Framework for assessing causality in disease management programs: principles

Mobile Integrated Healthcare Intervention and Impact Analysis with a Medicare Advantage Population

Mobile Integrated Healthcare (MIH) is a patient-centered, innovative delivery model offering on-demand, needs-based care and preventive services, delivered in the patient's home or mobile environment. An interprofessional MIH clinical team delivered a care coordination program for a Medicare Advantage Preferred Provider Organization that was risk assigned prior to intervention to target the highest risk members. Using claims and eligibility data, 6 months of pre-program experience and 6 months of program-influenced experience from the intervention cohort was compared to a propensity score-matched comparison cohort to measure impact. The intervention led to a reduction in inpatient and emergency department utilization, resulting in net savings amount totals of $2.4 million over the 6 months of the program. After accounting for the costs of implementing the program, the intervention produced a return on investment of 2.97. Additionally, high patient activation and experience lend strength to this MIH intervention as a promising model to reduce utilization and costs while keeping patient satisfaction high.

Mobile Integrated Healthcare: Preliminary Experience and Impact Analysis with a Medicare Advantage Population

Background: Mobile Integrated Healthcare (MIH) is a novel, patient-centered approach to population management. This concept creates a needs-matched, time appropriate assignment of one or more members of a multi-professional clinical team to care for patients on a scheduled or unscheduled basis. The selection of the site of care for scheduled interventions is driven by patient choice and, most often occurs in the patient's home; unscheduled interventions are guided by a 5-point triage system and, based on acuity, may be treated in the home, primary care office, urgent care or, rarely, in an emergency department. Methods: An MIH team was assigned to deliver a care coordination program for a Medicare Advantage PPO (MAPPO) population (55% female, 71.2 years mean age), with risk assignment and interventions designed to affect potentially avoidable utilization of Emergency Medical Services (EMS), emergency department, and medical inpatient admissions. Patients participating in the MIH program were compared with contemporaneous, risk-matched non-participants as well as to actuarially expected cost and utilization based on historical claim experience. Results: All measured trends demonstrated favorable results for patients participating in the MIH program when compared against a matched cohort: 19% decrease in emergency department per member per month (PMPM) cost, 21% decrease in emergency department utilization, 37% decrease in inpatient PMPM cost, 40% decrease inpatient utilization, all measures reached statistical significance. Member experience satisfaction scores and patient activation measures also showed favorable preliminary trends. Conclusion: This initial impact analysis of a MIH care coordination program for this MAPPO population demonstrates promising trends regarding utilization, cost, member experience and patient activation. These preliminary findings indicate both that implementation of such a program is feasible and strongly suggest meritorious impacts upon the health, experience and cost of care for the population.

An Application of Survival Analysis to Population Health Management Program Evaluation

Purpose.

Evaluating the financial impact of long-term lifestyle management interventions is difficult because of the variability across the program members' enrollment and participation levels. This variability is often referred to as “censored” health claims data. Survival analysis is designed to overcome censored data of various kinds (e.g., disenrollment, loss to follow-up, missing data).

Design.

A quasi-experimental program versus matched reference group study design was used. Participants (N = 142) in smoking cessation or weight management programs in 1997 were retrospectively matched to nonparticipants (N = 142).

Setting.

The study location was a regional hospital in Tennessee.

Subjects.

Hospital employees with health plan benefits served as subjects.

Intervention.

Program interventions included health risk appraisals, screenings, and telephonic health coaching for weight management and smoking cessation.

Measures.

The major dependent measure was paid claims information.

Results.

Program participants experienced more health care claims but significantly lower cost than nonparticipants. Nonparticipants averaged $40.77 more per claim than participants. Participants were less likely than nonparticipants to experience a high-cost or outlier claim event. For example, by month 72 nonparticipants had twice the probability of experiencing an outlier claim as participants.

Conclusions.

Effective lifestyle health management may increase low-cost health claims activity, because many patients improve at self-care. As demonstrated here, preventive initiatives result in lower cumulative costs and decrease the risk of high-cost or outlier claim events.

Chronic care improvement in primary care: evaluation of an integrated pay-for-performance and practice-based care coordination program among elderly patients with diabetes

OBJECTIVE

To examine the effects of an intervention comprising (1) a practice-based care coordination program, (2) augmented by pay for performance (P4P) for meeting quality targets, and (3) complemented by a third-party disease management on quality of care and resource use for older adults with diabetes.

DATA SOURCES/STUDY SETTING

Claims files of a managed care organization (MCO) for 20,943 adults aged 65 and older with diabetes receiving care in Alabama, Tennessee, or Texas, from January 2004 to March 2007.

STUDY DESIGN

A quasi-experimental, longitudinal study in which pre- and postdata from 1,587 patients in nine intervention primary care practices were evaluated against 19,356 patients in MCO comparison practices (>900). Five incentivized quality measures, two nonincentivized measures, and two resource-use measures were investigated. We examined trends and changes in trends from baseline to follow-up, contrasting intervention and comparison group member results.

PRINCIPAL FINDINGS

Quality of care generally improved for both groups during the study period. Only slight differences were seen between the intervention and comparison group trends and changes in trends over time.

CONCLUSIONS

This study did not generate evidence supporting a beneficial effect of an on-site care coordination intervention augmented by P4P and complemented by third-party disease management on diabetes quality or resource use.

[Modern concepts of medical care--what has been achieved by the implementation of disease management programs?]

Since 2003, structured treatment programs for chronically ill patients (disease management programs; DMPs) have been under development in Germany. Virtually nationwide, programs in which physicians and patients can register are being offered for diabetes mellitus types 1 and 2, breast cancer, coronary heart disease and asthma/COPD. The medical content of the programs is determined on the basis of evidence-based medicine. Even though the effectiveness of structured treatment programs is documented for diabetes, adequate studies confirming the overall transferability of results to the German health care system are as yet lacking. Physicians above all strongly criticise the coupling of DMPs with the risk adjustment scheme of the statutory health insurance funds, as well as the large amount of paperwork involved.

Strengthening the case for disease management effectiveness: un-hiding the hidden bias

As is the case with most health care program evaluations, disease management (DM) programs typically follow an observational study design, indicating that randomization to treatment or control was not performed. The foremost limitation of observational studies, compared to randomized studies, is that the only biases that can be controlled for are those associated with observed variables. Hidden bias refers to all those unobserved covariates that may distort the conclusions of the study. This paper introduces a sensitivity analysis that is used to determine the magnitude of hidden bias necessary to alter the conclusion that a DM program intervention was indeed effective.

Implementation and outcomes of commercial disease management programs in the United States: the disease management outcomes consolidation survey

Despite widespread adoption of disease management (DM) programs by US health plans, gaps remain in the evidence for their benefit. The Disease Management Outcomes Consolidation Survey was designed to gather data on DM programs for commercial health plans, to assess program success and DM effectiveness. The questionnaire was mailed to 292 appropriate health plan contacts; 26 plans covering more than 14 million commercial members completed and returned the survey. Respondents reported that DM plays a significant and increasing role in their organizations. Key reasons for adopting DM were improving clinical outcomes, reducing medical costs and utilization, and improving member satisfaction. More respondents were highly satisfied with clinical results than with utilization or cost outcomes of their programs (46%, 17%, and 13%, respectively). Detailed results were analyzed for 57 DM programs with over 230,000 enrollees. Most responding plans offered DM programs for diabetes and asthma, with return on investment (ROI) ranging from 0.16:1 to 4:1. Weighted by number of enrollees per DM program, average ROI was 2.56:1 for asthma (n = 1,136 enrollees) and 1.98:1 for diabetes (n = 25,364). Most (but not all) respondents reported reduced hospital admissions, increasing rates of preventive care, and improved clinical measures. Few respondents provided detailed information about DM programs for other medical conditions, but most that did reported positive outcomes. Lack of standardized methodology was identified as a major barrier to in-house program evaluation. Although low response rate precluded drawing many general conclusions, a clear need emerged for more rigorous evaluation methods and greater standardization of outcomes measurement.

Assessing Return on Investment of Defined-Population Disease Management Interventions

BACKGROUND

Strategies to reduce health expenditures through the improvement of health and quality of care are in high demand. A group of experts formed a nonpartisan, independent work group, under the sponsorship of the National Managed Health Care Congress. Its goal was to establish a list of easy-to-understand, actionable, and usable recommendations to enable disease management program advocates to conduct basic-level evaluations.

RECOMMENDATIONS

The work group made recommendations concerning identification of reference and intervention population, population definitions, quantitative methods and data quality, confounding and bias, and stakeholder agreements/contracting.

CASE STUDY

A case study was created to quantitatively illustrate some of the major issues raised by the work group. Five typical errors were simulated by applying different rules to the intervention population than to the reference population: differential inclusion (high versus low risk), differential exclusion (high versus low risk) and differential claims run-out. Compared with the true impact, four of the five errors resulted in a bias toward "intervention effect," while one (differential inclusion of high-risk patients) was biased against the "intervention effect." The direction and magnitude of the bias in natural settings will not necessarily follow this pattern.