I am known in the disease management and wellness fields as a naysayer, critic, curmudgeon, and/or traitor…and those are only the nouns that are allowed to be blogged across state lines. This is because I am driven not by wishful thinking but rather by data. The data usually goes the wrong way, and all I do is write down what happened. Then the vendors blame me for being negative — sort of like blaming the thermometer because the room is too hot — because they can’t execute a program.
However, the nonprofit Iowa Chronic Care Consortium (ICCC) apparently can execute a program. They reduced total diabetes events by 6% in the rural counties they targeted. This success supports a hypothesis that in rural (presumably underserved) areas, disease management fulfills a critical clinical gap: it provides enough basic support that otherwise would not be provided even to those who actively seek it to reduce near-term complications and exacerbations.
This result will likely produce its own unanticipated consequence: because many people now believe (thanks, ironically, to some of my own past work) that disease management doesn’t produce savings, there will be widespread skepticism about the validity of this study. Quite the opposite: this “natural experiment” is as close to pristine as one could hope for in population health, for five reasons:
- There was no participation/self-selection bias because outcomes were measured on all Iowa Medicaid members.
- The program was offered in some Iowa counties but not others, so there was no eligibility or benefits design bias, Medicaid being a statewide program.
- The program encompassed only one chronic condition (diabetes) rather than all five common chronic conditions normally managed together (asthma, CAD, CHF, and COPD being the other four). Since all five conditions were tracked concurrently, whatever confounders affected the event rate in one of those conditions should have affected all of them. And event rates in the four other conditions did indeed move together in both the control and study counties. Just not diabetes.
- The data was collected exactly the same manner by the same (unaffiliated) analysts using exactly the same database so there is no inter-rater reliability issue.
- Both groups contained hundreds of thousands of person-years and thousands of events.
As one who has reviewed another high-profile “natural experiment,” North Carolina Medicaid, and found that the financial outcomes were the reverse of what the state’s consultants originally claimed (incorrectly, as they later acknowledged by changing their answer), I can also say that natural experiments in population health don’t harbor some as-yet-unidentified confounder that causes the study population to outperform the control population.
The analysis of the data, like all good population health analyses (meaning very few of them), is fully transparent. I will share it gratis with any researcher in a nonprofit organization, and I welcome private or public criticisms. I’ll respond to the latter right beneath this posting.
So what did ICCC do to achieve this enviable result? Much of the intervention was standard procedure. To begin with, a technology platform provided by a population health vendor used an interactive voice response (IVR) system to populate a web-based decision support system with self-reported daily diabetes self-management activities. Unfortunately, my conclusion — one in which the New England Journal of Medicine concurs — is that IVR by itself doesn’t improve chronic disease outcomes.
But in addition to this standard procedure came some much more personal and community-based interactions, which likely accounted for the improvement due to the lack of other resources in these rural areas. A patient centered care manager developed a personal connection with no more than 250 participants at a time (vs. twice that in a typical program), providing each with what might now be called health advocacy. Clinical variances from “normal” were flagged, enabling the care manager to easily identify participants who needed extra support, coaching or referrals to their physician for medical care. Quarterly behavioral health screenings identified those with co-morbid depression for referral into Medicaid’s statewide Magellan Behavioral Health program.
Participants were also referred to community based programs operating in some counties, like Better Choices, Better Health®, the Stanford University Chronic Disease Self-Management Program, to promote development of self-care skills, as well local diabetes education programs, programs that 96% of ICCC program participants had not previously even known existed. Use of these community-based resources improved medication adherence, attention to diet and self-confidence regarding their diabetes self-care skills.
In a well-served population, even a well-served Medicaid population, little incremental adverse event reduction has been achieved through providing similar additional care management resources and/or referrals to community-based resources. But this is first time that a rural Medicaid population has been segregated from the total Medicaid population, and the promising result in that specific population shows that there could be an opportunity to disease-manage other underserved rural populations, at least in diabetes.
Now if somebody could please find me a wellness vendor that can “move the needle” in a similar fashion, I’ll be able to say that, in the immortal words of the great philosopher Robert Browning, all’s right with the world.
Al Lewis is the author of Why Nobody Believes the Numbers, co-author of Cracking Health Costs: How to Cut Your Company’s Health Costs and Provide Employees Better Care, and president of the Disease Management Purchasing Consortium.