BACKGROUND AND STUDY AIMS: There is widespread consensus on the need for better indicators of the effectiveness of healthcare. We carried out an analysis of the validity of amenable mortality as an indicator of the effectiveness of healthcare, focusing on the potential use in routine surveillance systems of between-country variations in rates of mortality. We assessed whether the introduction of specific healthcare innovations coincided with declines in mortality from potentially amenable causes in seven European countries. In this paper, we summarise the main results of this study and illustrate them for four conditions. DATA AND METHODS: We identified 14 conditions for which considerable declines in mortality have been observed and for which there is reasonable evidence in the literature of the effectiveness of healthcare interventions to lower mortality. We determined the time at which these interventions were introduced and assessed whether the innovations coincided with favourable changes in the mortality trends from these conditions, measured using Poisson linear spline regression. All the evidence was then presented to a Delphi panel. MAIN RESULTS: The timing of innovation and favourable change in mortality trends coincided for only a few conditions. Other reasons for mortality decline are likely to include diffusion and improved quality of interventions and in incidence of diseases and their risk factors, but there is insufficient evidence to differentiate these at present. For most conditions, a Delphi panel could not reach consensus on the role of current mortality levels as measures of effectiveness of healthcare. DISCUSSION AND CONCLUSIONS: Improvements in healthcare probably lowered mortality from many of the conditions that we studied but occurred in a much more diffuse way than we assumed in the study design. Quantification of the contribution of healthcare to mortality requires adequate data on timing of innovation and trends in diffusion and quality and in incidence of disease, none of which are currently available. Given these gaps in knowledge, between-country differences in levels of mortality from amenable conditions should not be used for routine surveillance of healthcare performance. The timing and pace of mortality decline from amenable conditions may provide better indicators of healthcare performance.
BACKGROUND AND STUDY AIMS: There is widespread consensus on the need for better indicators of the effectiveness of healthcare. We carried out an analysis of the validity of amenable mortality as an indicator of the effectiveness of healthcare, focusing on the potential use in routine surveillance systems of between-country variations in rates of mortality. We assessed whether the introduction of specific healthcare innovations coincided with declines in mortality from potentially amenable causes in seven European countries. In this paper, we summarise the main results of this study and illustrate them for four conditions. DATA AND METHODS: We identified 14 conditions for which considerable declines in mortality have been observed and for which there is reasonable evidence in the literature of the effectiveness of healthcare interventions to lower mortality. We determined the time at which these interventions were introduced and assessed whether the innovations coincided with favourable changes in the mortality trends from these conditions, measured using Poisson linear spline regression. All the evidence was then presented to a Delphi panel. MAIN RESULTS: The timing of innovation and favourable change in mortality trends coincided for only a few conditions. Other reasons for mortality decline are likely to include diffusion and improved quality of interventions and in incidence of diseases and their risk factors, but there is insufficient evidence to differentiate these at present. For most conditions, a Delphi panel could not reach consensus on the role of current mortality levels as measures of effectiveness of healthcare. DISCUSSION AND CONCLUSIONS: Improvements in healthcare probably lowered mortality from many of the conditions that we studied but occurred in a much more diffuse way than we assumed in the study design. Quantification of the contribution of healthcare to mortality requires adequate data on timing of innovation and trends in diffusion and quality and in incidence of disease, none of which are currently available. Given these gaps in knowledge, between-country differences in levels of mortality from amenable conditions should not be used for routine surveillance of healthcare performance. The timing and pace of mortality decline from amenable conditions may provide better indicators of healthcare performance.
Authors: Elizabeth R Stevens; Qinlian Zhou; Kimberly A Nucifora; Glen B Taksler; Marc N Gourevitch; Matthew C Stiefel; Patricia Kipnis; R Scott Braithwaite Journal: Popul Health Manag Date: 2018-12-04 Impact factor: 2.459
Authors: Maria Michela Gianino; Jacopo Lenzi; Aida Muça; Maria Pia Fantini; Roberta Siliquini; Walter Ricciardi; Gianfranco Damiani Journal: Health Serv Res Date: 2016-10-05 Impact factor: 3.402
Authors: Rasmus Hoffmann; Iris Plug; Martin McKee; Bernadette Khoshaba; Ragnar Westerling; Caspar Looman; Gregoire Rey; Eric Jougla; Katrin Lang; Kersti Pärna; Johan P Mackenbach Journal: Int J Public Health Date: 2013-08-29 Impact factor: 3.380