Pengembangan Instrumen RDQA Untuk Surveilans Epidemiologi DBD Di Dinas Kesehatan Kota Tarakan

In 2016 from 7 Puskesmas in Tarakan City, 4 (four) Puskesmas (58%) sent their reports above the 5th of each month. There is still a mismatch of the number of source data with the results of recapitulation such as the number of DHF cases in Tarakan DHO with the number of DHF cases in the Ministry of Health Republic of Indonesia SKDR as well as the incompatibility of the reporting format by recording surveillance staff. The purpose of this study was to develop a Routine Data Quality Assessment (RDQA) instrument for DHF Epidemiological Surveillance in Tarakan City Health Office. The type of research used is Research and Development. The total subjects of the study were 9 people with details of 7 data management officers in the Puskesmas in the Tarakan DKK working area and 1 person in charge of the DHF Program in Tarakan DKK. The steps in this study, namely: (1) Potential and problems, (2) Data Collection (3) Product Design (4) Design Validation (5) Design Revision (6) Product Trial (7) Product Revision (8) Trial Use. The results of this study are that data quality assessment instruments have been developed according to RDQA and routine data quality assessments by the Ministry of Health with R & D research methods modified with eight indicators namely timeliness, data availability, data completeness, monitoring and evaluation unit capabilities, reporting indicators and guidelines, data collection and reporting format, data management process, linkages with the national reporting system and the use of data for decision making. The results of the assessment of the instruments developed, namely the aspect of content feasibility has an average value of 81%, the feasibility aspect of presentation is 78% and language assessment aspects 81%. Based on the results of the assessment of the three aspects assessed in the development of the RDQA instrument, a good conclusion is reached, but there are general recommendations given both by the Chair of the DHF Program in the DHO and the Epidemiological Surveillance Data Management Officer in DHO and Puskesmas, namely the use of modules and manuals RDQA instrument.

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Institutionalization of a routine data quality assessment (RDQA) procedure for improved data quality of electronic patient medical records in Kenya

Annals of Global Health ◽

10.1016/j.aogh.2016.04.264 ◽

2016 ◽

Vol 82 (3) ◽

pp. 460 ◽

Cited By ~ 1

Author(s):

V. Muthee ◽

N. Liku ◽

N. Puttkammer

Keyword(s):

Data Quality ◽

Quality Assessment ◽

Medical Records ◽

Routine Data ◽

Data Quality Assessment

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Pengembangan Metode Penilaian Mandiri Kualitas Data Rutin Di Dinas Kesehatan Kota Surakarta

Jurnal Manajemen Kesehatan Indonesia ◽

10.14710/jmki.5.1.2017.47-54 ◽

2017 ◽

Vol 5 (1) ◽

pp. 47-54

Author(s):

Puguh Ika Listyorini ◽

Mursid Raharjo ◽

Farid Agushybana

Keyword(s):

Data Quality ◽

Quality Assessment ◽

Method Development ◽

Routine Data ◽

Health Department ◽

Assessment Methods ◽

Quality Of Data ◽

Data Quality Assessment ◽

Independent Assessment

Data are the basis to make a decision and policy. The quality of data is going to produce a better policy. The quality assessment methods nowadays do not include all indicators of data quality. If the indicators or assessment criteria in the quality assessment methods are more complete, the level of assessment methods of the data will be higher. The purpose of this study is to develop the method of independent assessment of routine data quality in Surakarta Health Department which is previously performed using the data quality assessment of PMKDR and HMN methods firstly.The design of this study is research and development (R&D) that has been modified into seven steps, namely formulating potential problems, collecting the data, designing the product, validating the design, fixing the design, testing the product, and fixing the product. The subjects consisted of 19 respondents who are managers of data in Surakarta Health Department. Data analysis method used is content analysis.The assessment results show that, in the pilot phase of the development of data quality assessment methods which have been developed, it is basically successful, or it can be used. The results of the assessment of the quality of the data by the developed method is the quality of data collection which is very adequate, the quality of data accuracy which is poor, the quality of data that consistency exists but is inadequate, the quality of the actuality of the data which is very adequate, the quality of periodicity data that is inadequate, the quality of the representation of the data that is very adequate, and sorting the data which is very adequate.It needs a commitment from Surakarta Health Department to take advantage of the development of these methods to assess the quality of data to support the availability of information, decision-making and planning of health programs. It also calls for the development of this research by conducting all stages of the steps of R&D so that the final result of the method development will be better.

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Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study

JMIR Medical Informatics ◽

10.2196/27842 ◽

2021 ◽

Vol 9 (8) ◽

pp. e27842

Author(s):

Hannelore Aerts ◽

Dipak Kalra ◽

Carlos Sáez ◽

Juan Manuel Ramírez-Anguita ◽

Miguel-Angel Mayer ◽

...

Keyword(s):

Heart Failure ◽

Pilot Study ◽

Data Collection ◽

Health Outcomes ◽

Data Quality ◽

Quality Assessment ◽

Temporal Stability ◽

Health Record ◽

Outcomes Measurement ◽

Data Quality Assessment

Background There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality. Objective In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure. Methods All available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability. Results We found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR. Conclusions Overall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals.

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Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study (Preprint)

10.2196/preprints.27842 ◽

2021 ◽

Author(s):

Hannelore Aerts ◽

Dipak Kalra ◽

Carlos Sáez ◽

Juan Manuel Ramírez-Anguita ◽

Miguel-Angel Mayer ◽

...

Keyword(s):

Heart Failure ◽

Pilot Study ◽

Data Collection ◽

Health Outcomes ◽

Data Quality ◽

Quality Assessment ◽

Temporal Stability ◽

Health Record ◽

Outcomes Measurement ◽

Data Quality Assessment

BACKGROUND There is increasing recognition that health care providers need to focus attention, and be judged against, the impact they have on the health outcomes experienced by patients. The measurement of health outcomes as a routine part of clinical documentation is probably the only scalable way of collecting outcomes evidence, since secondary data collection is expensive and error-prone. However, there is uncertainty about whether routinely collected clinical data within electronic health record (EHR) systems includes the data most relevant to measuring and comparing outcomes and if those items are collected to a good enough data quality to be relied upon for outcomes assessment, since several studies have pointed out significant issues regarding EHR data availability and quality. OBJECTIVE In this paper, we first describe a practical approach to data quality assessment of health outcomes, based on a literature review of existing frameworks for quality assessment of health data and multistakeholder consultation. Adopting this approach, we performed a pilot study on a subset of 21 International Consortium for Health Outcomes Measurement (ICHOM) outcomes data items from patients with congestive heart failure. METHODS All available registries compatible with the diagnosis of heart failure within an EHR data repository of a general hospital (142,345 visits and 12,503 patients) were extracted and mapped to the ICHOM format. We focused our pilot assessment on 5 commonly used data quality dimensions: completeness, correctness, consistency, uniqueness, and temporal stability. RESULTS We found high scores (>95%) for the consistency, completeness, and uniqueness dimensions. Temporal stability analyses showed some changes over time in the reported use of medication to treat heart failure, as well as in the recording of past medical conditions. Finally, the investigation of data correctness suggested several issues concerning the characterization of missing data values. Many of these issues appear to be introduced while mapping the IMASIS-2 relational database contents to the ICHOM format, as the latter requires a level of detail that is not explicitly available in the coded data of an EHR. CONCLUSIONS Overall, results of this pilot study revealed good data quality for the subset of heart failure outcomes collected at the Hospital del Mar. Nevertheless, some important data errors were identified that were caused by fundamentally different data collection practices in routine clinical care versus research, for which the ICHOM standard set was originally developed. To truly examine to what extent hospitals today are able to routinely collect the evidence of their success in achieving good health outcomes, future research would benefit from performing more extensive data quality assessments, including all data items from the ICHOM standards set and across multiple hospitals.

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