A Framework for Contracted Health IT Performance Assessments.

Limited research exists which aids in structuring health IT contracts in an era of performance-based payments. We provide an assessment of common approaches to contracting and measuring of performance in practice. We conducted a review of existing literature and compliment this approach with a survey of healthcare professionals directly involved with health IT systems to further understand and classify current approaches. We identified architypes for structuring healthcare IT performance contracts to include: (1) internal operations, (2) external evaluation and (3) joint agreement for the delivery of value-based care.

Assessing the pro-poor effect of different contracting schemes for health services on health facilities in rural Afghanistan.

BACKGROUND: Despite progress in improving health outcomes in Afghanistan by contracting public health services through non-governmental organizations (NGOs), inequity in access persists between the poor and non-poor. This study examined the distributive effect of different contracting types on primary health services provision between the poor and non-poor in rural Afghanistan. METHOD: Contracts to NGOs were made to deliver a common set of primary care services in each province, with the funding agencies determining contract terms. The contracting approaches could be classified into three contracting out types (CO-1, CO-2 and CO-3) and a contracting-in (CI) approach based on the contract terms, design and implementation. Exit interviews of patients attending randomly sampled primary health facilities were collected through systematic sampling across 28 provinces at two time points. The outcome, the odds that a client attending a health facility is poor, was modelled using logistic regression with a robust variance estimator, and the effect of contracting was estimated using the difference-in-difference approach combined with stratified analyses. RESULTS: The sample covered 5960 interviews from 306 health facilities in 2005 and 2008. The adjusted odds of a poor client attending a health facility over time increased significantly for facilities under CO-1 and CO-2, with odds ratio of 2.82 (1.49, 5.36) P-value 0.001 and 2.00 (1.33, 3.02) P-value 0.001, respectively. The odds ratios for those under CO-3 and CI were not statistically significantly different over time. When compared with the non-contracting facilities, the adjusted ratio of odds ratios of poor status among clients was significantly higher for only those under CO-1, ratio of 2.50 (1.32, 4.74) P-value 0.005. CONCLUSIONS: CO-1 arrangement which allows contractors to decide on how funds are allocated within a fixed lump sum with non-negotiable deliverables, and actively managed through an independent government agency, is effective in improving equity of health services provision.

Predicting subcontractor performance using web-based Evolutionary Fuzzy Neural Networks.

Subcontractor performance directly affects project success. The use of inappropriate subcontractors may result in individual work delays, cost overruns, and quality defects throughout the project. This study develops web-based Evolutionary Fuzzy Neural Networks (EFNNs) to predict subcontractor performance. EFNNs are a fusion of Genetic Algorithms (GAs), Fuzzy Logic (FL), and Neural Networks (NNs). FL is primarily used to mimic high level of decision-making processes and deal with uncertainty in the construction industry. NNs are used to identify the association between previous performance and future status when predicting subcontractor performance. GAs are optimizing parameters required in FL and NNs. EFNNs encode FL and NNs using floating numbers to shorten the length of a string. A multi-cut-point crossover operator is used to explore the parameter and retain solution legality. Finally, the applicability of the proposed EFNNs is validated using real subcontractors. The EFNNs are evolved using 22 historical patterns and tested using 12 unseen cases. Application results show that the proposed EFNNs surpass FL and NNs in predicting subcontractor performance. The proposed approach improves prediction accuracy and reduces the effort required to predict subcontractor performance, providing field operators with web-based remote access to a reliable, scientific prediction mechanism.

Choice of contracts in the British National Health Service: an empirical study.

Following major reforms of the British National Health Service (NHS) in 1990, the roles of purchasing and providing health services were separated, with the relationship between purchasers and providers governed by contracts. Using a mixed multinomial logit analysis, we show how this policy shift led to a selection of contracts that is consistent with the predictions of a simple model, based on contract theory, in which the characteristics of the health services being purchased and of the contracting parties influence the choice of contract form. The paper thus provides evidence in support of the practical relevance of theory in understanding health care market reform.

A new method based on fuzzy logic to evaluate the contract service provider performance.

This paper puts forward a fuzzy inference system for evaluating the service quality performance of service contract providers. An application service provider (ASP) model for computerized maintenance management was used in establishing common performance indicators of the quality of service. This model was implemented in 10 separate hospitals. As a result, inference produced a service cost/acquisition cost (SC/AC) ratio reduction from 16.14% to 6.09%, an increase of 20.9% in availability, with a maintained repair quality (NRR) in the period of December 2001 to January 2003.