BACKGROUND

The practice of medicine is currently undergoing a transformation to become more efficient, cost effective, and patient centered in its delivery of care. Sleep medicine encompasses multiple disorders across many disciplines that affect millions of individuals; however, its traditional management approaches have limitations.

OBJECTIVES

We designed the Sustainable Methods, Algorithms, and Research Tools for Delivering Optimal Care Study (SMART DOCS) to meet 2 specific aims: (1) Develop a patient-centered outcomes and coordinated-care management (PCCM) approach for sleep medicine enabling providers and patients access to specific and relevant information and resources, thereby allowing patients to make informed health care decisions and providers to assist patients in achieving their preferred outcomes; and (2) conduct a randomized trial to test the PCCM approach for sleep medicine against a conventional diagnostic and treatment outpatient medical care (CONV) approach with assessment of patient satisfaction and perception of care.

METHODS

SMART DOCS was a randomized, 2-arm, single-center, long-term, comparative effectiveness trial with 1836 patients aged 18 years or older randomized to either the PCCM or CONV approach. Patients in the PCCM approach were provided access to new tools, tests, and technologies for management of their sleep disorder. We followed patients over the course of 1 year with endpoints of improved health care performance, better health, and cost control. We measured improved health care performance using the global rating score on the Clinician and Group Survey-Consumer Assessment of Healthcare Providers and Systems (CG-CAHPS) questionnaire (co-primary outcome). We used the Vitality Scale Score on the Short Form-36 (SF-36) questionnaire (co-primary outcome) at baseline and at the end of the study to measure health. In addition, we analyzed provider communication and helpfulness of the provider's website and use of computers. We estimated the financial burden of patient care via out-of-pocket costs.

RESULTS

The PCCM approach did not significantly impact the primary outcomes of the global rating score of the providers on the CG-CAHPS (unadjusted mean ± SD [n]: PCCM 8.4 ± 1.65 [534], CONV 8.3 ± 1.97 [544]; adjusted difference in means [SE]: 0.02 [0.074]; 95% CI, −0.124 to 0.166; = .778) or the Vitality Scale Score (unadjusted mean ± SD [n]: PCCM 47.1 ± 11.19 [520], CONV 48.0 ± 10.84 [515]; transformed scale adjusted difference in means [SE]: −0.015 [0.042]; 95% CI, −0.098 to 0.068; = .716) on the SF-36. For the secondary outcomes, we found no group differences for provider communication (unadjusted average score ± SD [n]: PCCM 3.6 ± 0.55 [524], CONV 3.6 ± 0.65 [528]; adjusted difference in total score [SE]: 0.09 [0.137]; 95% CI, −0.183 to 0.353; = .537); however, we found minor provider effects. Additionally, we found significant group differences (unadjusted average score ± SD [n]: PCCM 3.3 ± 0.77 [268], CONV 3.3 ± 0.79 [266]; adjusted difference in total score [SE]: 0.18 [0.061]; 95% CI, 0.061-0.301; = .003) and minor provider effects on the adoption of new technology by patients. Retention in the research study was not significantly different by arm. Finally, self-reported median out-of-pocket costs for patients in the PCCM arm were not significantly different ( = .328) from those for patients in the CONV arm.

CONCLUSIONS

In this prospective study of a new patient-centered approach, the use of new tools, tests, and technologies in sleep medicine did not affect the primary outcomes of patient ratings of their providers or patient vitality.

LIMITATIONS AND SUBPOPULATION CONSIDERATIONS

The principal limitation of SMART DOCS is that implementing some of the new strategies with the PCCM arm was difficult because SMART DOCS was so useful to the providers that it became part of standard practice throughout the progression of the study (eg, electronic branching-logic Alliance Sleep Questionnaire with eventual completion rates of 39% in CONV arm and 46% in the PCCM arm). This contamination bias diluted the comparative benefit of the PCCM arm and could have been prevented by conducting a cluster-randomized trial instead of a patient-level randomized trial. The extensive (38%) missing data for the primary outcomes and the available cases analysis resulted in possible selection bias and reduced precision.