Evidence map›Paper›PMID 32401763›Full record

ArticlePloS one2020

Process evaluation of health system costing - Experience from CHSI study in India.

Shankar Prinja, Sehr Brar, Maninder Pal Singh, Kavitha Rajsekhar, Oshima Sachin, Jyotsna Naik, Malkeet Singh, Himanshi Tomar, CHSI Study Collaborating Investigators, Pankaj Bahuguna and 1 more

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Shankar PrinjaDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.ORCID 0000-0001-7719-6986
Sehr BrarDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.ORCID 0000-0003-4979-3200
Maninder Pal SinghDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Kavitha RajsekharDepartment of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Oshima SachinDepartment of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Jyotsna NaikDepartment of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Malkeet SinghDepartment of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
Himanshi TomarDepartment of Health Research, Ministry of Health and Family Welfare, Government of India, New Delhi, India.
CHSI Study Collaborating Investigators
Pankaj BahugunaDepartment of Community Medicine and School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India.
Lorna GuinnessIndependent Researcher, Imperial College London, London, England.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA national study, 'Costing of healthcare services in India' (CHSI) aimed at generating reliable healthcare cost estimates for health technology assessment and price-setting is being undertaken in India. CHSI sampled 52 public and 40 private hospitals in 13 states and used a mixed micro-costing approach. This paper aims to outline the process, challenges and critical lessons of cost data collection to feed methodological and quality improvement of data collection.

methodsAn exploratory survey with 3 components-an online semi-structured questionnaire, group discussion and review of monitoring data, was conducted amongst CHSI data collection teams. There were qualitative and quantitative components. Difficulty in obtaining individual data was rated on a Likert scale.

resultsMean time taken to complete cost data collection in one department/speciality was 7.86(±0.51) months, majority of which was spent on data entry and data issues resolution. Data collection was most difficult for determination of equipment usage (mean difficulty score 6.59±0.52), consumables prices (6.09±0.58), equipment price(6.05±0.72), and furniture price(5.64±0.68). Human resources, drugs & consumables contributed to 78% of total cost and 31% of data collection time. However, furniture, overheads and equipment consumed 51% of time contributing only 9% of total cost. Seeking multiple permissions, absence of electronic records, multiple sources of data were key challenges causing delays.

conclusionsMicro-costing is time and resource intensive. Addressing key issues prior to data collection would ease the process of data collection, improve quality of estimates and aid priority setting. Electronic health records and availability of national cost data base would facilitate conducting costing studies.

Indexed as

Health Care CostsData CollectionGovernment ProgramsHealth ServicesHumansIndiaModels, EconomicSurveys and Questionnaires

Identifiers

PMID32401763
PMCPMC7219765

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.