
==== Front
BMC Health Serv Res
BMC Health Serv Res
BMC Health Services Research
1472-6963
BioMed Central London

11498
10.1186/s12913-024-11498-8
Research
Determining the minimum data set of geriatric assessment at the Iran primary health care referral system: shifting from fragmentation to integration care for older people
Mirzaeian Razieh 12
Shafiee Mohsen 3
Afrash Mohammad Reza 45
http://orcid.org/0000-0002-8882-5765
Kazemi-Arpanahi Hadi h.kazemi@abadanums.ac.ir

6
1 https://ror.org/0506tgm76 grid.440801.9 0000 0004 0384 8883 Department of Health Information Management, Shahrekord University of Medical Sciences, Shahrekord, Iran
2 https://ror.org/0506tgm76 grid.440801.9 0000 0004 0384 8883 Department of Modeling in Health Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran
3 https://ror.org/03w04rv71 grid.411746.1 0000 0004 4911 7066 Department of Nursing, Abadan University of Medical Sciences, Abadan, Iran
4 https://ror.org/03w04rv71 grid.411746.1 0000 0004 4911 7066 Department of Artificial Intelligence, Smart University of Medical Sciences, Tehran, Iran
5 https://ror.org/03w04rv71 grid.411746.1 0000 0004 4911 7066 Artificial Intelligence in Medical Sciences Research Center, Smart University of Medical Sciences, Tehran, Iran
6 https://ror.org/03w04rv71 grid.411746.1 0000 0004 4911 7066 Department of Health Information Technology, Abadan University of Medical Sciences, Abadan, Iran
7 9 2024
7 9 2024
2024
24 103923 6 2023
27 8 2024
© The Author(s) 2024
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
Background

Geriatric assessment (GA) is a multidimensional process that disrupts the primary health care (PHC) referral system. Accessing consistent data is central to the provision of integrated geriatric care across multiple healthcare settings. However, due to poor-quality data and documentation of GA, developing an agreed minimum data set (MDS) is required. Therefore, this study aimed to develop a GA-MDS in the PHC referral system to improve data quality, data exchange, and continuum of care to address the multifaceted necessities of older people.

Methods

In our study, the items to be included within GA-MDS were determined in a three-stepwise process. First, an exploratory literature search was done to determine the related items. Then, we used a two-round Delphi survey to obtain an agreement view on items to be contained within GA-MDS. Finally, the validity of the GA-MDS content was evaluated.

Results

Sixty specialists from different health geriatric care disciplines scored data items. After, the Delphi phase from the 230 selected items, 35 items were removed by calculating the content validity index (CVI), content validity ratio (CVR), and other statistical measures. Finally, GA-MDS was prepared with 195 items and four sections including administrative data, clinical, physiological, and psychological assessments.

Conclusions

The development of GA-MDS can serve as a platform to inform the geriatric referral system, standardize the GA process, and streamline their referral to specialized levels of care. We hope GA-MDS supports clinicians, researchers, and policymakers by providing aggregated data to inform medical practice and enhance patient-centered outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-024-11498-8.

Keywords

Geriatric assessment
Referral and consultation
Primary health care
Minimum data set
issue-copyright-statement© BioMed Central Ltd., part of Springer Nature 2024
==== Body
pmcBackground

The aged population is growing faster than any other age group worldwide [1]. It’s estimated that by 2050, people aged 60 years or older will make up over 21.4% of the global population. This percentage is predicted to triple to more than 27.7% by the year 2100 [2]. This demographic shift is having a significant impact on developing countries, which are home to two-thirds of the world’s aging population. Iran is one such country where the population is shifting from youth to old age. Currently, 10% of Iran’s population is aged 60 or older, and projections indicate that by 2050, the number of people aged 65 and over will make up 31% of the country’s total population [3, 4]. Population aging has negative impacts on the economy, society, and health fields [5]. This period of life closely contributes to a similar rise in the wide variety of chronic and costly diseases. Older people are hospitalized more frequently than other age groups, exposing them to iatrogenic diseases and leading to physical and psychological complications [6, 7]. Declining health in older adults has been linked to functional disabilities, dependencies, and comorbidities. Additionally, psychosocial stressors such as loneliness, the loss of loved ones, loss of individuality, and changes in socioeconomic status can increase the risk of mental health issues in older people [8]. Therefore, it is crucial to address the health needs of this vulnerable group by considering their economic and social status and prioritizing the affordability of their healthcare should be the primary focus of health policymakers [9, 10]. Given the high incidence of undiagnosed and untreated health conditions in older adults, it is necessary to establish an effective geriatric assessment (GA) plan [11]. GA involves identifying a list of health problems related to older people’s general health status, including comorbidities, functional, cognitive, social, nutritional, and psychological aspects [12, 13].

Despite the broadly encouraged worth of preventive and promotive care, most healthcare systems still mainly focus on treating single diseases. This approach leads to inefficient, wasteful, and fragmented care for older adults, causing patient confusion, low participation in treatment, and even treatment faults [14]. Even within healing medicine, care for older people is facing a crisis, remarkable fragmentation, and aggressiveness of emergency care rather than thoughtful planning and effective care management. This fragmentation in service delivery impedes proactive, person-centered, and integrated care for older adults [15, 16]. To overcome these problems, effective communication between primary health care (PHC) and specialist care is crucial [17].

PHC level serves as a gateway to providing healthcare services and has a determining effect on the economic and social progress of nations. Providing longitudinal, comprehensive, and coordinated care at the PHC level has a direct influence on public health and reduces the number of non-essential visits to healthcare settings [18, 19]. However, PHC providers report a high volume of outpatient visits daily, making it impossible to allocate appropriate time for examining and performing a comprehensive assessment of older people’s health status [20, 21]. Additionally, PHC providers are less equipped to manage complex clinical situations, so they need a system that simplifies the process of seeking help from experts or using higher-level resources for direction in the management of clinical events without shifting accountability [22].

In this regard, a referral system is a fundamental necessity for connecting primary care to specialty care [23]. The traditional referral system has several challenges that include the accumulation of errors in the next stages, the absence of a comprehensive and uniform referral system, the direct referral to medical centers by bypassing lower levels, which causes an increase in the burden of hospitals and disrupts service delivery, lack of expert and motivated workforce, failure to comply with the guidelines intended for an effective referral system, inadequate responsibility to control needless referrals at each level, and insufficient back referral system of trivial cases that come straight to the higher level [24–26].

These problems are partly due to the lack of a nationally agreed framework to guide the workforce to collect required data and perform documentation processes efficiently [27, 28]. However, the current referral processes in Iran PHC are often paper-based and poorly documented. The data relating to older people has not been received by the next health settings [29, 30]. Paper-based referrals are particularly difficult to track, information is regularly inadequate and does not encompass all important data required for the delivery of quality care. These referral methods are susceptible in the fragmented ambulatory environment where information is transferred between health centers physically [31]. To address these challenges, we developed a minimum data set (MDS) to standardize and improve the quality of GA data [32–34]. Having an agreed MDS enables the generation of nationally comparable and reliable data, regardless of how the data is gathered. It allows for consistent assessment across various authorities, organizations, and subdivisions, and encourages more efficient data gathering by reducing duplication of effort [35]. Hence, the objective of this study is to establish an MDS for this purpose. This MDS can serve as a foundation for developing a consistent referral system for older people throughout the primary healthcare system.

Methods

Study design

This study is a mixed-method investigation performed in 2023 in Iran. It utilized both quantitative and qualitative methods to design GA-MDS. First, a review of scientific and grey literature was conducted to extract potential data items related to GA. Then, a two-round Delphi survey was used to obtain the perspective of experts. Finally, two additional supplementary surveys were conducted to calculate the content validity ratio (CVR) and content validity index (CVI) of the final GA-MDS.

Literature review

As part of the literature review, scientific databases, including Web of Science, PubMed, Scopus, Google Scholar, Society for Information Display (SID), and MagIran, were searched to retrieve relevant data sources and data collection projects related to GA. The search utilized keywords such as “referral system”, “information system”, “primary care”, “registry system”, “data management”, “MDS”, “minimum data set”, “minimum dataset”, “required data set”, “core data items”, along with elderly-related terms (elderly, geriatric, aged, aging, senior, older age, older adults, older person, older people, older population, older individual, older patient) in individual or combined form. The search was conducted in English and Persian languages up until 2023, with no restrictions applied regarding the publication date. A systematic literature review was not conducted, and instead, a formative review was performed to extract possible data items. Additionally, grey literature, such as geriatric health websites and records, was reviewed until data saturation was achieved, where no new piece of data item emerged from the sources. Finally, relevant data points were extracted and compiled into a primary checklist, which was organized into four distinct sections: administrative, clinical assessment, body systems assessment, and psychology assessment items.

Delphi study

Following the preparation of the initial checklist in the previous step, a Delphi survey consisting of two rounds was conducted to identify the most significant data items among the primary extracted ones. The first and second rounds were held two months apart. During this period, the data collection tool was refined based on the feedback received from the experts. The same panel members participated in both rounds, and a 5-point Likert scale was used to evaluate responses. There is no standard agreement level for Delphi studies, but some suggest a threshold of ≥ 70% for each round [36–38]. In this study, an 80% agreement level was set for each item to be included in the GA-MDS. This means that items with an agreement level of less than 50% and a mean score of < 3.5 were excluded. Items with an agreement level of 50–79% and a mean score ranging from 3.5 to < 4, as well as any additional data items suggested by the expert panel, were evaluated in the second round. Any items with an agreement threshold of 80% or more were accepted in the first round [39, 40]. In the second round of Delphi, the experts’ feedback and comments on the initial items from the first round were taken into consideration. The acceptance criteria for the data items remained the same as in the first round. Finally, the collected data was analyzed using SPSS 22 (SPSS Inc., Chicago, IL), and a statistical significance level of p-value < 0.05 was set.

Panel of experts

In Delphi surveys, a panel of 15–20 experts is typically used. However, we selected a sample of 60 experts to reduce errors [41]. The participants were selected using a purposive/non-random sampling method. The criteria for participation were as follows: (1) have sufficient expertise in the care and treatment of older people, (2) have more than three years of practical skill, and, if possible, have related scientific publications. The panel of experts comprised 60 participants, including psychiatrists, general physicians, gerontologists, geriatrics specialists, nursing geriatrics, community health nursing, cardiologists, urologists, neurologists, respiratory specialists, and epidemiologists was formed. The panel of experts used to develop and evaluate the MDS remained consistent across the Delphi phase and content evaluation. Specifically, the same group of experts participated in both stages of the process.

Evaluating the content validity of GA-MDS

To compute the ultimate multidimensional scaling MDS, we evaluated the temporal information of the initial MDS, utilizing the phases as the fundamental metric for analysis. During the Delphi phase of our study, we relied on the input of 60 panel experts to evaluate the MDS content. The data collection period for this phase lasted three months. Following the Delphi stage, a group of experts was tasked with assessing the content of the MDS using an initial checklist. To facilitate the evaluation process, the team enlisted the services of ten individuals, who were responsible for the collection of data in a blind manner. These individuals subsequently followed up on the return of the initial checklist to gather relevant information for further analysis. The MDS content validity was checked in the following steps:

CVI

The most commonly used way to measure an instrument’s content validity is the CVI calculation. The CVI can be calculated for each item on the instrument (known as item level-CVI or I-CVI) as well as for the instrument as a whole (known as the instrument level-CVI). To assess the CVI, experts rate each item based on its relevance or representativeness on a 4-point Likert scale ranging from 1 (not relevant or not representative) to 4 (extremely relevant or representative). The I-CVI is calculated by determining the proportion of experts who rated an item as 3 or 4, divided by the total number of experts. It is important to note that using the CVI as a measure of inter-rater agreement can lead to an inflation of agreement due to chance factors. To address this issue, Lynn has provided guidelines for the number of experts and the minimum number of experts who must agree with an item or instrument’s content to achieve an acceptable CVI, using the standard error of the proportion. So, the CVI evaluates the relevancy of the items to the main purpose of the instrument based on experts’ opinions. In the present study, the items selected from the Delphi survey were sent to the panel of experts, and they were asked to assign an importance value for the relevancy of items using a four-point Likert scale from not relevant to completely relevant. The CVI was calculated using Formula 1. The acceptable value for CVI was considered 0.78% [42–45]. To eliminate this chance, Scale-CVI (universal agreement) and (average) were calculated. It is suggested that adequate S-CVI should be considered 0.8 to indicate content validity. (see formula 1)

1 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{array}{l}\:\text{C}\text{V}\text{I}\\=\frac{\text{t}\text{h}\text{e}\:\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{a}\text{l}\text{i}\text{s}\text{t}\text{s}\:\text{w}\text{h}\text{o}\:\text{a}\text{s}\text{s}\text{i}\text{g}\text{n}\:\text{a}\text{n}\:\text{i}\text{m}\text{p}\text{o}\text{r}\text{t}\text{a}\text{n}\text{c}\text{e}\:\text{v}\text{a}\text{l}\text{u}\text{e}\:\text{o}\text{f}\:3\:\text{o}\text{r}\:4\:\text{f}\text{o}\text{r}\:\text{e}\text{a}\text{c}\text{h}\:\text{i}\text{t}\text{e}\text{m}}{\text{t}\text{h}\text{e}\:\text{t}\text{o}\text{t}\text{a}\text{l}\:\text{n}\text{u}\text{m}\text{b}\text{e}\text{r}\:\text{o}\text{f}\:\text{s}\text{p}\text{e}\text{c}\text{i}\text{a}\text{l}\text{i}\text{s}\text{t}\text{s}.}\end{array}$$\end{document}

Kappa Statistic coefficient

The Kappa statistic is a widely recognized measure for evaluating inter-rater agreement. Yet, it does have its limitations, and the proportion of the agreement index is often deemed basic. In response to these shortcomings, the CVI was developed, which assesses inter-rater agreement based on relevance and non-relevance. The CVI has an edge over kappa and other inter-rater agreement measures that solely focus on relevance. To determine the CVI, one must first calculate the probability of chance agreement using a specific formula. The I-CVI is then calculated for each item, and the Kappa modified (k*) can be derived from the values of both the probability of chance agreement (Pc) (see formula 2) and the I-CVI. Several different standards have been proposed for evaluating kappa, including the Landis and Koch standard, which deems a value above 0.60 to be substantial, and the Fleiss Cicchttie and Sparrow standards, which suggest that a value of 0.75 or higher is excellent. The Kappa coefficient is an index that eliminates the possibility of chance agreement between several raters [46]. In our study, first, the likelihood of chance agreement was computed according to Formula 2, where N indicates the number of experts and A is the number of experts who agreed that the item was relevant. Then, the Kappa coefficient was measured for each item according to Formula 3. The evaluation for K* is that values greater than 0.74 indicate that the item was excellent; values between 0.6 and 0.74 mean good, and the K* values between 0.4 and 0.59 indicate that the item is fair.

2 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{pc}}\,{\rm{ = }}\,{\rm{[N!/A!}}\,{\rm{(N}} - {\rm{A)!]}}\,{\rm{*}}\,{\rm{[0}}{\rm{.5]}}{\,^ \wedge }\,{\rm{N}}$$\end{document}

3 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\text{K}\text{*}\:=\frac{(\text{I}-\text{C}\text{V}\text{I}-\text{P}\text{C})}{\:(1-PC)}$$\end{document}

CVR

One of the most reliable techniques for ensuring the content validity of an instrument is to gather a group of experts who can evaluate the relevance of each item. Among the many methods available for measuring content validity, the CVR developed by Lawshe in 1975 has gained widespread popularity. This approach involves asking experts to classify each item as “Essential,” “Useful, but not essential,” or “Not necessary.” The items that receive a critical mass of “Essential” ratings are retained in the final form, while those that fall short are eliminated. This process helps to ensure that the final instrument is both effective and reliable, providing accurate results. CVR shows the necessity of the items for operating a construct [47]. In our study, to measure the CVR, the experts were requested to score each item using a three-point Likert scale, where a score of 1 shows the non-necessity and a score of 3 shows the necessity of an individual item. CVR was calculated according to Formula 4. In this formula Ne is the number of panelists representing “essential” and N is the total number of panelists.

4 \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:\text{C}\text{V}\text{R}\:=\frac{(\text{N}\text{e}\:-\:\text{N}\:/\:2)}{\:(\text{N}\:/\:2)}$$\end{document}

Results

Extracting potential data items related to the GA

After conducting an extensive search, a list of primary items was compiled under the guidance of a geriatric nurse and two HIM experts. These items were organized into a checklist and forwarded for validation through the Delphi survey. All the possible data items related to the GA process were extracted and a maximum of probable data items was determined. The initial set of items were classified into four classes in a checklist.

Participant characteristics

The panel of experts comprised 60 participants, including psychiatrists, general physicians, gerontologists, geriatrics specialists, nursing geriatrics, community health nursing, cardiologists, urologists, neurologists, respiratory specialists, and epidemiologists was formed. Table 1 shows the characteristics of the expert panel.

Table 1 Characteristics of the expert panel

Variables	Frequency	Percentage	
Gender	
Female	36	60	
Male	24	40	
Educational	
Psychiatrists	4	6.67	
General physician	6	10	
Gerontologist	8	13.33	
Geriatrics specialist	2	3.33	
Nursing geriatric	18	30	
Community health nursing	6	10	
Cardiologist	3	5	
Urologist	3	5	
Neurologist	2	3.33	
Respiratory specialist	4	6.67	
Epidemiologists	4	6.67	
Age	
30–40	26	43.33	
40–50	20	33.33	
> 50	14	22.34	
Work experience	
< 10	12	20	
10–15	20	33.33	
15–20	18	30	
20–25	6	10	
> 25	4	6.67	
Total	60	100	
Mean	SD	
Age	35.4	± 5.4	
Work experience	13.32	± 7.2	

The present study employed a Delphi survey in two rounds to identify the important primary components of an initial checklist. The checklist comprised 256 items grouped into four categories. Panel experts kept 205 items in during the first round of the survey, while they rejected 51 items. They considered for inclusion but ultimately omitted, in the second round, five items. The outcome was a primary checklist of 200 essential items, as determined by the panel of experts. Table 2 provides an illustrative example of the Delphi survey results. After the completion of the Delphi phase, the MDS was formulated and made available for assessment. In the Delphi phase, the Wilcoxon test and Bonferroni correction were performed to reduce type I error and ensure the accuracy of the answer.

Table 2 CVI and Delphi phase for the cardiovascular examination class

Items	Delphi phase	Calculation of I-CVI	Final Decision	
Round 1	Round 2	
Mean (± SD)	Median	Mean (± SD)	Median	Relevant
(Rating 3 or 4)	I-CVIs	
Rhythm	4.87 (± 0 0.044)	5	-	-	60	1	Kept	
Edema	4.69 (± 0.087)	5	-	-	60	1	Kept	
Skin signs and symptoms	4.68 (± 0.087)	5	-	-	58	0.97	Kept	
Nails signs and symptoms	4.88 (± 0.065)	5	-	-	59	0.99	kept	
Face signs and symptoms	4.87 (± 0 0.044)	5	-	-	60	1	Kept	
Eyes signs and symptoms	4.78 (± 0. 0.087)	5	-	-	57	0.95	Kept	
Mouth signs and symptoms	2.68 (± 0.16)	2	3.68 (± 0.26)	3	50	0.84	Kept	
Neck signs and symptoms	4.68 (± 0.087)	5	-	-	60	1	Kept	
Chest configuration	4.08 (± 0.080)	4	-	-	51	0.85	Kept	
Sound of heart	4.68 (± 0.087)	5	-	-	60	1	Kept	
Structural assessment	1.38 (± 0.079)	1	-	-	26	0.44	Removed	
Halter monitoring	1.28 (± 0.079)	1	-	-	28	0.47	Removed	
Hypotension orostatic	4.88 (± 0.065)	5	-	-	60	1	Kept	
Referral institute	4.88 (± 0.065)	5	-	-	60	1	Kept	
Hypertension	4.68 (± 0.087)	5	-	-	58	0.97	Kept	
Quality of pulse (power)	4.88 (± 0.065)	5	-	-	59	0.99	kept	
Dyspnea	4.68 (± 0.087)	5	-	-	58	0.97	Kept	
Chest pain	4.88 (± 0.065)	5	-	-	59	0.99	kept	
Cardiovascular risk factor	4.88 (± 0.065)	5	-		60	1	Kept	
Symmetry of the extremities	4.78 (± 0. 0.087)	5	-	-	57	0.95	Kept	
Varicosities	4.88 (± 0.065)	5	-	-	59	0.99	kept	
Arterial pulses	4.88 (± 0.065)	5	-	-	60	1	Kept	
Grading of pulses	4.78 (± 0. 0.087)	5	-	-	57	0.95	Kept	
Lymphatic system	4.88 (± 0.065)	5	-	-	60	1	Kept	
Arterial supply in the lower extremities	4.08 (± 0.080)	4	-	-	51	0.85	Kept	
Capillary refill time	4.88 (± 0.065)	5	-	-	60	1	Kept	
Retrograde filling	4.08 (± 0.080)	4	-	-	51	0.85	Kept	

Checking validity

After the Delphi survey, selected items were sent to a panel of experts to calculate the CVI and 200 items were identified as relevant items. Table 3 shows the CVI of the cardiovascular examination items as a sample of GA-MDS. The S-CVI was also computed to remove the chances of agreement (Table 3).

Table 3 S-CVI for the cardiovascular examination class as a sample of GA-MDS

Cardiovascular examination class	The number giving a rating of 3 or 4 to the relevancy of the item	I-CVIs	S-CVI/UA
The proportion of items on a scale that achieves a relevance rating of 3 or 4 by all the experts	S-CVI/Ave
Average of the I-CVIs for all items on the scale	
Rhythm	60	1	S-CVI: 0.85

S-CVI/UA: 0.48

	S-CVI/Ave: 0.903	
Edema	60	1			
Skin signs and symptoms	58	0.97			
Nails signs and symptoms	59	0.99			
Face signs and symptoms	60	1			
Eyes signs and symptoms	57	0.95			
Mouth signs and symptoms	50	0.84			
Neck signs and symptoms	60	1			
Chest configuration	51	0.85			
Sound of heart	60	1			
Hypotension orostatic	60	1			
Referral institute	60	1			
Hypertension	58	0.97			
Quality of pulse (power)	59	0.99			
Dyspnea	58	0.97			
Chest pain	59	0.99			
Cardiovascular risk factor	60	1			
Symmetry of the extremities	57	0.95			
Varicosities	59	0.99			
Arterial pulses	60	1			
Grading of pulses	57	0.95			
Lymphatic system	60	1			
Arterial supply in the lower extremities	51	0.85			
Capillary refill time	60	1			
Retrograde filling	51	0.85			

CVR and modified kappa

CVR and kappa were computed for 200 items. Of them, 195 items remained and five items were removed. Table 4 demonstrates the CVR and kappa of each item of the cardiovascular examination class.

Table 4 CVR, modified Kappa

Items of cardiovascular examination class MDS	The number giving a rating of 3 or 4 to the relevancy of the item	CVR	pc	K	Interpretation	
Rhythm	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Edema	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Skin signs and symptoms	58	0.94	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	∼ 1	Excellent	
Nails signs and symptoms	59	0.97	0/01× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Face signs and symptoms	60	1	0/01× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	1	Excellent	
Eyes signs and symptoms	57	0.9	0/048× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Mouth signs and symptoms	50	0.67	0/048× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Neck signs and symptoms	60	1	0/02 × \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	1	Excellent	
Chest configuration	51	0.7	4× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Sound of heart	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Hypotension orostatic	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Referral institute	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Hypertension	58	0.94	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	∼ 1	Excellent	
Quality of pulse (power)	59	0.97	0/01× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Dyspnea	58	0.94	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	∼ 1	Excellent	
Chest pain	59	0.97	0/01× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Cardiovascular risk factor	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Symmetry of the extremities	57	0.9	0/048× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Varicosities	59	0.97	0/01× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Arterial pulses	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Grading of pulses	57	0.9	0/048× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Lymphatic system	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Arterial supply in the lower extremities	51	0.7	4× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	
Capillary refill time	60	1	0/009× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-56}$$\end{document}	1	Excellent	
Retrograde filling	51	0.7	4× \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\:{10}^{-52}$$\end{document}	∼ 1	Excellent	

Final GA-MDS

After the literature review step, Delphi survey, and validation of content. The final platform of GA-MDS with 195 items was prepared. The MDS items in their final form can be referred to from Tables 5, 6, 7, and 8, which are presented in the appendix for reference.

Table 5 Administrative items

Class	Data items	Content definition	
Referral information	Date of referral					
	Chief compliant					
	Reason of referral					
	Blood group	A	RH +		
		RH -		
		B	RH +		
		RH -		
		AB	RH +		
		RH -		
		O	RH +		
		RH -		
	Place of primary assessment	Clinic				
		Emergency department			
		Health care setting			
		Nursing home			
		Other geriatric care centers		
Demographic characteristics	Gender	Male				
		Female				
	Age	Years				
	Marital status	Married				
		Single				
		Divorced				
		Widow				
		Other, unspecified			
	Educational level	Illiterate				
		Elementary			
		High school			
		University				
	Racial status	Lor				
		Kurd				
		Turkish				
		Fars				
		Other				
	Occupation status	Retired				
		Unemployed			
		Working part-time			
		Working full time			
		Housewife				
	Income level	Low income			
		Middle income			
		High income			
	Family support					
	Insurance status					
		Health care setting			
		Home	Private house	Urban	Alone	
	Residence				With offspring	
					With wife	
				Rural	Alone	
					With offspring	
					With wife	
			Rental house	Urban	Alone	
					With offspring	
					With wife	
				Rural	Alone	
					With offspring	
					With wife	
		Homeless	

Table 6 Clinical assessment

Class	Data items	Content definition		
Past medical history	Comorbidities	Disease name		
	Family history			
	Previous surgery(s)			
		None		
		If yes; location	Head	
			Neck	
			Arm	
			Hand	
			Abdomen	
			Back	
			Leg	
	History of injury	Cause of injury	Falling down	
			Car Accident	
			Motor accident	
			Other specified	
			None specified	
		Complication of injury	None	
			Fracture	
			Dislocation	
			Wound	
			Cerebral hemorrhage	
			Stretch	
			Sprain	
			Brain damage	
			Spine damage	
			Internal damage	
			Others	
	History of poising	None		
		Drug poising		
		Corrosive ingestion		
		Overdose		
		Gas poisoning		
	Addiction			
	Tabaco use	Past smoker		
		Current smoker		
		Never smoker		
	Drug history	Present drug use	Names	
		Allergic to drug		
		Previous drug used	Names	
	Blood pressure	Systole/diastole		
Vital sings	Respiratory rate			
	Pulse rate			
	Body temperature			
	Pain	None		
		Yes		
		Pain score (0–10)		

Table 7 Physiological assessment

Class	Data items	Content definition	
Cardiovascular examination		Rhythm	Regular				
			Irregular				
		Edema	None				
			Pitting edema				
			Non-pitting edema				
			Temperature		Normal		
					Warm		
					Cold		
		Skin signs and symptoms	Tendon xanthomata				
			Pruritus				
			Eruptive xanthomata				
			Erythema marginatum				
			Color		Normal		
					Abnormal		
		Nails signs and symptoms	Normal				
			Splinter hemorrhages				
			Clubbing				
		Face signs and symptoms	Normal				
			Widely set eyes				
			Strabismus				
			Low-set ears				
			An upturned nose				
			Hypoplasia of the mandible				
			Moon faces				
			Puffy eyelids				
			Lichtstein’s sign				
			Larlobe crease				
		Eyes signs and symptoms	Normal				
			Xanthelasma				
			Opacities				
			Displacement of the lens				
			Hypertelorism				
			Roth’s spots				
		Mouth signs and symptoms	Normal				
			Petechiae				
		Neck signs and symptoms	Normal				
			Webbing				
		Chest configuration	Normal				
			Pectus excavatum				
			Pectus carinatum or pigeon chest				
		Sound of heart	Normal				
			Murmurs present				
		Hypotension orostatic					
		Hypertension	Primary				
			Secondary				
		Quality of pulse (power)	+				
			++				
			+++				
			++++				
		Dyspnea	None				
			Paroxysmal natural dyspnea (PND)				
			Orthopnea				
			Dyspnea during exercise				
			Dyspnea during rest				
		Chest pain	None				
			Yes				
			If yes; the severity		0–10		
			Pain onset		Suddenly		
					Gradually		
			Radiation		None		
					Neck		
					Left shoulder		
					Right shoulder		
					Jaw		
			Quality		Sharp		
					Compress		
					Dull		
					Stabbing		
					Burning		
					Crushing		
					Throbbing		
					Nauseating		
					Shooting		
					Twisting or stretching		
			Duration		30–60 minutes		
					> 60 minutes		
					< 30 minutes		
			Reduction factors		None		
					Rest		
					Drug		
			Aggravating factors		Activity		
					Stress		
					Eating		
					Ambient heat		
		Cardiovascular risk factor	Low-density lipoprotein (LDL) abnormality				
			Obesity				
			Smoking				
			High-density lipoprotein (HDL) abnormality				
			Alanine transaminase (ALT) abnormality				
			Acute coronary syndrome				
			Cerebrovascular accident (CVA)				
			Old myocardial infarction (MI)				
			Family history				
		Symmetry of the extremities					
		Varicosities					
		Arterial pulses	Normal				
			Abnormal				
		Grading of pulses	Absent		0		
			Diminished		1		
			Normal		2		
			Increased		3		
			Bounding		4		
		Lymphatic system	Pain				
			Single				
			Matted				
			Generalized				
			Lymphangitis				
			Lymphedema				
		Arterial supply in the lower extremities	Normal		(10–15s)		
			Moderate ischemia		(15–30s)		
			Severe ischemia		(> 40s)		
		Capillary refill time	Normal		(3 to 5 seconds)		
			Abnormal		(> 5 s)		
		Retrograde filling	Normal		(30 seconds)		
			Abnormal		(> 30 s)		
Breast examination		Mass or swelling					
		Pain					
		Nipple discharge					
		Change in skin over breast					
		Arm power	Left		0–5		
			Right		0–5		
		Leg power	Left		0–5		
			Right		0–5		
		Arm movement	Symmetric				
			Asymmetric				
		Leg movement	Symmetric				
			Asymmetric				
		Pupil size	Left		1–8		
			Right		1–8		
		Reaction pupil	Fast				
			Sluggish				
		Type of pupil	Argyll robertson				
			Horner’s syndrome				
			Essential anisocoria				
			Adie’s tonic pupil syndrome				
			Sylvian aqueduct Syndrome				
			Pharmacologically dilated pupil				
Neurological examination		Smell disorder	None				
			Anosmia				
			Hyposmia				
			Parosmia				
			Phantosmia				
		Visual disorders	Reduced vision				
			Blind spots				
			Double vision				
			Droopy eyelids				
			Abnormal alignment of the eyes				
			Abnormal eye movements				
			Vision loss from stroke or tumor				
			Optic neuritis – inflammation of the optic nerve				
			Optic atrophy				
			Ischemic optic neuropathy				
			Ocular myasthenia gravis				
			Alzheimer’s disease with vision problems				
			Focal dystonia				
		Sensor neural hearing loss					
		Ataxia					
		Five senses disorder					
		Involuntary movements	Grimacing				
			Pursing of the lips				
			Myoclonus				
			Tics				
			Athetosis				
			Rapid blinking of the eyes				
			Protruding tongue				
			Smacking of the lips				
			Puckering of the lips				
			Tremors				
		Seizure					
			Normal				
			Tachypnea				
			Bradypnea				
			Apnea				
			Cheyne-Stokes breathing				
			Kussmaul breathing				
			Biot’s breathing				
		Breathing pattern	Hyperpnea				
			Hypopnea				
			Apneustic breathing				
			Agonal breathing				
			Ataxic breathing				
			Paradoxical breathing				
Respiratory examination		Color (centrally and peripherally)	Pink				
			Flushed				
			Pale				
			Mottled				
			Clubbing				
			Cyanosed				
		Symmetry of chest wall	Symmetric				
			Asymmetric				
		Using accessory muscles	None				
			Head bob				
			Tracheal tug				
			Nasal flaring				
			Substernal retractions				
			Supraclavicular				
			Suprasternal				
			Subcostal				
		Chest shape	Normal				
			Abnormal		Pigeon chest		
					Barrel chest		
					Sunken chest		
		Cough	None				
			Productive				
			Dry				
			Normal				
		Lung sound	Abnormal		Stridor		
					Wheeze		
					Grunt		
					Vocalization		
					Roncai		
					Ralls or crackle		
					Fraction rub		
Gastrointestinal examination		Appetite	Good				
			Poor				
		Dominant diet	Regular				
			Low salt/ low fat				
			Soft				
			High potassium				
			Liquid				
			Low protein				
			Low fat				
			Low salt				
			Diabetic				
			Surgical				
		Nausea					
		Diarrhea					
		Distention					
		Vomiting					
		Tenderness					
		Constipation					
		Dysphasia					
		Bloating					
		Melena					
		Indigestion					
		Abdominal pain	Right lower quadrant (RLQ)				
			Left lower quadrant (LLQ)				
			Right upper quadrant (RUQ)				
			Left upper quadrant (LUQ)				
		Liver examination	Normal				
			Abnormal				
		Spleen examination	Normal				
			Abnormal				
		Ascites					
		Gall bladder examination	Normal				
			Abnormal				
Genitourinary (GU) examination		Symptoms and signs	None				
			Frequently				
			Abdominal pain				
			Suprapubic pain				
			Hematuria				
			Flank or back pain				
			Dribbling				
			Tenderness				
			Scrotal or groin pain				
			Urine incontinency		None		
					Urge incontinence		
					Overflow incontinence		
					Functional incontinence		
					Mixed incontinence		
					Neurogenic incontinence		
					Bedwetting		
			Genital sores				
			Urinary retention				
			Genital swelling				
			Dysuria				
			Genital discoloration				
			Oliguria				
			Anuria				
			Lack of circumcision				
			Polyuria				
			Purulent or milky urine				
			Enuresis				
			Irritability				
			Location of the urethral				
			Meatus				
			Discharge at urethra				
			Inflammation of foreskin or head of penis				
			Vulvar irritation				
			Bleeding				
			Ulcerative or inflammatory lesions				
			Urethral irritation				
			Vaginal discharge				
			Enlargement of vaginal				
		Renal function	Blood urea nitrogen (BUN)		Normal	7–20 mg/dL	
					Abnormal	< 7 mg/dL	
						> 20 mg/dL	
			Microalbuminuria		Normal	Less than 30 mg	
					Abnormal	30 to 300 mg	
						More than 300 mg	
			Creatinine clearance		Normal	88–137 mL/min	
					Abnormal	< 88 mL/min	
			Urine culture (U/C)		Bacteria growing	Name	
					Non bacteria growing		
			Urine analysis (U/A)		PH	Normal	
						Acidizes	
						Alkaline	
					Wight blood cells (WBC)	Few	
						Many	
						Moderate	
					Red blood cells (RBC)	Few	
						Many	
						Moderate	
					Clarity	Cloudy	
						Clear	
					Specific Gravity	Normal	
						Abnormal	
					Protein	Seen	
						Not seen	
					Glucose	Seen	
						Not seen	
					Ketone	Seen	
						Not seen	
					Crystals	Few	
						Many	
						Moderate	
					Nitrite	Seen	
						Not seen	
					Bilirubin	Seen	
						Not seen	
			Protein urea		Normal	less than 150 milligrams	
					Abnormal	> 150 mg	
			Serum Creatinine		Normal	0.7 to 1.3 mg/dL	
					Abnormal	< 0.7 mg/dL	
						> 1.3 mg/dL	
			Glomerular filtration rate (GFR)		Normal	≥ 60	
					Abnormal	< 60	
		Mass in scrotum	Yes		Swelling		
					Tender		
					Shape	Smooth	
						Twisted	
						Irregular	
					Consistency	Liquid	
						Firm	
						Solid	
					Inguinal lymph node	Tender	
						Enlarge	
			None				
		Cremasteric reflex	Positive		Move ≥ 0.5 cm		
			Negative		Move < 0.5 cm		
		Testicular size	Normal		4–5 cm long, 3 cm high, and 2.5 cm wide		
			Abnormal		< normal size		
					>Normal size		
		Testicular position	Normal				
			Abnormal				
		Testicular consistency	Normal				
			Abnormal				
		Testicular tenderness					
		Swelling in inguinal Canal					
		Vaginal discharge	None				
			If yes		No malodorous		
					Normal vaginal secretions		
					Mucoid		
		Self-void					
			None				
		Pap smear	If yes		Normal		
					Unclear		
					Abnormal		
					Unsatisfactory		
		B-hcg	Negative				
			Borderline				
			Positive				
	Laboratory tests	Complete blood cells (CBC)	Normal				
			Abnormal		Increase RBC		
					Decrease RBC		
					Increase PLT		
					Decrease PLT		
					Decrease WBC		
					Increase WBC		
		Anemia test	None				
			Total iron-binding capacity (TIBC)		Normal		
					Abnormal		
			Serum ferritin		Normal		
					Abnormal		
			Mean corpuscular volume (MCV)		Normal		
					Abnormal		
			Mean corpuscular hemoglobin concentration (MCHC)		Normal		
					Abnormal		
			Reticulocyte count		Normal		
					Abnormal		
Hematologic examination			RBC		Normal		
					Abnormal		
			Transferrin		Normal		
					Abnormal		
	Disorders	Anemia	Microcytic anemia		Iron deficiency		
					Thalassemia		
			Normocytic anemia		Hemolytic		
					Aplastic		
			Macrocytic anemia		Anemia pernicious		
			Cycle cell anemia				
		Thrombocytopenia					
		Polycythemia vera					
		Hyper-coagulopathy and anticoagulation	International normalized ratio (INR)		Normal		
					Abnormal		
			Partial thromboplastin time (PTT)		Normal		
					Abnormal		
			Prothrombin time (PT)		Normal		
					Abnormal		
Muscle-skeletal examination		Range of motion	Normal				
			Abnormal				
		Strength of muscle	Hand (number (0–5)		0–5		
			Leg (number (0–5))		0–5		
		Deep tendon reflex	Biceps		0–4		
		Tendon name	Radial brachialis		0–4		
			Triceps		0–4		
			Distal finger flexors		0–4		
			Quadriceps knee jerk		0–4		
			Ankle jerk		0–4		
			Jaw jerk		0–4		
		Sensory examination	Normal				
			Abnormal				
		History of fracture	Positive				
			Negative				
		Osteoporosis					
		Osteopenia					
		Osteomalacia					
		Osteoarthritis					
		Rheumatoid arthritis					
		Bone mineral densitometry	Normal				
			Abnormal				
Endocrine examination		Examining the thyroid	Normal				
			Abnormal				
		Examining the patient with diabetes	Normal				
			Abnormal				
Skin examination		Rash or skin lesion	Primary lesions		Nonpalpable, flat		
					Palpable solid mass		
					Palpable fluid-filled		
					Comedo		
					Burrow		
					Cyst		
					Abscess		
					Furuncle		
					Carbuncle		
					Milia		
			Secondary lesions		Erosion		
					Ulcer		
					Fissure		
					Excoriation		
					Atrophy		
					Sclerosis		
					Scaling		
					Crusting		
			Vascular lesions		Erythema		
					Petechiae		
					Purpura		
					Ecchymosis		
					Telangiectasia		
					Spider angioma		
			Miscellaneous lesions		Scar		
					Keloid		
					Lichenification		
		Itching (pruritus)					
		Changes in hair					
		Changes in nails	Inspect the nail beds		Beau’s lines		
					Mees’ bands		
					Lindsay’s nails		
					Terry’s nails		
					Koilonychia		
					Clubbing		
					Psoriasis		
			Inspect the nails for clubbing				
			Inspect the nails for pitting				
Eye examination		Loss of vision	OD (oculus dexter)				
			OS (oculus sinister)				
			OU (oculus uterque)				
		Eye pain	OD				
			OS				
			OU				
		Diplopia	OD				
			OS				
			OU				
		Tearing and dryness	OD				
			OS				
			OU				
		Discharge	OD				
			OS				
			OU				
		Redness	OD				
			OS				
			OU				
		Visual eye symptoms	Non				
			Loss of vision		OD		
					OS		
					OU		
			Spots		OD		
					OS		
					OU		
			Flashes		OD		
					OS		
					OU		
			Loss of visual field or presence of shadows or curtains		OD		
					OS		
					OU		
			Glare, photophobia		OD		
					OS		
					OU		
			Distortion of vision		OD		
					OS		
					OU		
			Difficulty seeing in dim light		OD		
					OS		
					OU		
			Colored halos around lights		OD		
					OS		
					OU		
			Colored vision change		OD		
					OS		
					OU		
			Double vision		OD		
					OS		
					OU		
		Painful eye symptoms	None				
			Foreign body sensation		OD		
					OS		
					OU		
			Burning sensation		OD		
					OS		
					OU		
			Throbbing, aching		OD		
					OS		
					OU		
			Tenderness		OD		
					OS		
					OU		
			Headache		OD		
					OS		
					OU		
			Drawing sensation		OD		
					OS		
					OU		
		Painless eye symptoms	None				
			Tearing		OD		
					OS		
					OU		
			Itching		OD		
					OS		
					OU		
			Dryness		OD		
					OS		
					OU		
			Sandiness, grittiness		OD		
					OS		
					OU		
			Fullness of eyes		OD		
					OS		
					OU		
			Twitching		OD		
					OS		
					OU		
			Eyelid heaviness		OD		
					OS		
					OU		
			Dizziness		OD		
					OS		
					OU		
			Excessive blinking		OD		
					OS		
					OU		
			Eyelids sticking together		OD		
					OS		
					OU		
		Visual acuity	OD		Normal (20/20)		
					Abnormal (1–19/20)		
			OS		Normal (20/20)		
					Abnormal (1–19/20)		
			OU		Normal (20/20)		
					Abnormal (1–19/20)		
		Visual fields	Normal				
			Blind eye				
			Hemianopsia				
			Homonymous hemianopsia				
			Optokinetic nystagmus				
			Quadrantanopsia				
		Ocular movements	Eye alignment		Normal		
					Strabismus		
					Esotropia		
					Exotropia		
					Hypertropia		
					Alternating tropia		
			Six diagnostic cardinal positions of gaze		Medial rectus		
					Inferior oblique		
					Superior oblique		
					Lateral rectus		
					Superior rectus		
					Inferior rectus		
			Pupillary light reflex		Marcus Gunn defect or relative afferent pupillary defect (RAPD)		
					Normal		
			Near reflex		Normal		
					Abnormal		
		External and internal eye structures	Orbits		Normal		
					Raccoon eyes		
			Eyelids		Normal		
					Evidence of drooping		
					Infection		
					Erythema		
					Swelling		
					Crusting		
					Masses		
					Kearns-Sayre syndrome		
					Lagophthalmos		
					Entropion		
					Herniated orbital fat		
					Sturge-Weber syndrome		
					Chalazion		
					Molluscum contagiosum		
					Herpes zoster ophthalmicus		
					Xanthelasma		
					Stye, or acute external hordeolum		
					Blepharitis		
					Malignant tumors		
					Cutaneous horn		
			Lacrimal apparatus		Normal		
					Epiphora		
					Note proptosis and lacrimal		
					gland enlargement		
					Dacryocystitis		
			Conjunctiva		Normal		
					Inflammation		
					Pallor		
					Unusual pigmentation		
					Swelling		
					Masses		
					Hemorrhage		
					Conjunctivitis		
					Acute hemorrhagic conjunctivitis		
					Subconjunctival hemorrhage		
					Chemosis		
					Giant papillary conjunctivitis		
					Pinguecula		
					Pterygium		
					Primary acquired melanosis		
					Cnjunctival nevus		
					Dermolipoma		
			Sclera		Normal		
					Jaundice, or icterus		
					Osteogenesis imperfecta		
					Episcleritis		
					Scleromalacia perforans		
					Scleritis		
			Cornea		Normal and Arcus senilis		
					Kayser-Fleischer ring		
					Corneal ulcers		
					Marked blepharospasm		
					Keratoconus		
					Dermolipoma		
			Pupils		Size		
					Round		
					Reactive to light		
					Accommodation		
					Normal		
					Mydriasis		
					Miosis		
					Argyll Robertson pupil		
					Horner’s syndrome		
					Adie’s tonic pupil		
			Iris		Shape		
					Color		
					Presence of nodules		
					Vascularity		
					Normal		
					Coloboma		
					Iritis or iridocyclitis		
					Keratic precipitates		
					Anterior synechiae		
					Posterior synechiae		
					Visualization		
			Anterior chamber		Depth of the anterior chamber		
					Normal		
					Hypopyon		
					Hyphema		
					Shadowing of the anterior chamber		
					Narrow-angle glaucoma		
			Lens		Normal		
					Opacification		
					Cataract		
		Ophthalmoscopy	Optic disc margins		Normal		
					Abnormal		
			Cup-disc ratio		Normal		
					Abnormal		
			Color optic disc		Normal		
					Abnormal		
			Optic disc		Normal		
					Myelinated		
					Medullated		
					Nerve fibers		
			Retinal vessels		Normal		
					Abnormal		
			Macula		Normal		
					Abnormal		
			Retinal lesions		Color	Red	
						Black	
						Gray	
						Whitish	
					Shape	Linear hemorrhages	
						Round hemorrhages	
		Extraocular muscles and cranial nerve examination	Medial rectus (Oculomotor (III) nerve)				
			Lateral rectus (abducens nerve (VI))				
			Inferior rectus (Oculomotor (III) nerve)				
			Superior rectus (Oculomotor (III) nerve)				
			Superior oblique (Abducens nerve (VI))				
			Inferior oblique (Oculomotor (III) nerve)				
Era examination			Normal exam				
			Hearing loss		Conductive		
					Sensorineural		
			Vertigo				
			Tinnitus		External ear	Otitis externa	
						Bullous myringitis	
						Foreign body	
						Cerumen	
						Tympanic membrane perforation	
					Middle ear	Otitis media	
						Vascular anomalies	
						Neoplasm	
						Eustachian tube dysfunction	
						Otosclerosis	
						Serous otitis media	
					Inner ear	Vascular anomalies	
						Cochlear otosclerosis	
						Ménière’s disease	
						Labyrinthitis	
						Noise trauma	
						Drug toxicity	
						Presbycusis	
					Central nervous system	Vascular anomalies	
						Hypertension	
						Syphilis	
						Degenerative disease	
						Cerebral atherosclerosis	
				Otorrhea	None		
					Bloody discharge		
					Watery discharge		
					Infected discharge		
				Otalgia			
				Itching			
				Auditory acuity testing	Normal		
					Abnormal		
				Tympanic Membrane	Color		
					Integrity		
					Transparency		
					Position		
					landmarks of the tympanic		
					membrane		
Nose examination				Normal exam			
				Obstruction	Rhinitis		
					Nonallergic rhinitis		
					Nasal polyps		
				Discharge	Thin and watery		
					Thick and purulent		
					Bloody		
					Foul smelling		
				Epistaxis, or bleeding			
				Sinus Disease Symptoms	Maxillary	Ocular abnormalities	
						Diplopia	
						Proptosis	
						Epiphora (tearing)	
						Nasal obstruction and rhinorrhea	
						Epistaxis	
						Loosening of teeth	
					Ethmoid	Orbital swelling	
						Nasal obstruction and purulent rhinorrhea	
						Ocular abnormalities	
						Proptosis	
						Diplopia	
						Tenderness over inner canthus of eye	
					Fronta	Nasal obstruction and rhinorrhea	
						Tenderness over frontal sinus	
						Pus in middle meatus	
						Signs of meningitis	
Oral examination				Lips	Color		
					Lesion	Osler-Weber-Rendu syndrome	
						Peutz-Jeghers syndrome	
						Mucocele	
				Buccal mucosa	Normal		
					Any lesion		
				Gingivae	Normal		
					Hyperplastic gingival changes		
					Bleeding		
					gingival hyperplasia		
				Teeth	Normal		
					Abnormal		
				Tongue	Normal		
					Moist		
					Move of tongue		
					Masses		
					Ulceration		
					Lesions		
					Varices		
					Benign lipoma		
					Geographic tongue		
					Black hairy tongue		
					Scrotal, or fissured, tongue		
					Halitosis		
					Candidiasis		
					Oral hairy leukoplakia		
					Squamous cell carcinoma		
				Floor of the mouth	Normal		
					Leukoplakia		
					Erythroplakia		
					Mass		
					Ranula		
					Lesion		
				Hard and soft palates	Normal		
					Mass		
					White plaque		
					Palate edematous		
					Location of uvula	Midline (normal)	
						Abnormal	
					Clefts		
					Petechiae		
					Fellatio		
					Torus palatinus		
					Torus mandibularis		
				Salivary glands	Normal		
					Glandular enlargement		
					Parotid enlargement		
					Pain		
					Visible		
				Twelfth cranial nerve	Normal		
					Abnormal		
Pharynx examination				The Pharynx	Normal		
					Abnormal		
				The Tonsils	Normal		
					Abnormal		
				Posterior Pharyngeal Wall	Normal		
					Ulceration		
					Discharge		
					Mass		
					Infection		
				Gag Reflex	Normal		
					Abnormal		
Larynx examination				Normal			
				Abnormal			
Vaccination examination				Name of Vaccination	Pneumococci		
					Influenza		
					Other		
				Date of Vaccination			
Fall risk				Fall risk assessment	No risk	< 6	
					Moderate risk	6–13	
					High risk	> 13	
Nutrition status				Nutrition assessment class (Mini-Nutritional Assessment)	Normal nutritional status	12–14	
					At risk of malnutrition	8–11	
					Malnourished	0–7	
Malnutrition status				Malnutrition Universal Screening Tool	Low	0	
					Moderate	1	
					High	2 or more	
Independence status				Activity daily living (ADL)	Total (0-100)		

Table 8 Psychological assessment

Class	Data items	Content definition	
Suicide assessment	Suicide ideation		
	Suicide attempt		
Depression assessment (for past week)		Normal	
		Mild depression	
		Moderate depression	
		Severe depression	
		Extreme depression	
Anxiety assessment		low	
		Moderate anxiety	
		Potentially concerning levels	
Mental disorders	Cognitive impairment		
	Personality disorders		
	Alcohol and substance abuse		
	Schizophrenia		
	Delirium		
	Dementia	None	
		Primary	
		Secondary	
Mood and Anxiety Disorders	Anxiety		
	Bipolar		

Discussion

In this study, the GA-MDS was developed with 195 items classified into four domains, including administrative, clinical (past medical history and vital signs), physiological, and psychological assessments. The administrative section contains socio-demographic data such as age, gender, residence status, economic level, and legal data, which can be used as a valued source to inform policy-making decisions about healthcare and other services demanded by the older population [48, 49]. The clinical section of GA-MDS provides a comprehensive assessment of the older person’s body systems based on normal and abnormal changes. In the GA process, abnormal changes in the body are examined and the referral process of the older person to the next levels, i.e., medical specialists, is clarified. Studies have shown that chronic pain or discomfort, mobility impairments, and depression or anxiety significantly affect the well-being of older adults. Therefore, PHC providers must proactively address these concerns. To achieve this, PHC practitioners can conduct a comprehensive health assessment of older adults using the GA-MDS. With this thorough examination, PHC providers can accurately refer patients, administer appropriate treatments, and reduce the risk of disease-related complications in older adults [50]. The physical domain of GA-MDS contains data about overall physical assessment, nutrition status, independence status or activities of daily living (ADLs), malnutrition, and fall risk assessment. Frailty as an important syndrome of geriatrics is a state of clear vulnerability to stressful conditions such as diseases, etc., which leads to a gradual decrease in physiological functions during a lifetime. This syndrome increases the risk of mortality, morbidity, and falls. One of the most important ways to identify and reduce the amount of this syndrome in older people is GA [51]. In our developed MDS, it was tried to examine the degree of older adults’ dependence so that their referral can be done better. One of the most effective factors in the referral of older persons is cognitive problems and frail conditions [36]. Therefore, the developed MDS in our study contain such information, improve their referral, and on the other hand, help health policy making for better planning. Nutrition is another important factor that affects the aging process, the incidence of diseases related to old age, and the functional changes of the body in the aging process. Therefore, consistent collection and analysis of data related to the nutritional status of older adults can help improve and promote their health [52]. In the physiological section of GA-MDS, it is also possible to capture the data regarding nutritional status, the risk of falling, and dependency. In the referral process, older people depend on daily tasks that may disturb their correct referral [53]. Falling is the second cause of death and the first cause of trauma in the older adults and the primary cause of their hospitalizations. It causes irreparable complications such as mobility, mortality, and greatly increases costs [54, 55]. So, using the present MDS developed in our study can assess the complications of falls in older people in the primary referral system.

In developing countries, mental disorders are common. For example, the rate of people with depression is 79–93% and the rate of people with anxiety is 85–95%. Many of these clients do not have access to proper treatment facilities. Therefore, WHO found it necessary to have an integrated program to assess patients in the primary referral system. However, there were some barriers to the implementation of this program such as the lack of an integrated information system and the lack of implementation in many areas of these countries [56]. So, the MDS designed in our study can provide a uniform system that assesses the physical and mental condition of the older adults at the primary level of referral in different regions of the country. Thus, it can solve the barriers to the implementation of the WHO program in developing countries to some extent.

So far, no MDS has been developed specifically for GA at the PHC level. However, some studies have developed MDS for other purposes for the older population. For instance, Lutomski et al. [57] developed an MDS survey for older persons and informal caregivers (TOPICS-MDS). This MDS has the advantage of gathering uniform data on a large sample of older persons and caregivers, and it also promotes data sharing between institutions. Abellan Van Kan et al. [58] developed an MDS for geriatric clinical trials. This MDS offers an opportunity for research in older people with appropriate outcome measures and significantly facilitates meta-analysis of relevant clinical trials. Soleimani et al. [32] developed an MDS for the information management system of aged care centers in Iran, which could be used to standardize data in aged care centers and improve the quality of care and services related to the older population. Massirfufulay et al. [59] and Jennifer et al. [60] also developed two MDSs for older people living in homecare centers. Our developed MDS represents the current scientific agreement view on GA across the PHC. It is a tool for capturing data related to the assessment of individuals aged 60 years and above. This instrument is designed to identify the key factors that influence their overall well-being. We envision that further development and use of this data set will foster collaboration between three levels of the care referral system, organizations involved in geriatric care, as well as researchers, and academic institutions. Significantly, the use of GA-MDS will contribute to streamlining the overall older adults referral process. It can address data requirements and furthermore enable data reporting purposes of the older adults referral system by lessening repetition of effort and enhancing data quality. It is expected that our developed MDS will show that standardization of clinical data and documentation will, in turn, have a great influence on providing geriatric care, clinical outcomes, and decrease older adults’ treatment costs and healthcare burden.

Globally, health policymakers, gerontologists, and other health authorities have long recognized the value of integrating minimal data gathering as part of routine management in healthcare organizations and hospitals as well as an instrument to reach standardized outcome measurements in clinical research [57]. Our developed MDS would not only have the inherent benefit of collecting consistent information on a large sample of older people but also promote data exchange between involved organizations. This MDS proposed specific patient data can then be shared to enable meta-analysis as well as serve as a source for external users. In this context, the GA-MDS was developed as a tool that not only collects information on older adults but also informs the decisions of policymakers and healthcare planners.

Our study has some limitations that need to be addressed. First, the primary literature search did not take a systematic method. However, we tried to review all the articles and documents available in the field of geriatric medicine to reach data saturation and find all the possible data items to enter into the GA-MDS. In addition, respondents were asked to suggest new data items that they felt were important but not included in the initial list. Second, although a multidisciplinary team, including physicians, allied health specialists, and pharmacists were requested to contribute, respondents were mainly geriatric nurses. In this study, to design MDS, various statistical methods and measures were taken to reduce the chance of error. In our study, GA-MDS was designed and developed because a standard core dataset is required to develop a uniform older adults’ referral information system. Therefore, in future studies, an external evaluation is suggested to refine some data categories.

Conclusions

The establishment of the MDS is a crucial first step in the development of an electronic referral system for GA in Iran. The proposed MDS will greatly simplify and standardize data capture in PHC settings, leading to higher data quality and streamlined referral processes. Health management professionals and policymakers will have access to this data set, which they can use to make informed decisions. The GA-MDS has been developed through a modified Delphi survey, specifically for geriatric medicine research. In the future, this MDS will enable the exchange and assembly of data across various organizations for individual patient data meta-analyses and secondary research analyses.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Supplementary Material 2

Supplementary Material 3

Acknowledgements

We thank the research deputy of the Abadan University of Medical Sciences for financially supporting this project. Also, we would like to thank all Experts who freely participated in this study.

Author contributions

HKA, MSH: Conceptualization; Data curation; Formal analysis; Investigation; Software; Roles/Writing - original draft. HKA, RM: Funding acquisition; Methodology; Project administration; Resources; Supervision; Writing – review & editing. HKA, MSH, MRA: Methodology; Validation; Writing – review & editing.

Funding

There was no funding for this research project.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The Research & Ethics Committee of the Abadan University of Medical Sciences approved the design and procedure of the study (ethic code: IR.ABADANUMS.REC.1401.120), and the implementation of all methods in this study complied with the Declaration of Helsinki. Written informed consents were required for all participants in this study in accordance with the institutional requirements. Participants were fully aware of the study’s objectives and were informed that their participation was voluntary, with the freedom to withdraw at any time. Participation in the study posed no risks to them, and they were assured that non-participation would not affect the services they received at the center.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Abbreviations

MDS Minimum data set

GA Geriatric assessment

CVI Content validly index

PHC Primary health care

SID Society for information display

CVR Content validity ratio

S-CVI Scale-level content validity indices

S-CVI/UA Universal agreement among experts

PHC Primary Health Centers

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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