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A Systematic Review and Content-Analysis of Service Quality Indicators Provided to Patients with Cardiovascular Disease Using Donabedian Model

Saber Azami-Aghdash, Morteza Ghojazadeh, Mozhgan Fardid, Mir Hossein Aghaei, Reza Nikanfar, Mohammad Mohseni

Saber Azami-Aghdash, Iranian Center of Excellence in Health Management, Tabriz University of Medical Sciences, Tabriz, Iran
Morteza Ghojazadeh, Cardiovascular Research Center, Associate Professor of physiology, Liver and Gastrointestinal Disease Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Mozhgan Fardid, Health management and economics research center, Iran University of medical sciences, Tehran, Iran
Mir Hossein Aghaei, Reza Nikanfar, Student Research commute, Tabriz University of Medical Sciences, Tabriz, Iran
Mohammad Mohseni, Research Center for Social Determinants of Health, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

Correspondence to: Morteza Ghojazadeh, Associate Professor of physiology, Liver & Gastrointestinal Disease Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Email: as4007@yahoo.com
Telephone: +989141144007
Received: September 26, 2014
Revised: December 2, 2014
Accepted: December 5, 2014
Published online: December 10, 2014

ABSTRACT

AIM: There is a large gap between healthcare quality provided to patients with cardiovascular disease and appropriate standards in this field. The aim of this study was to systematic review and content analysis of service quality indicators provided to patients with cardiovascular disease using Donabedian model.

METHODS: We conducted a systematic review and Content-Analysis of service quality indicators provided to patients with cardiovascular disease using Donabedian model. Manual search, reference of references and gray literature were employed in this study as well as different database searching methods using the search words like “quality”, “Cardiovascular diseases”,“ indicator*”,“Cardiac care” and“ heart diseases”) in the following databases: Iranmedex, Science Direct, Google Scholar, Ovid Medline, Ovid Embase, Cochrane Library, PubMed, Magiran and SID. After identifying and extracting service indicators from the cardiovascular literature, we utilized content analysis approach. Then the indicators were analyzed and categorized Donabedian Model.

RESULTS: Out of 2,342 articles, 15 articles met the inclusion criteria and entered study consisting of 463 indicators. Collected indicators divided into 7 categories and the most frequent indicators were belonged to MI and AMI category by 215 frequent. The extracted indicators were broken down into input, process and output categories using of Donabedian model and then each of these categories were again divided to hospital interior and hospital exterior indicators. Most indicator formulation methods which were applied in prior studies were included literature review (8 studies), Delphi method (7 studies) and expert panel (6 studies).

CONCLUSION: In this study, service quality indicators provided to patients with cardiovascular disease were systematically collected and categorized using Donabedian model to introduce the formulation methods for these indicators. Thus these results can be beneficial to health policy makers and managers in planning, providing, measurement and promotion of services provided to patients with cardiovascular disease by.

Key words: Indicator; Healthcare Quality; Cardiovascular diseases; Systematic review; Content-Analysis; Donabedian Model

© 2014 The Authors. Published by ACT Group Ltd.

Azami-Aghdash S, Ghojazadeh M, Fardid M, Aghaei MH, Nikanfar R, Mohseni M. A Systematic Review and Content-Analysis of Service Quality Indicators Provided to Patients with Cardiovascular Disease Using Donabedian Model. Journal of Cardiology and Therapy 2014; 1(9): 228-242 Available from: URL: http://www.ghrnet.org/index.php/jct/article/view/947

INTRODUCTION

Cardio-Vascular Diseases (CVD) are the main causes of morbidity and mortality in many High Income Countries (HICs) and Low and Meddle Income Countries (LMICs). Despite the availability of novel advanced treatments and complex interventional and surgical methods, the fatality rate from these diseases is still too high[1-4]. In spite of much attention to CVD during past years, evidences reveal that services provided to such patients is yet poor quality and too far from ideal standards[5-7].

Recently, different methods have been utilized for promoting service quality[8,9] and the most important of which is measurement and promotion of service quality by using the indicators of provided service quality[10-13]. Nowadays measurement of indicators of service quality provided to patients is widely used in different countries for their health system[14]. The first effort of indicator formulation was made in United Stated (US) when Research And Development (RAND) Corporation, college of Heart and America Heart Association (AHAC) Committed to formulate measurement indicators of service quality provided to patients with cardiovascular disease[10]. Project of care quality improvement for CVD and Joint Commission on Accreditation of Healthcare Organizations (JCAHO) subsequently started to formulate the indicators of quality assessment and to measure them for the first hand data which was existed[15].

Considering the variety of prior studies on CVD, we need a proper given framework to use their findings. Therefore, the aim of this study was to systematic review and content analysis of service quality indicators provided to patients with cardiovascular disease using Donabedian model.

Methods

In this systematic review and Content-Analysis study the required data for systematic review was collected by searching Iranmedex, Science Direct, Google Scholar, Ovid Medline, Ovid Embase, Cochrane Library, PubMed, Magiran and SID. The following keywords were used to identify eligible studies: quality indicator, cardiovascular diseases, cardiac care and heart diseases.

Besides manual search, checking reference lists (reference of references) and grey literature were applied in the current study. After identifying and extracting service indicators from the cardiovascular literature, we utilized content analysis approach. Then the indicators were analyzed and categorized using Donabedian Model. A topic expert as well as an experienced librarian helped us to design PubMed search strategy as follows. This search strategy was edited in different steps of searching according to the characteristics of various data bases.

{[(quality indicator*) AND Cardiovascular diseases) OR Cardia* care} OR heart diseases.

There was no time limitation for paper searching and this search included published articles in the English and the Persian.

The following inclusion criteria was applied: (1) the study should be on the field of provided care to patients with cardiovascular disease; (2) studies should formulate or report indicators of service quality provided to patients with cardiovascular disease. We excluded studies such as editorials, case reports and Interventional studies.

To select articles, an initial screening of titles and abstracts was performed to identify potentially relevant papersafter that the full papers were screened to identify possibly relevant articles. The total search showed 2,342 articles. However after removing the irrelevant and duplicate papers or those not eligible, 15 articles entered this study (Figure 1). The selected articles were entirely reviewed and studied to extract the required data by using a designed extraction table. The author’s name, the place and time of the studies in CVD which reported service quality indicators, the methods of indicator formulation as well as the number and name of final reported indicators were included in this table. To organize and identify duplicate references, reference management software of Endnote X5 was used[16].

After identifying and extracting service indicators from the cardiovascular literature, we utilized content analysis approach using Donabedian modelDonabedian model is the most popular assessment model of healthcare (Figure 2) which was introduced in 1966. This model contains three groups: input (including appropriate facilities and equipments, adequate and skilled human resources, and anything relevant to primary structure and facilities), process (indicating the state and quality of provided services) and output or outcome (involving outcomes and effects of healthcare)[17-19].

In this study, all three components of Donabedian Model were subdivided to hospital interior and exterior indicators.

Results

The final results of literature review in the current study showed 15 papers which included 436 indicators presented in Appendex1[6,14,20-31].

Extracted indicators were divided into 7 groups and the most frequent indicators are illustrated in figure 3.

As presented in figure3, the most frequent indicators were belonged to the category of acute myocardial infarction (AMI). Indicators of myocardial infarction (MI) also were inserted into this category. The methods in formulating indicators were mostly literature review, Delphi method, expert panel, using recorded data and focus group. Such methods used in prior studies are arranged by their frequency in figure 4.

As it is shown, the most frequent method in formulating indicator was literature review including simple and systematic review.

The extracted indicators in this study were divided into three groups: input, process and output. These groups also were subdivided to hospital interior and exterior indicators (Figure 5).

Discussion

Nowadays there is a large gap between healthcare quality provided to patients with cardiovascular disease and proper standards which exist in this field[32,33]. Therefore, recently much attention is given to using indicators of service quality in order to measure and promote service quality provided to patients with cardiovascular disease[34]. So in the current study to present a model for designing, formulating and applying indicators, we applied a systematic review and Content-Analysis of service quality indicators provided to patients with cardiovascular disease using Donabedian model. In total, 463 indicators in 7 fields were eligible to be reported. Hence, these indicators model were categorized in three groups: input, process and output using Donabedian model and then they were broken down into hospital interior and exterior indicators. Besides, our findings showed that systematic review is the most frequent method in formulating indicators. The findings also demonstrated that the indicators of MI and AMI in had the most frequency indicating the importance of CVD. In the recent years, lots of studies have applied these indicators to increase service quality. showing improvement and promotion in service quality provided to these patients[35-38]. Thus using available indicators or formulating, developing and using new indicators in this field may have a positive effect on service quality provided to these patients.

In the current study we conducted Content-Analysis of indicators using Donabedian model. This model is the most popular and significant model of quality assessment in healthcare[39,40]. Recently many studies have formulated and developed indicators of service quality provided to patients with cardiovascular disease using Donabedian model[20,21,26]. Therefore, this model can be considered as a suitable model in formulating and measuring indicators. In the current study, the utilized indicators in each three groups of Donabedian model (input, process and output) were categorized into hospital interir and exterior indicators. This categorizing can be effective in identifying weaknesses and needed interventions. Furthermore, literature review of indicators revealed that most studies focused on formulation and measurement of hospital interior indicators but little attention is given to hospital exterior indicators, especially in regard of input compared with two others[41]. The results of Khalid study is in line with this study[29]. Thus developing and implementing incorporating care managers' models, such as "Project Leonardo" that introduced by Ciccone and colleagues (2010) into the primary healthcare systemare necessary to improve CVD patients health outcomes out of hospitals[42].

The methods of reviewing indicator formulation showed that literature review, expert panel and Delphi method were the most frequent methods in formulating indicators. The findings of Sadeghi-Bazargani et al on the types and formulation process of clinical indicatorsalso revealed that literature review, expert panel and Delphi method were the most popular methods in formulating indicators. These findings are consistent with the results of the current study[43]. Thus, the mentioned methods can be applicable in formulating indicators for future studies.

During literature review we noticed that most of these studies have been conducted in HICs. Out of 15 reviewed papers only one was done in LMIC[24] which may be due to some issues as follows: publishing LMIC studies in their language rather than English, limited of valid journals, lack of attention paid to the importance of using service quality indicators . The probability of the last is more . Therefore, the present study used Donabedian model for formulating indicators of service quality in LMIC.

This study was limited to relevant literature in the English and the Persian language which bounded accessibility to studies published in other languages.

conclusion

In this study, indicators of service quality provided to patients with CVD were systematically collected and categorized using Donabedian model to introduce methods of formulating such indicators. Thus the results of the current study will be help health policy makers and managements in planning, providing and measuring services delivered to patients with CVD by. Moreover findings of the current study showed that the main focus of studies on formulating and using indicators of service quality provided to patients with cardiovascular disease is on hospital interior indicators but poor attention is given to hospital exterior indicators, especially input indicators. In formulating indicators, literature review, expert panel and Delphi technique are recommended.

CONFLICT OF INTERESTS

There are no conflicts of interest with regard to the present study.

REFERENCES

1 Chung M, Asher R, Yamada D, Eagle K, Podrid P, P K. Arrhythmias after cardiac and non cardiac surgery. In Cardiac arrhythmia. 2 ed. Philadelphia: Lippincott Williams Wilkins; 2001 631-8 p.

2 Ratcliffe JA, Wilson E, Islam S, Platsman Z, Leou K, Williams G, Lucido D. Mortality in the coronary care unit. Coronary Artery Disease 2014; 25(1): 60-65

3 Zobel C, Do¨rpinghaus M, Reuter H, Erdmann E. Mortality in a cardiac intensive care unit. Clin Res Cardiol 2012; 101(7): 521-524

4 Naghavi-Behzad M, Alizadeh M, AzamiS, Foroughifar S, Ghasempour-Dabbaghi K, Karzad N, Ahadi HR. Risk Factors of Congenital Heart Diseases: A Case-Control Study inNorthwest Iran. J Cardiovasc Thorac Res 2013; 5(1): 23-28

5 Saxena A. Strategies for the improvement of cardiac care services in developing countries: what does the future hold? Future Cardiol 2012; 8(1): 29-38

6 Gorzkiewicz V, Lacroix J, Kingsbury K. Cardiac care quality indicators: a new hospital-level quality improvement initiative for cardiac care in Canada. Healthc Q 2012; 15(1): 22-25

7 A national survey on health and diseases in iran. Thran- IRAN: Iranian Ministry of Health and Medical Eucation, 2000.

8 Tabrizi J, Wilson A, Gholipour K. Comparing Technical Quality Assessment Methods for Measuring Quality of Healthcare: Systematic Review. Journal of Clinical Research & Governance 2012; 1(1): 3-11

9 Tabrizi JS, Gholipoor K, Asghari jafarabadi M, Farahbakhsh M, Mohammadzedeh M. Customer quality and maternity care in Tabriz urban health centers and health posts. J ClinRes Gov 2012; 1: 12-15

10 Brown A, Kerr E, Asch S, Hamilton E, McGlynn E. Quality of Care for Cardiopulmonary Conditions: A Review of the Literature and Quality Indicators.Santa Monica. RAND 2000: 179-200

11 Ordin D. CMS National Surgical Infection Prevention Project: quality indicator rate for Rhode Island 2001. Med Health R I 2003; 86(1): 22-23

12 Chiu W, Yang C, Lin H. Development and implementation of a nationwide health care quality indicator system in Taiwan. Int J Qual Health Care 2007; 19(1): 21-28

13 Azami-Aghdash S, Sadeghi-Bazargani H, ghasemi B, Mirzaei A, Abdollahi L, Asghari G. Preparation and priority setting of clinical governance performance indicators in dimensions of risk management and clinical effectiveness from the healthcare staff viewpoints. Int J Health Syst Disaster Manage 2013; 1(1): 16-21

14 Ulla M, Laura L, Soeren M, Vin M, Heather P, Jack V. Selecting indicators for the quality of cardiac care at the health system level in Organization for Economic Co-operation and Development countries. International Journal for Quality in Health Care 2006, 18(1): 39-44

15 Joint commission heart failure core measures. Joint Commission on Accreditation of Healthcare Organizations, 2001.

16 Sadeghi-Bazargani H, Tabrizi J, Azami-Aghdash S. Barriers to evidence-based medicine: a systematic review. Journal of Evaluation Clinical Practice, 2014 Aug 18. doi: 10.1111/jep.12222. [Epub ahead of print]

17 Nikpour B, Majlesi F. Evaluating the quality of health services. Tehran: Tehran University; 2002.

18 Donabedian A, Bashshur R. An introduction to quality assurance in healthcare. Oxford: Oxford University Press; 2003.

19 Donabedian A. The quality of care. How can it be assessed? JAMA 1988; 260(12):1743-1748

20 Veena Guru V, Geoffrey M. Anderson GM, Stephen E. Fremes SE, Gerald T. O’Connor GT, Frederick L. Grover FL, Jack V. Tu JV. The identification and development of Canadian coronary artery bypass graft surgery quality indicators. J Thorac Cardiovasc Surg 2005; 130(5): 1257-1264

21 Tu JV, Khalid L, Donovan LR, Ko DT. Indicators of quality of carefor patients with acute myocardial infarction. CMAJ 2008; 179(9): 909-915

22 Tran C, Lee D, Flintoft V, Higginson L, Grant F, Tu J, Cox J. CCORT/CCS quality indicators for acute myocardial infarction care. Can J Cardiol 2003; 19(1): 38-45

23 Hickey A, Scott I, Denaro C, Stewart N, Bennett C, Theile T. Using clinical indicators in a quality improvement programme targeting cardiac care. International Journal for Quality in Health Care 2004; 16(1): 11-25

24 Azami-Aghdash S, Ghaffari S, Sadeghi-Bazargani H, Tabrizi JS, Yagoubi A, Naghavi-Behzad M. Developing Indicators of Service Quality Provided for CardiovascularPatients Hospitalized in Cardiac Care Unit. J Cardiovasc Thorac Res 2013; 5(2): 45-49

25 McMartin K. In-hospital performance indicators for in-hospital heart failure management: a rapid review. Toronto: Health Quality Ontario, 2012.

26 Putnam W, Bower KN, Cox J, Twohig P, Pottie K, Jackson L, Burge F. Quality indicators for card iac care: national standa rds in a communit y context. J of Health Services Research & Policy 2006; 11(1): 5-12

27 Burge FI, Bower K, Putnam W, Cox JL. Quality indicators for cardiovascular primary care. Can J Cardiol 2007; 23(5): 383-388

28 Heidenreich PA, Fonarow GC. Quality Indicators for the Care of Heart Failure in Vulnerable Elders. Journal of the American Geriatrics Society 2007; 55(2): 340-346

29 Khalid L. A review of quality indicators for acute myocardial infarction care. CMAJ 2008; 179(9): 909-915

30 Budoff MJ, MacLean C, Shekelle PG. Quality Indicators for the Management of Ischemic Heart Disease in Vulnerable Older Persons. California: Rand Health, 2004.

31 Grace S, Suskin N, Alter D, Bacon S, Dai S, Gurevich Y, Johnstone D. Cardiac Rehabilitation/Secondary Prevention Quality Indicators. Canada: The Canadian Cardiovascular Society Quality Indicators E-Catalogue 2013.

32 Foxwell R, Morley C, Frizelle D. Illness perceptions, mood and quality of life: a systematic review of coronary heart disease patients. Ann Thorac Surg 2013; 96(5): 1695-1701

33 Fox K, Goodman S, Klein W, Brieger D, Steg P, Dabbous O, Avezum A, Kiefe CI, Allman RM, Vogel RA, Jencks SF. Management of acute coronary syndromes. Variations in practice and outcome; findings from the Global Registry of Acute Coronary Events (GRACE). Eur Heart J 2002; 23(15): 1177-1189

34 Department of Health. Coronary heart disease: national service framework for coronary heart disease — modern standards and service models. London (UK):The Department; 2000. Available: www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_4094275 (accessed 2008 Aug 22).

35 Marciniak TA, Ellerbeck EF, Radford MJ, Kresowik TF, Gold JA, Krumholz HM, Kiefe CI, Allman RM, Vogel RA, Jencks SF. Improving the quality of care for Medicare patients with acute myocardial infarction: results from the Cooperative Cardiovascular Project. JAMA 1998; 279(17): 1351-1357

36 Rogers WJ, Canto JG, Lambrew CT, Tiefenbrunn AJ, Kinkaid B, Shoultz DA, Paul, DF, Every N. Temporal trends in the treatment of over 1.5 million patients with myocardial infarction in the U.S. from 1990 through 1999: The National Registry of Myocardial Infarction 1, 2 and 3. Journal of the American College of Cardiology 2000; 36(7): 2056-2063

37 Chassin M. Achieving and sustaining improved quality: lessons from New York State and cardiac surgery. Health Affairs (Millwood) 2002; 21(4): 40-51

38 Masoudi F, Magid D, Vinson D, Tricomi A, Lyons E, Crounse L. Implications of the failure to identify high-risk ECG findings for the quality of care of patients with AMI: results of the ED quality in MI (EDQMI) study. Circulation 2006; 114: 1565-1571

39 Donabedian A. An introduction to quality assurance in health care. 1 ed. New York: Oxford University Press; 2003.

40 Donabedian A. Evaluating the quality of medical care. 1966. The Milbank quarterly 2005; 83(4): 691-729

41 Department of Health. Coronary heart disease: national service framework for coronary heart disease - modern standards and service models. 16602. 2000. http://www.dh.gov.uk/en/Publicationsandstatistics/Publications/PublicationsPolicyAndGuidance/DH_4094275. Accessed September 10, 2007.

42 Ciccone M, Aquilino A, Cortese F, Scicchitano P, Sassara M, Mola E, Rollo R, Caldarola P, Giorgino F, Pomo V, Bux F. Feasibility and effectiveness of a disease and care management model in the primary health care system for patients with heart failure and diabetes (Project Leonardo). Vasc Health Risk Manag 2010; 6(6): 297-305

43 Sadeghi-Bazargani H, Farhoudi M, Hajebrahimi S, Naghavi-Behzad M, sohrab navi Z, Azami-Aghdash S. A systematic review on clinical indicators, their types and codification processes. Journal of Clinical Research & Governance 2015; 4(1) [In Press]

Peer reviewers: Marco Matteo Ciccone, Associate Professor, University of Bari, Cardiology Department, Policlico, Piazza G. Cesare, 11 – 70124 Bari, Italy; Marie-Noëlle Giraud, Lab 0.105, Université de Fribourg- Faculté des sciences, Département de médecine- Chaire de Cardiologie, Ch. du Musée 5, 1700 Fribourg, Switzerland; Goran P. Koraćević, MD, PhD, Assoc Prof, Department for cardiovascular diseases, Clinical Centre Niš and Medical Faculty, University of Niš, Niš, 18000, Serbia.

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