Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry
Mostafa Shanbehzadeh1, Hadi Kazemi-Arpanahi2, Arezo Arzani-Birgani2, Azimeh Karimyan3, Fatemeh Mobasheri2
1 Department of Health Information Technology, School of Paramedical, Ilam University of Medical Sciences, Ilam, Iran 2 Department of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan, Iran 3 Department of Public Health, Abadan Faculty of Medical Sciences, Abadan, Iran
Date of Submission | 11-Jan-2020 |
Date of Acceptance | 01-Mar-2020 |
Date of Web Publication | 30-Jun-2020 |
Correspondence Address: Dr. Hadi Kazemi-Arpanahi Department of Health Information Technology, Abadan Faculty of Medical Sciences, Abadan Iran
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jehp.jehp_37_20
BACKGROUND: Hypertension (HTN) has become a major public health problem which can cause serious complications when it is not well-controlled. Prevention and effective care of HTN require a population-based registry. Thus, establishing this registry can be used to collect comprehensive, timely, and reliable data on epidemiology cases. The aim is to create a registry for the collection of highly required prospective data that will present an in-depth analysis of the characteristics of all individuals with HTN and track them over a particular chronological interval. MATERIALS AND METHODS: The study was divided into three phases: At first, a comprehensive literature review was conducted to determine the proposed data classes and data fields. Then, the final minimum data set was designed by a two-round Delphi consensus approach of 20 experts of cardiologists, nephrologists, nutritionist, and health information management. Finally, a web-based registry system was developed by a Structured Query Language environment. RESULTS: A total of two clinical and nonclinical data categories with nine data classes and 68 data fields were selected for their inclusion in the registry following the consensus phase. A web-based registry was designed with a modular and layered architecture. CONCLUSIONS: This study provides an appropriate information infrastructure for active tracing and monitoring of individuals with HTN. It has provided a practical information system allowing quality improvement, aggregate reporting for planning, and research purposes.
Keywords: Hypertension, minimum data set, registry system
How to cite this article: Shanbehzadeh M, Kazemi-Arpanahi H, Arzani-Birgani A, Karimyan A, Mobasheri F. Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry. J Edu Health Promot 2020;9:134 |
How to cite this URL: Shanbehzadeh M, Kazemi-Arpanahi H, Arzani-Birgani A, Karimyan A, Mobasheri F. Improving hypertension surveillance from a data management prospective: Data requirements for implementation of population-based registry. J Edu Health Promot [serial online] 2020 [cited 2023 Sep 26];9:134. Available from: https://www.jehp.net//text.asp?2020/9/1/134/288339 |
Introduction | |  |
Hypertension (HTN) or high blood pressure is a physiological condition considered as the most important and well-known determinant of cardiovascular diseases. HTN can often be a preliminary phase to develop coronary heart disease, stroke, sudden death, heart failure, peripheral artery disease, and end-stage renal disease, which are likely to raise the risk of death and disability.[1],[2],[3] HTN is known as the silent killer since it is considerably or completely asymptomatic; individuals with HTN may not know they have it or may not view their condition as a serious problem.[4],[5] It affects more than 1 billion people worldwide and is currently ranked as the leading cause for more than 10 million largely preventable deaths globally each year.[6],[7] Studies have reported a high incidence of this condition; it was reported to be 14%–34% in Iran.[8],[9] In Iran, the National Blood Pressure Control Program was implemented throughout the country from May 17, 2018 (coinciding with the World Blood Pressure Control Day) to 6 July.
Given the significant burdens associated with HTN, the decision was made to adopt public health informatics approaches for the promotion of HTN surveillance. Clinical registry is one of such population-based health promotion programs. Clinical registries facilitate studying the real clinical practice, capturing quality metrics, monitoring the disease and health-care delivery patterns, and tracing clinical outcomes. They also provide real highly generalizable data and can be used to improve population health surveillance and research support. In other words, clinical registries are essential for integrating research and clinical practice and eventually translating them into therapeutic solutions.[10],[11],[12],[13],[14],[15] The population-based HTN registry has been considered in Iran due to the high prevalence of HTN and the need for effective monitoring.[16] To the best of our knowledge, there has been limited investigation on the features of HTN registry from a data management perspective in Iran. In order to address the above-mentioned issues, our objective is to determine HTN required data elements and then its clinical registry.
Materials and Methods | |  |
Clinical registries, albeit being valuable instruments, are difficult to initially develop and implement, requiring the involvement of a multidisciplinary team.[17] This project was structured in two phases: initially, the aim was to define the variables required to be included in the HTN registry; the second goal was establishing the registry.
The choice of data elements for inclusion in clinical registry is a critical component which defines the quality and clinical usefulness of the eventual output. For this purpose, a literature review coupled with the expert consensus was performed. Initially, a comprehensive review of the HTN literature was conducted to determine a preliminary data element of HTN.[18],[19],[20],[21] Data sources for this stage were papers, reports, and forms on the internet. In this stage, a checklist was used to extract the data fields and their variables. To find materials relevant to the subject, Google Scholar, Elsevier, Science direct, Scopus, Cochran, and PubMed Data bases were explored. In this study, all resources related to minimum data set (MDS), registry, and data fields of HTN were examined, and the main data field and their variables were extracted.
The studies were identified by keywords including “Minimum data,” “Minimum Data Set,” “Data field,” “MDS,” “Hypertension,” “High blood pressure,” “HTN,” “Registry,” and “Surveillance system.” Sampling was not performed at this stage, while all the relevant literature was retrieved and evaluated based on the inclusion criteria (English language resources between 2009 and 2019, in full text from valid sources). Short articles, letters to the editor, papers accepted in conferences, and reports extracted from blogs were not included in this study.
To determine the final data elements of MDS related to HTN registry, data elements were chosen by 20 experts of cardiologists, nephrologists, and specialists in health nutrition and health information management (HIM) through the Decision Delphi technique in two rounds. Biostatistician support was also required to enable a robust analysis of acquired data.
The participating experts were asked to score the items according to the importance perceived by them based on a five-point Likert scale. In this scale, a score of 1 naturally represented the “lowest level of importance” while a score of 5 represented the “highest level of importance.” The content validity of the questionnaire was evaluated by four experts, including two HIM experts and two cardiologists. Test-retest reliability (with a 10-day interval) was performed to determine the reliability of the questionnaire. The collected data were analyzed using Statistical Package for the Social Sciences (SPSS) version 19 (IBM corporation: USA, New York), where a Spearman's rank correlation coefficient of 84% was achieved. Through the decision Delphi technique in two rounds, decisions on the included data fields were based on the agreement level. Accordingly, data fields with < 50% agreement were excluded in the first round while those with >75% agreement were included in the primary round. Those with 50%–75% agreement were surveyed in the second round, and if there was 75% consensus over a subject, it was regarded as a final data field.
An Agile software development model was utilized for this project. The Agile model comprises increasing the development of functionality and frequent feedback from the user, allowing for adjustment to uncertain or changing requirements.[22] The development tools utilized in this project were as follows.
Due to the benefits of web-based applications, including cost savings, productivity, efficiency, improved communication, data security, scalability, and accessibility, most of the world's registry systems have been developed on the web platform.[23] Thus, this platform has been used in this study to develop the system. Meanwhile, Structured Query Language (SQL) server database was used to store the data; capabilities of SQL Server database can be relational data bank, Extensive Markup Language support, unlimited record volume and number, online analytical processing, full text search, quick information retrieval, and use of natural language in searches. The C # programming language was also used in the NET4.5 technology platform for high-level interface programing.
Results | |  |
The results of this study are divided into three parts, including determining a preliminary list of data elements for HTN registry, identifying final MDS for HTN registry, and design the HTN registry system.
Proposed minimum data set of review studies
In order to identify a preliminary list of data elements, an extensive literature review was done. The MDS designed in this study included data categories (general level), data classes (detailed level), and data fields (atomic level). Following the literature review, the proposed MDS consisted of two data categories (nonclinical and clinical), nine data classes, and 91 data fields.
Final minimum data set of Delphi survey
To determine the final data elements of the HTN registry, data fields were chosen by 20 samples of attending experts through the Decision Delphi technique in two rounds. [Table 1] presents the attending expert's demographic characteristics.
[Table 2] indicates A number of data elements were excluded after the second round of Delphi.[Table 3] shows the final necessary data classes and data fields along with data type and content for HTN in clinical and nonclinical categories. | Table 2: Delphi results for clinical and nonclinical hypertension registry categories
Click here to view |
 | Table 3: Final data classes, field format, and content for hypertension registry
Click here to view |
The final MDS was composed of two data categories, nine data classes, and 68 data elements [Table 3]. Data categories included both clinical and nonclinical. The clinical data category consisted of seven data classes and 46 data fields including physical examination (seven data fields), laboratory tests (ten data fields), ECG evaluation (seven data fields), patient history (six data fields), family history (four data fields), signs and symptoms (eight data fields), and treatment recommendations (four data fields). On the other hand, the socio-demographic data (13 data fields) and life style (9 data fields) were the only nonclinical classes. In general, the final MDS was divided into two data categories, including clinical and nonclinical with seven and two data classes along with 46 and 22 data fields, respectively.
The hypertension registry framework
In the software development phase, the emphasis has been laid on accessibility and user-friendliness of the system to shorten the reporting time. The designed system used an advanced search capability to enable quick search of data for research purposes. Where possible, check boxes and radio buttons have been used, and free text data fields avoided.
Access to the registry was given to registered members. Each user had a unique identification number and password to log into the database. The purpose of all the above-mentioned measures was to maximize the accuracy of data. On login, the system home page would be displayed. This page included patient list, search, reporting, and user management menus. [Figure 1] and [Figure 2] show the web-based registry of HTN.
Discussion | |  |
In the present study, initially, we determined the MDS required for entry into the HTN registry based on the expert's consensus. Data collection is an important step for information management and design of information systems in clinical and research domains. The required MDS is a coherent set of data elements established for mandatory reporting at the national level, which is very important to be determined in a standard and integrated way from a scientific perspective.[24],[25],[26] Integrating data between research and clinical systems are a major challenge. Clinical trials are often not integrated with clinical care. Poor integration leads to the repetition of activities and limited learning of health care.[27] In addition, the quality of research results depends on good data. A very important step in clinical research is the collection of accurate and reliable data to ensure valid results.[28],[29]
HTN registry is central for studying the epidemiological characteristics of volunteers eligible to HTN in Iran. Many research findings have indicated that most risk factors for HTN are related to individuals' behavior, awareness, and educational programs.[30] By designing and implementing HTN registry, we were able to establish an active tracking system which improved treatment monitoring for individuals with HTN.[31] In fact, the HTN registry is a secondary solution for managing HTN, which can be important in studying and evaluating the relation of HTN with other diseases, as well as improving the quality of care and follow-up among the patients continuously. A well-designed registry encompasses a set of chronological collected and stored data focusing on a specific condition. Its practicality and reliability depend directly on the completeness and validity of the data contained therein.[32],[33],[34],[35],[36] Since the most effective design for a new registry is web based,[37] the registry framework in this study has also been web-based, offering a cost-effective alternative to paper-based disease tracking. The web-based application was compatible with the workflow of HTN visit, and it is very easy to use in terms of data entry and requesting reports.
Manual data entry is a time-consuming and error-prone process, so an accurate data entry process is essential for high quality research. Information should also be comprehensive so that it can be recorded in a few clicks. Consideration should be given to the format in which a data element is recorded to guarantee its use for secondary applications such as epidemiological research and reporting. From the physicians' point of view, it is easier to analyze the data elements that are compulsory options rather than free text data.[38] In this study, the designed registry system has been convenient and reliable, and even manual data entry has been avoided.
We believe that valid data on the frequency and distribution of the HTN can offer a clear understanding of the improvement in care quality of patients. Likewise, it can support researches that are conducted to addresses high-priority issues. This promotes a deeper understanding of how HTN behaves in epidemiological aspects in Iran. This registry system stands to be a major benefit to researchers, as it will enable them to undertake increasingly sophisticated investigations more easily. However, in order to take advantage of improved data availability, we must first create effective systems to extract, store, utilize, and protect this information with thoughtfully designed disease-specific databases and informatics infrastructures.[39] Population based registry is an appropriate method to HTN monitoring. The registry in this study is a web-based HTN registry that offers a cost-effective alternative to paper-based disease tracking. However, this work does have a limitation. It is not probable to comprehensively capture all the data items which limit the practicality of the MDS; however, this will be outweighed by providing the most necessary data elements and possible subcategories.
Conclusions | |  |
International experience proves that the development of an HTN registry has a pivotal role in public health promotion.[40] This registry provides a wealth infrastructure for capturing data on HTN; the next steps are to carry out an in-depth analysis on collected data, in particular looking at the pattern history of the condition. We have adopted some new methods and technologies that can facilitate the capture and auditing of data which also have the potential to be used for future quality-improvement initiatives.
In the near future, a wider use of HTN registry would be desirable to better understand the nature and behavior of HTN in Iran. We hope that the knowledge generated from the HTN registry can be useful worldwide. Although the database is already a useful resource for many investigators, it has a limitation; it is not yet fully inclusive or complete.
Acknowledgments
This article is extracted from a research project which supported by Abadan University of Medical Sciences with the Ethical code no IR.ABADANUMS.REC.1398.088. We appreciate Research Deputy of Abadan University of Medical Sciences who sponsored this project financially.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
References | |  |
1. | Gorostidi M, Banegas JR, de la Sierra A, Vinyoles E, Segura J, Ruilope LM. Ambulatory blood pressure monitoring in daily clinical practice – the Spanish ABPM Registry experience. European Journal of Clinical Investigation 2016;46:92-8. doi: 10.1111/eci.12565. Epub 2015 Dec 23. |
2. | Aleali AM, Latifi SM, Rashidi H, Payami SP, Sabet A. Prevalence of hypertension and prehypertension in adolescence in Ahvaz, Iran. Diabetes & Metabolic Syndrome: Clinical Research & Reviews. 2017;11:S547-S50. doi: 10.1016/j.dsx.2017.04.002. |
3. | Katibeh M, Sanjari Moghaddam A, Yaseri M, Neupane D, Kallestrup P, Ahmadieh H. Hypertension and associated factors in the Islamic Republic of Iran: A population-based study. East Mediterr Health J 2019;25. |
4. | Kim H, Andrade FCD. Diagnostic status of hypertension on the adherence to the Dietary Approaches to Stop Hypertension (DASH) diet. Preventive Medicine Reports 2016;4:525-31. doi: 10.1016/j.pmedr.2016.09.009. |
5. | Zhou Y, Jia L, Lu B, Gu G, Hu H, Zhang Z, et al. Updated hypertension prevalence, awareness, and control rates based on the 2017ACC/AHA high blood pressure guideline. The Journal of Clinical Hypertension 2019. doi: 10.1111/jch.13564. |
6. | Patel P, Ordunez P, DiPette D, Escobar MC, Hassell T, Wyss F, et al. Improved Blood Pressure Control to Reduce Cardiovascular Disease Morbidity and Mortality: The Standardized Hypertension Treatment and Prevention Project. The Journal of Clinical Hypertension 2016;18:1284-94. doi: 10.1111/jch.12861. |
7. | Ndanuko RN, Tapsell LC, Charlton KE, Neale EP, Batterham MJ. Associations between Dietary Patterns and Blood Pressure in a Clinical Sample of Overweight Adults. Journal of the Academy of Nutrition and Dietetics. 2017;117:228-39. doi: 10.1016/j.jand.2016.07.019. |
8. | Motlagh Z, Fazel S, Chaman R, Ghafari SR, Parisay Z, Golabi MR, et al. Knowledge, treatment, control, and risk factors for hypertension among adults in Southern Iran. International journal of hypertension 2015;2015. doi: 10.1155/2015/897070. |
9. | Sadeghi M, Talaei M, Gharipour M, Oveisgharan S, Nezafati P, Dianatkhah M, et al. Anthropometric indices predicting incident hypertension in an Iranian population: The Isfahan cohort study. Anatol J Cardiol 2019;22:33-43. doi: 10.14744/AnatolJCardiol. |
10. | Korngut L, Genge A, Johnston M, Benstead T, Bourque P, Briemberg H, et al. Establishing a Canadian registry of patients with amyotrophic lateral sclerosis. Canadian Journal of Neurological Sciences 2013;40:29-35. doi: 10.1017/s0317167100012919. |
11. | Bergin K, Moore E, McQuilten Z, Wood E, Augustson B, Blacklock H, et al. Design and development of the Australian and New Zealand (ANZ) myeloma and related diseases registry. BMC medical research methodology 2016;16:151. doi: 10.1186/s12874-016-0250-z. |
12. | LeBrun EEW. Registries as tools for clinical excellence and the development of the Pelvic Floor Disorders Registry. Obstetrics and Gynecology Clinics 2016;43:121-30. doi: 10.1016/j.ogc.2015.10.006. |
13. | McBride D, Dohan D, Handley MA, Powe NR, Tuot DS. Developing a CKD registry in primary care: provider attitudes and input. American Journal of Kidney Diseases. 2014;63:577-83. doi: 10.1053/j.ajkd.2013.10.012. |
14. | Rodrigues C, Vaz J, Aristimunho P, Vacca C, Verboski B, Kalil R. Management of Standardised, Interoperable Clinical Registries: Visioning Quality of Care and Clinical Research. Journal of the International Society for Telemedicine and eHealth. 2017;5:(GKR); e64:1-5. |
15. | Mercuri E, Finkel R, Scoto M, Hall S, Eaton S, Rashid A, et al. Development of an academic disease registry for spinal muscular atrophy. Neuromuscular Disorders. 2019. doi: 10.1016/j.nmd.2019.08.014. |
16. | Motedayen M, Sarokhani D, Ghiasi B, Khatony A, Hasanpour Dehkordi A. Prevalence of Hypertension in Renal Diseases in Iran: Systematic Review and Meta-Analysis. I Int J Prev Med 2019;10:124. doi: 10.4103/ijpvm.IJPVM_522_18. |
17. | Bellgard MI, Walker CE, Napier KR, Lamont L, Hunter AA, Render L, et al. Design of the Familial Hypercholesterolaemia Australasia Network Registry: Creating opportunities for greater international collaboration. J Atheroscler Thromb. 2017:37507. doi: 10.5551/jat.37507. |
18. | Posnenkova O, Kiselev A, Gridnev V, Schwartz V, Dovgalevskyi PY, Oshchepkova E. Blood pressure control in primary care patients with arterial hypertension: analysing the Hypertension Register data. Cardiovascular therapy and prevention 2012;11:4-11. |
19. | Chazova I, Ratova L, Boytsov S, Nebieridze D, Karpov YuA BY. Diagnosis and treatment of hypertension (Guidelines of Russian Society of Hypertension and Russian Society of Cardiology). Sistemnye gipertenzii. 2010;3:5-26. |
20. | Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Boehm M, et al. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). J Hypertens 2013;31:1925-38. doi: 10.1097/HJH.0b013e328364ca4c. |
21. | Weintraub WS, Karlsberg RP, Tcheng JE, Boris JR, Buxton AE, Dove JT, et al. ACCF/AHA 2011 key data elements and definitions of a base cardiovascular vocabulary for electronic health records: a report of the American College of Cardiology Foundation/American Heart Association Task Force on Clinical Data Standards. J Am Coll Cardiol 2011;58:202-22. doi:10.1016/j.jacc.2011.05.001. |
22. | McFadden N, Daniel B, Hoyt R, Snider D. Development of a Web-Based Registry to Support Diabetes Care in Free Medical Clinics. Perspect Health Inf Manag. 2017;14(Winter):1a-a. |
23. | Shahraki AD, Safdari R, Shahmoradi L, Malak JS, Pourghaz B, Ghabaee M. Acute Stroke Registry Planning Experiences. J Registry Manag 2018;45:37-42. |
24. | Cox N, Brennan A, Dinh D, Brien R, Cowie K, Stub D, et al. Implementing Sustainable Data Collection for a Cardiac Outcomes Registry in an Australian Public Hospital. Heart, lung & circulation 2018;27:464-8. doi: 10.1016/j.hlc.2017.01.023. |
25. | Kazemi-Arpanahi H, Vasheghani-Farahani A, Baradaran A, Mohammadzadeh N, Ghazisaeedi M. Developing a Minimum Data Set (MDS) for Cardiac Electronic Implantable Devices Implantation. Acta Inform Med. 2018;26:164-8. doi: 10.5455/aim.2018.26.164-168. |
26. | Kazemi-Arpanahi H, Vasheghani-Farahani A, Baradaran A, Ghazisaeedi M, Mohammadzadeh N, Bostan H. Development of a minimum data set for cardiac electrophysiology study ablation. Journal of education and health promotion. 2019;8:101. doi: 10.4103/jehp.jehp_232_18. |
27. | Dunn WD, Jr., Cobb J, Levey AI, Gutman DA. REDLetr: Workflow and tools to support the migration of legacy clinical data capture systems to REDCap. International journal of medical informatics. 2016;93:103-10. doi: 10.1016/j.ijmedinf.2016.06.015. |
28. | Barchard K, Verenikina Y. Improving data accuracy: Selecting the best data checking technique. Computers in Human Behavior. 2013;29:1917-22.doi: https://doi.org/10.1016/j.chb.2013.02.021. |
29. | HĂŞMĂŞANU MG, BOLBOACĂ SD, Jäntschi L, Zaharie GC, Drugan TC. Design and implementation of data collection instruments for neonatology research. Applied Medical Informatics. 2014;35(4):35-44. doi: 10.1002/hast.407. |
30. | Moeini B, Hazavehei M, Moghimbeigi A, Homayonfar S, Moslem A, Jamal S, et al. Relationship between Adults' Blood Pressure, Occupation and Physical Activity: A cross-sectional study among 20 to 65 years adults in Sabzevar, Iran. 2019:2015-6. |
31. | Lindoerfer D, Mansmann U. Enhancing requirements engineering for patient registry software systems with evidence-based components. Journal of biomedical informatics 2017;71:147-53. doi: 10.1016/j.jbi.2017.05.013. |
32. | Rojas JI, Carrá A, Correale J, Cristiano E, Liguori NF, Alonso R, et al. The Argentinean multiple sclerosis registry (RelevarEM): Methodological aspects and directions. Multiple sclerosis and related disorders. 2019;32:133-7. doi: 10.1016/j.msard.2019.05.004. |
33. | Sharif-Alhoseini M, Azadmanjir Z, Sadeghi-Naini M, Ghodsi Z, Naghdi K, Mohammadzadeh M, et al. National Spinal Cord Injury Registry of Iran (NSCIR-IR)–a critical appraisal of its strengths and weaknesses. Chinese Journal of Traumatology. 2019. doi: 10.1016/j.cjtee.2019.05.003. |
34. | Arthursson AJ, Furnes O, Espehaug B, Havelin LI, Söreide JA. Validation of data in the Norwegian Arthroplasty Register and the Norwegian Patient Register: 5,134 primary total hip arthroplasties and revisions operated at a single hospital between 1987 and 2003. Acta orthopaedica. 2005;76:823-8. doi: 10.1080/17453670510045435. |
35. | Barsoum WK, Higuera CA, Tellez A, Klika AK, Brooks PJ, Patel PD. Design, implementation, and comparison of methods for collecting implant registry data at different hospital types. The Journal of arthroplasty. 2012;27:842-50. e1. doi: 10.1016/j.arth.2011.12.014. |
36. | Golan R, Bernstein A, Sedrakyan A, Daskivich TJ, Du DT, Ehdaie B, et al. Development of a nationally representative coordinated registry network for prostate ablation technologies. The Journal of urology. 2018;199:1488-93. doi: 10.1016/j.juro.2017.12.058. |
37. | Ingvarsson G, Dufour DN, Killasli H, Sartorius K, Lapins J, Skau PA, et al. Development of a clinical Scandinavian registry for hidradenitis suppurativa; HISREG. Acta dermato-venereologica. 2013;93:350-1. doi: 10.2340/00015555-1468. |
38. | Davey CJ, Slade SV, Shickle D. A proposed minimum data set for international primary care optometry: A modified Delphi study. Ophthalmic and Physiological Optics 2017;37:428-39. doi: 10.1111/opo.12372. |
39. | Won B, Carey GB, Tan Y-HC, Bokhary U, Itkonen M, Szeto K, et al. The Chicago Thoracic Oncology Database Consortium: A Multisite Database Initiative. Cureus. 2016;8(3). doi: 10.7759/cureus.533. |
40. | Jaffe MG, Lee GA, Young JD, Sidney S, Go AS. Improved blood pressure control associated with a large-scale hypertension program. Jama 2013;310:699-705. doi: 10.1001/jama.2013.108769. |
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
|