The effect of the Iranian health transformation plan on hospitalization rate: insights from an interrupted time series analysis

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Abstract

Background

Healthcare policy- and decision-makers make efforts to build and maintain high-performing and effective health systems, implementing effectiveness programs and health reforms. In May 2014, the Iranian Ministry of Health and Medical Education has launched a series of ambitious reforms, known as the Health Transformation Plan (HTP). This study aimed to determine the effect of the HTP on hospitalization rate in Iranian public hospitals affiliated to the Ministry of Health and Medical Education.

Methods

This study was designed as a quasi-experimental, counterfactual study utilizing the interrupted time series analysis (ITSA), comparing the trend of hospitalization rate before and after the HTP implementation in 16 hospitals in the Lorestan province. Data was collected from March 2012 to February 2019.

Results

In the first month of the HTP implementation, an increase of 2.627 [95% CI: 1.62–3.63] was noted ( P < 0.001). Hospitalization rate increased by 0.68 [95% CI: 0.32–0.85] after the HTP implementation compared to the first month after the launch of the HTP ( P < 0.001). After the HTP implementation, monthly hospitalization rate per 1000 persons significantly increased by 0.049 [95% CI: 0.023–0.076] ( P < 0.001).

Conclusions

The HTP implementation has resulted in an increased hospitalization rate. Health planners should continue to further improve this service. ITSA can play a role in evaluating the impact of a given health policy.

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Most cited references 30

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Interrupted time series regression for the evaluation of public health interventions: a tutorial

James Lopez Bernal, Steven Cummins, Antonio Gasparrini (2016)

Abstract Interrupted time series (ITS) analysis is a valuable study design for evaluating the effectiveness of population-level health interventions that have been implemented at a clearly defined point in time. It is increasingly being used to evaluate the effectiveness of interventions ranging from clinical therapy to national public health legislation. Whereas the design shares many properties of regression-based approaches in other epidemiological studies, there are a range of unique features of time series data that require additional methodological considerations. In this tutorial we use a worked example to demonstrate a robust approach to ITS analysis using segmented regression. We begin by describing the design and considering when ITS is an appropriate design choice. We then discuss the essential, yet often omitted, step of proposing the impact model a priori. Subsequently, we demonstrate the approach to statistical analysis including the main segmented regression model. Finally we describe the main methodological issues associated with ITS analysis: over-dispersion of time series data, autocorrelation, adjusting for seasonal trends and controlling for time-varying confounders, and we also outline some of the more complex design adaptations that can be used to strengthen the basic ITS design.

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Health Sector Evolution Plan in Iran; Equity and Sustainability Concerns.

Maziar Moradi-Lakeh, Abbas Vosoogh-Moghaddam (2015)

In 2014, a series of reforms, called as the Health Sector Evolution Plan (HSEP), was launched in the health system of Iran in a stepwise process. HSEP was mainly based on the fifth 5-year health development national strategies (2011-2016). It included different interventions to: increase population coverage of basic health insurance, increase quality of care in the Ministry of Health and Medical Education (MoHME) affiliated hospitals, reduce out-of-pocket (OOP) payments for inpatient services, increase quality of primary healthcare, launch updated relative value units (RVUs) of clinical services, and update tariffs to more realistic values. The reforms resulted in extensive social reaction and different professional feedback. The official monitoring program shows general public satisfaction. However, there are some concerns for sustainability of the programs and equity of financing. Securing financial sources and fairness of the financial contribution to the new programs are the main concerns of policy-makers. Healthcare providers' concerns (as powerful and influential stakeholders) potentially threat the sustainability and efficiency of HSEP. Previous experiences on extending health insurance coverage show that they can lead to a regressive healthcare financing and threat financial equity. To secure financial sources and to increase fairness, the contributions of people to new interventions should be progressive by their income and wealth. A specific progressive tax would be the best source, however, since it is not immediately feasible, a stepwise increase in the progressivity of financing must be followed. Technical concerns of healthcare providers (such as nonplausible RVUs for specific procedures or nonefficient insurance-provider processes) should be addressed through proper revision(s) while nontechnical concerns (which are derived from conflicting interests) must be responded through clarification and providing transparent information. The requirements of HSEP and especially the key element of progressive tax should be considered properly in the coming sixth national development plan (2016-2021).

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Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico

Omar Galarraga, Sandra G Sosa-Rubí, Aarón Salinas Rodríguez … (2009)

The goal of Seguro Popular (SP) in Mexico was to improve the financial protection of the uninsured population against excessive health expenditures. This paper estimates the impact of SP on catastrophic health expenditures (CHE), as well as out-of-pocket (OOP) health expenditures, from two different sources. First, we use the SP Impact Evaluation Survey (2005–2006), and compare the instrumental variables (IV) results with the experimental benchmark. Then, we use the same IV methods with the National Health and Nutrition Survey (ENSANUT 2006). We estimate naïve models, assuming exogeneity, and contrast them with IV models that take advantage of the specific SP implementation mechanisms for identification. The IV models estimated included two-stage least squares (2SLS), bivariate probit, and two-stage residual inclusion (2SRI) models. Instrumental variables estimates resulted in comparable estimates against the “gold standard.” Instrumental variables estimates indicate a reduction of 54% in catastrophic expenditures at the national level. SP beneficiaries also had lower expenditures on outpatient and medicine expenditures. The selection-corrected protective effect is found not only in the limited experimental dataset, but also at the national level.

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Author and article information

Contributors

Siavash Beiranvand: beiranvandsiavash@yahoo.com

Mandana Saki: mandanasakilums@yahoo.com

Meysam Behzadifar: m_behzadifar67@yahoo.com

Ahad Bakhtiari: ah.bakhtyari@gmail.com

Masoud Behzadifar: masoudbehzadifar@gmail.com

Mohammad Keshvari: mohamadkeshvari@gmail.com

Nicola Luigi Bragazzi: robertobragazzi@gmail.com

Journal

Journal ID (nlm-ta): BMC Health Serv Res

Journal ID (iso-abbrev): BMC Health Serv Res

Title: BMC Health Services Research

Publisher: BioMed Central (London )

ISSN (Electronic): 1472-6963

Publication date (Electronic): 19 April 2020

Publication date PMC-release: 19 April 2020

Publication date Collection: 2020

Volume: 20

Electronic Location Identifier: 327

Affiliations

[1 ]GRID grid.411406.6, ISNI 0000 0004 1757 0173, Social Determinants of Health Research Center, , Lorestan University of Medical Sciences, ; Khorramabad, Iran

[2 ]GRID grid.411746.1, ISNI 0000 0004 4911 7066, Health Management and Economics Research Center, , Iran University of Medical Sciences, ; Tehran, Iran

[3 ]GRID grid.411705.6, ISNI 0000 0001 0166 0922, Department of Health Management and Economics, School of Public Health, , Tehran University of Medical Science, ; Tehran, Iran

[4 ]GRID grid.411406.6, ISNI 0000 0004 1757 0173, Vice Chancellor Treatment, , Lorestan University of Medical Sciences, ; Khorramabad, Iran

[5 ]GRID grid.5606.5, ISNI 0000 0001 2151 3065, School of Public Health, Department of Health Sciences (DISSAL), , University of Genoa, ; Genoa, Italy

[6 ]GRID grid.21100.32, ISNI 0000 0004 1936 9430, Laboratory for Industrial and Applied Mathematics (LIAM), Department of Mathematics and Statistics, , York University, ; Toronto, Canada

Article

Publisher ID: 5186

DOI: 10.1186/s12913-020-05186-6

PMC ID: 7168862

PubMed ID: 32306975

SO-VID: 9d11cf3c-1c24-4ce9-82c4-418b6b9c149f

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 13 October 2019

Date accepted : 5 April 2020

Custom metadata

ScienceOpen disciplines: Health & Social care

Keywords: health policy,interrupted time series analysis,health transformation plan,hospitalization rate,iran

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ScienceOpen disciplines: Health & Social care

Keywords: health policy, interrupted time series analysis, health transformation plan, hospitalization rate, iran

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The effect of the Iranian health transformation plan on hospitalization rate: insights from an interrupted time series analysis

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Abstract

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Sushruta Journal of Health Policy & Opinion

Most cited references 30

Interrupted time series regression for the evaluation of public health interventions: a tutorial

Health Sector Evolution Plan in Iran; Equity and Sustainability Concerns.

Health insurance for the poor: impact on catastrophic and out-of-pocket health expenditures in Mexico

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