavior medicine specialists, clinical health educators, or nurses) or provided all of the BI services (screening and intervention). Her results were rather dramatic. While more got screened by the non-physician group (PP/NPP 11%/37%) the physician group provided a great many more actual interventions (PP/NPP 54%/1%). This seems to show both that physicians are reluctant to screen but, as described by Richard Brown, also that the hand off process is a killer for interventions.

Antoinette Krupski from CHAMMP at the University of Washington Harborview (Self-reported drug use six months after brief intervention: do changes in reported use vary by mental health status?) studies substance misuse BI outcomes of those with and without mental health diagnoses (e.g., depression, bipolar, psychosis). While the results are tentative because of the lack of a control group, to their surprise, they found that mental illness did not negatively impact BI success rates. The audience was surprised as well and one researcher from Sweden who was studying BI specifically with mental health patients has found that her participants do require interventions tailored to their conditions. It would be interesting to look at BI delivered using a motivational interviewing approach – with that method the intervention is always tailored to meeting the patient where they are.

Dean Fixsen from the University of North Carolina Chapel Hill and Co-Director of the National Implementation Research Network (NIRN) presented a fascinating description of the research behind implementation. The NIRN book Implementation Research: A Synthesis of the Literature is freely available as a PDF document and should be invaluable reading to help design research based implementation practices. He described the importance of good implementations with this formula

Effective interventions x effective implementations = good outcomes

and explicitly pointed out the multiplication sign. If 1 (one) is a perfect intervention effect and 1 is a perfect implementation you get the maximal outcome. However, as either number decreased you radically decrease the impact of the outcome. So a poor implementation kills any great intervention.

What doesn’t work – the thing that we normally do

• Diffusion/Dissemination of information
• Training
• Laws/mandates/regulations
• Funding/incentives
• Organizational change/reorganization

What does work – focusing on a variety of systems and areas across the board

• Drivers of competency
  • Selection
  • Training
  • Coaching
  • Performance Assessment

• Organization drivers
  • DSS data system
  • Facilitation administration
  • Systems intervention

• Leadership drivers
  • Technical
  • Adaptive

the focus needs to be on making the change happen with the responsibility on the shoulders of a team of 3-5 implementers and the 3-5 year process has four stages.

• Exploration
• Installation
• Initial implementation
• Full implementation (50% of folks are using it consistently)

The implementation team knows the innovation, knows implementation science, and most importantly knows and uses improvement cycles (e.g., the Plan, Do, Study, Act cycle).

The day ended with a presentation by Peter Anderson from Maastricht University, Netherlands and Newcastle University, England (SBI in the World Health strategy). The World Health Organization (WHO) measures health with the Disability Adjusted Life Year (DALY). Using that measure alcohol abuse is THE most significant cause of lost days of any problem (followed by unsafe sex and tobacco use). The highest rates of death for those between 45-64 is also related to alcohol. He also talked about the recent multi-national study also found that BI had the greatest impact on reducing medical costs in all countries (except, as noted by Wilson Compton, in the US).

At the end of the day my mind was reeling with ideas for new research and ways to improve our MOSBIRT efforts.

Other posts from the 2011 INEBRIA conference:

• Day 1
• Day 2
• Day 3
• Computer supported SBI

Health Literacy Missouri held their 2nd Annual conference in Columbia Missouri this week. I had naively assumed that we would be learning about how to present information in a way that people with lower levels of health literacy would be able to understand. What I quickly cam to realize is that we have met those people … and they are us.

Barbara Jones, Literacy Advocacy Health Science Library UM-C and Susan Center, Director Missouri Area Health Education Center Digital Library presented some frightening statistics

• 9 our of 10 patients lack the skills necessary to manage their disease
• 80% of patients cannot successfully recall what they are told after leaving the physician
• Almost 1/2 of what patients remember from their physician visit is false

It is tempting to blame this on the patients. Surely they must lack the education, training, interest, or motivation to understand what is happening. But that is blaming the victim. Encounters with medicine are often in the context of anxiety provoking symptoms or conditions. The terms and concepts understood and used by medical professionals are complex and confusing. And the time physicians, in particular, have to spend with patients is limited.

In my own life I have recently an emergency appendectomy. I went to a good hospital and got good care. But once they realized what I had I was, thankfully, given a powerful powerful pain reliever. I thought I understood all that was said to me. But face it, I was also in a condition where it would have been illegal for me to drive a car – a well learned skill – making medical decisions. Fortunately, the woman with whom I am married was with me to make sure that we understood the various implications. (Not that there is a lot of choice when you need an appendectomy.)

My parents provide another example of the difficulties involved. They are currently facing a large variety of medical issues which have resulted in multiple hospitalizations and multiple physicians all working to cope with significant chronic illness. Both of my parents are college educated but with hearing losses and the other changes common in those in their 80s, they do not understand all of what is said by their multiple physicians. Fortunately they qualify for programs that help them manage but even with those they find the whole confusing. As would I in their place.

So, what did I learn that can be done to help us all understand?

Dr. Howard Koh, Assistant Secretary for Health HHS presented a talk entitled Building a patient-centered health home - Policy Implications.

• Starts patient conversations with "Tell me what you understand about your current condition." Faced with the same information people have very different reactions and understanding. With this approach he can reach them where they are, gauge their emotional reaction, and can then join them as partners in their treatment.
• Focuses on making the information provided to patients accurate, accessible, and actionable.
• Described the plain writing act which will require all federal documents to be written clearly.

Stan Hudson - Associate Director Center for Health Policy, UM-C spoke on Missouri Health Literacy: Best practices in health professions and librarian education.

• Treat everyone as at risk for health literacy difficulties
• In medical education he recommends teaching five core competencies
  • Adopt universal precautions approach to information exchange to all patients (reduce miscommunications with everyone)
  • Work on the ability to translate jargon into layman's terms providing everyday analogies and words that they understand
  • Teach back - check the patient's understanding of what they know (very strong evidence based literature to support this)
  • Shared responsibility for information exchange across the health system In overcoming motivational and informational barriers within the health care system.
  • Use short action-oriented statements focus on one to three "need to know" and "need to do" concepts during any given communication.
• When a patient does not follow instructions is it “non-compliance” or “ineffective communication?”
• Health Literacy is a stronger predictor of health status than age, income, employment, education, or racial and ethnic groups.
• Losses associated with low health literacy $238 billion each year, 10% of US health care costs

And now for something you can use

The most useful takeaway I got from the conference was the teach-back methodology. This is an evidence based practice that has been demonstrated to greatly reduce patient-professional misunderstands. It was mentioned in many of the presentations. There are also numerous descriptions of this on the web and even YouTube demonstrations.

• The goal is not to test the patient.
• The goal is to see if the medical professional was able to communicate effectively so that the patient really understands.
• Focus this on what patients need to know and what they need to do.
• You might say the patient “I want to understand if I explained this to you clearly. Can you tell me how you will explain this to your spouse/family/roommate/… when you get home.”
• If they do not understand portions of the information congratulate them on what they do understand then go back and correct the missed information. Repeating the teach back for the new information.
• This is a preventative measure, therefore worth your time, which will reduce the chances of the patient not doing what they should.

At the conference this was presented as a technique for the professionals but it seems to me that as a patient I could easily do this with my physicians. After they tell me something I could say something like, “OK so what you are saying is …” Repeating their statements in my own words.

Teach back seems like a great approach that has wide spread applicability in the areas in which I work. Where could you use this approach?