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

Moral distress among physicians in Norway: a longitudinal study

OBJECTIVES

To explore and compare physicians' reported moral distress in 2004 and 2021 and identify factors that could be related to these responses.

DESIGN

Longitudinal survey.

SETTING

Data were gathered from the Norwegian Physician Panel Study, a representative sample of Norwegian physicians, conducted in 2004 and 2021.

PARTICIPANTS

1499 physicians in 2004 and 2316 physicians in 2021.

MAIN OUTCOME MEASURES

The same survey instrument was used to measure change in moral distress from 2004 to 2021. Logistic regression analyses examined the role of gender, age and place of work.

RESULTS

Response rates were 67% (1004/1499) in 2004 and 71% (1639/2316) in 2021. That patient care is deprived due to time constraints is the most severe dimension of moral distress among physicians, and it has increased as 68.3% reported this 'somewhat' or 'very morally distressing' in 2004 compared with 75.1% in 2021. Moral distress also increased concerning that patients who 'cry the loudest' get better and faster treatment than others. Moral distress was reduced on statements about long waiting times, treatment not provided due to economic limitations, deprioritisation of older patients and acting against one's conscience. Women reported higher moral distress than men at both time points, and there were significant gender differences for six statements in 2021 and one in 2004. Age and workplace influenced reported moral distress, though not consistently for all statements.

CONCLUSION

In 2004 and 2021 physicians' moral distress related to scarcity of time or unfair distribution of resources was high. Moral distress associated with resource scarcity and acting against one's conscience decreased, which might indicate improvements in the healthcare system. On the other hand, it might suggest that physicians have reduced their ideals or expectations or are morally fatigued.

Referral assessment and patient waiting time decisions in specialized mental healthcare: an exploratory study of early routine collection of PROM (LOVePROM)

BACKGROUND

Norway has prioritized health services according to the principle of "severity of conditions", where waiting time reflects patients' medical urgency. We aim to investigate if the "severity-of-condition" principle performs well in the priority setting of waiting time, between and within groups of patients using community mental health services. We also aim to investigate the association between patients' diagnoses and symptom severity at the start of treatment and the corresponding waiting time.

METHODS

The study analyzed routine data from Lovisenberg electronic Patient-Reported Outcome Measurement (LOVePROM) at Lovisenberg Diaconal Hospital in Norway. We estimated patient-reported severity by using Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM), together with patients' diagnoses to identify patients' needs in general. To assess the performance of current prioritization, we compared waiting times for patients with major depressive disorder and their maximum recommended waiting time. Multivariate regression models were used to assess the association between patient-reported severity, their diagnosis, and waiting times.

RESULTS

Of the 6108 mental health disorder patients, patients with moderate to severe conditions waited seven weeks, while patients with mild conditions or below clinical cutoff waited 8 weeks. Included in the sample, 1583 were diagnosed with depression. Results indicated that patients with moderate and severe depression had a slightly shorter wait-time than patients with mild depression. However, 32.4% patients with moderate depression and 83.3% patients with severe depression, waited longer than their maximum recommended waiting time. CORE-OM identified depressive patients with risk-to-self harm, who had a 0.84 weeks shorter wait-time. These results were also applied to patients with other common mental health disorders.

CONCLUSION

Overall, patients waited in accordance with the "severity of condition" principle, but the trend was not strong. Therefore, we advocate that there is substantial room for quality improvements in priority setting on waiting time. We suggest further research should investigate if routine collection of PROM and assessment of referral letters, can better inform specialists when deciding on waiting time.

Patient waiting time analysis for elective gynecologic surgeries in a tertiary training hospital in the Philippines: A retrospective cross-sectional study

Objectives

This study aimed to determine the median waiting time and assess the factors affecting patient waiting time and scheduling for elective gynecologic surgery in a tertiary training hospital in the Philippines.

Methods

A retrospective analysis of waiting times for elective gynecologic surgeries was performed. The different time intervals for each step of the process map were determined. Regression models were used to study the relationship between waiting time intervals and demographic data, consideration of malignancy, and surgeries performed.

Results

The median waiting time from the date of the first consult to surgery was 154 days. Patients with consideration of malignancy and pelvic organ prolapse had significantly longer intervals from the Waitlist Clinic to actual surgery with regression coefficients of 6.76 and 17.53 days, respectively. Other intervals in the process map did not show significant differences.

Conclusions

The median waiting time for elective gynecologic surgeries in a tertiary training institution in the Philippines was longer than global standards. A significant amount of time was spent waiting for diagnostic studies and referral to the Waitlist Clinic. The study recommends regulating and improving systems processes at the hospital and national levels to decrease patient waiting time. Surgical waitlists, referral systems, and benchmarks for safe waiting times should be established.

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The median waiting time for elective gynecologic surgeries in a tertiary training institution in the Philippines was found to be longer than global standards.

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At the hospital level, strategies to decrease the waiting time should involve logistical analysis and changes in the physical setup, human resources, and process flows.

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Referral systems to other hospitals capable of providing care for less specialized surgeries should be explored. Interventions should improve coordination between providers to enhance the quality of care and avoid unnecessary delays in healthcare delivery.

Designing centralized waiting lists for attachment to a primary care provider: Considerations from a logic analysis

Access to a regular primary care provider is essential to quality care. In Canada, where 15 % of patients are unattached (i.e., without a regular provider), centralized waiting lists (CWLs) help attach patients to a primary care provider (family physician or nurse practitioner). Previous studies reveal mechanisms needed for CWLs to work, but focus mostly on CWLs for specialized health care. We aim to better understand how to design CWLs for unattached patients in primary care. In this study, a logic analysis compares empirical evidence from a qualitative case study of CWLs for unattached patients in seven Canadian provinces to programme theory derived from a realist review on CWLs. Data is analyzed using context-intervention-mechanism-outcome configurations. Results identify mechanisms involved in three components of CWL design: patient registration, patient prioritization, and patient assignment to a provider for attachment. CWL programme theory is revised to integrate mechanisms specific to primary care, where patients, rather than referring providers, are responsible for registering on the CWL, where prioritization must consider a broad range of conditions and characteristics, and where long-term acceptability of attachment is important. The study provides new insight into mechanisms that enable CWLs for unattached patients to work.

Patient prioritisation methods to shorten waiting times for elective surgery: A systematic review of how to improve access to surgery

BACKGROUND

Concern about long waiting times for elective surgeries is not a recent phenomenon, but it has been heightened by the impact of the COVID-19 pandemic and its associated measures. One way to alleviate the problem might be to use prioritisation methods for patients on the waiting list and a wide range of research is available on such methods. However, significant variations and inconsistencies have been reported in prioritisation protocols from various specialties, institutions, and health systems. To bridge the evidence gap in existing literature, this comprehensive systematic review will synthesise global evidence on policy strategies with a unique insight to patient prioritisation methods to reduce waiting times for elective surgeries. This will provide evidence that might help with the tremendous burden of surgical disease that is now apparent in many countries because of operations that were delayed or cancelled due to the COVID-19 pandemic and inform policy for sustainable healthcare management systems.

METHODS

We searched PubMed, EMBASE, SCOPUS, Web of Science, and the Cochrane Library, with our most recent searches in January 2020. Articles published after 2013 on major elective surgery lists of adult patients were eligible, but cancer and cancer-related surgeries were excluded. Both randomised and non-randomised studies were eligible and the quality of studies was assessed with ROBINS-I and CASP tools. We registered the review in PROSPERO (CRD42019158455) and reported it in accordance with the PRISMA statement.

RESULTS

The electronic search in five bibliographic databases yielded 7543 records (PubMed, EMBASE, SCOPUS, Web of Science, and Cochrane) and 17 eligible articles were identified in the screening. There were four quasi-experimental studies, 11 observational studies and two systematic reviews. These demonstrated moderate to low risk of bias in their research methods. Three studies tested generic approaches using common prioritisation systems for all elective surgeries in common. The other studies assessed specific prioritisation approaches for re-ordering the waiting list for a particular surgical specialty.

CONCLUSIONS

Explicit prioritisation tools with a standardised scoring system based on clear evidence-based criteria are likely to reduce waiting times and improve equitable access to health care. Multiple attributes need to be considered in defining a fair prioritisation system to overcome limitations with local variations and discriminations. Collating evidence from a diverse body of research provides a single framework to improve the quality and efficiency of elective surgical care provision in a variety of health settings. Universal prioritisation tools with vertical and horizontal equity would help with re-ordering patients on waiting lists for elective surgery and reduce waiting times.

How the design and implementation of centralized waiting lists influence their use and effect on access to healthcare - A realist review

CONTEXT

Many health systems have centralized waiting lists (CWLs), but there is limited evidence on CWL effectiveness and how to design and implement them.

AIM

To understand how CWLs' design and implementation influence their use and effect on access to healthcare.

METHODS

We conducted a realist review (n = 21 articles), extracting context-intervention-mechanism-outcome configurations to identify demi-regularities (i.e., recurring patterns of how CWLs work).

RESULTS

In implementing non-mandatory CWLs, acceptability to providers influences their uptake of the CWL. CWL eligibility criteria that are unclear or conflict with providers' role or judgement may result in inequities in patient registration. In CWLs that prioritize patients, providers must perceive the criteria as clear and appropriate to assess patients' level of need; otherwise, prioritization may be inconsistent. During patients' assignment to service providers, providers may select less-complex patients to obtain CWLs rewards or avoid penalties; or may select patients for other policies with stronger incentives, disregarding the established patient order and leading to inequities and limited effectiveness.

CONCLUSION

These findings highlight the need to consider provider behaviours in the four sequential CWL design components: CWL implementation, patient registration, patient prioritization and patient assignment to providers. Otherwise, CWLs may result in limited effects on access or lead to inequities in access to services.

Long Waiting Times for Elective Hospital Care - Breaking the Vicious Circle by Abandoning Prioritisation

Background: Policies assigning low-priority patients treatment delays for care, in order to make room for patients of higher priority arriving later, are common in secondary healthcare services today. Alternatively, each new patient could be granted the first available appointment. We aimed to investigate whether prioritisation can be part of the reason why waiting times for care are often long, and to describe how departments can improve their waiting situation by changing away from prioritisation.

Methods: We used patient flow data from 2015 at the Department of Otorhinolaryngology, Haukeland University Hospital, Norway. In Dynaplan Smia, Dynaplan AS, dynamic simulations were used to compare how waiting time, size and shape of the waiting list, and capacity utilisation developed with and without prioritisation. Simulations were started from the actual waiting list at the beginning of 2015, and from an empty waiting list (simulating a new department with no initial patient backlog).

Results: From an empty waiting list and with capacity equal to demand, waiting times were built 7 times longer when prioritising than when not. Prioritisation also led to poor resource utilisation and short-lived effects of extra capacity. Departments where prioritisation is causing long waits can improve their situation by temporarily bringing capacity above demand and introducing "first come, first served" instead of prioritisation.

Conclusion: A poor appointment allocation policy can build long waiting times, even when capacity is sufficient to meet demand. By bringing waiting times down and going away from prioritisation, the waiting list size and average waiting times at the studied department could be maintained almost 90% below the current level – without requiring permanent change in the capacity/demand ratio.