The impact of decentralisation on sexual and reproductive health services in Ghana

This paper analyses the impact of decentralisation on the political organisation, management and provision of sexual and reproductive health services in Ghana. It draws on qualitative research and interviews with key informants from the Ministry of Health, donors, NGOs, regional and district health management teams, local government and community leaders. Within a national reproductive health policy framework, previously disparate family planning, maternal and child health, STI and HIV/AIDS programmes have become more integrated, and donors have pooled or co-ordinated their funding. Some decision-making about resource allocation is meant to happen at district and regional level but in practice, this remains centrally controlled, which may be a necessary safeguard for sexual and reproductive health services. Earmarked donor funds still ensure a regular supply of contraceptives and STI drugs. However, paying for these is problematic at local level. Sexual and reproductive health staff make up a large proportion of primary health care staff, but especially in rural areas they experience poor working conditions, and there is high turnover and vacancies. District and sub-district level links are working well in this new system, but clarity is still needed on how different national sexual and reproductive health bodies relate to each other and to regional and district health authorities. The development of formal mechanisms for priority setting and advocacy at local levels could help to secure benefits for sexual and reproductive health care.

Integrating healthcare: the Counties Manukau experience

In 1998, Counties Manukau District Health Board (CMDHB) was experiencing rapidly increasing demands on its secondary services. It was finding it increasingly difficult to meet the health needs of its relatively deprived population. There was widespread evidence of "systems failure", with poor coordination of primary and secondary services. A strategic plan was devised to meet identified priorities and this was subsequently implemented with extensive community involvement. A "disruptive change" model was utilised. Thirty separate projects were undertaken to improve coordination and integration of health services. Brief summaries of all projects are presented, and full evaluations were performed of major projects. Factors critical to project success were: dedicated and effective leadership; involvement of clinical staff; early engagement of the Maori and Pacific community; careful selection of stakeholders; reassurance for providers about privacy issues; close monitoring of project progress; realistic timeframes; and adequate initial funding. CMDHB believes that the critical factor to success in improving the performance of the health sector will be the ability of our key leaders in primary and secondary care, in both management and clinical roles, to adopt a systems view to problem analysis and solution building

How to release allocated operating room time to increase efficiency: predicting which surgical service will have the most underutilized operating room time

At many facilities, surgeons and patients choose the day of surgery, cases are not turned away, and staffing is adjusted to maximize operating room (OR) efficiency. If a surgical service has already filled its allocated OR time, but has an additional case to schedule, then OR efficiency is increased by scheduling the new case into the OR time of a different service with much underutilized OR time. The latter service is said to be "releasing" its allocated OR time. In this study, we analyzed 3 years of scheduling data from a medium-sized and a large surgical suite. Theoretically, the service that should have its OR time released is the service expected to have the most underutilized OR time on the day of surgery (i.e., any future cases that may be scheduled into that service's time also need to be factored in). However, we show that OR efficiency is only slightly less when the service whose time is released is the service that has the most allocated but unscheduled (i.e., unfilled) OR time at the moment the new case is scheduled. In contrast, compromising by releasing the OR time of a service other than the one with the most allocated but unscheduled OR time markedly reduces OR efficiency. OR managers can use these results when releasing allocated OR time.

[Barriers to the fair allocation of healthcare resources]

The gap between infinite healthcare needs and finite health resources imposes on practicing physicians a dual commitment to patients' needs and to the fair allocation of health care resources. The ethical principles of a fair allocation of resources are egalitarianism, utilitarianism and a transition from individual to group-based ethics. These principles are ambiguous and occasionally conflicting. Their implementation is further impeded by practice norms, such as private practice by physicians employed by public institutions, incentives for physicians to save, and marketing of clinical interventions of unproven efficacy. Proposed approaches to these barriers to the fair allocation of resources include respect of patient autonomy with full disclosure of the limitations in the services provided by the health plan; adherence to clinical practice guidelines; and an open access for patients to second medical opinion. I believe that the fairness of resource allocation may be further improved by the prohibition of private practice by physicians employed in public health care institutions, and by enhancement of physicians' self-awareness of subconscious discrimination against some patients.

Looking at the forest instead of counting the trees: an alternative method for measuring faculty's clinical education efforts

PURPOSE

To present an alternative approach to mission-based management (MBM) for assessing the clinical teaching efforts of the faculty in the third and fourth years of medical students' education.

METHOD

In fiscal years 2000 and 2001, interviews were conducted with department chairs and faculty members with major responsibilities in education at the University of Maryland School of Medicine. Using a standard worksheet, each rotation was categorized according to the amounts of time students spent in five teaching modes. After each department described its rotation and maximum teaching time, the department team and the MBM team negotiated the final credit received for its course. This final determination of departmental clinical teaching was used in subsequent calculations. Adjustments were made to the department clinical education time based on the teaching mode. Groups of medical students were surveyed to determine the relative value of each teaching mode. These relative values were then used to modify the clinical education times credited to the department. The last step was to distribute the effort of the faculty between clinical and educational missions.

RESULTS

The data analysis showed approximately 57,000 credited faculty hours in one year for direct education of medical students in each curriculum year. These hours equal the annual workload of 28 full-time faculty members.

CONCLUSIONS

A powerful use of MBM data is to move from thinking about resource allocation to thinking about the effective management of a complex organization with interlaced missions. Reliable data on faculty's contributions to medical students' education across departments enhances other MBM information and contributes to a picture of the dynamic interconnectedness of missions and departments.

Optimal resource allocation for curing Chlamydia trachomatis infection among asymptomatic women at clinics operating on a fixed budget

GOAL

The goal was to determine the optimal strategy for screening coverage, test selection, and treatment for infection in asymptomatic women for a given family-planning-program budget.

STUDY DESIGN

We developed a resource allocation model to determine the optimal strategy using data from 5078 visits by women universally screened for infection in a publicly funded family planning clinic system in Philadelphia. We maximized the number of infected women cured from the clinic perspective and maximized the cost-savings from the healthcare system perspective. The model incorporated the following age distributions: <20 years (27%), 20 to 24 years (30%), and >24 years (43%), with prevalences of 10.6%, 6.9%, and 2.3%, respectively. We modeled two screening test assays (DNA probe and ligase chain reaction [LCR] for cervical specimens) and two treatments (doxycycline and azithromycin). The model allowed for different test and treatment choices by age group.

RESULTS

At the baseline annual budget of $6 per visit, the strategy that maximized both the number of infected women cured and cost savings would be to screen all women with DNA probe and to treat all women with positive tests with azithromycin. This strategy would result in 183 women cured at a cost-savings of $140,176. Sensitivity analysis showed that the total budget had a great impact on the optimal strategy, incorporating screening coverage, test selection, and treatment.

CONCLUSIONS

Using resource allocation models enables clinic managers operating with a fixed budget to identify a strategy that maximizes the number of asymptomatic women cured and cost savings when the clinic age distribution and age-specific prevalences are known.