Adult asthma disease management: an analysis of studies, approaches, outcomes, and methods.

Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC 27701, USA.
Respiratory care (Impact Factor: 2.03). 08/2009; 54(7):878-86. DOI: 10.4187/002013209793800385
Source: PubMed

ABSTRACT Disease management has been implemented for patients with asthma in various ways. We describe the approaches to and components of adult asthma disease-management interventions, examine the outcomes evaluated, and assess the quality of published studies.
We searched the MEDLINE, EMBASE, CINAHL, PsychInfo, and Cochrane databases for studies published in 1986 through 2008, on adult asthma management. With the studies that met our inclusion criteria, we examined the clinical, process, medication, economic, and patient-reported outcomes reported, and the study designs, provider collaboration during the studies, and statistical methods.
Twenty-nine articles describing 27 studies satisfied our inclusion criteria. There was great variation in the content, extent of collaboration between physician and non-physician providers responsible for intervention delivery, and outcomes examined across the 27 studies. Because of limitations in the design of 22 of the 27 studies, the differences in outcomes assessed, and the lack of rigorous statistical adjustment, we could not draw definitive conclusions about the effectiveness or cost-effectiveness of the asthma disease-management programs or which approach was most effective.
Few well-designed studies with rigorous evaluations have been conducted to evaluate disease-management interventions for adults with asthma. Current evidence is insufficient to recommend any particular intervention.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Our nation is in the midst of an important debate on health care. The issues revolve around affordability, accessibility, quality and funding. Of these issues, the one that all experts agree must be resolved for the good of the country is the high cost of healthcare. Supported by years of testing and overwhelming empirical evidence by independent research, the MedEncentive Program has surfaced as a real breakthrough in resolving the issue of healthcare afforda- bility. This report presents the findings from five years of testing and the independent research that vali- dates the Program's efficacy and its underlining design principles. Background - From 1997 through 2007, a small group of innovators consisting of practicing physicians, a medical academician, a self-insured business owner, a medical practice management consultant, and a health insurance executive sought to find ways to align the interests of healthcare consumers, providers and insurers. After years of studying the issues, the group concluded that the single most pressing problem in healthcare was affordability. Understanding that the majority of healthcare costs are driven by people's poor health habits and medical provid- ers' variable practice patterns, the group focused on using incentives to align these stakeholders' interests to improve both health behaviors and practice patterns. This thought process led to the development of what would become a web-based incentive system called MedEncentive.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Decision support systems linked to administrative databases provide a unique opportunity to monitor adherence to guidelines and target disease management strategies towards patients not receiving guideline-based therapy. The objective of this study was to evaluate the discrepancy between actual asthma treatments prescribed by primary care physicians compared to those recommended by evidence-based guidelines using a decision support tool linked to a provincial health administrative database. The drug and medical services information of individuals with asthma was identified from the provincial health database and was pushed through an asthma decision support system (ADSS). Recommendations aimed at optimising asthma treatment were generated on two index dates, 15 September 2007 (index date 1) and 15 March 2008 (index date 2). Primary care settings in a large Canadian metropolitan area. Individuals with asthma and provincial health insurance primary and secondary outcome measures: well controlled asthma. 16 803 eligible individuals were identified on index date 1, and 18 103 on index date 2. The distribution of recommendation categories was similar on both index dates. 94% were classified as well controlled and 7% as not well controlled. Among well-controlled individuals, the largest proportion was in the maintain treatment category (63.8%), followed by the maintain/decrease treatment category (28.2%) and the decrease treatment category (2.7%). Almost all individuals who were not well controlled had the recommendation to increase treatment (88%) with a small proportion in the refer category (1%). The ADSS was able to identify subgroups of patients from an administrative database that could benefit from a medication review and possible change. Decision support systems linked to an administrative database can be used to identify individuals with uncontrolled asthma or prescriptions that deviate from recommended treatment. When connected to the point of care, this can provide an opportunity for physicians to intervene early.
    BMJ Open 01/2014; 4(3):e003759. · 2.06 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: OBJECTIVE: To develop a quasi-experimental method for estimating Population Health Management (PHM) program savings that mitigates common sources of confounding, supports regular updates for continued program monitoring, and estimates model precision. DATA SOURCES: Administrative, program, and claims records from January 2005 through June 2009. DATA COLLECTION/EXTRACTION METHODS: Data are aggregated by member and month. STUDY DESIGN: Study participants include chronically ill adult commercial health plan members. The intervention group consists of members currently enrolled in PHM, stratified by intensity level. Comparison groups include (1) members never enrolled, and (2) PHM participants not currently enrolled. Mixed model smoothing is employed to regress monthly medical costs on time (in months), a history of PHM enrollment, and monthly program enrollment by intensity level. Comparison group trends are used to estimate expected costs for intervention members. Savings are realized when PHM participants' costs are lower than expected. PRINCIPAL FINDINGS: This method mitigates many of the limitations faced using traditional pre-post models for estimating PHM savings in an observational setting, supports replication for ongoing monitoring, and performs basic statistical inference. CONCLUSION: This method provides payers with a confident basis for making investment decisions.
    Health Services Research 08/2012; · 2.29 Impact Factor