title: Rethinking satisfaction surveys: time to next complaint.
abstract: BACKGROUND
  Patient satisfaction surveys require considerable time and resources. Instead of only systematically seeking patient's input through standardized satisfaction surveys, it is proposed that insights into the performance of the organization should also be based on patient complaints. Complaint data are available at a fraction of the cost of conducting satisfaction surveys, and even though complaints may be rare, new analytical tools (for example, time-between control charts) enable the analysis of these data in ways that are helpful to improvement teams.
  
  
  METHODS
  MEDICAL/SURGICAL UNIT: The choice of whether the analysis should be done per day, per visit, or per discharge depends on the availability of data and the frequency of complaints. A case study shows that an analysis of the last 100 complaints (collected in a 50-day period) was sufficient to detect statistically significant change in the process of care. In the medica/surgical unit, although a complaint occasionally occurred, a series of complaints for the 22nd through the 24th day was unusual. These days of back-to-back complaints marked a departure from the general pattern of no complaints, for which improvement teams could determine the special cause.
  
  
  CONCLUSIONS
  Whereas complaint data represent only the very dissatisfied patients, satisfaction surveys report the average of satisfied and dissatisfied patients. As a consequence, complaint data allow health care managers to hear the voice of their customers without the distortions caused by including other, more satisfied patients. The cost advantage of time to complaint is obvious. The most expensive component of conducting satisfaction surveys is the data collection. In contrast, most hospitals and many other organizations maintain a system for collecting patient complaints for legal and risk management reasons. Much more can be revealed about a unit's operations when both the complaint and the satisfaction rates are calculated.
authors.affiliation: Department of Health Systems Administration, Georgetown University, Washington, DC, USA. fa@georgetown.edu
authors.forename: Farrokh
authors.initials: F
authors.lastname: Alemi
authors.forename: Patrick
authors.initials: P
authors.lastname: Hurd