Do maximum waiting times guarantees change clinical priorities for elective treatment? Evidence from Scotland

Nikolova, Silviya; Sinko, Arthur; Sutton, Matt

doi:10.1016/j.jhealeco.2015.02.001

Cited by 17 publications

(20 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…My results also highlight a potential downfall of waiting time targets as a policy lever. Although targets have been shown to be effective in reducing some waiting time measures in elective care (Kelman & Friedman, ; Propper, Sutton, Whitnall, & Windmeijer, ), waiting time targets may lead to gaming of the distribution of waits (e.g., Nikolova, Sinko, & Sutton, ) especially if overall waiting time cannot be reduced because of the additional demand response.…”

Section: Discussionmentioning

confidence: 99%

Should I stay or should I go? Hospital emergency department waiting times and demand

Sivey

2017

Health Economics

View full text Add to dashboard Cite

In the absence of the price mechanism, hospital emergency departments rely on waiting times, alongside prioritisation mechanisms, to restrain demand and clear the market. This paper estimates by how much the number of treatments demanded is reduced by a higher waiting time. I use variation in waiting times for low-urgency patients caused by rare and resource-intensive high-urgency patients to estimate the relationship. I find that when waiting times are higher, more low-urgency patients are deterred from treatment and leave the hospital during the waiting period without being treated. The waiting time elasticity of demand for low-urgency patients is approximately -0.25 and is highest for the lowest-urgency patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Should I stay or should I go? Hospital emergency department waiting times and demand

Sivey

2017

Health Economics

View full text Add to dashboard Cite

show abstract

“…However, the priority profiles as measured by the distribution of the guaranteed waiting times may roughly classify the specialties into three different typologies: two with distinct peaks for respectively short or long guaranteed waiting times, and the third with a more heterogeneous distribution. Nikolova et al 14 also identify three sets of disease categories which are based on the difference in the magnitude of the effects, and present the results for circulatory, digestive system diseases and diseases of the nervous system. We selected four different specialties fitting the three typologies for further detailed analysis: gastroenterology, pulmonary diseases, orthopedic surgery, and mental healthcare for adults.…”

Section: Methodsmentioning

confidence: 99%

Norwegian Priority Setting in Practice – an Analysis of Waiting Time Patterns Across Medical Disciplines

Gangstøe

Heggestad

Norheim

2016

Int J Health Policy Manag

View full text Add to dashboard Cite

Background: Different strategies for addressing the challenge of prioritizing elective patients efficiently and fairly have been introduced in Norway. In the time period studied, there were three possible outcomes for elective patients that had been through the process of priority setting: (i) high priority with assigned individual maximum waiting time; (ii) low priority without a maximum waiting time; and (iii) refusal (not in need for specialized services). We study variation in priority status and waiting time of the first two groups across different medical disciplines. Methods: Data was extracted from the Norwegian Patient Register (NPR) and contains information on elective referrals to 41 hospitals in the Western Norway Regional Health Authority in 2010. The hospital practice across different specialties was measured by patient priority status and waiting times. The distributions of assigned maximum waiting times and the actual ones were analyzed using standard Kernel density estimation. The perspective of the planning process was studied by measuring the time interval between the actual start of healthcare and the maximum waiting time. Results: Considerable variation was found across medical specialties concerning proportion of priority patients and their maximum waiting times. The degree of differentiation in terms of maximum waiting times also varied by medical discipline. We found that the actual waiting time was very close to the assigned maximum waiting time. Furthermore, there was no clear correspondence between the actual waiting time for patients and their priority status. Conclusion: Variations across medical disciplines are often interpreted as differences in clinical judgment and capacity. Alternatively they primarily reflect differences in patient characteristics, patient case-mix, as well as capacity. One hypothesis for further research is that the introduction of maximum waiting times may have contributed to push the actual waiting time towards the maximum. The finding that the actual waiting time was very close to the maximum waiting time supports this. The lack of clear correspondence between the actual waiting time for patients and their priority status may imply that urgency, described in the referral letter, and severity of illness, according to guidelines, are two separate entities. Keywords: Waiting Lists, Prioritization, Healthcare Sector Copyright: © 2016 by Kerman University of Medical Sciences Citation: Gangstøe JJ, Heggestad T, Norheim OF. Norwegian priority setting in practice -an analysis of waiting time patterns across medical disciplines.

show abstract

“…Long waiting lists have, however, been an issue in many healthcare systems, e.g. the UK (Frankel, 1993;Nikolova et al, 2015), Norway (Askildsen et al, 2011) andSweden (Robertsson et al, 2017), to name just a few. In Sweden, waiting times have varied considerably, for example in cancer care, with large differences in waiting times between patients in different regions and with different types of cancer (Robertsson et al, 2017).…”

Section: Rq3: How Do the Hospital Organisation And Middle Management Involvement Influence The Use Of Actions To Handle Variation In Acutmentioning

confidence: 99%

Managing variation in hospital patient flows

Olsson

2021

Linköping Studies in Science and Technology. Dissertations

View full text Add to dashboard Cite

Do maximum waiting times guarantees change clinical priorities for elective treatment? Evidence from Scotland

Cited by 17 publications

References 31 publications

Should I stay or should I go? Hospital emergency department waiting times and demand

Should I stay or should I go? Hospital emergency department waiting times and demand

Norwegian Priority Setting in Practice – an Analysis of Waiting Time Patterns Across Medical Disciplines

Managing variation in hospital patient flows

Contact Info

Product

Resources

About