Résumé

Objectif

Évaluer les effets d'une réforme importante du système de santé sur les taux d'utilisation des hôpitaux – un programme introduisant un médecin de famille et un régime de protection sociale – engagée dans les zones rurales de la République islamique d'Iran en 2005.

Méthodes

Une province «traceur», qui n'était pas un centre d'aiguillage des patients, a été sélectionnée pour recueillir les données mensuelles d'hospitalisation pendant une période d'environ 10 ans; cette collecte a débuté deux ans avant le début de la réforme du système de santé en zone rurale («l'intervention»). Une analyse de la série chronologique interrompue a été menée et une analyse de régression segmentée a été utilisée pour évaluer les effets immédiats et progressifs de l'intervention sur les taux d'hospitalisation dans un groupe d'intervention composé d'habitants des zones rurales et d'un groupe témoin composé principalement d'habitants des zones urbaines.

Résultats

Avant l'intervention, le taux d'hospitalisation dans la population rurale était significativement inférieur à celui du groupe témoin. Bien qu'il n'y ait eu ni d'augmentation ni de baisse significatives des taux d'hospitalisation dans le groupe d'intervention ou le groupe témoin avant l'intervention, une hausse significative du taux d'hospitalisation – de 4,6 hospitalisations pour 100 000 personnes assurées en moyenne par mois – a été observée dans le groupe d'intervention après l'intervention (P < 0,001). L'augmentation mensuelle du taux d'hospitalisation s'est poursuivie pendant plus d'un an, puis elle s'est stabilisée par la suite. Aucune augmentation du taux d'hospitalisation n'a été constatée dans le groupe témoin.

Conclusion

Le programme de soins de santé primaires établi dans le cadre du processus de réforme du système de santé a amélioré l'accès aux soins hospitaliers au sein d'une population qui, auparavant, utilisait insuffisamment les services hospitaliers. Il n'a pas diminué les hospitalisations ou les dépenses liées aux hospitalisations.

Resumen

Objetivo

Evaluar los efectos sobre las tasas de utilización hospitalaria tras una importante reforma del sistema sanitario (un programa de médicos de familia y un esquema de protección social) realizada en las zonas rurales de la República Islámica del Irán en 2005.

Métodos

Se seleccionó una provincia «indicadora», que no era un centro de referencia de pacientes, para recabar los datos mensuales de hospitalización durante un periodo de 10 años aproximadamente, el cual comenzó dos años antes de que empezara la reforma del sistema de salud rural (la «intervención»). Se llevó a cabo el análisis de una serie cronológica interrumpida y se empleó un análisis de regresión segmentada para evaluar los efectos inmediatos y graduales de la intervención en las tasas de hospitalización en un grupo de intervención compuesto por residentes rurales y un grupo de comparación formado principalmente por residentes urbanos.

Resultados

Antes de la intervención, la tasa de hospitalización de la población rural era considerablemente inferior que la del grupo de comparación. Aunque no hubo un aumento o disminución relevante en las tasas de hospitalización del grupo de intervención o de comparación antes de la intervención, se observó un aumento significativo de la tasa de hospitalización en el grupo de intervención tras la misma. En concreto, un aumento medio de 4,6 hospitalizaciones por cada 100 000 personas aseguradas por mes (P < 0,001). El incremento mensual en la tasa de hospitalización continuó durante más de un año y posteriormente se estabilizó. Respecto al grupo de comparación, no se observó aumento alguno en la tasa de hospitalización.

Conclusión

El programa de salud de atención primaria instituido como parte del proceso de reforma del sistema sanitario ha aumentado el acceso a la atención hospitalaria en una población que anteriormente no utilizaba los servicios hospitalarios de forma suficiente. Por otro lado, no ha reducido las hospitalizaciones ni los gastos relacionados con las mismas.

ملخص

الغرض

تقييم تأثيرات إصلاح رئيسي للنظام الصحي على معدلات استخدام المستشفيات – برنامج طبيب الأسرة ومخطط الحماية الاجتماعية - الذي تم تنفيذه في المناطق الريفية في جمهورية إيران الإسلامية في عام 2005.

الطريقة

تم اختيار مقاطعة "اقتفاء الأثر" التي لم تكن مركزاً لإحالة المرضى من أجل جمع البيانات الشهرية للإدخال إلى المستشفيات على مدار فترة 10 سنوات تقريباً، بدأت قبل عامين من بدء إصلاح النظام الصحي الريفي ("التدخل"). وتم إجراء تحليل سلسلة زمنية متقطعة، وتم استخدام تحليل ارتداد مقسم لتقييم التأثيرات الفورية والتدريجية للتدخل على معدلات الإدخال إلى المستشفيات في مجموعة تدخل مكونة من سكان المناطق الريفية ومجموعة مقارنة مكونة من سكان المناطق الحضرية بالدرجة الأولى.

النتائج

كان معدل الإدخال إلى المستشفيات بين سكان المناطق الريفية، قبل التدخل، أقل على نحو كبير عنه في مجموعة المقارنة. وعلى الرغم من عدم وجود ازدياد أو انخفاض كبير في معدلات الإدخال إلى المستشفيات في مجموعة التدخل أو المقارنة قبل التدخل، إلا أنه لوحظ بعد التدخل وجود ازدياد كبير في معدل الإدخال إلى المستشفيات – 4.6 إدخال إلى المستشفيات لكل 100000 شخص مؤمن عليه لكل شهر في المتوسط - في مجموعة التدخل (الاحتمال < 0.001). واستمر الازدياد الشهري في معدل الإدخال إلى المستشفيات لأكثر من سنة واستقر بعدها. ولم يتم ملاحظة أي ازدياد في معدل الإدخال إلى المستشفيات في مجموعة المقارنة.

الاستنتاج

أدى برنامج الرعاية الصحية الأولية الذي تم تأسيسه كجزء من عملية إصلاح النظام الصحي إلى زيادة إتاحة رعاية المستشفيات في فئة سكانية كانت تستخدم في السابق خدمات المستشفيات على نحو قليل. ولم يؤدِ إلى تقليل مرات الإدخال إلى المستشفيات أو الإنفاق المتصل بالإدخال إلى المستشفيات.

摘要

目的

评估2005 年在伊朗伊斯兰共和国农村地区实施的主要卫生系统改革(家庭医生计划和社会保护方案)对住院率的影响。

方法

选择一个非病人转诊中心的“示踪”省份,收集大约10 年的每月住院数据,该期间从农村卫生系统改革(“干预”)开始之前的两年算起。执行中断时间序列分析,使用分段回归分析,评估在由农村居民组成的干预组和主要由城市居民组成的对照组当中此干预对住院率的即时和渐进的影响。

结果

在干预之前,农村人口的住院率显著低于对照组。尽管在干预之前,干预组或对照组中住院率没有显著的提高或下降,但在干预之后,干预组的住院率显著增加——平均每月每十万名受保人4.6 例住院(P < 0.001)。在超过一年时间内,住院率每月提高,之后趋于稳定。对照组中没有看到住院率有所提高。

结论

作为卫生体制改革过程的组成部分所制定的初级卫生保健计划,在之前未充分利用医院服务的人群中,提升了使用医院护理的可及性。这没有减少住院或住院相关的支出。

Резюме

Цель

Оценить влияние крупной реформы здравоохранения (программа семейных врачей и схема социальной защиты), проведенной в сельских областях Исламской Республики Иран в 2005 году, на уровни использования услуг больниц.

Методы

Для целей сбора ежемесячных данных о госпитализации в течение примерно 10-летнего периода, начавшегося за два года до осуществления реформы системы здравоохранения в сельской местности («вмешательства»), была выбрана «индикативная» провинция, которая не была центром направления пациентов. Были проведены анализы прерванных временных рядов, а сегментированный регрессионный анализ был использован для оценки непосредственного и постепенного влияния вмешательства на уровни госпитализации в группе вмешательства, включающей сельских жителей, и группы сравнения, состоящей преимущественно из городских жителей.

Результаты

До вмешательства уровень госпитализации сельского населения был значительно ниже, чем аналогичный уровень в группе сравнения. Хотя до вмешательства отсутствовало какое-либо существенное увеличение или снижение уровней госпитализации в группе вмешательства или группе сравнения, после вмешательства было отмечено значительное увеличение частоты госпитализаций в группе вмешательства (P <0,001) — на 4,6 госпитализаций на 100 000 застрахованных лиц в среднем за месяц. Ежемесячный рост уровня госпитализаций продолжался более года, а затем стабилизировался. В группе сравнения увеличение уровня госпитализаций не наблюдалось.

Вывод

Программа первичной медико-санитарной помощи, внедренная в рамках процесса реформирования системы здравоохранения, повысила уровень доступности стационарной медицинской помощи для той части населения, которая ранее в недостаточной мере пользовалось услугами больниц. Она не привела к сокращению числа госпитализаций или расходов на госпитализацию.

Introduction

According to the World Health Organization (WHO), the purpose behind universal health coverage (UHC) is to ensure for all people, whether rich or poor, access to effective health services that meet most of their needs without being exposed to the risk of financial hadrship.¹1 The world health report – health systems financing: the path to universal coverage. Geneva: World Health Organization; 2010. Available from: http://www.who.int/whr/2010/en/ [accessed 3 September 2013].
http://www.who.int/whr/2010/en/... ^,22 Carrin G, James C, Evans DB. Achieving universal health coverage: developing the health financing system. Geneva: World Health Organization; 2005. Available from: http://www.who.int/health_financing/documents/cov-pb_e_05_1-universal_cov/en/index.html [accessed 3 September 2013].
http://www.who.int/health_financing/docu... In most low- and middle-income countries, these conditions are not met and the effective health services that are available are not accessible to the entire population.¹1 The world health report – health systems financing: the path to universal coverage. Geneva: World Health Organization; 2010. Available from: http://www.who.int/whr/2010/en/ [accessed 3 September 2013].
http://www.who.int/whr/2010/en/... ^,33 The world health report 2008: primary health care – now more than ever. Geneva: World Health Organization; 2008. Available from: http://www.who.int/whr/2008/en/ [accessed 3 September 2013].
http://www.who.int/whr/2008/en/...

An important prerequisite for UHC is the adequate provision of health services, which depends on factors such as the availability of physicians and hospital beds to meet demand. By adequate service provision we mean the existence of a sufficient number of services of acceptable quality distributed in a manner that allows the population's health-care needs to be fulfilled. People who lack health insurance coverage or another form of financial protection find it very difficult to access health services, especially inpatient care,⁴4 Saksena P, Antunes AF, Xu K, Musango L, Carrin G. Mutual health insurance in Rwanda: evidence on access to care and financial risk protection. Health Policy 2011;99:203–9. doi: http://dx.doi.org/10.1016/j.healthpol.2010.09.009 PMID:20965602
https://doi.org/10.1016/j.healthpol.2010... ^–66 Sepehri A, Simpson W, Sarma S. The influence of health insurance on hospital admission and length of stay – the case of Vietnam. Soc Sci Med 2006;63:1757–70. doi: http://dx.doi.org/10.1016/j.socscimed.2006.04.029 PMID:16766108
https://doi.org/10.1016/j.socscimed.2006... or delay in doing so. This is commonly referred to as the “uninsured access gap”.⁷7 Kataoka SH, Zhang L, Wells KB. Unmet need for mental health care among U.S. children: variation by ethnicity and insurance status. Am J Psychiatry 2002;159:1548–55. doi: http://dx.doi.org/10.1176/appi.ajp.159.9.1548 PMID:12202276
https://doi.org/10.1176/appi.ajp.159.9.1... ^–1111 Cunningham PJ, Hadley J. Differences between symptom-specific and general survey questions of unmet need in measuring insurance and racial/ethnic disparities in access to care. Med Care 2007;45:842–50. doi: http://dx.doi.org/10.1097/MLR.0b013e318053678f PMID:17712254
https://doi.org/10.1097/MLR.0b013e318053... When not enough services are covered under a protection plan or when the financial protection for those services that are “covered” is insufficient, households can be deprived of essential health care or face catastrophic costs.¹²12 Kavosi Z, Rashidian A, Pourreza A, Majdzadeh R, Pourmalek F, Hosseinpour AR et al. Inequality in household catastrophic health care expenditure in a low-income society of Iran. Health Policy Plan 2012;27:1–7. doi: http://dx.doi.org/10.1093/heapol/czs001 PMID:21324972
https://doi.org/10.1093/heapol/czs001... Delayed care can also lead to hospitalizations that could have been avoided with timely treatment.²2 Carrin G, James C, Evans DB. Achieving universal health coverage: developing the health financing system. Geneva: World Health Organization; 2005. Available from: http://www.who.int/health_financing/documents/cov-pb_e_05_1-universal_cov/en/index.html [accessed 3 September 2013].
http://www.who.int/health_financing/docu... ^,99 Cummings JR, Lavarreda SA, Rice T, Brown ER. The effects of varying periods of uninsurance on children’s access to health care. Pediatrics 2009;123:e411–8. doi: http://dx.doi.org/10.1542/peds.2008-1874 PMID:19254977
https://doi.org/10.1542/peds.2008-1874... ^,1313 Weissman JS, Gatsonis C, Epstein AM. Rates of avoidable hospitalization by insurance status in Massachusetts and Maryland. JAMA 1992;268:2388–94. doi: http://dx.doi.org/10.1001/jama.1992.03490170060026 PMID:1404795
https://doi.org/10.1001/jama.1992.034901...

Poor access to health care and underutilization of health-care services are problems that may be remedied by expanding primary care and social protection schemes through measures such as social insurance or publicly-funded health care.¹1 The world health report – health systems financing: the path to universal coverage. Geneva: World Health Organization; 2010. Available from: http://www.who.int/whr/2010/en/ [accessed 3 September 2013].
http://www.who.int/whr/2010/en/... ^,33 The world health report 2008: primary health care – now more than ever. Geneva: World Health Organization; 2008. Available from: http://www.who.int/whr/2008/en/ [accessed 3 September 2013].
http://www.who.int/whr/2008/en/... However, social protection schemes have a mixed effect on hospital utilization – in theory at least.¹⁴14 Dafny L, Gruber J. Public insurance and child hospitalizations: access and efficiency effects. J Public Econ 2005;89:109–29. doi: http://dx.doi.org/10.1016/j.jpubeco.2003.05.004
https://doi.org/10.1016/j.jpubeco.2003.0... By increasing the use of effective outpatient primary care services, improvements in social protection could reduce hospitalizations that are potentially avoidable – i.e. “primary-care-sensitive” hospitalizations – in what is known as an “efficiency effect”. At the same time, people with better social protection are more likely to be hospitalized when they need to be. This would lead to an increase in “referral-sensitive” hospitalizations in what is termed the “access effect”.¹⁴14 Dafny L, Gruber J. Public insurance and child hospitalizations: access and efficiency effects. J Public Econ 2005;89:109–29. doi: http://dx.doi.org/10.1016/j.jpubeco.2003.05.004
https://doi.org/10.1016/j.jpubeco.2003.0... ^,1515 Gusmano MK, Rodwin VG, Weisz D. A new way to compare health systems: avoidable hospital conditions in Manhattan and Paris. Health Aff (Millwood) 2006;25:510–20. doi: http://dx.doi.org/10.1377/hlthaff.25.2.510 PMID:16522605
https://doi.org/10.1377/hlthaff.25.2.510... The efficiency and access effects of social protection materialize only if health service provision is adequate.

Health-care financing and delivery in rural parts of the Islamic Republic of Iran

Since the mid-1980s, the Islamic Republic of Iran has enjoyed an extensive network of publicly funded primary health-care (PHC) services in rural areas.¹⁶16 Kruk ME, Porignon D, Rockers PC, Van Lerberghe W. The contribution of primary care to health and health systems in low- and middle-income countries: a critical review of major primary care initiatives. Soc Sci Med 2010;70:904–11. doi: http://dx.doi.org/10.1016/j.socscimed.2009.11.025 PMID:20089341
https://doi.org/10.1016/j.socscimed.2009... The network has relied primarily on community health workers (behvarz) as first-line service providers. The behvarz are selected from the locality where they live, receive training for two years and provide basic services at a “health house”. A health house is a part of the district PHC network. It is staffed by one or two behvarz who serve a population of about 1500 on average. A health house offers primary services to mothers and children, including vaccinations, prenatal and postnatal care, growth monitoring, family planning, management of common infectious and chronic conditions, and environmental health services. PHC physicians are based in rural health centres and manage the patients referred to them by the behvarz. The PHC network is well organized and is credited with the improvements in health outcomes that have been observed since the 1980s in rural areas.³3 The world health report 2008: primary health care – now more than ever. Geneva: World Health Organization; 2008. Available from: http://www.who.int/whr/2008/en/ [accessed 3 September 2013].
http://www.who.int/whr/2008/en/... ^,1717 Islamic Republic of Iran: health sector review. Washington: The World Bank Group Human Development Sector, Middle East and North Africa; 2007 (Report No: 39970). Available from: http://www.worldbank.org/en/topic/health/research/all?docty_exact=Health+Sector+Review&qterm=&lang_exact=English&count_exact=Iran%2C+Islamic+Republic+of [accessed 3 September 2013].
http://www.worldbank.org/en/topic/health... ^,1818 Takian A, Rashidian A, Kabir MJ. Expediency and coincidence in re-engineering a health system: an interpretive approach to formation of family medicine in Iran. Health Policy Plan 2011;26:163–73. doi: http://dx.doi.org/10.1093/heapol/czq036 PMID:20732859
https://doi.org/10.1093/heapol/czq036...

Secondary care services for the Islamic Republic of Iran's rural population have been less easily accessible. Unlike PHC, which is almost entirely financed by the central government, outpatient care is not free and is delivered mostly by private sector professionals in urban areas. Such care includes, for example, visits to non-PHC physicians, specialist visits, laboratory and radiology services and medicines dispensed at private pharmacies. Access to hospital care for rural residents has been hindered by financial and organizational factors and by the lack of a fully implemented referral system.¹⁷17 Islamic Republic of Iran: health sector review. Washington: The World Bank Group Human Development Sector, Middle East and North Africa; 2007 (Report No: 39970). Available from: http://www.worldbank.org/en/topic/health/research/all?docty_exact=Health+Sector+Review&qterm=&lang_exact=English&count_exact=Iran%2C+Islamic+Republic+of [accessed 3 September 2013].
http://www.worldbank.org/en/topic/health... Uninsured rural households used a “rural insurance card” that covered 90% of hospital costs, but only upon referral by a PHC service. The card, which was issued free of charge by the Medical Services Insurance Organization (MSIO), did not cover any outpatient care, apart from the PHC services which were covered by the government funding.

In recent years, concerns have arisen about the PHC's ability to respond to the needs of the population in light of changing epidemiologic trends, such as the increase in chronic diseases.¹⁹19 Takian AH, Doshmangir L, Rashidian A. Implementing family physician programme in rural Iran: exploring the role of an existing primary health care network. Fam Pract 2013;30:551–9. doi: http://dx.doi.org/10.1093/fampra/cmt025 PMID:23788202
https://doi.org/10.1093/fampra/cmt025... To respond to these changes, in 2005 the Islamic Republic of Iran's parliament approved a reform that substantially increased the national budget for rural health care.¹⁸18 Takian A, Rashidian A, Kabir MJ. Expediency and coincidence in re-engineering a health system: an interpretive approach to formation of family medicine in Iran. Health Policy Plan 2011;26:163–73. doi: http://dx.doi.org/10.1093/heapol/czq036 PMID:20732859
https://doi.org/10.1093/heapol/czq036... The reform covered all villages and towns with populations of up to 20 000 and had two main elements: a family physician programme and a social protection scheme for rural inhabitants (known as “rural insurance”).¹⁸18 Takian A, Rashidian A, Kabir MJ. Expediency and coincidence in re-engineering a health system: an interpretive approach to formation of family medicine in Iran. Health Policy Plan 2011;26:163–73. doi: http://dx.doi.org/10.1093/heapol/czq036 PMID:20732859
https://doi.org/10.1093/heapol/czq036... About 6000 physicians and 400 midwives were added to the PHC network in a span of three years as part of the reform.

Since the health system reform process was intended to improve access to more comprehensive preventive and outpatient care, policy-makers expected it to result in a decrease in hospitalizations. Our objective was to assess the immediate and long-term effect of the reform (henceforth referred to as “the intervention”) on hospitalization rates among rural residents, which were the target population.

Methods

Study design

The intervention was implemented in June 2005. We conducted an interrupted time series study and analysed: (i) monthly hospitalization rates starting two years before the intervention (2003–2007) to assess its immediate effects; and (ii) monthly hospitalization rates up to September 2012 to assess its long-term effects. An interrupted time series study does not require a concurrent “control group” to establish a causal link between an intervention and an outcome.²⁰20 Cook TD, Campbell DT. Quasi-experimentation: design and analysis issues for field settings. Boston: Houghton Mifflin; 1979. However, the use of a comparison group can result in a better understanding of the effects of the intervention on the intervention group.²¹21 Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299–309. doi: http://dx.doi.org/10.1046/j.1365-2710.2002.00430.x PMID:12174032
https://doi.org/10.1046/j.1365-2710.2002... For this reason, we used a concurrent series of monthly hospitalization rates for a non-equivalent “comparison group” consisting of primarily urban civil servants and their dependants, who were the target population of another insurance fund also managed by the MSIO.

Setting

We hypothesized that the intervention would affect hospitalization rates more strongly in areas where households were poor and hence more likely to benefit from the intervention than affluent households. We also needed to select a province that was not a patient referral hub for other provinces. Lorestan, a province in the western part of the Islamic Republic of Iran, met these criteria (Table 1).

The intervention

The purpose of the intervention was to improve rural households' access to outpatient and hospital care.¹⁹19 Takian AH, Doshmangir L, Rashidian A. Implementing family physician programme in rural Iran: exploring the role of an existing primary health care network. Fam Pract 2013;30:551–9. doi: http://dx.doi.org/10.1093/fampra/cmt025 PMID:23788202
https://doi.org/10.1093/fampra/cmt025... ^,2323 National Unit for PHC Expansion and Health Promotion. The operational instructions for family medicine and behvarz. 8th ed. Tehran: Ministry of Health and Medical Education; 2007. Persian. All households in villages and small towns were eligible to join the social protection scheme by paying a nominal fee – approximately 0.25 United States dollars – that covered the printing costs of the “insurance” booklet. There was no additional cost for remaining in the scheme. Since most rural household members were employed in the informal sector, the majority of rural households joined the scheme. According to data for the province, 92% coverage had been attained within two years.

The intervention improved access to health care at two levels. First, better pay drew more family physicians and midwives to PHC centres. Between 2004 and 2005 the number of PHC physicians in the province increased from 124 to 191.²⁴24 Center for PHC Network Development and Health Promotion. Report on the family physician and rural insurance program operational conduct. Tehran: Ministry of Health and Medical Education; 2007. Of the new physicians, many came from the private sector, which they were required to leave to work as a PHC family physician. Others were new graduates or physicians who had previously held managerial posts in the PHC system. Second, households were given access to outpatient services – visits to specialists, radiology services, laboratory and pharmacy services – and to hospital care (located primarily in cities) at a reduced cost. This was facilitated by possession of the “insurance booklet”, signed by the referring family physician. Patients referred by a family physician were expected to pay 10% of inpatient costs and 30% of outpatient costs out of pocket; self-referred patients had no financial coverage.

Data sources

We obtained population data from the Statistics Centre of the Islamic Republic of Iran and social protection coverage and monthly hospitalization data from MSIO records.

The inpatient services provided by the Imam Khomeini Relief Foundation for poor rural households, which existed before the intervention, could have exerted a confounding effect on our results. However, the Relief Fund had ceased to function within two years of the intervention. We obtained from the Relief Fund its monthly hospitalization claims for rural households for the study period – there were none from 2008 onwards – and included them when calculating the number of hospitalizations. We asked experienced officers to check the data for accuracy. We engaged three physicians and PHC managers in the province to verify the accuracy of all dates and activities.

Sample size and data analysis

We modelled data using segmented regressions to assess causal links between the intervention and the outcome of interest.²⁰20 Cook TD, Campbell DT. Quasi-experimentation: design and analysis issues for field settings. Boston: Houghton Mifflin; 1979.^,2121 Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299–309. doi: http://dx.doi.org/10.1046/j.1365-2710.2002.00430.x PMID:12174032
https://doi.org/10.1046/j.1365-2710.2002... It takes at least 48 observations in a segmented regression analysis to be able to assess seasonality in the data.²¹21 Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299–309. doi: http://dx.doi.org/10.1046/j.1365-2710.2002.00430.x PMID:12174032
https://doi.org/10.1046/j.1365-2710.2002... ^,2525 Time series analysis. In: Pharmacoepidemiology: behavioural and cultural themes. Newcastle: Center for Clinical Epidemiology and Biostatistics; 2001. Our sample included 60 observations (i.e. one per month) – 27 before and 33 after the intervention – to assess the intervention's immediate effects, and a longer time series – 114 observations – to assess its long-term effects.

To eliminate the effects of population growth, we defined each observation as the number of hospitalizations per month divided by the population under coverage during the year (i.e. the hospitalization rates) (Table 2). We looked for abrupt drops or increases in the hospitalization rate and for gradual changes in trends at the interruption times.

We analysed data for the comparison group for the entire study period except for about two years after 2008. This is because during the latter period the MSIO's civil servant fund transferred the care of the elderly population to another insurer and this altered the demographic profile of the population under its coverage.

We conducted several diagnostic assessments. The Durbin-Watson test suggested the existence of autocorrelations, which we corrected using the Cochrane-Orcutt method.²⁶26 Kutner MH, Nachtsheim CJ, Neter J. Applied linear regression models. 4th ed. Chicago: Irwin/McGraw-Hill; 2004. We estimated the Kolmogorov–Smirnov statistic to check the normality of the residuals and saw that a power transformation correction was required for the analysis of long-term effects. We estimated the Dicky-Fuller statistic to determine if the series was stationary and the Breusch-Pagan statistic to check for heteroscedasticity in the residuals. The results suggested a normal residual distribution and a lack of seasonality and heteroscedasticity.²⁶26 Kutner MH, Nachtsheim CJ, Neter J. Applied linear regression models. 4th ed. Chicago: Irwin/McGraw-Hill; 2004.

The first “interruption” time was set at June 2005, when the intervention was first implemented. To identify the next interruption point, we used segmented regressions with multiple time periods for each point and monitored the time series to find the first point showing a significant change in the trend (Appendix A, available at: https://docs.google.com/file/d/0B32jQZp_KmJzeHFmRUhwRU5ySGs/edit?usp=sharing). All analyses were conducted using R statistical software version 2.12.1 (The R Foundation for Statistical Computing, Vienna, Austria).

Results

Over 700 000 inhabitants of rural areas, including small towns, were covered by the intervention, and about 150 000 urban inhabitants were covered by the MSIO fund for civil servants (Table 2). From 2003 to 2007, the annual hospitalization rate in the population covered by the intervention increased from 44.3 to 65.6 per 1000 inhabitants. The corresponding rates in the population covered by the MSIO's fund for civil servants were 92.7 in 2003 and 95.7 in 2007. In 2011, the annual hospitalization rate for the intervention group and the comparison group was 62.5 and 78.8 per 1000 inhabitants, respectively.

Immediate effect on hospitalization rate

No significant increase or decline in the hospitalization rate was noted in either the intervention or the comparison group before the intervention. The pre-intervention rates remained stable in both groups (Table 3) even though the baseline monthly hospitalization rate per 1000 inhabitants was markedly lower in the intervention group than in the comparison group.

We looked for changes in slope and intercept in the comparison group to check for confounding factors unrelated to the intervention – e.g. disease epidemics, data recording policies at the MSIO – that might have occurred at the same time as the intervention and biased the findings. We observed no significant changes in slope or intercept in the hospitalization rate of the comparison group after the intervention (P > 0.4). However, we did note a significant change in the regression slope (P < 0.001) in the intervention group right after the intervention started (Table 3). This finding suggests that the intervention resulted in a greater likelihood that people would use hospital services (Fig. 1). To develop the model for the hospitalization rate in the intervention group, we transformed the model back to its original coefficients (after correcting for autocorrelation; Y_t − ρY_t-1). Hence, for Model 1:

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Fig. 1

Segmented regression model showing hospitalization rates over the short-term in the intervention group, April 2003 to March 2008

where Y is the hospitalization rate, ρ is the autocorrelation parameter and equals 0.125516; T is pre-intervention slope; P is the change in slope and D is the change in intercept.

According to Model 1, the hospitalization rate in the intervention group increased, on average, by about 4.6 hospitalizations per 100 000 insured people per month. Fig. 1 shows that before the intervention the slope was close to zero but showed a much steeper forward incline after the intervention. Segmented regression analysis conducted in both groups revealed that the post-intervention slopes in the intervention group and the comparison group differed statistically (P = 0.004). After the intervention, the intervention group had about 7 monthly hospitalizations more per 100 000 insured people than the comparison group (Appendix B, available at: https://docs.google.com/file/d/0B32jQZp_KmJzN3YtWWp1cXRLbWc/edit?usp=sharing).

Long-term effect on hospitalization rate

In the intervention group we observed a second statistically significant “interruption” point in the trend in hospitalization rate 40 months after the start of the intervention (Fig. 2). At that point the upward trend in the hospitalization declined significantly and returning to the modest upward trend that had existed before the intervention started (P < 0.001). The slopes before the intervention and after the second interruption point were not statistically different (P = 0.75) (Appendix C, available at: https://docs.google.com/file/d/0B32jQZp_KmJzWUdjS1pGcGpNNzA/edit?usp=sharing). As a result, the long-term effect of the intervention can be described as an abrupt increase in the hospitalization rate lasting more than one year, followed by a secular upward trend that was comparable to the trend that had existed before the intervention (Fig. 2). Analysis of the comparison group over the long term showed an unexplained significant reduction in the hospitalization rate – seen as a change in the intercept – after 2009 (P < 0.001).

Discussion

A family physician programme and a social protection scheme for rural inhabitants in the Islamic Republic of Iran resulted in a modest and statistically significant increase in the hospitalization rate. The upward trend in the rate remained relatively constant for about one year and then began to decline, perhaps under the influence of external factors not observed by our study, since we also noted a reduction in the hospitalization rate in the comparison group at about the same time.

The intervention increased the utilization of hospital beds in a population that had historically underutilized hospital services. This suggests that the “access effect” of the intervention outweighed its potential “efficiency effect”. It appears, therefore, that while family physicians provided rural inhabitants with a “point of referral” to specialists, the social protection scheme increased their actual use of specialists, and, ultimately, of hospital services.

Our results differ from those of previous studies that claim that expanding primary care services – or access to such services – would result in a decrease in the hospitalization rate by reducing primary-care-sensitive hospitalizations.¹⁴14 Dafny L, Gruber J. Public insurance and child hospitalizations: access and efficiency effects. J Public Econ 2005;89:109–29. doi: http://dx.doi.org/10.1016/j.jpubeco.2003.05.004
https://doi.org/10.1016/j.jpubeco.2003.0... ^,2727 Parchman ML, Culler S. Primary care physicians and avoidable hospitalizations. J Fam Pract 1994;39:123–8. PMID:8057062^–3232 Guanais F, Macinko J. Primary care and avoidable hospitalizations: evidence from Brazil. J Ambul Care Manage 2009;32:115–22. doi: http://dx.doi.org/10.1097/JAC.0b013e31819942e51 PMID:19305223
https://doi.org/10.1097/JAC.0b013e318199... All such studies but one³²32 Guanais F, Macinko J. Primary care and avoidable hospitalizations: evidence from Brazil. J Ambul Care Manage 2009;32:115–22. doi: http://dx.doi.org/10.1097/JAC.0b013e31819942e51 PMID:19305223
https://doi.org/10.1097/JAC.0b013e318199... were conducted in high-income countries with high baseline access to inpatient hospital services and have one major limitation: they focused exclusively on primary-care-sensitive avoidable hospitalizations. Only Friedman & Basu (2001) measured total hospitalizations and observed a reduction in all hospitalizations among children in the state of New York, United States of America.³¹31 Friedman B, Basu J. Health insurance, primary care, and preventable hospitalization of children in a large state. Am J Manag Care 2001;7:473–81. PMID:11388127

Other studies have led to conclusions similar to those derived from ours. In a study in Canada, improving access to primary care resulted in a reduction in primary-care-sensitive hospitalizations among the elderly but did not change total hospitalization rates.³³33 Menec VH, Sirski M, Attawar D, Katz A. Does continuity of care with a family physician reduce hospitalizations among older adults? J Health Serv Res Policy 2006;11:196–201. doi: http://dx.doi.org/10.1258/135581906778476562 PMID:17018192
https://doi.org/10.1258/1355819067784765... In Ireland, Nolan et al. (2011) observed no changes in avoidable hospitalizations as a result of improved access to primary care.³⁴34 Nolan A. An extension in eligibility for free primary care and avoidable hospitalisations: a natural experiment. Soc Sci Med 2011;73:978–85. doi: http://dx.doi.org/10.1016/j.socscimed.2011.06.057 PMID:21831496
https://doi.org/10.1016/j.socscimed.2011... A study conducted in the United States revealed that reductions in the hospitalization rate were not linked to the use of primary care services.³⁵35 Ricketts TC, Randolph R, Howard HA, Pathman D, Carey T. Hospitalization rates as indicators of access to primary care. Health Place 2001;7:27–38. doi: http://dx.doi.org/10.1016/S1353-8292(00)00035-6 PMID:11165153
https://doi.org/10.1016/S1353-8292(00)00...

Saha et al. (2007) had hypothesized, like we did, that improving access to primary care – by expanding the Medicaid programme in the state of Oregon in the United States to cover an additional 100 000 low-income families – would result in fewer hospitalizations. Instead, they observed an increase in the hospitalization rate.³⁶36 Saha S, Solotaroff R, Oster A, Bindman AB. Are preventable hospitalizations sensitive to changes in access to primary care? The case of the Oregon Health Plan. Med Care 2007;45:712–9. doi: http://dx.doi.org/10.1097/MLR.0b013e318053717c PMID:17667304
https://doi.org/10.1097/MLR.0b013e318053... In their study, the baseline hospitalization rate in the intervention group was lower than in the rest of the population. In ours, the hospitalization rate at baseline was also substantially lower in the rural than in the urban population. These findings suggest that the increase in the hospitalization rate that we observed in the rural population reflects a pre-existing unmet need for hospitalizations. We would expect the increase to have occurred in referral-sensitive hospitalizations,³⁷37 Shah BR, Gunraj N, Hux JE. Markers of access to and quality of primary care for aboriginal people in Ontario, Canada. Am J Public Health 2003;93:798–802. doi: http://dx.doi.org/10.2105/AJPH.93.5.798 PMID:12721147
https://doi.org/10.2105/AJPH.93.5.798... although this should be the focus of future studies.

Our study has important methodological strengths. We took advantage of the opportunity to perform a natural experiment and used robust research methods.¹⁹19 Takian AH, Doshmangir L, Rashidian A. Implementing family physician programme in rural Iran: exploring the role of an existing primary health care network. Fam Pract 2013;30:551–9. doi: http://dx.doi.org/10.1093/fampra/cmt025 PMID:23788202
https://doi.org/10.1093/fampra/cmt025... ^,2121 Wagner AK, Soumerai SB, Zhang F, Ross-Degnan D. Segmented regression analysis of interrupted time series studies in medication use research. J Clin Pharm Ther 2002;27:299–309. doi: http://dx.doi.org/10.1046/j.1365-2710.2002.00430.x PMID:12174032
https://doi.org/10.1046/j.1365-2710.2002... We made certain that all statistical assumptions were met. We also looked for potential confounding influences during the intervention period that might have biased the results and found none. The study involved a relatively large number of observations (months) that resulted in enough power to test the hypothesis and obtain significant results at the desired confidence level.

The study also has important limitations. It was conducted in only one province, whereas ideally it should have been conducted in a nationally representative sample. On the other hand, by focusing on a single province we were able to better monitor data quality and contextual factors that could have influenced hospitalizations in the intervention group. We lacked data on hospitalization length and causes of admission. Future studies should explore whether hospitalization patterns changed after the rural health system reform.

Our study has important policy implications. If the hospitalization rate in the intervention group had continued to increase for over one year after the intervention as a response to unmet needs, it should have continued to rise until the unmet need was satisfied – i.e. until it had reached a level similar to that in the comparison group. However, the hospitalization rate in the intervention group did not reach the level observed in the comparison group. This is difficult to explain because the two groups were not comparable in terms of demographic or access characteristics. The comparison group was predominantly composed of more affluent urban residents with better geographical access to specialist and hospital care than the intervention group.

To conclude, programmes that focus on improving access to primary care do not necessarily lead to reduced hospitalization rates and hence to lower hospitalization-related expenditures. Improved accessibility offsets potential efficiency gains from the intervention, especially in societies with an unmet need for hospitalization.

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References

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