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Abstract

Background and objective

Goiter, primarily caused by iodine deficiency, remains one of the most common endocrine disorders globally. The absence of standardized and structured data hampers effective monitoring, diagnosis, and management. This study aimed to develop a minimum data set (MDS) for goiter to facilitate accurate and consistent data collection and support the development of a national registry system for improved healthcare delivery.

Methods

A cross-sectional study was conducted in Kerman, Iran, from October 2023 to May 2024, in three phases. In the first phase, relevant data elements were extracted from the literature and existing records. In the second phase, a checklist was designed based on the extracted elements. In the third phase, a two-round Delphi method was conducted with a panel of domain experts, including endocrinologists and health informatics specialists, to validate and finalize the proposed MDS.

Results

Initially, 57 data elements were identified across clinical and managerial categories. After the first Delphi round, 15 elements were approved. Following the second round, the final MDS was refined to 9 core elements that met the experts’ consensus.

Conclusion

This study demonstrates that a carefully designed MDS, developed with input from both clinical and informatics experts, can significantly enhance the quality and consistency of goiter-related data. It supports better planning, resource allocation, and clinical outcomes while addressing existing challenges such as poor registration systems and lack of standardized documentation.

Keywords

Goiter data set Minimum data set Delphi method Information Management

Introduction

Goiter can be defined as a simple enlargement of the thyroid gland.¹ In cases of severe iodine deficiency, the thyroid gland increases salt absorption by up to 80%, leading to goiter.² Iodine deficiency is the most common cause of goiter worldwide.³ Due to differences in iodine intake across various geographical regions, the prevalence of goiter varies globally. For example, 41% of individuals affected by goiter, equating to 267 million people, reside in South Asia and the Mediterranean region.⁴ Therefore, goiter is a major public health issue in many world areas, particularly developing countries.⁵ The incidence of goiter may increase with age and weight but may decrease with increased iodine intake.⁶

Iodized salt is a simple and effective intervention for preventing iodine deficiency disorders.^7,8 While approximately 90% of households globally have access to iodized salt, inadequate iodine intake remains a concern, affecting nearly 30% of students and over half the population in 39 countries.^9,10 Several factors influence goiter incidence, including age,^11–13 gender,¹⁴ socioeconomic status,¹⁵ family history,¹⁶ and the iodine content of household salt.¹⁷ Estimating the prevalence of thyroid dysfunction is therefore vital, particularly in high-risk groups.¹⁸ The American Thyroid Association recommends targeted screening, especially during pregnancy, when iodine requirements and thyroid gland size significantly increase, with a nearly 50% increase in iodine demand and more pronounced gland enlargement in iodine-deficient regions.^19,20

The first report on iodine deficiency disorders in Iran was published in 1968.²¹ An epidemiological study of goiter, a primary indicator of iodine deficiency, was first conducted in 1969 by the Institute of Nutrition and Food Industries of Iran under the leadership of Dr. Emami and his colleagues.²² A recent systematic review and meta-analysis revealed that the prevalence of thyroid dysfunction among pregnant Iranian women was 18.10%.²³ Furthermore, a study by Nazarpour et al. demonstrated that more than 35% of pregnant women with thyroid dysfunction are not identified during screening, as recommended by the American Thyroid Association.²⁴ Effective disease management and prevention rely on precise and accurate data recording. To ensure this, various disease registration systems, including those for drug poisoning, breast cancer, diabetes, and congenital heart disease, are in place today.^25–28 These systems provide dynamic, flexible, and secure platforms for the collection of reliable medical data, enabling evidence-based reporting and decision-making.^25,29

The goiter registration system, as a component of health information systems, is capable of identifying the occurrence and prevalence of goiter, as well as temporal and spatial changes, quality of care, and resource and facility shortages in different regions. It also plays a vital role in facilitating research evaluation and improvement through systematic data collection.^25,30 The initial step in developing an information registration system involves designing a minimum data set (MDS) relevant to the disease.²⁵ The creation and development of an MDS with standardized definitions and methods allows for the collection of reliable and comparable data on patient numbers, treatment modalities, and the outcomes of healthcare services provided across regions.³¹ An MDS is a structured collection of data from multiple sources, developed using specific definitions and procedures. It enables the establishment of a comprehensive database on a particular disease, which can be used to standardize healthcare services in hospitals, nursing homes, and other healthcare institutions. The MDS includes two types of data: general disease-related data (such as demographic data, referral, and follow-up information) and specific disease-related data (including disease progression, risk factors, complications, and care outcomes).³²

MDS is essential for advancing the development of electronic health records, personal health records, hospital information systems (HIS), and facilitating the exchange of information across different healthcare centers. In many countries, the primary goals of an MDS for diseases include data comparison and analysis, statistical reporting, reducing disparities, ensuring quality, decreasing mortality, supporting planning and evaluation, enabling research, conducting clinical audits, informing education, guiding policy-making, and optimizing resource allocation.³³ Research conducted by the team has shown that efforts to establish MDS and information registration systems for thyroid diseases, including hypothyroidism, hyperthyroidism, and thyroid cancer, have been implemented both in Iran and globally. However, no MDS or information registration system for goiter currently exists. Therefore, this study aims to develop a MDS specifically for individuals with goiter. The outcomes of this study will serve as a reliable and standardized resource for the establishment of a goiter registration system, improving data collection and the overall management of the disease.

Method

This descriptive and cross-sectional study was conducted in Kerman, Iran, between October 2023 and May 2024, aiming to design and develop a MDS for goiter-related health information management. The study was carried out in three sequential and methodologically robust phases.

Phase 1: Identification of relevant data elements

An extensive literature review was conducted to identify and extract relevant data elements associated with goiter. Key international databases PubMed, Scopus, Web of Science, and Google Scholar, along with general web search engines such as Google, were systematically searched using a combination of keywords: “Minimum Dataset,” “MDS,” “Metadata,” “Registry,” and “Goiter.” In addition, expert consultations were held with endocrinologists to ensure the clinical relevance and completeness of the extracted items. A researcher-designed data extraction form was used to record variables, including bibliographic information, data categories (e.g. demographic, clinical, diagnostic), and the original sources.

Phase 2: Development and validation of the evaluation instrument

Based on the extracted data elements, a structured questionnaire was developed to assess the necessity and relevance of each item using a five-point Likert scale (ranging from “Strongly Disagree” to “Strongly Agree”). Content validity of the instrument was assessed and confirmed by a multidisciplinary panel, including experts in health information management, medical informatics, and endocrinology. Reliability was established using Cronbach's alpha, with a coefficient of 0.89, indicating strong internal consistency. Participants were purposively selected according to specific inclusion criteria, such as at least five years of experience and affiliation with Kerman University of Medical Sciences.

Phase 3: Consensus building using the Delphi technique

To refine and validate the identified data elements, the Delphi technique was employed—an iterative, structured method that seeks to reach consensus among a panel of experts, particularly in fields lacking standardized frameworks. This technique relies on multiple rounds of anonymized feedback, allowing experts to reconsider their responses based on collective insights.

A two-round Delphi process was implemented as follows:

Round 1: Initial Evaluation and Feedback

The initial version of the questionnaire was distributed among a purposive sample of 10 experts (5 endocrinologists and 5 health informatics specialists), selected based on their subject matter expertise (Table 1).

Table 1.

Demographic characteristics of specialists participating in the determination of the elements of the minimum data set for goiter.

Educational	Age group	Gender	Qualification	Quantity specialists
Doctorate in Health Information Management	30–39: 1 people40–49: 0 people50–59: 0 people60–69: 1 people	Women: 2 peopleMen: 0 people	2 people	Health Information Management
Doctorate in Medical Informatics	30–39: 0 people40–49: 1 people50–59: 2 people	Women: 1 peopleMen: 2 people	3 people	Medical informatics
Subspecialty in Endocrinology and Metabolism	30–39: 0 people40–49: 3 people50–59: 2 people	Women: 3 peopleMen: 2 people	5 people	Endocrine disease

Each expert rated the relevance and necessity of each data element on a Likert scale and was encouraged to provide qualitative comments or suggest additional elements. Items with high consensus were retained, while those with divergent evaluations were revised or removed.

Round 2: Feedback Integration and Final Consensus

A revised questionnaire—incorporating feedback and aggregated statistics from Round 1 was redistributed to the same panel. Experts were invited to reassess their initial judgments in light of the group's feedback. Items reaching a predefined consensus threshold were included in the final MDS, while elements lacking agreement were excluded or refined further.

Validity and reliability assessment

To evaluate the methodological rigor and consensus reliability, the following metrics were employed:

Content Validity Ratio (CVR):

Calculated using Lawshe's formula, CVR = (Ne − N/2) / (N/2), where Ne represents the number of experts rating an item as essential and N is the total number of panelists. A CVR ≥ 0.62 (based on Lawshe's table for 10 experts) was considered acceptable.

Content Validity Index (CVI):

The CVI was determined by averaging the CVR values across all items. Items with CVI < 0.70 were excluded; those between 0.70 and 0.79 were revised; and items with CVI ≥ 0.79 were retained.

Inter-Rater Reliability (Kappa Statistic):

The Kappa coefficient was employed to assess expert agreement beyond chance. A value greater than 0.74 indicates strong agreement and supports the reliability of the consensus.

Data analysis

All quantitative data were analyzed using SPSS version 23. Descriptive statistics (mean, frequency, standard deviation) were applied to summarize expert responses. The final structure of the goiter-specific MDS was determined based on the level of expert consensus regarding each data element's relevance and necessity.

Results

By reviewing texts and studying library resources, as well as content from websites and articles, and consulting with an endocrinologist, a researcher-created checklist of the identified MDS elements was prepared. The MDS elements included two sections: management information (11 data elements) and clinical information (46 data elements). Additionally, Table 2 presents the definitions and scales of the identified MDS elements for goiter.

Table 2.

Definitions of the elements of the minimum data set for goiter and their scale.

Variables	Type	Definition	Values
Character string	-	The term is used to address an individual.	First name
Character string	-	A part of a person's full name that indicates their affiliation to a family.	Last name
Character string	-	The name is recognized in the individual's identification documents under this title.	Father name
Year	Quantity	The number of years that have passed since a person's birth date.	Age
Men/women	Nominal	The gender of patients.	Gender
Numbering string	-	This code is a unique national identification number, and as national information systems expand and integrate, this code will eliminate the need to collect other identity information (first name and last name) or administrative details (postal code and address).	National code
Fars, Turks (Azerbaijani Turks, Fars Turks), Kurdish, Lor, Afghan, Turkmen, Armenian, Jewish, Assyrian, and others	Nominal	Ethnic affiliation of the patient.	Ethnicity
Single/ married	Nominal	Current living situation of the patient, whether single or married.	Married or single
Under school age, illiterate, elementary, cycle, diploma, postgraduate, bachelor, master, doctorate	Ordinal	Educational status of the patient.	Education
Unemployed, farmer, simple worker, service Worker and salesman, businessman, manager and specialist, technician and assistant, craftsman, office worker, and armed forces	Nominal	Occupation from which the patient earns income.	Job
Integer	Quantity	The amount the individual receives in a month for their work.	Income
Integer	Quantity	Age of the patient at the time the illness was diagnosed.	Age of disease diagnosis
Has/has not	Quantity	Number of times fertilization has occurred (instances of pregnancy).	Number of pregnancies
Has/has not	Quantity	Number of miscarriages before 20 weeks of pregnancy.	Number of miscarriages
Has/has not	Nominal	Inability to conceive after one year of trying to get pregnant.	Infertility
Has/has not	Quantity	Number of times the individual has breastfed.	Number of breastfeeding periods
Has/has not	Nominal	Menopause in women occurs due to a decline in hormones, leading to menopausal symptoms.	Menopause
Has/has not	Nominal	If a past iodine deficiency has been diagnosed in the patient by an endocrinologist and internist.	History of iodine deficiency in the patient
Has/has not	Nominal	If hypothyroidism has been diagnosed in the patient by an endocrinologist and internist.	History of hypothyroidism in the patient
Has/has not	Nominal	If hyperthyroidism has been diagnosed in the patient by an endocrinologist and internist in the past.	History of hyperthyroidism in the patient
Has/has not	Nominal	If multinodular goiter has been diagnosed in the patient by an endocrinologist and internist in the past.	History of multinodular goiter in the patient
Has/has not	Nominal	If the patient has a history of using immunosuppressive medications in the past.	History of use of immunosuppressive medications
cm/m	Quantity	A part of the physical examination is measured by a measuring tape.	Height
Kg	Quantity	A part of the physical examination is measured by a scale.	Weight
mmHg	Quantity	A part of the physical examination is measured by a blood pressure monitor.	Blood pressure
Has/has not	Nominal	A part of the physical examination is conducted by a specialist physician.	Mass in the front of the neck
Has/has not	Nominal	A part of the physical examination assesses the sensation of something being in the throat or the swelling of the throat by a specialist physician.	The sensation of tightness in the throat area
Has/has not	Nominal	Part of the physical examination that assesses the abnormality of an individual's voice by a specialist physician.	Hoarseness (raspy voice)
Has/has not	Nominal	Part of the physical examination that evaluates the swelling of the carotid arteries located on both sides of the neck by a specialist physician.	Swelling of the neck veins
Has/has not	Nominal	Part of the physical examination assesses body balance and the sensation of spinning in the environment or oneself, weakness, and fatigue.	Dizziness
Has/has not	Nominal	Part of the physical examination that evaluates the ability to breathe normally in adequate and suitable air.	Difficulty breathing (shortness of breath)
Has/has not	Nominal	Part of the physical examination assesses the body's defensive reaction (reflex) to respiratory irritants or air pollution, or to expel secretions during illness.	Coughing
Has/has not	Nominal	Part of the physical examination evaluates the presence of a loud wheezing sound during breathing, both on inhalation and exhalation.	Wheezing
Has/has not	Nominal	Part of the physical examination assesses the functional status of the mouth or esophagus in delivering food and liquids to the stomach, the sensation of pain while eating or the inability to digest and expel food.	Difficulty swallowing
Mm	Nominal	Part of the physical examination that evaluates the size of the thyroid gland.	Thyroid size (millimeters)
Has/has not	Nominal	Part of the physical examination that assesses the symmetry of the thyroid gland.	Thyroid asymmetry
Has/has not	Nominal	Part of the physical examination that evaluates the presence of more than one nodule or gland in the thyroid gland.	Multinodular goiter
MU/L	Quantity	Part of the laboratory data assesses the thyroid-stimulating hormone from the pituitary gland.	TSH^a
MU/L	Quantity	This is a portion of laboratory data that evaluates the overall level of triiodothyronine hormone in serum, including free or protein-bound hormones.	3T^b
MU/L	Quantity	This is a portion of laboratory data that evaluates the overall level of thyroxine hormone in serum, including free or protein-bound hormones.	4T^c
MU/L	Quantity	This is a portion of laboratory data that evaluates the level of free thyroid hormones (non-protein-bound).	T3,T4^d
MIU/mL	Quantity	This is a portion of laboratory data that evaluates human chorionic gonadotropin/pregnancy tests.	HCG^e
IU/mL	Quantity	This is a part of laboratory data that evaluates thyroid peroxidase antibodies.	Anti TPO^f
mg/dL	Quantity	This is a part of laboratory data that assesses fasting serum glucose levels (after 8 h).	FBS^g
mg/dL	Quantity	This is a part of laboratory data that evaluates lipid or blood fat tests.	LDL^h
mg/dL	Quantity	This is a part of laboratory data that assesses cholesterol and triglyceride levels in the blood.	Cholesterolⁱ
g/dL	Quantity	This is a part of laboratory data that evaluates anemia/comprehensive blood cell count.	Hb^j
mg/dL	Quantity	This is a part of laboratory data that assesses cholesterol and lipoproteins.	TG^k
MIU/mL	Quantity	This is a part of laboratory data that evaluates human chorionic gonadotropin/pregnancy tests.	HCG^l
mg/dL	Quantity	This is a part of laboratory data that assesses kidney function.	Cr^m
mg/dL	Quantity	This is a part of laboratory data that evaluates liver damage.	LFT HDLⁿ
U/L	Quantity	This is a part of laboratory data that assesses the extent of tissue damage.	LDH^o
	Quality	In this diagnostic method, the size of the thyroid, thyroid nodularity, and examination for the presence of cysts are conducted.	Thyroid Ultrasound
	Nominal	The name of the medication used by the patient in the treatment of the disease.	Medication
Has/has not	Nominal	If the patient has undergone surgery for the treatment of the disease.	Thyroid Surgery
Has/has not	Nominal	If the patient has used radioactive iodine for the treatment of the disease.	Radioactive Iodine
Has/has not	Nominal	If the patient has used hormone therapy for the treatment of the disease.	Hormone Therapy
Has/has not	Nominal	If the patient has changed their lifestyle for the treatment of the disease, including changes in diet, engaging in physical activities, and altering work conditions.	Lifestyle Changes (Diet–Exercise–Occupation)
	Nominal	Name of the medication the patient is taking.	Medication Name
Date	Quantity	Year, month, and day the medication was started.	Start Date of Medication
Number	Quantity	Dosage of the medication per week.	Weekly Dosage of Medication
Time	Quantity	Duration of medication use.	Time of Medication Intake

TSH.

T3.

T4.

T4&T3.

HCG (human chorionic gonadotropin).

Anti-TPO.

FBS (fasting blood sugar).

LDL (low-density lipoprotein).

Cholesterol.

Hb (Hemoglobin).

TG (Triglyceride).

HCG (Human chorionic gonadotropin).

Cr (Creatinine).

LFT HDL (liver function Test).

LDH (lactic dehydrogenase).

Findings from the first stage of the Delphi technique

After completing the first stage of the Delphi technique, in the management axis related to demographic information, only two data elements required revision, and no data elements were removed. In the clinical axis concerning history and risk factors, five data elements were removed, and three data elements needed revision. In the section on medical history and physical examination, six data elements were removed, four data elements required revision, and five data elements were accepted. In the section on diagnostic methods for goiter, only the thyroid ultrasound data element was accepted. In the laboratory data section, only the TSH data element was accepted, while seven data elements were removed, and two data elements needed revision. In the section on medications affecting the incidence of goiter, one data element was accepted, one data element was removed, and two data elements remained that required revision. In the treatment types section, three data elements were accepted, one data element was removed, and one data element needed revision. Ultimately, as a result of the first stage of the Delphi technique, 15 data elements were accepted (Table 3).

Table 3.

Calculations conducted in the first stage of the Delphi technique.

Classification	Variables	Content Validity Ratio (CVR)	k* coefficient	Result
Demographic Information	Name	6-5/5 = 0/2	0/336	Rejected
	Last Name	5-5/5 = 0	0/336	Rejected
	Father's Name	3-5/5 = 0/4	./245	Rejected
	Age	8-5/5 = 0/6	1	Second Delphi Stage
	Gender (Female, Male)	8-5/5 = 0/6	1	Second Delphi Stage
	National ID	5-5/5 = 0	0/245	Rejected
	Ethnicity (Persian, Turk, Kurd, Lor, etc.)	6-5/5 = 0/2	0/336	Rejected
	Marital Status (Single, Married)	4-5/5 = −0/2	0/245	Rejected
	Education Level	2-5/5 = −0/6	0/207	Rejected
	Occupation	4-5/5 = −0/2	0/336	Rejected
	Income	3-5/5 = 0/4	0/336	Rejected
History and Risk Factors	Name	6-5/5 = 0/2	0/336	Rejected
	Last Name	5-5/5 = 0	0/336	Rejected
	Father's Name	3-5/5 = 0/4	./245	Rejected
	Age	8-5/5 = 0/6	1	Second Delphi Stage
	Gender (Female, Male)	8-5/5 = 0/6	1	Second Delphi Stage
	History of iodine deficiency in the patient	9-5/5 = 0/8	1	Selected
	History of hypothyroidism in the patient	9-5/5 = 0/8	1	Selected
	History of hyperthyroidism in the patient	10-5/5 = 1	1	Selected
	History of multinodular goiter in the patient	10-5/5 = 1	1	Selected
	History of immunosuppressive medication use	7-5/5 = 0/4	0/790	Second Delphi Stage
	History of surgery in the thyroid area	8-5/5 = 0/6	1	Second Delphi Stage
Medical History and Physical Examination	Height	5-5/5 = 0	0/496	Rejected
	Weight	5-5/5 = 0	0/336	Rejected
	Blood pressure	4-5/5 = −0/2	0/245	Rejected
	Mass in the front of the neck	10-5/5 = 1	1	Selected
	The feeling of tightness in the throat	8-5/5 = 0/6	0/899	Second Delphi Stage
	Hoarseness (rough voice)	9-5/5 = 0/8	0/899	Selected
	Swelling of the neck veins	8-5/5 = 0/6	0/899	Second Delphi Stage
	Dizziness	4-5/5 = −0/2	0/336	Rejected
	Difficulty breathing (shortness of breath)	7-5/5 = 0/4	0/899	Second Delphi Stage
	Coughing	5-5/5 = 0	0/660	Rejected
	Wheezing	5-5/5 = 0	0/660	Rejected
	Difficulty swallowing	8-5/5 = 0/6	0/899	Second Delphi Stage
	Thyroid size (millimeters)	10-5/5 = 1	1	Selected
	Asymmetry of the thyroid	9-5/5 = 0/8	0/899	Selected
	Multinodular goiter	9-5/5 = 0/8	1	Selected
Goiter diagnosis methods	Thyroid ultrasound	9-5/5 = 0/8	1	Selected
Laboratory Data	TSH	10-5/5 = 1	1	Selected
	T3	7-5/5 = 0/4	0/496	Rejected
	T4	8-5/5 = 0/6	1	Second Delphi Stage
	T3,T4	7-5/5 = 0/4	0/660	Rejected
	Antibody TP A	8-5/5 = 0/6	1	Second Delphi Stage
	Hb	3-5/5 = 0/4	0/245	Rejected
	Tg	3-5/5 = 0/4	0/245	Rejected
	Cr	3-5/5 = 0/4	0/207	Rejected
	Hdl	2-5/5 = −0/6	0/245	Rejected
	Ldh	2-5/5 = −0/6	0/245	Rejected
Medication (Medication Affecting the Risk of Goiter)	Medication Name	8-5/5 = 0/6	0/899	Second Delphi Stage
	Start Date of Medication	9-5/5 = 0/8	0/899	Selected
	Weekly Dosage of Medication	8-5/5 = 0/6	0/790	Second Delphi Stage
	Time of Medication	7-5/5 = 0/4	0/660	Rejected
	Thyroid Surgery	10-5/5 = 1	1	Selected
	Radioactive Iodine	10-5/5 = 1	1	Selected
	Hormone Therapy	9-5/5 = 0/8	0/899	Selected
	Lifestyle Changes (Diet–Exercise–Occupation)	6-5/5 = 0/2	0/660	Rejected

Findings from the second stage of the Delphi technique

At the end of the first stage of the Delphi technique, 15 data elements required revision, which led to their entry into the second stage of the Delphi technique. Neither of the two data elements that needed revision in the demographic information section was accepted. All three data elements that required revision were eliminated in the history and risk factors section. Two data elements were accepted in the medical history and physical examination section, and two in the laboratory data section were also accepted. In the section on medications affecting the incidence of goiter, two data elements that needed revision were removed, and in the treatment types section, one data element that required revision was rejected. At the end of this stage, four data elements were accepted, bringing the total number of accepted data elements in the MDS to 19. The final accepted elements of the MDS for goiter are presented in Table 4.

Table 4.

Accepted the final elements of the minimum data set for water quality.

Accepted items	Group
— — — — —	Demographic Information
History of iodine deficiency in the patient	History and Risk Factors
History of hypothyroidism in the patient
History of hyperthyroidism in the patient
History of multinodular goiter in the patient
Lump in front of the neck	Medical History and Physical Examination
Hoarseness
Stiffness in the throat
Difficulty breathing (shortness of breath)
Thyroid size (mm)
Hypothyroidism
Multinodular goiter
Thyroid ultrasound	Goiter diagnosis methods
TSH	Laboratory Data
T4
Anti-TPA
Date of starting medication	Medication (Medication Affecting the Risk of Goiter)
Thyroid surgery	Types of Treatment
Radioactive iodine
Hormone therapy

Discussion

In the present research, by identifying and determining relevant internal and external information sources related to the MDS for goiter, extracting and categorizing data elements, and surveying specialists in Health Information Management, medical informatics, and endocrinology through a two-round Delphi technique, the creation of a MDS for goiter was addressed. The established MDS consisted of two management and clinical axes, which included 11 and 46 data elements, respectively. Through the analysis of the CVR and CVI on these data elements, the total accepted data elements in the MDS reached 19 data elements.

Although searches conducted in Iran and other countries yielded no results for a study addressing the creation of a MDS for gout, there are studies available regarding the creation of MDSs for other diseases and chronic conditions such as thalassemia, pregnancy status, diabetic foot management, nursing data, perinatal period, health management in crises, congenital anomaly management in Iran, orthopedic injuries, and thyroid cancer in Iran and other countries.^34–37

In a study conducted by Beita Beitarfan and her colleagues, a MDS for thyroid cancer was established, which, unlike the present research, considered demographic information as essential. Additionally, due to the similarities between goiter and thyroid cancer, both studies took into account the history of hyperthyroidism and hypothyroidism in the section on history and risk factors. Furthermore, similar to the current study, TSH and Anti TPO were also deemed necessary in this research. Moreover, in this study, as in the present research, hoarseness and shortness of breath are considered essential elements. Given the nature of thyroid cancer, the established MDS includes surgical data, morphology, histopathology, tumor staging, process data, and examination findings, whereas the current study lacks these data.³⁸

Based on our searches conducted so far, a study has been created regarding the establishment of a MDS for other diseases; however, no MDS has been developed for goiter to date, and this study could serve as the first to address this issue.

In the MDS for aging created by G. Abalan Van Kan and colleagues, seven domains are covered. General information includes clinical diagnosis data, medication use, functional performance, cognitive and emotional status, cardiovascular risk profiles, nutritional status, biochemical parameters, and social status. Similar to the present study, where demographic information of the patient is considered unnecessary in the Delphi survey, in this study, patient demographic information is also not part of the data elements. Due to the nature of aging, other data in the MDS for aging differs from the MDS of the current research. Additionally, the laboratory data referred to in this study as biological parameters include tests, electrolytes (sodium, potassium, creatinine, glucose), liver function, lipids, thyroid function, vitamin B12 and folic acid, albumin and total protein levels, HbA1c, CRP, hemoglobin levels, red and white blood cell counts, platelets, and creatinine clearance, which again differs from the laboratory data of the present research.³⁹

Miraji and his colleagues, in their MDS for pregnancy status, considered 68 data elements across seven axes: referral details, maternal characteristics, maternal medical history, previous pregnancy and delivery history, current pregnancy description, ultrasound results, and laboratory test results. Unlike the present study, which, according to specialists, did not require demographic information, all demographic details of the mother, along with blood type, maternal Rh factor, the name and surname of the spouse, participation in childbirth preparation classes, and delivery date, have been categorized under maternal characteristics. Due to the importance of understanding the mother's status, maternal medical history has been included in this study, just as the present research also considers history and risk factors. Given the nature of pregnancy, referral details are part of the data elements. Additionally, due to the impact of previous pregnancies and deliveries on the current pregnancy, previous pregnancy and delivery history has also been taken into account. Unlike the present study, laboratory test results and ultrasound findings are included in the dataset. Furthermore, due to the significance of assessing the mother's condition, the description of the current pregnancy has been incorporated into this study.³⁷

In the MDS for diabetic foot created by Khadijeh Molaei and her colleagues, due to the nature of this chronic condition, data on hospitalization, medication, prevention, amputations, telehealth services, laser therapy, and rehabilitation have been considered as different components of the MDS. While in this study, the history of the disease and risk factors are considered as separate cases, in the current research, the history and risk factors are combined. Additionally, demographic information is included in this study; however, in the current study, it was deemed unnecessary. Similar to the current research, the MDS for diabetic foot includes symptoms and signs, which in the present study are addressed under the title of medical history and physical examination.³⁹

In contrast to the present study, the MDS for COVID-19 recognizes, due to the nature of the disease, exposure to incidental factors, reporting of identification, admission, and discharge data, laboratory findings, and CT imaging as essential data elements. Additionally, demographic information is present in this study, whereas it has not been considered in the current research. Similar to the present study, in this research, symptoms and signs, physical examination, and treatment are regarded as part of the MDS elements.⁴⁰

In general, it can be said that most research efforts aim to create a multi-faceted and often comparative MDS. In many of these studies, as in the current research, the focus has been on examining the country's present situation, identifying, selecting, and reviewing foreign information sources, and providing solutions or models for the nation. Although the criteria for selecting foreign information sources may vary based on the subject of study, the methods for examining and analyzing the findings remain largely similar.

Study limitations

Although the current study's development of a MDS for goiter using a structured methodology and expert consensus has notable strengths, several limitations should be recognized.

First, the selection of experts for the Delphi process, although based on relevant expertise in Health Information Management, medical informatics, and endocrinology, was restricted to professionals within Iran. This could impact the applicability of the findings to wider international settings where healthcare systems, clinical practices, and documentation standards may vary.

Second, the study mainly concentrated on the conceptual design of the MDS, and the proposed data elements were not tested through actual implementation in HIS or real-world clinical workflows. Therefore, potential technical, operational, or usability issues related to integrating this MDS into existing digital health systems remain unexamined.

Third, although the study used robust methods like the CVR and CVI to validate the selected data elements, other psychometric properties such as reliability, feasibility, and inter-rater agreement were not evaluated. Future research should incorporate these aspects to strengthen the robustness and applicability of the proposed MDS. Finally, the exclusion of demographic data elements based on the Delphi panel's consensus might limit certain uses of the dataset in epidemiological research or population-level reporting.

Although this decision was justifiable within the scope of the study, it may need reevaluation for broader health data standards. In summary, although this study marks a pioneering step in standardizing data collection for goiter, addressing these limitations in future research and system validations will be critical to maximize its usefulness and adoption.

Conclusion

Based on the findings obtained in this research from the perspective of specialists, the elements of the MDS for goiter include history and risk factors, medical history and physical examination, methods for diagnosing goiter, laboratory data, medications, and types of treatment. A MDS has the potential to standardize data and overcome the issue of low-quality goiter data in Iran by providing coherent, complete, and uniform data elements. Therefore, the use of this MDS is beneficial for effective policymaking and planning to provide more efficient and cost-effective services to individuals. Additionally, it seems that in the country, due to issues such as a lack of attention to recording information related to goiter care, untimely access to medical records, diversity of health forms, the presence of redundant data elements in health forms, the absence of standardized data elements, and the lack of integrated information systems at the national level, the design and implementation of a MDS for goiter is essential.

Footnotes

Acknowledgements

The authors would like to thank the participants of the study. They would also be grateful for the cooperation of the Hospital settings affiliated with the Kerman University of Medical Sciences.

ORCID iDs

Sadrieh Hajesmaeel-Gohari

Farzaneh Behnam

Ethics approval and consent to participate

This study was approved by the Research Ethics Committee of the Kerman University of Medical Sciences Research Council (Number: IR.Kmu.Rec.1401.368) and conducted following the guidelines of the Declaration of Helsinki. By the opinion of the Ethics Committee mentioned above and given the fact that no information about participants is provided in this paper, participants who participated in this study gave informed consent to participate in this research.

Author contributions

F.B., S.N, S.H.G, P.A, and M.M.Gh contributed to the conception and design of the study, acquisition and interpretation of the data, and drafting of the paper. S.N. was primarily responsible for the statistical analysis of the data. All of the authors read and approved the final version of the submitted manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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The minimum data set for goiter disorder in Iran

Abstract

Background and objective

Methods

Results

Conclusion

Keywords

Introduction

Method

Phase 1: Identification of relevant data elements

Phase 2: Development and validation of the evaluation instrument

Phase 3: Consensus building using the Delphi technique

Validity and reliability assessment

Data analysis

Results

Findings from the first stage of the Delphi technique

Findings from the second stage of the Delphi technique

Discussion

Study limitations

Conclusion

Footnotes

Acknowledgements

ORCID iDs

Ethics approval and consent to participate

Author contributions

Funding

Declaration of conflicting interests

References