A controlled time-series trial of clinical reminders: using computerized firm systems to make quality improvement...

To explore the feasibility of conducting unobtrusive interventional research in community practice settings by integrating firm-system techniques with time-series analysis of relational-repository data.

A satellite teaching clinic divided into two similar, but geographically separated, primary care group practices called firms. One firm was selected by chance to receive the study intervention. Forty-two providers and 2,655 patients participated.

A nonrandomized controlled trial of computer-generated preventive reminders. Net effects were determined by quantitatively combining population-level data from parallel experimental and control interrupted time series extending over two-month baseline and intervention periods.

Mean rates at which mammography, colorectal cancer screening, and cholesterol testing were performed on patients due to receive each maneuver at clinic visits were the trial's outcome measures.

Mammography performance increased on the experimental firm by 154 percent (0.24 versus 0.61, p = .03). No effect on fecal occult blood testing was observed. Cholesterol ordering decreased on both the experimental (0.18 versus 0.1 1, p = .02) and control firms (0.13 versus 0.07, p = .03) coincident with national guidelines retreating from recommending screening for young adults. A traditional uncontrolled interrupted time-series design would have incorrectly attributed the experimental-firm decrease to the introduction of reminders. The combined analysis properly indicated that no net prompting effect had occurred, as the difference between firms in cholesterol testing remained stochastically stable over time (0.05 versus 0.04, p = .75). A logistic-regression analysis applied to individual-level data produced equivalent findings. The trial incurred no supplementary data collection costs.

The apparent validity and practicability of our reminder implementation study should encourage others to develop computerized firm systems capable of conducting controlled time-series trials.