Feeling guilty about wanting to read about Ms. Lucci or Ms. Obama rather than page through the Journal? You’re in luck! You can have the dancing, the dress and this disease management knowledge dump by taking advantage of this quick summary - courtesy of the DMCB.
Maio V: Light and Fire, from the Department of Health Policy at Jefferson.
This is an editorial that describes the good (light) and the bad (it burns) of “biologics” or those drugs that are grown in DNA-altered bacteria filled vats. The number of these agents is not only growing, so are their indications. The only thing that is falling is the threshold of doctors to using them. The author suggests that the growing appetite for these miracle drugs will inevitably lead to the discovery of some horrid side effect that was previously unknown. Either that or a batch will eventually go bad and hapless patients will be exposed to curdled biologic. We need head-to-head comparative effectiveness trials that also account for their cost and hassles (IV administration for example), and the sooner the better. The DMCB seconds that motion.
Fetterolf D, Tucker TL: Assessment of Medical Management Outcomes in Small Populations, from Alere
Dr. Fetterolf was an author in many of the DMAA Outcomes recommendations, so when he writes, readers should pay attention. In this review paper, he and Mr. Tucker patiently examine why small numbers of observations are the bane of DMO marketing and salespersons who want to, but can’t say “our results are ‘statistically significant!’” Common approaches to this vexing problem include ignoring the statistics, ignoring the results, or reporting the results with a statistical caveat emptor. But do not fret, Fetterolf and Tucker describe other approaches including cumulative sum plots, passing patients’ data through a series of binary tests and weighted blending of the study population data into those of a larger book of business. Confused? So is the DMCB, but it promises that if you read this article more than once, some of it will sink in.
Serxner S, Mattke S, Zakowski, Gold D: Testing the DMAA’s Recommendations for Disease Management Program Evaluation, from Mercer and Rand (Mattke)
The authors set out to compare an old DMAA method (without requalification), one recommended by the lead author and some other approaches to assess the savings from care management programs. To do this, medical and prescription drug claims from over 200,000 persons over the two years prior to and one year after the institution of a ‘health and productivity management program’ were used to test the role of using 1) a non-chronic trend, 2) a non-chronic trend with statistical adjustments, 3) a non-chronic trend adjusted for relative and 4) absolute historical differences, 5) the client specific trend (which is Sexner’s preferred method) and 6) a national trend. The authors also measured the impact of not having a $100,000 cap, not excluding certain conditions like cancer and extending the baseline out to 24 months instead of 12. The change in the per member per month cost swung from a savings of $153 to a loss of $15. Guess what the author’s conclusions are: baseline trend assumptions have a large impact on assessing program impact. Now are you REALLY confused? So is the DMCB, but the authors raise an interesting point: if there is no clear definition of just what the “truth” is when it comes to analyses like this, perhaps it should be an industry standard to obtain multiple analyses and use them all to make an informed judgment on the effectiveness of a program. The DMCB is aware of other insurance industries that rely on multiple actuarial models to ultimately derive a single best estimate of trend, projected surplus and premium setting.
Glave Frazee S, Sherman B, Fabius R, Ryan P, Kirkpatrick P, Davis J: Leveraging the trusted clinician: Increasing retention in disease management through integrated program delivery, from Care Health Systems and Case Western Reserve.
Care Health Systems has “an innovative methodology” that has the secret sauce in “identifying, contacting, enrolling and retaining patients in DM programs.” The term ‘secret’ is no joke because the “tracking of patient demographic and clinical information, the patient contact and enrollment process, as well as all contacts between the nurse coach and patient were performed using a proprietary DM information system application” that is “patent pending.” The group getting the intervention did indeed have a clinically and statistically significantly higher 12 month participation rate, but without knowing what’s inside the black box, the DMCB stopped rea
Rohrer JE, Takahashi PY, Adamson SC. Age, obesity and medical visits in family medicine, from the Mayo Clinic.
This is a descriptive study from the folks at the Mayo Clinic who used a convenience sample of 1715 patients who were referred out of the Department of Family Medicine for a specialty consultation. The authors were interested in the interplay of age (less than vs. older 65 years), co-morbidities (measured by the Charlson Index) and BMI. Unless there were significant co-morbidities, a BMI greater than 35 was not, repeat not, a predictor of many physician visits among the elderly, but it was among persons that were younger. If visits are a surrogate measure of health, the authors ask if population-based interventions for obesity are really necessary for geriatric patients. Though this was an observational study, the DMCB feels redeemed by recalling that he told many of his otherwise healthy older women patients to stop worrying about being size 20. Maybe the rest of us should not worry if our rotund grandpas enjoy another helping of pie this Thanksgiving.
Duncan I, Lodh M, Berg, GD and Mattingly: Understanding patient risk and its impact on chronic and non-chronic member trends, from Solucia, Schrammraleigh Health Strategy and McKesson.
Whoa, actuary alert! These authors used a data base and from a state Medicaid plan that had purchased disease management services to assess a risk adjustment method to “further assure equivalence between the baseline and intervention period populations” that are requalified under the DMAA methodology. After staring at a paper that had more numbers than words, the DMCB believes the authors set out to statistically neutralize the impact of the varying costs involving extrinsic factors involved in new, continuing and terminating members’ patterns of utilization. Really really confused? The DMCB fears it will stay that way also, but the good news is that this paper is further evidence of the growing sophistication behind the evaluation of disease management programs.
Finally the Journal published a preview of all the upcoming abstracts from the 10th Annual DMAA Forum and the 2nd Integrated Care Summit. Use it to plan your upcoming meeting diet of education, knowledge and insight.