Mark D. Sullivan

Health utility (HU) measures are used as overall measures of quality of life and to determine quality adjusted life years (QALYs) in economic analyses. We compared baseline values of three HUs including Short Form 6 Dimensions (SF-6D), and Health Utilities Index, Mark II and Mark III (HUI2 and HUI3) and the feeling thermometer (FT) among type 2 diabetes participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. We assessed relationships between HU and FT values and patient demographics and clinical variables. ACCORD was a randomized clinical trial to test if intensive controls of glucose, blood pressure and lipids can reduce the risk of major cardiovascular disease (CVD) events in type 2 diabetes patients with high risk of CVD. The health-related quality of life (HRQOL) sub-study includes 2,053 randomly selected participants. Interclass correlations (ICCs) and agreement between measures by quartile were used to evaluate relationships between HU’s and the FT. Multivariable regression models specified relationships between patient variables and each HU and the FT. The ICCs were 0.245 for FT/SF-6D, 0.313 for HUI3/SF-6D, 0.437 for HUI2/SF-6D, 0.338 for FT/HUI2, 0.337 for FT/HUI3 and 0.751 for HUI2/HUI3 (P < 0.001 for all). Common classification by quartile was found for the majority (62%) of values between HUI2 and HUI3, which was significantly (P < 0.001) higher than between other HUs and the FT: SF-6D/HUI3 = 40.8%, SF-6D/HUI2 = 40.9%, FT/HUI3 = 35.0%, FT/HUI2 = 34.9%, and FT/SF-6D = 31.9%. Common classification was higher between SF-6D/HUI2 and SF-6D/HUI3 (P < 0.001) than between FT/SF-6D, FT/HUI2, and FT/HUI3. The mean difference in HU values per patient ranged from −0.024 ± 0.225 for SF-6D/ HUI3 to −0.124 ± 0.133 for SF-6D/HUI2. Regression models were significant; clinical and demographic variables explained 6.1% (SF-6D) to 7.7% (HUI3) of the variance in HUs. The agreements between the different HUs were poor except for the two HUI measures; therefore HU values derived different measures may not be comparable. The FT had low agreement with HUs. The relationships between HUs and demographic and clinical measures demonstrate how severity of diabetes and other clinical and demographic factors are associated with HUs and FT measures. ClinicalTrials.gov Identifier: NCT00000620

Shared decision-making is not widely implemented in healthcare. We aimed to set a research agenda about promoting shared decision-making through continuing professional development.

Shared decision making (SDM) is a process by which a healthcare choice is made jointly by the healthcare professional and the patient. SDM is the essential element of patient-centered care, a core concept of primary care. However, SDM is seldom translated into primary practice. Continuing professional development (CPD) is the principal means by which healthcare professionals continue to gain, improve, and broaden the knowledge and skills required for patient-centered care. Our international collaboration seeks to improve the knowledge base of CPD that targets translating SDM into the clinical practice of primary care in diverse healthcare systems.

Chronic opioid therapy (COT) is now a common strategy for managing chronic noncancer pain (CNCP).^1-3 Concurrent with an increase in COT for CNCP has been an increase in reported opioid abuse and deaths from prescription opioid overdose. In Washington state, an increase in overdose deaths among individuals receiving workers' compensation benefits was observed between 1996 and 2002, concurrent with a shift toward the use of more potent Schedule II opioids and a 50% increase in average daily morphine dose.⁴ Similar increases in opioid-related fatal poisoning rates have been found in Massachusetts⁵ and in Oregon.⁶ Nonfatal adverse events resulting from prescription opioid use also appear to be increasing. The Centers for Disease Control⁷ estimates that the number of emergency department (ED) visits for nonmedical use of opioid analgesics increased 111% from 2004 to 2008 (from 144 600 to 305 900 visits) and increased 29% just during the 2007-2008 period. Oxycodone, hydrocodone, and methadone were most frequently noted, and the use of all of these showed statistically significant increases.

The use of chronic opioid therapy (COT) for chronic non-cancer pain (CNCP) has increased dramatically in the past two decades. There has also been a marked increase in the abuse of prescribed opioids and in accidental opioid overdose. Misuse of prescribed opioids may link these trends, but has thus far only been studied in small clinical samples. We therefore sought to validate an administrative indicator of opioid misuse among large samples of recipients of COT and determine the demographic, clinical, and pharmacological risks associated with possible and probable opioid misuse. A total of 21,685 enrollees in commercial insurance plans and 10,159 in Arkansas Medicaid who had at least 90 days of continuous opioid use 2000-2005 were studied for one year. Criteria were developed for possible and probable opioid misuse using administrative claims data concerning excess days supplied of short-acting and long-acting opioids, opioid prescribers and opioid pharmacies. We estimated possible misuse at 24% of COT recipients in the commercially insured sample and 20% in the Medicaid sample and probable misuse at 6% in commercially insured and at 3% in Medicaid. Among non-modifiable factors, younger age, back pain, multiple pain complaints and substance abuse disorders identify patients at high risk for misuse. Among modifiable factors, treatment with high daily dose opioids (especially >120 mg MED per day) and short-acting Schedule II opioids appears to increase the risk of misuse. The consistency of the findings across diverse patient populations and the varying levels of misuse suggest that these results will generalize broadly, but await confirmation in other studies.