Patient satisfaction is an integral component of measuring health care quality. Attention to patient complaints is part of a strategy to resolve dissatisfaction and improve care. Our aim was to review patient complaints in a UK fertility centre, and their outcome. Data regarding all complaints made to the fertility services over 3 years, the outcome and actions implemented were collected retrospectively. Between 2008 and 2011, the fertility unit received 27 (6%) complaints from a total of 450 complaints for the entire Trust (NHS hospital). Complaints could be categorised as Primary Care Trust (funding body) (PCT) (n = 7) and non PCT related (n = 20). Most PCT complaints related to funding restrictions imposed by the PCT. The majority of complaints (n = 20) related to the fertility services and most complaints were multifactorial. Of the total, communication errors and administrative delays accounted for 19 out of 27 complaints, the remainder being due to staff attitude and direct clinical care issues. Of the 27, 25 (93%) were satisfied with a written response and only 2 required a further meeting; 67% of complaints were settled with an apology or explanation alone (18/27), while 30% (8/27) required a review of policy. Improved communication with patients, General Practitioners and commissioners should reduce complaints. The resolution of the majority of complaints can be achieved locally and should be used in a positive way to improve patient care.

A computer-aided semen analysis (CASA) was used to allow digitizing the motion of the spermatozoon. This procedure allows an objective means of judging semen quality, especially the translational movements of spermatozoa. Forty-three couples were included in the study. The average age of the male was 35.5 +/- 4.7 years and that of the female was 32.7 +/- 4.7 years. The average duration of infertility was 3.8 +/- 2.3 years. Using multiple linear regression analysis of 26 prognostic variables, a cluster of 8 variables significantly predicted pregnancy maximally. The 8 variables and the resultant multiple correlation coefficients were used to generate a multiple regression equation which allowed the correct separation of the population into fertile and infertile couples. The mean pregnancy predictor values of the fertile and infertile populations were significantly different using the analysis of variance.

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