Clinical data systems, part 1: data and medical records

Clinical practice Clinical data systems, part 1: data and medical records

What is information for? The amount of it is said to be doubling every 5 years, and more has been generated in the past 30 years than in the previous 5000;1 yet the producers and the consumers seldom stop to ask this question. Information has been defined as "that which helps decision-making". When we have to decide about a patient’s management (figure 1), the relevant information

consists of clinical data (presenting symptoms, signs, laboratory results) and clinical knowledge (general facts about diseases, how to interpret lab results, how to choose therapies, and so on). Thus, clinical data vary from patient to patient while clinical knowledge applies to many patients. Some doctors carry all their clinical knowledge in their heads; most rely on "knowledge media" such as journals, books and bibliographic systems,3 or even computers4 to lighten the load. However, when it comes to information about individual patients, medical records are essential. This series of three papers arose out of concern that expensive computing systems are being developed and installed in health-care informed clinical institutions without sufficient involvement. My goal is to instruct hospital and officebased clinicians about the medical and technical issues underlying paper and computer based medical records, while avoiding gratuitious detail and unsubstantiated claims. In this paper I discuss the sort of data that goes into patient records, criteria for judging quality, and some possible alternatives to conventional systems.

criticised:

subjective has become a pejorative term, that what patients tell us is "all in the mind", implying while the data that we clinicians capture is often biased and anything but objective. Donnelly et aF propose that instead we use the term "history" for a narrative account of events composed by patient and physician together, and substitute "observations" for the old headings "subjective" and "objective", leaving us with the acronym HOAP. Another proposal is the inclusion of an explicit heading for "risk factors" in Weed’s subjective section, to counter our excessive emphasis on disease and to emphasise instead preventive activities. Whatever the method of subdivision, all data originating directly from the patient, from laboratory results, or from records can be grouped as "patient findings" (figure 1).

Clinical data and sources As shown in figure 1, data on the patient may originate directly from the patient, from diagnostic services, from medical records, or from the clinician. The most obvious category is the identifier, such as name, date of birth, address, and identity numbers. Some clinical departments use their own identity numbers, so during a hospital stay one patient can accumulate ten or more of them; establishing that data under two identifiers apply to the same patient can be surprisingly difficult.5 What of specifically clinical data? Weedidentified four major kinds: subjective, objective, assessment, and plan (SOAP). Subjective data include a patient’s symptoms, clinical history, drug history, allergies, and so on, while objective data include clinical signs whether observed directly, reported by witnesses, or recorded with the notes and also test results. However, these categories have been

Categories

Biomedical Informatics Unit, Imperial Cancer Research Fund, PO Box 123, Lincoln’s Inn Fields, London WC2A 3PX, UK

(J Wyatt DM)

Figure

1: Medical

decision-making and categories of clinical

data

Weed’s "assessments" include abstractions such as diagnoses, staging of a chronic disease, problem lists, and causal explanations of findings or events; while his "plans" include diseases that must be ruled out and actions to be taken. Both assessments and plans originate solely from clinicians and may usefully be grouped to form another new category, "hypotheses". Finally, to inform future decision-making, another category of data needs to be recorded-the actions performed by clinicians, such as the therapies or advice given. Thus,

retaining Weed’s nomenclature as much as possible, we have four main categories of clinical data: * Identifiers s Patient findings, including history and observations (subjective and objective data) * Hypotheses, including assessments and plans * Actions 1543

Table 1:

Categories of clinical

data

In addition most clinical notes include "modifiers" to indicate who recorded an item, when, its severity, and how certain they were of their statement. Some may doubt the wisdom of including subjective estimates of certainty alongside objective clinical data; however, in clinical medicine such expressions are used with remarkable consistency.99 Also, since modifiers may completely alter the interpretation of data (eg, "asthma excluded"), they earn their place as the fifth category of clinical data (table 1).

The form of the record "Our first moments with a patient are packed with visual, auditory and tactile information that determines both the effectiveness and costs of our subsequent care".’ Nonetheless, the content of most records is text, which is easily stored and transported, rather than the source data such as magnetic resonance images or histology slides, which are stored in the originating department with an identifier in the medical record. Here the medical record is summarising the existing data, and summaries imply loss of information, future departmental record systems may store data in greater amounts and in many different forms-true "multimedia" records. Table 2 lists the forms taken by raw clinical data, and how they are typically summarised in records.

Quality and significance of data items In this computer age we are told that "Never before has the cost of collecting, storing and distributing information been so low".’ However, it makes little sense to collect, store, and distribute data without ensuring its quality. 10 The quality of clinical data can be measured along three dimensions. Validity Does the data item measure what is intended (how does it compare with the "gold standard", if any)? Useful measures of validity include the sensitivity and specificity of the data item, and likelihood ratios." Precision How much agreement or repeatability is there between different observers collecting the same data item

1544

Figure

2: Sources of

error

in

recording clinical data

at the same time, or the same observer collecting the same item on two occasions?" The kappa statistic is a useful measure, since it corrects for the agreements expected by chance. 12 Cost How much patient discomfort, risk, delay, financial cost, or other disadvantage is associated with collecting the data item? For many clinical findings the validity and precision have never been properly assessed.’3 This is not for want of good methods for assessing reliability, validity, and clinical significance. 14,15 Figure 2 shows some points at which errors can be introduced into records of clinical data. There are many recorded instances of apparent misinformation by patients. For example, one-third of mothers of girls with vaginal clear-cell carcinoma failed to recall taking the diethylstilboestrol documented in their obstetric records;’6 patients with acute myocardial infarction failed to recall a family history of myocardial infarction in 30% of affected first-degree relatives;17 and parents claimed a history of prematurity in 10% of normal births, denied it when it was present in 20%, and denied an episode of otitis media in their child during the previous summer in 24% of documented cases.18 Such mismatches may reflect poor rapport or bad history-taking, denial, or simple memory lapse,19 but they should warn us against undue reliance on symptoms, whether recorded on paper or on computer. When regular recording of symptoms or drug intake is necessary, a patient-completed diary card is useful. This can be upgraded by a portable computer which prompts the patient to enter data,20 or even a telephone voice-mail system in which a patient records symptoms by tapping keys on the phone. The quality of clinical signs demands similar caution. For example, eye opening, verbal responses, and motor responses in head-injured patients seemed to be easily and reliably elicited and were incorporated into the Glasgow Coma Scale.2’ However, we now know that these signs can be misinterpreted, with poor agreement between experts and less experienced observers, particularly in patients whose scores fall in the middle of the scale-the very group in which they are used for critical decisions such as need for neurosurgery.22 In hypertension, accurate, repeatable measurement of blood pressure may be "much too serious to be left to physicians".23 Not all the misrecordings are accidental. Burnum24 suggested that US physicians are now deliberately misrecording patient data to avoid litigation, and this alarming notion is supported by a study of anaesthetists

striking reluctance to record extreme blood of the four systolic readings above 205 pressures: mm Hg or of thirty-three diastolic readings above 110 mm Hg appeared in the notes, even though they were documented by a carefully calibrated machine.25 The authors suggest that "the paucity of extreme values in the who showed

none

handwritten record may be

an

unconscious defensive

strategy". The heading

of this section refers to "significance". know what is significant? A data item can earn this label if it is unusual, unexplained, or relevant to decision-making, perhaps because of an association with a serious treatable but undiagnosed disease. Measures of significance include the "weight of evidence" (technically the logarithm of the likelihood ratio 14), the "information content", measured by the expected decrease in uncertainty,26 and the "import". 27 Many routine items of clinical data, including subdiagnoses with identical prognostic and therapeutic implications, or even TNM staging in breast cancer,28 are not significant by this definition since they do not influence decisions. As a profession, we should apply the principles of the "rational clinical examination" to the collection and recording of clinical data.1O How do

we

Medical records Functions The main purpose of medical records is to store clinical data and facilitate their retrieval, so that clinicians can quickly answer questions such as: When did problem P start, how did it develop over time? Has there been an abnormality of Q (eg, red cell

volume)? * Was the disease R (eg, SLE) ever excluded, and how? < What did S (eg, Dr Smith) decide about the

diagnosis? Did the patient respond to T (eg, phenothiazines)? Such questions accounted for 53% of requests for information that arose (average 5 per patient) during clinical teaching.29 Thus, a medical record must be a structured, accurate, complete record of what has been observed, thought, and done.3° It will quite possibly contain contradictory data (eg, "diagnosis: diabetes" and "diabetes excluded"), reflecting differing beliefs of different observers or at different times, or statements about a clinician’s intentions (eg, "exclude cancer") which correlate poorly with the patient’s state. 30 The record may also act as a "scratch pad", containing requests to other team members to perform services and their responses to these requests. While we have concentrated on the uses of clinical data and medical records in patient management, we should not forget that they also support ancillary functions, including clinical research and epidemiology, education and clinical audit, and health services management. They also provide a signed, attributable, permanent record in case of litigation. 31 *

detail

appropriate to the decision for which they are collected, retaining fidelity to the original (eg, the patient’s choice of words for symptoms or the clinician’s verbal expression of uncertainty) with each item of data occurring once only, and linkage between items and any index. Each data item should be the coding for data temporarily missing unambiguous; should be different from that of "data unknown" and "finding absent". The system should have sufficient capacity for all clinical applications. Data should be easily entered whenever and wherever the need arises. This implies that the record should be compact and portable, usable without training and capable of recording data fast (at the same time as eliciting data); all data items should be entered once only, and any data that can be captured from other sources (such as the patient, another record system, or a laboratory computer) should be directly transferred. The plausibility of the data item (range limits) and its consistency with other data items should be checked during data entry, since later correction may be impossible. Only authorised persons should be able to record data, and all entries and alterations should be attributable and time-stamped. Data can be added incrementally without need for reorganisation or re-entry. A search for the required items of data should be summary

or

accurate, fast, and simple. The system should allow for many possible search strategies, at any time after the data were entered, by authorised people involved in patient care or by other computer systems used. These criteria mean that data must be stored in a standard wellorganised and unambiguous form, with no redundancy. For computerised data, this requires use of terms from a

controlled

vocabulary. 32 Finally, the size of the system, and the necessary training and infrastructure, should be such that costs of storage and handling are as low as possible. Few of these criteria have been evaluated for conventional records, but paper systems often fail in their fundamental role of answering questions that arise during routine patient management. Answers can usually be obtained, but only by a search through progress notes, correspondence, and sheaves of lab reports. Fries showed that, with the traditional layout, 1 in 10 items could not be found at al. 33 Other disadvantages of paper-based systems include: Missing records They may be needed simultaneously in several places; Duplication For example, missing records may necessitate the creation of temporary records; Bulk I recall a Crohn’s patient with four volumes of

records, totalling 30 cm thick; Incompleteness Failure to include all the data for managing a patient; Cost A

typical hospital stores half a million records, occupying 5 km of shelf space, and employs 100 staff in the records department36; Confidentiality It is easy to borrow notes and photocopy relevant sections, returning them with no sign they have been tampered with. These drawbacks of the paper record

Ideal record

The failings of conventional paper medical records are best appreciated by considering criteria for an ideal repository of patient data. An ideal record should allow accurate, complete storage of all categories and forms of clinical data (sounds, images, and so on), at a level of

necessary

can

lead

to

duplicate investigation,37 administration of treatments that have already failed, and delays in identifying and resolving clinical problems. Unfortunately, matters will get worse as greater teamwork leads more professionals to share records, as patients become more mobile, as the prevalence of 1545

disease increases because of the ageing population, and as more data are generated per encouter. If we continue with paper-based notes, we may end up "drowning in data" while lacking the ability to answer simple clinical questions, because each patient has several parallel, disorganised records in which results and correspondence are never filed because the records are constantly in transit. Paper medical records are also inadequate for many of their ancillary roles, often failing to record why actions were taken, so making audit difficult,34 and providing poor-quality data to test scientific hypotheses.35 No wonder an influential committee of the US Institute of Medicine considered computer-based medical records "an essential technology for health care".36 chronic

Innovative

There

approaches

to conventional records

four ways to improve paper medical records: their contents, change their format, store them change differently, and change their form. Content In the 1960s Weed proposed organising the are

according

presenting problems, distinguishing clearly between subjective and objective data, and maintaining a complete historical summary of both active and inactive problems.6 The principles of problemoriented medical records (POMR) have been widely adopted by medical educators and institutions, though rigorous evidence of clinical benefit has proved elusive. When two complete case histories were examined in both POMR and conventional formats, the answers yielded by POMR were no more accurate or speedy.38 Another study content

to

looked at clinical management in three centres before and after introduction of POMR: there were improvements in quality scores for the management of two out of three surgical conditions, but for four medical conditions the quality of management was unchanged.39 Although the POMR format makes sense and is backed by many authorities, its benefits have not been proved by randomised studies-a familiar frustration for advocates of evidence-based medicine. Even if the approach does improve access to clinical data, it fails to address many of the other issues listed above. Format To improve the format of records, many clinical units now use disease or problem focused proformas or questionnaires to act as "checklists", and thus achieve more complete, standardised, and legible records. These structured data-collection forms not only allow speedy data retrieval;33they have also improved the diagnostic accuracy of junior doctors (by 10%)40 and in antenatal care they generated 8% more actions in response to patient risk factors.4’ Devising a data collection form that is acceptable to all staff can be tedious, and those who agree in principle may not use them in practice since forms may slow down clinics and are associated by some with loss of professionalism. Nevertheless, they do

improve patient care. Place of storage One way to improve availability of records and assist communication between primary and secondary care is to consign them to the patient. Patientheld records have been introduced in several settings including obstetric practice, where they improved patients’ satisfaction and had no adverse effects.42 In a psychiatric setting, however, the record was brought by the patient to only 29 of 67 encounters.43 Form of records Concern about the bulk of records has led to widespread introduction of microfiche filming of 1546

old notes, which are then destroyed. One 13 by 8 cm microfiche holds black-and-white images of 80 A4 pages-a 400-fold reduction in volume-and readers are cheap enough to be sited in clinics and on wards. Microfilming may destroy data that was printed in colour or written faintly, and makes data retrieval more difficult. Moving up in cost, the insurance industry has introduced "document archival systems"-computer scanning of documents to yield images that are held on optical disks in a "jukebox". This does allow shared simultaneous access to document images from remote computer displays in a few seconds, and is being marketed to hospitals as a solution to storage problems, but it requires substantial investment in fast electronic networks to transmit high-resolution images. Also, despite the claims, the result is not an electronic patient record: only a picture of the page is stored. Manual searches through the images are still necessary, since the computer cannot detect that some parts correspond to diagnoses and some to concentrations of serum sodium; so they are no answer to the search problems described above.

Conclusion The

promising technology for medical records is a computerised clinical data system or electronic patient record, in which data are held in a form that allows automatic searching and summarising of specific items. These systems offer the potential to overcome many of the disadvantages of conventional medical most

true

records. Clinical and technical aspects of these systems, their strengths and their weaknesses, are the subject of the next two articles.

References 1 Wurman RS. Information anxiety. Pan, 1991, quoted in Dean M. Facts, statistics and the anxiety syndrome. Lancet 1991; 337: 37-38. 2 Shortliffe E, Perrault L, Wiederhold G, Fagan L, eds. Medical informatics. Wokingham: Addison Wesley, 1990. 3 Wyatt J. Use and sources of medical knowledge. Lancet 1991; 338: 1368-73. 4 Wyatt J. Computer-based knowledge systems. Lancet 1991; 338: 1431-36. 5 Sideli RV, Friedman C. Validating patient names in an integrated clinical information system. In: Clayton P, ed. Proceedings of 15th Symposium on Computer Applications in Medical Care, Washington 1991. New York: McGraw Hill, 1991: 588-92. 6 Weed LL. Medical records that guide and teach. N Engl J Med 1968; 278: 593-99, 652-57. 7 Donnelly WJ, Hines E, Brauner DJ. Why SOAP is bad for the medical record. Arch Intern Med 1992; 152: 481-84. 8 Sheargren JN, Zweifler AJ, Woolliscroft JO. The present medical database needs reorganisation. Arch Intern Med 1990; 150: 2014-15. 9 Clark DA. Verbal uncertainty expressions: a critical review of two decades of research. Curr Psychol Res Rev 1990; 9: 203-35. 10 Sackett DL, Rennie D. The science of the art of the clinical examination. JAMA 1992; 267: 2650-52. 11 Sackett DL. A primer on the precision and accuracy of the clinical examination. JAMA 1992; 267: 2638-44. 12 Cohen J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychol Bull 1968; 70: 213-30. 13 Koran LM. The reliability of clinical methods, data and judgements. N Engl J Med 1975; 292: 642-46, 695-701. 14 Spiegelhalter DJ. Statistical methodology for evaluating gastrointestinal symptoms. Clin Gastroenterol 1985; 14: 489-515. 15 Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; i: 307-10. 16 Sharp GB, Cole P, Anderson D, Herbst AL. Clear cell adenocarcinoma of the lower genital tract: correlation of mother’s recall of DES with obstetrical records. Cancer 1990; 66: 2215-20. 17 Kee F, Robo JY, Nicaud V, McCrum E, Evans A, Cambien F. Reliability of reported family history of myocardial infarction. BMJ

1993; 307: 1528-30.

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Daly KA, Lindgren B, Giebink GS. Validity of parental report of a child’s medical history in otitis media research. Am J Epidemiol 1994;

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Antimicrobial

prophylaxis

31 Brahams D, Wyatt J. Decision-aids and the law. Lancet 1989; ii: 632-34. 32 Buckland R. The language of health. BMJ 1993; 306: 287-88. 33 Fries JF. Alternatives in medical record formats. Med Care 1974; 12: 871-81. 34 van der Lei J, Musen M, van der Does E, Man in’t Veld AJ, van Bemmel JH. Comparison of computer-aided and human review of general practitioners’ management of hypertension. Lancet 1991; 338: 1504-08. 35 Byar DP. Why data bases should not replace randomised controlled clinical trials. Biometrics 1980; 36: 337-42. 36 Dick RS, Steen EB, eds. The computer-based patient record: an essential technology for health care. Washington, DC: National Academy Press, 1991. 37 Tufo HM, Speidel JJ. Problems with medical records. Med Care 1971; 9: 509-17 38 Fletcher RH. Auditing problem-oriented records and traditional records. N Engl J Med 1974; 290: 829-33. 39 Fernow LC, Mackie C, McColl I, Rendall M. The effect of problemoriented medical records on clinical management controlled for patient risks. Med Care 1978; 16: 476-87. 40 Adams ID, Chan M, Clifford PC, et al. Computer aided diagnosis of acute abdominal pain: a multicentre study. BMJ 1986; 293: 800-04. 41 Lilford RJ, Kelly M, Baines A, et al. Effect of using protocols on medical care: randomised trial of three methods of taking an antenatal history. BMJ 1992; 305: 1181-84. 42 Hodnett ED. Women carrying their own case-notes during pregnancy. In: Enkin MW, Keirse MJNC, Renfrew MJ, Neilson JP, eds. Pregnancy and childbirth module. Cochrane database of systematic reviews: review no 03776, 27 April 1993. Oxford: Update Software, Spring, 1993. 43 Reuler JB, Balazs JR. Portable medical record for the homeless mentally ill. BMJ 1991; 303: 446.

in neurosurgery and after head

Although infection

after neurosurgery is relatively it is an uncommon, important cause of patient morbidity. trivial or Apparently superficial sepsis at the operative site

of the

to osteomyelitis, meningitis, cerebritis, formation, or even death. It may delay the patient’s discharge from hospital, lead to further surgery, and ultimately increase the overall cost of hospital care.

Clean

may progress

abscess

Antibiotics have been used for many years to prevent postoperative infection, yet support for the efficacy of this strategy is equivocal. The reason for this lack of consensus is that virtually all of the many clinical trials have been flawed in design or execution, the most important and prevalent of these weaknesses being inadequate statistical power. Against this background the working party assessed the benefits of prophylaxis in neurosurgery. Other important factors that affect the incidence of infection, including host resistance, microbial virulence, duration of the surgery, environment

*Members of the working party listed at end of article.

Correspondence to: Dr J de Louvois, Public Health Laboratory Service Headquarters, 61 Colindale Avenue, London NW9 5DF,

UK

injury

operating theatre, and skill and experience surgeon, were not in the working party’s remit.

of the

non-implant procedures

Efficacy of prophylaxis Antibiotics are administered

patients undergoing clean, non-implant neurosurgical procedures with the principal aim of preventing infection at the operative site; if this can be achieved, a reduction in the risks of subsequent septicaemia, meningitis, and other intracranial infections would be expected. In the absence of prophylaxis, the to

incidence of infection after this type of surgery has varied from less than 1% to 18%, with 3-4% being the average.’ Most early studies demonstrated that antibiotics reduced the incidence of postoperative infection; however, all but 3 of these studies were retrospective. All the more recent trials, most of which were prospective, have also shown that in clean neurosurgical procedures prophylaxis is statistically significantly better than either a placebo or no treatment. Although each of these studies involved far fewer patients than the number recommended by Tenney and colleagues2 for the result to be statistically significant, the likelihood of all the trials independently reaching the

widely

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